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Cumulative effects of agricultural intensification on nutrient and trace metal pollution in the Sumas… Smith, Ione Marie 2004

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CUMULATIVE EFFECTS OF AGRICULTURAL INTENSIFICATION ON NUTRIENT AND TRACE METAL POLLUTION IN THE SUMAS RIVER WATERSHED, ABBOTSFORD, B.C. by IONE MARIE SMITH B.Sc.(Env), The University of Guelph, 2001 A THESIS SUBMITTED IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE in THE FACULTY OF GRADUATE STUDIES (RESOURCE MANAGEMENT AND ENVIRONMENTAL STUDIES) We accept this thesis as conforming to the required standard THE UNIVERSITY OF BRITISH COLUMBIA October 2004 © lone Marie Smith, zoo^ JUBCl. THE UNIVERSITY OF BRITISH COLUMBIA FACULTY OF GRADUATE STUDIES Library Authorization In presenting this thesis in partial fulfillment of the requirements for an advanced degree at the University of British Columbia, I agree that the Library shall make it freely available for reference and study. I further agree that permission for extensive copying of this thesis for scholarly purposes may be granted by the head of my department or by his or her representatives. It is understood that copying or publication of this thesis for financial gain shall not be allowed without my written permission. X Name of Author (please print) 01 hoj^LooH-Date (dd/mm/yyyy) Title of Thesis: CVrUuJ A J T ' I V ^ E^fecj S ^ A -9 V' C t l l f u X ^ f Xf l ktlSj PiC A - T ~ i D ^ On Nui-rie.nf as\c\ ""Pace. WeX-aA FoVfufioo ;n iUe. Sum as Degree: PLSc. Year: Departmentof fesolAfCJl- \AlX/\ tXt^mef) ^ CLnd tr\V\rZ>r) Y Y ) I £ > 'TMol I fS T h e University of British Columbia Vancouver, B C C a n a d a grad.ubc.ca/forms/?formlD=THS page 1 of 1 last updated: 20-M-04 Abstract The Sumas River transboundary watershed is characterized by an asbestos landslide in a headwater tributary and intensive hog and poultry operations in the flat Sumas Prairie floodplain. The quality of water and sediment in the Sumas River watershed is important from the point of view of fish habitat and recreation. A recent intensification of agricultural activities has renewed concerns about environmental impacts in the region, notably with regard to non-point source pollution. This study used land use indicators such as livestock density, nitrogen application surpluses, and crop cover along with the analysis of water and sediment samples to investigate cumulative effects of agricultural intensification on an aquatic ecosystem. Long-term trends were explored using historical data to track changes over time. Water quality results indicated that nitrate levels have significantly increased during the wet season since 1993 in the Sumas River and in tributaries that are surrounded by intensive agricultural operations. Marshall Creek, which is influenced by the Abbotsford Aquifer, has experienced significant increases in nitrate during the dry season since 1993. Levels of ammonium have risen above provincial water quality guidelines for aquatic health in the Sumas Canal. Tributaries throughout the watershed were often eutrophic during summer months, with algal blooms observed at several sites. Trace metals associated with agricultural operations (Cu, Fe, Mn, and Zn) and the asbestos landslide (Ni, Cr, Co, Mg) were investigated by measuring the dissolved, bioavailable (using the diffusive gradient thin film technique (DGT)), and sediment-bound metal fractions. DGT results indicated that bioavailable Zn levels were consistently highest in Marshall Creek. Spatially, sediment concentrations of Cu, Fe, and Zn increased in the downstream direction of the Sumas River. Temporally, several ii sediment bound elements (Cu, K, P, and Zn) have significantly increased in tributaries associated with intensive agricultural operations since 1993. Livestock density was significantly correlated to higher levels of nutrients and trace metals in water and sediment. Nitrate was also significantly correlated to nitrogen surplus applications, the percent clay content within sediment, and the amount of corn and pasture crops cultivated adjacent to the sampling sites. The results indicate that more effective manure management practices are needed in order to stabilize water and sediment quality within the watershed. Substantial improvements in manure storage infrastructure, increases in manure exports, or a limit on livestock density may be required to remediate water and sediment quality. The current environmental state of the Sumas River watershed warrants renewed attention from private landowners and all levels of government. iii Table of Contents Abstract ii Table of Contents iv List of Tables viii List of Figures xi List of Abbreviations and Symbols xiii Acknowledgements xiv Chapter 1 Introduction 1 1.1 Biophysical Characteristics of the Sumas River Watershed 1 1.2 Fisheries Resources in the Sumas River Watershed 4 1.3 Agricultural Intensification as an Indicator of Environmental Quality 5 1.4 Agricultural Non-Point Source Pollution 6 1.4.1 Nutrient Pollution 7 1.4.2 Trace Element Pollution 10 1.4.3 Trace Element Bioavailability 14 1.5 The Use of the Diffusive Gradient Thin Film Technique (DGTs) in Water Quality Investigations 16 1.6 Cumulative Effects 18 Chapter 2 Research Scope and Objectives 20 2.1 Overall Scope 20 2.2 Objectives 20 iv Chapter 3 Methods 21 3.1 Land Use Indices and Climate Data 21 3.1.1 Meteorological and Hydrometric Data 21 3.1.2 Geographic Information Systems (GIS) Data 21 3.1.3 Agricultural Census Data and Animal Unit Equivalents (AUEs) 22 3.1.4 Nutrient Budgets 22 3.2 Sampling Site Selection 23 3.3 Field Sampling and Laboratory Analysis 25 3.3.1 Water Sampling and Laboratory Analysis 25 3.3.2 DGT Sampling and Laboratory Analysis 26 3.3.3 Sediment Sampling and Laboratory Analysis 28 3.4 Data Analysis Methods 30 3.4.1 Quality Analysis and Quality Control 30 3.4.2 Water Data: Statistical Analysis 30 3.4.3 DGT Data: Statistical Analysis 33 3.4.4 Sediment Data: Statistical Analysis 34 3.4.5 Relationships between Land Use, Sediment, and Water Quality 35 Chapter 4 Results 37 4.1 Land and Climate Results 37 4.1.1 Precipitation and Flow Data 37 4.1.2 Land Use in the Sumas River Watershed 39 4.1.3 Population Changes in Abbotsford, B.C 40 4.1.4 Crop Cover in the Canadian Portion of the Sumas River Watershed 42 v 4.1.5 Changes in Livestock Production in the Abbotsford, B.C., Region 46 4.1.6 Animal Unit Equivalent (AUE) Densities 49 4.1.7 Nutrient Budgets by Enumeration Area in the Sumas Prairie 51 4.2 Water Quality Results 51 4.2.1 Spatial and Seasonal Variations in Water Quality 52 4.2.2 Long-Term Trends in Nutrients and Dissolved Oxygen (1994 to 2004)... 70 4.2.3 Dissolved Elements in Water Results 79 4.2.4 Correlations between Water Quality Parameters 85 4.3 DGT Results 87 4.3.1 Laboratory Calibration Results 87 4.3.2 Field Deployment Results 88 4.3.3 Relationships between Bioavailable Trace Metals, pH, Temperature, and Precipitation 94 4.4 Sediment Results 94 4.4.1 Particle Size Distribution 96 4.4.2 Trace Elements in Sediments 96 4.4.3 Relationships between Elements in Sediments 111 4.4.4 Long-Term Trends in Sediment Quality (1993-2004) 111 4.5 Relationships between Dissolved, Bioavailable, and Extractable Elements .112 4.6 Relationships between Land Use Indices and Environmental Quality 115 Chapter 5 Discussion 122 5.1 Nutrient Water Quality Guidelines 122 5.2 Physical Water Quality Guidelines 125 vi 5.3 Trace Element Guidelines for Water and Sediments 130 5.3.1 Trace Elements from the Swift Creek Landslide: Cr, Co, Ni 130 5.3.2 All Other Trace Elements: Al, As, Cu, Fe, Mn, Pb, and Zn 134 5.4 Interactions Between Land Use and Water and Sediment Quality 142 Chapter 6 Summary 144 6.1 Land Use 144 6.2 Nutrients in Water and Sediment 145 6.3 Metals in Water (Dissolved and Bioavailable) and Sediment 146 6.4 Links Between Land Use and Water Quality 148 Chapter 7 Recommendations 150 References 152 Appendices 161 Appendix A: Literature Review Data 161 Appendix B: Land Use and Land Cover Maps of the Sumas River Watershed . 164 Appendix C: Water Sampling Results 171 Appendix D: DGT Sampling Results 212 Appendix E: Sediment Sampling Results 223 Appendix F: Spearman Rank Correlation Coefficients 246 Appendix G: Photographs of Field Stations 265 vii List of Tables Table 1.4.1 2000/2001 Manure shipments from Fraser Valley regions 8 Table 1.4.2 Nutrient and trace elements contents of typical manures 13 Table 1.5.1 Selectivity for Divalent Cations 17 Table 3.2.1 List of water and DGT sampling sites and years they were sampled 23 Table 4.1.1 Land use by area and % of total area for the Canadian portion of the Sumas River watershed: Changes over time 39 Table 4.1.2 Categories of crop cover in the Sumas Prairie (2003) ranked by area 43 Table 4.1.3 Comparison of area under crops: 2003 crop cover map and 2001 EA census data 44 Table 4.1.4 Changes in livestock numbers and farm densities in Abbotsford, B.C. census region. ...47 Table 4.1.5 Changes in livestock numbers and farm densities in the Sumas Prairie sub-region 48 Table 4.1.6 Changes in livestock numbers and farm densities in the Abbotsford Aquifer sub-region.48 Table 4.1.7 Canadian Regions with highest livestock density in 2001 49 Table 4.1.8 Animal unit equivalents per ha by EA in the Sumas Prairie 50 Table 4.1.9 Average animal unit equivalents for the Abbotsford Aquifer (Matsqui South) and Sumas Prairie sub-regions 50 Table 4.1.10 Nutrient surpluses by enumeration area (EA) in the Sumas Prairie 51 Table 4.2.1a Significant Mann-Whitney results (a<0.01) for Cl" by site 52 Table 4.2.1b Significant Mann-Whitney results (a<0.01) for N0 3"-N by site 54 Table 4.2.1c Significant Mann-Whitney results (ct<0.01) for NH 4 +-N by site 56 Table 4.2.1d Significant Mann-Whitney results (ct<0.01) for P 0 4 by site 58 Table 4.2.1e Significant Mann-Whitney results (ct<0.01) for DO by site 60 Table 4.2.1f Significant Mann-Whitney results (a<0.01) for DOC by site 62 Table 4.2.1g Significant Mann-Whitney results (a<0.01) for pH by site 64 Table 4.2.1h Significant Mann-Whitney results (a<0.01) for specific conductivity by site 68 Table 4.2.2 Summary of R 2 values for significant changes in Cl" levels from 1994-2004 70 Table 4.2.3 Summary of R 2 values for significant changes in N0 3"-N levels from 1994-2004 72 Table 4.2.4 Summary of R 2 values for significant changes in NH 4 +-N levels from 1994-2004 76 Table 4.2.5 Summary of R 2 values for significant changes in DO levels from 1994-2004 78 viii Table 4.2.6 Occasions when dissolved Al was above detection limit of 0.05 ppm 79 Table 4.2.7 Descriptive data for dissolved ions in water 80 Table 4.2.8a Significant Mann-Whitney results (a<0.01) for dissolved Ca by site 81 Table 4.2.8b Significant Mann-Whitney results (a<0.01) for dissolved Fe by site 81 Table 4.2.8c Significant Mann-Whitney results (ct<0.01) for dissolved K by site 82 Table 4.2.8d Significant Mann-Whitney results (a<0.01) for dissolved Mg by site 83 Table 4.2.8e Significant Mann-Whitney results (a<0.01) for dissolved Mn by site 83 Table 4.2.8f Significant Mann-Whitney results (a<0.01) for dissolved Na by site 84 Table 4.2.8g Significant Mann-Whitney results (a<0.01) for dissolved Si by site 85 Table 4.2.9 Significant Spearman Rank correlations (<x=0.10) for water parameters (wet season). ..85 Table 4.2.10 Significant Spearman Rank correlations (a=0.10) for water parameters (dry season). ..86 Table 4.3.1 Results from DGT laboratory calibration (1 s t run) 87 Table 4.3.2 Results from DGT laboratory calibration (2 n d run) 87 Table 4.3.3 Significant Spearman Rank correlations (cx=0.10) between DGTs, precipitation, DO, specific conductivity and pH 94 Table 4.4.1 As in sediment results for sites with at least one sample above detection limit 95 Table 4.4.2 Pb in sediment results for sites with at least one sample above detection limit 95 Table 4.4.3 Particle size distribution results for sediments collected in 2003 96 Table 4.4.4 Significant Mann-Whitney test results (a<0.01) for Cr, Co, Mg, and Ni 98 Table 4.4.5 Significant Mann-Whitney test results (a<0.01) for Al, Ca, Cu, K, Na, P and Zn 100 Table 4.4.5 Significant Spearman Rank correlations (cx=0.10) between elements in sediments 111 Table 4.4.6 Significant Wilcoxon Signed Rank test results (a=0.10) for elements in sediment 112 Table 4.5.1 Significant Spearman Rank correlations (a=0.10) between dissolved, bioavailable, and extractable elements measured in 2003 and 2004 112 Table 4.5.2 Significant Spearman Rank correlations (a=0.10) between dissolved and extractable elements 115 Table 4.6.1 Characteristics of land cover within buffer areas 116 Table 4.6.2 Land use indices within buffer areas 118 Table 4.6.3 Significant Spearman Rank correlations (a = 0.10) between land use indices and nutrient levels in water 119 ix Table 4.6.4 Significant Spearman Rank correlations (a=0.10) between land use indices and physical water quality parameters 120 Table 4.6.5 Significant Spearman Rank correlations (oc=0.10) between land use indices and dissolved elements in water 120 Table 4.6.6 Significant Spearman Rank correlations (cc=0.10) between land use indices and sediment quality 121 Table 5.1.1 Background levels and water quality guidelines for nutrients 122 Table 5.1.2 Exceedences of NH 4 +-N water quality criteria in the Sumas River watershed 124 Table 5.2.1 Background levels and water quality guidelines for physical water quality parameters. 125 Table 5.2.2 Tributaries with the greatest range of DOC levels in the Sumas River watershed 127 Table 5.2.3 Tributaries with exceedences of pH above or below the water quality criteria 128 Table 5.3.1 Water and sediment criteria and background levels for Cr, Co, and Ni 130 Table 5.3.2 Water and sediment criteria and background levels for Al, As, Cu, Fe, Pb, Mn, Zn 134 x List of Figures Figure 1.1.1 Aerial ortho-photograph of Sumas Prairie 3 Figure 1.3.1 Hierarchy of indicators to assess the impact of nutrient loss from agriculture on environmental quality and human health 6 Figure 1.4.1 Interactions between abiotic and biotic systems in the aquatic environment 14 Figure 1.5.1 Schematic of a DGT unit: Side view and top view 16 Figure 3.2.1 Aerial ortho-photograph with outline of Sumas River watershed boundary and sampling sites 24 Figure 4.1.1 Monthly precipitation in Abbotsford, flow data for the Sumas River, and sampling date indicators 37 Figure 4.1.2 Average monthly precipitation at Abbotsford airport and average flow of the Sumas River at the international border 38 Figure 4.1.3. Summary of land use changes for the Sumas River watershed between 1988 and 2002 based on GIS maps created in ArcView 40 Figure 4.1.4 Housing development in Abbotsford B.C. by category 41 Figure 4.1.5 Top ten categories of crop cover as a percent of total area in the Sumas Prairie for the 2003 growing season 42 Figure 4.1.6 Trends of major crop production in Abbotsford, B.C. census region based on Agricultural Census data 45 Figure 4.1.7 Trends of minor crop production in Abbotsford, B.C. census region based on Agricultural Census data 45 Figure 4.1.8 Livestock in the Abbotsford Region, 2001 (StatsCan, 2001) 46 Figure 4.2.1a Cl (mg/L): Wet and dry season trends in the Sumas River watershed 53 Figure 4.2.1b N0 3"-N (mg/L): Wet and dry season trends in the Sumas River watershed 55 Figure 4.2.1c NH / -N (mg/L): Wet and dry season trends in the Sumas River watershed 57 Figure 4.2.1d P04 (mg/L): Wet and dry season trends in the Sumas River watershed 59 Figure 4.2.1e DO (mg/L): Wet and dry season trends in the Sumas River watershed 61 Figure 4.2.1f DOC (mg/L): Wet and dry season trends in the Sumas River watershed 63 Figure 4.2.1g pH: Wet and dry season trends in the Sumas River watershed 65 Figure 4.2.1h Temperature (°C) Wet and dry season trends in the Sumas River watershed 67 Figure 4.2.1i Specific conductivity: Wet and dry season trends in the Sumas River watershed 69 Figure 4.2.2 Dry and wet season differences in Cl" between 1993 and 2004 71 Figure 4.2.3 Dry and wet season differences in N0 3"-N between 1993 and 2004 73 xi Figure 4.2.4 Wet season differences in N0 3"-N between 1993 and 2004 in Sumas River sites 74 Figure 4.2.5. Historical wet season N0 3 ' -N (mg/L) trends in the Sumas River mainstem 75 Figure 4.2.6 Dry season NH 4 +-N changes in the Sumas River watershed 76 Figure 4.2.7 Wet season NH 4 +-N changes in the Sumas River watershed 77 Figure 4.2.8 Temporal DO trends in the Sumas River watershed 78 Figure 4.3.1 DGT results for bioavailable Al by site 89 Figure 4.3.2 DGT results for bioavailable Fe by site 90 Figure 4.3.3 DGT results for bioavailable Mn by site 91 Figure 4.3.4 DGT results for bioavailable Ni by site 92 Figure 4.3.5 DGT results for bioavailable Zn by site 93 Figure 4.4.1 Ni and Mg in sediment: Differences from 1994 to 2004 along the Sumas River 98 Figure 4.4.2 Co and Cr in sediment: Differences from 1994 to 2004 along the Sumas River 99 Figure 4.4.3a Spatial and temporal trends in Al from sediments of the Sumas River watershed 101 Figure 4.4.3b Spatial and temporal trends in Ca from sediments of the Sumas River watershed 102 Figure 4.4.3c Spatial and temporal trends in Cu from sediments of the Sumas River watershed 103 Figure 4.4.3d Spatial and temporal trends in Fe from sediments of the Sumas River watershed 104 Figure 4.4.3e Spatial and temporal trends in K from sediments of the Sumas River watershed 105 Figure 4.4.3f Spatial and temporal trends in Mn from sediments of the Sumas River watershed 106 Figure 4.4.3g Spatial and temporal trends in Na from sediments of the Sumas River watershed 107 Figure 4.4.3h Spatial and temporal trends in P from sediments of the Sumas River watershed 108 Figure 4.4.3i Spatial and temporal trends in Si from sediments of the Sumas River watershed 109 Figure 4.4.3j Spatial and temporal trends in Zn from sediments of the Sumas River watershed 110 Figure 4.5.1 Relationships between bioavailable (DGT) and extractable (sediment-bound) Zn 113 Figure 4.5.2 Relationships between bioavailable (DGT) and extractable (sediment-bound) Fe 114 Figure 4.5.3 Relationships between bioavailable (DGT) and extractable (sediment-bound) Ni 114 Figure 4.5.4 Relationships between bioavailable (DGT) and extractable (sediment-bound) Mn 115 Figure 5.1.1 Relationships between livestock intensity and water and sediment quality indicators... 143 Figure 5.1.2 Relationships between nitrate, wet season water quality parameters, and land use indicators 143 xii List of Abbreviations and Symbols AUE Animal Unit Equivalent Al Aluminum ALR Agricultural Land Reserve As Arsenic Ca Calcium Co Cobalt Cr Chromium Cu Copper DGT Diffusive Gradient Thin Film Technique DO Dissolved Oxygen DOC Dissolved Organic Carbon EA Enumeration Area EC Environment Canada Fe Iron GIS Geographic Information System ha Hectare ICP-AES Inductively Coupled Plasma-Atomic Emission K Potassium Mg Magnesium Mn Manganese N Nitrogen Na Sodium Ni Nickel NPS pollution Non-point source pollution P Phosphorus Pb Lead Si Silicon Zn Zinc xiii Acknowledgements I am grateful to the following agencies for providing research funding: the Natural Sciences and Engineering Research Council of Canada (NSERC), the Canadian Water Network National Centre of Excellence, and Environment Canada. The following individuals assisted by providing information and expertise: George Derksen and Lynne Campo, Environment Canada; Eric Hoogenraad, City of Abbotsford; Andrew Phay, Whatcom Conservation; Bernard Houle, Statistics Canada; Sandy Traichel, Abbotsford Soil Conservation Association; and Kevin Chipperfield, Sustainable Poultry Farmers Group. My supervisor Hans Schreier supported me immeasurably with his encouragement, inspiration, and humour. I'm also grateful to my other committee members, Ken Hall and Les Lavkulich, for guiding me both in the field and in the classroom. A large number of people helped me out in the field, in the lab, and around the office. They include: Sandra Brown, Gina Bestbier, Julia Brydon, Jenn MacDonald, Jamie Ross, Patricia Keen, Simone Magwood, Lea Elliott, Kevin Li, Michelle Revesz, Kim Barber, Gaby Solano, Sharon Bennett, Stephanie Grand, Carol Dyck, Keren Ferguson, Paula Parkinson, and Sara Harrison. I'm grateful to my family and friends for always providing me with such great encouragement in all my endeavours. Special thanks to Huxley for prying me away from my work for long walks and to Luke for daily love and support and for always helping me keep perspective. xiv Chapter 1 Introduction 1.1 Biophysical Characteristics of the Sumas River Watershed The Sumas River watershed is 277 km2 in size and is located between the municipalities of Abbotsford and Chilliwack in the Lower Fraser Valley of B.C. The river originates in the Cascade Mountain range of the northwestern region of Washington State, U.S.A, and flows northward into Canada as a tributary of the Fraser River. The headwaters of the Sumas River watershed encompass the towns of Sumas, Nooksack, and Everson in Whatcom County, Washington State. The Sumas Canal, Arnold Slough, Marshall Creek, and Saar Creek are all tributaries of the Sumas River located in the Canadian portion of the watershed. One of the main landforms characterizing the Sumas River watershed is a flat floodplain of fertile soil located adjacent to the Fraser River called the Sumas Prairie, which is approximately 10,000 ha in size. The Sumas Prairie is flanked by Sumas Mountain to the northwest and Vedder Mountain to the southeast (Figure 1.1.). The Sumas River watershed once consisted of large wetlands and Sumas Lake, an 8,000 ha waterbody. In 1924, Sumas Lake and a majority of the wetlands were drained during the construction of the 9 km long Sumas Canal in an effort to control flooding and create more agricultural land by increasing the size of Sumas Prairie (Stevens and Eriksson, 1997). As a result, the average elevation of Sumas Prairie is less than 6 m above sea level and pump stations are used to control the level of the Sumas River for irrigation purposes (EC, 1998). Drainage pipes and dykes are used to control the flow of the Sumas River, Saar Creek, and Arnold Slough (EC, 1998). The water level of the Sumas River is controlled mainly by the Barrowtown pump station, which prevents flooding and ensures water availability for irrigation purposes. The floodgates of the pump station are closed from mid-May to mid-September every year 1 and occasionally during the winter months if the Fraser River rises by more than 4.5 m and risks flooding the Sumas River (IRC, 1994). The surficial materials of the Sumas River watershed are comprised of post-glacial lacustrine deposits in the Sumas Prairie region and eolian deposits over glacial till on Sumas and Vedder Mountains, while the Abbotsford Aquifer region is comprised mainly of glaciofluvial sand and gravel deposits (Luttmerding, 1980). The soils of Sumas Prairie are comprised mainly of sands and loams (Luttmerding, 1980). A natural landslide in Swift Creek, a headwater tributary of the Sumas River, introduces large amounts of serpentinitic material, namely asbestos fibres into the river, which contain high levels of metals such as nickel (Ni), chromium (Cr), cobalt (Co), and magnesium (Mg) (Schreier and Taylor, 1981). The climate of the Sumas River watershed is characterized by warm dry summers and cool wet winters. Some of the precipitation falls as snow during the winter in the higher elevations of the Sumas and Vedder mountains. Mean annual precipitation has been known to exceed 2000 mm with averages of 1500 mm per year (EC, 2004). Peak river flows occur between November and February and minimum flows occur from July to September (EC, 1998). One tributary of the Sumas River, Marshall Creek, is fed by the Abbotsford groundwater aquifer year-round; therefore the quality of water and the physical characteristics of the tributary (temperature, pH, etc) are heavily influenced by the aquifer. 2 Figure 1.1.1 Aerial ortho-photograph of Sumas Prairie. Sumas Mountain is to the northwest and Vedder Mountain to the southeast. The municipality of Abbotsford, B.C. is located to the southwest. Agricultural operations occur mainly in the Sumas Prairie and are characterized by a recent intensification in activity. Land use other than agriculture includes some suburban development on the slopes of Sumas and Vedder mountains and commercial activity along some of the major roads such as Sumas Way and the TransCanada Highway. Land use in the relatively flat U.S. portion of the watershed is primarily agriculture, and is characterized by large dairy operations. Small urban areas associated with the towns of Nooksack, Everson, and Sumas also exist on the Washington State side of the watershed. Moreover, a wastewater treatment plant in the Town of Sumas ensures that the effluent reaching the Sumas River is not contributing to the pollution of the waterway (Stevens et al., 2001). Land use and land cover is discussed in more detail in the Results section. 3 1.2 Fisheries Resources in the Sumas River Watershed Historically, the salmon in the Sumas River watershed have been a major source of food and spiritual connection for the local Sto:lo First Nations. The species of fish present in the Sumas River watershed include coho, chum, and pink salmon, rainbow, steelhead and cutthroat trout, sturgeon, black crappy, brown bullhead, dace, carp, lamprey, whitefish, sculpin, and stickleback (DFO, 2002). However, due to water quality concerns, recreational activities in the Sumas River, including fishing, are discouraged. The main concern in the watershed with regards to fisheries is to keep the salmon-spawning habitat optimal. The quality of fish habitat in the Sumas River is ideal in the U.S. headwaters, but degrades in the downstream direction (DFO, 2002). Berka (Berka, 1996) found that during the summer, dissolved oxygen levels decrease and temperatures increase to levels that are unsuitable for many fish in the Saar Creek and Arnold Slough tributaries. This seasonal variation in water quality has serious consequences on migration and spawning activities for the salmonid species. The Department of Fisheries and Oceans (2002) reports that riparian vegetation is vital for providing shelter for salmonids but that it is routinely removed as part of dyke maintenance in the Sumas River and its tributaries. The Barrowtown pump station presents a physical obstruction to fish trying to move between the Sumas River and the Fraser River, although efforts are being made to create better entry for fish. Fish populations have also suffered from the input of sediment, nutrients, and pesticides from agricultural activities. Fish kills due to agricultural runoff have been reported in the tributaries of the Sumas Canal (DFO, 2002). 4 1.3 Agricultural Intensification as an Indicator of Environmental Quality Agricultural intensification occurs when the production rate of plants and animals increases while the area of the land base remains stable or decreases. Intensification usually involves producing livestock and poultry in the manner of large business operations. However, Beaulieu (2001) notes that there is no broad Canadian definition of intensive agricultural operations. The classifications that do exist are found mainly in by-laws that are adapted to local climatic conditions and agricultural practices. In general, a farm can be considered intensive if it uses large amounts of energy inputs or if it produces large amounts of plants and animals in relation to the area that it encompasses (Beaulieu, 2001). The long-term trend in Canadian agriculture is a gradual decrease in the number of livestock farms coupled with a steady increase in livestock population (StatsCan, 2002). Areas that are characterized by agricultural intensification may be at risk of soil and water (surface and groundwater) contamination due to a lack of sufficient land available for animal waste application. Regional nutrient budgets, soil characteristics, and the use of historical agricultural census trends can be used in order to determine whether or not agricultural practices have reached limits that could result in the degradation of water quality for a specific watershed. Schroder et al. (2004) have proposed a hierarchy of agricultural indicators that can be used to assess the risk of a waterbody or ecosystem to agricultural non-point source (NPS) pollution (Figure 1.3.1). The highest indicator level in the hierarchy is the number of livestock. 5 Human Health and Welfare Manure Applied to Soil T Livestock Produced and Manure Excreted Figure 1.3.1 Hierarchy of indicators to assess the impact of nutrient loss from agriculture on environmental quality and human health adapted from Schroder et al. (2004). 1.4 Agricultural Non-Point Source Pollution Contributions of agricultural non-point source (NPS) pollution to waterways include soil particles, pesticides, nutrients, trace metals, hormones, and antibiotic residues (Kpomblekou-A et al., 2002). In order to ensure that agricultural waste does not end up in waterways, crop requirements and the assimilation capacity of the soil must not be exceeded. If manure or fertilizer is spread onto land and the soil is not capable of absorbing, recycling and breaking down the residues that it receives, then pollutants may leach into groundwater aquifers and surface water systems (Schreier et al., 1991). Soil often bears the brunt of fertilizer over-applications, which is indicated by 6 high rates of erosion, chemical contamination, a loss of organic matter, and soil structure changes (Lavkulich et al., 1999). Agricultural NPS pollution is the primary cause of water quality problems including nutrients and trace metals in over 40% of surveyed rivers and lakes in the U.S. (EPA, 2002). 1.4.1 Nutrient Pollution NPS pollution from agriculture is considered to have an impact on water quality even in the headwaters of the Sumas River watershed, where 50 individual dairy farms contribute to high levels of nutrient levels, low dissolved oxygen (DO), and fecal coliform problems (Stevens et al., 2001). It has been noted that manure spreading may occur during the wettest times of year and on top of snow (Wills, 1998). Efforts have been made to improve water quality in the U.S. portion of the Sumas River in the last twenty years through dredging programs and the removal of canary reed grass and manure residue from stream channels. Although the town of Sumas has a municipal sewage treatment plant along the Sumas River, it any water quality impairments have been demonstrated to be localized and minimal (Cusimano, 1992; Glenn, 1992). A recent farm practices survey of the Sumas Prairie in the Canadian region of the watershed analyzed manure storage capacity and disposal methods by local farmers in order to determine the risk of water contamination (Carter, 1998). It was determined that 18% of farms in the watershed were applying nitrogen (N) above the environmental risk threshold rate of 350 kg N/ha and 100% of farms were applying phosphorus (P) above the rate of 100 kg (P205)/ha (Carter, 1998). Only 20% of dairy farms, 55% of poultry farms, and 57% of hog farms in the Sumas Prairie were considered to have a low potential for degrading water quality in this survey. Carter (1998) found that the average poultry manure application rate in the Sumas and 7 Matsqui Prairies was 767 kg N/ha/yr in 1994 and 436 kg N/ha/yr in 1997. Although both of these rates are excessive there has been an overall decline in application rates, which can be partly attributed to poultry manure exports that were initiated by the Sustainable Poultry Farmers Group in 1996. As of 1997, 86% of poultry producers reported shipping some of their manure off-farm (Carter, 1998) but the amount shipped represented less than 20% of total poultry manure production (EC, 1999). The soil bioremediation and mushroom compost industries are the largest users of poultry manure in B.C. (Chipperfield, 2001). However, poultry manure from the Abbotsford Aquifer region is often shipped to the closest market, nearby Sumas Prairie, effectively remaining within the Sumas River watershed (Chipperfield, 2001). Table 1.4.1 presents the amount of poultry manure produced, calculated using Statistics Canada data, and the amount of poultry manure exported from regions in the Fraser Valley using data from the Sustainable Poultry Farmers Group. Table 1.4.1 2000/2001 Manure shipments from Fraser Valley regions (Chipperfield, 2001; StatsCan, 2001). Source Area Poultry Manure Produced (m3/year) Poultry Manure Exported (m /year) Proportion of Manure Exported (%) Abbotsford Aquifer 162,188 23,658 14.6 Central Fraser Valley 471,947 16,432 3.5 Upper Fraser Valley 138,831 1,109 0.8 Lower Fraser Valley 89,687 6,640 7.4 Total 862,653 47,839 5.5 Nitrate (NCV-N) and P have both been linked to the eutrophication of streams and lakes, and excess algal growth may result in reduced oxygen levels and fish deaths. Eutrophication also reduces the potential use of water for recreation, industry, and drinking purposes. The rate of nutrient runoff will depend on the form of the 8 compounds and their availability to crops in addition to topography and drainage characteristics. For instance, nutrients from manure sources tend to be released to plants more gradually than nutrients from inorganic fertilizers. Between 60 to 90% of the total N in poultry manure is released during the year of application depending on the manure source (turkey, broiler or layer). Phosphorus in poultry manure is generally considered to be about 50% available, while about 95% of potassium (K) is considered available in the year of application (Chipperfield, 1994). For a detailed list of nutrient concentrations found in livestock and poultry feed and manure please see Appendix A. It has been estimated that up to 48% of the total N applied as fertilizer in parts of the Lower Fraser Valley is lost through tile drainage systems (Nagpal et al., 1990). Nitrogen can be converted to N03"-N once it is applied to land through the nitrification process. The negative charge associated with NGy-N means that it is not readily adsorbed by soil particles and can easily be leached into water. It is introduced to waterways from various sources including leaking septic tanks, leaching from soils, manure storage tanks, and as fertilizer runoff. Nitrate is a health concern because it can cause fatal methemoglobinemia in infants and can be toxic to livestock when found in drinking water at high levels. The Canadian Drinking Water Quality Guidelines has therefore set the limit for N03"-N in water at 10 mg/L (Health-Canada, 2003). Ammonia ( N H 3 ) is another species of N found in manure, urine, and fertilizers and can be toxic to fish especially when ionized to the ammonium cation (NH4+-N) (BCMAFF, 1997). Soils with excessive levels of plant-available P have increased in areas of intensive agricultural production due in part to the fact that approximately 80% of P consumed by livestock is excreted (Sharpley et al., 1998). High water tables, tile drainage, and drainage channels exacerbate the potential for loss from P-saturated 9 soils. However, due to the strong adsorption potential of P to soil particles, it is usually introduced to waterways through erosion processes. 1.4.2 Trace Element Pollution In comparison to the large amount of information available on nutrients in the Lower Fraser Valley, less is known about agricultural inputs of trace metals in the region. However, chemical processes involved in the transportation of trace elements from soil to waterways are well documented on a global scale (Crecelius et al., 1975; Edwards et al., 1997; Forstner and Salomons, 1991; Han et al., 2000; Hemond and Fechner-Levy, 2000; Moore and Ramamoorthy, 1984; Sharpley et al., 1998; Sims, 1995). Studies on the depth to which metals travel in several different regions have shown varying results, depending on the pH, the moisture content of the manure applied, the organic matter content of the soil, the soil texture, and the time scale involved in the study. Researchers have found that both surface water and groundwater can be at risk of metals leaching from fields receiving livestock manure (Boswell, 1975; Ellis et al., 1981; Kirkham, 1975; Lund et al., 1976; Moore et al., 1998; Peryea and Kammereck, 1997; Sharpley et al., 1998; Sims, 1995; Sommers et al., 1979). In the North American and European agricultural industries, trace metal compounds are frequently added to livestock and poultry feed as growth promoters and prophylactic antibiotics and are found in all types of manures (Abdulrahim et al., 1999; Del Castilho et al., 1993; Jackson et al., 2003; Kidd et al., 1996; Kpomblekou-A et al., 2002; McBride and Spiers, 2001; Mohanna and Nys, 1999; Nicholson et al., 1999; Potter et al., 1971; Ruffin and McCaskey, 1990; Smith et al., 1992; Stahl et al., 1989; Tufft and Nockels, 1991; Webber and Webber, 1983). As a result of excretion processes, manure runoff can be a source of trace elements including aluminum (Al), 10 copper (Cu), iron (Fe), manganese (Mn), zinc (Zn) and even arsenic (As) and lead (Pb). These elements play a major role as coenzymes or enzyme catalysts in biological systems and are used for disease resistance and to enhance growth rates (Mohanna and Nys, 1999). In the United States, an analysis of 43 elements (transition, inner-transition and light metals, metalloids, and non-metals) in several livestock feeds and manures showed that the levels of Al, chlorine (Cl), cobalt (Co), calcium (Ca), Mn, and Zn in manure were considerably higher than in feed (Westing et al., 1985). Zinc and copper are the most common trace metals associated with livestock and poultry manure (Kpomblekou-A et al., 2002; Miller et al., 1986; Mohanna and Nys, 1997; Pimentel et al., 1991; Van der Watt et al., 1994). Globally, fertilizer applications account for approximately 10% of copper input into soils (9.4x103 tons per year) (Moore and Ramamoorthy, 1984). High levels of Cu and Zn have been found in soils fertilized with poultry litter (Han et al., 2000; Kingery et al., 1994; Kingery et al., 1993; Safo, 1978). Soils subjected to long-term (more than 25 years) poultry manure applications have been shown to have increased concentrations of Cu and Zn and increased leaching of these elements (Han et al., 2000; Kingery et al., 1994; Safo, 1978). Zinc is used in poultry feed for bone and feather development and to improve the immune function and disease resistance in young chicks (Kidd et al., 1996; Scott et al., 1982; Underwood, 1977). Mohanna and Nys, (1999) have reported that poultry feed often contains Zn levels 2 to 3 times higher than is nutritionally required. Furthermore, it has been shown that up to 94% of the Zn ingested by poultry is eventually excreted (Mohanna and Nys, 1997). Zinc is given to piglets as zinc oxide to improve growth performance, and to adult pigs as zinc sulphate to prevent mineral deficiency syndromes (Brumm, 1998). Zinc sulphate is also used as a plant fertilizer, 11 ZnCI2 is used as a pesticide and organic zinc compounds are used as fungicides (Ohnesorge and Wilhelm, 1991). Copper sulfate has been routinely added to the diets of poultry and pigs to promote weight gain, suppress digestive bacteria and improve feed efficiency since the 1950s (Miller et al., 1986; Nicholson et al., 1999; Scheinberg, 1991). As much as 80 to 95% of dietary Cu has been found in manure (Kpomblekou-A et al., 2002; Taiganides, 1963). Due to the fact that Cu is a bactericide at concentrations as low as 5 to 10 ppm, microorganism communities in manure storage areas may be altered and could negatively influence nutrient biodegradation rates (Nicholson et al., 1999). Moore et al. (1998) noted soluble Cu levels up to 1 mg/L in runoff from soils amended with 9x103 kg/ha of poultry manure 7 days after application, which is approaching the USEPA drinking water maximum contaminant level of 1.3 mg/L (Jackson et al., 2003). Agricultural uses of As include calcium arsenate, which is used in several insecticides, and sodium arsenite, which is used in herbicides, fungicides, and wood preservatives. Arsenic is found in conjunction with Pb, Ca, Cu, Mn, Zn, and Na compounds for pesticides and herbicides, especially on blueberry crops (Leonard, 1991). Inorganic and organic As compounds used in pesticides and herbicides can accumulate in agricultural soils and plants (Peterson et al., 1981). Most fertilizers also contain detectable levels of As (McBride and Spiers, 2001). Arsenic occurs in poultry feed as 4-aminovessel phenylarsonic acid (p-ASA), 4-nitrophenylarsonic acid, 3-nitro-4-hydroxyphenylarsonic acid (ROX), and arsenilic acid for the prevention of coccidiosis, to increase weight gain, and to improve feed efficiency (Kpomblekou-A et al., 2002). It has been reported that up to 88% of arsenilic acid, ROX, and 4-nitrophenylarsonic acid may be excreted in poultry litter (Bhattacharya and Taylor, 1975; EPA, 2002; Isaac et al., 1976; Jackson et al., 2003; Webb and Fontenot, 1975). Arsenic speciation changes 12 may occur in manure either through metabolic processes through the digestive system or through biotic or abiotic processes during manure storage prior to soil application (Jackson et al., 2003). Jackson et al. (1999) showed that 72% of total As from poultry litter could be solubilized by water extraction. Initial soluble As concentrations of >200 u,g/L were reported in runoff from soils amended with 9x103 kg/ha of poultry manure and measurements 7 days after application indicated that concentrations were still >50 u_/L (Moore, 1998). The feed additive ROX was found to be the source of 50% of the As in manure leachate. Other elements associated with agriculture include Cr, Mn, and Pb. Manganese compounds are used as feed additives, fertilizers and fungicides in agriculture (Schiele, 1991). Chromium picolinate is added to the diets of pigs to enhance the percentage of muscling and reduce fat levels (Brumm, 1998). Lead is used in association with other metals, mainly in pesticides, and is also found in livestock manures. The level of nutrients and metals commonly found in manure is summarized in Table 1.4.2. For a more complete listing of results found in the literature please see Appendix A. Table 1.4.2 Nutrient and trace elements contents of typical manures (Nicholson et al., 1999; Sharpley et al., 1998). Manure Type Dry Matter N P K Zn Cu Pb As % % mg/kg Cow 10 3.6 0.8 2.6 17 4.5 0.7 0.2 Pig 10 7.6 1.8 2.6 65 47 0.8 0.2 Poultry (Broiler/Turkey) 60 4.0 1.7 1.9 130 19 2.0 0.3 Poultry (Layer) 30 4.0 1.7 1.9 175 27 2.7 0.1 13 1.4.3 Trace Element Bioavailability Elements in aquatic ecosystems can be present as dissolved ions, adsorbed onto particulates, precipitated on clays, or chelated with hydrous oxides and organic matter (Frimmel, 1983). These speciations are all in dynamic equilibrium, however, some fractions are more available to biotic systems than others (Figure 1.4.1). Anthropogenic Activities Sediment Groundwater Interstitial Water Figure 1.4.1 Interactions between abiotic and biotic systems in the aquatic environment (Forstner and Salomons, 1983). There is evidence that the toxic effects of trace elements in aquatic organisms is not related to the total concentration but rather to the bioavailable fraction (Leppard, 1983). Bioavailable elements in the environment are defined as those species of metals, non-metals, and metalloids that plants or animals can absorb or passively consume (Campbell et al., 1988). Examples of possible interactions and transport routes for trace metals across cell membranes include direct lipid solubility, passage through aqueous pores, lipid-mediated transport, protein-mediated transport, and binding with surface proteins (Batley, 1983). 