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Land use and water quality dynamics on the urban-rural fringe : a GIS evaluation of the Salmon River… Wernick, Barbara Gail 1996

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L A N D U S E A N D W A T E R Q U A L I T Y D Y N A M I C S O N T H E U R B A N - R U R A L F R I N G E : A G I S E V A L U A T I O N O F T H E S A L M O N R I V E R W A T E R S H E D , L A N G L E Y , B . C . B Y B A R B A R A G A I L W E R N I C K B . S c , T R I N I T Y W E S T E R N U N I V E R S I T Y , L A N G L E Y , B . C . 1991 A THESIS S U B M I T T E D I N P A R T I A L F U L F I L M E N T O F T H E R E Q U I R E M E N T S F O R T H E D E G R E E O F M A S T E R O F S C I E N C E I N T H E F A C U L T Y O F G R A D U A T E S T U D I E S ( R E S O U R C E M A N A G E M E N T A N D E N V I R O N M E N T A L S T U D I E S ) We accept this thesis as conforming to the required standard The University of British Columbia April 1996 © Barbara G . Wernick 1996 In presenting this thesis in partial fulfilment 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. Department of feugCg /nMQCjfflGhlT /W£ Ghl\J(&0A//HBfdTAL- STUbieS The University of British Columbia Vancouver, Canada DE-6 (2/88) 11 A B S T R A C T The Salmon River Watershed, Langley, B.C., is on the urban-rural fringe of the Greater Vancouver Regional District. A major aquifer within the Salmon River Watershed provides rural residents with drinking water and maintains stream flow during the summer. The highly mixed land use activities in the watershed, consisting of residential development, commercial agriculture and hobby farming, are resulting in non-point source nitrogen pollution of stream and ground-water. The purpose of this study was to determine how the type, intensity and changes in land use activities have affected water quality. Indicators such as nitrate-N, ammonia-N, ortho-phosphate, and faecal coliforms and streptococci were used to characterize water quality. Animal unit and septic system densities and nitrogen loading were used as land use indicators. Land use/water quality relationships were analyzed with a Geographic Information System (GIS). The Salmon River and its tributaries are relatively healthy. Most of the water quality indicators met the appropriate criteria for drinking water and aquatic life. Nitrate-N concen-trations and microbial counts, however, have been and continue to be a concern. While nitrate-N was below the maximum drinking water quality criterion of 10 mg-N L' 1 at all stations there are localized areas where nitrate-N concentrations are above background and reaching levels of concern (5 mg-N L"1). The highest nitrate-N concentrations were measured during low-flow conditions. This suggests that the nitrogen-polluted groundwater is affecting the stream during the summer. In contrast, faecal coliforms and streptocci counts were higher during high-flow conditions suggesting runoff from agricultural fields on which manure is spread in the late fall. More than 3,200 septic systems have been installed in the Salmon River Watershed between 1930 and 1994, a large number of which are located on the Hopington Aquifer. The pattern of increasing septic system densities closely matched the increase in streamwater nitrate-N Ill from up to downstream in both the Salmon River mainstem and Coghlan Creek upstream of their confluence. Agricultural activities are concentrated on large commercial operations. However, hobby farms are becoming a more important component of the agricultural sector in the urban-rural fringe environment. There has been an overall decrease in animal numbers, mostly due to fewer cattle, poultry and pigs between 1986 and 1991. In contrast, horses and sheep, often associated with small farms, increased in number over the same time period. Animal unit densities increased from up to downstream in the Salmon River mainstem to its confluence with Coghlan Creek as does the streamwater nitrate-N concentration. In the Coghlan, however, animal unit densities did not vary, yet the nitrate-N values in this section of the stream increased the most. These results suggest that residential and agricultural uses are both sources of nitrogen in the Salmon mainstem, while septic systems are the primary source in Coghlan Creek. A nitrogen mass balance was used to quantify the sources (manure, fertilizers, the atmosphere and septic systems) and sinks (crop uptake, management losses, dentrification) of nitrogen in the watershed in order to determine the amount of surplus nitrogen being applied. The contribution of septic systems accounted for about 20 % of the surplus loading in the watershed, while large farms contributed about 68 % and small farms 12 % of the surplus loading. There is a poor linear relationship between high nitrate-N values in the stream and corresponding spatial inputs of nitrogen from manure, fertilizers and septic systems. This is due to the highly variable surficial geology, the complexity of groundwater hydrology and the spatial lag between areas of high nitrogen surplus applications and water quality sampling stations. The area near the Salmon River-Coghlan Creek confluence is the most affected section of streams in the watershed and should be used as the key site to monitor environmental quality in the watershed. iv T A B L E O F C O N T E N T S Abstract 1 1 Table of Contents i v List of Tables i x List of Figures x l Acknowledgements xv* 1. Introduction I 1.1 Study goal 6 1.2 Study objectives 6 2. Salmon River Watershed: Description of Study Area 7 2.1 Setting 7 2.1.1 Climate 7 2.1.2 Surficial geology. . . 10 2.2 Surface water resources 10 2.2.1 Drainage network 10 2.2.2 Stream discharge 12 2.2.3 Surface water quality 14 2.3 Groundwater resources 16 2.3.1 Major aquifers . 16 2.3.2 Groundwater quality 20 2.4 Fish 21 2.5 Human activity 22 2.5.1 Population 22 2.5.2 Land use and zoning 24 2.5.3 Water and sewerage 26 2.5.4 Environmental management in the watershed 28 3. Streamwater quality 30 3.1 Indicators of water quality 30 3.1.1 Nitrate and Ammonia 32 3.1.2 Orthophosphate • 33 3.1.3 Dissolved organic carbon 34 3.1.4 Chloride 35 3.1.5 Dissolved oxygen 35 3.1.6 Specific conductance 36 3.1.7 pH 37 3.1.8 Temperature 37 3.1.9 Micro-organisms 38 3.2 Methodology 39 V 3.2.1 Water sample collection 39 3.2.2 Laboratory analysis 41 3.3 Results and discussion 43 3.3.1 Spatial and temporal variation in nitrate-nitrogen 44 3.3.2 Spatial and temporal variation in ammonia-nitrogen . 