14 Factors that can affect trace element bioavailability in aquatic environments include the pH of the water, the number of adsorption sites (clays, hydroxides, organic matter), water hardness, and redox conditions (Forstner and Salomons, 1991; Reichman, 2002). The suitability of water as biological habitat is determined in part by pH, which has an influence on the speciation of dissolved ions, therefore it is often called a master variable (Hemond and Fechner-Levy, 2000). As pH decreases, cations compete with extra hydrogen (H+) and aluminum (Al3+) from clay particles for positions on exchange sites. As a result, the solubility of cations increases as pH decreases, thereby increasing the fraction of bioavailable species (Jackson et al., 2003). Metal ions tend to be positively charged whereas clay colloids are negatively charged. Therefore, increasing clay and hydrous oxide contents in sediments provides more sites for metal adsorption thus reducing the amount of metals that are in the bioavailable fraction. Chelation of trace elements by acidic functional groups in manure may increase bioavailability and transport into the ecosystem (Kpomblekou-A et al., 2002). Dissolved organic carbon (DOC) is made up of humic and fulvic acids, which generally originate from decaying plant material (Hemond and Fechner-Levy, 2000). DOC acts as a complexing agent to form metal-organic complexes in natural waters. Increasing the number of anions in solution (salts or carbonates) may result in dissolved cations complexing with chloride (Cl") or bicarbonate/carbonate (HCO37CO3") anions as opposed to binding with clay particles (Albergoni and Piccinni, 1983; Forstner and Salomons, 1983; Forstner and Salomons, 1991; Miller and Mackay, 1980; Yuan, 2000). Oxidation/reduction (redox) conditions can play a role in the availability of elements by affecting the proportion of a metal species with a particular oxidation state and its solubility (Reichman, 2002). For instance, Fe and Mn solubility is known to increase under reducing conditions (Schmitt and Sticher, 1991). 15 Interactions between certain metals can also affect toxicity risks. Metal ions can compete for adsorption sites, metabolic sites, or interact with excretory systems to decrease toxicity in the presence of one another. For instance, studies have shown that Cu accumulation in the livers of mammals decreases in the presence of Fe or Zn and a relationship between Ni and Fe has been found whereby Ni converts unavailable ferric iron ions into a bioavailable form (Albergoni and Piccinni, 1983). 1.5 The Use of the Diffusive Gradient Thin Film Technique (DGTs) in Water Quality Investigations Diffusive gradients in thin films (DGTs) consist of a binding agent that accumulates solutes quantitatively after passing through a diffusion layer (DGT-Research, 2002). A polyacrylamide hydrogel is commonly used as the diffusive layer, while a resin layer consisting of Chelex 100 acts as the binding agent. The two gels are enclosed in a small plastic device that can be deployed in waterways for up to several weeks at a time (Gimpel et al., 2001; Peters et al., 2003). Ions must diffuse through a filter and the diffusive layer in order to reach the resin layer (Figure 1.5.1). The establishment of a constant concentration gradient in the diffusive layer allows for the measurement of metal concentrations in solution quantitatively (DGT-Research, 2002). Figure 1.5.1 S c h e m a t i c of a D G T unit: S i d e v iew and top v iew (modi f ied f rom D G T R e s e a r c h , 2002) 16 The pore size of the diffusive gel generally permits free metal ions and inorganic and small organic metal complexes to diffuse through to the resin while excluding particles and large colloids. Metal complexes must dissociate during their transport through the diffusive layer. Therefore, only labile complexes are measured, which includes metal-fulvic complexes (Gimpel et al., 2001). Ion exchange resins such as Chelex 100 accumulate ions through exchange mechanisms, thus modeling the action of cell walls on plant roots, fish gills, and aquatic invertebrates (DGT-Research, 2002). Chelex 100 resin is composed of styrene divinylbenzene copolymers containing paired iminodiacetate ions that act as chelating groups for binding polyvalent metal ions. Chelex 100 resin differs from ordinary exchangers because it has a high selectivity for polyvalent metal ions and higher bond strength. It has a high preference for heavy metals over other cations such as Na + or K + (Bio-Rad, 2003). Using Zn 2 + as the reference, Chelex 100 selectivity factors for metal ions in NOV or Cl" solutions are summarized in Table 1.5.1. Table 1.5.1 Selectivity for Divalent Cations (Bio-Rad, 2003). Divalent cation Selectivity factor Hg 2 + 1060 C u 2 + 126 N i 2 + 4.4 Pb 2 + 3.88 Zn 2 + 1.00 Co 2 + 0.615 C d 2 + 0.390 Fe 2 + 0.130 Mn 2 + 0.024 C a 2 + 0.013 Mg 2 + 0.009 Na + 1 0.0000001 17 It should be noted that the actual selectivity for a metal ion depends on pH, ionic strength and the presence of other complex-forming metal species in the water column. DGTs are appropriate field tools because they preconcentrate cations, which eliminates the problem of poor detection at very low concentrations (Harris, 1999). Any metal removed from solution is replaced by an equivalent amount of Na + ions originally on the resin (Bio-Rad, 2003). The total capacity of Chelex 100 resins to accumulate metals is a function of pH but calculations have shown that less than 1 % of the total DGT capacity is reached after one month in solutions with high concentrations of metals (Gimpel et al., 2001). Metal concentrations in rivers may be highest during and directly after a storm event when runoff first enters the waterway (Hall et al., 1999; Wilbur and Hunter, 1977). This flush of metals during storms may be missed when water sampling occurs on a weekly or monthly basis. DGTs are a good solution to this problem because they are able to accumulate all of the cations present during the deployment period, including storm events. Furthermore, the concentrations of metals measured by DGTs in solutions with pH values between 5 and 8.3 are identical to those obtained by direct measurement (Gimpel et al., 2001). The pH range (6.0 - 8.0) and flow of most rivers in the Lower Fraser Valley provide appropriate conditions for accurate results. When DGTs are deployed in rivers or streams with reasonable flow rates (>0.02 m/s), measurements are independent of flow to within 5%. Therefore, DGT units can be expected to work reliably well as a device for measuring concentrations of metal ions in natural waters such as those found in the Sumas River watershed. 1.6 Cumulative Effects Unfortunately, due to the nature of NPS pollution, it is very difficult to follow nutrient and trace metal levels in the environment back to the original sources of 18 contamination. Many variables involved in ecosystem processes exhibit a temporal or spatial lag between the time or place that the event occurs and the time or place that the effects can be measured. This phenomenon is known as cumulative effects (CEs). One type of NPS pollution CE occurs when contamination from several different locations enters the receiving environment at the same time. A second type of CE can result from continual low-impact, or chronic, contamination in the same location over time. In most environmental cases, CEs are a combination of both types, and result from multiple activities occurring in space and time that persist and interact with other subsequent activities (MacDonald, 2000). For instance, a lag time between fertilizer application and water contamination may occur due to soil characteristics and chemical pathways combined with climatic conditions (Paul and Zebarth, 1996; Schepers et al., 1991). Studies have also suggested that runoff and erosion are subjected to CEs from land management and natural processes (Garbrecht, 1991). In order to properly determine CEs, information is required on land use, hydrological pathways, water quality indicators, and the response of the receiving environment. In the case of the Sumas River it is useful to link indicators of land use activities with water and sediment quality data from throughout the watershed to determine whether agricultural operations are posing spatial or temporal cumulative contamination burdens on the environment. 19 Chapter 2 Research Scope and Objectives 2.1 Overall Scope The scope of this research project was to determine whether water quality has been degraded as a result of recent increases in agricultural intensity in the Sumas River watershed. The data collection included a follow-up investigation to research conducted by Berka (1996) regarding nutrient levels in the surface water and trace elements in sediment. The bioavailability of trace elements at various sites throughout the watershed was given particular attention. The instruments used to measure the links between land use and environmental quality were agricultural census data, land cover data, water, DGT, and sediment analysis, geographic information systems (GIS), and various statistical techniques. 2.2 Objectives a) Document and quantify changes in land use and agricultural activities in the Sumas River watershed over the past 10 years. b) Analyze sediment and water samples for environmental quality indicators and compare results with historic data collections. c) Characterize the bioavailability of trace metals in water using a method known as the diffusive gradient thin film technique (DGTs). d) Examine links between agriculture and environmental quality using land use indicators, correlations, trends, and tests of significance to determine spatial and temporal cumulative effects. 20 Chapter 3 Methods 3.1 Land Use Indices and Climate Data 3.1.1 Meteorological and Hydrometric Data Precipitation data from the Abbotsford Airport climate station was obtained from Environment Canada's on-line meteorological data files (EC, 2004). The precipitation regime for 2003 and 2004 was compared with historical data from 1970 to 2000. Flow data measured from a hydrometric station at the U.S./Canada border on the Sumas River was also obtained from Environment Canada (unpublished data) and was used to compare the 2003 and 2004 data set to historical trends and to spot anomalies. 3.1.2 Geographic Information Systems (GIS) Data The Canadian portion of the Sumas River watershed was the main unit of study for the Geographic Information System (GIS) analysis due to the availability and accessibility of maps (land use and land cover) and climate data. All spatial data was analyzed using ArcView (v.3.2) GIS. Base map information was obtained from digital ortho-photographs taken in 1995 and provided by the Triathlon Mapping Corp. of Burnaby, B.C. Hard copies of land use maps (scale 1:20,000) produced in 1988 and 1995 were digitized to create land use map layers for those years. A hardcopy of an ortho-photograph produced in 2002 was used to digitize the 2002 land use map layer. Farm buildings were included in the calculation of area for the agricultural land use category. A windshield survey conducted on October 1st and 2 n d, 2003 was used to produce a detailed land cover map by identifying crops on an acetate sheet placed over the 2002 ortho-photo map. This crop cover map was digitized to create a 2003 land cover layer for the GIS. 21 3.1.3 Agricultural Census Data and Animal Unit Equivalents (AUEs) All census data was obtained from Statistics Canada's Agricultural Censuses (1991, 1996, and 2001). Statistics Canada enumeration area (EA) data for the Sumas Prairie and Abbotsford Aquifer (Matsqui South) sub-regions was used to explore land cover and livestock densities for 1996 and 2001. The number of animal units per hectare of farmland for each EA was used to help determine agricultural intensity. The OMAF Nutrient Calculator (2002) computer program was used along with Statistics Canada EA data from the 1996 and 2001 agricultural censuses to determine Animal Unit Equivalents (AUEs) for the EAs in the Sumas Prairie and the Abbotsford Aquifer sub-regions. EA boundaries changed somewhat between 1996 and 2001 therefore changes in AUEs were calculated using all the EAs for the Sumas Prairie and Abbotsford Aquifer areas so that adequate comparisons could be made between 1996 and 2001 for the two regions. 3.1.4 Nutrient Budgets Nutrient budgets were carried out using a model developed by Brisbin (Brisbin, 1995) to provide an estimate as to whether or not the manure produced in a specified area creates a deficit or surplus of N, P, or K once all the sources and sinks are considered. The Brisbin method has been used for similar studies in the Lower Fraser Valley by both Wernick et al. (1998) and Berka (1996). For this study, the nutrient budgets were performed using the EA geographical boundaries of Statistics Canada, which provided the most detailed level of analysis, for both 1996 and 2001 censuses. The N surplus results for each EA was incorporated into the GIS and used for correlations with environmental variables. 22 3.2 Sampling Site Selection The water and sediment sampling stations were chosen based on the locations sampled in the 1990s so that historical comparisons of the results could be made (Table 3.2.1). Three new sites were added: one in Whatcom County on Aim Rd. (#18) and two new reference sites (#17 and #19) on Vedder Mountain (Figure 3.2.1). It was felt that the historical reference site on Sumas Mountain (site #15) could no longer represent an area that was minimally impacted by human activity due to recent increases in gravel and shale mining and other development activities in that area. Results from Vedder Mountain site #17 were not used during data analysis because it was an ephemeral stream and appeared to be contaminated by a nearby septic field. Table 3.2.1 List of water and D G T sampling sites and years they were sampled. Tributary Site ID # Years Sampled D G T 2003/2004 Sumas River (headwaters) 16 1994, 1995, 2003, 2004 No Sumas River (headwaters) 2 1994, 1995, 2003, 2004 Yes Sumas River (headwaters) 18 2003, 2004 No Sumas River (border area) 3 1994, 1995, 2003, 2004 Yes Sumas River (border area) 4 1994, 1995, 2003, 2004 No Sumas River (downstream) 12 1994,1995, 2003, 2004 No Sumas River (downstream) 6 1994,1995, 2003, 2004 No Sumas River (downstream) 7 1994, 1995, 2003, 2004 Yes Swift Creek 1 1994, 1995, 2003, 2004 No Arnold Slough 10 1994, 1995, 2003, 2004 Yes Arnold Slough 11 1994, 1995, 2003, 2004 No Saar Creek 14 1994,1995, 2003, 2004 No Marshall Creek 13 1994, 1995, 2003, 2004 Yes Marshall Creek 5 1994,1995, 2003, 2004 No Sumas Canal 8 1994, 1995, 2003, 2004 Yes Sumas Canal 9 1994,1995, 2003, 2004 No Vedder Mountain (Reference) 19 2003,2004 Yes Sumas Mountain 15 1994,1995, 2003, 2004 No V e d d e r Moun ta in . 17 2003, 2004 No Total 18 7 23 Sumas Watershed 10 0 10 Kilometers Figure 3.2.1 Aerial ortho-photograph with outline of Sumas River watershed boundary and sampling sites. DGTs were deployed at site #2 (Sumas River directly downstream from Swift Creek confluence), site #3 (Sumas River at the Canada/U.S. border), site #7 (Sumas 24 River at MacDonald Park), site #8 (Sumas Canal), site #10 (Arnold Slough), site #13 (Marshall Creek), and site #19 (Vedder Mountain reference site). 3.3 Field Sampling and Laboratory Analysis 3.3.1 Water Sampling and Laboratory Analysis Water samples were collected on 14 occasions (approximately every month) between May 2003 and June 2004. Samples were collected in clean acid-bathed 250 ml Nalgene bottles and were stored in a cooler during transportation to the laboratory. All samples were collected at arm's length from the stream bank after rinsing the collection bottle thoroughly with the stream water. Triplicate samples were taken at one site per sampling occasion to be used for quality control analysis. Parameters that were measured in situ include conductivity, specific conductivity and temperature using a Yellow Springs Instrument Co. (YSI) Model #30M/50 Fl meter and dissolved oxygen using a YSI Model #58 meter. Samples were kept in a cooler on ice prior to analysis. In the laboratory, the Orion 420A pH meter was used to measure pH within 12 hours of sample collection. For every set of samples one was measured in triplicate in order to determine variability as a result of the pH meter. Chloride (Cl"), nitrate (N03"-N), total ammonia as ammonium (NH4+-N), and orthophosphate (PO4) were analyzed the day after sampling in the UBC Soils Department laboratory. The water samples were filtered using Whatman #41 filter paper prior to analysis. The nutrients were then analyzed on a Lachat XYZ QuickChemAE autoanalyzer using method #12-107-04-1-B for N03"-N (detection limit 0.10 mg/L), method #10-107-06-2-Afor NH 4 +-N (detection limit 0.10 mg/L), method #10-115-01-1-A for P 0 4 (detection limit 0.02 mg/L), and method #10-117-07-1-A for Cl" (detection limit 6.0 mg/L). Dissolved elements were analyzed in the UBC Soils 25 Department laboratory using the Inductively Coupled Plasma-Atomic Emission Spectrometer (ICP-AES). Dissolved organic carbon (DOC) was analyzed in the UBC Civil Environmental Engineering laboratory. Samples were filtered using Whatman #41 filter paper and analyzed using a Shimadzu (TOC-500) Total Organic Carbon Analyzer. DOC was then determined by subtracting the dissolved inorganic carbon from the total dissolved carbon. 3.3.2 DGT Sampling and Laboratory Analysis DGT performance was tested in the laboratory prior to deploying any of the units in the field using a procedure adapted from DGT Research, Ltd. (2002). Three DGT units were suspended in 1000 ml of 0.01 M Cd(N0 3) 2 in the laboratory at room temperature for a period of four hours. At the same time, a blank version of the test was performed using DGTs suspended in 0.01 M NaN0 3. Aliquots of 20 ml were removed from the Cd(N0 3) 2 and NaN0 3 solutions at the start and end of the four-hour period in order to determine if the concentration of elements in solution had changed during the course of the experiment. After four hours, the DGTs were removed from solution and placed into 30 ml acid-washed Teflon bottles containing 20 ml 1M HN0 3 and were eluted over a 72-hour period. The samples were then analyzed in the UBC Soils Department laboratory for total metal analysis on the ICP-AES and the results were used to calculate performance efficiency. The experiment was run twice, with the solution being stirred manually every ten minutes during the second experiment. The stirring motion minimized the accumulation of air bubbles on the surface of the DGT units and mimicked a natural flowing environment. 26 DGT units were deployed for periods ranging between 3 and 4 weeks at a time. The first set of DGTs was deployed on October 14th, 2003 and the final set of DGTs was collected on July 13th, 2004 for a total of ten deployments. Duplicate DGTs were used at rotating sites in order to calculate within site variability. The field procedures were carried out using the methods provided by DGT Research Ltd. (2002). In summary: 1) The DGT unit was suspended by using fishing wire to anchor it to a rock or bamboo stick on the riverbank. 2) The DGTs were deployed in areas of flowing water, but excessive turbulence and bubbles (riffles) were avoided. 3) The time of deployment and retrieval were recorded to the nearest minute. Temperature was measured using the YSI conductivity meter at the start and end of the deployment period. 4) Upon retrieval the DGT units were rinsed with deionized water from a wash-bottle, placed in sealed individual plastic bags, and stored in a cooler on ice during transportation to the laboratory. In the laboratory, the resin gel was retrieved from the DGT by inserting a screwdriver into the groove on the side of the unit and twisting it. The cap was then removed and the filter and diffusive gel layer was peeled off using plastic tweezers to reveal the bottom resin gel layer. The resin gel was placed in an acid-washed 30 ml plastic Teflon bottle containing 20 ml of 1M HN0 3 solution. The resin was then left to elute in the acid for at least 72 hours before analysis in the UBC Soils Department laboratory for total metal analysis on the ICP-AES. For a complete description of the calculations used to determine the time-averaged bioavailable metal concentrations using DGTs, please refer to the instruction manual by DGT Research (2002). 27 3.3.3 Sediment Sampling and Laboratory Analysis Grab samples of sediment were collected on July 7, 2003 at 30 sites and May 17, 2004 at 29 sites during low flow conditions. These sites included the water sampling stations as well as additional sites in the agricultural ditches of Sumas Prairie. A 2.5 m wooden pole with an aluminum pot at one end was used to collect the surface sediment layer on the top centimetres of the streambed in the centre of the waterway. For quality control and analysis, duplicate or triplicate samples were collected at several sites to calculate within-site parameter variability. The samples were placed into labelled plastic bags and transported to the laboratory in an ice-filled cooler. In the laboratory, the sediment sample was wet-sieved through stainless steel sieves in order to obtain the <63 u,m sediment fraction, which includes both silt and clay particles. This portion of sediment tends to accumulate the greatest amounts of metals and represents the total trace element fraction. The sieved sediment was placed into acid-washed beakers and left at room temperature for 24 hours in order to allow any suspended particles to settle out. After settling, the beakers were transferred to ovens and dried at approximately 70°C. Once dried to a muddy consistency, the sample was transferred to plastic weigh boats and left to fully dry at air temperature. A mortar and pestle was then used to break apart large aggregates of the dried sediment and the samples were stored in sealed labelled plastic containers until analysis. The U.S. Environmental Protection Agency method #200.2 was used to prepare the sediment samples for elemental analysis (USEPA, 2003). This method uses the 'acid-soluble metal' technique for the analysis of biologically active elements. Blank controls and a certified standard reference material from Priority PollutnT™/CLP (Lot 28 No. DO35-540) was used to test the accuracy of results. A summary of the USEPA method #200.2 for trace metal analysis is provided here: 1) 1.0g of sieved, dried sediment sample is added to a 250 ml beaker 2) 10 ml of 1:4 HCI and 4 ml of 1:1 HN0 3" is added to the beaker and covered with a watch glass 3) Beakers are placed into an oven at 85°C and refluxed for approximately 30 minutes 4) Beakers are removed from the oven and allowed to cool for 30 minutes 5) The solution is filtered through at Whatman filter #42 into a 100 ml volumetric flask 6) Solution is brought up to 100 ml using deionized water, covered with Parafilm and shaken 6 times 7) Sample is transferred to a 60 ml Teflon sample container for analysis Sediment samples that had been collected from the same sites on September 3, 1993 and August 15, 1994, were stored over the years in airtight plastic containers in the laboratory. These samples were re-analyzed using the same USEPA method #200.2 so that accurate comparisons of the results could be made. Long-term storage of sediments in airtight plastic containers is not expected to alter the amount or speciation of metals in the samples. The acid-digested samples were analyzed in the UBC Soils Department laboratory for total metal analysis on the ICP-AES. The method used for particle size analysis was modified from one that allowed for large batches to be analyzed at once (Kettler et al., 2001). A summary is provided here: 1) Samples are wet-sieved to separate out the <2 mm sediment fraction 2) Hexametaphosphate (HMP) is added to the samples (45 ml: 15 g HMP to sediment ratio) 3) Samples are placed on a shaker for 2 hours 4) The samples are sieved to separate the sand fraction (>0.053 mm) which is then dried in an oven and weighed 5) The remaining silt and clay fractions are allowed to settle out at room temperature for 3 hours 6) The solution is decanted and discarded (this represents the clay fraction) 29 7) The remaining silt fraction is dried in an oven and weighed 8) The percent of sand and silt is calculated based on the dried weights and the clay fraction is calculated based on the difference between the original sample weight (15 g) and the combination weight of sand and silt 3.4 Data Analysis Methods 3.4.1 Quality Analysis and Quality Control The coefficient of variance for sampling site replicates was used to determine within site variability and sampling errors for water, DGT, and sediment data. In the laboratory, several duplicate analyses of water and sediment samples were used to determine the variability caused by instrument analysis. Accuracy of water sample analysis was determined by measuring standard samples with known concentrations on the Lachat autoanalyzer and ICP-AES during each sampling run. Certified standard reference material (Priority PollutnT™/CLP Lot No. DO35-540) was used to determine the accuracy of the trace metal analysis for sediment samples. Blanks were included in water, DGT, and sediment analyses to ensure that solutions were not contaminated. 3.4.2 Water Data: Statistical Analysis In order to facilitate data analysis, the 18 sampling sites were pooled together by region. A total of ten regions or tributaries were identified using this method: Region 1: Sumas River headwaters: sites #16, #2 and #18 (n=3) Region 2: Sumas River border area: sites #3 and #4 (n=2) Region 3: Sumas River downstream area: sites #12, #6, and #7 (n=3) Region 4: Swift Creek: site #1 (n=1) Region 5: Arnold Slough: sites #10 and #11 (n=2) Region 6: Saar Creek: site #14 (n=1) Region 7: Marshall Creek: sites #13 and #5 (n=2) Region 8: Sumas Canal: sites #8 and #9 (n=2) 30 Region 9: Sumas Mountain: site #15 (n=1) Region 10: Vedder Mountain: site #19 (n=1) The water results were separated into wet and dry seasons based on several characteristics (changes in flow, precipitation, and nitrate medians). The dry season included samples taken from May 2003 to early October 2003 and March 2004 to June 2004 while the wet season ranged from late October 2003 to February 2004. In total, there were nine sampling outings in the dry season and five sampling outings in the wet season. Medians for each variable in these data sets were computed for each region and used to determine seasonal trends and differences between tributaries. Graphs were created in order to visualize the trends in water quality parameters in both the Sumas River mainstem and it's tributaries from the upstream to the downstream direction. Data series in these graphs each represented a wet season and dry season trend based on medians for each sampling site. Descriptive statistics, boxplots, and normality tests for all sites were created using SPSS software v. 12.0. The boxplots were created for each variable on the basis of both sampling site and sampling date. The data for most variables followed non-normal distributions and therefore data transformation was attempted. Both the natural log (In) and RANK : BLOM procedures in SPSS were employed, however, several of the variables failed to adhere to normality even after transformation. This was likely due to the fact that several parameters were highly skewed to the right because many results were below detection limit. Low sample numbers for the seasonally-tested data (n=9 during the dry season and n=5 during the wet season) also created normality problems. As a result, all further analyses were performed on non-transformed data using non-parametric statistical testing. 31 Based on the boxplots of water quality parameters by date, it was determined that Marshall Creek was often an outlier. Marshall Creek is under significant influence from the Abbotsford Aquifer and therefore often displays opposite seasonal tendencies in comparison to other surface water systems. A study by Berka (1996) found similar results. For instance, N03"-N levels are highest in the dry season in Marshall Creek whereas the opposite is true for all other sites. Temperature oscillations in Marshall Creek were also dampened. Therefore, results from Marshall Creek samples were included in graphs, descriptive statistics, normality plots and boxplots, and statistical analysis of the seasonal data pooled together, but was omitted from wet and/or dry season comparisons by site. The non-parametric Kruskal-Wallis test, which can be used as a substitute for the parametric ANOVA test, was performed on the water data (wet and dry seasons separately and both seasons together) to determine whether any differences existed between the medians of the parameters by region using a significance level of a=0.05. If the results from the Kruskal-Wallis test indicated significant differences between regions, a Mann-Whitney U test was performed to determine which pairs of regions specifically differed from one another. The Mann-Whitney U test is the non-parametric equivalent to the z and t tests for independent samples. The three regions within the Sumas River (headwaters, border, and downstream) were not compared to one another because it was assumed that they might be autocorrelated and were therefore not likely to be independent. The Mann-Whitney significance level was determined by using the Bonferroni adjustment in order to reduce the Type I error that may occur when testing several pairs of samples. This method divides the initial a level (0.05) by the possible number of pair wise comparisons for a resulting significance level of a<0.01. 32 Long-term cumulative effects were explored by comparing nutrient and dissolved oxygen data from 1994/95 to the 2003/04 dataset. This was achieved by creating scatter plots for each variable (seasons combined and wet and dry seasons separately) and computing a linear trendline between the two sets of data. To further determine whether the changes in N03"-N concentrations over time where significant, the Wilcoxon Signed Rank test (a=0.05) was performed to compare 1994/95 to the 2003/2004 data. The Wilcoxon Signed Rank test was chosen over the Mann-Whitney U test because the samples were assumed to be dependent due to the fact that comparisons were being made within regions over time, not between regions for one time period. The Wilcoxon Signed Rank test was run on the data for both seasons combined, and on both wet and dry seasonal data. Marshall Creek was included in all of the Wilcoxon Signed Rank tests for nitrate because it was being compared to itself and not to other regions. Spearman Rank correlation coefficients (a=0.10) were calculated for the water variables (nutrients, physical parameters, and dissolved elements) to determine if any relationships existed between the parameters. The correlations were calculated for both seasons combined as well as the wet and dry seasons separately. The combined seasons correlations included data from Marshall Creek while the separated seasons correlations omitted that region. 3.4.3 DGT Data: Statistical Analysis Bar graphs were created to visualize the changes in the concentration of bioavailable metals measured over time at each DGT sampling station. Descriptive statistics, normality tests and boxplots (by site and by date) were created using SPSS. 33 Due to the non-normal distributions and low number of samples associated with the DGT data, non-parametric statistical tests were employed. A Kruskal-Wallis test (a=0.05) was used to determine whether any differences existed between the medians of the variables by site. If the results from the Kruskal-Wallis test indicated significant differences between sites, a Mann-Whitney U test (aO.01 using the Bonferroni adjustment) was performed to determine which pairs of DGT deployment sites specifically differed from one another. Spearman Rank correlation coefficients (<x=0.10) were calculated for the metals detected (Al, Fe, Mn, Ni, Zn), the precipitation data, pH, and temperature to determine if any relationships existed between the parameters. The correlations were calculated for both seasons combined as well as the wet and dry seasons separately. The combined seasons correlations included data from Marshall Creek while the separated seasons did not. 3.4.4 Sediment Data: Statistical Analysis Graphs were created to visualize changes in metal concentrations from the upstream to downstream direction in both the Sumas River mainstem and its tributaries. These graphs plotted the averages from the samples collected during each decade (1993/1994 and 2003/2004 data pooled). Descriptive statistics, normality tests, and boxplots (by site and by year) were created using SPSS. Based on the non-normality of the data distributions and the low number of samples collected, non-parametric statistical analyses were used. A Kruskal-Wallis test (oc=0.05) was performed on the 2003/04 data to determine if differences existed in metal concentrations by region. The regions were the same as 34 those identified during the water data analysis but also included the additional Sumas Prairie ditches region for a total of 11 regions. Mann-Whitney U tests (ct<0.01 using the Bonferroni adjustment) were used to make pair-wise comparisons of the regions for the 2003 and 2004 sampling period. Swift Creek, Sumas Mountain, and Vedder Mountain sites were omitted from the Mann-Whitney comparisons due to their small sample sizes (n=2). Spearman Rank correlation coefficients (cc=0.10) were calculated for the 2003/04 sediment metal data to determine if any relationships existed between the parameters. A Kruskal-Wallis test (a=0.05) was also performed on the four sets of data categorized by year (1993, 1994, 2003, 2004) using only data from sites that were sampled during each of the four sampling years. A Wilcoxon Signed Rank test (cc=0.10) was used to determine if the levels of metals changed significantly over time. The Wilcoxon Signed Rank test was first used to determine if differences existed between the annual pairs of samples (1993 vs. 1994 and 2003 vs. 2004). If few differences existed, the data for each decade was then pooled together and a Wilcoxon Signed Rank test (a=0.10) was performed to determine if differences existed from one decade to the next (1993/4 vs. 2003/4). The lumped decadal data was then tested using a Wilcoxon Signed Rank test (a=0.10) by region to determine which tributaries had changed significantly over time. Swift Creek, Sumas Mountain, and Vedder Mountain regions were omitted from the Wilcoxon Signed Rank tests due to their small sample sizes (n=2). 3.4.5 Relationships between Land Use, Sediment, and Water Quality In order to determine relationships between environmental quality and land use, the water, DGT and sediment data were graphically and statistically linked to land use 35 indicators. Addah (2003) and Berka (1996) indicated that the use of buffers was preferable to the use of contributing areas for determining relationships between water quality and land use in agricultural watersheds with low topography. Land use buffers were therefore created using ArcView GIS for all of the sites in the Canadian portion of the watershed. These buffers extended 100 m on either side of the stream and 500 m upstream from each sampling site. The following attributes were identified within the buffers: AUE/ha and N surplus, (based on the EA the buffer was located in), land cover (%corn, crop residue, vegetable, pasture, berry or nursery crop, and forest) and % clay content of sediment samples (based on the particle size distribution results). Spearman Rank correlation coefficients (a=0.10) were calculated to determine relationships between water quality, metal bioavailability (DGT data), sediment quality, and land use indices within buffers. These correlation coefficients were calculated for each site for the wet season, dry season and both seasons together. 36 Chapter 4 Results 4.1 Land and Climate Results 4.1.1 Precipitation and Flow Data In order to determine if the 2003-2004 water sampling was conducted during a typical meteorological and hydrological period, long-term precipitation and flow data was obtained for comparison. Precipitation data from a climate station at Abbotsford airport and flow data from a hydrometric station in the Sumas River at the international border are presented in Figure 4.1.1 along with flags indicating water sampling dates. 400 350 _ 300 E 250 c I 200 •§" 150 °" 100 50 0 Precipitation Flow • Sampling Date I I 25 20 15 J2 CO E 10 rr May- Jun- Jul- Aug- Sep- Oct- Nov- Dec- Jan- Feb- Mar- Apr- May- Jun-03 03 03 03 03 03 03 03 04 04 04 04 04 04 Figure 4.1.1 Monthly precipitation in Abbotsford, flow data for the Sumas River, and sampling date indicators. Monthly precipitation data for 2003 was lower than average during February, August, and December and higher than average in October (Figure 4.1.2). However, the total precipitation for 2003 in Abbotsford was 1550.7 mm, which compares well with the 1971-2000 annual average of 1573.2 mm (EC, 2004). Historical flow data indicates that the 2003-2004 Sumas River range of flow is within the normal scope (EC, 2003). 37 However, it should be noted that the flow data from mid-January to mid-February 2004 was missing from the data set. Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec Month Sumas River at International Boundary m3/s Figure 4.1.2 Average monthly precipitation at Abbotsford airport (top) and average flow of the Sumas River at the international border (bottom). 38 4.1.2 Land Use in the Sumas River Watershed Fruit, vegetable, dairy, hog, and poultry operations are found along over 90% of the Sumas River (Stevens and Eriksson, 1997). A summary of land use for the Canadian portion of the Sumas River watershed is provided in Table 4.1.1. Detailed maps created using ArcView GIS are presented in Appendix B. The residential land use category changed the most between 1988 and 2002, increasing from 4.6 km2 to 6.9 km2. The total impervious area (residential and commercial/transportation) reached 7.6% of the total watershed area for the Canadian portion of the watershed by 2002, which is approaching the 10% threshold for aquatic health impacts (Hall et al., 1999). The amount of land associated with agricultural use has changed very little since 1988, which may be attributed to the agricultural land reserve (ALR) in this region. Table 4.1.1 Land use by area and % of total area for the Canadian portion of the Sumas River watershed: Changes over time. Year Land Use 1988 (km2) 1988 % Total Area 1995 (kmz) 1995 % Total Area 2002 (kmz) 2002 % Total Area Forest 47.8 30.9 46.7 30.2 45.8 29.6 Agricultural 91.7 59.2 91.4 59.0 91.3 59.0 Commercial/Transportation 39 2.5 4.3 2.8 4.7 3.1 Residential 4.6 2.9 6.5 4.2 6.9 4.5 None Perceived 5.0 3.2 4.3 2.8 4.2- 2.7 Wildlife/Recreation 1.8 1.2 1.7 1.1 1.7 1.1 Total 154.8 100 154.8 100 154.8 100 The smaller land use categories (commercial/transportation, residential, none perceived and wildlife/recreation) are presented by total area in Figure 4.1.3. 39 Land Use in the Sumas River Watershed 1988 - 2002 1988 1995 2002 • Commercial/Transportation • Residential • None Perceived •Wildlife/Recreation Figure 4.1.3. Summary of land use changes for the Sumas River watershed between 1988 and 2002 based on GIS maps created in ArcView 4.1.3 Population Changes in Abbotsford, B.C. The number of people living in the City of Abbotsford has increased from approximately 90,000 residents in 1991 to nearly 120,000 residents in 2000. This growth is resulting in increasing amounts of residential and commercial land use. The majority of the housing developments are on the Sumas Mountain hill slopes and are large, single family dwellings or townhouses (Figure 4.1.4). 40 5 0 4 0 J 3 0 'E L o n E * 1 0 1991 1 9 9 4 Year 1 9 9 7 2 0 0 0 I Single Family Homes • Townhouses • Apartments Figure 4.1.4 Housing development in Abbotsford B.C. by category (City-of-Abbotsford, 2 0 0 3 ) The types of housing being created to meet the demands of population growth is of specific interest with regards to impervious surface area within the watershed. Apartment buildings are able to house the greatest number of people per area of paved surface, while single-family dwellings house the least number of people per area. The Sumas River may become affected by this urbanization through the re-engineering and contamination of its tributaries. Marshall Creek runs through a commercial area and along the base of Sumas Mountain before entering the Sumas River and may be particularly at risk of the effects of population pressures. 41 4.1.4 Crop Cover in the Canadian Portion of the Sumas River Watershed The land cover results for the 2003-growing season represent a total of 8194 ha of farmed land in the Sumas Prairie alone, and not for the Abbotsford region as a whole. Large homesteads, barn buildings and other large structures were omitted from the total crop area digitized. Figure 4.1.5 presents the top ten crop cover categories as a percent of the total land cover area. Corn, forage and pasture land together make up approximately two thirds of the crop cover in the Sumas Prairie (5490 ha or 67.0%). Turf grass operations covered more area than all of the nursery crops combined. Berries (blueberry, raspberry and strawberry) also made up a significant amount of land under agricultural production (Table 4.1.2). At the time of crop cover data collection (October 1st and 2n d, 2003), 5.8% of the land (470 ha) was sowed with a winter cover crop, however it is not known how many other fields were planted with a winter cover crop after this date. • Com (32.5%) • Forage (28.0%) •Vegetab les (7%) • Pasture (6.5%) • Cole (6.0%) • Winter Cover (5.7%) • Turf (3.6%) • Nursery and Flowers (3.3%) • Berries (3.1%) • Other (1.6%) Figure 4.1.5 Top ten categories of crop cover as a percent of total area in the Sumas Prairie for the 2003 growing season. 