48 3.3.3 Spatial and temporal variation in orthophosphate 50 3.3.4 Spatial and temporal variation in dissolved organic carbon 50 3.3.5 Spatial and temporal variation in chloride 53 3.3.6 Spatial and temporal variation in dissolved oxygen 55 3.3.7 Spatial and temporal variation in specific conductance 58 3.3.8 Spatial and temporal variation in pH 58 3.3.9 Spatial and temporal variation in temperature 61 3.3.10 Spatial and temporal variation in 63 3.4 Relationship between water quality indicators 65 3.5 Storm monitoring 66 4. Land use 72 4.1 Land use maps 72 4.1.1 Methods 72 4.1.2 Land use dynamics 74 4.2 Septic system database 80 4.2.1 Database construction 80 4.2.2 Distribution of septic systems 81 4.3 Agricultural Census 85 4.3.1 Data collection and analysis 85 4.3.2 Agricultural intensity and dynamics 86 4.3.3 North Langley study area 89 4.4 Agricultural Waste Management Survey 94 4.4.1 Methods 95 4.4.2 Survey analysis 95 4.4.3 Watershed stocking density 98 4.5 Windshield survey of horse locations 99 5. Linking water quality to land use 103 5.1 Methods 103 5.2 Land use and surface water quality 105 5.2.1 Septic systems on all surficial materials 106 5.2.2 Septic systems on outwash material 109 5.2.3 Overall animal units and agricultural land I l l 5.2.4 Agricultural subtypes and streamwater nitrate-N 113 5.2.5 Comparison of land use components 119 5.3 Land use and groundwater nitrate-N 120 5.3.1 Septic systems 120 5.3.2 Animals 122 5.4 Statistical evaluation of land use-water quality interaction 122 vi 6. Nitrogen mass balance 126 6.1 The nitrogen mass balance calculation 126 6.1.1 The model 126 6.1.2 Data Sources 133 6.2 Nitrogen budget with census information 134 6.2.1 1986 Census data 134 6.2.2 1991 Census data . 136 6.2.3 Comparison Between Census Years . . . 136 6.3 Nitrogen budget with waste management survey data 140 6.3.1 Individual farm nitrogen balances 140 6.3.2 Nitrogen balance for contributing areas 145 6.3.3 The relationship between nitrogen loading and water quality 152 6.4 Partitioning nitrogen sources 159 6.5 Comparison between data sets 161 6.6 Evaluation of the nitrogen mass balance calculation 163 7. Summary and recommendations 166 7.1 Summary of research findings 166 7.1.1 Spatial and temporal variability in water quality 166 7.1.2 Land use dynamics 167 7.1.3 Spatial relationships between land activities and water quality 168 7.1.4 Nitrogen mass balance 169 7.2 Recommendations 171 7.2.1 Further research 171 7.2.2 Management recommendations 173 8. Literature cited 175 Personal communication 181 Appendices 182 Appendix 1 Determination of water quality for detailed sampling in the Coghlan Creek near where it joins the Salmon River mainstem 183 Appendix 2 Determination of nitrate-N in streamwater in the Salmon River Watershed, March 1994 - February 1995 184 Appendix 3 Determination of ammonia-N in streamwater in the Salmon River Watershed, March 1994 - February 1995 185 Appendix 4 Determination of orthophosphate in streamwater in the Salmon River Watershed, March 1994 - February 1995 186 Appendix 5 Determination of dissolved organic carbon in streamwater in the Salmon River Watershed, March 1994 - February 1995 187 Vll Appendix 6 Determination of chloride in streamwater in the Salmon River Watershed, March 1994 - February 1995 188 Appendix 7 Determination of dissolved oxygen in streamwater in the Salmon River Watershed, March 1994 - February 1995 189 Appendix 8 Determination of specific conductance in streamwater in the Salmon River Watershed, March 1994 - February 1995 190 Appendix 9 Determination of pH (in laboratory) in streamwater in the Salmon River Watershed, March 1994 - February 1995 191 Appendix 10 Determination of pH (in situ) in streamwater in the Salmon River Watershed, March 1994 - February 1995 192 Appendix 11 Determination of temperature in streamwater in the Salmon River Watershed, March 1994 - February 1995 .193 Appendix 12 Determination of faecal coliforms in streamwater in the Salmon River Watershed, March 1994 - February 1995 194 Appendix 13 Determination of faecal streptococci in streamwater in the Salmon River Watershed, March 1994 - February 1995 195 Appendix 15 Determination of water quality in streamwater at Station 6 in the Salmon River Watershed for three storm events, October 1994 - November 1995 196 Appendix 16 Enumeration area equivalents for 1986 and 1991 Census 197 Appendix 17 Summary of number of farms contacted via letter for the Salmon River Agricultural Waste Management Survey 198 Appendix 18 Survey form used for the Salmon River Agricultural Waste Management Survey 199 Appendix 19 Survey form used for horse operations included in the Salmon River Agricultural Waste Management Survey 203 Appendix 20 Database structure for the Salmon River Agricultural Waste Management Survey 205 Appendix 21 Animal and crop data collected from individual farms for the Salmon River Agricultural Waste Management Survey 208 Appendix 22 Summary of nitrogen mass balance calculation for the 1986 census data . . . .212 Vlll Appendix 23 Summary of nitrogen mass balance calculation for the 1991 census data . . . .213 Appendix 24 Summary of nitrogen mass balance calculation for individual farms included in the Salmon River Agricultural Waste Management Survey 214 Appendix 25 Summary of nitrogen mass balance calculation for contributing areas of the Salmon River Watershed 217 ix LIST OF TABLES Table 2.1 Summary information for the Aldergrove, Hopington and Fort Langley Aquifers, the major groundwater resources in the Salmon River Watershed (based on Dakin 1994) 20 Table 3.1 Canadian guidelines and British Columbian water quality objectives for drinking water, livestock and freshwater aquatic life. All units are mg L' 1 except where indicated. Data sources: Swain and Holmes (1985), Health and Welfare Canada (1989) 31 Table 3.2 Matrix of water quality measurements made for each sampling date 39 Table 3.3 Spearman Rank Correlation coefficients for selected water quality indicators for the Salmon River Watershed 66 Table 3.4 Spearman Rank Correlation coefficients showing the relationship between water quality indicators and stream discharge at Station 6 during three storm events in the Salmon River Watershed 69 Table 4.1 General categories of land uses, summarized based on the B.C. Land Use Classification (Sawicki and Runka 1986) 74 Table 4.2 Number of septic systems installed in the Salmon River Watershed and Hopington Aquifer, separated into decade of installation 84 Table 4.3 Ranges for septic system density, based on pollution potential (based on Canter and Knox 1985) 85 Table 4.4 Animal Unit Equivalents used to determine animal stocking density (Ontario Ministry of Agriculture and Food 1976) 88 Table 4.5 Total animal numbers for 1986 and 1991 and calculated animal units and stocking density. Data source: Statistics Canada 88 Table 4.6 Agricultural Census data showing animal numbers in the North Langley waste management zone, partitioned into small and large farms (based on Brisbin 1995) 92 Table 4.7 Criteria for large livestock farms (from Brisbin 1995) 94 Table 5.1 Contributing areas grouped for examining the relationship between land use and water quality (based on Cook 1994) 104 Table 5.2 Spearman Rank Correlation coefficients illustrating the association between selected land use and water quality indicators in the Salmon River Watershed . 