42 Table 4.1.2 Categories of crop cover in the Sumas Prairie (2003) ranked by area. Rank# Crop Area (ha) % Total Area 1 Corn 2663 32.5 2 Forage 2293 28.0 3 Pasture 534 6.5 4 Cole 489 6.0 5 Mixed Vegetable 444 5.4 6 Winter Cover 326 4.0 7 Turf 296 3.6 8 Woods and Trees 235 2.9 9 Crop Residue/Winter Cover 144 1.8 10 Blueberry 121 1.5 11 Raspberry 100 1.2 12 Mixed Nursery 93 1.1 13 Sudan Grass 87 1.1 14 Ornamental Nursery 82 1.0 15 Potato 74 0.9 16 Carrot 54 0.7 17 Fruit Nursery 47 0.6 18 Flower 39 0.5 19 Strawberry 35 0.4 20 Marsh 19 0.2 21 Barley 8.6 0.1 22 Perennial Nursery 8.4 0.1 23 Bean 2.1 0.0 24 Other Berry 0.8 0.0 Total 8194 100.0 The 2001 Statistics Canada agricultural census data for the EAs in the Sumas Prairie sub-region was compared to the 2003 crop cover GIS map in order to determine if major changes had occurred during those two years or if any noticeably different conclusions had been reached. Unfortunately the 2001 Census Data was not complete for all of the EAs in the Sumas Prairie. This is mainly due to the fact that Statistics Canada does not release data if there are less than 14 farms in units of land associated 43 with the crops in order to protect anonymity. For this reason the total area for each crop category using the 2001 EA data is often less than the area determined by the 2003 GIS map (Table 4.1.3). It is interesting to note, however, that the ranking order of main crop categories is the same for both data sets. No extreme differences in the data sets were noted. Table 4.1.3 Comparison of area under crops: 2003 crop cover map and 2001 EA census data Crop 2003 GIS Data (ha) 2001 EA Census Data (ha) Total Forage (forage, winter cover, grass, alfalfa) 2831 2807 Total Corn (grain and silage) 2663 1609 Total Vegetables (cole, carrots, potatoes, beans) 1062 1145 Pasture (improved and unimproved) 534 438 Turfgrass/Sod 296 Not Available Total Nursery (perennial, ornamental, mixed) 230 122 Blueberry 121 123 Raspberry 100 24 Fruit Nursery 47 5 Strawberry 35 Not Available Total Area 8194 7584 To complement this comparison, historical Statistics Canada Census data was analyzed to see if any major changes in the types of crops being grown had occurred between 1991 and 2001. It should be noted that this data is not as precise as either the EA data or the GIS crop cover map because it refers to the Abbotsford census region as a whole. However, the majority of agricultural land in the Abbotsford census region is located in the Sumas Prairie. Results indicate that the amount of farmed land increased slightly from 7689 ha to 8124 ha between 1991 and 2001. Trends in pasture, corn, and forage crop production are provided in Figure 4.1.6. Berry and nursery/greenhouse production trends are shown in Figure 4.1.7. 44 3500 3000 2500 $ 2000 | 1500 1000 500 1990 1994 1998 2002 Forage Crops •Pasture Corn Figure 4.1.6 Trends of major crop production in Abbotsford, B.C. census region based on Agricultural Census data (StatsCan, 1991,1996, 2001) 300 0 i 1990 1994 1998 2002 Strawberries • Raspberries —A—Blueberries —•—Nursery and Greenhouses Figure 4.1.7 Trends of minor crop production in Abbotsford, B.C. census region based on Agricultural Census data (StatsCan, 1991,1996, 2001) 45 4.1.5 Changes in Livestock Production in the Abbotsford, B.C., Region The livestock characteristics were determined for the Abbotsford, B.C. census region as a whole, the Abbotsford Aquifer sub-region using Matsqui South EA data, and the Sumas Prairie sub-region using Statistics Canada Agricultural Census data from 1996 and 2001. The livestock characteristics of the Abbotsford region (2001) are presented in Figure 4.1.8. in _ QL — c re _ a re O 70 60 50 4 0 30 2 0 10 0 60,086 1,816,021 19,778 Beef and Dairy Cattle Pigs 2 0 0 0 1800 1600 1400 1200 1000 8 0 0 600 4 0 0 200 0 Poultry Figure 4.1.8 Livestock in the Abbotsford Region, 2001 (StatsCan, 2001) Many changes in livestock production have occurred from 1991 to 2001. Namely, a surge in poultry numbers has characterized the region. The number of pigs in the Abbotsford census region has also increased, which is notable because the number of pigs in the majority of the Lower Fraser Valley census regions have been decreasing. Table 4.1.4 summarizes the changes in livestock numbers and the average number of animals per farm in Abbotsford. 46 Table 4.1.4 Changes in livestock numbers and farm densities in Abbotsford, B.C. census region (StatsCan, 1986; StatsCan, 1991; StatsCan, 1996; StatsCan, 2001). Abbotsford Region 1986 1991 1996 2001 Pigs Pig Farms Average # Pigs per Farm 26,049 24 1,085 38,862 36 1,080 41,429 28 1,480 60,086 26 2,311 Beef and Dairy Cattle Cattle Farms Average # Cattle per Farm 18,318 180 102 18,535 180 103 18,293 161 114 19,778 142 139 Poultry Poultry Farms Average # Poultry per Farm 323,902 46 7,041 488,976 52 9,403 872,075 71 12,283 1,816,021 86 21,117 Data for the EAs that encompass the Sumas Prairie was examined to get a more precise analysis of livestock numbers and trends in the Sumas River watershed. This data is basically a subset of the Abbotsford regional census data, however the number of livestock present in the Sumas Prairie EAs in 2001 represented the majority of poultry and cattle in the Abbotsford census region. Maps of the EA boundaries for both 1996 and 2001 censuses are presented in Appendix B. Detailed census information was not available for the U.S. portion of the watershed and is therefore not presented here. However, based on field excursions, the headwaters of the Sumas River can be characterized as being surrounded by several large dairy operations. It should be noted that the numbers presented are likely to be an underestimation because Statistics Canada will not release census data if there are less than 14 farms within the EA in order to protect anonymity. Table 4.1.5 summarizes the main changes that occurred in the Sumas Prairie sub-region between 1996 and 2001. 47 Table 4.1.5 Changes in livestock numbers and farm densities in the Sumas Prairie sub-region (StatsCan, 1996; StatsCan, 2001). Sumas Prairie Region 1996 2001 Pigs Pig Farms Average # Pigs per Farm 41,423 27 1,534 34,557 23 1,502 Beef Cattle Beef Farms Average # Beef per Farm 8,679 56 155 8,952 38 236 Dairy Cattle Dairy Farms Average # Dairy per Farm 9,414 100 94 10,052 91 110 Poultry Poultry Farms Average # Poultry per Farm 712,368 56 12,721 1,432,034 66 21,697 Data for the Abbotsford Aquifer was analyzed by examining the Agricultural Census data of the Matsqui South region, which encompasses the Abbotsford Aquifer. The number of animals being raised on land over the Abbotsford Aquifer is of interest due to the influence of this groundwater on Marshall Creek, a tributary of the Sumas River. Table 4.1.6 summarized the changes in agricultural operations since 1991. Table 4.1.6 Changes in livestock numbers and farm densities in the Abbotsford Aquifer sub-region (StatsCan, 1991; StatsCan, 1996; StatsCan, 2001). Abbotsford Aquifer Region 1991 1996 2001 Pigs 6,015 5,807 6,134 Pig Farms 11 12 7 Average # Pigs per Farm 547 484 876 Beef and Dairy Cattle 2,196 1,957 1,334 Cattle Farms 102 94 46 Average # Cattle per Farm 22 21 29 Poultry 2,724,660 2,709,513 3,176,719 Poultry Farms 129 139 116 Average # Poultry per Farm 21,121 19,493 27,386 48 4.1.6 Animal Unit Equivalent (AUE) Densities The Lower Fraser Valley has the highest density of livestock within Canada (Table 4.1.7) (Beaulieu, 2001). This is a direct consequence of the relatively small amount of land available for agricultural production in this region. For instance, although Lethbridge County, Alberta, has higher numbers of livestock, the amount of land available per animal is also greater, which results in a lower livestock density. The animal unit equivalent (AUE) per area of land is therefore a good indicator of the intensity of agricultural production within a region, as was suggested in the hierarchy presented in Figure 1.3.1. Table 4.1.7 Canadian Regions with highest livestock density in 2001 (Beaulieu, 2001). Total Animal Units Per km 2 Rank Province Region Animal Units 1991 2001 Difference 1 B.C. Fraser Valley 177,500 304 365 +61 2 B.C. Greater Vancouver 71,500 179 183 +4 3 Quebec La Nouvelle-Beauce 80,800 162 157 -5 4 Nova Scotia Digby County 7,300 77 145 +68 5 Alberta Lethbridge County 427,000 62 143 +81 The AUE density data for the Sumas River watershed region was compiled using Statistics Canada 1996 and 2001 agricultural census data as well as the OMAF Nutrient Calculator (2002). There were four EAs representing the Sumas Prairie sub-region and one EA representing the Abbotsford Aquifer subregion. Maps of the EA boundaries for both 1996 and 2001 are presented in Appendix B. The geographic boundaries of the Sumas Prairie EAs were modified somewhat by Statistics Canada between the 1996 and 2001 censuses. Therefore, in order to make comparisons of livestock changes over time, AUEs were calculated for every EA within the Sumas Prairie and averaged for both 1996 and 2001. The AUE results for individual EAs and regions are presented in 49 Tables 4.1.8 and 4.1.9. The EAs are listed in order of similar geographic areas in 1996 and 2001. Table 4.1.8 Animal unit equivalents per ha by EA in the Sumas Prairie. E A # A U E s Hectares A U E s / h a 1996-59007201 4949 1121 4.41 1996-59007118 6015 1662 3.62 1996-59007117 6923 2913 2.38 1996-59007116 5980 1317 4.54 Total 23867 7013 3.40 2001-59006207 5709 1179 4.84 2001-59006210 7176 1960 3.66 2001-59006208 8418 2578 3.27 2001-59006209 5400 1867 2.89 Total 26703 7584 3.52 Table 4.1.9 Average animal unit equivalents for the Abbotsford Aquifer (Matsqui South) and Sumas Prairie sub-regions. Year Region A U E s A U E s / h a 1996 Abbotsford Aquifer 387 2.13 2001 Abbotsford Aquifer 1,651 6.45 1996 Sumas Prairie 23,867 3.40 2001 Sumas Prairie 26,703 3.52 According to Beaulieu (2001), livestock density in Canada can be broken down into the following categories: Low Density: < 0.03 AUEs/ha Medium Density: between 0.03 and 0.80 AUEs/ha High Density: > 0.80 AUEs/ha Several European countries including Denmark and Germany consider farms to be intensive if the density levels exceed 2.0-2.5 AUEs/ha (OMAF, 2003). Based on these classification systems the Abbotsford Aquifer (Matsqui South) and Sumas Prairie 50 sub-regions are characterized as having high livestock densities for both 1996 and 2001 census years. 4.1.7 Nutrient Budgets by Enumeration Area in the Sumas Prairie Nutrient budget results are summarized in Table 4.1.10. According to Brisbin (1995), surplus N levels of 50-100 kg/ha are considered normal. Many of the EAs in the Sumas Prairie had high (>200 kg/ha) surpluses of N and K and as well high (>50 kg/ha) surpluses of P both in 1996 and in 2001. None of the EAs had any nutrient deficits for either 1996 or 2001. EA boundary maps are provided in Appendix B. Table 4.1.10 Nutrient surpluses by enumeration area (EA) in the Sumas Prairie. Year E A # N P K surplus kg/cropped hectare 1996 96-59007116 319 73 214 1996 96-59007117 169 57 159 1996 96-59007118 278 69 285 1996 96-59007201 340 81 267 2001 01-59006207 389 78 161 2001 01-59006208 197 53 162 2001 01-59006209 219 49 78 2001 01-59006210 238 64 119 4.2 Water Quality Results Quality Analysis and Quality Control (QA/QC) The QA/QC results (see Appendix C) did not indicate any large deviations between duplicate or triplicate samples. Ammonia consistently had the largest coefficient of variation (CV) between triplicates, which is expected because of it's relatively high volatility. Dissolved Fe also occasionally had a CV larger than 10%. However, none of the results showed deviations large enough to require omitting any of the parameters from further analysis. 51 4.2.1 Spatial and Seasonal Variations in Water Quality Chloride (Cl): Spatial and Seasonal Trends The concentration of chloride (Cl") in the watershed ranged from <6.0 to 38.8 mg/L, with a median of 15.4 mg/L. For the majority of the sites the higher values occurred during the summer months when runoff was lowest (see boxplots in Appendix C). The high values in the wet winter months at Marshall Creek are likely related to that tributary's influence from the Abbotsford Aquifer. The Cl" levels in the Sumas River from the headwaters to downstream direction, as well as the tributaries for both wet and dry seasons are summarized in Figure 4.2.1a. Table 4.2.1a Significant Mann-Whitney results (a<0.01) for Cl" by site. Tributaries cr (mg/L) levels < or > In compar ison to Data Set Marshall Creek > All other tributaries except: Arnold Slough Seasons combined Vedder Mountain < All other tributaries Seasons combined Arnold Slough > Sumas Canal Saar Creek Seasons combined Sumas Mountain < All other tributaries except: Vedder Mountain Swift Creek Saar Creek Seasons combined Sumas River (border area) > Arnold Slough Sumas Canal Sumas Mountain Vedder Mountain Dry season Vedder Mountain < All other tributaries except: Sumas Mountain Dry season Saar Creek Sumas Mountain Vedder Mountain < Sumas River (all regions) Sumas Canal Arnold Slough Wet season Swift Creek < Sumas River (border area) Wet season 52 Chloride in Ma ins tern and Tributaries 16 2 18 3 4 12 6 7 Station #IDs (Direction: Headwaters to Mouth of the Sumas River (not to scale)) Legend: SW: Swift Creek, SA: Saar Creek, AS: Arnold Slough, MC: Marshall Creek, SC: Sumas Canal, SM: Sumas Mountain, RF: Reference Site Triangles represent Dry Season medians and squares represent Wet Season medians. Bars represent 25th and 75th quartiles. 1 14 10 11 13 5 9 8 15 19 Station #IDs (Direction: Headwaters to Mouth of the Sumas River (not to scale)) Figure 4.2.1a Cl (mg/L): Wet and dry season trends in the Sumas River watershed by sampling station. 53 Nitrate (N03"-N): Spatial and Seasonal Trends The concentration of NGV-N in the watershed ranged from <0.10 to 9.85 mg/L with a median of 1.56 mg/L. There was a very distinct seasonal variation in N03"-N levels for all of the sites. The highest concentration (9.85 mg/L) was measured in Marshall Creek (site #13) in August 2003. This site is highly influenced by the Abbotsford Aquifer and, unlike other sites, had the highest levels of NCV-N during the summer months when the aquifer was proportionally contributing the most water to the creek. Both sites along Marshall Creek (sites #13 and #5) consistently had high levels of N03"-N throughout the year; the lowest concentration at these sites was 2.55 mg/L at site #5 in November 2003. Figure 4.2.1b summarizes the NCV-N levels in the Sumas River from the headwaters to downstream direction, as well as the tributaries for both wet and dry seasons. Table 4.2.1b Significant Mann-Whitney results (a<0.01) for N0 3"-N by site. Tributaries N O 3 - N (mg/L) levels < o r > In compar ison to Data Set Marshall Creek > All other tributaries Seasons combined Sumas River (border and downstream) > All other tributaries except: Marshall Creek Seasons combined Sumas River (headwaters) > Swift Creek Sumas Mountain Vedder Mountain Seasons combined Sumas River (border and downstream) > All other tributaries (Marshall Creek not included) Dry season Swift Creek Vedder Mountain < All other tributaries Wet season Saar Creek Sumas River (headwaters) Sumas Mountain < Arnold Slough Sumas Canal Sumas River (border and downstream areas) Wet season 54 Nitrate in Mainstem and Tributaries 16 2 18 3 4 12 6 7 Station #IDs (Direction: Headwaters to Mouth of the S u m a s River (not to scale)) Legend: SW: Swift Creek, SA Saar Creek, AS: Arnold Slough, MC: Marshall Creek, SC: Sumas Canal SM: Sumas Mountain, RF: Reference Site Triangles represent Dry Season medians and squares represent Wet Season medians. Bars represent 25th and 75th quartiles. Grey lines are 1994 and 1995 data for comparison. 8 i 1 14 10 11 13 5 9 8 15 19 Station #IDs (Direction: Headwaters to Mouth of the S u m a s River (not to scale)) Figure 4.2.1b N0 3"-N (mg/L): Wet and dry season trends in the Sumas River watershed by sampling station. 55 Total Ammonium (NH 4 +-N): Spatial and Seasonal Trends The concentration of NH 4 +-N in the watershed ranged from <0.10 mg/L to 9.96 mg/L and the median was 0.20 mg/L. The highest level (9.96 mg/L) was measured at site #5 in Marshall Creek in February 2004 and the second-highest level (5.10 mg/L) was measured at the same site in March 2004. The high results found on these two sampling dates appear to be localized to site #5. The third highest NH 4 +-N level was 2.20 mg/L measured in Arnold Slough (site #10) in October 2003. These highest levels were not included on the seasonal trend graphs because they were extreme outliers. The lowest levels of NH4 +-N were consistently found in tributaries associated with minimal or no agricultural activities (Sumas River headwaters, Swift Creek, Sumas Mountain, and Vedder Mountain reference site). These sites often had levels of NH 4 +-N below the laboratory detection limit of 0.10 mg/L. Figure 4.2.1c summarizes the NH 4 +-N levels in the Sumas River from the headwaters to downstream direction, as well as the tributaries for both wet and dry seasons. Table 4.2.1c Significant Mann-Whitney results (a<0.01) for NH 4 +-N by site. Tributaries NH/ -N (mg/L) levels < or > In comparison to Data Set Vedder Mountain < All tributaries except: Sumas River (headwaters) Swift Creek Sumas Mountain Seasons combined Arnold Slough > Marshall Creek Sumas River (all regions) Seasons combined Arnold Slough Sumas Canal Saar Creek > Sumas River (headwater region) Swift Creek Vedder Mountain Dry season Sumas Canal > All other tributaries Wet season Arnold Slough Sumas River (downstream area) > Sumas Mountain Vedder Mountain Wet season 56 Ammonium in Mainstem and Tributaries 16 2 18 3 4 12 6 7 Station #IDs (Direction: Headwaters to Mouth of the Sumas River (not to scale)) Legend: SW: Swift Creek, SA Saar Creek, AS: Arnold Slough, MC: Marshall Creek, SC: Sumas Canal, SM: Sumas Mountain, RF: Reference Site Triangles represent Dry Season medians and squares represent Wet Season medians. Bars represent 25th and 75th quartiles. 1.6 1.2 d0.8 O) E z +' £0.4 0.0 1 k MC SC 1 SA i 1 SW i ' i AS S M RF L i 1 1 14 10 11 13 5 9 8 1 15 19 Station #IDs (Direction: Headwaters to Mouth of the Sumas River (not to scale)) Figure 4.2.1c NH 4 +-N (mg/L): Wet and dry season trends in the Sumas River watershed by sampling station. Note: Three extreme outliers: MC (site 5) 9.96 mg/L and 5.10 mg/L and AS (site 10) 2.20 mg/L. 57 Orthophosphate (P0 4): Spatial and Seasonal Trends For the majority of sites orthophosphate (P04) levels remained at or below the detection limit (0.02 mg/L). The amount of P 0 4 ranged from <0.02 mg/L to 0.30 mg/L with a median of 0.02 mg/L. The high value of 0.30 mg/L was found in Marshall Creek (site #5) in March 2004. For many sites, the November 2003 sampling produced some of the highest P 0 4 values. Levels at Vedder Mountain reference site (#19) were never detected above 0.02 mg/L. Figure 4.2.1 d summarizes the P 0 4 levels in the Sumas River from the headwaters to downstream direction, as well as the tributaries for both wet and dry seasons. Table 4.2.1d Significant Mann-Whitney results (a<0.01) for P04 by site. Tributaries P 0 4 (mg/L) levels < o r > In comparison to Data Set Sumas River (all regions) > Swift Creek Vedder Mountain Sumas Mountain Seasons combined Vedder Mountain < Saar Creek Marshall Creek Arnold Slough Seasons combined Sumas Canal < Sumas River (border and downstream areas) Seasons combined Sumas River (border region) > Arnold Slough Marshall Creek Seasons combined Sumas River (headwaters and border regions) > Vedder Mountain Dry season Sumas River (all regions) Arnold Slough > Sumas Mountain Vedder Mountain Wet season Sumas River (border and downstream regions) > Swift Creek Sumas Canal Wet season 58 Orthophosphate in Mainstem and Tributaries 16 2 18 3 4 12 6 7 Station #IDs (Direction: Headwaters to Mouth of the Sumas River (not to scale)) Legend: SW: Swift Creek, SA: Saar Creek, AS: Arnold Slough, MC: Marshall Creek, SC: Sumas Canal, SM: Sumas Mountain, RF: Reference Site Triangles represent Dry Season medians and squares represent Wet Season medians. Bars represent 25th and 75th quartiles. 0 . 1 0 1 14 10 11 13 5 9 8 15 19 1 8 Station #IDs (Direction: Headwaters to Mouth of the S u m a s River (not to scale)) Figure 4.2.1d P04 (mg/L): Wet and dry season trends in the Sumas River watershed by sampling station. 59 Dissolved Oxygen (DO): Spatial and Seasonal Trends The levels of DO ranged from 1.3 to 14.3 mg/L with a median of 8.4 mg/L. The lowest levels were found during the dry summer months in Arnold Slough and Saar Creek while the highest levels were found year-round in Swift Creek and at the Vedder Mountain reference site. Seasonal trends are somewhat apparent in the boxplots by date (see Appendix C), however, graphs of medians in the downstream direction for the wet and dry seasons display minimal seasonal trends for the Sumas River mainstem and most tributaries (Figure 4.2.1 e). Exceptions are Marshall Creek, which exhibited higher DO levels in the dry season (likely due to the influence of the Abbotsford Aquifer) and Sumas Canal, which had higher DO levels in the wet season. It is worthy to note that the headwaters of the Sumas River (site #16) had low DO levels during both wet and dry seasons. Due to equipment problems, DO was only measured on four occasions during the wet season. As a result, significance levels for many of the pair-wise comparisons was greater than 0.01 (a) even though medians were often very different from one another. Table 4.2.1e Significant Mann-Whitney results (ct<0.01) for DO by site. Tributaries DO (mg/L) levels < o r > In comparison to Data Set Arnold Slough < All other tributaries except: Saar Creek Seasons combined Vedder Mountain > Sumas Canal Marshall Creek Arnold Slough Sumas River (all regions) Seasons combined Arnold Slough < Vedder Mountain Sumas River (border and downstream areas) Dry season Arnold Slough < Sumas Canal Sumas River (all regions) Wet season 60 Dissolved Oxygen in Mainstem and Tributaries AS 16 2 18 3 4 12 6 7 Station #IDs (Direction: Headwaters to Mouth of the Sumas River (not to scale)) Legend: S W : Swift Creek, SA : Saar Creek, A S : Arnold Slough, M C : Marshall Creek, S C : Sumas Cana l , S M : Sumas Mountain, R F : Reference Site Triangles represent Dry Season medians and squares represent Wet Season medians. Bars represent 25th and 75th quartiles. 14 12 10 i s E, O 6 Q 4 2 SW f "SA" ^ 4 RF-"SM" "AS" 1 14 10 11 13 5 9 8 15 19 Station #IDs (Direction: Headwaters to Mouth of the Sumas River (not to scale)) Figure 4.2.1e DO (mg/L): Wet and dry season trends in the Sumas River watershed by sampling station. 61 Dissolved Organic Carbon (DOC): Spatial and Seasonal Trends Dissolved organic carbon (DOC) ranged from 0.8 to 15.9 mg/L with a median of 3.9 mg/L. The highest concentration was measured on Sumas Mountain (site #15) in August 2003. The lowest values were consistently measured in Swift Creek (site #1), Vedder Mountain reference (site #19) and site #13 in Marshall Creek. Interestingly, the seasonal patterns of DOC closely resembled the N03"-N results along the Sumas River. Due to an unavailability of equipment, no DOC samples were taken in December 2003, which reduced the sample size to n=4 during the wet season for Swift Creek, Saar Creek, Sumas Mountain and Vedder Mountain. This may account for a lack of significant differences between sites for wet season DOC data even though medians between sites were often quite different. Figure 4.2.1f summarizes the DOC levels in the Sumas River from the headwaters to downstream direction, as well as the tributaries for both wet and dry seasons. Table 4.2.1f Significant Mann-Whitney results (a<0.01) for DOC by site. Tributaries D O C (mg/L) levels < o r > In compar ison to Data Set Swift Creek Vedder Mountain < All other tributaries Seasons combined and dry season separately Marshall Creek < Sumas Mountain Arnold Slough Sumas River (downstream area) Seasons combined Sumas Canal < Arnold Slough Sumas Mountain Seasons combined Sumas Mountain > Sumas River (all regions) Dry season Arnold Slough > Sumas Canal Sumas River (headwaters) Dry season Sumas Canal > Arnold Slough Sumas River (border and downstream areas) Wet season 62 Dissolved Organic Carbon in Mainstem and Tributar ies Legend: SW: Swift Creek, SA: Saar Creek, AS: Arnold Slough, MC: Marshall Creek, SC: Sumas Canal, SM: Sumas Mountain, RF: Reference Site Triangles represent Dry Season medians and squares represent Wet Season medians. Bars represent 25th and 75th quartiles. 19 Figure 4.2.1f DOC (mg/L): Wet and dry season trends in the Sumas River watershed by sampling station. 63 pH: Spatial and Seasonal Trends The pH values ranged from 6.3 to 8.8 with a median of 7.2 throughout the year. The highest pH values were found in Swift Creek where the median was 7.8. The likely source of the high pH at this site is the natural asbestos landslide originating in the headwaters of the Swift Creek. In general, higher pH values were detected in the dry season in Arnold Slough, Marshall Creek, Sumas Canal, and the downstream region of the Sumas River. This seasonal difference may be partly due to photosynthetic activity, which is higher during the warmer summer months and will increase pH levels. Boxplots (see Appendix C) indicate that the lowest pH values occurred at most sites in late October 2003, which was shortly after a large rainstorm. Therefore, runoff is the likely reason for a decreased pH throughout the majority of the watershed on that date. Figure 4.2.1g summarizes the pH levels in the Sumas River watershed. Table 4.2.1g Significant Mann-Whitney results (a<0.01) for pH by site. Tributaries PH < or > In comparison to Data Set Swift Creek > All tributaries except: Vedder Mountain Seasons combined Vedder Mountain > All tributaries except: Swift Creek Sumas River (border area) Seasons combined Arnold Slough < All tributaries except: Sumas Mountain Saar Creek Seasons combined Swift Creek > All tributaries Dry season Sumas River (border and downstream areas) > All tributaries except: Swift Creek Vedder Mountain Dry season Sumas River (border area) > Arnold Slough Wet season Swift Creek > Sumas River (border and downstream areas) Arnold Slough Sumas Canal Wet season Vedder Mountain > Arnold Slough Sumas Canal Sumas River (downstream area) Wet season 64 pH in Mainstem and Tributaries Legend: SW: Swift Creek, SA: Saar Creek, AS: Arnold Slough, MC: Marshall Creek, SC: Sumas Canal, SM: Sumas Mountain, RF: Reference Site Triangles represent Dry Season medians and squares represent Wet Season medians. Bars represent 25th and 75th quartiles. 1 14 10 11 13 5 9 8 15 19 Station #IDs (Direction: Headwaters to Mouth of the Sumas River (not to scale)) Figure 4.2.1g pH: Wet and dry season trends in the Sumas River watershed by sampling station. 65 Temperature (°C): Spatial and Seasonal Trends Temperature ranged from 2.4 to 23.9°C and had a median of 10.1 °C throughout the watershed. The highest temperatures were recorded during the dry season in the downstream region of the Sumas River and in the Sumas Canal and the lowest temperatures were recorded in the wet season at the Vedder Mountain and Sumas Mountain sites. Marshall Creek, which is influenced by the Abbotsford Aquifer, has the most moderated temperature regime. It was one of the coolest tributaries during the summer and one of the warmest in the winter. Kruskal-Wallis test results (a=0.05) did not indicate a significant difference between any of the sites for temperature. Upon further pair-wise analysis using Mann-Whitney tests it was determined that the only significant difference between sites was that the Sumas Canal had a higher temperature than the border area of the Sumas River during the dry season. Figure 4.2.1 h summarizes the temperature levels in the Sumas River from the headwaters to downstream direction, as well as the tributaries for both wet and dry seasons. 66 Temperature in Mainstem and Tributaries 20 15 o o "10 £ 3 2 E & s w r ] [I 1 I L—— • . 1 , 1 1 , — 16 2 18 3 4 12 6 7 Station #IDs (Direction: Headwaters to Mouth of the Sumas River (not to scale)) Legend: SW: Swift Creek, SA: Saa r Creek, A S : Arnold S lough, MC: Marshal l Creek, S C : S u m a s C a n a l , S M : S u m a s Mountain, R F : Reference Site Tr iangles represent Dry S e a s o n med ians and squares represent Wet S e a s o n med ians . Bars represent 25th and 75th quarti les. 20 15 O o "a 10 3 4-1 2 0) Q . E 5 0) MC i u ^ \ ^ i T SW J SA • L AS SM A 0 1 14 10 11 13 5 9 8 15 19 Station #IDs (Direction: Headwaters to Mouth of the Sumas River (not to scale)) Figure 4.2.1h Temperature (°C) Wet and dry season trends in the Sumas River watershed by sampling station. 67 Specific Conductivity: Spatial and Seasonal Trends Specific conductivity ranged from 70.2 to 445.0 u,S/cm with a median value of 263.3 uS/cm. The highest values were found at site #5 (Marshall Creek) and in the border area of the Sumas River. The lowest values were found at the Vedder Mountain reference site, Sumas Mountain, Swift Creek, and Saar Creek. Figure 4.2.1 i summarizes the specific conductivity levels in the Sumas River from the headwaters to downstream direction, as well as the tributaries for both wet and dry seasons. Samples collected in 1994 and 1995 by Berka (1996) displayed a much stronger seasonal variation for the Sumas River and the tributaries. This may be due to somewhat different precipitation patterns and river flows during the sampling periods. Table 4.2.1 h Significant Mann-Whitney results (a<0.01) for specific conductivity by site. Tributaries Specif ic Conductivity (uS/cm) levels < or > In comparison to Data Set Sumas Mountain Vedder Mountain < Marshall Creek Arnold Slough Sumas Canal Sumas River (all regions) Seasons combined Swift Creek Saar Creek < Arnold Slough Sumas Canal Sumas River (all regions) Seasons combined Sumas River (border area) > All tributaries except: Arnold Slough Marshall Creek Seasons combined Saar Creek Vedder Mountain < Arnold Slough Sumas River (all regions) Dry season Swift Creek Sumas Mountain < Arnold Slough Sumas River (border area) Dry season Sumas Canal < Sumas River (border area) Dry season Swift Creek Saar Creek Sumas Mountain Vedder Mountain < Arnold Slough Sumas Canal Sumas River (all regions) Wet season 68 Legend: SW: Swift Creek, SA: Saar Creek, AS: Arnold Slough, MC: Marshall Creek, SC: Sumas Canal, SM: Sumas Mountain, RF: Reference Site Triangles represent Dry Season medians and squares represent Wet Season medians. Bars represent 25th and 75th quartiles. 1 14 10 11 13 5 9 8 15 19 Station #IDs (Direction: Headwaters to Mouth of the Sumas River (not to scalen Figure 4.2.1 i Specific conductivity (uS/cm): Wet and dry season trends in the Sumas River watershed by sampling station. 69 4.2.2 Long-Term Trends in Nutrients and Dissolved Oxygen (1994 to 2004) Chloride (Cl)Temporal Trends Based on scatter plots to compare the two data sets (1994/95 to 2003/04), increases in Cl" results in Marshall Creek are noted during both the wet and dry seasons. The Sumas River headwaters and downstream areas experienced an increase in levels of Cl" since 1994 during the dry season only. Interestingly, Cl" levels in Saar Creek have decreased since 1994 for both wet and dry seasons. The Vedder Mountain reference site was excluded from this part of the analysis because it had not been sampled in 1994/95. Other sites have not experienced notable trends. Figure 4.2.2 presents the significant Cl" trends for both dry and wet seasons and Table 4.2.2 summarizes the R 2 values. There is more variability within the wet season data set, which is likely due to greater variations in precipitation and discharge than during the dry season. Table 4.2.2 Summary of R 2 values for significant changes in Cl" levels from 1994-2004. Region Wet Season Dry Season Sumas River (headwaters) <0.10 0.30 Sumas River (downstream) <0.10 0.26 Saar Creek 0.33 0.23 Marshall Creek 0.40 0.41 70 Dry Season Chloride Results 27/11/1993 05/02/1996 15/04/1998 23/06/2000 01/09/2002 09/11/2004 • Sumas River headwaters A Saar Creek - - Linear (Saar Creek) - - Linear (Sumas River headwaters) • Sumas River downstream O Marshall Creek Linear (Marshall Creek) Linear (Sumas River downstream) 11/05/1993 20/07/1995 27/09/1997 06/12/1999 13/02/2002 23/04/2004 • Marshall Creek - - - Linear (Marshall Creek) O Saar Creek Linear (Saar Creek) Figure 4.2.2 Dry and wet season differences in Cl" between 1993 and 2004. 71 Nitrate (N03"-N) Temporal Trends Scatter plots with trendlines were created for each river or tributary, for both the dry and wet seasons. Figures 4.2.3 and 4.2.4 present the significant differences for both dry and wet seasons (Sumas River regions and tributaries separately) and Table 4.2.3 summarizes the R 2 values. Some of the variability within the seasonal data sets may be attributed to variations in precipitation and river discharge. The data from 2003/04 collected along the mainstream of the Sumas River was added to a scatterplot (Figure 4.2.5) originally produced by Berka (1996) which includes data compiled from several sources since the 1970s (Benedict et al., 1973; ESL and Webb, 1987; Hall et al., 1974; Schreier, 1986; Schreier, 1987). The graph shows increasing N03'-N levels over the long term in the Sumas River. Long-term N03"-N trends were of particular interest because it is a good indicator of agricultural pollution. The Vedder Mountain reference site was excluded from this part of the analysis because it had not been sampled in 1994/95. Table 4.2.3 Summary of R 2 values for significant changes in N0 3"-N levels from 1994-2004. Region Wet Season Dry Season Sumas River (headwaters) 0.50 <0.10 Sumas River (border area) 0.72 0.63 Sumas River (downstream) <0.10 0.47 Arnold Slough 0.23 <0.10 Sumas Canal 0.78 0.40 Saar Creek 0.70 <0.10 Marshall Creek <0.10 0.12 Sumas Mountain 0.57 <0.10 72 Dry Season Nitrate Results 05 £ 27/11/1993 05/02/1996 15/04/1998 23/06/2000 01/09/2002 09/11/2004 • Sumas River downstream A Sumas River border O Sumas Canal • Marshall Creek — —Linear (Sumas River downstream) Linear (Sumas River border) — - Linear (Marshall Creek) Wet Season Nitrate Results (Tributaries) E 0 J • T » , , 11/05/1993 20/07/1995 27/09/1997 06/12/1999 13/02/2002 23/04/2004 O Sumas Canal • Saar Creek O Arnold Slough • Sumas Mountain - - - Linear (Arnold Slough) Linear (Sumas Canal) — - Linear (Sumas Mountain) Figure 4.2.3 Dry and wet season differences in N03"-N between 1993 and 2004. 73 6 5 Wet Season Nitrate Results (Sumas River) A A A A A ti A O _. A A <*> O 11/05/1993 20/07/1995 27/09/1997 06/12/1999 13/02/2002 23/04/2004 A Sumas River border O Sumas River headwaters - - - Linear (Sumas River headwaters) Figure 4.2.4 Wet season differences in N0 3"-N between 1993 and 2004 in Sumas River sites. Rates of Change and Significance of N0 3"-N Trends Results from the Wilcoxon Signed Rank test (a=0.05) indicate that the Sumas River has significantly higher levels of NCV-N in every main region (headwaters, border area, and downstream) for both dry and wet seasons in 2003/04 compared to 1994/95. Levels of NCV-N have significantly increased in Arnold Slough and Sumas Canal during the wet season and in Marshall Creek during the dry season. Increases for Saar Creek were noted on the wet season scatter plot (R2=0.70) but were not significant. The rate of NCV-N increase in Marshall Creek during the dry season is comparable to the rate of NCV-N increase during the wet season in the downstream region of the Sumas River and in Arnold Slough. The border region of the Sumas River and the Sumas Canal have higher rates of increase than Marshall Creek. 74 75 Ammonium (NH 4 +-N) Temporal Trends The results from 2003/04 differ somewhat from the concentrations measured in 1994 and 1995 by Berka (1996). Scatter plots of NH4 +-N data for 1994/95 and 2003/04 are presented in Figures 4.2.6 and 4.2.7 to better visualize these trends. Table 4.2.4 summarizes the R 2 values of the scatter plots. Some of the variability within the seasonal data sets may be attributed to variations in precipitation and river discharge throughout the sampling period. Table 4.2.4 Summary of R 2 values for significant changes in NH 4 +-N levels from 1994-2004. Region Wet Season Dry Season Sumas River (downstream) <0.10 0.15 Arnold Slough 0.34 <0.10 Sumas Canal 0.46 0.18 Saar Creek 0.18 0.23 Marshall Creek <0.10 0.12 0.0 27/11/1993 Dry Season Ammonium Results 05/02/1996 15/04/1998 23/06/2000 01/09/2002 09/11/2004 • Sumas River downstream O Sumas Canal - - Linear (Saar Creek) Linear (Sumas Canal) A Saar Creek • Marshall Creek Linear (Sumas River downstream) — —Linear (Marshall Creek) Figure 4.2.6 Dry season NH 4 +-N changes in the Sumas River watershed. 76 Wet Season Ammonium Results 11/05/1993 20/07/1995 27/09/1997 06/12/1999 13/02/2002 23/04/2004 • A Saar Creek Sumas Canal •Linear (Arnold Slough) • Arnold Slough - - Linear (Saar Creek) — Linear (Sumas Canal) Figure 4.2.7 Wet season NH4+-N changes in the Sumas River watershed. Orthophosphate (P04) Temporal Trends When comparing the data sets, the majority of sites showed a decrease in P0 4 concentrations for both wet and dry seasons from 1994 to 2004. However, due to the fact that a majority of samples were measured at or below detection limit (0.02 mg/L), it is difficult to make any conclusions about these declining trends. Dissolved Oxygen (DO) Temporal Trends DO levels have decreased in the Sumas River border and downstream areas and at the Sumas Mountain site during the wet season (Figure 4.2.8). However, there 77 were no significant increasing or decreasing trends at any sites during the dry season. The R2 values are summarized in Table 4.2.5. Table 4.2.5 Summary of R 2 values for significant changes in DO levels from 1994-2004. Region Wet Season Dry Season Sumas River (border area) 0.21 <0.10 Sumas River (downstream) 0.31 <0.10 Sumas Mountain 0.25 O.10 11/05/1993 20/07/1995 27/09/1997 06/12/1999 13/02/2002 23/04/2004 • Sumas River border area A Sumas Mountain ^—Linear (Sumas Mountain) • Sumas River downstream area - - - Linear (Sumas River downstream area) — - Linear (Sumas River border area) Figure 4.2.8 Temporal DO trends in the Sumas River watershed. 78 4.2.3 Dissolved Elements in Water Results The following dissolved elements were of interest with regards to either geological or anthropological influences on water quality (detection limits in ppm given in brackets): aluminum (0.05), arsenic (0.20), calcium (0.10), cadmium (0.025), cobalt (0.055), chromium (0.025), copper (0.05), iron (0.05), potassium (0.50), magnesium (0.01), manganese (0.005), sodium (0.025), nickel (0.10), phosphorus (0.20), lead (0.20), silicon (0.15), and zinc (0.01). However, dissolved As, Cd, Co, Cr, Cu, Ni, and Pb were found to be below their respective detection limits in water samples at all sites on all sampling occasions. Dissolved Zn was consistently found at or below detection limit (0.01 ppm) except in October 2003 at Marshall Creek (0.05 ppm) and in June 2004 at Marshall Creek (0.02 ppm), Sumas River headwaters (0.02 ppm), Sumas Mountain (0.02 ppm), and Vedder Mountain (0.04 ppm). It is worth noting, however that the detection limit of 0.01 ppm for dissolved Zn is fairly high. Additionally, dissolved P was only found above detection limit in Marshall Creek in November 2003 and March 2004. Dissolved Al was found at or below detection limit (0.05 ppm) at most sites on the majority of sampling dates. Exceptions occurred during the wet season and are listed in Table 4.2.6. Table 4.2.6 Occasions when dissolved Al was above detection limit of 0.05 ppm. Tributary Date Al (ppm) Arnold Slough 30/10/03 0.13 24/11/03 0.14 10/12/03 0.08 12/01/04 0.13 02/02/04 0.10 Marshall Creek (site #5 only) 24/11/03 0.11 12/01/04 0.16 02/02/04 0.07 01/03/04 0.06 Saar Creek 14/10/03 0.12 30/10/03 0.08 24/11/03 0.27 10/12/03 0.10 79 Saar Creek (continued) 12/01/04 0.33 02/02/04 0.10 22/03/04 0.07 Sumas River headwaters 12/01/04 0.13 Sumas River border area 24/11/03 0.08 12/01/04 0.18 02/02/04 0.06 Sumas River downstream 14/10/03 0.07 30/10/03 0.06 24/11/03 0.10 12/01/04 0.21 02/02/04 0.09 Swift Creek 30/10/03 0.08 12/01/04 0.34 Vedder Mountain 24/11/03 0.09 12/01/04 0.09 Therefore, due to a lack of data, dissolved Al, As, Cd, Co, Cr, Cu, P, Ni, Pb and Zn were omitted from further statistical analysis. In August 2004, extremely high levels of Fe and Mn were detected at Sumas Mountain site #15 (16.1 and 8.1 ppm respectively). These values were at least one order of magnitude higher than the next highest values for those elements at that site. Therefore, this sample was considered an extreme outlier and was omitted from further statistical analysis. The descriptive data for the remaining dataset is provided in Table 4.2.7 and boxplots are in Appendix C. Table 4.2.7 Descriptive data for dissolved ions in water. C a Fe K Mg Mn Na Si ppm ppm ppm ppm ppm ppm ppm Median 17.1 0.40 2.3 16.6 0.053 8.5 9.2 Minimum 4.4 <0.05 <0.5 2.3 <0.005 1.4 2.9 Maximum 34.9 2.79 7.4 31.6 1.102 24.9 20.7 Percentiles 25 13.5 0.15 1.3 11.4 0.019 6.9 7.3 50 17.1 0.40 2.3 16.6 0.053 8.5 9.2 75 20.6 0.64 3.3 20.4 0.104 10.2 10.5 Dissolved Calcium (Ca): Spatial and Seasonal Trends The highest levels of Ca were found in Marshall Creek, while the lowest levels were found in Swift Creek. Higher Ca levels were present during the dry season. 80 Table 4.2.8a Significant Mann-Whitney results (a<0.01) for dissolved Ca by site. Tributary C a (ppm) < o r > In compar ison to Data Set Marshall Creek > All other tributaries Seasons combined Saar Creek and Swift Creek < All other tributaries except Vedder Mountain Seasons combined Sumas Canal, Sumas River (border and downstream areas) > Swift Creek, Arnold Slough, Saar Creek Dry season Sumas Canal, Arnold Slough, Sumas River (all regions) > Swift Creek and Saar Creek Wet season Dissolved Iron (Fe): Spatial and Seasonal Trends Saar Creek, Arnold Slough and the Sumas Mountain sites had the highest Fe concentrations. Vedder Mountain had levels at or below detection limit (0.05 ppm) on every sampling occasion except in January 2004 (0.10 ppm). Swift Creek and the headwaters of the Sumas River also had very low Fe levels over the year. Table 4.2.8b Significant Mann-Whitney results (a<0.01) for dissolved Fe by site. Tributary Fe (ppm) < or > In compar ison to Data Set Swift Creek and Vedder Mountain < All other tributaries Dry season Arnold Slough > Swift Creek, Vedder Mountain, Sumas Canal, Sumas River (headwaters and border areas) Dry season Vedder Mountain < Arnold Slough, Sumas Canal, Sumas River (all regions) Wet season Sumas Canal > Sumas River,(all regions), Swift Creek, Sumas Mountain, Vedder Mountain Wet season Arnold Slough > Vedder Mountain, Sumas River (headwaters and border areas) Wet season 81 Dissolved Potassium (K): Spatial and Seasonal Trends The highest K levels were detected in Arnold Slough and the border and downstream areas of the Sumas River. The lowest K levels were in Swift Creek, Sumas Mountain, and Vedder Mountain. Concentrations of K were always below detection limit at the Vedder Mountain site. Levels of K tended to be higher during the wet season. Table 4.2.8c Significant Mann-Whitney results (a<0.01) for dissolved K by site. Tributary K (ppm) < o r > In comparison to Data Set Arnold Slough > All other tributaries Seasons combined, dry season and wet season Vedder Mountain < All other tributaries Seasons combined, dry season Marshall Creek > Sumas River (headwaters), Sumas Mountain, Vedder Mountain Seasons combined Sumas Canal > Sumas River (headwaters), Swift Creek, Sumas Mountain, Vedder Mountain Dry season Swift Creek, Sumas Mountain, Vedder Mountain < All other tributaries except Saar Creek Wet season Saar Creek < Sumas Canal and Sumas River (border and downstream areas) Wet season Dissolved Magnesium (Mg): Spatial and Seasonal Trends The highest Mg levels were detected in Swift Creek, Arnold Slough and all regions of the Sumas River. The lowest values were found at Marshall Creek, Sumas Mountain, and Vedder Mountain sampling sites. There did not appear to be any seasonal trends associated with dissolved Mg levels. 82 Table 4.2.8d Significant Mann-Whitney results (a<0.01) for dissolved Mg by site. Tributary Mg (ppm) < o r > In comparison to Data Set Swift Creek Arnold Slough Sumas River (headwaters and border areas) > All other tributaries Seasons combined, dry season Sumas River (downstream area) > All other tributaries except: Swift Creek Arnold Slough Seasons combined, Sumas River (downstream area) > All other tributaries except: Swift Creek Arnold Slough Saar Creek Dry season Vedder Mountain Sumas Mountain < All other tributaries Dry season Sumas River (headwaters and border areas) > All other tributaries except: Swift Creek Wet season Saar Creek Vedder Mountain Sumas Mountain < All other tributaries except: Swift Creek Wet season Dissolved Manganese (Mn): Spatial and Seasonal Trends Mn concentrations were highest in Arnold Slough and the Sumas Canal, and were always below detection limit (0.005 ppm) at the Vedder Mountain site. Table 4.2.8e Significant Mann-Whitney results (a<0.01) for dissolved Mn by site. Tributary Mn levels < or > In compar ison to Data Set Swift Creek Vedder Mountain < All other tributaries Seasons combined Dry season Sumas River (all regions) < Arnold Slough Sumas Canal Seasons combined Arnold Slough > All other tributaries except: Sumas Canal Sumas Mountain Dry season Sumas Canal > All other tributaries Wet season Vedder Mountain < Sumas River (all regions) Arnold Slough Sumas Canal Wet season 83 Dissolved Sodium (Na): Spatial and Seasonal Trends The highest Na concentrations were in Marshall Creek (site #5) and Sumas Mountain (site #15) sites and the lowest were at the Vedder Mountain site. There was a slight seasonal trend, with higher Na values occurring during the dry season. Table 4.2.8f Significant Mann-Whitney results (<x<0.01) for dissolved Na by site. Tributary Na (ppm) < o r > In compar ison to Data Set Vedder Mountain < All other tributaries Seasons combined Dry season Swift Creek < All other tributaries except: Saar Creek Vedder Mountain Seasons combined Sumas Canal < Arnold Slough Marshall Creek Sumas River (border and downstream areas) Sumas Mountain Seasons combined Swift Creek < All other tributaries except: Saar Creek Dry season Sumas Canal < Arnold Slough Sumas River (border and downstream areas) Sumas Mountain Dry season Vedder Mountain < All other tributaries except Sumas Mountain Wet season Sumas Canal > Swift Creek Saar Creek Wet season Swift Creek Saar Creek Sumas Canal < Arnold Slough Sumas River (border and downstream areas) Sumas Mountain Wet season Dissolved Silicon (Si): Spatial and Seasonal Trends The highest levels of dissolved Si were found in Arnold Slough and the Sumas Canal, while the lowest values were found in Swift Creek, Sumas Mountain, and Vedder Mountain sites. There did not appear to be a seasonal variation in dissolved Si. 84 Table 4.2.8g Significant Mann-Whitney results (<x<0.01) for dissolved Si by site. Tributary Si (ppm) < o r > In comparison to Data Set Vedder Mountain Sumas Mountain Swift Creek < All other tributaries Seasons combined Arnold Slough > All other tributaries Seasons combined Dry season Vedder Mountain Swift Creek < All other tributaries Dry season Sumas Mountain < All other tributaries except: Sumas Canal Dry season Arnold Slough Sumas Canal > All other tributaries Wet season Swift Creek Saar Creek Sumas Mountain Vedder Mountain < All other tributaries Wet season 4.2.4 Correlations between Water Quality Parameters Wet Season Water Parameter Correlations Several distinct groups of correlations emerge during the wet season. Nutrients (Cl", N03"-N, NH 4 +-N, and P04) are all positively correlated to one another and the majority of dissolved elements (Ca, Fe, K, Mg, Mn, Na, Si) are positively correlated to each other (exceptions are Mg to Fe and Mg to Mn). The remaining results are summarized in Table 4.2.5. Table 4.2.9 Significant Spearman Rank correlations (a=0.10) for water parameters (wet season). Parameter(s) Correlation + o r - With Parameter(s) DO, - All nutrients All dissolved elements except Mg PH - All nutrients All dissolved elements SpCond, Temp + All nutrients All dissolved elements 85 D O C + All nutrients All dissolved elements except Mn cr, NO3 - -N, + All dissolved elements P O 4 + All dissolved elements except Fe and Mn NH 4 +-N + All dissolved elements except Mg Dry Season Water Parameter Correlations During the dry season the relationships between parameters change somewhat. Most nutrients (Cl", NCV-N, and P04) are all still positively correlated to one another, but NH 4 +-N is not correlated to the rest of the nutrients. Table 4.2.10 Significant Spearman Rank correlations (a=0.10) for water parameters (dry season). Parameter Correlation (+ or- ) With Parameter(s): DO - Cl, NH4-N, DOC, SpCond, Temp, Fe, K, Mn, Na. Si PH - NH4-N, DOC, Fe, K, Mn, Si DOC + NH4-N, P04, pH, Fe, K, Mn, Na, Si SpCond + Cl, N03-N, Temp, Ca K, Mg, Mn, Na, Si Temp + Cl, SpCond, Ca, Na Temp - DO, P04 N O 3 - N + Ca, K, Na, Si P 0 4 + Fe, K, Mg, Si Cl" + Ca, K, Mg, Na, Si NH 4 +-N + Fe, K, Mn, Si 8 6 4.3 DGT Results 4.3.1 Laboratory Calibration Results Two separate laboratory experiments were run in order to test the absorption efficiency of the DGT units using a solution of known C d + 2 concentration in a controlled setting. The first run yielded only fair results, with the percent error ranging from 19 to 39% (Table 4.3.1). Table 4.3.1 Results from DGT laboratory calibration (1 s t run). Sample D G T C d (ppm) Soln C d (ppm) % Error DGT rep1 1.29 2.11 38.8 DGT rep2 1.70 2.11 19.3 DGT rep3 1.38 2.11 34.6 The second experiment included manual stirring of the solution in order to better mimic conditions of flowing water. This modification increased absorption efficiency and the percent error was reduced to 14 to 21% (Table 4.3.2). Table 4.3.2 Results from DGT laboratory calibration (2 n d run). Sample DGT C d (ppm) Soln C d (ppm) % Error DGT rep1 1.64 2.00 18.0 DGT rep2 1.58 2.00 20.8 DGT rep3 1.71 2.00 14.4 Due to the fact that the DGT units never measured levels above the solution concentration, it was concluded that results obtained from DGTs deployed in the field would not be over-estimations of actual concentrations. 87 4.3.2 Field Deployment Results Quality Analysis and Quality Control (QA/QC) Results from duplicate DGTs placed at rotating sites throughout the sampling period indicate varying coefficients of variation (CV) for each trace metal measured. The QA/QC results are presented in the Appendix D. In general, the CV for the metals detected were Al: 14 to 141%, Fe: 1 to 136%, Mn: 2 to 141%, Ni: 0 to 44%, and Zn: 0 to 141%. Discrepancies may have been due to one of the following problems: biofouling, which was a major concern in the Arnold Slough site; sediment burying the DGT unit for any length of time, which occurred at the border site of the Sumas River; or the river level dropping below the levels of the DGTs such that one or both of them become exposed to air, which occurred both at the Sumas River and Sumas Canal sites. Results from duplicates were averaged before statistical analyses were performed. Trace Metal Bioavailability Results Complete results from the field deployments of DGT units are presented in the Appendix D. The DGT units are not capable of measuring non-metals such as As, Ca, K, Mg, Na, or P and therefore the bioavailability of these elements was not examined in this study. Many of the positively charged metal ions that the DGTs are capable of measuring were always below detection limit (Cd, Co, Cu, Cr, and Pb). The metals that were consistently measured above detection limit were Al, Fe, Mn, Ni, and Zn and are therefore the focus here. The total sample number for each site over the course of the year was 10, therefore the data was not further separated into wet and dry seasons but was analyzed as a whole. 88 Bioavailable Aluminum (Al): Spatial Trends Based on monthly bar graphs, the sites with the highest concentration of bioavailable Al were Vedder Mountain and Marshall Creek. Other dates and sites were usually below detection limit. Based on Mann-Whitney tests (a<0.01), Vedder Mountain Al levels were significantly higher than both Sumas Canal and Arnold Slough. Figure 4.3.1 presents the DGT Al results by site and by deployment date. I IDGTAI i I 350 n a. a. Swift Creek Sumas River Sumas River Sumas Canal Arnold Marshall Vedder border downstream Slough Creek Mountain Arrow indicates DGT was lost. • Oct-30-03 BNov-24-03 DDec-10-03 DJan-12-04 BFeb-02-04 • Mar-01-04 BMar-22-04 «Apr-19-04 DJun-07-04 DJul-13-04 Figure 4.3.1 DGT results for bioavailable Al by site. 89 Bioavailable Iron (Fe): Spatial Trends Iron levels were highest in Arnold Slough and Swift Creek confluence while the Sumas River and Sumas Canal had the lowest levels of bioavailable Fe throughout the year. Marshall Creek and Vedder Mountain had moderate levels of bioavailable Fe, which peaked in the early part of the wet season. There were no significant differences in Fe levels between sites based on the Mann-Whitney tests (a<0.01). Figure 4.3.2 presents the DGT Fe results by site and by deployment date. 2000 1800 1600 1400 1200 1000 ft800 600 400 200 0 DGT Fe I • • • • C • 1 1 r | m n _nJl_ - 1 J L fcnrfM. B -TL MBB=k__JH iL. Swift Creek Sumas River Sumas River Sumas Canal Arnold border downstream Slough Marshall Creek Vedder Mountain Arrow indicates DGT was lost. • Oct-30-03 BNov-24-03 ODec-10-03 DJan-12-04 QFeb-02-04 OMar-01-04 BMar-22-04 BApr-19-04 DJun-07-04 DJul-13-04 Figure 4.3.2 DGT results for bioavailable Fe by site. 90 Bioavailable Manganese (Mn): Spatial Trends Bioavailable manganese was detected at all sites on all occasions except for late March 2004 in Marshall Creek, which was below detection limit. The highest Mn levels were found in the Sumas Canal and at the Swift Creek confluence. Mann Whitney results (ct<0.01) for differences in Mn between sites indicated that Vedder Mountain had lower levels than all other sites except Marshall Creek and Sumas River border area. The Swift Creek confluence site had significantly higher levels than Vedder Mountain and the Sumas River border area site. Figure 4.3.3 presents the DGT Mn results by site and by deployment date. 160 I D G T Mn Swift Creek Sumas River Sumas River Sumas Canal Arnold Marshall Vedder border downstream Slough Creek Mountain Arrow indicates DGT was lost. • Oct-30-03 • Mar-01-04 INov-24-03 aDec-10-03 CIJan-12-04 IMar-22-04 «Apr-19-04 DJun-07-04 OFeb-02-04 • Jul-13-04 Figure 4.3.3 DGT results for bioavailable Mn by site. 91 Bioavailable Nickel (Ni): Spatial Trends Bioavailable Ni was below detection limit at Vedder Mountain and was rarely found above detection limit at the Sumas Canal or Marshall Creek sites. The sites with the most consistently high bioavailable Ni concentrations were Swift Creek confluence and the Sumas River (border and downstream sites). Mann Whitney results (a<0.01) indicated that the Swift Creek confluence and Sumas River border area sites both had significantly higher Ni levels than Sumas Canal, Marshall Creek, and Vedder Mountain. Figure 4.3.4 presents the DGT Ni results by site and by deployment date. iDGT Ni 60 50 40 30 A a. a. 20 10 I I • In. n. i 1 i11 iSwift Creek Sumas River Sumas River Sumas Canal Arnold Slough Marshall border downstream Creek Vedder Mountain Arrow indicates DGT was lost. IOct-30-03 BNov-24-03 • Dec-10-03 OJan-12-04 OFeb-02-04 IMar-01-04 BMar-22-04 BApr-19-04 OJun-07-04 nJul-13-04 Figure 4.3.4 DGT results for bioavailable Ni by site. 92 Bioavailable Zinc (Zn): Spatial Trends The highest levels of bioavailable Zn were found at the Marshall Creek and Arnold Slough sites. The lowest levels of bioavailable Zn were found at Vedder Mountain, Sumas River, and the Swift Creek confluence sites. Many of the highest levels peaked at the beginning of the wet season in Sumas Canal, Arnold Slough, and Marshall Creek. Mann Whitney results (<x<0.01) for Zn indicated that Marshall Creek had significantly higher levels than all other sites. Figure 4.3.5 presents the DGT Zn results by site and by deployment date. I - DGT Zn Swift Creek Sumas River Sumas River Sumas Canal Arnold Marshall Vedder border downstream Slough Creek Mountain Arrow indicates DGT was lost •Oct-30-03 BNov-24-03 • Dec-10-03 • Jan-12-04 OFeb-02-04 OMar-01-04 BMar-22-04 BApr-19-04 OJun-07-04 DJul-13-04 Figure 4.3.5 DGT results for bioavailable Zn by site. 93 4.3.3 Relationships between Bioavailable Trace Metals, pH, Temperature, and Precipitation Spearman Rank correlation coefficients (a=0.10) were calculated for relationships between bioavailable metals, pH, temperature, the amount of precipitation to fall in the Abbotsford area 24 hours, 72 hours, and 7 days prior to retrieval, and the amount of precipitation to fall during the entire deployment period. Data was pooled to combine all of the data collected during the year and included results from Marshall Creek. Table 4.3.3 Significant Spearman Rank correlations (ct=0.10) between DGTs, precipitation, DO, specific conductivity and pH. Parameter(s) Correlated + o r -T o Parameter(s) Total Precipitation + Al, Fe, Ni, Zn DO - Mn, Ni DOC + Ni DOC, Specific Conductivity - Al Specific Conductivity + Mn, Ni PH + Al PH - Mn, Ni, Zn Al + Fe Mn + Ni 4.4 Sediment Results Quality Analysis and Quality Control (QA/QC) There were no notable QA/QC problems associated with the sediment samples and the standard reference material yielded an acceptable range of results (see Appendix E). Selenium (Se), cadmium (Cd), boron (B), and molybdenum (Mo) were consistently below detection limit. Results for arsenic (As) and lead (Pb) were site-94 specific and were not consistent across 1993, 1994, 2003 or 2004 sampling periods (Tables 4.4.1 and 4.4.2). Table 4.4.1 As in sediment results for sites with at least one sample above detection limit. A s (ppm) Site Sample ID 1993 1994 2003 2004 Sumas Canal 128 56.5 NA <25 51.5 9 <25 <25 <25 NA 146 120.2 78.3 49.1 39.8 Sumas Prairie Ditches 126 38.3 NA 35.9 37.7 127 32.9 NA 29.8 42.4 129 NA <25 28.9 42.8 130 <25 30.1 45.2 30.2 131 101.2 NA 121.0 54.7 133 25.7 31.2 29.4 26.9 136 <25 <25 <25 <25 Marshall Creek 13 <25 <25 <25 <25 5 <25 <25 32.3 <25 Pb in sediment results for sites with at least one sample above detection limit. Pb (ppm) Site Sample ID 1993 1994 2003 2004 Sumas River (headwaters) 16 <25 <25 34.2 <25 2 <25 <25 <25 29.6 Sumas River (downstream] 6 <25 <25 60.1 <25 Sumas Canal 128 <25 NA 110.3 <25 9 <25 <25 36.6 NA 146 <25 <25 <25 <25 Sumas Prairie Ditches 126 <25 NA <25 <25 127 <25 NA 29.5 <25 129 NA <25 <25 <25 130 <25 <25 <25 <25 131 <25 NA 29.1 <25 133 <25 <25 33.2 <25 136 <25 36.0 40.6 <25 Marshall Creek 13 <25 63.2 <25 <25 5 <25 <25 <25 Arnold Slough 121 <25 <25 33.0 26.1 10 <25 <25 <25 <25 11 <25 <25 88.1 31.5 Saar Creek 14 <25 <25 28.9 <25 118 <25 <25 35.0 <25 95 4.4.1 Particle Size Distribution Results from the particle size analysis are presented in the following table. Order of results are presented in the headwaters to downstream direction for the Sumas River mainstem. Sites that did not coincide with water sampling stations are given three-digit site ID numbers. Table 4.4.3 Particle size distribution results for sediments collected in 2003. Tributary Site ID % Sand % Silt % Clay Sumas River 16 36.4 36.7 26.9 2 61.5 34.7 3.8 18 28.1 65.0 6.9 3 50.4 37.3 12.3 115 27.0 49.5 23.5 4 44.7 39.3 16.0 12 95.5 1.9 2.7 6 73.5 17.3 9.2 7 77.9 17.6 4.5 Marshall Creek 5 54.2 33.7 12.1 Saar Creek 118 89.5 4.5 6.0 14 76.8 15.1 8.1 Swift Creek 1 65.9 24.7 9.4 Arnold Slough 10 74.8 12.5 12.7 11 94.5 2.2 3.3 Sumas Canal 128 89.5 7.1 3.3 9 70.5 21.1 8.4 146 77.5 18.2 4.3 Sumas Prairie 126 85.8 7.2 7.0 Agricultural Ditches 127 94.0 1.8 4.2 129 83.8 9.0 7.2 130 95.6 1.4 3.0 131 61.7 26.8 11.5 133 95.8 2.0 2.2 136 63.4 21.7 14.9 Sumas Mountain 15 77.0 15.3 7.7 4.4.2 Trace Elements in Sediments The following elements in sediment consistently measured above their respective detection limits and were further analyzed to determine spatial and temporal trends: Al, Ca, Cr, Cu, Co, Fe, K, Mg, Mn, Na, Ni, P, Si, and Zn. Results are presented by element 9 6 based on two groupings: elements typically associated with the asbestos landslide in Swift Creek and all other elements. The analyses include spatial differences as well as short-term and long-term trends between sites. These comparisons were made for the Sumas River, Arnold Slough, Saar Creek, Marshall Creek, and the Sumas Prairie agricultural ditches. The Swift Creek, Sumas Mountain and Vedder Mountain sites had too few samples per sampling period to be compared to other regions accurately and were therefore omitted from this portion of the analysis. However, differences can be visually noted based on scatter plots of sediment concentrations by site for every element presented in the following graphs and in the boxplots presented in Appendix E. Swift Creek Asbestos Landslide Influence: Cr, Co , Mg, and Ni Results The landslide present in Swift Creek introduces naturally occurring asbestos material into the tributary, which enters the Sumas River just after the headwater sampling station (#16). The influence of the asbestos material, which contains high levels of Cr, Co, Mg and Ni (Schreier and Taylor, 1981), is evident along the mainstem of the Sumas River based on the graphs of metal concentrations against distance from the headwaters (Figures 4.4.1 and 4.4.2). These elements appear to have increased in the mid-region of the Sumas River since 1993/94, suggesting that the asbestos material has moved in the system over time in the downstream direction. The Wilcoxon Signed Rank test (a=0.10) indicated significant increases in Mg in the Sumas River (data from all mainstem sites tested together) from 1993/94 to 2003/04. The levels of Cr, Co, Mg and Ni in all other tributaries were very low and similar to levels in the extreme headwaters and downstream areas of the Sumas River. 97 Table 4.4.4 Significant Mann-Whitney test results (a<0.01) for Cr, Co, Mg, and Ni in sediment by site. Element Tributaries <or> In comparison to Cr Sumas Prairie ditches < Sumas River (all areas) Saar Creek Cr Arnold Slough < Sumas River (headwater and border areas) Mg Sumas River (all areas) > Arnold Slough Sumas Prairie ditches Ni Sumas River (headwaters) > Arnold Slough Sumas Prairie ditches Nickel and Magnesium in Mainstem 16 2 18 3 115 4 12 6 7 Site #IDs: Direction: Headwaters to the Mouth of the Sumas River (not to scale) Legend: 2003/04 (black) and 1993/94 (grey) sediment averages along the Sumas River. Ni: squares, Mg: triangles. Swift Creek points are denoted by the arrow, which indicates the confluence point into the Sumas River. For every data point n=2. Figure 4.4.1 Ni and Mg in sediment: Differences from 1994 to 2004 along the Sumas River mainstem. 9 8 Legend: 2003/04 (black) and 1993/94 (grey) sediment averages along the Sumas River. Co: diamonds, Cr: circles. Swift Creek points are denoted by the arrow, which indicates the confluence point into the Sumas River. For every data point n=2. Figure 4.4.2 Co and Cr in sediment: Differences from 1994 to 2004 along the Sumas River mainstem. All Other Elements: Al , Ca , Cu , Fe, K, Mn, Na, P, Si , and Zn Results Many elements (Al, Ca, Cu, K, Na, P and Zn) were high in the headwaters of the Sumas River, dropped off after the Swift Creek confluence and rose steadily along the mainstem of the Sumas River in the downstream direction. The concentration of many of these elements increased such that they were higher in the downstream of the Sumas River than in the headwaters. Exceptions include Fe and Mn, which were high in the headwaters, dropped after the Swift Creek confluence and did not rise considerably thereafter. The levels of Si in the Sumas River were fairly consistent through the length of the mainstem. 99 Table 4.4.5 Significant Mann-Whitney test results (a<0.01) for Al, Ca, Cu, K, Na, P and Zn in sediment by site. Element(s) Tributaries < o r > In compar ison to Ca and Si Sumas Prairie ditches > Sumas River (border area) Cu Arnold Slough > Sumas River (all areas) Sumas Prairie ditches Mn Sumas River (headwaters) > Sumas Prairie ditches Fe and P Sumas River (all areas) < Arnold Slough Sumas Prairie ditches Zn Arnold Slough > Sumas River (all areas) Other differences in element concentrations between tributaries are visible in Figures 4.4.3a to 4.4.3j presented below, although they were not necessarily significantly different. The highest levels of Mn, P, Fe, and Zn are found in Arnold Slough and lowest levels in Swift Creek and Vedder Mountain. Background levels of Cu detected at the Vedder Mountain site are moderately high, but the highest levels are in Arnold Slough. 100 Aluminum in Mainstem Aluminum in Tributaries 4 A \ A \ A _ / A A A A y A / ^ • • • A • A i " \ / \ / \ / \ s A A • A A A • U H 1 • 1 — 1 • - i SW SA AS MC SC SM RF PD 1 118-14 10-121-11 13-5 128-9-146 15 19 126-136 Site #IDs: Direction: Headwaters to the Mouth of the Sumas River (not to scale) Legend: Black squares : 2003 and 2004 averages, grey triangles: 1993 and 1994 sediment averages. SW: Swift Creek, SA: Saar Creek, AS: Arnold Slough, MC: Marshall Creek, SC: Sumas Canal, SM: Sumas Mountain, RF: Vedder Mountain, PD: Sumas Prairie Agricultural Ditches. For every data point n=2. Figure 4.4.3a Spatial and temporal trends in Al from sediments of the Sumas River watershed. 101 Calcium in Mainstem 16 2 18 3 4 12 6 7 Site #IDs: Direction: Headwaters to the Mouth of the Sumas River (not to scale) Calcium in Tributaries E 6 a. ° - 5 o o 1 * 5 3 X r > A= A • ^ A - i -T SW SA AS MC SC SM RF PD 1 118-14 10-121-11 13-5 128-9-146 15 19 126-136 Site #IDs: Direction: Headwaters to the Mouth of the Sumas River (not to scale) Legend: Black squares : 2003 and 2004 averages, grey triangles: 1993 and 1994 sediment averages. SW: Swift Creek, SA: Saar Creek, AS: Arnold Slough, MC: Marshall Creek, SC: Sumas Canal, SM: Sumas Mountain, RF: Vedder Mountain, PD: Sumas Prairie Agricultural Ditches. For every data point n=2. Figure 4.4.3b Spatial and temporal trends in Ca from sediments of the Sumas River watershed. 102 Copper in Mainstem 90 80 70 60 E" 50 Q. a J 4 0 30 20 10 \ A * A—A A A / A A SW SA AS MC SC SM RF PD 1 118-14 10-121-11 13-5 128-9-146 15 19 126-136 Site #IDs: Direction: Headwaters to the Mouth of the Sumas River (not to scale) Legend: Black squares : 2003 and 2004 averages, grey triangles: 1993 and 1994 sediment averages. SW: Swift Creek, SA: Saar Creek, AS: Arnold Slough, MC: Marshall Creek, SC: Sumas Canal, SM: Sumas Mountain, RF: Vedder Mountain, PD: Sumas Prairie Agricultural Ditches. For every data point n=2. Figure 4.4.3c Spatial and temporal trends in Cu from sediments of the Sumas River watershed. 103 Iron in Mainstem Iron in Tributaries 250 200 E 150 ct a. o o o 100 50 A 1 A 1 ! 1 \ / A I A A A \ ! 1 A A . A _ \ A 1 A X • • A a SW SA AS MC SC SM RF PD 1 118--14 10-121-11 13-5 128-9-146 15 19 126-136 Site #IDs: Direction: Headwaters to the Mouth of the Sumas River (not to scale) Legend: Black squares : 2003 and 2004 averages, grey triangles: 1993 and 1994 sediment averages. SW: Swift Creek, SA: Saar Creek, AS: Arnold Slough, MC: Marshall Creek, SC: Sumas Canal, SM: Sumas Mountain, RF: Vedder Mountain, PD: Sumas Prairie Agricultural Ditches. For every data point n=2. Figure 4.4.3d Spatial and temporal trends in Fe from sediments of the Sumas River watershed. 104 Potassium in Mainstem 16 2 18 3 4 12 6 7 Site #IDs: Direction: Headwaters to the Mouth of the S u m a s River (not to scale) Potassium in Tributaries 800 700 600 500 E §; 400 300 200 100 \ / A / A B • \ A • A I A * A . / / A A * • • A • SW SA AS MC SC SM RF PD 1 118-14 10-121-11 13-5 128-9- -146 15 19 126-136 Site #IDs: Direction: Headwaters to the Mouth of the S u m a s River (not to scale) Legend: Black squares : 2003 and 2004 averages, grey triangles: 1993 and 1994 sediment averages. SW: Swift Creek, SA: Saar Creek, AS: Arnold Slough, MC: Marshall Creek, SC: Sumas Canal, SM: Sumas Mountain, RF: Vedder Mountain, PD: Sumas Prairie Agricultural Ditches. For every data point n=2. Figure 4.4.3e Spatial and temporal trends in K from sediments of the Sumas River watershed. 105 Manganese in Mainstem 80 16 2 18 3 4 12 6 7 Site #IDs: Direction: Headwaters to the Mouth of the Sumas River (not to scale) Manganese in Tributaries 1 5 12 ? a a § g c S 6 3 0 SW SA AS MC SC SM RF PD 1 118-14 10-121-11 13-5 128-9-146 15 19 126-136 Site #IDs: Direction: Headwaters to the Mouth of the Sumas River (not to scale) Legend: Black squares : 2003 and 2004 averages, grey triangles: 1993 and 1994 sediment averages. SW: Swift Creek, SA: Saar Creek, AS: Arnold Slough, MC: Marshall Creek, SC: Sumas Canal, SM: Sumas Mountain, RF: Vedder Mountain, PD: Sumas Prairie Agricultural Ditches. For every data point n=2. Figure 4.4.3f Spatial and temporal trends in Mn from sediments of the Sumas River watershed. 106 Sodium in Mainstem 600 16 2 18 3 4 12 6 7 Site #IDs: Direction: Headwaters to the Mouth of the S u m a s River (not to scale) Sodium in Tributaries 1 118-14 10-121-11 13-5 128-9-146 15 19 126-136 Site #IDs: Direction: Headwaters to the Mouth of the Sumas River (not to scale) Legend: Black squares : 2003 and 2004 averages, grey triangles: 1993 and 1994 sediment averages. SW: Swift Creek, SA: Saar Creek, AS: Arnold Slough, MC: Marshall Creek, SC: Sumas Canal, SM: Sumas Mountain, RF: Vedder Mountain, PD: Sumas Prairie Agricultural Ditches. For every data point n=2. Figure 4.4.3g Spatial and temporal trends in Na from sediments of the Sumas River watershed. 107 Phosphorus in Mainstem 4 0 -I , , , , 1 16 2 18 3 4 12 6 7 Site #IDs: Direction: Headwaters to the Mouth of the Sumas River (not to scale) Phosphorus in Tributaries 14 12 SW SA AS MC SC SM RF PD 1 118-14 10-121-11 13-5 128-9-146 15 19 126-136 Site #IDs: Direction: Headwaters to the Mouth of the Sumas River (not to scale) Legend: Black squares : 2003 and 2004 averages, grey triangles: 1993 and 1994 sediment averages. SW: Swift Creek, SA: Saar Creek, AS: Arnold Slough, MC: Marshall Creek, SC: Sumas Canal, SM: Sumas Mountain, RF: Vedder Mountain, PD: Sumas Prairie Agricultural Ditches. For every data point n=2. Figure 4.4.3h Spatial and temporal trends in P from sediments of the Sumas River watershed. 108 Sil icon in Mainstem Sil icon in Tributaries E Q. ft to 4000 3500 3000 2500 2000 1500 1000 500 A W A • \ A \ \ 1 \ W " A " \ \r + tK • ^ ]/ . N ^ r A " A • A • * A A S A • • x • SW SA AS MC SC SM RF PD 1 118-14 10-121-11 13-5 128-9-146 15 19 126-136 Site #IDs: Direction: Headwaters to the Mouth of the S u m a s River (not to scale) Legend: Black squares : 2003 and 2004 averages, grey triangles: 1993 and 1994 sediment averages. SW: Swift Creek, SA: Saar Creek, AS: Arnold Slough, MC: Marshall Creek, SC: Sumas Canal, SM: Sumas Mountain, RF: Vedder Mountain, PD: Sumas Prairie Agricultural Ditches. For every data point n=2. Figure 4.4.3i Spatial and temporal trends in Si from sediments of the Sumas River watershed. 109 Zinc in Mainstem Zinc in Tributaries 300 250 200 £ 150 N 100 50 f 1 • I J A • f \ / \ A A ' / A A A I • — • A A A \ \ A 1 A A • A . • • S W S A A S M C S C S M RF PD 1 118-14 10-121-11 13-5 128-9- -146 15 19 126-136 Site #IDs: Direction: Headwaters to the Mouth of the S u m a s River (not to scale) Legend: Black squares : 2003 and 2004 averages, grey triangles: 1993 and 1994 sediment averages. SW: Swift Creek, SA: Saar Creek, AS: Arnold Slough, MC: Marshall Creek, SC: Sumas Canal, SM: Sumas Mountain, RF: Vedder Mountain, PD: Sumas Prairie Agricultural Ditches. For every data point n=2. Figure 4.4.3j Spatial and temporal trends in Zn from sediments of the Sumas River watershed. 110 4.4.3 Relationships between Elements in Sediments The 2003/04 sediment data was used to determine if relationships existed between any of the elements. The Spearman Rank correlation (a=0.10) identified two main groups of significant relationships: Fe, P, Zn, Cu, and K were all positively correlated to one another (except the Fe and Cu pair) and Cr, Co, Ni and Mg were all positively correlated to one another. Table 4.4.5 Significant Spearman Rank correlations (cc=0.10) between elements in sediments. Parameter(s) Correlated + o r -To Parameter(s) Fe and Ca + P, Zn, K, Na, Si Ni, Cr, Co, Mg - Ca, P, Zn, Cu, Si Na + Fe, Al, Ca, K, Zn, P Al - Mn, Ni Al + Ca, Zn, Cu, K, Na Mg + Mn, Cr, Co, Ni Mn - Cu Fe - Mg, Cr, Co 4.4.4 Long-Term Trends in Sediment Quality (1993-2004) Results from the Wilcoxon Signed Rank test (a=0.10) indicate significant changes in the concentrations of certain elements in sediment since 1993/94 in several tributaries. Notably, metals associated with the asbestos landslide (Co, Cr, and Mg) have not increased at any of the sites. However, Swift Creek, Sumas Mountain, and Vedder Mountain sites were omitted from the Wilcoxon Signed Rank tests due to their small sample sizes for each decade (n=2). 111 Table 4.4.6 Significant Wilcoxon Signed Rank test results (a=0.10) for elements in sediment over time. Tributary Element(s) in Sediment Increased or Decreased From 1993/94 to 2003/04 Sumas River (all sites) K and Zn Increased Arnold Slough Cu, Na, Zn Increased Saar Creek Ca, Cu, K, Na, Zn Increased Marshall Creek Cu, Fe, K, Na, P, Zn Increased Sumas Prairie ditches Ca Increased Other changes were apparent on the graphs but were not statistically significant. 4.5 Relationships between Dissolved, Bioavailable, and Extractable Elements Spearman's Rank correlation coefficients (a = 0.10) were calculated to determine if relationships existed between the water, DGT, and sediment results. The entire data set (seasons combined) was used. The sediment results from 2003 and 2004 were averaged, and these values were assigned to the respective sampling sites for every water and DGT sampling date during 2003 and 2004. The complete correlation matrix is presented in the Appendix F and significant results are summarized in Table 4.5.1. Table 4.5.1 Significant Spearman Rank correlations (cc=0.10) between dissolved, bioavailable, and extractable elements measured in 2003 and 2004 (N/S: not significant). Element Relationship between Dissolved and Bioavailable metal phases Relationship between Bioavailable and Extractable metal phases Relationship between Extractable and Dissolved metal phases Fe N/S N /S + Mn + + N / S Ni N/S + N / S Zn N/S + N/S Al N/S N /S N /S 112 Dissolved Ni was always below detection limit so no relationships were identifiable with it. The dissolved phases of Zn and Al were not correlated to the other phases, however the dissolved levels of both these metals were mainly under detection limit. Figures 4.5.1 to 4.5.4 graphically represent the relationships between the extractable (sediment-bound) and bioavailable (DGT) results per site for Fe, Mn, Ni, and Zn. Sediment and DGT results were averaged for each site, therefore the R 2 values are somewhat different than the coefficients derived from the Spearman Rank correlations using the raw data. Bioavailable and Sediment Zn Figure 4.5.1 Relationships between bioavailable (DGT) and extractable (sediment-bound) Zn with a linear trendline (R2=0.33). 113 Bioavailable and Sediment Fe 500 _ 400 A a. a. u. o A n 300 « 200 re > re o m 100 Arnold Slough] • Sumas w ^ River/Swift Creek Vedder Mountain _ ,. =-»—— Confluence Reference 4} Marshall Creek Downstream 4>t Sumas River Sumas Canal • 1 1 Border Region 1 20000 40000 60000 80000 Sediment Fe (ppm) 100000 120000 Figure 4.5.2 Relationships between bioavailable (DGT) and extractable (sediment-bound) Fe with linear trendline (R2=0.30). Bioavailable and Sediment Ni 18 Sediment Ni (ppm) Figure 4.5.3 Relationships between bioavailable (DGT) and extractable (sediment-bound) Ni with linear trendline (R2=0.89). 114 Bioavailable and Sediment Mn Sediment Mn (ppm) Figure 4.5.4 Relationships between bioavailable (DGT) and extractable (sediment-bound) Mn with linear trendline (R2=0.81). Table 4.5.2 Significant Spearman Rank correlations (a=0.10) between dissolved and extractable elements. Dissolved Element(s) Correlation + o r -with Sediment Element (s) Fe, K, Mn + Cu, Fe, K, P, Zn Na + K and Zn Fe, Ca, and K - Cr Mg + Mn, Cr, Ni Mg - Al, P, Zn, Cu, K Si + Fe, P, Mn, Zn, Ni 4.6 Relationships between Land Use Indices and Environmental Quality Buffers were created around the water sampling sites as outlined in the methodology section. Sumas Mountain (site #15) was assigned a value of 75% forest cover within the associated land use buffer, which accounted for the mining operation occurring in the near vicinity. Vedder Mountain (site #19) and Swift Creek (site #1) were 115 assigned values of 100% forest cover within their buffers. Due to a lack of crop cover data, buffers were not created for Sumas River sites #16, #2, and #18 (headwaters in the U.S.). Land cover results for each buffer are summarized in Table 4.6.1 and a map is provided in Figure 4.6.1. Table 4.6.1 Characteristics of land cover within buffer areas. % Land Cover within Buffer Cover Pasture/ Berries/ Location Site ID Corn Crop Forage Vegetables Nursery Forest Sumas 3 77.5 0 22.5 0 0 0 River 4 48.1 3.0 29.7 0 10.6 0 12 40.1 0 5.0 0 0 0 6 0 0 32.0 0 0 0 7 1.8 48.4 2.7 0 0 0 Saar Creek 14 1.4 40.1 58.4 0 0 0 Arnold 10 30.5 0 38.6 0 0 0 Slough 11 43.0 0 6.9 40.1 0 0 Sumas 9 31.6 45.9 0 0 14.2 0 Canal 8 12.2 0 0 74.7 0 0 Marshall 13 0 0 0 0 45.0 0 Creek 5 3.0 0 40.4 0 0 0 Sumas Mountain 15 0 0 0 0 0 75.0 Swift Creek 1 0 0 0 0 0 100.0 Vedder Mountain 19 0 0 0 0 0 100.0 116 117 Other land use indices included AUEs/ha and N surplus data for associated EAs, and clay content of the sediment (Table 4.6.2). N budget results were not available for Marshall Creek site #13 because the EA associated with this site has an area that is too small for the calculations to be accurate. Swift Creek, Sumas Mountain, and Vedder Mountain sites do not have any associated N budget results because there are no livestock in the respective EAs. These sites were given an AUE/ha value of zero. Samples from Marshall Creek (#13) and Vedder Mountain (#19) were not available for particle size distribution, therefore the clay content values within the streambed were obtained from local soil maps (Luttmerding, 1980). Table 4.6.2 Land use indices within buffer areas. Surplus N Location Site ID AUE/ha kg/ha % Clay Sumas River 3 4.84 389 12.3 4 2.89 219 16.0 12 2.89 219 3.0 6 2.89 219 9.2 7 2.89 219 4.5 Saar Creek 14 3.27 197 8.1 Arnold Slough 10 3.27 197 12.7 11 3.27 197 3.3 Sumas Canal 9 3.66 238 3.3 8 3.66 238 4.3 Marshall Creek 13 6.45 N/A *15.0 5 2.89 219 12.1 Sumas Mountain 15 0 N/A 7.7 Swift Creek 1 0 N/A 9.4 Vedder Mountain 19 0 N/A *15.0 'Indicates that values were taken from soils maps, not particle size analysis. Spearman Rank correlation coefficients (cc=0.10) were calculated in order to 118 determine relationships between land use indices and environmental quality. Correlations with the DGT results showed that the best indicators for bioavailable Zn were AUE/ha and the amount of berry and nursery crops in the buffer zone. Bioavailable Mn was also positively correlated to AUE/ha. The proportion of clay in sediments had a negative correlation with bioavailable levels of Al and Mn. Tables 4.6.3 to 4.6.6 present the significant correlations between land use indices and the remaining water and sediment quality variables. For a complete list of correlation coefficients between land use indices and water and sediment quality variables please see Appendix F. Table 4.6.3 Significant Spearman Rank correlations (a = 0.10) between land use indices and nutrient levels in water. Land Use Indice(s) Correlation + o r -with Nutrient(s) % Corn cover % Pasture cover AUE/ha + All nutrients Nitrogen surplus + N0 3"-N % Clay in sediment + cr NO3-N P 0 4 % Clay in sediment - NH 4 + -N % Forest cover - All nutrients 119 Table 4.6.4 Significant Spearman Rank correlations (a = 0.10) between land use indices and physical water quality parameters. Land Use Indice(s) Correlation + o r -Parameter(s) % Corn cover % Pasture cover + DOC, Specific conductivity % Corn cover % Pasture cover % Vegetable cover AUE/ha Nitrogen surplus - DO, pH % Berry/Nursery cover AUE/ha Nitrogen surplus + Specific conductivity % Berry/Nursery cover Nitrogen surplus - DOC % Forest cover + DO, pH % Forest cover - DOC, Specific conductivity, Temperature Table 4.6.5 Significant Spearman Rank correlations (a = 0.10) between land use indices and dissolved elements in water. Land Use Indice(s) Correlation + o r -Dissolved Element(s) % Corn cover + All dissolved elements % Pasture cover + All dissolved elements except Ca % Vegetable cover + Fe, K, Mn, Si % Crop residue cover + Fe % Berry/Nursery cover Nitrogen surplus + Ca % Forest cover - All dissolved elements AUE/ha + All dissolved elements except Na Nitrogen surplus - Fe, K, Mn, Si % Clay in sediment + Na % Clay in sediment - Fe, Mn 120 Table 4.6.6 Significant Spearman Rank correlations (a = 0.10) between land use indices and sediment quality. Land Use Indice(s) Correlation + o r -Sediment Metal(s) % Vegetable cover + Fe, P, Zn % Pasture cover + Fe, P, Ni % Vegetable cover - Cr, Ni, Co, Mg AUE/ha + Fe, P, Zn, Cu, Si % Forest cover - Al, Fe, P, K, Zn, Na AUE/ha - Co Nitrogen surplus - Fe, Zn, Cu 121 Chapter 5 Discussion 5.1 Nutrient Water Quality Guidelines Table 5.1.1 Background levels and water quality guidelines for nutrients (MWLAP, 1998; MWLAP, 2003; Nordin and Pommen, 1986). Indicator cr N 0 3 - N N H / - N Total P Units in Water mg/L mg/L mg/L mg/L Background Levels in B .C. 1-100 <1.0 <0.1 N/A Water Quality Criteria Drinking Water 250 10 Depends 0.01 Aquatic Life 600 40-200 on pH N/A Irrigation 100-700 20-30 and N/A Livestock 600 100 temperature N/A Chloride (Cl) The application of road salt for winter accident prevention represents the single largest use of salt in B.C. and is the main anthropogenic source of Cl" to the environment (MWLAP, 2003). However, potassium chloride is the dominant component in fertilizers, therefore some of the Cl" in the Sumas River watershed may originate from fertilizer runoff. While none of the samples exceeded the B.C. Water Quality Guidelines, site #5 in Marshall Creek consistently had the highest levels of Cl". Marshall Creek had higher levels of Cl" in the wet season than the dry season whereas the other sites displayed opposite seasonal trends. The buffer area around one of the Marshall Creek sites (#5) includes the Trans Canada Highway, which receives salt applications to the road surface to reduce ice build-up. Furthermore, there are many intensive poultry farm operations located above the Abbotsford Aquifer, which directly influences Marshall Creek site #13. The fact that ammonia and orthophosphate levels were also high in Marshall Creek during the winter months suggests that the source of Cl" may be both agricultural runoff and road salts. Waterways surrounded by agricultural operations (Sumas River, Arnold Slough, Sumas Canal) had significantly higher levels of Cl" than 122 the mountain sites (Vedder and Sumas Mountains). Nitrate (N0 3 -N) The Canadian Drinking Water Quality guideline for N03"-N is 10 mg/L, and levels in Marshall Creek (site #13) reached 9.85 mg/L in August 2003. Other areas with high N03"-N were the Sumas River (border and downstream areas), Arnold Slough, Sumas Canal, and Saar Creek, where wet season concentrations often rose above 3.0 mg/L. These levels of N03"-N are of concern in the Sumas River watershed because aquatic organisms can be affected through the reduction of DO levels as a result of the nitrification process. Furthermore, N03"-N in waterways may contribute to eutrophication in the Sumas River, Arnold Slough, Sumas Canal. The long-term trends in the watershed are of increasing N03"-N levels in the Sumas River, Sumas Canal, Marshall Creek, and Arnold Slough waterways. This is an indication that current agricultural waste management practices in the region are not sufficient for the protection of water quality. Ammonium (NH 4 +-N) The NH4+-N results indicate that many of the tributaries located in agricultural areas have significantly higher levels than the Vedder Mountain reference site throughout the year. Sumas Canal was the only area that experienced seasonal trends, with lower levels occurring during the dry summer months (median of 0.48 mg/L) in comparison to the wet winter months (median of 1.19 mg/L). Higher water temperatures in the summer will favour the process of nitrification (the conversion of NH 4 +-N to N03"-N) and will also allow aquatic plants to take up N, which may account for the lower 123 seasonal medians and eutrophication (aquatic plant growth and proliferation) noted in Sumas Canal, Arnold Slough, and the downstream region of the Sumas River. B.C. Water Quality Guidelines for NH/-N are based on average 30-day concentrations of total ammonia and depend and on the pH and temperature of the water (Nordin and Pommen, 1986). Table 5.1.2 highlights samples that exceeded the maximum allowable concentration (MAC) criteria based on the pH and temperature for the date of sampling. Table 5.1.2 Exceedences of NH 4 +-N water quality criteria in the Sumas River watershed. Site Date Temperature (°C) PH NH 4 +-N (mg/L) MAC NH 4 +-N (mg/L) Arnold Slough (#10) 14/Oct/03 10.6 7.0 2.20 1.84 Marshall Creek (#5) 02/Feb/04 5.1 7.1 5.10 1.92 Marshall Creek (#5) 01/Mar/04 7.2 7.2 9.96 1.90 The use of the B.C. guidelines for the analysis of NH/-N results is difficult because the samples were not taken over a 30-day period for each site, however it does not seem implausible that average levels at these sites were sustained above the MAC for the duration of a month. Increased ammonia levels in water can affect the physiology of aquatic organisms. Studies of salmonids have shown that levels of un-ionized ammonia (NH3) can be lethal to rainbow trout at 0.4 mg/L (Haywood, 1983). It is therefore recommended that waters that are inhabited by salmon should not exceed 1 mg/L of ionized ammonia (NH4+-N) (Nordin and Pommen, 1986). Levels of NH4 +-N exceeded 1 mg/L in the Sumas Canal on all sampling dates from October 2003 to March 2004. Arnold Slough and Saar Creek had levels greater than 1 mg/L in August and October 2003 and sampling in March 2004 indicated high NH 4 +-N levels in Sumas Canal, Saar Creek, Marshall Creek, and the downstream region of the Sumas River. 