124 X Table 6.1 Unit livestock nutrient production. The values are based on locally derived data (from Brisbin 1995). The values were averaged by livestock category for use with the Agricultural Census data 129 Table 6.2 Manure management nutrient loss factors. The values were inferred from the Abbotsford large farm example included in Brisbin 1995 130 Table 6.3 Unit crop nutrient uptake and inorganic fertilizer application rates (based on Brisbin 1995) 131 Table 6.4 Soil-atmosphere nitrogen exchange factors (based on Brisbin 1995) 132 Table 6.5 Summary of nitrogen inputs into the Salmon River Watershed for the census years 1986 and 1991 137 Table 6.6 Summary statistics for the surplus(deficit) nitrogen loading for individual farms included in the Agricultural Waste Management Survey for the Salmon River Watershed, by commodity type 144 Table 6.7 Summary of nitrogen inputs for the Salmon River Watershed 148 Table 6.8 Summary of surplus nitrogen before and after crop uptake 149 xi LIST OF FIGURES Figure 1.1 The nitrogen cycle (adapted from Brisbin 1995) 4 Figure 2.1 Location of the Salmon River Watershed in the Lower Fraser Valley of British Columbia 8 Figure 2.2 Location of the Salmon River and major tributaries, and residential areas within the watershed in the Township of Langley 9 Figure 2.3 Surficial geology of the Salmon River Watershed, generalized from the 1:20000 soils map (Luttmerding 1980) 11 Figure 2.4 Hydrograph of the Salmon River at 72 Ave., location of gauge station 08MH090, based on discharge measurements from 1970 to 1994. Data from Environment Canada 13 Figure 2.5 Hydrograph of the Salmon River at 72 Ave., location of gauge station 08MH090, based on discharge measurements for 1994 and 1995. Data from Environment Canada 15 Figure 2.6 Location of sampling stations on the Salmon river represented in the EQUIS and SEAM databases 17 Figure 2.7 Temporal variation in nitrate-N at four sampling stations in the Salmon River Watershed. Letters indicate location of sampling stations as shown in Figure 2.6. Data from EQUIS, SEAM, Beale (1976) and Cook (1994) 18 Figure 2.8 Temporal variation in faecal coliform counts at four sampling stations in the Salmon River Watershed. Letters indicate location of sampling stations as shown in Figure 2.6. Data from EQUIS, SEAM, Beale (1976) and Cook (1994). . . 19 Figure 2.9 Location of the urban areas within the Township of Langley and the Salmon River Watershed (adapted from the Corporation of the Township of Langley 1994) . 23 Figure 2.10 The 1994 land use cover map of the Salmon River Watershed 25 Figure 2.11 Land-use concept for the Township of Langley, from the 1993 Rural Plan (adapted from the Corporation of the Township of Langley 1994) 27 Figure 3.1 Location of streamwater sampling stations in the Salmon River Watershed . . 40 Figure 3.2 Spatial variation in average low-flow streamwater nitrate-N in the Salmon River Watershed. The nitrate-N values are averages of the June, July and August measurements 45 Xll Figure 3.3 Seasonal variation in streamwater nitrate-N in the Salmon River Watershed.. . 47 Figure 3.4 Long-term temporal variation in low-flow streamwater nitrate-N 48 Figure 3.5 Seasonal variation in streamwater ammonia-N in the Salmon River Watershed. 50 Figure 3.6 Seasonal variation in streamwater orthophosphate in the Salmon River Watershed 52 Figure 3.7 Seasonal variation in streamwater dissolved organic carbon in the Salmon River Watershed 53 Figure 3.8 Seasonal variation.in streamwater chloride in the Salmon River Watershed. . . 55 Figure 3.9 Seasonal variation in streamwater dissolved oxygen, in mg L' 1 , in the Salmon River Watershed 57 Figure 3.10 Seasonal variation in streamwater dissolved oxygen, in % saturation, in the Salmon River Watershed 58 Figure 3.11 Seasonal variation in streamwater specific conductance in the Salmon River Watershed 60 Figure 3.12 Seasonal variation in streamwater pH in the Salmon River Watershed 61 Figure 3.13 Seasonal variation in streamwater temperature in the Salmon River Watershed 63 Figure 3.14 Seasonal variation in streamwater faecal coliform and faecal streptococci counts in the Salmon River Watershed 65 Figure 3.15 Temporal variation in streamwater ammonia-N and orthophosphate at Station 6 during three storm events in the Salmon River Watershed 68 Figure 3.16 Relationship between three water quality indicators, ammonia-N, orthophosphate, and nitrate-N, and stream discharge at Station 6 in the Salmon River Watershed 71 Figure 4.1 Delineation of contributing areas to surface water sampling stations in the Salmon River Watershed (based on Cook 1994) 75 Figure 4.2 The 1994 land use activity map of the Salmon River Watershed 76 Figure 4.3 The area of land use activities in the Salmon River Watershed for 1979-1980 (Watts 1992), 1989-1990 (Watts 1992) and 1994 78 Xlll Figure 4.4 The change in agricultural and residential land use activity by contributing area in the Salmon River Watershed 79 Figure 4.5 Number of septic systems installed per year and cumulative number of septic systems installed in the Salmon River Watershed 82 Figure 4.6 Location of septic systems in the Salmon River Watershed and Hopington Aquifer installed between 1930 and 1994 83 Figure 4.7 The 1991 census boundaries in the Salmon River Watershed. Data source: Statistics Canada 87 Figure 4.8 Animal unit densities for census units in the Salmon River Watershed, based on the 1991 census data. Data source: Statistics Canada 90 Figure 4.9 Change in animal unit densities between 1986 and 1991 by animal type, in the Salmon River Watershed 91 Figure 4.10 Location of North Langley waste management zone in relation to the Salmon River Watershed (based on Brisbin 1995) 93 Figure 4.11 Location of the Agricultural Waste Management Survey farms in the Salmon River Watershed 96 Figure 4.12 Animal unit densities for individual farms grouped by commodity type in the Salmon River Watershed 97 Figure 4.13 Animal unit density by contributing area in the Salmon River Watershed. . . .100 Figure 4.14 Location of horses in the Salmon River Watershed 102 Figure 5.1 Relationship between septic system density and nitrate-N in surface water during low-flow conditions in the Salmon River Watershed 107 Figure 5.2 Location of septic systems and agricultural areas in the northern portion of the Hopington Aquifer 108 Figure 5.3 Temporal variation in streamwater temperature in the Salmon River Watershed for August 1994 110 Figure 5.4 Relationship between animal unit density, agricultural area density and nitrate-N in surface water during low-flow conditions in the Salmon River Watershed. ..112 Figure 5.5 Relationship between horse unit density, horse area density and nitrate-N in surface water during low-flow conditions in the Salmon River Watershed.. . .114 xiv Figure 5.6 Relationship between poultry unit density, poultry area density and nitrate-N in surface water during low-flow conditions in the Salmon River Watershed. . .116 Figure 5.7 Relationship between all other animal unit density, all other animal area density and nitrate-N in surface water during low-flow conditions in the Salmon River Watershed 118 Figure 5.8 Relationship between septic system density and nitrate-N in groundwater from wells on all surficial materials and wells on outwash only, in the Salmon River Watershed 121 Figure 5.9 Relationship between animal unit density and nitrate-N in groundwater in the Salmon River Watershed 123 Figure 6.1 Flow diagram of the model used to calculate nitrogen mass balance for the Salmon River Watershed 127 Figure 6.2 Surplus(deficit) nitrogen loading by census areas in the Salmon River Watershed for 1986 and 1991 135 Figure 6.3 Change in surplus(deficit) nitrogen loading from 1986 to 1991 in the Salmon River Watershed 138 Figure 6.4 Surplus(deficit) nitrogen loading for individual non-livestock farms included in the Agricultural Waste Management Survey for the Salmon River Watershed. Operations include nursery, berry and sod production 141 Figure 6.5 Surplus(deficit) nitrogen loading for individual poultry farms included in the Agricultural Waste Management Survey. Poultry operations include broilers, layers, and turkeys 142 Figure 6.6 Surplus(deficit) nitrogen loading for individual livestock farms included in the Agricultural Waste Management Survey for the Salmon River Watershed. Operations include dairy, sheep and horses 143 Figure 6.7 Total nitrogen inputs into the Salmon River Watershed, by contributing area. . 