124 Orthophosphate (P0 4) There are no provincial or federal guidelines for phosphate in water. However, total phosphorus should not exceed 0.01 mg/L for drinking water. Many of the sites in the Sumas River had non-detectable (<0.02 mg/L) levels of P0 4 . The first flush of runoff after the summer months occurred after a large rainstorm at the end of October 2003. Samples from the November 2003 sampling period had relatively high levels of PO4 (>0.10 mg/L) in Marshall Creek, Arnold Slough, Saar Creek, and the border and downstream regions of the Sumas River. These levels were sustained in Marshall Creek and peaked in that tributary at 0.30 mg/L in March 2004. Levels throughout the watershed were comparatively lower during the dry season. The main reason for low P 0 4 values found during the summer months is likely a combination of a lack of runoff from low levels of precipitation as well as higher biological uptake by aquatic plants in the waterways. 5.2 Physical Water Quality Guidelines Table 5.2.1 Background levels and water quality guidelines for physical water quality parameters (McKean and Nagpal, 1991; MELP, 1997; MWLAP, 1998; MWLAP, 2001a; MWLAP, 2001b). Specif ic Indicator DO D O C PH Temperature Conductivity Units in Water mg/L mg/L ° C uS/cm Background Levels in B .C . >10 <5 5.8-8.3 various various Water Quality Criteria Drinking Water 6.5-8.5 Aquatic Life 5.5-9.5 Monthly 6.5-9.0 4-13 700 Irrigation Median 700-5000 Livestock +/- 20% 1400-4200 Recreation 5.0-9.0 125 Dissolved Oxygen (DO) B.C. Water Quality Guidelines for DO depend on the life stage of the fish species inhabiting the waterway. In general, the instantaneous minimums are 9 mg/L for buried embryo/alevin and 5 mg/L for all other life stages (MELP, 1997). Several sites over many sampling dates had lower DO levels than these minimum concentrations. Swift Creek had DO levels below 9 mg/L on two occasions (August 2003 and May 2004) while the Vedder Mountain reference site fell below 9 mg/L only in August 2003. Arnold Slough had levels of DO consistently below 5 mg/L, as did the headwater site of the Sumas River (site #16). The low DO levels are likely related to the flow stagnancy and summer eutrophication noted at these sites in addition to aquatic plant growth. Levels of DO throughout the rest of the Sumas River and in the Sumas Canal generally measured above 5 mg/L over the course of the year and occasionally rose above 9 mg/L. Values of 9 mg/L and above were noted at a majority of sites during the October 30, 2003 sampling. This set of samples was collected directly after an extreme rainfall event and DO levels were likely elevated due to an increase in flow coupled with a decrease in temperature. Dissolved Organic Carbon (DOC) The B.C. Water Quality Guidelines for DOC are based on changes in concentration over time rather than a specific maximum or minimum level. High DOC levels have been linked to increases in primary productivity and decreases in the bioavailability of dissolved trace metals (Forstner and Salomons, 1983; Mantoura et al., 1978; Van der Watt et al., 1994). Increases in DOC levels can raise the metabolism of bacteria, which can lead to decreases in DO levels (MWLAP, 2001a). 126 Recommendations are for the monthly median DOC to be within ±20% of seasonally-adjusted median background levels as measured at reference sites. Based on the methodology used in this analysis it is not feasible to compare the data to these recommendations. However, in an attempt to identify waterways most at risk for DOC pollution in the Sumas River, those with the greatest ranges of values are listed. Table 5.2.2 indicates sites where the most dramatic changes occurred. Table 5.2.2 Tributaries with the greatest range of DOC levels in the Sumas River watershed. Site Minimum Maximum Range DOC (mg/L) DOC (mg/L) (mg/L) Sumas Mountain 3.4 15.9 12.5 Saar Creek 3.1 11.7 8.6 Marshall Creek 1.0 8.8 7.8 Arnold Slough 3.5 10.2 6.7 Median DOC concentrations in B.C. waters are generally less than 5 mg/L (MWLAP, 2001a). The tributaries that had medians > 5 mg/L DOC throughout the year were Sumas Mountain (6.3 mg/L) and Arnold Slough (5.1 mg/L). The border and downstream areas of the Sumas River both had DOC medians of 4.4 mg/L. pH The pH of water is the result of a balance between leaching and weathering within the watershed. Therefore, the underlying geology and the amount of precipitation to fall play major roles in the pH of a waterbody. The average pH values in lakes of the Fraser Lowland sub-region of the Cascade Mountain region range from 5.8 to 8.3 (McKean and Nagpal, 1991). The results from this study indicate that some samples fall outside of criteria for drinking water and aquatic health. These exceedences are 127 presented in Table 5.2.3. Table 5.2.3 Tributaries with exceedences of pH above or below the water quality criteria. Site PH Date Sumas River (site #7) 8.7 26/08/03 Swift Creek (site #1) 8.8 14/10/03 Arnold Slough (site #10) 6.3 30/10/03 Arnold Slough (site #11) 6.3 30/10/03 Saar Creek (site #14) 6.4 30/10/03 Marshall Creek (site #5) 6.3 30/10/03 Sumas Mountain (# 15) 6.4 30/10/03 In general, Swift Creek and Vedder Mountain had higher pH levels than other sites. Waterways most susceptible to agricultural runoff (Arnold Slough, Saar Creek, Sumas Canal) had some of the lowest pH levels measured. Agricultural waste and fertilizers tend to be acidic, therefore runoff from fields and manure storage areas would likely reduce the pH of the receiving waters (Sharpley et al., 1998; Sims and Wolf, 1994). Temperature The Sumas and Vedder mountain sites had the lowest temperatures, which is likely a result of a combination of higher altitude and more shade cover than other sites. Sumas Canal and Arnold Slough had the highest temperatures and did not have vegetated riparian zones that could have offered shade cover. During the summer months they were often stagnant, which contributes to higher water temperatures. Marshall Creek, which is influenced by groundwater, had a more mediated temperature range. 128 Temperature has a direct effect on the solubility of oxygen in water and interacts with many other chemical characteristics such as pH and conductivity (MWLAP, 2001b). The B.C. Water Quality Guidelines for temperature advise against exceeding the optimal range of temperature for fish by more that one degree. The most temperature-sensitive fish species found in the Sumas River watershed are cutthroat and rainbow trout, which spawn in the early spring and begin rearing in late spring/early summer. During this time the optimal temperature range for these fish is 7.0-18.0°C (MWLAP, 2004). This temperature range was exceeded in July 2003, August 2003, and May 2004 in the downstream area of the Sumas River and in the Sumas Canal. Fish kills have been previously reported in the Sumas Canal (DFO, 2002), and some dead fry were spotted while sampling in the downstream area (site #12) of the Sumas River in May 2004. Specific Conductivity Specific conductivity refers to the ability of the water to conduct electricity, which indicates the amount of dissolved salts in the water. A temperature of 25°C is used as a constant for the calculation of specific conductivity. High specific conductivity may indicate a high level of dissolved solids or total solids in the waterway. The B.C. water quality guidelines indicate that specific conductivity should not exceed 700 u.S/cm (MWLAP, 1998). No samples taken in this study exceeded this level. Throughout the watershed there were minimal seasonal trends, with higher levels found generally in the drier months. Downstream Marshall Creek (site #5) consistently had the highest levels of specific conductivity. This trend concurs with samples from the same sites analyzed in 1994 and 1995 by Berka. 129 5.3 Trace Element Guidelines for Water and Sediments The following elements are of interest because they may present toxicity problems for aquatic biota: Al, As, Cd, Cr, Co, Cu, Fe, Pb, Mn, Ni, and Zn. These compounds fall into two categories: those associated with the naturally occurring asbestos landslide (Co, Cr and Ni) and those associated with agricultural operations (As, Cu, Fe, Pb, Mn, and Zn). It is encouraging that several potentially toxic elements (As, Cd, Cr, Cu, Co, Mo, and Pb) were never measured above their respective detection limits in water samples. However, it is worth noting that the detection limits for dissolved As, Co, Cu and Pb were higher than the lower threshold of aquatic health toxicity guidelines. Furthermore, these elements were present in sediment samples except for Cd, which was not detected above detection limit in any of the water or sediment samples collected and will therefore not be discussed here. There are no water or sediment guidelines for Mg therefore it is not discussed here either. 5.3.1 Trace Elements from the Swift Creek Landslide: Cr, Co , Ni Table 5.3.1 Water and sediment criteria and background levels for Cr, Co, and Ni (MWLAP, 1998; Nagpal, 2003; Rieberger, 1992; Stancil, 1980; Swain and Walton, 1990). Indicator Cr Co Ni Units in Water ug/L ug/L ug/L Background Levels in B.C. <2.0 <1.9 1-3 Water Quality Criteria Drinking Water 50 Aquatic Life 1.0-8.9 0.9 25-150 Irrigation 4.9-8.0 6-110 200 Livestock 50 1000 1000 Recreation Units in Sediment ppm ppm ppm Background Levels in B.C. 12-206 <20 12.7 Sediment Quality Criteria Interim Sediment Quality Guidelines 37.3 Probable Effects Level 90 Lowest Effect Level* 16 Severe Effect Level* 75 130 The background concentrations of Cr, Co, and Ni remain higher than other levels in regions across the Lower Mainland of B.C. throughout Swift Creek and most of the main stem of the Sumas River (Schreier et al., 1987). Numerous studies have found pH to have a large effect on metal bioavailability because the equilibrium between metal speciation, solubility, adsorption and exchange on solid phase sites is connected to pH (Campbell et al., 1988; Clement and Faust, 1981; Forstner and Salomons, 1991; Jackson et al., 2003). As the pH decreases away from the landslide site, the metals associated with the asbestos sediments may become more dissolved into the water column. These metals have been shown to bioaccumulate in fish in the Sumas River and therefore may present a natural contamination risk of Cr, Co, and Ni (Schreier et al., 1987). Magnesium is not considered to be a toxic element and is therefore not discussed here. Chromium (Cr) While Cr was not found to be above detection limit in water samples, it was found in very high concentrations in sediment samples. Levels in sediment samples exceeded interim guidelines of 37.3 ppm in 1993, 1994, 2003, and 2004 in Swift Creek, Saar Creek, and all regions of the Sumas River except for the site furthest from the Swift Creek confluence (site #7). Other sites with high levels of Cr (>37.3 ppm) include Vedder Mountain in 2004, Arnold Slough in 1993 and 2003, and one of the Sumas Prairie agricultural ditches in 2004. The likely source of Cr is the underlying geology in Swift Creek because sediments from this source are transported throughout the length of the Sumas River. It is possible that Vedder Mountain has similar, albeit smaller, deposits of geological material high in Cr. The headwaters of Saar Creek is Vedder 131 Mountain, which would account for the high levels found in that tributary. There is not much evidence of Cr bioaccumulation in invertebrates or fish although it can be transferred through the food web. Mammals can tolerate high Cr levels without showing negative symptoms because the gastrointestinal environment reduces Cr + 6 to Cr + 3 , which is much less toxic (Moore and Ramamoorthy, 1984). However, chronic low-levels of Cr in the aquatic environment can depress growth rates and decrease body size, and reduce reproduction rates of fish. The potential of Cr to be toxic appears to be somewhat dependent upon the presence of other cations (calcium reduces toxicity) and the water temperature (lower temperatures reduce toxicity) and the species in question (Moore and Ramamoorthy, 1984). Cobalt (Co) Cobalt was not found above detection limit in the water or DGT samples. However, it was found in high levels in some sediments, which followed a similar spatial pattern within the watershed as Cr and Ni. The asbestos material found in the Swift Creek landslide is known to contain high levels of Co (Schreier et al., 1987). While guidelines exist for Co in water, none are available for Co in sediments. However, common background levels are 20 ppm in B.C., and levels were 2 to 3 times higher than this in Swift Creek and in the Sumas River downstream from the Swift Creek confluence throughout the 1993, 1994, 2003, and 2004 sampling periods. Aquatic invertebrates are more susceptible to Co toxicity than fish or aquatic plants, however rainbow trout is the most sensitive fish species (Nagpal, 2003). Cobalt is essential in trace amounts for mammals because it is a component of the vitamin B12 complex (Nagpal, 2003). The toxicity of Co in freshwater is likely influenced by water 132 hardness, as is the case for most dissolved metals (Loring, 1979). Nickel (Ni) Water samples did not have detectable (>0.10 mg/L) levels of dissolved Ni, however, DGT results indicated that the most bioavailable Ni in the water column was in sites in the Sumas River downstream from the confluence with Swift Creek. Sediment samples were highly contaminated (>75 ppm) with Ni in Swift Creek, Sumas River (all regions), Arnold Slough, Saar Creek, and several of the Sumas Prairie agricultural ditches. The main source of Ni is the landslide in Swift Creek, which transports the metal throughout the length of the Sumas River. Saar Creek headwaters are located on Vedder Mountain which may have similar geological deposits as the Swift Creek sub-watershed. It is possible that the high Ni levels in Arnold Slough and the Sumas Prairie ditches originates from agricultural sources. Stainless steel, which includes Ni, is involved in fertilizer manufacturing (Moore and Ramamoorthy, 1984). Toxicity of Ni depends on the aquatic species in question and the presence of other metals (Mandal et al., 2002). Zinc, hard water, and DOC will reduce Ni toxicity (Anderson, 1988; Snodgrass, 1980). Several elements including Cu, Pb, Zn, Cr, and As are all more toxic to fish than Ni. The main effects of Ni on fish are a reduction in egg survival, fecundity, and gill diffusion capacity. High levels of Ni residues in fish gills can lead to death by asphyxiation (Moore and Ramamoorthy, 1984). 133 5.3.2 All Other Trace Elements: Al , A s , Cu , Fe, Mn, Pb, and Zn Table 5.3.2 Water and sediment criteria and background levels for Al, As, Cu, Fe, Pb, Mn, and Zn (MWLAP, 1998; MWLAP, 2001c; Nagpal, 1987; Nagpal, 1999; NRCC, 1978; Rieberger, 1992; Standi, 1980). Indicator Al A s C u Fe Pb Mn Zn Units in Water m g / L b u g / L u g /L mg/L u g / L u g / L mg/L Background Levels in B .C. 0.03 <5 <2.0 N/A <1.0 10-1700 <0.01 Water Quality Criteria Drinking Water Aquatic Life Irrigation Livestock Recreation 0.1 0.05-0.10 5.0 5.0 0.2 25 5 100 12-25 0.5 2.0-4.0 200 300 1000 0.30 5.0 50 1.0-7.0 200 100 50 0.7-1.9 200-1000 5.0 0.0075-0.030 1.0-5.0 2.0 5.0 Units in Sediment ppm ppm ppm ppm ppm ppm ppm Background Levels in B .C. 19,800a 2.7-29.7a <15 N/A <10 614a 88.7a Sediment Quality Criteria Interim Sediment Quality Guidelines Probable Effects Level Lowest Effect Level Severe Effect Level 5.9 17.0 35.7 197.0 21,200 43,766 35.0 91.3 123 315 a: Background levels are for Canada. Aluminum (Al) The average concentration of dissolved Al in B.C. rivers is 0.03 mg/L, with 25% of streams having levels >0.05 mg/L (Butcher, 1988). During the wet season, Arnold Slough, Marshall Creek, Saar Creek, and the downstream region of the Sumas River often had levels of dissolved Al >0.05 mg/L. The highest levels were detected in November 2003 and January 2004, with peaks of 0.33 mg/L in Saar Creek, 0.21 mg/L in the Sumas River, and 0.34 mg/L in Swift Creek. This time of year coincides with the lowest pH conditions (^ 7), which may present toxicity problems for fish and other 134 aquatic biota. Waters with high levels of dissolved Al tend to have low pH, high temperature, high salt concentrations, or be fast moving (Butcher, 1988). Bioavailable Al was highest at the Vedder Mountain reference site. In general, there was no correlation between bioavailable Al and sediment-bound Al. Therefore the absence of other cations (Fe, Mn, Ni, or Zn) competing for the DGT resin-gel may be part of the reason behind high bioavailable Al results at the Vedder Mountain site. Marshall Creek had relatively high bioavailable Al during the wettest time of the year (December and January). There are no sediment quality guidelines for Al, however, levels were especially high (>10,000 ppm) in the sediments of the Sumas River headwaters, Arnold Slough, Saar Creek, Marshall Creek, and Vedder Mountain reference site. Acute Al toxicity for aquatic biota decreases as pH increases above 7.0 and also as water hardness increases. Butcher (1988) describes chronic effects in fish, which are noted at concentrations as low as 0.5 mg/L. Symptoms include weight loss, decrease in fright reaction times, higher respiration rates, gill hyperplasia and loss of equilibrium. These effects could make fish vulnerable to predation and habitat loss. The gills of fish are major uptake and elimination routes for Al but there is no indication of biomagnification in the food chain. Arsenic (As) Typical As levels in natural waters are <0.45 u.g/L (Ferguson and Gavis, 1972) whereas higher levels of up to 33 u,g/L have been found in streams in the vicinity of agricultural operations (Richardson et al., 1978). Arsenic levels in Canadian lake sediments are higher in agricultural areas compared to those situated on the 135 Precambrian shield, suggesting that run-off from land applications likely increases As concentrations (Huang and Liaw, 1978). Neither water nor DGT samples had measurable levels of As. However, sediment levels of As were detected above probable effects levels (>17 ppm) in Sumas Canal and several vSumas Prairie agricultural ditches on all sediment sampling occasions (1993, 1994, 2003, and 2004). Based on the location of these sites, the most probable source of As is agricultural runoff. Agricultural uses of As include compounds added to poultry feed, as summarized in the introduction. While the levels in the agricultural ditches are not a major concern due to their relative isolation from aquatic biota, the high levels of As in the Sumas Canal may affect fish, invertebrates, and aquatic plants. The desorption of As from sediments depends on the reduction of Fe(lll) to Fe(ll) and on anaerobic conditions, which have been shown to produce a ten-fold increase in As(lll) compared to aerobic conditions (Clement and Faust, 1981). Arsenic is able to bioaccumulate in algae, benthic invertebrates, and zooplankton (NRCC, 1978). Water concentrations may transfer to plants, invertebrates and ultimately fish through the food chain (Leonard, 1991). Invertebrates and algae tend to be more sensitive to As than fish. A detailed review of As toxicity is presented in Moore and Ramamoorthy (1984). Copper (Cu) The rate of weathering of Cu from geological material into soil depends on redox conditions, organic matter, drainage, and pH. Copper is mainly found in soils with high organic carbon and clay contents (Scheinberg, 1991). Humic materials bind more than 90% of Cu in freshwaters (Mantoura et al., 1978). Neither water nor DGT samples 136 indicated detectable levels of dissolved Cu at the sampling sites in the Sumas River watershed. However, background levels of Cu in Sumas River watershed sediments (45 to 61 ppm at the Vedder Mountain reference site) are higher than average levels (26 ppm) in the Vancouver region (Cook, 1994). Cu levels were consistently found above interim sediment quality guidelines in areas most affected by agriculture such as Arnold Slough, Saar Creek, Marshall Creek, and Sumas Canal. Furthermore, Cu levels in Arnold Slough, Saar Creek, and Marshall Creek have significantly increased since 1993/1994, indicating deteriorating sediment quality in these regions. Copper is a heavy metal that is essential to life while at the same time potentially toxic, especially to bacteria and viruses (Scheinberg, 1991). Cu is important in enzyme activities in biological systems and interacts with both nitrogen and sulphur complexes (Kieffer, 1991; Moore and Ramamoorthy, 1984). The L C 5 0 levels of dissolved Cu range from 0.017 - 1.0 mg/L depending on the species of fish, however the presence of calcium ions may decrease toxicity levels somewhat (Moore and Ramamoorthy, 1984). Chronic Cu exposure can lead to a reduction in reproduction rates, growth, energy efficiency, and an increase in oxygen consumption in fish (Waiwood and Beamish, 1978). The absorption of Cu by fish is likely to occur passively rather than through the food chain. Cows, sheep and other ruminants are susceptible to Cu toxicity at levels as low as 8 - 10 ppm in forage (Scheinberg, 1991). This toxicity is not attributable to either swine or poultry. There have been interaction effects noted between Cu and other metals. Specifically, Cu and Zn are more toxic when in the presence of one another than when alone in the aquatic environment (Anderson, 1988; Parrot et al., 1988). Antagonistic relationships exist between Cu, organic matter, and CaCC>3 (Miller and Mackay, 1980). 137 Iron (Fe) Water samples from the Sumas River watershed indicated that Fe was present in levels above water quality guidelines for aquatic organisms (>0.30 mg/L) over the course of the year in the downstream region of the Sumas River, Arnold Slough, Saar Creek, Marshall Creek, Sumas Canal, and Sumas Mountain. Dissolved Fe levels were always low in the headwaters of the Sumas River, Swift Creek, and Vedder Mountain. The DGT results indicated that the highest levels of bioavailable Fe were in Arnold Slough. The likely sources of these high dissolved Fe levels are agricultural runoff and desorption from geological deposits due to lower pH levels at these sites. Iron is abundant in livestock waste, and Safo (1978) showed that leaching of Fe will occur from soils amended with poultry manure. Iron is able to undergo a change in oxidation state, depending on the redox conditions. In reduced conditions Fe is commonly found as Fe + 2 , which can be oxidized to Fe + 3 . In terms of sediments, Fe was higher than the severe effects level (44,000 ppm) in Arnold Slough, Saar Creek, Sumas Canal, and the Sumas Prairie ditches in 1993, 1994, 2003, and 2004. Fe levels were high in the headwaters and downstream areas of the Sumas River in 2003 and 2004. Marshall Creek had levels of Fe above the lowest effects level (>21,000 ppm) and had significantly increased since 1993/94. The Vedder Mountain reference site had Fe levels less than half the severe effects level. Iron is an essential element to aquatic organisms. Problems are more likely to arise due to Fe deficiencies rather than Fe toxicity. However, Fe may be toxic in aquatic environments because it can catalyze the production of a hydroxyl radical, which is a strong oxidizing agent (Huebers, 1991). Solutions containing Fe concentrations exceeding 200 mg/L have been found to be toxic to plants. Unfortunately there is a 138 deficit of information regarding Fe toxicity and fish. Lead (Pb) Lead was not found to be above detection limit (>0.2 mg/L) for water or DGT samples, or at the majority of sediment sampling sites. The Pb levels were higher than interim sediment quality guidelines (>35 ppm) in one of six samples collected from Marshall Creek, three of 28 samples collected from the Sumas River, one of six samples collected from Arnold Slough, two of ten samples collected from Sumas Canal, and five of 19 samples collected from the Sumas Prairie agricultural ditches. These sites are all surrounded by intensive agricultural operations, indicating that the likely source of contamination is from agricultural runoff. Without soluble complexing species present in the water column, Pb will become adsorbed to sediments when pH > 6.0 (Moore and Ramamoorthy, 1984). Both Cu and Mn may increase Pb toxicity in aquatic plants. Pb is moderately toxic to invertebrates: less toxic than Cu, Zn, or Cd but more toxic than Ni, Co, or Mn (Nagpal, 1987). Increases in pH and water hardness will reduce Pb toxicity for aquatic biota. Early fish life stages are more susceptible to Pb toxicity and exposure can result in life-long sensitivity to Pb (Davies et al., 1976). In fish, Pb can affect blood cell health, decrease liver enzyme activities, and lead to spinal deformities (Moore and Ramamoorthy, 1984). Manganese (Mn) The concentration of Mn in surface waters in B.C. commonly varies from 0.01 to 1.7 mg/L in the Coastal Region with an average concentration <0.2 mg/L (MWLAP, 2001c). Health Canada recommends an aesthetic objective of 0.05 mg/L Mn in drinking 139 water to protect against staining and taste problems, but not for toxicity purposes. In the Sumas River watershed, dissolved Mn levels were always lowest in the Vedder Mountain reference site, but often exceeded water quality guidelines in the Sumas River, Arnold Slough, Marshall Creek, Saar Creek, and Sumas Canal. Dissolved Mn levels peaked at 1.10 mg/L in Arnold Slough in June 2004. Sumas Canal consistently had levels >0.20 mg/L. These results are reflected in the DGT results, which indicated the lowest levels of bioavailable Mn at the Vedder Mountain site and the highest levels at the Sumas Canal site. Dissolved Mn is also subject to redox reactions. In it's reduced state it is found as Mn + 2, which can be oxidized to Mn + 4. No sediment quality guidelines currently exist for Mn, however typical sediment levels are 614 ppm in B.C (MWLAP, 2001c). The Vedder Mountain site had levels lower than this, while the headwaters and border regions of the Sumas River, Arnold Slough, Sumas Canal, and Sumas Prairie ditches consistently had levels of Mn higher than average. Manganese is an essential trace element for aquatic and terrestrial biota, and is only slightly to moderately toxic to aquatic organisms in excessive amounts (MWLAP, 2001c). It forms an essential part of the enzyme systems that metabolize proteins and energy in all animals (Schiele, 1991). It is present in almost all organisms, and often reduces the toxicity of other metals. In aquatic environments, Mn toxicity is influenced mainly by water hardness, salinity, pH, redox conditions, and the presence of other contaminants (Schiele, 1991). Chronic toxicity in fish was found to occur at 0.79 mg/L and acute toxicity (96-h LC 5 0) was found to occur 2.4 mg/L in soft water (MWLAP, 2001c). 140 Zinc (Zn) Zinc levels in water rarely exceeded detection limit (>0.01 mg/L) in the Sumas River watershed. Detection limit was occasionally met in Arnold Slough, Marshall Creek, the border area of the Sumas River, Swift Creek, and Sumas Canal. However, DGT results indicated that higher levels of bioavailable Zn were located in Marshall Creek and Arnold Slough than other sites on the majority of sampling occasions. The likely source of Zn in these tributaries is agricultural runoff. In sediments, Zn concentrations exceeded the interim sediment quality guideline of 123 ppm in several of the samples collected from Arnold Slough, Marshall Creek, Sumas Canal, and the Sumas Prairie ditches. Furthermore, since 1993/94 Zn levels have been significantly rising in all regions of the Sumas River, Arnold Slough, Saar Creek, and Marshall Creek. The release of Zn from sediments depends on pH, biological processes, and ligand availability. Humic and fulvic acids do not complex Zn as much as Cu, Ni, or Cr (Moore and Ramamoorthy, 1984), however low DOC levels in Marshall Creek may partly explain why bioavailable levels in are consistently higher in that tributary than in other sites. Zinc is an essential element for many organisms and is vital to the efficiency of several enzymes, hormone metabolism, and the production of nucleic acids (Moore and Ramamoorthy, 1984). Zn is less toxic to fish than Cu or Cd but more toxic than Pb or Ni (Ohnesorge and Wilhelm, 1991). Fish species, stage of development, temperature and DO levels appear to have the most effect on Zn toxicity levels (Nagpal, 1999). Chronic Zn exposure can lead to gill damage, a decrease in oxygen consumption, decrease of blood pH, kidney damage, decrease in growth rate and size and changes in reproductive behaviour (Moore and Ramamoorthy, 1984; Nagpal, 1999). 141 5.4 Interactions Between Land Use and Water and Sediment Quality The intensity of livestock operations (AUE/ha) and the percent of corn cover within a buffer zone were the best indicators of water pollution as a result of agricultural runoff. These two indicators were positively correlated to all nutrients and negatively correlated to DO and pH. AUE/ha was also positively correlated to higher concentrations of most dissolved elements and higher levels of Fe, P, Zn, and Cu in river sediments. In terms of metal bioavailability, AUE/ha was a good indicator of higher levels of bioavailable Zn and Mn. Besides being correlated to nutrients, percent corn cover was also positively correlated to higher levels of DOC, greater specific conductivity, and higher levels of all dissolved elements. Surplus N had varying relationships with water and sediment quality and was not a reliable indicator of environmental degradation. This may be partly due to the fact that the model was designed to be used on a larger region than EAs and therefore the budgets could not be accurately averaged over the entire EA. The percent of forest cover within a buffer zone was the best indicator of water and sediment quality and basically had opposite correlation relationships than AUE/ha or percent corn cover. The amount of clay in sediments had expected relationships to water and sediment quality. Due to the fact that clay particles are negatively charged, they are likely to be positively correlated to anions and negatively correlated to cations. This is because the more negative sites present, the less cations will remain in solution. The results for the correlation analysis confirm this, with percent clay being positively correlated to Cl", N03"-N, and P04 and negatively correlated to NH 4 +-N, dissolved Fe, dissolved Mn, bioavailable Al, and bioavailable Mn. Diagrams depicting the significant relationships between the main land use 142 indicator (AUE/ha) and the main water quality indicator (nitrate) and water and sediment quality are provided in Figures 5.1.1 and 5.1.2. • cr, N0 3 ' -N, P04, NH 4 +-N • Specific Conductivity • Dissolved Fe, Mn, K, Mg • Bioavailable Mn and Zn • Sediment-bound Fe, P, Cu, Zn • Dissolved Oxygen • pH Figure 5.1.1 Relationships between livestock intensity and water and sediment quality indicators. • Cf, P04, NH 4 +-N • Specific Conductivity • DOC • Temperature • All dissolved elements • % Corn Cover • % Pasture Cover • AUE/ha • Nitrogen Surplus • % Clay Content • % Forest Cover • Dissolved Oxygen • pH Figure 5.1.2 Relationships between nitrate, wet season water quality parameters, and land use indicators. 143 Chapter 6 Summary This thesis aimed to explore the relationships between increases in livestock density and water and sediment quality, with an emphasis on spatial and temporal cumulative effects of non-point source pollution. Changes in land cover and livestock density were identified, water and sediment samples were collected and analyzed, and relationships between environmental quality and land use indices were investigated. Comparisons were made between data collected at the same sites in the early 1990s and this data set to determine if significant changes in water and sediment quality had occurred in relation to agricultural intensification. The spatial trends of trace metal bioavailability were explored using DGTs. 6.1 Land Use Agriculture is the predominant use of land throughout the Sumas River watershed. Characteristics of agricultural operations have changed in the last decade and have shifted from smaller-scale dairy farms towards high-density hog and poultry operations. Since 1991, the number of livestock per hectare of land increased dramatically in the areas encompassing the Abbotsford Aquifer region, and substantially in the Sumas Prairie region. This shift has resulted in greater amounts of manure being produced on a relatively unchanged land base. As of 1997, many farms still had insufficient manure storage infrastructure and the waste produced could not be stored sufficiently over the wet winter months. Crop cover trends in Sumas Prairie include increases in specialty crops such as blueberry, nursery, and greenhouse production and decreases in raspberry production. Nutrient budgets are in excess of 200 kg-N/ha, 50 kg-P/ha and 75 kg-K/ha in the Sumas Prairie and Abbotsford Aquifer regions. These 144 land use indicators all suggest that agricultural intensification is placing waterways at risk of contamination. 6.2 Nutrients in Water and Sediment The water and sediment quality of the Sumas River and its tributaries has been significantly degraded since the early 1990s. Poor water quality appears to be exacerbated directly after the first large rainstorms in the fall, which flush manure and fertilizer residues from fields into adjacent waterways. Nitrate levels have increased significantly since 1993 during the wet season in rivers surrounded by intensive agricultural operations such as the Sumas River, Sumas Canal, Arnold Slough, and Saar Creek. Historic nitrate levels are an indicator of temporal cumulative effects of agricultural NPS pollution. Marshall Creek displayed opposite seasonal trends in nitrate in comparison to most tributaries due to its influence by the Abbotsford Aquifer. During the summer months the Abbotsford Aquifer contributes proportionally more water to Marshall Creek, therefore nitrate levels are higher in the dry summer months and become diluted duing the wet season. These trends correspond well with results found by Berka (1996). There has been a significant increase in ammonia levels since 1993 in the Sumas Canal and levels now exceed provincial water quality guidelines. Dissolved phosphorus, which is often the most limiting nutrient in aquatic environments, was generally not found above detection limits at the majority of sites. Dissolved potassium was significantly higher in Arnold Slough than all other tributaries. Excessive eutrophication in the from of substantial algal growth was witnessed during the warm summer months in Arnold Slough, Sumas Canal, and the downstream regions of the 145 Sumas River and Marshall Creek. This algal growth contributed to extremely low levels of DO in Arnold Slough. During the wet season, higher levels of nutrients were significantly correlated to lower DO and pH levels and higher DOC and specific conductivity levels. Sampling sites not characterized by agricultural activities such as Swift Creek, Sumas Mountain, and Vedder Mountain, had the lowest nutrients levels. Phosphorus and potassium were also detected in sediments. Sediment-bound phosphorus was detected at significantly higher levels in Arnold Slough and Sumas Prairie agricultural ditches than in other sites. Downstream reaches of the Sumas River had higher levels of both phosphorus and potassium in sediment collected in 2003/04 than in 1993/94, reflecting the temporal and spatial cumulative effects of agricultural intensification in the watershed. 6.3 Metals in Water (Dissolved and Bioavailable) and Sediment Two main categories of metals were identified in the Sumas River: those associated with a naturally-occurring asbestos landslide (Cr, Co, Mg, and Ni) and those associated with agricultural operations (Fe, Mn, Cu, and Zn). In the water samples, dissolved Cr, Co, and Ni were always below detection limits. The highest levels of bioavailable Ni were detected in DGTs deployed directly downstream from the confluence of Swift Creek and levels then decreased consistently in the downstream direction. Extremely high levels of Ni, Cr, and Co were present in the sediments of Swift Creek and the Sumas River directly downstream from the confluence. Sediment samples often exceeded B.C. interim sediment quality guidelines for Cr, Co, and Ni in these waterways. Arnold Slough and the Sumas Prairie agricultural ditches also had elevated Ni concentrations in sediments, the source of which is likely agricultural runoff. 146 The highest levels of dissolved Fe and Mn were in Arnold Slough and the Sumas Canal, often under conditions of low DO. Saar Creek and the Sumas River also had elevated levels of dissolved Fe and Mn. The lowest levels were found in the Vedder Mountain reference site. Dissolved Cu and Zn were nearly always below detection limit at all sites. The use of DGTs provided an appropriate indicator of spatial trends in the bioavailability of trace metals throughout the watershed. Bioavailable Fe was highest in Arnold Slough, followed by the Swift Creek confluence and Vedder Mountain sites. It is likely that the source of bioavailable Fe in the latter two sites is geological. Bioavailable Mn was highest in the Sumas Canal, followed by the Sumas River downstream from the Swift Creek confluence, Marshall Creek, and Arnold Slough. Marshall Creek had the highest levels of bioavailable Zn, followed by Arnold Slough. Bioavailable Fe and Zn were positively correlated to the total precipitation that fell during the deployment period. The first major storm event of the rainy season in October 2003 resulted in the highest bioavailable Zn levels in Sumas Canal, Arnold Slough, and Marshall Creek, indicating that the most likely source is agricultural runoff. Sediment-bound Cu and Zn levels were higher in Arnold Slough than all other sites. Background Cu levels in sediment from Vedder Mountain were moderately high, which is in keeping with much of the underlying geology of the region. The headwaters of the Sumas River, which are characterized by intensive dairy operations, had the highest levels of sediment-bound Mn. Sediment samples from Swift Creek and Vedder Mountain reference sites had the lowest levels of Fe, Mn, and Zn. Since 1993, Cu, Fe, and Zn levels have increased in the sediments of Saar Creek, Arnold Slough, Marshall Creek, and the downstream region of the Sumas River, indicating deterioration in sediment quality as a result of agricultural intensification. Sumas Canal has experienced increases in the levels of sediment-bound 147 Cu since 1993. Sodium, which is associated with agricultural manures, has increased in the sediments of the Sumas River, Arnold Slough, Saar Creek, and Marshall Creek. Significant, positive relationships were found between bioavailable and sediment-bound Zn, bioavailable and sediment-bound Ni, dissolved and sediment-bound Fe, and between all three fractions (dissolved, bioavailable, and sediment-bound) of Mn. It is worth noting that some sites with low dissolved Zn concentrations (below detection limit) such as Arnold Slough and Marshall Creek had very high bioavailable Zn levels as measured by the DGTs. This indicates that monthly water sampling may miss flushes of higher dissolved metal concentrations from storm events and fail to account for the accumulation of chronic, low levels of metals over time. 6.4 Links Between Land Use and Water Quality Land use indicators were identified for each water sampling site by creating buffers around the sites using a GIS. Livestock density (AUE/ha) was the best indicator of envrionmental pollution as it was significantly correlated to high levels of nutrients (Cl", N03"-N, NhV-N, P04) and specific conductivity, low DO and pH, high levels of the majority of dissolved elements, higher bioavailability of Zn and Mn, and high levels of sediment-bound Fe, P, Zn, and Cu. Based on the results from this study, long-term temporal and spatial trends indicate that agricultural intensification is clearly leading to the deterioration of water and sediment quality in the Sumas River watershed. Despite attempts by local organizations such as the Sustainable Poultry Farmer's Group to export manure to nutrient-deficient regions, the lack of long-term manure storage capabilities on many farms coupled with a wet climate is leading to the destruction of fish habitat due to 148 agricultural runoff. The critical state of water quality in the Sumas River watershed warrants attention not only from private landowners but also from all levels of government. 