146 Figure 6.8 Total surplus nitrogen from agriculture and septic systems after losses in the Salmon River Watershed, by contributing area 147 Figure 6.9 Surplus(deficit) nitrogen loading in kg-N ha'1 from agriculture and septic systems in the Salmon River Watershed, by contributing area 150 Figure 6.10 Combined surplus(deficit) nitrogen loading in the Salmon River Watershed, by contributing area 151 XV Figure 6.11 Surplus nitrogen loading from agriculture and septic systems versus streamwater nitrate-N in the Salmon River Watershed 153 Figure 6.12 Combined surplus nitrogen loading versus streamwater nitrate-N in the Salmon River Watershed 154 Figure 6.13 Surplus nitrogen loading from agriculture and septic systems (based on total contributing area hectares) versus streamwater nitrate-N in the Salmon River Watershed 156 Figure 6.14 Combined surplus nitrogen loading (based on total contributing area hectares) versus streamwater nitrate-N in the Salmon River Watershed 158 Figure 6.15 Total surplus(deficit) nitrogen after losses by contributing area in the Salmon River Watershed. Surplus(deficit) nitrogen is partitioned into major sources: septic system, horse/sheep farms, and all-other farms 160 Figure 6.16 Comparison of nitrogen mass balance results for the Salmon River Watershed area from three different data sources 162 xvi ACKNOWLEDGEMENTS I am grateful to the Tri-coucil Eco-research Secretariat for the financial assistance I received through the Lower Fraser Basin Eco-research Project at the University of British Columbia. Additional funding was provided by the Township of Langley and the Fraser River Action Plan (Department of Fisheries and Oceans and Environment Canada). There are a number of people I would like to thank for the roles they played in my successful stay at UBC. Firstly, to Dr. Hans Schreier, my advisor, thank you for your continued support and enthusiasm. To the other members of my committee, Jennifer Nener, Dr. Ken Hall and Dr. Les Lavkulich, thank you for your guidance and the time you gave me. The technicians in both Dr. Schreier's GIS lab and the Soils lab provided data and advice. Thanks, in particular, to Sandra Brown and Alice Kenney for their GIS expertise. To my colleagues in Resource Management and Environmental Studies, thank you for helping me with some of my field work, listening to me and teaching me. I learned as much in the Rain Forest Room as I did in any of my classes. Finally, to my family and friends, thank you for keeping me sane and helping me remember what is really important in life. Mom and Dad, thanks for being my anchor. 1 1. Introduction The urban-rural fringe areas of many cities in North America are facing environmental and land use planning dilemmas. Increasing populations result in the migration of people out of the city to partake in a rural lifestyle, putting pressure on valuable land and water resources. As agricultural lands are converted to other uses, the intensity of almost all uses increase. Commercial agricultural operations continue with the same numbers of animals on smaller pieces of property. Rural residential areas are both expanding and experiencing increasing septic system densities. The phenomenon of small estate, or hobby, farms results in higher animal stocking densities in the backyards of the rural community. The mixed land-use in an urban-rural setting often results in diffuse and wide spread non-point source pollution, making the protection of drinking water sources such as groundwater aquifers increasingly difficult (Harper, et al 1992). In the province of British Columbia, the Greater Vancouver Regional District (GVRD) is growing at an average rate of 4% per year, and by the year 2021, the GVRD will have a population of 2,676,000 people (GVRD Strategic Planning 1995). As the urban population grows, the urban-rural fringe is being forced eastward in the Lower Fraser Valley. Currently, the interface between the urban and rural portions of the Basin is located in the Township of Langley (Corporation of the Township of Langley 1993). The Fraser Basin Ecosystem Study, funded by the Tri-Council Secretariat Eco Research Program, is devoted to describing the ecosystem structure and function of the Lower Fraser River Basin, and determining policy instruments and processes for future sustainability of the Basin (Westwater Research Centre and Sustainable Development Research Institute 1994). Three case study watersheds, all tributaries to the Fraser River, were selected to demonstrate the effect that differing landscapes and land uses can have on the aquatic health of a river. The 2 Brunette River, Burnaby, B.C., is a highly urbanized basin. Increasing traffic density and impermeability of the watershed surface have resulted in trace metal contamination of the streams in the Brunette system (McCallum 1995). At the other geographical end of the Lower Fraser Basin is the Sumas River Watershed, Abbotsford, B.C., one of the most intensively used agricultural areas in Canada. High manure application rates have resulted in elevated nutrient and microbial levels in the stream (Berka 1996). The third case study, also the subject of this thesis, is the Salmon River Watershed, Langley, B.C., which straddles the interface between the urban and rural areas of the Lower Fraser Basin. Nitrogen contamination of both stream and groundwater in the watershed from septic systems and animal manure are prominent environmental concerns. Non-point source nitrogen pollution of stream and groundwater is a global problem (Spalding and Exner 1993). A non-point source (NPS) pollutant is diffuse in nature and difficult to trace back to the original source, presenting unique challenges in developing management strategies for control and abatement (Libby and Boggess 1990). In an urban-rural environment, several land use activities contribute to NPS pollution. Agricultural NPS pollution includes leaching or runoff from fertilizer or manure spread on a field. Rural residential areas frequently rely on on-site waste disposal systems. While the literature defines a septic system as a point source (Cherry 1987) several septic systems in close proximity to one another may also be referred to as a NPS of pollution. This is because the nitrogen in the groundwater beneath or adjacent to a residential area cannot be traced back to a single home. As well, in mixed land-use areas, nitrogen which comes from a septic tank cannot necessarily be distinguished from that of agricultural origin. In order to determine the extent of the sources, the actual mechanisms by which nitrogen reaches stream or groundwater must be studied. Figure 1.1 is a flow diagram showing the 3 nitrogen cycle. The primary biological transformations are located on the thick grey circle, while other pathways are shown with thin black lines. After nitrogen is applied to the soil surface, in the form of plant residues or animal and human wastes, soil organisms mineralize organic nitrogen (-NH2) into inorganic nitrogen such as ionic ammonia (NH4+). Organic nitrogen is bound to organic matter, while inorganic nitrogen is not. Nitrification, the oxidation of nitrite (NOz) and ammonia, is accomplished by another set of soil organisms. The product of this process, nitrate (N03), may then be taken up by plants. In the natural environment, a nitrogen-bearing molecule does not necessarily follow the simplistic pathway as described above. Nitrogen may come from a host of other sources, such as the atmosphere, biological fixation, and inorganic fertilizers. At any stage throughout the cycle, nitrogen may also be diverted through any one of several other pathways. Particularly important are those that result in losses from the system. For example, inorganic nitrogen may be denitrified, or converted into gases (N2, N20) which escape to the atmosphere. When the inputs of nitrogen into the system exceed the nutrient needs of plants and soil organisms, nitrate may leach into the groundwater, or be transported to streams in runoff. The nitrogen available for leaching or runoff may be estimated by calculating a nitrogen budget, which essentially quantifies the sources (the atmosphere, plant residue, animal and human wastes, soil organic matter) and sinks (plant uptake, denitrification, ammonia volatilization) which constitute the nitrogen cycle. Most nitrogen budgets, however, are simplified to accommodate the availability of relevant data (Barry, et al. 1993, Wylie, et al. 1994). Water movement is the primary means by which wastes are transported to receiving water bodies (Libby and Boggess 1990). For this reason, a watershed is a useful geographic unit in which to study non-point source pollution. A watershed is a drainage area delineated by Figure 1.1 The nitrogen cycle (adapted from Brady 1990) 4 -| Primary biological pathways — Other pathways losses 5 topography; the watershed boundary is located at the topographic high, while the mouth of a watershed is located at the lowest point. Land use activities upstream can have an effect on downstream water quality. In order to link non-point sources of pollution to water quality, land use and water quality indicators can be spatially related throughout the watershed. An indicator provides a measure of ecosystem quality or of trends in water quality (Water Quality Guidelines Task Group 1994). By spatially relating land use and water quality indicators, the present health and potential changes in health of a watershed may be monitored. Geographical information system (GIS) can be a useful tool in quantifying spatial and temporal changes in land-use indicators of non-point source pollution in a watershed context. A GIS is a combined computer mapping and database management system (Burroughs 1986), which can be used either to simply quantify spatial data, or query complex spatial relationships between different characteristics of a watershed in order to develop a classification scheme. The former analysis has been used in many watersheds to determine the empirical relationships between land use and water quality (Osborne and Wiley 1988, Kalkhoff 1993, Bauder, et al. 1993). The latter analysis has been useful in determining the pollution potential of various land uses by spatially relating human activities to physically sensitive landscapes (Halliday and Wolfe 1991, He, et al 1993, Wylie, et al. 1994). This thesis is built on previous work which initially identified the relationship between land use and stream habitat and water quality in the Salmon River Watershed (Cook 1994, Watts 1992, Beale 1976). The link between residential and agricultural activities in this urban-rural watershed was further described through indicators which reflected the intensity of land use. The indicators, which included septic system and animal unit densities, were quantified from spatial land use data in a GIS database. An additional indicator, surplus nitrogen application, was calculated from a nitrogen mass balance model. Graphical and statistical analyses were then 6 used to relate land use with water quality indicators measured throughout the watershed. The suite of land use and water quality indicator relationships identify problem areas and provide information which can contribute to a resource management strategy for the Salmon River Watershed. 1.1 Study goal The goal of this study was to examine how the type, intensity and changes in urban and rural land use activities have affected streamwater quality in the Salmon River Watershed, Langley, B.C. A Geographical Information System (GIS) based approach was used to quantify land use indicators of non-point source nitrogen pollution and spatially relate them to streamwater quality. 1.2 Study objectives 1. to describe spatial and seasonal streamwater quality trends over one annual hydrological cycle; 2. to examine temporal trends in selected water quality indicators between 1974 and 1994; 3. to describe spatial and temporal variability in land use activities, using indicators which quantify non-point sources of nitrogen; 4. to quantify spatial and temporal variation in nitrogen loading in the watershed; 5. to identify spatial relationships between water quality and land use indicators. 7 2. Salmon River Watershed: Description of Study Area The characteristics of some of the natural resources and how human activities affect them are influenced by the physical setting in which the Salmon River Watershed is located. The seasonal flow regime of the Salmon River and its tributaries is governed by climate and surficial geology. A large aquifer in the watershed, consisting of a glacial outwash deposit, provides excellent fish habitat where the stream has incised the outwash material, and also supplies drinking water for a majority of rural residents. The following chapter presents a description of the physical setting and human activities of the watershed which have an influence on water quality, as well as a description of the water and fish resources which are important to the area. 2.1 Setting The Salmon River Watershed is located at the urban-rural fringe of the Lower Mainland area of British Columbia (Figure 2.1). The river originates in the western most portion of the City of Abbotsford, flows northwest through the Township of Langley and drains into the Fraser River west of Fort Langley (Figure 2.2). The watershed is approximately 8020 ha, and ranges in elevation from sea level to 140 m (Cook 1994). 