149 Chapter 7 Recommendations At this point, the Sumas River watershed has been the subject of many studies and the general consensus is that NPS pollution from agriculture is leading to the deterioration of water and sediment, thereby directly harming fish habitat and the potential for recreation. The reduction of agricultural runoff in the Sumas River watershed requires a policy shift at the provincial and municipal levels. Several jurisdictions have gone through the process of policy reform with respect to agriculture and the environment. Ontario, spurred into action by the Walkerton tragedy of 2000, has introduced the Nutrient Management Act (NMA). Ontario's NMA is intended to provide standards for managing fertilizer and manure management with the goal of reducing NPS water pollution (OMAF, 2002). Several European countries have also adopted progressive agricultural policies. OMAF (2003) has reviewed much of the European guidelines and practices with regards to manure management. In Denmark, farmers are required to develop buffer zones between farm fields and all watercourses and to create nutrient budgets that prove that they have sufficient manure storage capacity so that waste applications during the winter months are minimized. In order to reduce costs associated with manure storage infrastructure, excess manure is sold to local biogas production plants. These policies are enforced and farmers are fined if nutrient quotas are exceeded. Germany also uses economic incentives to discourage intensive farming operations. Government grants and livestock sale prices are higher for farms that have fewer than 2.0 AUE/ha. Recently, the UK government announced that it will be introducing taxes on fertilizer and nutrient surpluses (DEFRA, 2004) and Denmark announced that it will apply taxes on excess phosphorus in animal feeds (SKAT, 2004). These are some 150 examples of governments who have taken a proactive approach to reducing the impacts of agriculture on the environment without reducing farmer's economic benefits. The Province of B.C. would do well to use these creative policies as templates for tools for improving the current state of agricultural NPS pollution in vulnerable watersheds such as the Sumas River. 151 References Abdulrahim, S.M., M.S.Y. Haddadin, N.H.M. Odetallah, and R.K. Robinson. 1999. Effect of Lactobacillus acidophilus and zinc bacitracin as dietary additives for broiler chickens. British Poultry Science 40:91-94. Addah, J . 2003. The impact of agricultural land uses on water and sediment quality in the Agassiz/Harrison Hot Springs watershed, B.C. 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Trace metal levels in livestock and poultry feed. Table A3. Nutrient and trace metal levels in poultry manure. Table A4. Nutrient and trace metal levels in livestock manure. 161 Table A1. Trace metal levels in various fertilizers Element (ppm) A s C d Cr C u Ni Pb Zn Range <1-11 <0.1-8.1 <1.0-83 1.0-12.0 <1-20 0.2-9.9 1.0-94 Source (Table A1): McBride and Spiers, 2001 Table A2. Trace metal levels in livestock and poultry feed Element Poultry Pigs Beef Cattle Dairy C o w s A s (ppm) O.1-0.4 0.3-0.4 0.5 0.4 C d (ppm) 0.1-0.4 O.1-0.2 0.3 0.2 Cr (ppm) 0.2-2.1 0.4-1.3 0.1-0.83 1.7 2.1 C u (ppm) 19.9-36.1 125-250b 28.5-185 34.6 42.2 Pb (ppm) <1.0 <1.0-2.1 <1.0 2.0 Ni (ppm) 1.8-2.6 1.2-3.1 3.1 2.8 Zn (ppm) 108-155 177-2194 50-100a 189 129 Source (Table A2): Nicholson et al. (1999) unless stated otherwise a: Brumm, 1998 b: Miller et al., 1986 Table A3. Nutrient and trace metal levels in poultry manure. N P K Mg Ca Na Al A s C d % % % % % % ppm ppm ppm 3.5d 1.6° 1.6d 0.4d 1.5d 0.7f 579b 0.5-9.09 <0.2f 4 0 a , b . c 1.7a 1.9a 0.5C 2.3° 0.8b 4-40m 0.4-1.19 2.1b 2.3C 0.6f 2.7f 19f 0.5b 2.5d 2.6f 0.7b 2.8b 29 b 6.11 2.7b 30-37j 35' 43 k Table A3 continued Cr C u Fe Pb Mn Ni Zn ppm ppm ppm ppm ppm ppm ppm 3.2f 0-232h 801 d 1.9' 257d 1.0f 0-669h 4.6-17.29 35-979 1144b 3.6-8.49 348c 3.6-8.49 280d 39 d 1596f 356 f 315C 55" 2377c 671 b 349-5119 410 f 371 f 473 c 5011 613b 543b 743' 631' 748k 647" 1196' 718k 162 Table A4. Nutrient and trace metal levels of livestock manure Element Pigs Beef Dairy N (%) 7.6a 3.3a 4.0a P (%) 1.8" 1.0a 0.7a 0.8e K(%) 2.6a 2.1a 3.2a 0.4e C d (ppm) 0.3-0.49 0.1-0.39 0.3-0.49 0.2e Pb (ppm) 2.5-2.99 2.0-7.19 3.6-5.99 2.2e Cr (ppm) 2.0-2.89 1,4-4.79 5.3-5.69 4.6e A s (ppm) 0.9-1.79 0.8-2.69 1.4-1.69 1.3e C u (ppm) 22-15759 16.4-33.29 37.5-62.39 139e Zn (ppm) 128-9819 81-1339 153-2099 191e Ni (ppm) 7.5-10.49 2.0-6.49 3.7-5.49 8.0e g: compiled by Nicholson et al., 1999 m: Isaac et al., 1976 h: Sims and Wolf, 1994 n: Edwards et al., 1997 i: Westing etai., 1985 j: Van der Watt et al., 1994 I: Jackson et al., 1999 k: Moore et al., 1998 Sources (Tables A3 and A4): a: Sharpley et al., 1998 b: Smith etai., 1992. c: Ruffin and McCaskey, 1990 d: Chipperfield, 1994 e: McBride and Spiers, 2001 f: Kpomblekou-A et al., 2002 163 Appendix B: Land use and land cover maps of the Sumas River watershed Figure B1. Map of Abbotsford, B.C. Census region indicating 1996 Enumeration Areas. Figure B2. Map of Abbotsford, B.C. Census region indicating 2001 Enumeration Areas. Figure B3. Land use in the Canadian portion of the Sumas River watershed (1988). Figure B4. Land use in the Canadian portion of the Sumas River watershed (1995). Figure B5. Land use in the Canadian portion of the Sumas River watershed (2002). Figure B6. Crop cover in the Sumas Prairie (2003). 164 165 166 167 168 169 170 Appendix C: Water Sampling Results Table C1. QA/QC Results for water samples: nutrients, pH, and dissolved organic carbon. Table C2. QA/QC Results for water samples: dissolved elements. Tables C3 to C6. Nutrient (mg/L) results. Tables C7 to C11. Physical parameter results. Table C12.Wet and dry season medians of nutrient and physical parameter results. Tables C13 to C21. Dissolved elements (ppm) results. Figures C1 to C4. Boxplots of nutrient results by site and by date. Figures C5 to C9. Boxplots of physical parameter results by site and by date. Figures C10 to C16. Boxplots of dissolved element results by site and by date. 171 Quality Control/Quality Analysis, Raw Data, Boxplots by Site, Boxplots by Date Table C1. QA/QC Results for water samples: nutrients, pH, and dissolved organic carbon Date Site # cr N 0 3 - N NH 4 + -N Ortho-P pH D O C mg/L mg/L mg/L mg/L mg/L mg/L 07/05/2003 6 - 1.79 0.26 0.07 7.37 -- 1.65 0.29 0.08 7.32 -- 2.02 0.35 0.09 7.29 -Average - 1.82 0.30 0.08 7.33 -Standard Deviation - 0.19 0.05 0.01 0.04 -Coefficient of Variation (%) - 10.22 15.62 9.18 0.55 -07/07/2003 7 20.00 0.74 0.42 <0.02 8.50 -19.73 0.76 0.38 <0.02 8.63 -19.96 0.76 0.15 <0.02 8.65 -Average 19.90 0.75 0.31 <0.02 8.59 -Standard Deviation 0.15 0.01 0.15 N/A 0.08 -Coefficient of Variation (%) 0.74 1.32 46.83 N/A 0.95 -26/08/2003 7 22.24 0.57 <0.10 O.02 8.73 5.00 22.38 0.56 <0.10 <0.02 8.75 4.80 21.43 0.57 0.10 <0.02 8.82 4.50 Average 22.02 0.57 N/A <0.02 8.77 4.77 Standard Deviation 0.51 0.00 N/A N/A 0.05 0.25 Coefficient of Variation (%) 2.34 0.64 N/A N/A 0.54 5.28 14/10/2003 6 15.35 1.54 0.48 0.02 7.39 4.00 15.27 1.52 0.35 0.02 7.41 4.10 Average 15.31 1.53 0.42 0.02 7.40 4.05 Standard Deviation 0.06 0.02 0.09 0.00 0.01 0.07 Coefficient of Variation (%) 0.39 1.15 21.75 3.96 0.19 1.75 30/10/2003 6 17.64 3.37 0.27 0.06 6.68 7.70 17.95 3.29 0.32 0.07 6.65 7.50 18.01 3.38 0.30 0.06 6.66 7.50 Average 17.87 3.35 0.29 0.06 6.66 7.57 Standard Deviation 0.20 0.05 0.03 0.00 0.02 0.12 Coefficient of Variation (%) 1.12 1.52 9.16 5.48 0.23 1.53 24/11/2003 1 11.58 0.45 0.30 <0.02 7.92 1.00 11.87 0.45 0.10 <0.02 8.08 1.10 11.63 0.44 0.12 <0.02 8.12 1.20 Average 11.69 0.45 0.17 <0.02 8.04 1.10 Standard Deviation 0.2 0.16 0.09 N/A 0.09 0.08 Coefficient of Variation (%) 1.4 1.36 51.89 N/A 1.07 7.42 172 Table C1 continued Date Site # Cl" N 0 3 - N NH 4 + -N Ortho-P PH D O C mg/L mg/L mg/L mg/L mg/L mg/L 10/12/2003 12 15.84 3.04 0.19 0.03 7.18 -15.85 3.05 0.19 0.03 7.28 -15.70 3.01 0.21 0.03 7.24 -Average 15.79 3.04 0.20 0.03 7.23 -Standard Deviation 0.08 0.02 0.01 0.00 0.05 -Coefficient of Variation (%) 0.53 0.65 5.48 0.00 0.70 _ 12/01/2004 4 14.72 3.98 0.17 0.07 7.39 6.34 13.52 3.93 0.10 0.06 7.36 6.35 13.38 3.91 0.11 0.06 7.38 6.27 Average 13.88 3.94 0.13 0.06 7.38 6.32 Standard Deviation 0.74 0.03 0.04 0.00 0.02 0.04 Coefficient of Variation (%) 5.31 0.89 29.93 7.35 0.21 0.66 02/02/2004 16 10.90 1.79 <0.1 0.04 7.04 5.07 10.84 1.78 <0.1 0.04 7.04 5.08 11.02 1.76 <0.1 0.04 7.05 5.08 Average 10.92 1.78 <0.1 0.04 7.04 5.08 Standard Deviation 0.09 0.02 N/A 0.00 0.01 0.01 Coefficient of Variation (%) 0.85 1.03 N/A 0.82 0.08 0.11 01/03/2004 9 12.75 1.32 1.56 <0.02 7.15 3.09 12.60 1.33 1.47 <0.02 7.15 3.02 12.33 1.31 1.45 0.02 7.16 3.03 Average 12.56 1.32 1.49 N/A 7.15 3.05 Standard Deviation 0.21 0.01 0.06 N/A 0.01 0.04 Coefficient of Variation (%) 1.69 0.73 4.20 N/A 0.08 1.35 22/03/2004 13 16.10 6.50 0.22 <0.02 7.18 1.70 16.23 6.70 0.21 <0.02 7.22 1.60 Average 16.16 6.60 0.22 <0.02 7.20 1.65 Standard Deviation 0.09 0.14 0.00 N/A 0.03 0.07 Coefficient of Variation (%) 0.54 2.12 1.67 N/A 0.39 4.29 19/04/2004 19 <6 0.43 <0.1 <0.02 7.89 0.97 <6 0.44 <0.1 <0.02 7.87 0.91 <6 0.44 <0.1 <0.02 7.85 0.97 Average <6 0.44 <0.1 <0.02 7.87 0.95 Standard Deviation N/A 0.01 N/A N/A 0.02 0.03 Coefficient of Variation (%) N/A 1.53 N/A N/A 0.25 3.65 17/05/2004 2 17.2 0.79 0.10 0.02 7.42 2.10 16.9 0.79 0.10 0.02 7.33 1.98 17.1 0.79 0.09 0.02 7.31 2.09 Average 17.07 0.79 0.10 0.02 7.35 2.06 Standard Deviation 0.14 0.00 0.01 0.00 0.06 0.07 Coefficient of Variation (%) 0.80 0.39 5.98 2.62 0.80 3.24 173 Table C1 continued Date Site # cr N0 3 ' -N NH 4 + -N Ortho-P PH D O C mg/L mg/L mg/L mg/L mg/L mg/L 07/06/2004 3 16.9 2.64 0.19 0.03 7.50 3.60 17.0 2.66 0.17 0.03 7.52 3.54 17.0 2.68 0.16 0.03 7.56 3.51 Average 16.97 2.66 0.17 0.03 7.53 3.55 Standard Deviation 0.05 0.02 0.02 0.00 0.03 0.05 Coefficient of Variation (%) 0.32 0.90 9.24 0.72 0.41 1.29 Table C2. QA/QC Results for water samples: dissolved elements. (Std Dev: Standard Deviation, CoV: Coefficient of Variation) Date Site# Al C a Fe K Mg Mn Na Si Zn ppm ppm ppm ppm ppm ppm ppm ppm ppm 07/05/2003 6 <0.05 - 0.62 - 0.061 - 8.53 <0.01 <0.05 - 0.51 - - 0.056 - 8.49 <0.01 <0.05 - 0.65 - - 0.066 - 8.54 <0.01 Average <0.05 - 0.59 - - 0.06 - 8.52 <0.01 Std Dev N/A - 0.08 - 0.00 0.02 N/A C o V (%) N/A - 12.78 - 8.13 0.29 N/A 07/07/2003 7 <0.05 21.52 0.06 2.32 15.18 <0.005 10.47 7.69 <0.01 <0.05 21.55 0.06 2.30 15.13 <0.005 10.49 7.74 <0.01 <0.05 21.31 0.06 2.29 15.07 <0.005 10.51 7.65 <0.01 Average <0.05 21.46 0.06 2.30 15.13 <0.005 10.49 7.69 <0.01 Std Dev N/A 0.13 0.00 0.01 0.05 N/A 0.02 0.05 N/A C o V (%) N/A 0.63 0.00 0.64 0.34 N/A 0.19 0.60 N/A 26/08/2003 7 <0.05 25.67 0.05 2.10 15.58 0.013 11.38 6.12 <0.01 <0.05 25.65 0.05 2.09 15.65 0.010 11.59 6.21 <0.01 <0.05 25.72 O.05 2.09 15.68 <0.005 11.29 6.13 <0.01 Average <0.05 25.68 N/A 2.10 15.64 0.01 11.42 6.16 <0.01 Std Dev N/A 0.04 N/A 0.00 0.05 0.00 0.15 0.05 N/A C o V (%) N/A 0.14 N/A 0.13 0.35 17.85 1.33 0.79 N/A 14/10/2003 6 <0.05 17.15 0.49 3.02 13.13 0.045 8.02 8.26 <0.01 <0.05 16.80 0.51 2.97 12.75 0.043 7.95 8.06 <0.01 Average <0.05 16.97 0.50 3.00 12.94 0.04 7.99 8.16 <0.01 Std Dev N/A 0.24 0.24 0.03 0.27 0.00 0.05 0.14 N/A C o V (%) N/A 1.44 1.44 1.04 2.10 3.79 0.60 1.75 N/A 30/10/2003 6 0.06 17.61 0.43 5.30 17.87 0.045 9.30 10.21 O.01 0.06 17.53 0.43 5.26 17.84 0.044 9.20 10.15 <0.01 0.06 17.52 0.42 5.32 17.83 0.044 9.23 10.18 0.01 Average 0.06 17.55 0.43 5.29 17.85 0.04 9.24 10.18 <0.01 Std Dev 0.00 0.05 0.01 0.03 0.02 0.00 0.05 0.03 N/A C o V (%) 0.00 0.28 1.68 0.60 0.12 1.80 0.56 0.30 N/A 174 Table C2 continued Date Site# Al C a Fe K Mg Mn Na Si Zn ppm ppm ppm ppm ppm ppm ppm ppm ppm 24/11/2003 1 0.05 5.92 0.06 0.61 18.28 0.008 3.10 4.25 <0.01 <0.05 5.79 <0.05 0.57 17.48 0.008 3.03 4.02 <0.01 <0.05 5.65 <0.05 0.56 17.60 0.007 2.98 4.06 <0.01 Average N/A 5.79 N/A 0.58 17.79 0.01 3.04 4.11 <0.01 Std Dev N/A 0.14 N/A 0.03 0.43 0.00 0.06 0.12 N/A C o V (%) N/A 2.34 N/A 4.97 2.42 6.52 1.97 3.01 N/A 10/12/2003 12 0.05 16.07 0.68 3.64 20.43 0.077 8.87 11.58 <0.01 0.06 15.85 0.73 3.58 20.10 0.076 8.72 11.43 <0.01 0.05 15.50 0.61 3.59 19.77 0.073 8.65 11.31 <0.01 Average 0.05 15.80 0.67 3.60 20.10 0.08 8.75 11.44 <0.01 Std Dev 0.01 0.29 0.06 0.03 0.33 0.00 0.11 0.14 N/A C o V (%) 12.56 1.83 9.24 0.89 1.65 2.86 1.26 1.18 N/A 12/01/2004 4 0.11 12.66 0.29 3.94 17.51 0.023 7.76 7.75 O.01 0.13 13.16 0.34 3.84 18.11 0.024 7.42 7.85 <0.01 0.15 13.13 0.36 3.85 18.10 0.025 7.34 7.86 <0.01 Average 0.13 12.98 0.33 3.88 17.91 0.02 7.51 7.82 <0.01 Std Dev 0.02 0.28 0.03 0.05 0.34 0.00 0.22 0.06 N/A C o V (%) 14.98 2.13 10.29 1.36 1.90 3.41 2.97 0.75 N/A 02/02/2004 16 <0.05 13.99 0.14 1.81 16.38 0.006 6.51 9.35 <0.01 <0.05 13.93 0.15 1.85 16.45 0.005 6.54 9.45 <0.01 <0.05 14.20 0.14 1.85 16.65 0.006 6.62 9.50 <0.01 Average <0.05 14.04 0.14 1.83 16.49 0.01 6.56 9.44 <0.01 Std Dev N/A 0.15 0.01 0.02 0.14 0.00 0.06 0.08 N/A C o V (%) N/A 1.03 5.72 1.36 0.85 2.04 0.88 0.81 N/A 01/03/2004 9 <0.05 19.42 0.53 2.38 17.37 0.258 6.97 14.27 <0.01 <0.05 19.22 1.30 2.33 17.10 0.259 6.85 14.13 <0.01 <0.05 19.32 1.56 2.32 17.10 0.259 6.76 14.08 0.02 Average <0.05 19.32 1.13 2.34 17.19 0.26 6.86 14.16 N/A Std Dev N/A 0.10 0.53 0.04 0.15 0.00 0.10 0.10 N/A C o V (%) N/A 0.49 47.18 1.54 0.90 0.12 1.53 0.68 N/A 22/03/2004 13 <0.05 27.85 0.17 1.52 7.75 0.059 9.04 8.19 <0.01 <0.05 28.35 0.17 1.54 7.86 0.058 8.87 8.20 <0.01 Average <0.05 28.10 0.17 1.53 7.80 0.06 8.96 8.19 <0.01 Std Dev N/A 0.36 0.00 0.02 0.08 0.00 0.12 0.00 N/A C o V (%) N/A 1.26 0.80 1.35 1.07 1.61 1.28 0.05 N/A 19/04/2004 19 <0.05 15.97 <0.05 <0.5 3.28 O.005 2.08 3.82 <0.01 <0.05 16.13 <0.05 <0.5 3.31 <0.005 1.98 3.84 <0.01 <0.05 16.09 O.05 <0.5 3.32 O.005 1.94 3.86 <0.01 Average <0.05 16.06 <0.05 <0.5 3.30 <0.005 2.00 3.84 <0.01 Std Dev N/A 0.09 N/A N/A 0.02 N/A 0.07 0.02 N/A C o V (%) N/A 0.54 N/A N/A 0.63 N/A 3.59 0.53 N/A 175 Table C2 continued Date Site# Al C a Fe K Mg Mn Na Si Zn ppm ppm ppm ppm ppm ppm ppm ppm ppm 17/05/2004 2 <0.05 17.41 0.16 0.94 26.67 0.118 9.66 10.90 0.01 <0.05 17.39 0.17 0.92 26.72 0.117 9.48 10.88 <0.01 <0.05 17.38 0.17 0.91 26.82 0.116 9.46 10.99 <0.01 Average <0.05 17.39 0.17 0.92 26.74 0.12 9.54 10.92 N/A Std Dev N/A 0.02 0.00 0.02 0.08 0.00 0.11 0.06 N/A C o V (%) N/A 0.10 2.12 1.64 0.28 0.87 1.17 0.55 N/A 07/06/2004 3 <0.05 20.86 0.35 2.17 20.15 0.071 9.84 9.83 0.01 <0.05 20.85 0.42 2.16 20.20 0.071 9.90 9.90 0.01 <0.05 20.99 0.35 2.16 20.26 0.071 10.08 9.90 0.01 Average <0.05 20.90 0.37 2.17 20.20 0.07 9.94 9.88 0.01 Std Dev N/A 0.08 0.04 0.01 0.06 0.00 0.12 0.04 N/A C o V (%) N/A 0.38 10.16 0.24 0.28 0.30 1.24 0.43 N/A 176 7-Jun 2004 12.2 15.7 12.6 16.9 17.5 16.5 19.1 18.2 12.2 18.1 17.0 cd 15.0 23.7 15.4 13.2 co CO <6.0 17-May 2004 13.3 17.2 15.4 19.9 20.9 19.9 20.0 19.8 17.0 18.0 17.2 14.8 14.7 22.4 16.0 11.2 o CO <6.0 19-Apr 2004 12.9 15.9 13.4 18.0 18.2 15.9 17.3 19.2 12.0 17.1 11.9 o i 15.7 26.0 l 11.0 <6.0 <6.0 22-Mar 2004 12.3 ! 14.8 | 11.7 16.9 17.0 13.9 16.9 17.0 CO co 15.9 15.1 oo CO 16.1 28.7 15.1 12.8 <6.0 <6.0 1-Mar 2004 13.4 16.4 13.2 18.7 18.6 15.5 19.1 19.6 10.2 15.8 15.3 CD 00 16.4 33.5 12.8 12.8 cd <6.0 2-Feb 2004 10.9 12.1 LO o i 14.0 14.3 11.9 15.0 14.4 co t-^ 13.4 13.7 <6.0 20.4 32.4 13.4 13.0 <6.0 <6.0 12-Jan 2004 10.5 12.0 CM a i 13.8 14.7 11.6 15.0 15.5 co 15.8 15.9 <6.0 30.9 38.8 13.6 13.3 co <6.0 10-Dec 2003 12.9 14.5 11.9 18.1 18.7 15.8 16.8 17.8 10.0 14.9 14.4 o> 15.0 29.2 13.0 12.2 <6.0 <6.0 24-Nov 2003 oo co LO LO CM T— CO T i -ed O) CD LO O) CO cq T— o T f 0 91 LO LO CO 21.7 co CO h-CO CD cd <6.0 30-Oct 2003 14.4 16.8 14.3 18.2 17.8 16.3 17.6 18.1 13.6 15.9 16.7 CO co 15.7 29.1 1.5.6 15.3 CD t v ! <6.0 14-Oct 2003 LO CO o o i OSI-oo LO 23.4 CO co T t LO o CO CO oo T f cd CO T f LO CO o i iri T f co T— CO <6.0 26-Aug 2003 15.2 18.4 17.4 21.0 22.8 21.3 19.9 22.2 26.0 16.8 17.8 23.5 15.7 18.5 20.6 19.2 11.6 <6.0 7-Jul 2003 13.5 16.6 15.6 20.4 21.6 19.8 19.8 20.0 16.3 16.1 17.3 18.4 15.0 23.6 16.8 13.0 10.6 I 5-May 2003 l l l l • 1 1 l l • l 1 • l l l l • Tributary Name (Site ID) Sumas River (16) Sumas River (2) Sumas River (18) Sumas River (3) Sumas River (4) Sumas River (12) Sumas River (6) Sumas River (7) Swift Creek (1) Arnold Slough (10) Arnold Slough (11) Saar Creek (14) Marshall Creek (13) Marshall Creek (5) Sumas Canal (9) Sumas Canal (8) Sumas Mountain (15) Reference (19) 177 CO 7-Jun 2004 0.75 0.46 0.66 2.64 2.57 1.65 2.38 2.21 0.19 0.06 0.23 0.42 4.87 4.67 1.05 0.64 0.31 0.31 17-May 2004 1.27 0.79 1.08 3.57 3.45 2.64 3.36 2.42 0.15 0.42 0.27 0.56 7.54 6.06 1.14 0.73 0.63 0.47 19-Apr 2004 1.20 0.65 1.00 3.40 3.26 2.41 I 2.90 2.55 0.23 0.61 0.70 0.70 6.43 4.60 • 1.23 0.27 0.43 22-Mar 2004 1.53 0.89 1.23 3.77 3.77 2.36 3.20 3.09 0.32 1.43 1.45 1.37 6.50 4.93 1.60 1.33 0.61 0.52 1-Mar 2004 1.81 1.03 1.31 3.86 3.75 2.25 3.36 3.21 0.31 1.26 1.20 1.31 6.54 5.11 1.45 1.32 0.57 0.47 2-Feb 2004 1.79 1.08 1.42 4.02 4.14 3.24 3.61 3.65 0.48 2.69 3.00 2.08 5.95 5.05 2.24 2.04 1.28 0.62 12-Jan 2004 1.58 1.02 1.29 3.93 3.98 2.89 3.52 3.43 0.48 2.73 3.35 1.67 4.77 5.70 2.28 2.02 0.94 0.60 10-Dec 2003 1.86 1.03 1.29 3.79 3.75 3.04 3.23 3.20 0.39 2.32 2.55 2.00 5.31 5.33 2.49 2.02 0.89 0.54 24-Nov 2003 2.15 1.08 1.30 4.63 4.92 4.05 4.54 4.51 0.45 3.55 6.04 2.24 2.55 4.50 2.83 2.73 1.14 0.60 30-Oct 2003 1.28 0.65 0.99 3.66 3.53 2.95 3.37 3.22 0.36 2.42 4.51 2.26 6.71 5.16 3.06 3.32 0.47 0.48 14-Oct 2003 0.89 0.58 0.67 1.97 1.61 2.01 1.54 2.07 0.53 <0.10 <0.10 1.35 6.52 2.97 1.21 0.59 <0.10 0.45 26-Aug 2003 1.61 0.91 1.10 2.84 2.25 1.17 3.39 0.57 <0.10 <0.10 <0.10 <0.10 9.85 7.39 <0.10 <0.10 <0.10 0.43 7-Jul 2003 1.15 0.69 1.01 2.85 2.53 1.51 1.85 0.74 0.19 0.14 <0.10 0.37 6.85 4.57 0.46 0.26 0.30 • 5-May 2003 0.86 0.51 l 2.22 2.16 1.41 1.79 2.01 0.32 0.57 0.66 0.79 4.74 3.72 1.34 1.23 0.47 • Tributary Name (Site ID) Sumas River (16) Sumas River (2) Sumas River (18) Sumas River (3) Sumas River (4) Sumas River (12) Sumas River (6) Sumas River (7) s o Arnold Slough (10) Arnold Slough (11) Saar Creek (14) Marshall Creek (13) Marshall Creek (5) Sumas Canal (9) Sumas Canal (8) Sumas Mountain (15) Reference (19) 178 7 ° d o d co N-d in CM o V ra S 2 • o r-- CN o d d o v LO LO d o v a r t i ° en CN co d O) o d CM d o v oo CM d O) CM d o v ra T t 5 2 • o CM CM CM T t d co CD o V 5 s s § CM co CD oSl O) o o V - Q T t LL. g CM ™ o V CO d o v T t CD d o LO LO co o V ss CM CM o V o V CO d CD d oo o CD 00 o CM d co CM o V u a) co a o • o O CM CM d CN CN o V T t CN LO co T? o V > O CO z 2 • o T t CM CM co d LO CO CM CO co CD d co d u co O o co CM r--d CM CM d T t o V o d o co O o • o T t CN T t 1 ^ CD CM d co co CM T t d O) 3 CO < ° i o CO CM CM CM d T t T— d CD o V CM o V o d o V LO d o V 3 in 0 CD E, co 'c o E E < LO o JD co ~ o r- CM o CO CM >» en «s 2 O tn ™ g ** w 0 E ra z ra o V o V o d T t d T t co CO d LO t -o V CO CM I I 00 I c o l CM Q) > I |5 (0 ra E 3 CO > cE (0 ra E 3 CO 0) > cE (A ra E 3 CO 0) > | E (0 ra E 3 I CD I Q) > (2 (A ra E 3 CO > (A ra E 3 CO o ICO Is o c §»' o CO o c 0) £ ra £ ra 21 re c re o (A re E 3 CO C O I 75 c , ™ IO (A ra E 3 CO ra e 3 O I S (A ra E 3 CO o c 0) CO It 179 tn •»-» E O 7-Jun 2004 0.04 0.02 <0.02 0.03 0.03 0.02 0.02 0.02 <0.02 0.02 <0.02 <0.02 <0.02 O.02 <0.02 <0.02 <0.02 <0.02 17-May 2004 0.03 0.02 0.02 0.03 0.02 0.02 0.02 <0.02 <0.02 CM O d V <0.02 0.02 0.02 <0.02 <0.02 0.02 <0.02 <0.02 19-Apr 2004 0.03 0.02 <0.02 0.03 0.03 0.02 0.02 0.02 O.02 0.02 <0.02 0.02 0.02 0.02 l 0.02 <0.02 <0.02 22-Mar 2004 0.03 0.02 0.02 0.03 0.03 0.02 0.02 0.02 <0.02 0.019 <0.02 0.02 <0.02 0.02 <0.02 <0.02 <0.02 <0.02 1-Mar 2004 <0.02 0.02 0.02 0.03 0.03 0.02 0.04 0.02 <0.02 0.02 <0.02 0.03 <0.02 0.30 <0.02 <0.02 <0.02 <0.02 2-Feb 2004 0.04 0.02 <0.02 0.06 0.06 0.04 0.05 0.04 <0.02 0.02 0.02 0.02 <0.02 0.09 0.02 <0.02 <0.02 <0.02 12-Jan 2004 0.03 0.02 0.02 0.04 0.07 0.03 0.03 0.03 O.02 0.02 0.02 0.02 <0.02 0.03 <0.02 0.02 <0.02 <0.02 10-Dec 2003 0.03 0.02 0.02 0.04 0.04 0.03 0.02 0.03 <0.02 0.02 0.02 0.02 <0.02 0.02 <0.02 <0.02 <0.02 <0.02 24-Nov 2003 0.05 0.03 0.02 0.10 0.11 0.05 0.09 0.12 <0.02 0.07 0.04 0.13 O.02 0.18 0.02 0.02 <0.02 <0.02 30-Oct 2003 0.04 0.02 0.02 0.08 0.09 0.06 0.06 0.06 0.02 0.03 0.03 0.04 0.02 0.06 0.02 0.02 <0.02 O.02 14-Oct 2003 0.04 0.02 0.02 0.03 0.05 0.03 0.02 0.02 <0.02 0.02 0.02 0.03 0.02 0.03 0.02 <0.02 <0.02 <0.02 26-Aug 2003 0.04 0.02 <0.02 0.02 0.02 O.02 <0.02 <0.02 <0.02 <0.02 <0.02 <0.02 0.02 <0.02 <0.02 <0.02 0.02 <0.02 7-Jul 2003 0.04 <0.02 <0.02 0.03 0.02 <0.02 <0.02 <0.02 <0.02 0.02 <0.02 O.02 <0.02 <0.02 <0.02 <0.02 <0.02 l 5-May 2003 0.07 0.07 l 0.09 0.08 0.10 0.07 0.07 0.06 0.09 0.09 0.10 0.08 0.08 0.09 0.10 0.06 • Tributary Name (Site ID) Sumas River (16) Sumas River (2) Sumas River (18) Sumas River (3) Sumas River (4) Sumas River (12) Sumas River (6) Sumas River (7) Swift Creek (1) Arnold Slough (10) Arnold Slough (11) Saar Creek (14) Marshall Creek (13) Marshall Creek (5) Sumas Canal (9) Sumas Canal (8) Sumas Mountain (15) Reference (19) 180 5 ° 7 ° ti ™ co d cq d CN co co co CD CD co co re ^ 5 ° CN d o> LO d co LO TT CO d CO d 9- "* < 2 0> CN co co T t d CD d co oS co d CD d co d co CN o CM CM CM 00 1^ o d CO TT 2 § ' CM CO d co cd CO CN CO T t LO d LO d o d JD ^ 0) o 4- ° CN ™ O d co oo oo T t d 7 § CM CM U CD Q CM O oo O) CD d d o co LO CO co oo oo CN d T t d oo d 3 CD E, c CD g X O •o a) > o CO w b o 0 JD CO > o z I T t CM O o I o CO o o I T t < I <o CM 7 CN d co CN CD CO LO co T t LO T t oo d co co co co co LO CO o oo o d o T t T t T t T t 1^ a> E ra I Z fr n 3 JD ' C H co CD CM I CO c o l CM CO (0 n E 3 CO > |E (0 ra E 3 (A ra CO a> > IS w ra E 3 CO tn ra E it J * a> a> o i O) 3 o CO o c .1 o CO o c L-< J£ 0 0) U ra , a Leo 0 o ra JC ra ra ra c ra IO w ra E c "ra c 3 o tn ra E 3 CO CO 0 u c £ 181 3 CO 0 CO E, c o A \— CO O o 'c ro co CD > o IT) CO 00 O _Q ro un T t o o r- CM CD o CD o cq co in o co in co CD o CM 7-J o CM T f CM CO CO co T t co T t iri iri iri CM co T t co o '-May '-May T t O T t T ~ CO co CD T ~ o CM CM co o T - p in CD O) o O '-May o CM CM CN CM CM CM co co CO T™" T t iri co CM co CM T " T— 9-Apr 9-Apr T t O CD CO T t CM co m in in cq in O co O 9-Apr o CM CM CM CM T t T t T t T t co T t CO co CM CO CO T " ra s T t O T t O x— CO N - CO CO in T t N - co CM CD oo CM CM CM o CM CO CO CO T t T t T t T t T f T t CO T - CO CO CO T t 1-Mar T t o cn cp o CD CD in oo co CM CD co CO CM 00 o O 1-Mar o CM CM CM CO co CO co co CO T t CO co T ~ iri CM CO iri T ~ eb T t o in in oo oo CD o O T t r- m oq o oo _^ T t u_ 1 CM o CM iri CO co iri iri T t T t iri T t T t CO iri CM CO co 2-Jan T t o oo cn CM CO co T t r - p T t CO co CO in T t co CM 2-Jan o CM cri co T t CD CD iri iri iri T ~ iri iri T t CM iri co CO T t T ~ 10-Dec 2003 > co o o z o o v - o> CD in oo T t O CO in cn co CD T t CM cq o CM iri T t T t cd CD iri iri co X— CO iri CM iri co T t iri T " CM CO o 30-Oc T - CM o CM oo CO r- p LO T ~ CM CM O oo co T - in 30-Oc o CM iri T t T t oo oo CD o co CM cb T t iri X— 14-Oct 2003 • • • • • i • • • • i • I • • 1 O) co o CD 26-Au in T t CD T - co CO oo o CD m CD p co oo O 26-Au o CM T— T— T™* CM CM CO CM iri d oo iri CO T " CM T t T t in 26-Au 7-Jul 2003 5-May 2003 Tributary Name (Site ID) Sumas River (16) Sumas River (2) Sumas River (18) Sumas River (3) Sumas River (4) Sumas River (12) Sumas River (6) Sumas River (7) Swift Creek (1) Arnold Slough (10) Arnold Slough (11) Saar Creek (14) Marshall Creek (13) Marshall Creek (5) Sumas Canal (9) Sumas Canal (8) Sumas Mountain (15) Reference (19) 182 3 7-Jun 2004 7.06 7.31 7.86 7.50 7.63 7.44 7.43 7.56 7.80 7.06 7.11 7.23 7.33 7.31 7.33 7.13 7.11 7.88 17-May 2004 6.99 7.42 7.91 7.53 7.79 7.56 7.50 8.11 8.17 7.13 7.30 7.00 7.42 7.43 7.67 7.39 6.99 7.94 19-Apr 2004 7.09 7.37 7.91 7.49 7.64 7.41 7.44 7.47 8.04 7.15 7.04 7.02 7.36 7.36 7.27 7.05 7.89 22-Mar 2004 7.03 7.17 7.53 7.28 7.42 7.12 7.26 7.28 7.47 6.98 6.95 7.13 7.18 7.18 7.14 7.07 7.05 7.63 1-Mar 2004 7.04 7.32 7.68 7.35 7.41 7.14 7.27 7.29 7.71 6.97 6.93 7.11 7.24 7.22 7.17 7.15 7.11 7.68 2-Feb 2004 7.04 7.34 7.48 7.27 7.31 7.12 7.23 7.27 7.77 6.97 6.95 7.04 7.11 7.12 7.12 7.13 7.06 7.51 12-Jan 2004 6.99 6.90 7.49 7.03 7.39 7.02 7.10 7.14 7.86 6.81 6.81 7.01 7.10 6.89 7.01 6.96 6.96 7.49 10-Dec 2003 7.07 7.26 7.64 7.29 7.38 7.18 7.15 7.32 7.67 6.88 6.89 6.98 7.21 7.07 7.17 7.09 6.98 7.64 24-Nov 2003 7.02 7.26 7.69 7.23 7.34 6.89 7.05 7.13 7.92 6.75 6.70 6.82 7.04 6.88 6.96 6.90 6.93 7.54 30-Oct 2003 6.57 6.89 7.57 6.94 6.97 6.78 6.68 6.75 7.61 6.29 6.33 6.42 6.83 6.33 6.65 6.59 6.35 7.27 14-Oct 2003 7.01 7.54 7.94 7.68 7.84 7.55 7.39 7.41 8.78 7.00 6.88 7.19 7.32 7.18 7.15 7.20 7.10 7.78 26-Aug 2003 7.01 7.44 8.11 7.47 7.81 7.92 7.93 8.73 8.42 6.82 6.80 7.04 7.51 7.40 7.37 7.58 6.87 7.94 7-Jul 2003 6.77 7.07 7.83 7.13 7.59 7.65 7.37 8.50 7.81 6.75 7.20 6.67 7.23 7.47 7.42 7.00 7.33 l 5-May 2003 7.18 7.53 l 7.57 7.69 7.25 7.37 7.43 8.09 7.04 7.17 7.18 7.13 7.27 7.23 7.13 7.59 l Tributary Name (Site ID) Sumas River (16) Sumas River (2) Sumas River (18) Sumas River (3) Sumas River (4) Sumas River (12) Sumas River (6) Sumas River (7) Swift Creek (1) Arnold Slough (10) Arnold Slough (11) Saar Creek (14) Marshall Creek (13) Marshall Creek (5) Sumas Canal (9) Sumas Canal (8) Sumas Mountain (15) Reference (19) 183 o o 7-Jun 2004 CO CN T f CN CD csi oo T f CO in CO d CO N in d o T f T f T f LO d d T f csi o d co d CD d in csi csj 17-May 2004 T f CD CD T f N T f CD in o oo CN d o ai ^— d CO d co d oo d I s -CN T f d I s -d o d o T f I s -csi 19-Apr 2004 CD oS O) ai CN d T " . oq csi d CD T f CO d csi CN CSj m d in d CO csi oo d oq csi T f co ai 22-Mar 2004 LO ai CO ai LO CD CD ai in d c o d CSJ T f d T f oq o ai co d o d c q CD CN d CN d 1-Mar 2004 CN N CD CD N cb 00 N i CO od CO d CD d CD ai o d T f ai CO ai m d CN ai CN N i in d o d o ai in d 2-Feb 2004 T f T f T f CD CO LO T f in T f CO T f CSI T f CD d CN d oo T f T f T f CO d CO N d 00 d CO T f T f csi co csi 12-Jan 2004 o LO LO ib 00 T f co Tf" o in o in o in d co ui CN d T f T f d oo d CO d N d in csi oo d 10-Dec 2003 N T f CD T f 00 T f CO ib ib CO in CO ib co T f LO T f o d N d CN d T f d co d T f d CN d oo d CD d 24-Nov 2003 CD T f o LO oq T f in N T f T f in CO in N T f T f CD d I s -d o d o d CD d I s -d CD d CO T f CN T f 30-Oct 2003 cb CO N LO N LO N T f d co d o ai O ai o in CO d m d 00 d oo ai ai CN 1^ CO N i CD d in T f 14-Oct 2003 CD CD CD d q CSj T— o CO CO co co csi o d co d T f c q d q LO csi oo T f CO d CSj c o ai 26-Aug 2003 CN csi CN CN LO o in c q d oo d CN N d CD d CN N oo T f CO d CD d CD in d in d CN ai r— o d 00 T f 7-Jul 2003 O CO CO CO I s -IO c o d d T f CN in CN CD d CN in ai in I s -^— CN d oo d CO Csi I s -d CSI Csi CN LO csi CN T f d i 5-May 2003 ai CD i in d csj CD T— CN CN CD Csi oo d CD d T— csi T f d 00 ai CSj csi CSj d T f d T f d i Tributary Name (Site ID) to 0 > E </> TO E 3 to 0 > E (0 CO E 3 CO co" 0 > E in re E 3 CO 0 > E in ra E 3 CO cu > E in ra E 3 CO CN" > E in ra E 3 CO 0 > E ra E 3 CO 0 > E in ra E 3 CO T -0 £ o 5 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T— 0 0 u tm ra ra CO to T -0 £ o ra £ ra S jn 0 £ o ra £ ra £ ST ra c ra O in ra E 3 CO ra c ra O in ra E 3 CO to" T " c ra c 3 O S in ra E 3 CO ST 0 o c £ 0 tc 184 CO 7-Jun 2004 265.1 311.0 289.9 325.8 329.3 304.1 315.3 310.7 203.1 337.0 311.0 127.3 257.3 318.4 278.0 253.0 184.9 132.0 17-May 2004 270.1 318.0 326.4 333.6 335.8 324.8 316.7 306.1 271.8 307.9 306.1 229.8 280.7 306.8 273.0 230.6 215.6 137.6 19-Apr 2004 266.4 308.0 294.8 311.6 312.6 283.8 277.9 283.1 227.0 285.5 211.7 161.8 280.9 315.5 225.5 222.7 149.7 120.8 22-Mar 2004 258.0 274.2 229.1 311.1 314.1 264.2 283.0 282.2 176.2 278.3 292.5 130.9 268.5 322.5 256.8 287.8 135.8 104.1 1-Mar 2004 297.0 332.0 324.0 354.0 358.0 307.0 322.0 325.0 220.0 322.0 314.0 190.0 299.0 445.0 270.0 307.0 152.6 130.7 2-Feb 2004 228.8 186.2 225.0 275.5 275.0 234.6 247.4 239.6 154.1 246.5 247.0 119.4 248.0 339.1 234.6 260.7 115.1 70.2 12-Jan 2004 208.5 202.4 195.5 255.0 251.7 200.9 226.0 224.9 137.0 265.6 270.3 93.7 260.0 325.4 235.7 249.5 123.1 86.1 10-Dec 2003 236.7 255.7 243.9 299.8 302.1 269.6 260.8 260.9 175.3 246.7 251.9 141.1 198.3 332.7 244.1 261.2 121.1 96.1 24-Nov 2003 252.0 271.3 241.3 308.3 317.7 221.8 259.2 272.7 184.2 248.0 263.3 124.5 185.7 235.8 247.0 266.8 124.7 77.5 30-Oct 2003 259.5 283.0 269.2 316.7 315.9 284.2 278.1 283.6 200.0 268.3 280.7 149.2 273.5 324.6 271.6 288.3 149.4 95.8 14-Oct 2003 228.0 276.5 245.4 275.8 280.4 229.2 236.1 247.3 209.4 300.9 321.8 109.8 269.6 234.5 272.3 279.0 242.1 140.1 26-Aug 2003 266.9 320.2 327.2 333.8 332.5 324.1 314.5 304.2 319.2 340.8 377.0 347.2 319.0 304.0 311.8 314.2 334.8 148.1 7-Jul 2003 239.0 280.0 277.0 288.0 288.0 259.0 266.0 241.0 197.0 267.0 259.0 208.0 238.0 267.0 238.0 216.0 249.0 l 2 CM 204.0 222.0 l 259.0 258.0 225.0 230.0 228.0 133.0 248.0 246.0 126.0 264.0 309.0 220.0 225.0 175.0 1 Tributary Name (Site ID) Sumas River (16) Sumas River (2) Sumas River (18) Sumas River (3) Sumas River (4) Sumas River (12) Sumas River (6) Sumas River (7) Swift Creek (1) Arnold Slough (10) Arnold Slough (11) Saar Creek (14) Marshall Creek (13) Marshall Creek (5) Sumas Canal (9) Sumas Canal (8) Sumas Mountain (15) Reference (19) 185 - J CO 0 re 5 CO c re x> 0 E c o CO ro 0 co C? Q X3 C ro -4—' 0 CM o 0 ro I-Temperature (°C) Wet CO T f o iri co T f iri IS-T f T f iri CO iri IS-T f LO T f CO iri IS-iri io T— od CO d CN d T f LO 00 CO CN T f Temperature (°C) Q T— d CO CO cq oq o CO co CO CD T f T f O CM CM CM CO d q o co CO CO co T f i in csi CO cn I Q . 0 o cq IS-CO IS-CN IS-CO IS-o IS-' IS-' IS-co IS-OO CD oq d o IS- IS-cn d d o IS-o IS-LO IS-Q q T f CO LO co T f T f IS-LO IS-o oo q IS-q IS- r> cq CO CM IS-' CO i> co Specific Conductivity (uS/cm) CD 5 IS-CD CO CM IS-iri LO CM CO T f CM oo co en CM CN o CO CD T f co CM CM ai LO CM C0 d CD CN co iri h-q 00 T f CM co CO CO CN In* T f CN i — o 00 T f CM T f iri CN co CM CO CM T f T f CN CO CN d co Specific Conductivity (uS/cm) i f Q IO CO CM O cd o co T f CN cn CN cq co T f T " CO oo co oo CN o co oo CN CO 00 CN T f CO o CM cn d o co T -d o CO oo co CD cri CO CN o cri o co O co in CM O o t^ f" CN cn T f co o cM CO Dissolved Organic Carbon (mg/L) 0) CO o iri CO co LO o T f cn LO co CN CO co cn CM iri CN co iri CO o CD LO CM CM CD T f co d d co T f csi CD LO iri T— o T f 00 T f CO IS-T f m IS-Dissolved Organic Carbon (mg/L) Q CM CO CM CO CO CM o o CO IS-00 CO LO co co o T f LO ao co 00 cn co cri T T . T -LO LO Tf" o o iri mm T f CD c i o IS-CO LO co o CO CO in 00 co o o IS-' o q Dissolved Oxygen (mg/L) 4-1 o 5 LO T f iri LO co IS-' o co CO o CM ai LO co CO o T f IS-LO IS-oci LO CD cri LO T f LO CO CO in IS-T f in CM CO o IS-00 in d o cn •> o CM 00 LO T f o i o T— T -Dissolved Oxygen (mg/L) Lv Q LO T f T f o o CO LO IS-CD o CN oS LO oS o oo o CN oo o LO oo o CN d T— LO LO T f in co T f d CO 00 in d LO CD h~ o CM IS-Ln: CO IS-in T f 00 o CO d Chloride (mg/L) 3 co 00 CM T -LO T f l~- IS-o co T -T f CD T— co CO LO co iri cn CO o o co cn T f IS-cn T f CO T f CO cn T f d co ai CM cn CN cri co co CO cn oo d o d V Chloride (mg/L) tv o CM co co co T f CD cn T -T f IS-co 00 LO IS-ai T— T— CM CD T— CM cn CN T f o i oo CM T f T— IS-LO co co in d cri cn CO CO CD iri in CD co CN cn. oo CN CM IS-m CO cq d o d V Ortho-P (mg/L) CU T f o CD CM o CD CN O CD co o d IS-o d T f O d LO o d T f o d CM p. o V CM o d CN q d CM O o ; CM o d V co o d CM o d CN o 5' v. CM o d V CN o d Ortho-P (mg/L) Q T f o CD CM O CD V CM O CD V co o d CO o d CM o d V CM o d V CN o d CM O d V CM q d V CN q d V CN o o V CM o d V CN o d V CM o d V CM O O y CM o d V CN O O V Ammonia (mg/L) o CD V CD O CD V co o IS-d T f CN d IS-CN d CM CN d TT.-o LO T f d T f co d cri r. q o CM d in co d in cq c§ q o T ™ d V d T T d V Ammonia (mg/L) £• a o CD V CM CD O x— d V IS-d T f d o CN d CD CN d IS-CM d o d T f d o CO d co T f . d CN d CO d oo T f d a i m d CN d o d V Nitrate (mg/L) 0) CO CO q cn CM CO co co co cn co T f O CO CM LO CO co T f CO iri T f o CO CO csi in CO co oo o CM T— CO iri CO iri T f o csi cri T f CM T f cn d o CO o Nitrate (mg/L) a O CM OD co CD LO q LO oq CN IS-LO csi T -o csi o cn CM CN CN CO CM O CM T f d IS-CN d o IS-d CM in d IS-co T f CO d CO: T T co d m T f o Tributary Name (Site ID) 7 CO 0 > DC in re E 3 CO 0 > DC in re E 3 CO CO 0 > DC in re E 3 CO 0 > DC in re E 3 CO 0 > DC in re E 3 CO cT T -0 > DC in re E 3 CO to 0 > DC in re E 3 CO 1*^ 0 > DC in re E 3 CO T -0 s> o m CO o T -J= O) 3 o CO T J O c < T -T -J= D) 3 O CO T J O c < TF T— IC 0 i&1 1 i co 0 0 k-o 15 JZ a re S 0 0 k. a 15 j= 12 re S 15 c re O in re E 3 ( 0 CO 15 c re O th .re E 3 CO to T— C re C 3 o S in re E 3 CO s> T -0 ic> IM m. DC 186 </> 3 • E Q . E C ' E < co 07-Jun 2004 <0.05 <0.05 <0.05 <0.05 <0.05 IO o d V <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 17-May 2004 <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 19-Apr 2004 O.05 <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 O.05 <0.05 <0.05 <0.05 <0.05 l <0.05 <0.05 <0.05 22-Mar 2004 <0.05 <0.05 <0.05 0.05 0.05 0.05 <0.05 0.05 <0.05 <0.05 <0.05 0.07 <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 01-Mar 2004 <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 0.06 <0.05 <0.05 <0.05 <0.05 02-Feb 2004 <0.05 <0.05 0.06 0.06 0.06 0.11 0.09 0.08 <0.05 0.08 0.11 0.10 <0.05 0.07 <0.05 <0.05 <0.05 <0.05 12-Jan 2004 0.07 0.20 0.10 0.26 0.11 0.13 0.24 0.25 0.34 0.15 0.11 0.33 <0.05 0.16 0.05 <0.05 <0.05 0.09 10-Dec 2003 <0.05 <0.05 <0.05 0.05 <0.05 0.05 O.05 0.05 <0.05 0.08 0.08 0.10 <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 24-Nov 2003 <0.05 <0.05 0.05 0.07 0.09 0.10 0.09 0.10 0.05 0.13 0.14 0.27 0.05 0.11 <0.05 <0.05 <0.05 0.06 30-Oct 2003 <0.05 <0.05 <0.05 <0.05 0.05 0.05 0.06 0.07 0.08 0.12 0.14 0.08 O.05 0.05 <0.05 <0.05 <0.05 <0.05 14-Oct 2003 <0.05 <0.05 <0.05 <0.05 <0.05 0.07 <0.05 <0.05 <0.05 <0.05 <0.05 0.12 <0.05 <0.05 <0.05 O.05 <0.05 <0.05 26-Aug 2003 <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 07-Jul 2003 <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 l 05-May 2003 <0.05 <0.05 1 O.05 <0.05 <0.05 <0.05 0.05 <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 0.05 l Site Name (ID#) Sumas River 1 (16) Sumas River 2 (2) Sumas River 3 (18) Sumas River 4 (3) Sumas River 5 (4) Sumas River 6 (12) Sumas River 7 (6) Sumas River 8 (7) Swift Creek 1 (1) Arnold Slough 1 (10) Arnold Slough 2 (11) Saar Creek 1 (14) Marshall Creek 1 (13) Marshall Creek 2 (5) Sumas Canal 1 (9) Sumas Canal 2 (8) Sumas Mountain 1 (15) Reference 1 (19) 187 § s 7 0 _ o I S - C M o CM LO CM CO CO cd CM O CM CO2 § I S - C M 00 LO o co IS-0 CM Q. T t < 2 • o O C M CO co CO oi CM « T t C M ~ CO IS-CM CM IS-CM CO 2 C M co co 06 CM CM "S T t L L . O • O C M C M O LO T t cd CM CO oi •? § C M C M O 00 o CD C O a 2 O C M co LO 0 CM > 0 C O z 2 1 o T t C M C M CO 00 LO 00 CM oi O o • o 2 P X co co co CM CM CM " C O O o • o T t C M LO co CO CM CM 3 CO CD E CL E o CO O T3 a> > o CO w T t O 0) JO CO TO 3 C O < 0 1 o C O C M C M CM CO co CM T t CM 3 C O •7 o KL 0 o *• CM CM CO o CM >» co co 5 0 1 o in C M o co 9 0) E CO z (7) ( O ^ C O c\T C M co C M C O C O 00 o CO o c L— < C M S i -C M JC 0) 2 o o> CO c CO o 10 CO E 3 CO 188 § s 7 § r«- CN o in co d r--T t d CO T t 2 2 • o r- C M C M C M Q . T t < 2 C D C M s in d oo « T t 2 2 • o C M C M C M co co S s 2 • o T- C M o co co in " § T t L L O • o C M C M O in C M a 2 7 § C M C M CD d u a> co 9 § O C M oo o) > O C O z 2 • o T t C M C M co " co O o • o 2 ^ co oo oo o C O O o • o T t C M C M T t CT 3 S2 < ° i o C O C M C M cn co d CO a> E CL a. c o td > o to CO m O a) CO 3 C O 7 ° C M CO co d co co S ° • o m C M o CO m g a> E co z <o 4-1 CO C O C O cn C O C O C M CM o CO o c < C M to OJ k. O ro c ro O tn ro E 3 CO oo C M To c ro O tn ro E 3 CO 189 7 § I S - C M o CO CO C M C M C M CO CM CO iri C O d V L O d v >» 2 N- ro C M CM C M C M CO d cn co oo cn LO d v d v Q . < S • o en C M C O C M CM C O o CM C M LO d v in d v ro T t • o C M C M C M CM in co Is-CM LOl d v C O d to in CM m d v ro T t 5 2 • o T- C M o co in co CM d CD LO o d v "S T t LU O • o C M C M co LO co CD d LO d v co LO LO d v 7 § C M C M CM CO d IO d v co d co LO d v u a> co D o • o O C M in co d m d o d co in d v > o co z 2 • o T t C M C M CJ) CD T t IO C M cn d o T t CJ) d o v o co O o ' o S P" co co d co d Is-d co C M o CM oo T t o d in d v O C O O o • o T t C M o d CM in d v cn 3 co < ° . o C O C M C M o> C M 00 CM O d Is-CM 00 C M OO in d v 3 CO 0 E Q . CL E 3 '(/) CO ro o 0. T J . > o co CO co O 0 JO co I— 3 C O " ? ° C M C M CM C M CM CM CO CM CJ) Is-CM co • >• S2 in ro 52 co g « E ro z 0 CO C O - - I - T J C M C M L O co C O .11 (0 ro E 3 CO I co u. 0 > (0 ro E 3 CO a* at o CO o c 0 0 u ro ro CO J C 0 S o « 2J C M J C 0 £ o ro £ ro cnl C M ro c ra O (01 ra CO n C 3 o S (0 ra E 3 CO cn 0 o c 0 a 0 cc 190 3 E CL CL C > 07-Jun 2004 16.9 25.0 24.1 20.1 20.6 19.0 17.2 16.5 19.3 20.4 20.2 CJ) CD T t 10.1 14.2 14.0 LO LO cd 17-May 2004 17.6 26.7 28.1 20.5 20.7 20.5 17.1 16.3 26.7 20.6 20.6 13.5 c d 10.0 14.1 10.6 co CO I s -cd 19-Apr 2004 17.6 26.3 25.2 19.8 20.0 18.1 15.5 15.7 22.8 18.5 15.1 o ai c d 10.4 l 12.9 o T f co cd 22-Mar 2004 17.1 24.0 22.2 20.7 21.0 17.0 17.0 16.9 17.1 18.1 19.4 I s -I s-' 11.4 12.9 15.8 co cd N ; CN 01-Mar 2004 18.1 25.5 25.4 21.5 21.8 19.1 17.9 18.1 19.8 19.9 20.8 o ai CM c d 11.8 12.5 17.4 co cd CNJ CO 02-Feb 2004 16.4 20.5 20.3 20.5 20.5 16.6 15.7 15.6 15.3 15.8 16.0 Oi CD T t I s - 11.3. 12.3 16.1 o o csi T t CNJ 12-Jan 2004 14.7 19.8 17.5 18.7 17.5 12.9 14.0 14.0 15.2 15.9 16.4 CO LO CM I s - 11.1 11.4 13.6 o cd LO c\i 10-Dec 2003 17.8 23.7 23.0 23.9 23.9 20.4 17.7 17.4 18.6 16.7 17.0 CO co CO l*~ 12.2 13.2 17.1 co CO c o csi 24-Nov 2003 17.7 23.2 21.7 22.5 23.8 13.4 15.3 16.2 18.3 13.9 14.5 CJ) CD oo T t CO 11.7 15.2 o CO CN CN 30-Oct 2003 17.9 25.5 26.1 24.4 24.2 19.7 17.9 18.1 20.6 16.5 16.0 T t co CNJ o d 12.0 14.1 17.1 o T t o q CNJ 14-Oct 2003 14.9 23.6 21.7 22.5 22.7 13.7 13.1 12.6 21.1 19.6 20.4 cd LO CO LO I s - 13.0 16.4 I s -T t 26-Aug 2003 16.6 25.3 27.5 18.1 19.7 20.0 15.1 15.6 31.5 17.8 22.4 25.4 T t ai T f o> 16.1 16.7 T t o d o T t 07-Jul 2003 16.8 26.5 26.8 20.7 20.7 20.3 16.6 15.2 25.2 18.5 20.5 14.2 T f o d LO ai 14.3 13.1 CO ai 1 05-May 2003 l l l l l l l 1 i i i 1 i • Site Name (ID#) Sumas River 1 (16) Sumas River 2 (2) Sumas River 3 (18) Sumas River 4 (3) Sumas River 5 (4) Sumas River 6 (12) Sumas River 7 (6) Sumas River 8 (7) Swift Creek 1 (1) Arnold Slough 1 (10) Arnold Slough 2 (11) Saar Creek 1 (14) Marshall Creek 1 (13) Marshall Creek 2 (5) Sumas Canal 1 (9) Sumas Canal 2 (8) Sumas Mountain 1 (15) Reference 1 (19) co I— 191 s s 7 § I S - C M CO Is-o o o CM O o o LO o d co o Is-LO o d CM o CM oo CM d co oo o d o LO o d Is-co o d >> (0 T f S 2 • o I S - C M oo d co d to co o d LO o o d v CM co T f d oo co CM d LO co o d Is-co o d a. T f < S • o en C M T f T f O T f CO O CD oo o CO Is-o o cn o d o d co cn oo T f o d oo cn o C M C M C M CO T— o d o T— o LO Is-o d CN d o d o o oo co o d cn LO o d LO CD T f CD CN d cn o d LO T f co cn o d CD d Is-CN co cn o LO CN d co co o d CM cn LO T f CM d CD C M co o o d CM LO o CM T f o cn T f o co LO o d LO o o d co oo o oo o o co T f co CM ss 7 § C M C M cn o o d Is-T f o d cn co o d T f LO o LO Is-o d CN Is-o T f o LO LO LO CN CN d u tv co 9 § O CM col o d Is-o CN CN o d CD LO o d Is-o CO oo o d LO o o CN co o CN CO o d o Is-CN o LO CN > O C O • o T f C M C M cn o d CO CO o CO co o LO CN o d o LO o d oo o o cn CO o co CN o O) CN o d CO CM d o co O o • o 2 P X co o co o d LO T f o Is-co o d CN CM o d LO T f o d co o d CT) T f o d LO cn o d CM d O o • o T f C M CM O d co co o d LO o d Is-o o LO T f o d LO o o d v co cn o d co oo o o T f o o T f 3 CO CD E O . _CL CD CO 0 c co O) c co TJ 0 > o 10 </> Q d O 0 JO co cn 3 co < ° . o ( O C M C M LO o o d LO o o d v CN o Is-o o d cn o o d LO o o d v T f co cn LO LO Is-d T f o CM T f o 3 C O " ? ° t; C M LO cn o d cn o LO o o d v LO o o d LO o o d v LO o o d v CN CM o LO o o d V to o o d v to o o d v • >» s L O ro 2 ° S C N g E re z a CO LO CO o co T f o d oo co p d > E in re E 3 CO C N C M 0 > E to re E 3 CO C O co co T f to co E 3 CO T f I O t_ 0 > E to ra E 3 CO C M r-( O k. 0 > E <f> ra E 3 CO CD LO o o d v T f o CN cn p d CO oo o d CO 00 J C 0 0 O CO s1 o CO T J o c  o CO o c JC 0 s> o C N J C 0 0 u co T f cn ra £ ra ra c ra O w re E 3 CO 192 2 2 I S - C M O O T f 06 o CM d LO o T f oo CM 00 T f CM CO oo co od C3 T f =? § I S - C M CO LO T f I s-CM I s-T f d CO Is-d cn CJ) cn d Q . T f < g • O C O C M I s-cn d Is-o d T f co o co d T f co d ra T t S 2 • o CM CM CM LO co d o Is- Is-d o CJ) d cn re T f • o T- C M oo CO CM CM d Is-CM CM LO d LO T f d T f Is-d o LO d "2 T f LL 2 C M C M O Is-o d l CJ) CJ) o LO d I s-co d CJ) co d T f I s-d Is-LO d re T f f o CM CM LO co d LO I s-CM CO CO d co CM d l o I s- oo LO d o cu co Q 2 • o O C M I s-d cn T f d T f co d > O CO z 2 • o T f C M C M O CJ) d co LO d | T f co Is-CM d o co 2 2 o co d CJ) o d Is-Is-d CJ) T f o co O 2 • o T t CM co d LO d CJ) CM d co CJ) d cn T f cn d l LO o d LO co CJ) cn 3 co < ° i o CO CM CM I s-Is-cn co d | o T f CJ) oo 3 CO E CL E 3 T3 O T 3 CD > O to CO CJ) T— O 0) JO CO 3 CO "? ° J_ O 5 M CM 00 d co co co CM d cn co CM o d re co S § m C M Q 0) E re z 0 4 - * CO CO CO CM C M k-0) > w CO E 3 CO ooi CO T t k-0) > cE (A CO E 3 CO C M T— co CD > in re E 3 CO r--_ oo Im (0 > w re E 3 CO C M a s i r CD CD 3 O co J J o c < J C 0) £ o •2.1 C M J C 0) 0) k-O O L . re re CO ra J = £ ra S cn ra c n O to ra E 3 CO 193 § s 7 § r«- C M o CO o CO T f 5 2 • o I S - C M oo Is-00 IO CO O T f Q . T t < 2 • o cn CM cn T f cri CD cri oq co oq co ro C M C M C M LO d co co Is-co T t o o C M CO CO 00 T f "S T t LL O • o C M C M CD CO d Is-co 7 § C M C M co d o T f o a> co Q o • o O CM CD LO d oo CO co > 0 CO z 2 1 o T t CM CM CO T f d oo co O o • o 2 ^ co Is-d o to u CO 2 ° T t C M CD O d CM T f C O C O C M C M CD CO C M d CD d C M T f CO CO E CL a. c o o w T3 0) .> o CO (0 o CM O a> .O co 3 CO " ? ° tt ° co d co o to oo to ro co T o L O C M o C M C M O CO Is-d co col o 0) E ra Z CO co 00 co 1 0 00 C M OX o> £ u l_ ro ro (0 O IS2J C M £ ro J Z 2 ro ro c ro O w ro CO oo CM 75 c ra a ID ra E 3 CO 0) 194 = s 2 ° O CN O T t O >i CO T t N. CM O d v q d v Q . T t < ° O en CN o V o V o d v « T t S 2 • o CN CM CN O V o d v CM O LL O V CO T t 7 g CM CM O V o a> co a 2 i o O CM o d v o d v o d v > O CO z 2 • o T t CM CM O V o co O 2 • o 2 ^ co o d o d o v • i- co TI- o 2 CM LO o d o d o v O) 3 CO < ° 7 O CO CM CN o V 3 CO "? ° ti ° © o V 3 w cu E CL a. CJ c KJ •a a> .> o CO CO b CN o 0) X ) co I— m 2 ° S CM o V CN O o V o d v CO O a> E ra z CD CO CO 00 co CO CM o a Oi L . o ra JC £2 ra 2 •2] CM CD s u re . c 12 re 2 cnl re c re U (A ra E 3 CO CO CN ra c ra U in ra E 3 CO c ra •*-» c 3 O s (A ra E 3 CO cn CD o c CD tc 195 40.0 ^ 30.0 H CO •§. 