2.1.1 Climate The Lower Fraser Valley experiences relatively warm, wet winters, and cool dry summers. Precipitation in the valley varies from south to north and west to east due to the influence of the nearby Coast and Cascade Mountains. White Rock to the south has an average total rainfall of 1093 mm yr"1, while Chilliwack to the northeast, has an average total rainfall of 1880 mm yr"1. In the Salmon River Watershed itself, rainfall increases from approximately 8 9 10 1400 mm at the southern boundary, to 1700 mm in the north near Fort Langley (based on isohyetal lines in Dakin 1994). Seventy-five percent of the rainfall takes place between October and May (Halstead 1986), resulting in increased stream flows and significant groundwater recharge. 2.1.2 Surficial geology The surficial geology of the Salmon River watershed is complex, due to repeated glacial events, marine inundation and river activity. Figure 2.3 shows the surficial geology of the Salmon River Watershed, generalized from the 1:25,000 soils map (Luttmerding 1980). Glacial marine sediments dominate the northeastern portion of the watershed as well as a small area in the western extreme of the watershed. A large, coarsely textured glacial outwash deposit, which constitutes the Salmon River Uplands, underlies the middle of the watershed. Fort Langley is built on a smaller outwash deposit near the confluence of the Salmon River with the Fraser River. Marine sediments have been deposited to the west of the Salmon River Uplands between glacial invasions. Fluvial deposits from a former meander of the Fraser River form the Fort Langley floodplain. Cook (1994) presents a more detailed documentation of the surficial geology of the watershed. 2.2 Surface water resources 2.2.1 Drainage network The Salmon River is joined by two major tributaries as it flows through the north central area of the Township of Langley (Figure 2.2). Coghlan Creek originates near the Langley-Abbotsford border and joins the Salmon mainstem in William's Park, on the western edge of the 11 12 Hopington Aquifer. Both the Salmon River and Coghlan Creek deeply incise the glacial outwash deposit of the Hopington Aquifer. Davidson Creek flows along the eastern watershed boundary, through the northern most portion of the Hopington Aquifer and then joins the Salmon mainstem in the Fort Langley floodplain. The stream drainage network has been modified by human activities in the watershed, affecting both the up and downstream migration of fish (Watts 1992). A flood gate and pump system at the mouth of the Salmon River is used to prevent flooding of the Fort Langley floodplain during times of high flow in the Fraser River. The pump is usually in operation between March and July, a critical time period for the downstream migration of Coho salmon. Throughout the watershed culverts and bridges have been installed at road crossings. Culverts can themselves physically impede the migration of fish, or cause an increase in stream velocity, which will also restrict fish passage (Chilibeck, et al. 1993). An accompanying affect of stream crossings is the diversion of road runoff directly into the stream channels. Runoff from roads may transport oil, metals and sediments into the streamwater. 2.2.2 Stream discharge The discharge of the Salmon River is monitored by Environment Canada with a hydrographic station (station # 08MH090) located at the intersection of 72 Ave and the Salmon River. Figure 2.4 shows the average minimum, maximum and mean flows for the period of 1970 to 1994. The lowest flows typically occur in July through August, at which time groundwater discharge contributes the greater proportion of water in the stream. The highest stream flows are measured during the months of November through February, when precipitation contributes the greater proportion of water in the stream. During the past 24 years the average daily discharge was 1.4 m3 s"1. The lowest average daily discharge, 0.099 m3 s"1, was 1 3 Figure 2.4 Hydrograph of the Salmon River at 72 Ave, location of gauge station 08MH090, based on discharge measurements from 1970 to 1994. Data from Environment Canada. 14 measured on 1 and 2 October 1974, while the highest, 39.03 m3 s"1, occurred on 24 February 1986. The average daily discharge for the 1994-1995 sampling season is depicted in Figure 2.5. Regular sampling dates are indicated with triangles. The dates for which a series of storms were monitored during October and November are indicated with filled in circles. 2.2.3 Surface water quality A water quality assessment performed by the B.C. Ministry of Environment in 1985 and an update in 1995 at several sites in the Salmon River downstream from the Hopington Aquifer area have been used to set water quality objectives for the protection of aquatic life in the river (Swain and Holmes 1985, Swain, et al. 1995). Generally, the water quality measurements met both Canadian drinking water and freshwater aquatic life standards. pH was slightly basic (between 7 and 8) and the streamwater has a good buffering capacity. Total hardness (mean of 60 mg L"1) and calcium concentrations (mean of 15 mg L"1) indicate that the Salmon River is moderately soft. Dissolved metal concentrations were below the maximum prescribed water quality criteria, and dissolved oxygen was sufficiently high for the embryo and larval stages of salmonid fish species. Of the nutrients measured, total ammonia and total phosphorus were acceptable. While nitrate values did not exceed the drinking water standard of 10 mg-N L"1, they were considered to be high (above 3 mg-N L"1) at several stations in the 1985 study. Faecal coliform counts exceeded water quality criterion for both study periods. A compilation of historical water quality data for the Salmon River Watershed provided evidence that while the river is relatively healthy, water quality problems such as high nitrate concentrations and faecal coliform counts existed as early as the 1970s (Cook 1994). Four stations at which both the provincial government and the University of British Columbia (UBC) 15 0 hai o 0) o w CD rt c o o nd "O — CD CO CD ba CJ 1_ o 'o CD o JZ X 00 to" CD o rt c T 3 o D ) C rt uge st samp co CD to H— o O T3 c C o CO *•+-; CO T3 rt 0 rt , loc angl Can CD -*—< > -*—' c < 0 0 CM Th E Th c o rt in CO > CD CO c > LU T J E on an o L_ H— E «t co rt rt CO rt oo 1— Q he i _ o H— CO 0) 0 +-» o c rt . c T3 cx E CD rt 0 c drogi k_ ZJ o drogi CO rt ' >» 0 o i E E in OJ 0 1 1 — - * — • < • • • i • • 1 1 o o i-a m U J L L < -3 o LU a < C O 3 ~3 LT a. < LT < m LU (t.s 6 L U ) 9 B J E L | 0 S ! P A||ep S B B J S A V 16 have undertaken water quality monitoring are shown in Figure 2.6. Figure 2.7 shows the temporal variation in nitrate-N at the four stations. While the drinking water criterion for nitrate-N was not exceeded, several samples had nitrate-N concentrations of 3 mg L"1 or more. At station D, a majority of samples were above 3 mg L"1, and some were as great as 6 mg L"1. The faecal coliform counts done at the same four stations frequently exceeded the water quality criterion for partially treated drinking water (Figure 2.8). Provincial water quality records for the period of 1971 to 1985 were maintained in a database named EQUIS. Current records are stored in the SEAM (System for Environmental Assessment and Management) database (Cook 1994). The two UBC programs included bi-monthly monitoring during the period of July 1974 to March 1975 (Beale 1976) and seasonal monitoring from August 1991 to August 1993 (Cook 1994). 