20.0-O 10.0" MC05 * BS04 O SA14 • _ „ „ o sli^ 5 RF19 RF19 n^18 n=^8 MC05* MCOS O M C 0 5 MC05 MC13 O O MC05 p c . Q SM15 RF19 R F 1 9 n &18 n $ 8 MC05 O n=i18 n= J : o i r a SMT5" SM15 R F 1 9 RF19 RF19 "O17 nT^s n 3 7 SM15 Rr*19 RF19 ngl8 n=48 RF19 n=17 n=J8 — I 1— 07-JUL-03 14-OCT-03 24-NOV-03 12-JAN-04 01-MAR-04 19-APR-04 07-JUN-04 26-AUG-03 30-OCT-03 10-DEC-03 02-FEB-04 22-MAR-04 17-MAY-04 Date 40-30 H CO E 2 0 H 10- 12-JAN-04 n=13 n=13 n=13 12-JAN-04 * 26-AUG-03 ° 26-AUG-03 T 1 -L -1-—L-i _07 l ^ r - W i 0 -JUL-03 MAY-OS O 02-FEB-04. 3E 26-AUG-03 ° 26-AUG-03 14-OCT-03 824 N&V-03 02-FEB-04 W19-APR-04 1 9 . A P R _ 0 £ 17-MAY-04 3O-OjpT-03° 12-JAN-04 n=13 n=13 n=13 n=13 n=13 n=13 n^l"Fn=V§n=13 n=13 n=13 n=12 n=13 n=13 n=12 l l i l l l i l i I i 1 1 1 1 1 1 1 01(HS16) 03(HS18) 05(BS4) 07(DS6) 09(SW1) 11(AS10) 13(MC13) 15(SC8) 17(SM15) 02(HS2) 04(BS3) 06(DS12) 08(DS7) 10(SA14) 12(AS11) 14(MC5) 16(SC9) 18(RF19) Downstream Order (Tributary and Site ID) Figure C1. Boxplots of Chloride (Cl) results by sampling date and sampling site. Tributary Legend: HS: Headwater region of Sumas River, BS: Border region of Sumas River, DS: Downstream region of Sumas River, SW: Swift Creek, SA: Saar Creek, AS: Arnold Slough, MC: Marshall Creek, SC: Sumas Canal, SM: Sumas Mountain, RF: Vedder Mountain Reference site. 196 1 0 . 0 H 7.5 H O) & 5.0-o 2.5-0.0 H MC13 * MC13 MC05 ° MC13 M C 1 3 MC05 MC13 MC13 MC13 o o o n=16 n=17 n=18 n=18 n=18 n=18 n=18 n=18 n=18 n=17 n=18 n=17 n=18 n=18 i i i i i i 1 1 1 1 1 1 1 r 05-MAY-03 26-AUG-03 30-OCT-03 10-DEC-03 02-FEB-04 22-MAR-04 17-MAY-04 07-JUL-03 14-OCT-03 24-NOV-03 12-JAN-04 01-MAR-04 19-APR-04 07-JUN-04 Date 10.00 H 7.50 H .§. 5.00-O 2.50 H 0.00 H LT B _ L O 26-AUG-03 O26-AUG-03 T 14-OCT-03 O - r T :::.::i::t> i n=14 n=14 n=13 n=14 n=14 n=14 n=14 n=14 n=14 n=14 n=14 n=14 n=14 n=14 n=13 n=14 n=14 n=12 01(HS16) 03(HS18) 05(BS4) 07(DS6) 09(SW1) 11(AS10) 13(MC13) 15(SC8) 17(SM15) 02(HS2) 04(BS3) 06(DS12) 08(DS7) 10(SA14) 12(AS11) 14(MC5) 16(SC9) 18(RF19) Downstream Order (Tributary and Site ID) Figure C2. Boxplots of Nitrate (N03"-N) results by sampling date and sampling site. Tributary Legend: HS: Headwater region of Sumas River, BS: Border region of Sumas River, DS: Downstream region of Sumas River, SW: Swift Creek, SA: Saar Creek, AS: Arnold Slough, MC: Marshall Creek, SC: Sumas Canal, SM: Sumas Mountain, RF: Vedder Mountain Reference site. 197 SC09 o SA14 o AS10 SA14 $ AS10 # AS11 SC09 * SC08 o T SC09 # * SC08 S£09 * SC08 SC09 o AS10 SC09 SC08 * AS10 * AS11 AS10* SA140 n=16 n=17 n=18 n=18 n=18 n=18 n=18 n=18 n=18 n=17 n=18 n=17 n=18 n=18 I 1 1 1 1 1 1 1 1 1 1 1 1 1 05-MAY-03 26-AUG-03 30-OCT-03 10-DEC-03 02-FEB-04 22-MAR-04 17-MAY-04 07-JUL-03 14-OCT-03 24-NOV-03 12-JAN-04 01-MAR-04 19-APR-04 07-JUN-04 Date 2.00 H =J 1.50-E + 1.00-X 0.50-0.00-14-OCT-03 O 01-MAR-04 14-OCT-03 14-OCT-03 *14-OCT-03* 14-OCT-03 * * 30-OCT-03" 24-NOV-03 -O- i ~r , • i n 14-OCT-03 O 07-JUL-03 T r _ o L_ 14-OCT-Q3_ X I G 14-OCT-03 14 03 -ocy J^ -NOy^03| n=14 n=14 n=13 n=14 n=14 n=14 n=14 n=14 n=14 n=14 n=14 n=14 n=14 n=14 n=13 n=14 n=14 n=12 01(HS16) ' 03(HS18) ' 05(BS4) ' 07(DS6) ' 09(SW1) ' 11(AS10) ' 13(MC13) 15(SC8) 17(SM15) 02(HS2) 04(BS3) 06(DS12) 08(DS7) 10(SA14) 12(AS11) 14(MC5) 16(SC9) 18(RF19) Downstream Order (Tributary and Site ID) Figure C3. Boxplots of Ammonia (NH/-N) results by sampling date and sampling site. Tributary Legend: HS: Headwater region of Sumas River, BS: Border region of Sumas River, DS: Downstream region of Sumas River, SW: Swift Creek, SA: Saar Creek, AS: Arnold Slough, MC: Marshall Creek, SC: Sumas Canal, SM: Sumas Mountain, RF: Vedder Mountain Reference site. Extreme outliers: MC5 (02-FEB-04): 5.10 mg/L and MC5 (01-MAR-04): 9.96 mg/L. 198 0.30 H _ 0.20 H _ J 13) E, a. 6 JZ O 0.10-o.oo-HS16 - 1 ' BS03 BS04 BS04 HS16 q A J H O * - T -MC05 MC05 BS04 ° ° T HS16 BS04, BSOf n=16 n=17 n=18 n=18 n=18 n=18 n=18 n=18 n=18 n=17 n=18 n=17 n=18 n=18 I l ~i 1 1 1 1 1 1 1 -05-MAY-03 26-AUG-03 30-OCT-03 10-DEC-03 02-FEB-04 22-MAR-04 17-MAY-04 07-JUL-03 14-OCT-03 24-NOV-03 12-JAN-04 01-MAR-04 19-APR-04 07-JUN-04 Date 0.30 H 0.20 H E o O 0.10-o.oo-o 01-MAR-04 24-NOV-03 24-NOV-03 05-MAY-03 * 05-MAY-03 -r-* * 3I *05-MAY-03l 05-MAY-03 O ° * 24-NOV-03 # 05-MAY-03 05-MAY-03 i ^ T - ° 3 0 5 - M A Y - 0 3 05-iyjAY-03 05-MAY( 24-NOV-03 03 05-MAY-03 * # 05-MAY-03 05-MAY-03 26-AUG-03 pssss] -L J_ L__J L _ J •—— .^fJbjJB3_J 1 ^ 3 I I f-^-i I J r-^-, 1 1 * — n=14 n=14 n=13 n=14 n=14 n=14 n=14 n=14 n=14 n=14 n=14 n=14 n=14 n=14 n=13 n=14 n=14 n=12 I I 1 1 1 1 1 1 1 1 1 1 1 1 1 1 01(HS16) 03(HS18) 05(BS4) 07(DS6) 09(SW1) 11(AS10) 13(MC13) 15(SC8) 17(SM15) 02(HS2) 04(BS3) 06(DS12) 08(DS7) 10(SA14) 12(AS11) 14(MC5) 16(SC9) 18(RF19) Downstream Order (Tributary and Site ID) Figure C4. Boxplots of Orthophosphate (P04) results by sampling date and sampling site. Tributary Legend: HS: Headwater region of Sumas River, BS: Border region of Sumas River, DS: Downstream region of Sumas River, SW: Swift Creek, SA: Saar Creek, AS: Arnold Slough, MC: Marshall Creek, SC: Sumas Canal, SM: Sumas Mountain, RF: Vedder Mountain Reference site. 199 O SW01 n=18 n=18 RF19 o ASjIO AS-y O o AS10 n=18 n=18 n=18 o AS11 n=17 HS16„ n=18 n=18 n=18 o HS16 n=18 , i i I I 1 1 1 1 1 — 26-AUG-03 30-OCT-03 10-DEC-0312-JAN-04 02-FEB-04 01-MAR-0422-MAR-0419-APR-0417-MAY-04 07-JUN-04 Date 12.0 H |> 8.0-O o 4.0—f 17-MAY-04 O 26-AUG-03 17-MAY-04-O * 19-APR-04 19-APR-04 O 17-MAY-QA O I T o 26-AUG-03 26-AUG-03 26-AUG-03 2 6 - A U G " 0 3 J- O * n=10 n=10 n=10 n=10 n=10 n=10 n=10 n=10 n=10 n=10 n=10 n=10 n=10 n=10 n=10 n=10 n=10 n=10 0.0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 01(HS16) 03(HS18) 05(BS4) 07(DS6) 09(SW1) 11(AS10) 13(MC13) 15(SC8) 17(SM15) 02(HS2) 04(BS3) 06(DS12) 08(DS7) 10(SA14) 12(AS11) 14(MC5) 16(SC9) 18(RF19) Downstream Order (Tributary and Site ID) Figure C5. Boxplots of Dissolved Oxygen (DO) results by sampling date and sampling site. Tributary Legend: HS: Headwater region of Sumas River, BS: Border region of Sumas River, DS: Downstream region of Sumas River, SW: Swift Creek, SA: Saar Creek, AS: Arnold Slough, MC: Marshall Creek, SC: Sumas Canal, SM: Sumas Mountain, RF: Vedder Mountain Reference site. 200 26-AUG-03 30-OCT-03 12-JAN-04 01-MAR-04 19-APR-04 07-JUN-04 14-OCT-03 24-NOV-03 02-FEB-04 22-MAR-04 17-MAY-04 Date 15.0-5- 10.0—i E, O O Q 5.0 H i 0.0 H 14-OCT-03 * 30-OCT-03 30-OCT-03 30-OCT-03 O 30-OCT-03. _ _ _ „_ t80-OCT-03 _J_ r O o 14-OCT-03 T 24-NOV-03 O T _ L T I J- I -1 _1_ 1 _X T o 26-AUG-03 n=11 n=11 n=11 n=11 n=11 n=11 n=11 n=11 n=11 n=11 n=11 n=11 n=11 n=11 n=10 n=11 n=11 n=11 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 01(HS16) 03(HS18) 05(BS4) 07(DS6) 09(SW1) 11(AS10) 13(MC13) 15(SC8) 17(SM15) 02(HS2) 04(BS3) 06(DS12) 08(DS7) 10(SA14) 12(AS11) 14(MC5) 16(SC9) 18(RF19) Downstream Order (Tributary and Site ID) Figure C6. Boxplots of Dissolved Organic Carbon (DOC) results by sampling date and sampling site. Tributary Legend: HS: Headwater region of Sumas River, BS: Border region of Sumas River, DS: Downstream region of Sumas River, SW: Swift Creek, SA: Saar Creek, AS: Arnold Slough, MC: Marshall Creek, SC: Sumas Canal, SM: Sumas Mountain, RF: Vedder Mountain Reference site. 201 8.5 H 8.0 H Q- 7.5—I 7.0 H 6.5 H DS07 O o SW01 SW01 o SW01 SW01 . . . . . . * SW01 o SW01 o RF19 HSI&O t RF19 O n=16 n=17 n=18 n=18 rd l8 n=18 n=18 n=18 n=18 n=17 n=18 n=17 n=18 n=18 I 1 1 1 1 1 1 1 1 1 1 1 1 1 05-MAY-03 26-AUG-03 30-OCT-03 10-DEC-03 02-FEB-04 22-MAR-04 17-MAY-04 07-JUL-03 14-OCT-03 24-NOV-03 12-JAN-04 01-MAR-04 19-APR-04 07-JUN-04 Date 8.5 H 8.0 H X 7.5-a 7.0 H 6.5 H JL 05-MAY-O3) O *07-JUL-03 *30-OCT-03 26-AUG-Q3 O 14-OCT-03 07-JUL-5J3 17-MA/-04 26-AUG-03 r _ O o 30-OCT-03 17-MAY-04 O JL 05-MAY-Q3 O * 26-AUG-03 T " 30-OCT-03 ° C30-OCT-03 * 30-OCT-03 n =l4 n=14 n=13 n=14 n=14 n=14 n=14 n=14 n=14 n=14 n=14 n=14 n=14 n=14 n=13 n=14 n=14 n=12 3 0 - O g T - 0 3 c | ° - O C T - 0 3 3 ? ) O C T - 0 3 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 01(HS16) 03(HS18) 05(BS4) 07(DS6) 09(SW1) 11(AS10) 13(MC13) 15(SC8) 17(SM15) 02(HS2) 04(BS3) 06(DS12) 08(DS7) 10(SA14) 12(AS11) 14(MC5) 16(SC9) 18(RF19) Downstream Order (Tributary and Site ID) Figure C7. Boxplots of pH results by sampling date and sampling site. Tributary Legend: HS: Headwater region of Sumas River, BS: Border region of Sumas River, DS: Downstream region of Sumas River, SW: Swift Creek, SA: Saar Creek, AS: Arnold Slough, MC: Marshall Creek, SC: Sumas Canal, SM: Sumas Mountain, RF: Vedder Mountain Reference site. 202 AS11 o T HS16 —*—• o 8woi SA14 n=16 n=17 RF19 SA14 * o RF19 o MCOS o SW01 o SM15 RF19 SA14 n=18 n=18 n=18 RFIg SA14 R F « n=18 n=18 n=18 MC05 S M 1 ^ RF19o RF19 n ^ 8 SM15 8 S A o 4 RF19 n=17 n=18 T" T RF10 RF19 § SA14 n=18 n=18 n=18 05-MAY-03 26-AUG-03 30-OCT-03 10-DEC-03 02-FEB-04 22-MAR-04 17-MAY-04 07-JUL-03 14-OCT-03 24-NOV-03 12-JAN-04 01-MAR-04 19-APR-04 07-JUN-04 Date 400—| E o to £ 300-'JP u 3 TJ C o o O 200-"5 a. to iooH X T 26-AUG-03 26-AUG-03O r o 01-MAR-04 p i 07-JUL-03 O *24W7V'-t>3- rJ llO-DEC-03 u-OG7-0r-O o 24-NOV-03 n=14 n=14 n=13 n=14 n=14 n=14 n=14 n=14 n=14 n=14 n=14 n=14 n=14 n=14 n=14 n=14 n=14 n=12 l l l i i I l l l l 1 1 1 1 1 1 1 1 01(HS16) 03(HS18) 05(BS4) 07(DS6) 09(SW1) 11(AS10) 13(MC13) 15(SC8) 17(SM15) 02(HS2) 04(BS3) 06(DS12) 08(DS7) 10(SA14) 12(AS11) 14(MC5) 16(SC9) 18(RF19) Downstream Order (Tributary and Site ID) Figure C8. Boxplots of Specific Conductivity (uS/cm) results by sampling date and sampling site. Tributary Legend: HS: Headwater region of Sumas River, BS: Border region of Sumas River, DS: Downstream region of Sumas River, SW: Swift Creek, SA: Saar Creek, AS: Arnold Slough, MC: Marshall Creek, SC: Sumas Canal, SM: Sumas Mountain, RF: Vedder Mountain Reference site. 203 MC13 M C 1 3 MC13 1 ^ MC13 O ° * - • - J _ S i m s i - — — @ RF19 17 n=16 n=17 n=18 n=18 n=18 n=18 n=18 n=18 n=18S Mn=17 n=18 n=18 n=18 n=18 i i i i i i i i i 1 1 1 1 1 05-MAY-03 26-AUG-03 30-OCT-03 10-DEC-03 02-FEB-04 22-MAR-04 17-MAY-04 07-JUL-03 14-OCT-03 24-NOV-03 12-JAN-04 01-MAR-04 19-APR-04 07-JUN-04 Date T i i i i i i i 1 r 01(HS16) 03(HS18) 05(BS4) 07(DS6) 09(SW1) 11(AS10) 13(MC13) 15(SC8) 17(SM15) 02(HS2) 04(BS3) 06(DS12) 08(DS7) 10(SA14) 12(AS11) 14(MC5) 16(SC9) 18(RF19) Downstream Order (Tributary and Site ID) Figure C 9 . Boxplots of Temperature (°C) results by sampling date and sampling site. Tributary Legend: HS: Headwater region of Sumas River, BS: Border region of Sumas River, DS: Downstream region of Sumas River, SW: Swift Creek, SA: Saar Creek, AS: Arnold Slough, MC: Marshall Creek, SC: Sumas Canal, SM: Sumas Mountain, RF: Vedder Mountain Reference site. 204 3 0 H E Q . (0 O "g 2 0 -> o in w 1 0 -M/M 3 M£13 MC13 O MC05 O SWjJI MC13 MC05O n=17 n=18 n=18 n=18 n=18 n=18 n=18 n=18 MC13 o MC13T o O MC05 SW01 o n=17 MC13j MC05O n=18 SW01 o n=17 SW01 o MCOS o SA14 o SW01 n=18 n=^8 0 7 - J U L - 0 3 1 4 - O C T - 0 3 2 4 - N O V - 0 3 1 2 - J A N - 0 4 0 1 - M A R - 0 4 1 9 - A P R - 0 4 0 7 - J U N - 0 4 2 6 - A U G - 0 3 3 0 - O C T - 0 3 1 0 - D E C - 0 3 0 2 - F E B - 0 4 2 2 - M A R - 0 4 1 7 - M A Y - 0 4 Date 3 0 . 0 — | E a. a. n o •g 2 0 . 0 -> o in in 1 0 . 0 - H 1 o 12-JAN-^4 1 26-AUG-03 1L03J 07-J 17-MAY-04 O 26-AUG-03 26-AUG-03 O _J_ n=13 n=13 n=13 n=13 n=13 n=13 n=13 n=13 n M ? n=^3 n=13 n=13 n=13 n=13 n=12 n=13 n=13 n=12 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 ( H S 1 6 ) 0 3 ( H S 1 8 ) 0 5 ( B S 4 ) 0 7 ( D S 6 ) 0 9 ( S W 1 ) 1 1 ( A S 1 0 ) 1 3 ( M C 1 3 ) 1 5 ( S C 8 ) 1 7 ( S M 1 5 ) 0 2 ( H S 2 ) 0 4 ( B S 3 ) 0 6 ( D S 1 2 ) 0 8 ( D S 7 ) 1 0 ( S A 1 4 ) 1 2 ( A S 1 1 ) 1 4 ( M C 5 ) 1 6 ( S C 9 ) 1 8 ( R F 1 9 ) Downstream Order (Tributary and Site ID) Figure C10. Boxplots of Dissolved Calcium (ppm) results by sampling date and sampling site. Tributary Legend: HS: Headwater region of Sumas River, BS: Border region of Sumas River, DS: Downstream region of Sumas River, SW: Swift Creek, SA: Saar Creek, AS: Arnold Slough, MC: Marshall Creek, SC: Sumas Canal, SM: Sumas Mountain, RF: Vedder Mountain Reference site. 205 3.00-E 2.00-CL a. 0) u. "D 0) > O in g 1.00-* SA14 SM15 SA14 MC13 AS10 O AS11 AS11 SA14 O SA14 * SM15 njj6 rg17 t_^ pj h^tf nj18 ngjj_8 nJl8 n^T8 n±L8 n i . 7 n^18 nJ17 1 n = j 8 "118 0.00 I I i i 1 1 1 — — i 1 1 1 1 1 i— 05-MAY-03 26-AUG-03 30-OCT-03 10-DEC-03 02-FEB-04 22-MAR-04 17-MAY-04 07-JUL-03 14-OCT-03 24-NOV-03 12-JAN-04 01-MAR-04 19-APR-04 07-JUN-04 Date 3.0-2.0-E a. a. a> UL •o 0) in in 5 o.o H 12-JAN-04 12-JAN-04 O 07-JUL-03 2-JAN-Q4 OCT-O; o 14-OCT-03 ^26-AUG-03 "05-MAY-03 * T f o 26-AUG-03 T 12-JAN-04 *fWIOV-03| 07-JUN-04 n=14 n=14 n=13 n=14 n=14 n=14 n=14 n=14 n=14 n=14 n=14 n=14 n=14 n=14 n=13 n=14 n=14 n=12 l i i 1 1 1 1 1 1 1 01(HS16) 03(HS18) 05(BS4) 07(DS6) 09(SW1) 11(AS10) 13(MC13) 15(SC8) 17(SM15) 02(HS2) 04(BS3) 06(DS12) 08(DS7) 10(SA14) 12(AS11) 14(MC5) 16(SC9) 18(RF19) Downstream Order (Tributary and Site ID) Figure C11. Boxplots of Dissolved Iron (ppm) results by sampling date and sampling site. Tributary Legend: HS: Headwater region of Sumas River, BS: Border region of Sumas River, DS: Downstream region of Sumas River, SW: Swift Creek, SA: Saar Creek, AS: Arnold Slough, MC: Marshall Creek, SC: Sumas Canal, SM: Sumas Mountain, RF: Vedder Mountain Reference site. Extreme outlier: SM15 (26-AUG-03): 16.13 mg/L. 206 6.0 H E a a • o a> > o i n (A 4.0 H 2.0-AS1P MCO^  AS1 AS11 O n=17 n=l8 a 18 nj 118 nj 18 n=18 nj 18 nA AS1CV AS11 o 18 n=17 n=l18 n=(17 n4l8 n4l8 I 1 1 1 1 1 1 1 1 1 1 1 1 -07-JUL-03 14-OCT-03 24-NOV-03 12-JAN-04 01-MAR-04 19-APR-04 07-JUN-04 26-AUG-03 30-OCT-03 10-DEC-03 02-FEB-04 22-MAR-04 17-MAY-04 Date 30-OCT-03 14-OCT-03 O O 30-QCT-030' 30-OCT-03 °24-NOV-03 O 14-OCT1-03— °30-OfcT-03^ T o 07-JUN-041 30-OCT-M _2_ 14-OCT-03 O *30-OCT-03 *24-NOV-03 I 1 *14-OCT-03 I 1, (14-OCT-03 o 17-MAY-04 n=13 n=13 n=13 n=13 n=13 n=13 n=13 n=13 n=13 n=13 n=13 n=13 n=13 n=13 n=12 n=13 n=13 n=12 l 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 01(HS16) 03(HS18) 05(BS4) 07(DS6) 09(SW1) 11(AS10) 13(MC13) 15(SC8) 17(SM15) 02(HS2) 04(BS3) 06(DS12) 08(DS7) 10(SA14) 12(AS11) 14(MC5) 16(SC9) 18(RF19) Downstream Order (Tributary and Site ID) Figure C12. Boxplots of Dissolved Potassium (ppm) results by sampling date and sampling site. Tributary Legend: HS: Headwater region of Sumas River, BS: Border region of Sumas River, DS Downstream region of Sumas River, SW: Swift Creek, SA: Saar Creek, AS: Arnold Slough, MC: Marshall Creek, SC: Sumas Canal, SM: Sumas Mountain, RF: Vedder Mountain Reference site. 207 I I I 1 1 1 1 1 1 1 07-JUL-03 14-OCT-03 24-NOV-03 12-JAN-04 01-MAR-04 19-APR-04 07-JUN-04 26-AUG-03 30-OCT-03 10-DEC-03 02-FEB-04 22-MAR-04 17-MAY-04 Date pO2-FEB-04-°12-JAN-04 j14-OCT-03 12-JAN-04 O 26-AUG-03 26-AUG-03 o 14-OCT-03 07-JUL-03 ] 8 1 17-MAY-04 T o 24-NOV-03 n=13 n=13 n=13 n=13 n=13 n=13 n=13 n=13 n=13 n=13 n=13 n=13 n=13 n=13 n=12 n=13 n=13 n=12 l l l l i l i i I I 1 1 l 1 1 1 1 1 01(HS16) 03(HS18) 05(BS4) 07(DS6) 09(SW1) 11(AS10) 13(MC13) 15(SC8) 17(SM15) 02(HS2) 04(BS3) 06(DS12) 08(DS7) 10(SA14) 12(AS11) 14(MC5) 16(SC9) 18(RF19) Downstream Order (Tributary and Site ID) Figure C13. Boxplots of Dissolved Magnesium (ppm) results by sampling date and sampling site. Tributary Legend: HS: Headwater region of Sumas River, BS: Border region of Sumas River, DS: Downstream region of Sumas River, SW: Swift Creek, SA: Saar Creek, AS: Arnold Slough, MC: Marshall Creek, SC: Sumas Canal, SM: Sumas Mountain, RF: Vedder Mountain Reference site. 208 1.00 H AS11 # SA14 AS10 05-MAY-03 26-AUG-03 30-OCT-03 10-DEC-03 02-FEB-04 22-MAR-04 17-MAY-04 07-JUL-03 14-OCT-03 24-NOV-03 12-JAN-04 01-MAR-04 19-APR-04 07-JUN-04 Date E a a XJ > o (A (A 1.00H 0.75 H 0.50 H 0.00 H O 07-JUN-04 * 26-AUG-03 26-AUG-03 0.25H17-MAY-04 0 7^ J U!i23J1-MAR-04 Rf94-a . *rQ1-l 01-MAR-04 O 30-OCT-03 T12-JAN-0pr 05-MAY-03 17-MAY-04 o n=U n=14 n=13 n=14 n=14 n=14 n=14 n=14 n=14 n=14 n=14 n=14 n=14 n=14 n=13 n=14 n=14 n=12 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 01(HS16) 03(HS18) 05(BS4) 07(DS6) 09(SW1) 11(AS10) 13(MC13) 15(SC8) 17(SM15) 02(HS2) 04(BS3) 06(DS12) 08(DS7) 10(SA14) 12(AS11) 14(MC5) 16(SC9) 18(RF19) Downstream Order (Tributary and Site ID) Figure C14. Boxplots of Dissolved Manganese (ppm) results by sampling date and sampling site. Tributary Legend: HS: Headwater region of Sumas River, BS: Border region of Sumas River, DS: Downstream region of Sumas River, SW: Swift Creek, SA: Saar Creek, AS: Arnold Slough, MC: Marshall Creek, SC: Sumas Canal, SM: Sumas Mountain, RF: Vedder Mountain Reference site. Extreme outlier: SM15 (26-AUG-04): 8.12 mg/L. 209 25 H 20-E a. a re" 15-Z T3 a> > 8 1°-5 H I I I I I 1 1 1 1 1 07-JUL-03 14-OCT-03 24-NOV-03 12-JAN-04 01-MAR-04 19-APR-04 07-JUN-04 26-AUG-03 30-OCT-03 10-DEC-03 02-FEB-04 22-MAR-04 17-MAY-04 Date 25 H 20 H E a a. "ra 15—I T J 0) > o tf> 10-(fl 5 H JL X T i — i - L 14. o - J OCT-03 07-JUL-03* 1 1 1 _L IG-03 26-AUG-03 O R07-JU1.-03T O ' " 17-MAY lAY-04—J I 12-JA^-04 02jFEB T 14-OCT-03 i T • 26-AUG-03 [ ^ J n=13 n=13 n=13 n=13 n=13 n=13 n=13 n=13 n=13 n=13 n=13 n=13 n=13 n=13 n=12 n=13 n=13 i i i i i i i i i i i i i i i i i i 01(HS16) 03(HS18) 05(BS4) 07(DS6) 09(SW1) 11(AS10) 13(MC13) 15(SC8) 17(SM15) 02(HS2) 04(BS3) 06(DS12) 08(DS7) 10(SA14) 12(AS11) 14(MC5) 16(SC9) 18(RF19) Downstream Order (Tributary and Site ID) Figure C15. Boxplots of Dissolved Sodium (ppm) results by sampling date and sampling site. Tributary Legend: HS: Headwater region of Sumas River, BS: Border region of Sumas River, DS: Downstream region of Sumas River, SW: Swift Creek, SA: Saar Creek, AS: Arnold Slough, MC: Marshall Creek, SC: Sumas Canal, SM: Sumas Mountain, RF: Vedder Mountain Reference site. 210 20 H ? 1 5 H Q. Q. V) •a o > o in in 10-5-i SW01 o SM15 SA14° A S l £ O AS11 AS10 AS11 o Rlfl9 Sivll5 Slil5SW01 o 8 AS10 AS11 SW01 o RF49 O SM1S AS1$ AS11 SW04 -RF19 n=16 n=17 n=18 n=18 n=18 n=18 n=18 n=18 n=18 n=17 n=18 n=17 n=18 n=18 i i i i i i i i i 1 1 1 1 r 05-MAY-03 26-AUG-03 30-OCT-03 10-DEC-03 02-FEB-04 22-MAR-04 17-MAY-04 07-JUL-03 14-OCT-03 24-NOV-03 12-JAN-04 01-MAR-04 19-APR-04 07-JUN-04 Date 20 H I 1 5" a co •a > 5 H 26-AUG-O? 14-OCT-03 o g . A U G . 0 3 14-OCT-03 07.JUJj.-03 X, T o 17-MAY-04 12-JAN-04 24-NOV-03J O 07-JUL-03 2$-AUG-03 o n=14 n=14 n=13 n=14 n=14 n=14 n=14 n=14 n=14 n=14 n=14 n=14 n=14 n=14 n d 3 n=14 n=14 n=12 I i i I i I 1 1 1 1 1 1 1 1 1 1 1 1 01(HS16) 03(HS18) 05(BS4) 07(DS6) 09(SW1) 11(AS10) 13(MC13) 15(SC8) 17(SM15) 02(HS2) 04(BS3) 06(DS12) 08(DS7) 10(SA14) 12(AS11) 14(MC5) 16(SC9) 18(RF19) Downstream Order (Tributary and Site ID) Figure C16. Boxplots of Dissolved Silicon (ppm) results by sampling date and sampling site. Tributary Legend: HS: Headwater region of Sumas River, BS: Border region of Sumas River, DS: Downstream region of Sumas River, SW: Swift Creek, SA: Saar Creek, AS: Arnold Slough, MC: Marshall Creek, SC: Sumas Canal, SM: Sumas Mountain, RF: Vedder Mountain Reference site. 211 Appendix D: DGT Sampling Results Table D1. QA/QC results for DGT samples. Table D2. DGT results for bioavailable Aluminum (ppb). Table D3. DGT results for bioavailable Iron (ppb). Table D4. DGT results for bioavailable Manganese (ppb). Table D5. DGT results for bioavailable Nickel (ppb). Table D6. DGT results for bioavailable Zinc (ppb). Figure D1. Boxplots of bioavailable Aluminum (ppb) by date and by site. Figure D2. Boxplots of bioavailable Iron (ppb) by date and by site. Figure D3. Boxplots of bioavailable Manganese (ppb) by date and by site. Figure D4. Boxplots of bioavailable Nickel (ppb) by date and by site. Figure D5. Boxplots of bioavailable Zinc (ppb) by date and by site. 212 Table D1. QA/QC results for DGT samples. Site Deployment Date Retrieval Date Al _p£b_ Fe _Epb_ Mn _EPb_ Ni _£Pb_ Sumas River 2 A v g Std Dev C o V (%) 12-Jan-04 2-Feb-04 52.66 0.00 26.33 37.24 141.42 35.58 239.67 137.62 144.31 104.86 43.77 42.57 43.17 0.85 1.97 8.30 15.81 12.05 5.30 44.01 Sumas River 3 A v g Std Dev C o V (%) 12-Jan-04 2-Feb-04 0.00 0.00 0.00 0.00 0.00 25.89 10.16 18.03 11.12 61.70 23.32 14.85 19.09 5.99 31.38 11.42 8.80 10.11 1.85 18.29 Sumas River 3 Avg Std Dev C o V (%) 2-Feb-04 1-Mar-04 9.48 11.54 10.51 1.46 13.92 42.21 59.68 50.95 12.36 24.25 15.06 17.68 16.37 I. 86 II. 35 7.15 8.05 7.60 0.64 8.37 Sumas River 3 Avg Std Dev C o V (%) 22-Mar-04 19-Apr-04 25.46 9.79 17.63 11.08 62.85 126.78 45.37 86.08 57.56 66.87 23.55 20.63 22.09 2.07 9.36 8.95 7.96 8.45 0.71 8.34 Sumas River 7 A v g Std Dev C o V (%) 14-Oct-03 7-Nov-03 10.62 5.90 8.26 3.34 40.41 24.79 11.94 18.37 9.09 49.50 18.32 18.32 18.32 0.00 0.00 9.70 9.70 9.70 0.00 0.00 Sumas Canal 8 A v g Std Dev C o V (%) 10-Dec-03 2-Feb-04 0.00 0.00 0.00 0.00 0.00 44.78 28.65 36.71 11.41 31.07 189.47 91.60 140.54 69.21 49.25 2.62 2.64 2.63 0.01 0.51 Arnold Slough 10 Avg Std Dev C o V (%) 14-Oct-03 30-Oct-03 0.00 0.00 0.00 0.00 0.00 319.90 180.56 250.23 98.52 39.37 25.58 28.56 27.07 2.10 7.77 0.00 0.00 0.00 0.00 0.00 Arnold Slough 10 A v g Std Dev C o V (%) 30-Oct-03 24-Nov-03 0.00 0.00 0.00 0.00 0.00 520.49 23.66 272.08 351.31 129.12 29.34 28.82 29.08 0.36 1.25 10.45 10.45 10.45 0.00 0.00 Arnold Slough 10 A v g Std Dev C o V (%) 10-Dec-03 12-Jan-04 0.00 0.00 0.00 0.00 0.00 57.73 149.44 103.59 64.85 62.61 42.20 44.38 43.29 1.54 3.56 8.48 8.48 8.48 0.00 0.00 213 Table D1. Continued Site Deployment Date Retrieval Date Al _p£b_ Fe _epb_ Mn _p£b_ Ni _p£b_ Arnold Slough 10 A v g Std Dev C o V (%) 12-Jan-04 2-Feb-04 0.00 0.00 0.00 0.00 0.00 29.00 28.79 28.90 0.15 0.51 38.23 40.48 39.36 1.59 4.03 8.10 8.60 8.35 0.35 4.22 |Arnold Slough 10 JAvg Std Dev C o V (%) 2-Feb-04 1-Mar-04 0.00 0.00 0.00 0.00 0.00 434.45 559.14 496.80 88.17 17.75 96.97 39.45 68.21 40.67 59.62 6.56 6.57 6.57 0.00 0.05 Arnold Slough 10 A v g Std Dev C o V (%) 1-Mar-04 22-Mar-04 0.00 0.00 0.00 0.00 0.00 50.49 33.37 41.93 12.11 28.87 50.14 46.59 48.36 2.51 5.19 5.84 5.66 5.75 0.13 2.19 Marshall Creek 13 A v g Std Dev C o V (%) 2-Feb-04 1-Mar-04 0.00 0.00 0.00 0.00 0.00 31.56 23.37 27.46 5.79 21.08 52.39 40.85 46.62 8.17 17.51 0.00 0.00 0.00 0.00 0.00 Vedder Mountain 19 A v g Std Dev C o V (%) 24-Nov-03 10-Dec-03 186.88 430.92 308.90 172.56 55.86 221.18 531.52 376.35 219.44 58.31 10.19 18.23 14.21 5.69 40.02 0.00 0.00 0.00 0.00 0.00 [Vedder Mountain 19 A v g Std Dev C o V ( % ) 10-Dec-03 12-Jan-04 126.26 196.31 161.28 49.53 30.71 163.24 202.42 182.83 27.70 15.15 5.50 7.33 6.42 1.29 20.17 0.00 0.00 0.00 0.00 0.00 Vedder Mountain 19 [Avg Std Dev C o V (%) 2-Feb-04 1-Mar-04 165.53 12.50 89.01 108.20 121.56 215.14 13.28 114.21 142.74 124.98 5.62 0.00 2.81 3.97 141.42 0.00 0.00 0.00 0.00 0.00 Vedder Mountain 19 |Avg Std Dev C o V (%) 1-Mar-04 22-Mar-04 0.00 302.48 151.24 213.89 141.42 5.72 340.87 173.30 236.99 136.75 35.92 8.39 22.16 19.47 87.86 0.00 0.00 0.00 0.00 0.00 214 T t o T t o I c 3 0 re re LU JD CL E 3 C "E _ 3 < JD ro 'ro > ro o CQ 3 (0 a) a: i -o Q csi Q 0 JD ro JQ Q) T t 9 c re co o 6 o> a co o • > o z co o I u O a 0 o o <( o o o 0 0 7 0 0 0 o o d d O CO CN O O O) N O o <9 < o o oo c i ^ z c i d oo T- O 0 0 ^ O O LO o o o o d d d d o o o o o d d c i c i d co CM o o o o d d oq < N-oo ^ T-co ^ in o o ^ d d z o co o o CN n N oo 0 0 0 0 2 §» _ > > > cci o O oc or oi o = co co co CO T , 2 ro ro ro ro 2 -c E E E E ° £ 3 3 3 3 E TO Cfl CO CO CO <t S Z Z Z O 0 0 CD CM CO d d co o co co oo O T f o 0 0 o o J g CO JD CL CL c 2 0 JD ro 'ro > ro o CO 3 CO 0 a: H o Q m Q 0 JD ro T t O 41 T t O I re re LU re JD co o I o 0 a CO o • > o z co o • o O a 0 co T o co < o i g> d d LO LO O LO g d ^ CD ° ° CO ^ LO 1^ P O CO jri LO ^ CO CO T— I s - CN CD co CO <C LO d I s - I s - h -O ^ S LO CO T-h - LO d CO T t CM ^_ § - <N ? 0 ) 0 . 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Boxplots of Bioavailable Aluminum (ppb) results by sampling date and sampling site. Tributary Legend: HS: Headwater region of Sumas River, BS: Border region of Sumas River, DS: Downstream region of Sumas River, AS: Arnold Slough, MC: Marshall Creek, SC: Sumas Canal, RF: Vedder Mountain Reference site. 218 1500H a a Fe 1000 — V £\ n ' ro > ra o 5 500 — O H * AS 10 AS 10 * AS 10 O AS 10 HS 2 l I I l 1 1 1 1 1 1 30-OCT-0324-NOV-03 10-DEC-0312-JAN-04 02-FEB-04 01-MAR-0422-MAR-0419-APR-0417-MAY-04 07-JUN-04 n=4 n=7 n=7 n=7 n=6 n=7 n=6 n=7 n=5 n=7  Date 22-MAR-04 o o 10-DEC-03 o 17-MAY-04 10-DEC-03 12-JAN-04 07-JUN-04 u 22-MAR-04 o 1— HS 2 n=10 1 RF 19 n=10 BS 3 n=8 D S 7 n=8 AS 10 n=10 Site ID MC 13 n=9 SC 8 n=8 Figure D2. Boxplots of Bioavailable Iron (ppb) results by sampling date and sampling site. Tributary Legend: HS: Headwater region of Sumas River, BS: Border region of Sumas River, DS: Downstream region of Sumas River, AS: Arnold Slough, MC: Marshall Creek, SC: Sumas Canal, RF: Vedder Mountain Reference site. 219 * S C 8 I I I I 1 I i 1 1 1 30-OCT-0324-NOV-03 10-DEC-03 12-JAN-04 02-FEB-04 01-MAR-0422-MAR-04 19-APR-0417-MAY-04 07-JUN-04 n=7 n=5 n=7 n=4 n=7 n=7 n=7 n=6 n=7 n=6 Date 1 2 0 H n a. a. o A as "<5 > n o 80 H OQ 4 0 H 17-MAY-04 22-MAR-04 O HS 2 n=10 BS 3 n=8 DS 7 n=8 AS 10 n=10 MC 13 n=9 SC 8 n=8 RF 19 n=10 Site ID Figure D 3 . Boxplots of Bioavailable Manganese (ppb) results by sampling date and sampling site. Tributary Legend: HS: Headwater region of Sumas River, BS: Border region of Sumas River, DS: Downstream region of Sumas River, AS: Arnold Slough, MC: Marshall Creek, SC: Sumas Canal, RF: Vedder Mountain Reference site. 220 30-OCT-0324-NOV-03 10-DEC-0312-JAN-04 02-FEB-04 01-MAR-0422-MAR-0419-APR-0417-MAY-04 07-JUN-04 n=7 n=5 n=7 n=4 n=7 n=7 n=7 n=6 n=7 n=6 Date o 22-MAR-04 HS 2 n=10 10-DEC-03 01-MAR-04 * 02-FEB-04 * BS 3 n=8 DS 7 n=8 AS 10 n=10 Site ID MC 13 n=9 SC 8 n=8 l RF 19 n=10 Figure D4. Boxplots of Bioavailable Nickel (ppb) results by sampling date and sampling site. Tributary Legend: HS: Headwater region of Sumas River, BS: Border region of Sumas River, DS: Downstream region of Sumas River, AS: Arnold Slough, MC: Marshall Creek, SC: Sumas Canal, RF: Vedder Mountain Reference site. 221 10.0 H J3 Q. a c N a) J3 ro 'ro > ro o ffi 7.5 H 5.0 H 2.5 H 0.0 H I I 1 1 1 1 1 30-OCT-03 24-NOV-03 10-DEC-03 12-JAN-04 02-FEB-04 01-MAR-04 22-MAR-04 19-APR-0417-MAY-04 07-JUN-04 n=7 n=5 n=7 n=4 n=7 n=7 n=7 n=6 n=7 n=6 Date 10.0 — n a. c N o> n ro 'ro > ro o m 7.5 H 5.0 — 30-OCT-03 •X-2.5 • 0.0 — 30-OCT-03 * HS 2 n=10 BS 3 n=8 DS 7 n=8 AS 10 n=10 Site ID MC 13 n=9 SC 8 n=8 RF 19 n=10 Figure D5. Boxplots of Bioavailable Zinc (ppb) results by sampling date and sampling site. Tributary Legend: HS: Headwater region of Sumas River, BS: Border region of Sumas River, DS: Downstream region of Sumas River, AS: Arnold Slough, MC: Marshall Creek, SC: Sumas Canal, RF: Vedder Mountain Reference site. 222 Appendix E: Sediment Sampling Results Table E1. QA/QC Results for sediment samples. Table E2. QA/QC Results for Priority PollutnT™/CLP Lot No. DO35-540 reference sediment sample (ppm). Table E3. Sediment sampling results (1993, 1994, 2003, 2004). Figure E1. Sediment data by tributary (2003 and 2004 data only). Figure E2. 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CM CO ^ I s - CO oi ( d i o i o i s c d CO CN co T - c o T t T t o o CN T t T-cocNscocqinN c o c o o i T - S T t s o o s co c o c o T - i n in T - T - 1 -p CD CO CD S CN LO O Tt T- ' CO O T~ d c q co c q CD oq T T - oq in in CN d T—• CM oi CM T t d I o u i n c o c o c o c o o o c o c o c o C N T t c N d d d d T t T t C O C O C O C D C D L O T - T - T -CN c q c q d T t co CM T - T -p co Tt d CD CO d d co co o o S S T t o CO O) c N ^ c / ) C M c / 3 T t t - - c N i n d s ' ^ d ^ i - d d d C N O O Z T t Z ^ o j T - T -co P o Z ^ v 00 T-; d CM o co T— (O yj in CO i i n o CO CO P CO c p z z ^  " z * ° co cn co C o C M c o p T t c q T - T t o ^ C O ^ T t C O T t C N T - T -T - S T t d d CN T t CD T t CM TT T t c o s in T"™" l O T ~ CN IO cy) 00 CO O) - r -Tf™" TT™ ^5 CO T ~ LO* T ~ OJ ai E re CO 2 CN " c o ^ T t C N CD IS-CD C N ° T -SZ CO 3 o co o c T t ~ CD £ o co co CQ_ « in 00 CD CM CJ) T t o ro sz £2 ro ro c ro O co ro E 3 co_ CD S O) O T - CO CD CM CN CN CO CO CO CO O b 0 ro 0. co ro E 3 229 E a. & z 2004 C O S 2 S 5 C M L O C O C N C O C O r-^.Zl(D<X)t~~COCOCO T J - ^ ^ O D C O O O T — T — T — 1180 94.4 100 RR ft 91.9 77.9 51.3 61.3 62.1 N/S 09.0 T f f- CO CM T t T - T f d d C N T t ' d T t in oo oo T ~ C D C D co 19.0 33.6 2003 1401 110 107 Qn Q 105 96.3 64.2 46.4 o o T f T f d oo co co N ; N ; T - CM in T - ; CO o s T f C N d d d CO CD CO 0 0 I S - CO CM 23.8 22.5 1994 c o ^ ^ i n ^ m i n o o C \ I ^ Z O O Z C O C N T - C O 1346 N/S 73.1 RR R OO.O 106 84.8 37.5 79.2 N/S 64.9 on 7 CO CO CO ° 0 CO O CO ^ ^ T - CM ^ O CN 20.5 N/S 1993 W C O C O O O T - C B C O N Z o i Z f l O ( O N W i - ( j ) 1330 T f T f C O CN s o co T - 85.2 91.5 43.3 61.3 ( O O r d d T-' C D C O CM co co co eg I S - C M oo O ) T f i S T-' c\i ^ L O S ^ C D T f CO C O N/S N/S Na (ppm) 2004 C M C N T - T J - C O C O T - C O O O i n c o c o c o i O T - T - c o T f M O M C O C O T t O X O S CN CM C O 1073 445 O LO L O 0 0 co co CO CM in r-T f CO co CO •<-oo ^  T -N - Z f- 508 1012 1088 848 629 1366 co co C O oo Na (ppm) 2003 io229oococotio C O S S S l D ' - O ' O O ) T ~ V V V T - T - T - C \ | T - <100 co T f s CM LO CO CN C O C O O CO L O f~-CN C O T - 0 0 T f oo CM CM 0 0 T f O L O C D in CM T - T -T f T f T - CN T - CD T f T - o co in CN CO CN CM CM CM T f CM T - T -C D co <100 Na (ppm) 1994 T f T f c o c o c o c o i ^ T - c g C N T - Z T - Z T - C N C N T - <100 CO I S - T -^ L O O Z CN CN O C O CO i -CM CM C O CN 0 0 T ~ T - CN co r: L O ^ o Z CM C N co co co co T t o —• O T f '— T f T — Z Z in T f Z CM CM 0 0 N/S Na (ppm) 1993 cOTtc/joo-<-Tf-T-r-.r^ Z T - Z T - T - T - C M T - C M <100 C O T f T -L O C O CO CN CM CM T - T f co co •<- CN C O C O f- CO C O T - oo C D CN T f C O CM T f T f C O C O C O CO 1^- CO CM O ^ T - C O f- L O C O C O Z CN CN CM T — N/S N/S E -Q . CL 2004 7232 2191 261 1629 1351 708 600 635 T f O co 1326 870 bob co co co in r-- C M CO f -f~- r~-co 515 N/S H 070 lZf\J ° co in S S S S 0 5 £2 T - "ii CO T f T - T f T f C O O CO T f IO f-CO co CO co T f T f 2003 6552 996 1404 917 1405 1063 1197 228 529 co 1889 525 707 r- i -co T -T f CO co o L O T f 431 744 1205 L O in C D C O CN CN C O s eg co T f T f co s T f CO h - CO CO I O L O 1306 oo eg CO Mn | 1994 1404 2653 1385 N/S 1124 711 306 420 CO CO CD CO CO CO ^ T t Z T f T -C O T -co co T f C O C D L O L O C O CN C O N/S 514 •\r\RO CO CO r- r- C O CN L O ^ ^ CO CO ^ CO CM Z Z io io Z s co 1219 N/S Mn | 1993 N/S 1363 k 1 IO N/S 966 870 1020 804 281 464 CM CO L O C O CN 0 0 CO L O CO com T -T f C O T f T t CO T ~ C O T f C D T f 979 402 137b CN S CO L O CN T f o CO S C O T f C O L O C O _ Z CO 0 0 CD T f N/S N/S E a. n 2004 17468 126150 116096 8628 119259 113189 23268 24294 21322 148202 6745 5149 7192 9184 8322 6916 6248 6159 N/S 6875 T f co T t oo C M m s i - in I M T f T f s o h - o co T f L O co s co co co co co co 3321 10296 2003 14988 117785 101620 119412 117405 99012 23243 20689 8711 149042 4293 7365 6131 10165 7883 6642 4575 8910 5187 3961 T - co T - o o L O T t co L O f-- co co o co C M co o •«- T t co co in N s T f co T f 3438 4507 CO S 1994 •—It — CO CO CO o ( D m W n c / J C O T f O N coS^co^ocNjcoco coSZcDZooTfCNO 1 - ~ T f | V - C N T - T - 156178 N/S 4993 5411 11744 7717 5176 7434 N/S 7667 4385 N/S N/S 11306 8131 N/S 6436 7061 2793 N/S 1993 |? co C M r- co T f cOis lcy jcocoT - coT fco ^ S ^ C O C M T - O C O C M ZlZZcOCMCDCOinCM h- C O L O CN T - T - 174870 CO CO o C O 1^  CM O CO o oo L O co 7552 7774 5111 5376 6541 8248 3101 6746 6099 N/S 5393 3955 7478 5429 N/S N/S Tributary Sample ID 5° CN » CO £ T f £ co ^  CD > or co co E — CO Swift Creek 1 Arnold Slough 121 10 11 Saar Creek 14 118 Marshall Creek 13 5 Sumas Canal 128 146 Sumas Prairie Ditch 126 127 129 130 131 133 136 Sumas Mountain 15 Vedder Mountain 19 230 E a. a. c N 2004 (j) O ) O O l L O T - 0 0 L O T _ O N CO T t ' CD CN LO ° CO T - L O i n c o co s o o T - cn 31.2 oo co co CO CD o T - T - T f 88.6 83.4 co oo in co T— T — 94.3 N/S 163 75.2 106 1 07 86.8 114 159 188 in 47.4 2003 CN LO s co CO CN O C O S C N c o ' c D i r i d c D ' o o ' s ' c o T - co co T J - s s oO co s 27.7 LO O CO CO CD CN ^— T ~ • T— 96.5 106 CN CN LO in 82.0 122 162 72.2 109 (0.3 85.1 92.0 153 135 CN CD T— 34.0 1994 109 40.7 N/S 60.6 N/S 79.4 75.3 62.7 62.7 31.4 N/S 124 RO A 79.8 76.0 in CM O T - N/S 76.1 139 CO CO cp co CO T - LO ^ ^ oo co ^ in co Z Z CO •«- Z T- CD co o N/S 1993 ^ oi ^ T t s C O S CO CN ^ , CN ^ LO CO CO s s s 26.6 92.4 . 164 7 70.0 83.2 00 T " i - CO 84.9 94.3 133 74.8 101 N/b 123 71.9 125 147 N/S N/S ? a CL CO 2004 C O C O T t T l - S C O L O C D C D C O S C O S C N C D L O C D l O c o c o T r c o T j - T j - c D L o c o s CO T f 1517 1066 970Q £.1 OO 2071 853 1759 1273 1029 N/S QfiQ 2042 4821 1118 648 639 604 1349 1643 CD CD 2003 CN r o c o c o c o c o C j S S C D T f L O L O T f T f ^ ^ C N T— CT> co 5013 789 QOQ OOO 2146 1750 1534 1326 S CO CD N CM O l CO O CD T - CM T - 1769 1254 745 3131 1791 1295 1526 2907 CO CO CO 1994 C O L O C O C D C O C O O S T -C O L O ^ L 0 ^ 5 - > - - < - c " c N CO CD Z CD Z C O S _ CO CO CD co N/S 854 4 4 OQ 1031 980 1340 713 N/S 1038 1 o / u CO CO S CD CO T - co Z Z S LO Z 00 CM 3225 N/S 1993 C O c o t f l c o c o c o c D r i o ^ O T ^ C N T f C O O ^ S Z m Z c n CD cn oo ^ N CO co T f 1- O CD CN CN S CO CO CO 1305 1126 1543 1163 3589 1148 OO 1 o 904 1223 N/S 695 2133 832 1485 S/N S/N ? CL a X I a. 2004 in co m m m LOLO L O L O C N r n C N C N C N C N C N C N C N V C N V V V v v v v <25 26.1 <25 31.5 in m CN CN V V in in CM CM V V in co in CM ^ CM V Z V in in m in in in in CM CN CN CM CM CM CM V V V V V V V <25 <25 2003 C N L O L O L O L O L O L O T - L O ,+ CM CN CN CN N ( N o N CO V V V V V V CD v <25 33.0 <25 88.1 28.9 35.0 in m CM CM V V 110 36.6 <Zo <25 29.5 <25 <25 29.1 33.2 40.6 <25 <25 1994 L O L O C O L O C O L O L O L O L O C N C N ^ C N ^ C N C N C N C N v v Z v Z v v v v <25 co LO m ^ CN CN Z V V in m CN CN V V 63.2 <25 co m in ^ CN CN Z V V co co LO LO co LO q ^ CM CM CM CD Z Z V V Z V CO <25 S/N 1993 C O L O C O L O L O L O L O L O L O ^ C N ^ C N C N C N C N C N C N Z v Z v v v v v v <25 in in in CN CN CN V V V in in CM CN V V LO in CM CN V V in in in CM CN CN V V V LO LO CO LO LO LO LO CN CM ^ CN CN CM CN V V Z V V V V N/S N/S ? a. n 2004 3296 622 312 1640 976 1016 2450 2005 1540 co T f 7117 7644 4855 3235 1653 1307 2402 8083 N/S 5216 8847 6354 6439 7273 10846 4973 2193 CN CN 00 o CM co 2003 ^ L o n N o o g g c N ^ T - C O T f O O C O ^ ^ C D 68.9 7680 7991 4759 3181 5057 1271 2855 1466 4631 5210 7528 9421 5588 8086 12676 4704 2989 O T f co CO s in a. 1994 2000 505 N/S 1038 N/S 1275 1493 1008 1013 85.1 N/S 9740 1139 1486 2353 CD CD 00 S CD CD N/S 1282 5067 N/S N/S 2889 8101 N/S 5524 1452 CO 00 S/N 1993 N/S 225 N/S 815 1675 1257 1689 1136 1078 52.4 3131 9941 1212 1921 2919 979 1741 8817 1592 5794 10465 6934 N/S 7720 8445 4522 3161 N/S N/S Tributary Sample ID £ ( N , ® C o ! £ T t C N c O S k . CD > bu m CO E CO Swift Creek 1 Arnold Slough 121 10 11 Saar Creek 14 118 Marshall Creek 13 5 Sumas Canal 128 146 Sumas Prairie Ditch 126 127 129 130 131 133 136 Sumas Mountain 15 Vedder Mountain 19 231 12000 — 10000H Tributary 2000 — Tributary Figure E1. Sediment data by tributary (2003 and 2004 samples only). Tributary Legend: HS: Sumas River Headwaters; BS: Sumas River Border Region; DS: Sumas River Downstream Region; SW: Swift Creek; SA: Saar Creek; AS: Arnold Slough; MC: Marshall Creek; SC: Sumas Canal; PD: Sumas Prairie Ditches; SM: Sumas Mountain; RF: Vedder Mountain Reference Site. 232 6 0 -Q . 4 0 -a o o 20-n=6 n=5 n=6 n=2 n=4 n=6 n=4 n=3 SC146 O PD12I I DS n =i6 PD13J 1 1 PD SM n=2 HS BS SW SA AS MC SC RF Tributary 300 — 200-E a a 100 —n O S503 AS122 O n=6 n=5 n=6 n=2 n=4 n=6 n=4 n=3 1 HS 1 BS DS 1 SW SA AS i MC SC PD i SM RF Tributary Figure E1 continued. Sediment data by tributary (2003 and 2004 samples only). Tributary Legend: HS: Sumas River Headwaters; BS: Sumas River Border Region; DS: Sumas River Downstream Region; SW: Swift Creek; SA: Saar Creek; AS: Arnold Slough; MC: Marshall Creek; SC: Sumas Canal; PD: Sumas Prairie Ditches; SM: Sumas Mountain; RF: Vedder Mountain Reference Site. 233 2 0 -* n=5 S116 n=6 n=2 - n=4 n=6 n=4 n=3 n=16 n=2 n=2 l — SW AS HS BS DS SA I MC SC PD SM RF Tributary 160000 — E a a 120000 — 80000 H 40000 — \ 11=6 I HS O S116 n=5 BS n=6 DS n=2 SW n=4 — I — SA n=6 AS n=4 MC n=3 SC n=16 PD n=2 — i — SM RF Tributary Figure E1 continued. Sediment data by tributary (2003 and 2004 samples only). Tributary Legend: HS: Sumas River Headwaters; BS: Sumas River Border Region; DS: Sumas River Downstream Region; SW: Swift Creek; SA: Saar Creek; AS: Arnold Slough; MC: Marshall Creek; SC: Sumas Canal; PD: Sumas Prairie Ditches; SM: Sumas Mountain; RF: Vedder Mountain Reference Site. 234 1000 — 750-E a a 500-250 -n=6 n=5 n=6 n=2 n=4 n=6 n=4 n=3 n=16 n=2 TFT HS BS DS SW SA AS MC SC PD SM I RF Tributary 1 5 0 0 0 0 — 5 0 0 0 0 — n=6 n=5 §503 n=6 n=2 i HS I DS I SA I — SM BS SW AS MC SC PD RF Tributary Figure E1 continued. Sediment data by tributary (2003 and 2004 samples only). Tributary Legend: HS: Sumas River Headwaters; BS: Sumas River Border Region; DS: Sumas River Downstream Region; SW: Swift Creek; SA: Saar Creek; AS: Arnold Slough; MC: Marshall Creek; SC: Sumas Canal; PD: Sumas Prairie Ditches; SM: Sumas Mountain; RF: Vedder Mountain Reference Site. 235 7500 5000 — ] SJ502 n=6 HS n=5 BS n ° . S 1 3 4 n = 2 H=4" DS SW SA n=6 AS n=4 MC n=3 SC n=16 PD n=2 — i — SM n=2 RF Tributary 1200 — E 800-a a « 400 — I 1 n=6 HS n=5 — I — BS n=6 DS n=2 — I — SW n=4 n=6 n=4 SA AS MC n=3 SC n=16 PD n=2 SM n=2 RF Tributary Figure E1 continued. Sediment data by tributary (2003 and 2004 samples only). Tributary Legend: HS: Sumas River Headwaters; BS: Sumas River Border Region; DS: Sumas River Downstream Region; SW: Swift Creek; SA: Saar Creek; AS: Arnold Slough; MC: Marshall Creek; SC: Sumas Canal; PD: Sumas Prairie Ditches; SM: Sumas Mountain; RF: Vedder Mountain Reference Site. 236 SA AS MC Tributary r sc i PD 12000H 8000 —i £ Q . a a. 4000 —i n=6 ~HS O S116 n=5 n = 6 — i 1— n=2 n=4 n=6 n=4 n=3 n=16 l SA AS n=2 SM n=2 BS DS SW MC SC PD RF Tributary Figure E1 continued. Sediment data by tributary (2003 and 2004 samples only). Tributary Legend: HS: Sumas River Headwaters; BS: Sumas River Border Region; DS: Sumas River Downstream Region; SW: Swift Creek; SA: Saar Creek; AS: Arnold Slough; MC: Marshall Creek; SC: Sumas Canal; PD: Sumas Prairie Ditches; SM: Sumas Mountain; RF: Vedder Mountain Reference Site. 237 Tributary Tributary Figure E1 continued. Sediment data by tributary (2003 and 2004 samples only). Tributary Legend: HS: Sumas River Headwaters; BS: Sumas River Border Region; DS: Sumas River Downstream Region; SW: Swift Creek; SA: Saar Creek; AS: Arnold Slough; MC: Marshall Creek; SC: Sumas Canal; PD: Sumas Prairie Ditches; SM: Sumas Mountain; RF: Vedder Mountain Reference Site. 238 1993 1994 2003 2004 Year * SC128 O SC146 O PD130 n=24 n=21 n= 30 n=28 i — 1994 I 2004 1993 2003 Year Figure E2. Sediment results by year collected (all sites). Site ID Legend: S: Sumas River; SW: Swift Creek; SA: Saar Creek; AS: Arnold Slough; MC: Marshall Creek; SC: Sumas Canal; PD: Sumas Prairie Ditches; SM: Sumas Mountain; RF: Vedder Mountain Reference Site. Numbers represent specific sampling locations along the tributary. 239 * S501 60.00 —| L L ) 40.00—] * * O o S501 SW500 S116 S114 n= 24 * SW500 O S116 O S114 nj21 I 1994 * SW500 S501 S600 S115 S116 S114 30 # S600 S501 # SW500 * S115 S114 S506 n=28 1993 2003 2004 Year SW500 * SW500 * S501 O S116 O S114 O S115 SW500 S501 § S116 O S114 * O S501 S115 S116 S600 S114 SW500 S600 S115 S114 S501 n — 1993 n=21 — I — 1994 n=30 2003 n=28 2004 Year Figure E2 continued. Sediment results by year collected (all sites). Site ID Legend: S: Sumas River; SW: Swift Creek; SA: Saar Creek; AS: Arnold Slough; MC: Marshall Creek; SC: Sumas Canal; PD: Sumas Prairie Ditches; SM: Sumas Mountain; RF: Vedder Mountain Reference Site. Numbers represent specific sampling locations along the tributary. 240 20 — Year 200000 — 150000—1 E a a U- 100000 —\ 50000 — * SC146 * AS122 O PD133 O PD130 -n=*r tH30 n=28~ 1 2003 2004 1993 1994 Year Figure E2 continued. Sediment results by year collected (all sites). Site ID Legend: S: Sumas River; SW: Swift Creek; SA: Saar Creek; AS: Arnold Slough; MC: Marshall Creek; SC: Sumas Canal; PD: Sumas Prairie Ditches; SM: Sumas Mountain; RF: Vedder Mountain Reference Site. Numbers represent specific sampling locations along the tributary. 241 * PD136 O SC135 n=24 n=21 O S503 O MC504 n " n S501 SW500 n=28 1993 1994 I 2003 2004 Year 150000H 100000—^ 50000 — SW500 S501 S116 * S115 O S114 ~n=2T~ * SW500 * S501 * S114 * S116 n=21 SW500 S501 S116 S115 S600 S114 i 2003 SW500 S501 S115 S600 S114 -n^28" — l 2004 1994 Year Figure E2 continued. Sediment results by year collected (all sites). Site ID Legend: S: Sumas River; SW: Swift Creek; SA: Saar Creek; AS: Arnold Slough; MC: Marshall Creek; SC: Sumas Canal; PD: Sumas Prairie Ditches; SM: Sumas Mountain; RF: Vedder Mountain Reference Site. Numbers represent specific sampling locations along the tributary. 242 3000 O S501 2000 — E o. Q . C S 1000 — n=24 n=21 n=30 n=28 1994 2003 2004 Year 1200 — E a a ra 4 0 0 - H SC146 n=24 O n=21 PD129 PD130 PD130 n=30 n=28 1993 1994 I 2003 2004 Year Figure E2 continued. Sediment results by year collected (ali sites). Site ID Legend: S: Sumas River; SW: Swift Creek; SA: Saar Creek; AS: Arnold Slough; MC: Marshall Creek; SC: Sumas Canal; PD: Sumas Prairie Ditches; SM: Sumas Mountain; RF: Vedder Mountain Reference Site. Numbers represent specific sampling locations along the tributary. Extreme outliers: Mn: Sumas River site #506: 6552 ppm (2003) and 7232 ppm (2004). 243 SW500 * S501 * S116 * S114 * S115 n=24 * SW500 * S501 * S116 O S114 # # SW500 S501 S116 S600 S115 S114 n=21 n=30 * SW500 S600 S501 S115 S114 S506 n=28 1993 1994 2003 Year 2004 n= 24 PD131 * AS122 * PD130 O PD133 O SC146 !fl2JL n=t30 28 I 1993 1994 2003 Year 2004 Figure E2 continued. Sediment results by year collected (all sites). Site ID Legend: S: Sumas River; SW: Swift Creek; SA: Saar Creek; AS: Arnold Slough; MC: Marshall Creek; SC: Sumas Canal; PD: Sumas Prairie Ditches; SM: Sumas Mountain; RF: Vedder Mountain Reference Site. Numbers represent specific sampling locations along the tributary. 244 SC128 # SC146 * AS121 * PD127 O PD131 n= 24 * SMS05 O SC146 n=l21 n= 30 1 — 1994 I 2003 2004 Year u^u • 150 —\ E a a c 1 0 0-I N 50 —H n=24 n=21 n=30 n=28 l 2003 1993 1994 2004 Figure E2 continued. Sediment results by Year year collected (all sites). Site ID Legend: S: Sumas River; SW: Swift Creek; SA: Saar Creek; AS: Arnold Slough; MC: Marshall Creek; SC: Sumas Canal; PD: Sumas Prairie Ditches; SM: Sumas Mountain; RF: Vedder Mountain Reference Site. Numbers represent specific sampling locations along the tributary. Extreme outlier: Zn: Arnold Slough site #125: 406 ppm (2004). 