2.3 Groundwater resources 2.3.1 Major aquifers There are three major aquifers in the watershed, Aldergrove, Hopington and Fort Langley (Table 2.1). Near the headwaters, the Aldergrove Aquifer is a thin (5 to 20 m), confined, fluvial sand deposit capped with silty sediments (Piteau 1991). While the predominant flow in the 35 km2 aquifer is south and east, some of the groundwater discharges into the Salmon River to the northwest, and Nathan Creek to the northeast. The largest of the three aquifers, the Hopington, is located in the middle portion of the Salmon River (Figure 2.3) and is composed of up to 30 m of sand and gravel deposits (Halstead 1986). Groundwater in this unconfined aquifer flows westward into the Nicomekl River, northwest into the Salmon River and its tributaries, and northeast to Nathan and Beaver Creeks (Dakin 1994). The third aquifer is located near Fort Langley and the mouth of the Salmon River. The Fort Langley Aquifer is an unconfined aquifer 17 18 at c a. E to to u— O c o 8 CD © co £2 ^ H 8 ^ o Q) CO > a: CD o o> E w ro » (0 ca m 0 0 CO 3 to" ™ 5 IS | E 11 1 CM <B a) E b c u_ § i CD O •c x: ca co > co ra 1 0 5 2 Q- o E a) iS I— co 1^ CN £ a> CN c o CO O c 0 CO 1 at • 1 V s CO CO co o CO CD g co io co (-|/6iu) N-a»BJj!N CN T -C o cu a •o I I I I I I I I V I 1 I 1 I 1 I 1 I 1 I 1 i n -<J- CO CN r-CO CO co CO cn o co co co co CN CO CO CN c o CO CN i t 1 • I I I I I 1 I 1 I 1 I 1 I CO IO CO <N (1/6UJ) N-9JEJUN 3 cn co co co 2 to o CO co ^ CO g co co e o CO ai 10 CD CO 3 ca O O 1 • 1 1 1 1 1 1 1 1 1 1 1 1 1 1 N . C O I O - « T C O C N ' « - 0 3 co co oo CD CO CO o CO CO CO CO g Q (T/6LU) N-a»E4!N (I/Bui) 19 c o s o 2 8 T3 C 0) 0) •a v .c 12 I (D > c 0 E ca co I-To W 00=3 .E a Q.LU | E i i w ai 8 § E 2* 1 = s.g (D 10 c 1 0 — (0 c c o g S ™ > c? 2 ^ 8.| E CO m W I— ^  00 cvi a> CN 1 1 1 C i l o I I •1—1 1 I. 1 § 1 1 CO 1 1 I 1 I 8 i i O | | 1 1 1 c o CO 1 1 1 1 . . Dl 1 1 1 1 1 ca . . i | i | i | i | i | i 8 co 00 00 s o> o oo CD CD CD CD O O O O O O O O O O O O O O O O O O CO i o ^ - CO CM « -(liuoOLAUncn) SWJOJHOO leoaej co a> ao T3 CD 8 •I o o o o o o o o o CO IO O O O CO I '• I o o o o o o CN •«-8 cn oo ao 00 CO o 00 CO CO a> g Oi oo CN c 0 1 CO CN CO 00 00 CO 2 to o 00 a> o o o O Q O o o o co in co c o CO co 0 1 CD 4) » 3 CO 0 o o o o o o o o o co m -^o o o co I ' I o o o o o o CN T -O) oo 00 01 00 CO o 00 CO CO CO CO a ( " | U i o o i A u n o ° ) suiio;!|oo leoaej (ituooi-Aunoo) sunoj!|oo |eoaej 20 composed of up tol8 m of sand and gravel deposits (Halstead 1986). Unlike the Aldergrove and Hopington Aquifers which rely on precipitation for recharge, the Fort Langley Aquifer receives exfilitration from the Salmon River (Dakin 1994). Table 2.1 Summary information for the Aldergrove, Hopington and Fort Langley Aquifers, the major groundwater resources in the Salmon River Watershed (based on Dakin 1994). Aquifer Area (km2) Average Thickness (m) Estimated Recharge (Mm3 yr1) Annual Abstraction (Mm3) Recharge source Aldergrove 24 15 6.5 4 precipitation only Hopington 40 8 8 3 precipitation only Fort Langley 20 8 6 4.5 significant recharge from Salmon River 2.3.2 Groundwater quality Unconfined sand and gravel aquifers, such as the Hopington Aquifer, are the most susceptible to contamination (Halstead 1986). Groundwater studies in the Salmon River area from the early 1970's to the present indicate that high nitrate levels, in particular, have been and continue to be a problem (Kwong 1986, Kerr 1984, Gartner-Lee Limited 1992, Schreier 1995). Kwong (1986) reviewed data collected for a period of 1969 to 1979, and identified three areas in which nitrate-N concentrations exceeded 20 mg N03-N L"1. All the sites are located between 232 and 256 St. to the west and east, and 48 and 64 Ave to the south and north (Figure 2.2). The highest concentration measured during the period of review was 50 mg N03-N L"1. The high nitrate values are reportedly due to a combination of animal manure and high densities of on-site sewage disposal (Gartner-Lee Limited 1992, Kwong 1986, Halstead 1986). 21 A more recent survey of groundwater in the Hopington Aquifer measured nitrate-N from seventy wells of differing depths, at different times throughout one annual cycle (Schreier 1995). During May and August, only two wells exceeded 10 mg N03-N L"1. The wells are located in a low-residential area surrounded by agriculture, to the north of the high nitrate areas identified by Kwong (1986). The remaining wells had nitrate-N concentrations varying from below detection limit to 9.9 mg N03-N L"1. In February, 9 wells, distributed throughout the central portion of the aquifer, exceeded 10 mg N03-N L'1. Some of these wells are in one of the high nitrate areas identified by Kwong (1986). The highest concentrations (up to 48 mg N03-N L"1) were consistently measured in a well that is 80 ft (25 m) deep. Nitrate-N levels above 10 mg L"1 can cause a condition known as methaemoglobinemia or cyanosis in infants younger than six months of age (Keeney 1986). Because of the high nitrate levels found in the Hopington Aquifer, health officials have circulated warnings to parents who use the groundwater as their source of drinking water, such as the March 1993 edition of the Health File (Ministry of Health and Ministry Responsible for Seniors 1993). The pamphlet describes the symptoms of methaemoglobinemia and advises parents to use alternate drinking water sources. 2.4 Fish The gravel substrate and consistent supply of clean, cool water from the Hopington Aquifer provide some of the best salmon spawning and rearing habitats in the Lower Fraser Basin (Cook, et al. 1993, Watts 1992). Important salmonid species found in the Salmon River include: coho salmon (Oncorhynchus kisutch), steelhead trout (Oncorhynchus mykiss) and cutthroat trout (Oncorhynchus clarki clarki). Non-salmonid species include various sculpin, shiner, minnow, lamprey, and sucker species. The headwaters of the Salmon River also contain 22 one of the last remaining habitats in British Columbia for the endangered Salish Sucker {Catostomus sp.) (Cook, et al. 1993). Fish habitat and productivity are not a focus of this thesis. However, agricultural and urban land use activities can affect fish in both direct and indirect ways (Watts 1992). Decreased stream flows and sedimentation are of primary concern, however, water quality may also impinge upon fish habitat and productivity. Salmonid species have high dissolved oxygen requirements (Chilibeck, et al. 1993). Elevated nutrient concentrations may cause oxygen depletion in localized parts of the stream during the summer months, degrading the quality of fish habitat. 