245 Appendix F: Spearman Rank Correlation Coefficients Table F1. Spearman rank correlation coefficients for wet season water data. Table F2. Spearman rank correlation coefficients for dry season water data. Table F3. Spearman rank correlation coefficients for both seasons water data. Table F4. Spearman rank correlation coefficients for DGT, physical water quality, and precipitation data. Table F5. Spearman rank correlation coefficients for sediment elements. Table F6. Spearman rank correlation coefficients for common metals in water, DGT, and sediment. Table F7. Spearman rank correlation coefficients for dissolved elements in water and sediment bound elements. Table F8. Spearman rank correlation coefficients for nutrients and land use indicators. Table F9. Spearman rank correlation coefficients for physical water quality parameters and land use indicators. Table F10. Spearman rank correlation coefficients for dissolved trace metals and land use indicators. Table F11. Spearman rank correlation coefficients for bioavailable trace metals and land use indicators. Table F12. Spearman rank correlation coefficients for sediment bound metals and land use indicators. 246 o II c o ro o o c co o i*— 'c g> 'w <o "co o TJ c o CQ CO CO Q l_ OJ •4—' co c o CO CO 0) CO co c 0) o it cu o O c o ro o O c ro Qi c ro ro co Q. CO J3 Diss. Si 0.641 0.000 80 0.497 0.000 80 0.662 0.000 80 0.276 0.013 80 -0.753 0.000 64 0.389 0.001 64 -0.509 0.000 80 0.700 0.000 80 0.533 0.000 80 0.777 0.000 1* 0.815 0.000 80 0.691 0.000 80 0.272 0.015 80 0.545 0.000 80 -0.511 0.000 64 0.781 0.000 64 -0.391 0.000 80 0.739 0.000 80 0.339 0.002 80 0.659 0.000 a 0.479 0.000 80 0.451 0.000 80 0.708 0.000 80 0.110 0.330 80 -0.467 0.000 64 0.204 0.106 64 -0.412 0.000 80 0.454 0.000 80 0.367 0.001 80 0.617 0.000 Q 0.618 0.000 80 0.224 0.046 80 -0.027 0.812 80 0.407 0.000 80 -0.198 0.117 64 0.266 0.034 64 0.202 0.072 80 0.691 0.000 80 0.248 0.026 80 0.249 0.026 Diss. K 0.804 0.000 80 0.864 0.000 80 0.643 0.000 80 0.678 0.000 80 -0.604 0.000 64 0.763 0.000 64 -0.523 0.000 80 0.803 0.000 80 0.536 0.000 80 0.719 0.000 % <» «5U- 0.307 0.006 80 0.504 0.000 80 0.684 0.000 80 0.103 0.362 80 -0.382 0.002 64 0.304 0.014 64 -0.478 0.000 80 0.283 0.011 80 0.406 0.000 80 0.465 0.000 Q 0.706 0.000 80 0.619 0.000 80 0.571 0.000 80 0.361 0.001 80 -0.509 0.000 64 0.464 0.000 64 -0.362 0.001 80 0.767 0.000 80 0.471 0.000 80 Temp 0.525 0.000 80 0.271 0.015 80 0.467 0.000 80 0.319 0.004 80 -0.337 0.006 64 0.499 0.000 64 -0.547 0.000 80 0.545 0.000 80 0.471 0.000 Sp. Cond. 0.908 0.000 80 0.663 0.000 80 0.473 0.000 80 0.601 0.000 80 -0.487 0.000 64 0.597 0.000 64 -0.257 0.021 80 ^ oo 0.545 0.000 80 0.767 0.000 X a. -0.252 0.024 80 -0.291 0.009 80 -0.452 0.000 80 -0.275 0.014 80 0.587 0.000 64 -0.577 0.000 64 ^ co -0.257 0.021 80 -0.547 0.000 80 -0.362 0.001 DOC 0.637 0.000 64 0.720 0.000 64 0.217 0.085 64 0.759 0.000 64 -0.486 0.000 48 -0.577 0.000 64 0.597 0.000 64 0.499 0.000 64 0.464 0.000 DO -0.426 0.000 64 -0.357 0.004 64 -0.340 0.006 64 -0.291 0.020 64 CO -0.486 0.000 48 0.587 0.000 64 -0.487 0.000 64 -0.337 0.006 64 -0.509 0.000 O a. 0.634 0.000 fin 0.735 0.000 an \J\J 0.239 0.033 80 ^ co -0.291 0.020 64 0.759 0.000 64 -0.275 0.014 Ou 0.601 0.000 fin ou 0.319 0.004 fin 0.361 0.001 z • + Tf X z 0.448 0.000 80 0.469 0.000 80 0.239 0.033 80 -0.340 0.006 64 0.217 0.085 64 -0.452 0.000 80 0.473 0.000 80 0.467 0.000 80 0.571 0.000 z 1 ' CO o z 0.688 0.000 80 0.469 0.000 80 0.735 0.000 80 -0.357 0.004 64 0.720 0.000 64 -0.291 0.009 80 0.663 0.000 80 0.271 0.015 80 0.619 0.000 a _ . o ^ co 0.688 0.000 80 0.448 0.000 80 0.634 0.000 80 -0.426 0.000 64 0.637 0.000 64 -0.252 0.024 80 0.908 0.000 80 0.525 0.000 80 0.706 0.000 Corr. Coef. Sig. (2-tailed) Corr. Coef. Sig. (2-tailed) N Corr. Coef. Sig. (2-tailed) N Corr. Coef. Sig. (2-tailed) N Corr. Coef. Sig. (2-tailed) N Corr. Coef. Sig. (2-tailed) N Corr. Coef. Sig. (2-tailed) N Corr. Coef. Sig. (2-tailed) N Corr. Coef. Sig. (2-tailed) N Corr. Coef. Sig. (2-tailed) o z i * CO o z z • + Tf X z Tf o a. DO DOC X O . Sp. Cond. Temp Diss. Ca 247 o co o CO o co o oo o oo o oo o oo T t co T t CO o 00 o oo TO 0 3 tz "E o o 0 JO co in o o o o cq q So d d co co o o o co q oo d d •«- o CJ) o o h 9 to o o fO LO ® o o to O o o o T t O o m o oo d d mo c o o o * o co o o CO o O O o T t q co o o CO T-oo T- o C M O » o o T t o T t T t ° * - T t c q q co d d 9° o n . o 9 d CO CN O CD o T- cq oo o o T t O CO O o c q q oo o o T t o O O o " o q oo o o rs. <o o o o c q q oo o o o5 1 o co O v • L J C N ' <S.S> CO 0) LU CO </> oo o co o o N O 00 o o CJ) o T t O o Is- O oo O O CO o CD O o in o oo d d CO CO CM O o co o oo o o o co q oo o o c n o T - O o s o oo o o c o o c o o o in q oo o o c o o o o o c o o oo d d c o o CN o r-i « ! § § 9 o CO o c o o ^ s q ( j d d 3 ° *°. o 9 d eo o N - o <o o c o o T t o iO q d d T t o c o o o c o q oo d d T t o o o c o q d d 0 ® ,9 co CO CD 00 CJ) o o CM O 00 o o oo i -Is- O o co o co O O O CO T t CM o o t— co o o C O C O C M O o c q q co o o 52 LO °2 o o 9 o c n to T t C M o C M q oo o o c o c o T t CN o CN O 00 o o T - o c n o o c o o oo d d C M C M O f - o C M q oo o o CO T t c o c o r t C M O CO d d SS I s -21 - T f • T CD 9 o r». o o o o T t q oo o o CN £ Q P oo § 9 o T t CO C N T t o C M q co o o C O o T- O o to q oo d d 0 ® ° CO O v • iJ £M ' CO CO CO o CO o o N O CO o o CJ) o O O o T t o oo o o o oo o co T t CN o O N CO o o CO o c o o o in q oo o o T- O c n o r - o d d r - o T - o o to q oo d d <o o o c q q c o o o T t o m o o T t q oo o o CM o rr o o t q o o 9 d T t CD O O T + CN T— cD d d I s - o t o 9 d o o T - CO o T - co oo o o oo o O O o s o c o o o in o T t o d d c n o t~ o o T t q oo o o 0 ® cS'|. <3.g> CO c £ tn tn co o co o o in o So d d o oo cn o o o o T t q co o o C O T-h- o c q q d d en o T t o r» o d d c o c o o o o c q q oo o o en o in o o to q oo o o c n CM CO O o c q q oo d d c n o c o o o t - o oo o o TT o f" o o ^ d o co o o z: o 5 S 9 d in o T t o o in q 55 C M in r ~ T- o CM O 00 o o T - O o> O o c o o oo o o in o T- O o c o o oo o o 0 ® 3' | . CO ra o oo c o o c o o in q d d o 2 ° q oo o c o c o c n o o C M o bo o o oo o c o o o Is", q oo o o in o o o c o o d d r-- o r» O o N 9 CO o o c o o c o o o L O o co o o o o O O o Is-. q oo o o en o § 8 ° " ! O © 9 o en T-c o o c q o d d I c o o £ o Tt h O CD 9 d c o c o t>- T- o C M q oo C M O CO O o to q co o o t - o en o o T t q oo o o 1 - o T t o <o o d d cS'|. L : CN • c§.c? CO CO tn tn 248 o II cz o •-«-» £ L . o o c co o * t 'c cp 'w CO 0 CO o TO c 32 o CD co Q w 0 co c o GO co 0 CO CT" Q w c CD o 3= 0 O o g ra £ o O c co a: tz co E L_ co 0 CL CO CM LL 0 JO CO Diss. Si 0.263 0.003 126 0.177 0.037 140 u O) o ,„ oo o jo CD O CM d d r CN CN _ N O CO CM O CM 0 0 ^ u T t oo o co jo O CJ) CM d d T~ O T t T - o o o o t O O ^ 5 IS- o T - O tO m o CM 6 6 ' " co s ,„ CD S JD O CN CM d o ' " CO tn ^ a m o ,„ co o jo T t o CM d d T~ TJ" CN ^ g S d d r IS- CO o co jp O CJ) CN d d T~ T t CO T - r- O T— T— T t d d r co oo o Jp T t O CM d d T~ co o CO o jo CO O CM d d r Temp LO O CO o JP T t O CN d d r O o 9 o ^ Sp. Cond. ui o ,„ O) O JP CO O CM d d *~ i^ - o _ T - O O co o T t d d ,~ z Q . 5 o to CN O CN d 6 ' r T t co co T - o T— T— T f d d T~ o o Q T t CD CJ) CN T " O CO T -d d r O Q P CJ) £ O) LO ^ P CD 9 o o) co LO CM m T - T - Q) o o Tf o 0 . n o , , oo T t jp T— O CN d d r CD O „ co o 2 T t o t d d r z 1 + Tf X z 5) T— JQ O CO CN O O ^ co T t 0 4 0 Cp CJ) T t z 1 ' < 0 o z c o o , „ T— o co CO O CM d d r 0 T - • T t u co T - • CN C O 0 T - 0 co c q q CN d o 1 " a) § 2 O CNJ. o co O co Z S a O 0 CO O CO z o z • ' CO 0 z T3 0) C c o O CM 0) co Diss. Si 0.429 0.000 140 0.199 0.019 140 -0.454 0.000 95 0.236 0.013 111 -0.545 0.000 140 0.553 0.000 140 -0.028 0.741 140 0.111 0.215 126 0.427 0.000 140 0.591 I 0.009 0.921 126 0.133 0.138 126 -0.227 0.027 95 0.405 0.000 111 -0.136 0.129 126 0.618 0.000 126 0.427 0.000 126 0.634 0.000 126 0.402 0.000 126 0.351 | tfi c Q * 0.461 0.000 140 0.124 0.143 140 -0.382 0.000 95 0.448 0.000 111 -0.693 0.000 140 0.301 0.000 140 -0.117 0.168 140 0.090 0.315 126 0,744 0.000 140 0.481 | $ £ o -0.038 0.671 126 0.170 0.058 126 -0.049 0.634 95 -0.167 0.080 111 0.227 0.011 126 0.618 0.000 126 -0.005 0.954 126 -0.139 0.120 126 -0.183 0.040 126 0.151 | vi </> ^ L5 0.628 0.000 126 0.245 0.006 126 -0.343 0.001 95 0.571 0.000 111 -0.345 0.000 126 0.443 0.000 126 0.112 0.213 126 0.282 0.001 126 0.529 0.000 126 o 0.456 0.000 140 0.174 0.040 140 -0.202 0.050 95 0.635 0.000 111 -0.574 0.000 140 0.136 0.110 140 -0.041 0.629 140 0.114 0.204 126 0 — • • T t 0.529 | Q -0.023 0.797 126 0.094 0.297 126 -0.137 0.184 95 0.131 0.170 111 0.078 0.382 126 0.449 0.000 126 0.453 0.000 126 CO T - • CM 0.114 0.204 126 0.282 | Temp -0.006 0.941 140 -0.334 0.000 140 -0.238 0.019 96 0.145 0.129 111 0.140 0.099 140 0.236 0.005 141 T - • T f 0.453 0.000 126 -0.041 0.629 140 0.112! Sp. Cond. 0.010 0.910 140 0.036 0.673 140 -0.255 0.012 96 0.102 0.285 111 0.014 0.871 140 T - • T f 0.236 0.005 141 0.449 0.000 126 0.136 0.110 140 0.443 X Q. -0.472 0.000 140 -0.123 0.148 140 0.601 0.000 95 -0.507 0.000 111 0 T - • T f 0.014 0.871 140 0.140 0.099 140 0.078 0.382 126 -0.574 0.000 140 -0.345 DOC 0.425 0.000 111 0.167 0.079 111 -0.322 0.001 95 -0.507 0.000 111 0.102 0.285 111 0.145 0.129 111 0.131 0.170 111 0.635 0.000 111 0.571 DO -0.371 0.000 95 -0.022 0.836 95 ^ CO -0.322 0.001 95 0.601 0.000 95 -0.255 0.012 96 -0.238 0.019 96 -0.137 0.184 95 -0.202 0.050 95 -0.343 O 0. 0.087 0.306 140 0 T - • T f -0.022 0.836 95 0.167 0.079 111 -0.123 0.148 140 0.036 0.673 140 -0.334 0.000 140 0.094 0.297 126 0.174 0.040 140 0.245 z • + X Z 0 1 - • • * 0.087 0.306 140 -0.371 0.000 95 0.425 0.000 111 -0.472 0.000 140 0.010 0.910 140 -0.006 0.941 140 -0.023 0.797 126 0.456 0.000 140 0.628 Z 1 ' « o z -0.006 0.944 140 0.489 0.000 140 0.159 0.123 95 -0.027 0.777 111 0.134 0.116 140 0.317 0.000 140 -0.119 0.160 140 0.396 0.000 126 0.114 0.179 140 0.174 o 0.091 0.310 126 0.183 0.040 126 -0.170 0.099 95 0.094 0.326 111 0.241 0.007 126 0.695 0.000 126 0.465 0.000 126 0.481 0.000 126 0.007 0.938 126 0.435 Corr. Coef. Sig. (2-tailed) N Corr. Coef. Sig. (2-tailed) N Corr. Coef. Sig. (2-tailed) N Corr. Coef. Sig. (2-tailed) N Corr. Coef. Sig. (2-tailed) N Corr. Coef. Sig. (2-tailed) N Corr. Coef. Sig. (2-tailed) N Corr. Coef. Sig. (2-tailed) N Corr. Coef. Sig. (2-tailed) N Corr. Coef. z • X z O Q. DO DOC X a Sp. Cond. Temp Diss. Ca Diss. Fe Diss. K 249 T J CD g. c o O CM LL 0 —\ co Diss. Si 0.000 126 0.375 0.000 126 0.685 0.000 140 0.299 0.001 126 O T- • T f § to O CM d T~ CO LO T f jo r - O O l o o r r*- o CM O JO cq q o i d d r co r- • CM O) * -o> o JP C M q O J 6 6'" | i o to o OJ d T _ CO CO T - CM JO o co O J d d *-o T- • r f r-- o ,„ C M O JO C O © O l d d r m o „ eo o 2 co o t 6 6'" si» Q 2 5) cp o O J d " co T - • CM O) O) T - CM JO o oo O J d d r a> m ,„ 1^ T f JO T - q O J 6 6'" m o ,„ s o jo co o O J 6 6 " tfi </> ^ Q co • CM T— 5 5 jo T - q CM 6 6 " C O o Jp r f q O J 6 6 " T ~ C D m o jp q q o i d d T~ T - O , ^ o» o jo in o O J 6 6'" is. • § CD o o i d T~ co o oo TJ- co T - o OJ T t o o o o o N O ,„ O O JO T t q o i d d r o „ C M o 2 T t q f 6 6'" o co o O J o T " CO Q 2^ o j co O LO CO T - JO o co o i d d r T f O , ^ co o jo co o o i d d 1 " T— T— CO T - CM O l o o " Temp £ CD CM O l d T~ £ •* O i r ) CD o CO o i h- oo _ 9 d " Is- o „ C M O JO r f q O l d d r CO T-CM r f O O T f 9 d " Sp. Cond. o co 5 o i d " C D O , „ T - O JO C D O O l d o r o o o d o ' " C O o T - o jo to O OJ d d r co o m o 2 m o t d o " X a 2 co q o i d " 1*- r - _ C M T— JO C M o OJ 6 d r C O o O o o C O Q T f 9 d " co cn $2 § <° 9 d T " in o T t o o L O O T f 9 d " o o a o o —• q T-d T _ h- o co So T-T o ^ co o 5 § —• m o o O T~ T f q T-d d r co co C O T - T-C M q T-d d " o a 2 L O q co o § J^ L O °. q co 9 o C M o SS ° m q co 9 o 8 a -. q OT 9 d ~ q co 9 d o a. <o O CD q O J d " O C O , „ r» in Jp T - o OJ r f CO CM T f O T— T— T f d o " " co oo 52 ^ CM d d r o> o> _ O) T - O —• q * 6 6 " z + rf X Z O CD O O l d " CO T-CO CD O CO o i o d -T ~ C D co o 2 rf q T f 6 6"" CO T— O CM JO O CO o i d o ' " oi o „ C M o 2 T f O T f 6 6 " Z 1 ' CO o z C N IO $p o O J q *~ co s co jp O CM O l d o ' " O T f T - o 2 o CO * d o 1 " C M C M r-. o jo C M q O J d d " " N C O O T - O *" 6 6 " o o co O OJ d T _ h-. C D „ T - O CO in o o i 6 d r T f 00 o co jo O CO o i d d T _ C l o ,„ C O o jo co o O J d d r co co co o jo C M q CM 6 6 " T J a) 'ro i CM co CO z 8S O jM kJ o CO O CO z T J 8 5 O CM o CO O CO z T J 8 3 O CM kJ u. • o CO O CO z T J S i s O CM t ~ o CO O CO z O) E tfi (0 5 c 2 co tf) Q ro z tfi co Q to V ) tf) O o II c o ro co Imm k. o o c 8 'c 0) 'to CO Q) ro o T J c J J o CQ ro ro Q k-0) ro T J OJ c !Q E o O CO c o (O co oj CO o CQ CO •+-* c 0J CJ CO o O c o ro CO 1 L . o O —\ c ro Oi c ro ro co CL CO co LL 0 J3 ro » ._ .<2 co Q 0.341 c\ r\r\r\ U.UUU 231 0.258 U.UUU r-- o co o jr I S - o co U ^ O J o o T t o o o cq o d d |i. r t CM O O JT CM O CO Z- CM O O co o co co T- o d d 5 O O CO O TT co o co < CM o o L O T™ 00 ^ o 9 d vi tf> ^ Q CD O r f O TT r f O CO ^ Z; CM O O LO O CM O T f O d d Diss. Fe CM 00 •<- CO TT T - o co • CM O O co T-T- o CM O d d 1" co o CO o c^  Z - ~^  CM o O N- O in o T f o d d Temp Ol CD in o N T f o co S ^ o i o o 2 o o i o 9 d Sp. Cond. 0 0 o co o o i IN- o co L: ^; CM o O co o CM O co o d d X Q. O T f •<- CO JM T - o co • ~- CM o o co co — ° T o 9 d o o Q 00 T-2 $2 d d d " CD OD CO O r - O d d O Q OD o in o co CM o Is-9 d " CM co 9 N -9 d Tf o 0 . CO T f co o JN " 9 S o o in o m o T t o d d z 1 + Tf X z co T-•<- O JM CM O CO X \< o i o o T t T f r f CM -<- o d d z 1 ' wi o z co o co J- Z; CM o o u CM r - • CO CM m o l>» o cq q d d i CM — ^ T J t CD • CD o o .5> = o o co B z i CM ^ M-: ^ T J t CD • CD o o O O co JS u z • * CO o z 250 .2 co • I s-T t CM 0.487 n nnn U.UUU 247 0.277 n nnn U.UUU 247 -0.563 n nnn U.UUU 178 0.305 n nnn U.UUU 196 -0.499 U.UUU 247 0.557 CO CM 0.104 0.11b 231 0.092 O.loo 231 -0.339 A AAA 0.000 178 0.280 A AAA 0.000 196 -0.083 A AAT7 0.207 231 0.699 Diss. Mn I s-T f CM 0.515 A nnn '• 0.000 247 0.123 0.054 247 -0.335 A AAA U.000 178 0.267 A AAA 0.000 196 -0.496 A AAA 0.000 247 0.339 Q T— CO CM -0.012 231 0.222 n nm U.UU 1 231 -0.131 n nm U.Uo I 178 0.029 196 0.226 A AA-1 U.UU1 231 0.566 oi '5 co CM 0.635 0.000 231 0.534 0.000 231 -0.419 0.000 178 0.675 0.000 196 -0.459 0.000 231 0.435 Diss. Fe I s -T f CM 0.536 0.000 247 0.224 0.000 247 -0.263 0.000 178 0.538 0.000 196 -0.502 0.000 247 0.149 .2 c5 Q CO CM 0.137 A AOTJ 0.037 231 -0.028 0.672 231 -0.195 A AAA 0.009 178 -0.067 A AC A 0.351 196 0.058 0.377 231 0.582 Temp CO T f CM 0.013 0.839 248 -0.304 0.000 248 -0.169 0.024 180 -0.168 0.018 197 0.301 0.000 248 0.378 Sp. Cond. CO T f CM 0.122 0.056 248 0.116 0.068 248 -0.305 0.000 180 0.081 0.256 197 0.044 0.494 248 -X Q. 00 T f CM -0.441 A nnn 0.000 248 -0.260 A AAA 0.000 248 0.523 A AAA 0.000 179 -0.592 A AAA 0.000 197 co T - • T f CM 0.044 DOC I s -cn 0.391 r\ nnn 0.000 197 0.521 A AAA 0.000 197 -0.352 A AAA 0.000 161 I s-T - • CD -0.592 A AAA 0.000 197 0.081 DO CD -0.330 0.000 179 -0.138 0.066 179 o T - • 00 -0.352 0.000 161 0.523 0.000 179 -0.305 >» O 0 . co T f CM 0.186 n nno U.UUo 248 CO T - • T f CM •0.138 U.UOO 179 0.521 U.UUU 197 •0.260 A AAA U.UUU 248 0.116 z 1 + X z oo T f CM co T - • ^ CM 0.186 0.003 248 -0.330 0.000 179 0.391 0.000 197 -0.441 0.000 248 0.122 z I ' CO o z 00 T f CM 0.144 0.024 248 0.455 A AAA U.UUU 248 -0.021 A "7Q *i O./ol 179 0.186 A AAA 0.009 197 -0.173 A AAC 0.006 248 0.323 o CM co CM 0.213 0.001 232 0.186 A A A A 0.004 232 -0.259 A AAA 0.000 179 0.108 0.131 197 0.110 0.094 232 0.768 z Corr. Coef. Sig. (2-tailed) N Corr. Coef. Sig. (2-tailed) N Corr. Coef. Sig. (2-tailed) N Corr. Coef. Sig. (2-tailed) N Corr. Coef. Sig. (2-tailed) N Corr. Coef. z • + Tf X z O 0 . DO DOC X a Sp. Cond. 251 T3 CJ) 3 C +3 C o o CO u. fl) X I CO H » ._ .<S CO Q 0.000 247 -0.007 n CM n u.y IU 247 0.240 U.UUU 231 0.497 U.UUU 247 0.659 n nnn U.UUU 231 0.385 n nnn U.UUU 231 0.000 231 0.485 n nnn U.UUU 231 0.649 n nnn U.UUU 231 0.323 n nnn U.UUU 231 0.358 n nnn 0.000 231 0.183 n nnc O.OOo 231 Diss. Mn 0.000 247 0.039 n CA 4 U.D4 l 247 0.266 n nnn U.UUU 231 0.737 n nnn U.UUU 247 0.461 n nnn 0.000 231 0.052 n A O A 231 Q 0.000 231 0.140 n noo U.Uoo 231 -0.112 U.Uoy 231 -0.097 n 4 yl o 231 0.217 n nn 4 0.001 231 T - • CO CM 00 Q 0.000 231 -0.079 0.231 231 0.251 0.000 231 0.576 0.000 231 T— T - C O CM 0.217 A AA4 0.001 231 Diss. Fe 0.019 247 -0.032 0.618 247 0.099 0.135 231 CM 0.576 0.000 231 -0.097 0.143 231 I" 0.000 231 0.507 0.000 231 T - • c o CM 0.099 0.135 231 0.251 0.000 231 -0.112 0.089 231 Temp 0.000 249 CD CN 0.507 0.000 231 -0.032 0.618 247 -0.079 0.231 231 0.140 0.033 231 Sp. Cond. CD • T T CM 0.378 0.000 249 0.582 0.000 231 0.149 0.019 247 0.435 0.000 231 0.566 0.000 231 X a 0.494 248 0.301 f\ AAA 0.000 248 0.058 0.377 231 -0.502 A AAA 0.000 247 -0.459 0.000 231 0.226 A AAai 0.001 231 DOC 0.256 197 -0.168 A A4 o 0.018 197 -0.067 A OC-1 196 0.538 A AAA U.UUU 196 0.675 A AAA 0.000 196 0.029 n £?on 0.689 196 DO 0.000 180 -0.169 0.024 180 -0.195 0.009 178 -0.263 0.000 178 -0.419 0.000 178 -0.131 0.081 178 •* O 0. 0.068 248 -0.304 A nnn U.UUU 248 -0.028 231 0.224 A AAA U.UUU 247 0.534 A AAA 0.000 231 0.222 A AA«f 0.001 231 z 1 + T T X z 0.056 248 0.013 0.839 248 0.137 0.037 231 0.536 0.000 247 0.635 0.000 231 -0.012 0.851 231 z 1 1 o o z 0.000 248 -0.246 A AAA 0.000 248 0.457 A AAA 0.000 231 0.218 A AA4 0.001 247 0.425 A AAA 0.000 231 -0.115 A AO<fl 0.081 231 u 0.000 232 0.452 A AAA 0.000 232 0.613 A AAA 0.000 231 0.112 A AOO 0.088 231 0.446 A AAA 0.000 231 0.390 A AAA 0.000 231 Sig. (2-tailed) N Corr. Coef. Sig. (2-tailed) N Corr. Coef. Sig. (2-tailed) N Corr. Coef. Sig. (2-tailed) N Corr. Coef. Sig. (2-tailed) N Corr. Coef. Sig. (2-tailed) N Temp 1* is. Q Diss. K a 252 .2 co Q 0.659 n nnn U.UUU 247 0.336 n ono U.UUU 231 Is-T - • T f CM s" Q CD O co o rr co o co J: Z: Oi O O T - • co CM co o co o rr CO o co • • CM © o Diss. Mn Is-T - • T f CM CD O CO O TT CO o co • - CM O O cn o ^ in o J> CO O T f • - CM o o 8 » Q CM T f LO co rr o T f co Z; 3 CM O O co in oo o rr T - o CO • • CM © O in o oo , o rr CO o CO • - CM © © (A (fl o T " O LO o rr, T t o co • - CM O O co o 1 0 o rr co o co ' • CN o o cn o in o rr co o co • • CM o © Diss. Fe I s- O ^ co o t o o CO o CN o rr co o co • - CM o o I s- O ^ cn o J> T t o T f • - CM © o i « .2 o Q <o o to o rr CM O CO • • CN O O cn o T f o rr co o co • - CM o o o o T f o rr CM O CO • - CM © © Temp CD T— co T f O LO T f ~^  ^ CM o o in o oo o rr T t O CO • • CM o o Is- o o it: Is-P CD T f 9 o N Sp. Cond. CD O co o ^ co o ^ f • - CM o o cn o o o rr co o co • - CM o o I s- o ^ m o t m o TT • • CM © © X CL co o T t § t o d -co r-00 O T ~ P CN CO 9 d CO o en o Is-T f o T f o d CM DOC to o co CM o CD d d T~ o O co o co CM o cn d d T~ o o co cq q co d d T~ O Q m o co o co co Jo Is-9 © ^ cn o co o co CO o Is-9 d ^ CO o co o co IO o Is-9 d T _ TF o 0. CO T f CM in T— O T T O O CM LO CD co rr o T - co ~^  • CN o o I s- o N O J -CM O T f r3 S CM o o z 1 + X z m o . r o J ; m o TT I< ^ CN o o T f CO T ~ T— CO • • CN o o oo o T t o T f • • CN o o z • * CO o z 00 o co co t T - O T f ^ S CM o o T t O o o rr co o co • • CN o o 00 o ^ m o t CM O T T • • CM o o u T f CM co  rr CM O CO • • CM © © IS- o en o rr © § a T - O T f o rr co o co • • CN O O i CM ^ t CD • CD o o .5* = O O co £ Z • CN t CD ' CD o o .9) = O O (fl s z i CM ^ t CD • CD O O .21-o o co 3 z (» c « • 1* w ._ .2 to Q 253 Precip (Total) 0.244 0.054 63 0.280 0.026 63 0.168 0.187 63 0.234 0.065 63 0.456 0.000 63 Precip (7 days) 0.210 0.099 63 0.210 0.098 63 0.155 0.225 63 0.288 0022 63 0.266 0.035 63 Precip (72hrs) 0.112 0.383 63 0.053 0.680 63 0.082 0.523 63 0.101 0.431 63 0.248 0.050 63 Precip (24hrs) 0.072 0.572 63 0.208 0.102 63 0.101 0.429 63 0.002 0.988 63 -0.076 0.554 63 Zn (DGT) 0:012 0.926 63 0.062 0.627 63 0.097 0.449 63 0.027 0.837 63 — . c o ^ CD Ni (DGT) 0.007 0.955 63 0.061 0.634 63 0.406 0.001 63 — . co ^ CO 0.027 0.837 63 Mn (DGT) -0.154 0.227 63 0.103 0.423 63 — . c o " co 0.406 0.001 63 0.097 0.449 63 Fe (DGT) 0.576 0.000 63 _ . CO " CD 0.103 0.423 63 0.061 0.634 63 0.062 0.627 63 Al (DGT) _ . CO " co 0.576 0.000 63 -0.154 0.227 63 0.007 0.955 63 0.012 0.926 63 Temp -0.211 0.115 57 -0.254 0.057 57 0.019 0.890 57 -0.215 0.109 57 -0.033 0.806 57 SpCond -0.311 0.019 57 -0.178 0.186 57 0.236 0.077 57 0.230 0.085 57 -0.114 0.398 57 X Q. 0.424 0.001 56 -0.085 0.535 56 -0.389 0.003 CC 56 -0.251 0.062 CC 56 -0.406 0.002 CC 56 DOC -0.392 0.005 49 -0.055 0.707 49 0.152 0.299 49 0.531 0.000 49 0.014 0.926 49 DO 0.211 0.141 50 -0.190 0.187 50 -0.373 0.008 50 -0.241 0.091 50 -0.131 0.363 50 Corr. Coef. Sig. (2-tailed) N Corr. Coef. Sig. (2-tailed) N Corr. Coef. Sig. (2-tailed) N Corr. Coef. Sig. (2-tailed) N Corr. Coef. Sig. (2-tailed) N Al (DGT) Fe (DGT) Mn (DGT) Ni (DGT) Zn (DGT) 254 o II c o I o o c CO o "c D ) 'co CO 0 •«—' CO o TJ c TJ o CO co -*—' c cu E 0 0 ^—' C 0 E TJ 0 CO CO c co o !t= 0 O o c q ro l_ o O c ro Oi c ro E i -co 0 Q. CO LO LL 0 JD ro Co (Sed) -0.363 0.032 35 -0.425 0.011 35 -0.645 0.000 35 0.383 0.023 35 0.801 0.000 35 -0.719 0.000 35 -0.645 0.000 35 -0.482 0.003 35 0.818 0.000 35 -0.341 0.045 Ca (Sed) 0.323 0.059 35 0.576 0.000 35 0.392 0.020 35 0.034 0.846 35 -0.438 0.009 35 0.455 0.006 35 0.414 0.013 35 0.566 0.000 35 -0.540 0.001 35 0.609 0.000 Mg (Sed) -0.323 0.058 35 -0.299 0.081 35 -0.535 0.001 35 0.223 0.198 35 0.935 0.000 35 -0.711 0.000 35 -0.679 0.000 35 -0.306 0.073 35 0.914 0.000 35 -0.219 0.207 Si (Sed) 0.323 0.059 35 0.287 0.094 35 0.486 0.003 35 -0.187 0.282 35 -0.733 0.000 35 0.671 0.000 35 0.550 0.001 35 0.420 0.012 35 -0.729 0.000 35 0.263 0.127 Na (Sed) 0.599 0.000 35 0.487 0.003 35 0.574 0.000 35 0.073 0.677 35 -0.240 0.164 35 0.487 0.003 35 0.286 0.096 35 0.704 0.000 35 -0.198 0.254 35 TJ— Ni (Sed) -0.135 0.438 35 -0.367 0.030 35 -0.387 0.022 35 0.319 0.062 35 0.929 0.000 35 -0.578 0.000 35 -0.668 0.000 35 -0.371 0.028 35 _ . LO " co -0.198 0.254 K (Sed) 0.425 0.011 35 0.548 0.001 35 0.566 0.000 35 -0.049 0.778 35 -0.435 0.009 35 0.526 0.001 35 0.355 0.036 35 . LO co -0.371 0.028 35 0.704 0.000 Cu (Sed) 0.390 0.020 35 0.582 0.000 35 0.689 0.000 35 -0.444 0.008 35 -0.652 0.000 35 0.589 0.000 35 _ . LO CO 0.355 0.036 35 -0.668 0.000 35 0.286 0.096 Zn (Sed) 0.634 0.000 35 0.506 0.002 35 0.756 0.000 35 0.067 0.702 35 -0.642 0.000 35 , - . LO ^ CO 0.589 0.000 35 0.526 0.001 35 -0.578 0.000 35 0.487 0.003 Cr(Sed) -0.282 0.101 35 -0.298 0.082 35 -0.506 0.002 35 0.292 0.089 35 — . LO CO -0.642 0.000 35 -0.652 0.000 35 -0.435 0.009 35 0.929 0.000 35 -0.240 0.164 Mn (Sed) 0.264 0.126 35 -0.226 0.193 35 -0.076 0.664 35 — . LO ^ CO 0.292 0.089 35 0.067 0.702 35 -0.444 0.008 35 -0.049 0.778 35 0.319 0.062 35 0.073 0.677 P (Sed) 0.837 0.000 35 0.538 0.001 35 ^_ . LO co -0.076 0.664 35 -0.506 0.002 35 0.756 0.000 35 0.689 0.000 35 0.566 0.000 35 -0.387 0.022 35 0.574 0.000 Al (Sed) 0.297 0.083 35 . LO ^ CO 0.538 0.001 35 -0.226 0.193 35 -0.298 0.082 35 0.506 0.002 35 0.582 0.000 35 0.548 0.001 35 -0.367 0.030 35 0.487 0.003 ^ CO 0.297 0.083 35 0.837 0.000 35 0.264 0.126 35 -0.282 0.101 35 0.634 0.000 35 0.390 0.020 35 0.425 0.011 35 -0.135 0.438 35 0.599 0.000 Corr. Coef. Sig. (2-tailed) N Corr. Coef. Sig. (2-tailed) N Corr. Coef. Sig. (2-tailed) N Corr. Coef. Sig. (2-tailed) N Corr. Coef. Sig. (2-tailed) N Corr. Coef. Sig. (2-tailed) N Corr. Coef. Sig. (2-tailed) N Corr. Coef. Sig. (2-tailed) N Corr. Coef. Sig. (2-tailed) N Corr. Coef. Sig. (2-tailed) Fe(Sed) Al (Sed) P(Sed) Mn (Sed) Cr(Sed) Zn(Sed) Cu (Sed) K (Sed) Ni (Sed) Na (Sed) 255 T J 0 c o O L O L L O J J D CO Co (Sed) co co -0.766 0.000 35 0.808 0.000 35 -0.368 0.030 35 " co Ca (Sed) L O C O 0.424 0.011 35 -0.412 0.014 35 — . L O C O -0.368 0.030 35 Mg (Sed) L O C O -0.744 0.000 35 — . L O " co -0.412 0.014 35 0.808 0.000 35 Si (Sed) L O C O _ . L O C O -0.744 0.000 35 0.424 0.011 35 -0.766 0.000 35 Na (Sed) L O co 0.263 0.127 35 -0.219 0.207 35 0.609 0.000 35 -0.341 0.045 35 Ni (Sed) L O co -0.729 0.000 35 0.914 0.000 35 -0.540 0.001 35 0.818 0.000 35 K (Sed) L O co 0.420 0.012 35 -0.306 0.073 35 0.566 0.000 35 -0.482 0.003 35 Cu (Sed) L O C O 0.550 0.001 35 -0.679 0.000 35 0.414 0.013 35 -0.645 0.000 35 Zn (Sed) L O C O 0.671 0.000 35 -0.711 0.000 35 0.455 0.006 35 -0.719 0.000 35 Cr(Sed) L O co -0.733 0.000 35 0.935 0.000 35 -0.438 0.009 35 0.801 0.000 35 c ~* 2 CO L O C O -0.187 0.282 35 0.223 0.198 35 0.034 0.846 35 0.383 0.023 35 P (Sed) L O C O 0.486 0.003 35 -0.535 0.001 35 0.392 0.020 35 -0.645 0.000 35 Al (Sed) L O C O 0.287 0.094 35 -0.299 0.081 35 0.576 0.000 35 -0.425 0.011 35 at L O C O 0.323 0.059 35 -0.323 0.058 35 0.323 0.059 35 -0.363 0.032 35 z Corr. Coef. Sig. (2-tailed) N Corr. Coef. Sig. (2-tailed) N Corr. Coef. Sig. (2-tailed) N Corr. Coef. Sig. (2-tailed) N Si (Sed) Mg (Sed) Ca (Sed) Co (Sed) o II a, c g '•4-» TO CL) k_ u . O o c CO C J <*= ' c g> ' w CO 0 , co ' o T J c T J O CO c 0 E T J 0 CO T J C co O Q i_T 0) 1 _co co 0 E c o E E 8 CO -*-» c 0) o e 0 O o c o 13 o O c co Cd c co E t_ co 0 CL CO C O L L 0 J O CO 256 Ni (Sed) -0.252 0.000 255 -0.195 0.002 255 -0.168 0.178 66 0.020 0.874 Fe(Sed) 0.567 0.000 255 0.520 0.000 255 -0.472 0.000 66 0.104 0.404 Al (Sed) 0.231 0.000 255 0.233 0.000 255 -0.138 0.268 66 0.045 0.722 Zn (Sed) 0.472 0.000 255 0.487 0.000 255 -0.466 0.000 66 0.074 0.556 Mn (Sed) -0.077 0.221 255 0.098 0.120 255 -0.221 0.074 66 0.139 0.265 Zn (DGT) -0.050 0.691 65 -0.112 0.376 65 0.069 0.584 66 0.103 0.409 Ni (DGT) 0.193 0.123 65 0.044 0.725 65 -0.031 0.803 66 0.030 0.814 Mn (DGT) 0.425 0.000 65 0.561 0.000 65 -0.129 0.301 66 0.114 0.363 Fe (DGT) -0.015 0.905 65 0.081 0.521 65 0.597 0.000 66 Al (DGT) -0.425 0.000 65 -0.339 0.006 65 _ . c o ^ CO 0.597 0.000 Mn (Water) 0.732 0.000 255 LO T- • LO CM -0.339 0.006 65 0.081 0.521 Fe (Water) LO T- • LO CM 0.732 0.000 255 -0.425 0.000 65 -0.015 0.905 Corr. Coef. Sig. (2-tailed) N Corr. Coef. Sig. (2-tailed) N Corr. Coef. Sig. (2-tailed) N Corr. Coef. Sig. (2-tailed) Fe (Water) Mn (Water) Al (DGT) Fe (DGT) 3 co Ni (Sed) CO CO 0.303 0.013 66 0.682 0.000 66 -0.174 0.163 66 0.233 0.000 256 -0.585 0.000 256 -0.430 0.000 256 -0.217 0.000 256 CD T - • LO CM Fe(Sed) CO CO 0.417 0.000 66 0.320 0.009 66 -0.143 0.252 66 0.319 0.000 256 0.694 0.000 256 0.343 0.000 256 CD T - • LO CM -0.217 0.000 256 Al (Sed) co CO -0.255 0.039 66 -0.285 0.020 66 0.252 0.041 66 -0.219 0.000 256 0.613 0.000 256 CO T - • LO CM 0.343 0.000 256 -0.430 0.000 256 Zn (Sed) CO CO 0.294 0.017 66 -0.149 0.231 66 0.316 0.010 66 0.165 0.008 256 CD T - • LO CM 0.613 0.000 256 0.694 0.000 256 -0.585 0.000 256 Mn (Sed) co co 0.639 0.000 66 0.272 0.027 66 0.067 0.593 66 CD T - • LO CM 0.165 0.008 256 -0.219 0.000 256 0.319 0.000 256 0.233 0.000 256 Zn (DGT) co CO 0.131 0.296 66 -0.038 0.761 66 _ . co ^ CD 0.067 0.593 66 0.316 0.010 66 0.252 0.041 66 -0.143 0.252 66 -0.174 0.163 66 Ni (DGT) CO CO 0.372 0.002 66 ^ CO -0.038 0.761 66 0.272 0.027 66 -0.149 0.231 66 -0.285 0.020 66 0.320 0.009 66 0.682 0.000 66 Mn (DGT) CO CO T - CD 0.372 0.002 66 0.131 0.296 66 0.639 0.000 66 0.294 0.017 66 -0.255 0.039 66 0.417 0.000 66 0.303 0.013 66 Fe (DGT) co co 0.114 0.363 66 0.030 0.814 66 0.103 0.409 66 0.139 0.265 66 0.074 0.556 66 0.045 0.722 66 0.104 0.404 66 0.020 0.874 66 Al (DGT) CD CD -0.129 0.301 66 -0.031 0.803 66 0.069 0.584 66 -0.221 0.074 66 -0.466 0.000 66 -0.138 0.268 66 -0.472 0.000 66 -0.168 0.178 66 Mn (Water) LO CD 0.561 0.000 65 0.044 0.725 65 -0.112 0.376 65 0.098 0.120 255 0.487 0.000 255 0.233 0.000 255 0.520 0.000 255 -0.195 0.002 255 Fe (Water) LO CD 0.425 0.000 65 0.193 0.123 65 -0.050 0.691 65 -0.077 0.221 255 0.472 0.000 255 0.231 0.000 255 0.567 0.000 255 -0.252 0.000 255 z Corr. Coef. Sig. (2-tailed) N Corr. Coef. Sig. (2-tailed) N Corr. Coef. Sig. (2-tailed) N Corr. Coef. Sig. (2-tailed) N Corr. Coef. Sig. (2-tailed) N Corr. Coef. Sig. (2-tailed) N Corr. Coef. Sig. (2-tailed) N Corr. Coef. Sig. (2-tailed) N Mn (DGT) Ni (DGT) Zn (DGT) Mn (Sed) Zn (Sed) Al (Sed) Fe(Sed) Ni (Sed) 257 O 2 ct 3. c c ro o i.I co cu Q. o CO O Co (Sed) -0.392 0.000 239 -0.332 0.000 255 -0.156 0.016 0.755 0.000 239 -0.292 0.000 ORR -0.087 0.181 -0.021 0.733 255 Ca (Sed) 0.201 0.002 239 0.128 0.042 255 -0.062 0.341 239 -0.683 0.000 239 0.013 0.840 255 0.027 0.680 239 -0.133 0.034 255 Mg (Sed) -0.361 0.000 239 -0.360 0.000 occ 255 -0.190 0.003 AAA 239 0.699 0.000 ion 239 -0.324 0.000 255 -0.222 0.001 239 -0.101 0.109 255 Si (Sed) 0.260 0.000 239 0.493 0.000 255 0.184 0.004 239 -0.645 0.000 239 0.413 0.000 255 0.201 0.002 239 0.097 0.121 255 Na (Sed) 0.219 0.001 0.533 0.000 ORR 4.00 0.443 0.000 -0.259 0.000 0.409 0.000 Zoo 0.282 0.000 0.363 0.000 255 Ni (Sed) -0.369 0.000 239 -0.252 0.000 255 -0.034 0.600 239 0.812 0.000 239 -0.195 0.002 255 -0.099 0.127 239 0.090 0.152 255 K (Sed) 0.420 0.000 239 0.558 0.000 255 0.576 0.000 239 -0.281 0.000 239 0.421 0.000 255 0.390 0.000 239 0.316 0.000 255 Cu (Sed) 0.224 0.000 239 0.315 0.000 255 0.309 0.000 239 -0.517 0.000 239 0.255 0.000 255 0.047 0.474 239 0.263 0.000 255 Zn (Sed) 0.357 0.000 239 0.472 0.000 255 0.457 0.000 239 -0.354 0.000 239 0.487 0.000 255 0.364 0.000 239 0.404 0.000 255 Cr (Sed) -0.406 0.000 239 -0.404 0.000 255 -0.256 0.000 239 0.660 0.000 239 -0.357 0,000 255 -0.191 0.003 239 -0.128 0.040 255 c ~* s CO -0.040 0.538 239 -0.077 0.221 255 -0.035 0.593 239 0.294 0.000 239 0.098 0.120 255 0.073 0.259 239 0.162 0.010 255 P(Sed) 0.278 0.000 239 0.530 0.000 255 0.609 0.000 239 -0.229 0.000 239 0.488 0.000 255 0.204 0.002 239 0.538 0.000 255 Al (Sed) 0.220 0.001 239 0.231 0.000 255 0.267 0.000 239 -0.415 0.000 239 0.233 0.000 255 0.164 0.011 239 0.270 0.000 255 Fe(Sed) -0.004 0.953 239 0.567 0.000 255 0.506 0.000 239 0.004 0.947 239 0.520 0.000 255 0.161 0.013 239 0.538 0.000 255 Corr. Coef. Sig. (2-tailed) N Corr. Coef. Sig. (2-tailed) N Corr. Coef. Sig. (2-tailed) N Corr. Coef. Sig. (2-tailed) N Corr. Coef. Sig. (2-tailed) N Corr. Coef. Sig. (2-tailed) N Corr. Coef. Sig. (2-tailed) N Diss. Ca Diss. Fe Diss. K Diss. Mg Diss. Mn Diss. Na Diss. Si 258 % Clay Content 0.152 0.027 212 0.188 0.004 227 -0.176 0.008 227 0.295 0.000 227 N Surplus 0.097 0.245 146 0.240 0.003 157 -0.097 0.227 157 0.047 0.559 157 AUE/HA 0.202 0.004 199 0.349 0.000 213 0.370 0.000 213 0.138 0.044 213 % Berries/ Nursery Cover 0.045 0.531 199 0.327 0.000 213 0.008 0.908 213 -0.016 0.818 213 % Forest Cover -0.525 0.000 199 -0.533 0.000 213 -0.446 0.000 213 -0.427 0.000 213 % Veg Cover -0.015 0.839 199 -0.141 0.040 213 0.245 0.000 213 -0.138 0.045 213 % Pasture Cover 0.417 0.000 199 0.271 0.000 213 0.236 0.001 213 0.464 0.000 213 % Cover Crop Cover 0.015 0.835 199 -0.007 0.922 213 0.129 0,059 213 0.161 0.019 213 % Corn Cover 0.332 0.000 199 0.187 0.006 213 0.271 0.000 213 0.386 0.000 213 Corr.Coef. Sig. (2-tailed) N Corr.Coef. Sig. (2-tailed) N Corr.Coef. Sig. (2-tailed) N Corr.Coef. Sig. (2-tailed) N o z • o z z • • * z z O 0. C O 0 co o TJ c 32 o CQ o co o T3 CD CO T3 c co _ i TJ C co C O k_ a> aJ E co i co D _ ro a i _ CD •4-* CD ro o 'w >» a C O . c 92 o i t a> o • O o c T g o ~ II ro a o o ^ I ro ^ a 8 S s 8 ro ^ CD c CL CO co '55 co _CD ro >i c co o> O jj (0 3 CO < X L U < CO "35 6 {cS ca co O ) Js ai 0) 55 O o> L . 5 (U (0 > (0 o a. o > Q. CD o o > i $ o 6 C D C O C O LO o O co CD 9 d " I S - T - _ T - o o co o T — o o T — S3 co _ co Q o C M o 9 d L O C O L O o O C M L O d d T~ CM O _ o o o TJ- O L O d d T " 22 C M T t o co CM o L O 9 d * " 9 o co co o L O 9 d ^ oo o _ C D T - O o T t LO d d T ~ co o 9 d T 3 CD ro (1) o O CM o 9? U CO o o T t O C O L O L O O C D I S -d d T " ° T t C O o o C M o CM 9 d CO 00 L O r— T t O Tt C D d d T~ co co C M 8 S 9 d "~ J O o cq o 9 d T t 00 oo oo ! J O C M C D d d 8 ^ O CD o o CM T t O CO T J T - T - C D 0 0 ^ " I O O _ IS- O T t C O O C D © ci T3 CD ro CD o O C M i_ • O 9? O CO o o o L O co o d T t CO eo C M d o T t C M CD o o d C O T t C D O q t_ o O 259 T3 CD C c o O oi LL 0 . Q CO % Clay Content 0.762 222 0.098 0.144 223 -0.075 0.262 223 N Surplus 0.000 153 0.144 0.075 154 0.046 0.568 154 AUE/HA 0.000 207 0.291 0.000 208 0.080 0.249 208 % Berries/ Nursery Cover 0.621 207 0.146 0.035 208 0.023 0.741 208 % Forest Cover 0.000 207 -0.531 0.000 208 -0.160 0.021 208 % Veg Cover 0.002 207 0.044 0.524 208 0.079 0.259 208 % Pasture Cover 0.000 207 0.325 0.000 208 0.035 0.621 208 % Cover Crop Cover 0.897 207 0.002 0.978 208 0.029 0.673 208 % Corn Cover 0.036 207 0.493 0.000 208 0.080 0.248 208 Sig. (2-tailed) N Corr.Coef. Sig. (2-tailed) N Corr.Coef. Sig. (2-tailed) N Sp. Cond. Temp c o ro 0 o o "c 3 'c g> 'co CO 0 ro o T 3 _c 32 o CO c2 o ro o _ C 0 w c CO _l T3 c CO w ro 0 0 o ro T 3 0 > o <n tn c 0 o e 0 O o c g ro o O _^  c ro £ c ro - A E ° co d co a. 0 ro % Clay Content 0.047 0.495 212 -0.251 0.000 227 -0.062 0.369 212 0.065 0.347 N Surplus 0.484 0.000 146 -0.323 0.000 157 -0.139 0.094 146 0.099 0.236 AUE/HA 0.385 0.000 199 0.202 0.003 213 0.363 0.000 199 0.131 0.065 % Berries/ Nursery Cover 0.359 0.000 199 -0.123 0.074 213 -0.055 0.440 199 -0.029 0.682 % Forest Cover -0.424 0.000 199 -0.436 0.000 213 -0.668 0.000 199 -0.292 0.000 % Veg Cover 0.061 0.390 199 0.193 0.005 213 0.322 0.000 199 0.056 0.429 % Pasture Cover -0.026 0.714 199 0.362 0.000 213 0.424 0.000 199 0.261 0.000 % Cover Crop Cover -0.045 0.526 199 0.137 0.047 213 0.070 0.325 199 0.070 0.323 % Corn Cover 0.117 0.100 199 0.293 0.000 213 0.624 0.000 199 0.611 0.000 Corr.Coef. Sig. (2-tailed) N Corr.Coef. Sig. (2-tailed) N Corr.Coef. Sig. (2-tailed) N Corr.Coef. Sig. (2-tailed) Diss. Ca Diss. Fe Diss. K Diss. Mg 260 T J CD — c o O 0 co t— % Clay Content CM CM -0.226 0.001 227 0.170 0.013 212 -0.096 0.150 227 N Surplus CO T t -0.146 0.068 157 0.005 0.956 146 -0.238 0.003 157 < X LU 3 < CO CO 0.380 0.000 213 0.081 0.258 199 0.462 0.000 213 % Berries/ Nursery Cover co CO 0.052 0.451 213 -0.056 0.433 199 0.064 0.356 213 % Forest Cover CO CO -0.464 0.000 213 -0.416 0.000 199 -0.644 0.000 213 % Veg Cover CO CO 0.250 0.000 213 -0.052 0.466 199 0.271 0.000 213 % Pasture Cover CO CO 0.206 0.002 213 0.393 0.000 199 0.374 0.000 213 % Cover Crop Cover CO CO 0.069 0.318 213 -0.048 0.498 199 0.036 0.600 213 % Corn Cover CO CO 0.255 0.000 213 0.266 0.000 199 0.559 0.000 213 z Corr.Coef. Sig. (2-tailed) N Corr.Coef. Sig. (2-tailed) N Corr.Coef. Sig. (2-tailed) N Diss. Mn Diss. Na Diss. Si c co o t £ 'c g> 'co CO cu - 4 — » co o T J c T J O CO co O co o T J c cu CO T J C co _i T J C co _co ro 0 CD o co OJ JD ro ro > ro o co i— a CO m-» c CD O !t= CD O O c o ro i_ o O —\ c ro LX ^ c o ro T E ° E n ro a a> mZ, a. c co o •4—• ro CD k_ k-LL 0 JD >t C co o> O CO 3 a 3 CO < X LU 3 < "35 S | <S OQ OJ co ,_ OJ | CO JJ; as 0> > O B a> co > CO o a. o 0i „ > 9-o p o o " - * T - CO U) O) Th T - ; CO CO O O eg co ^ - CO T CO LO 9 d CO CO CO T f CD T - T - ; m o o T- O IO O CD * o m o o 5 1^  S S (D CM O LO 9 o P LO fc 0 9 d 25 co co h-9 r~~ 9 d fc o 9 d T J Oi ro 0 o q CM kJ o 2* O CO Q T ~ T f T ^ T f | o o Oi LO ig S T f i ^ 9 co !fi <o | g 2 co P T f IO T - CO LO o o h-co oo co o T - co co ^ f . Ol LO CD ^ co m 9 o CM t — CO I CJ LO LO | o o 2 LO 3 o LO mmm oo co P LO 9 d 0 CO o -v q CM kJ o o CO o Q LL 261 T J 0 3 C c o O % Clay Content 0.000 44 -0.167 0.279 44 0.158 0.307 44 N Surplus 0.380 34 0.119 0.501 34 -0.307 0.077 34 AUE/HA 0.000 56 0.031 0.818 56 0.477 0.000 56 % Berries/ Nursery Cover 0.102 56 -0.287 0.032 56 0.682 0.000 56 % Forest Cover 0.000 56 -0.313 0.019 56 -0.196 0.148 56 % Veg Cover 0.001 56 -0.192 0.156 56 -0.125 0.357 56 % Pasture Cover 0.803 56 0.554 0.000 56 -0.234 0.083 56 % Cover Crop Cover 0.908 56 0.219 0.105 56 -0.244 0.070 56 % Corn Cover 0.151 56 0.541 0.000 56 -0.360 0.006 56 Sig. (2-tailed) N Corr.Coef. Sig. (2-tailed) N Corr.Coef. Sig. (2-tailed) N Ni (DGT) Zn (DGT) c CD CJ 1= c D) 'to co 0 to o TJ c T J O CQ o -4—» CD O T J c 0 CO T J C co _ i T J C co JOT co -4—» 0 0 o co T J c 3 o CQ • c 0 E T J 0 CO w "c 0 o i t 0 o O c o 0 i— o O c ro tt ^ c o ro T E ° E II ro a, 0 <H CO o CNJ 1— LL 0 JD. ro > i c ro o c o o o (0 z e-3 CO L U < 0 CO 0 > o o £< tfl . £ 0 £ o CO «r fl) 0 > o 55 O £ _ 3 0 w > ro o 0. cj 0) l_ > 9- Q) o p > o u o LO T -co co o co CO r -P CNJ o o 3; co p CN o oo CM co CO CNJ o o co p CN o o T T CO P CNJ o oo LO CO P CNJ o T t CM CO oq CN o i--2 co P CN o T J 0 ro +-> i CN CO CO TJ 0 CO 0 LL CO CO CO CM T -q N n o o CO o co i=: 9 d CNJ CO T t o oo co CNJ CNJ CNJ d d ° - o> P p gj P o co r-- co «•? P O J 9 o T - LO LO CD CD P ^ CNJ O O CO LO CD TT CD T CO CM O O r- co CM CO CD CM CM CM d d oo oo o d LO CO T J 0 ro 0 o . q CM O CJ) O CO T3 0 CO rr co 2. T - l 9 Is- co 9 o co S oo . M- T CNJ| 9 o 00 CM «°. P CM| o o S CM . § JO CO • CM fe co 8 8g2 co co "2 r; co T t o CM| o o CO h-£2 S3 co CO O CM I d d T t LO oo co co P co CM| o o T t co I" CNI CD * P CM| o o 0 co o -v q CM o 9? O CO TJ 0 CO 262 3 c c % Clay Content 0.437 31 0.279 0.129 31 0.038 0.840 31 -0.092 0.624 31 -0.280 0.128 31 0.249 0.178 31 -0.110 0.557 31 -0.252 0.172 31 0.113 0.546 31 -0.200 N Surplus 0.438 21 -0.032 0.890 21 -0.368 0.101 21 -0.636 0.002 21 0.115 0.621 21 -0.034 0.885 21 -0.224 0.330 21 -0.232 0.312 21 0.127 0.583 21 0.036 AUE/HA 0.806 29 -0.134 0.489 29 0.428 0.020 29 0.331 0.080 29 0.217 0.259 29 -0.029 0.879 29 0.184 0.338 29 0.320 0.090 29 -0.152 0.430 29 -0.037 % Berries/ Nursery Cover 0.899 29 0.080 0.678 29 -0.027 0.887 29 -0.125 0.517 29 -0.042 0.828 29 0.049 0.800 29 0.031 0.872 29 0.034 0.861 29 0.030 0.876 29 -0.135 % Forest Cover 0.507 29 -0.006 0.976 29 -0.390 0.036 29 -0.224 0.243 29 -0.554 0.002 29 -0.183 0.341 29 -0.361 0.054 29 -0.219 0.254 29 -0.019 0.921 29 -0.014 % Veg Cover 0.116 29 -0.426 0.021 29 0.455 0.013 29 0.286 0.133 29 0.142 0.463 29 -0.321 0.089 29 0.087 0.653 29 0.202 0.294 29 -0.315 0.096 29 0.035 % Pasture Cover 0.931 29 0.281 0.139 29 0.135 0.486 29 0.244 0.201 29 0.188 0.328 29 0.355 0.058 29 0.232 0.226 29 0.021 0.914 29 0.176 0.360 29 -0.109 % Cover Crop Cover 0.411 29 0.102 0.599 29 -0.280 0.141 29 -0.050 0.796 29 0.289 0.128 29 0.145 0.453 29 0.117 0.546 29 0.055 0.775 29 0.201 0.296 29 -0.043 % Corn Cover 0.062 29 0.114 0.557 29 0.045 0.816 29 0.050 0.795 29 0.198 0.303 29 0.304 0.109 29 0.118 0.542 29 -0.173 0.370 29 0.153 0.428 29 -0.234 Sig. (2-tailed) N Corr.Coef. Sig. (2-tailed) N Corr.Coef. Sig. (2-tailed) N Corr.Coef. Sig. (2-tailed) N Corr.Coef. Sig. (2-tailed) N Corr.Coef. Sig. (2-tailed) N Corr.Coef. Sig. (2-tailed) Corr.Coef. Sig. (2-tailed) N Corr.Coef. Sig. (2-tailed) N Corr.Coef. Cr(Sed) Zn(Sed) Cu (Sed) K (Sed) Ni (Sed) Na (Sed) Si (Sed) Mg (Sed) Ca (Sed) 263 % Clay Content 0.280 31 0.251 0.173 31 N Surplus 0.878 21 0.031 0.895 21 AUE/HA 0.847 29 -0.431 0.020 29 % Berries/ Nursery Cover 0.484 29 -0.090 0.641 29 % Forest Cover 0.941 29 0.315 0.096 29 % Veg Cover 0.856 29 -0.472 0.010 29 % Pasture Cover 0.573 29 0.084 0.666 29 % Cover Crop Cover 0.824 29 0.014 0.941 29 % Corn Cover 0.222 29 0.081 0.675 29 Sig. (2-tailed) N Corr.Coef. Sig. (2-tailed) N Co (Sed) 264 Appendix G: Photographs of field stations Figure G1. DGT unit deployed at the Vedder Mountain reference site #19. Figure G2. Duplicate DGT units deployed in Marshall Creek site #13. Figure G3. Arnold Slough site #10 showing signs of eutrophication during the summer of 2003. Figure G4. Arnold Slough site #11 showing signs of eutrophication during the summer of 2003. Figure G5. Sumas River border station (site #3) showing sediment residues on the river bank due to a large storm event in October 2003. Figure G6. Sumas River site #4 showing high water mark from a large storm event in October 2003. Figure G7. Sumas River (site #12) showing signs of eutrophication in 2003. Fish mortality was noted at this site on this sampling date (October 14, 2003). Figure G8. Sumas Canal (site #8) showing signs of eutrophication, summer 2003. Figure G9. Covered manure storage located directly adjacent to a waterway (Sumas Canal) at site #9. Figure G10. Sumas Canal (site #9) during high water conditions. Fields are at risk of being flooded. Figure G11. Sumas Prairie farm showing poor drainage (ponding) in fields. Figure G12. Liquid manure being spread onto a field in the Sumas Prairie. Figure G13. Naturally occurring asbestos landslide located in the headwater of Swift Creek. Figure G14. Landslide asbestos material notable in Swift Creek (site #1). Figure G15. Vedder Mountain reference site #19 during low-flow conditions. Figure G16. Vedder Mountain reference site #19 during moderate flow conditions. Figure G17. Recent suburban development on Sumas Mountain. Figure G18. View of Sumas Prairie and Mount Baker from Sumas Mountain. Figure G19. View of Mount Baker from a corn field in the Sumas Prairie. Figure G20. View of Sumas Mountain from the Canada/U.S. border. 265 266 Figure G3. Arnold Slough site #10 showing signs of eutrophication during the summer of 2003. Figure GA. Arnold Slough site #11 showing signs of eutrophication during the summer of 2003. 267 Figure G5. Sumas River border station (site #3) showing sediment residues on the river bank due to a large storm event in October 2003. Figure G6. Sumas River site #4 showing high water mark from a large storm event in October 2003. 268 Figure G7. Sumas River (site #12) showing signs of eutrophication in 2003. Fish mortality was noted at this site on this sampling date (October 14, 2003). 269 Figure G 9 . Covered manure storage located directly adjacent to a waterway (Sumas Canal site #9). 270 272 Figure G17. Recent suburban development on Sumas Mountain. 274 Figure G19. View of Mount Baker from a com field in the Sumas Prairie. Figure G20. View of Sumas Mountain from the Canada/U.S. border. 275 r^j THE UNIVERSITY OF BRITISH COLUMBIA FACULTY OF GRADUATE STUDIES BIBLIOGRAPHY OF THESES RELATED TO BRITISH COLUMBIA The University of British Columbia Library maintains The Bibliography of Theses on British Columbia History and Related Subjects. This important online reference source is available on the Internet through the UBC Library online catalogue. The Bibliography is used by students and researchers at UBC and other libraries and research institutions in British Columbia, Canada, and other countries. If your thesis topic is related to British Columbia (e.g., history, geography, literature, science, special topics, etc.), please complete in the following: Name: Smi+U Tone. K (Last) (First) Degree: Mc\sVe.r- p£ SC^K&ACJL Graduating Year: cQoO1-^ Department ^ £ £ o U ^ O c t ~ \Aojtnt%^w&X\\ cLn d FtlVl^Dh i n g r i S-l-a-rlixtS J Title of thesis: (Vn A uA A \n \J-? . ^ f f i p C ^ S O £ fl flfi CAJJ 4U raJ Accompanying Materials: • Yes No If yes, indicate type: List keywords that describe your thesis topic (be specific and use as many as possible: Thank you for your assistance. grad.ubc.ca/forms/?formlD= page 1 of 1 last updated: 20-Jul-04 

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