2.5 Human activity 2.5.1 Population The population of the Township of Langley increased from 22,000 in 1971, to over 80,000 people in 1995; the most recent data shows an average growth rate of about four percent per year (Crawford 1993, Corporation of the Township of Langley 1994b, GVRD Strategic Planning 1995). Much of this growth has occurred in the urban centres in the Township (Figure 2.9). However, a substantial portion of the population is locating in rural residential areas and on hobby farms (Crawford 1993). The 1991 population of the Salmon River Watershed was about 13,000, estimated from 1991 Population Census data (Statistics Canada 1991c). Approximately 2,500 people live in Fort Langley and 6,000 in the Salmon River Uplands, where the major urban centres in the watershed are located (Corporation of the Township of Langley 1994b). The remaining 4,500 people live scattered throughout the watershed. The population growth rate varies throughout the watershed. The largest average rates, 5.6 and 3.4 % per year between 1986 and 1991, igure 2.9 Location of the urban areas within the Township of Langley and the Salmon River Watershed (adapted from the Corporation of the Township of Langley 1994). 24 occurred in Central Langley and the Salmon River Uplands, respectively. Fort Langley, already a dense urban centre, only grew at an average rate of 0.7% per year. 2.5.2 Land use and zoning Langley was first settled in 1827, with the establishment of the Hudson's Bay Company at Derby Reach near the Fraser River (Crawford 1993). A s the fur trade declined, logging and farming grew in importance, and were accompanied by a slowly increasing population. B y the 1950's the population had increased to the point at which urban services were in demand and residential areas started to expand in the Township (Crawford 1993). Current land uses in the watershed include agriculture, un-developed forested land and residential activities (Cook 1994). Agricultural production in the rural areas of the Township of Langley include: livestock operations (dairy, swine, sheep, beef, and rabbits); poultry; small fruits (strawberries, raspberries, blueberries and cranberries); mushrooms; vegetables and cole crops, flowers and nursery stock; fur bearing animals; turf; and, nuts (Corporation of the Township of Langley 1993). The horse industry has also become a significant part of the rural economy; the presence of over 6,500 horses makes Langley the horse capital of British Columbia (Corporation of the Township of Langley 1993). Hobby farms are also a growing component of the agricultural sector. A hobby farm, as defined in the Township of Langley's Rural Plan, is operated for enjoyment or as a supplementary income source (Corporation of the Township of Langley 1993). A hobby farmer typically derives his or her main income from off-farm activities. A large proportion of the watershed remains either treed or open space as is depicted by the 1994 land use cover map (Figure 2.10). Along with watercourses and marshes, the large treed tracts provide natural areas and wildlife habitat (Corporation of the Township of Langley 25 26 1993; Cook, et al. 1993). In the middle portion of the watershed, forests and pasture land are fragmented by residential areas (see previous section for location of major residential areas). Approximately 75% of the Township of Langley is designated as rural residential/ agricultural in the Official Community Plan (Corporation of the Township of Langley 1993). This zoning reflects the Agricultural Land Reserve (ALR) Act which was established in 1972 in order to preserve high quality agricultural land from urban encroachment (Crawford 1993). Rural Langley is further subdivided into three zoning categories, agricultural/countryside, small farms/country estates and the Salmon River Uplands (Figure 2.11). In areas zoned as agricultural/countryside, agricultural uses take priority over non-agricultural uses, and the minimum lot size is eight hectares. Small farms/country estates have a minimum lot size of 1.7 hectares. While agricultural uses are given priority in this zone, the ALR Commission does not support the subdivision of ALR land into smaller lots because it promotes residential and other non-farm uses (Crawford 1993). The Salmon River Uplands is maintained for rural residential and agricultural uses. A more detailed plan for future use of the area is forthcoming (Corporation of the Township of Langley 1993). 2.5.3 Water and sewerage A majority of the residents in the Salmon River Watershed obtain drinking water from private or community wells (Cook 1994). Fort Langley and Forest Knol ls receive water from the Greater Vancouver Regional District, supplemented by municipal wells. Residents located near the community of Aldergrove are also serviced by municipal wells. Almost all houses in the watershed have on-site sewage disposal (Cook 1994). A few residences and Trinity Western University are connected to a municipal sewerage service which is extending northward to the watershed along Glover Road. 27 Figure 2.11 Land-use concept for the Township of Langley, from the 1993 Rural Plan (adapted from the Corporation of the Township of Langley 1993). 28 2.5.4 Environmental management in the watershed Attention to the unique qualities of the Salmon River Watershed was first given during a failed attempt to implement a "cooperative watershed and management planning program" for salmonid enhancement (Howard Paish & Associates 1980). Renewed interest in 1993 resulted in the creation of the Salmon River Watershed Management Partnership (SRWMP), the mission of which is "to establish a cooperative, community based stewardship of the Salmon River Watershed which balances economic, environmental and social needs of the watershed" (SRWMP 1995). The Partnership consists of various federal, provincial and municipal governments, educational institutions and citizen groups that have a mandate or interest in promoting the stewardship of resources in the watershed. To date, the primary stewardship activities in the watershed have included extensive tree planting and in-stream rehabilitation by the working arm of the SRWMP, the Langley Environmental Partners Society (LEPS). The agency portion of the Partnership is engaged in drafting a Memorandum of Understanding, which will outline the roles and responsibilities of the members, and lay the foundation for a management plan. A citizen group, the Salmon River Enhancement Society (SRES), is actively involved in public education regarding stream stewardship. Significant progress towards the protection of the Salmon River's resources include a moratorium on subdivision of lots in the Hopington Aquifer area (P. Scales, pers. comm.). A planning model being developed at the Institute of Resources and Environment at UBC is a tool which will be used to aid the Township of Langley in planning the future of this sensitive area. The activities of SRWMP, LEPS and SRES serve as examples to other communities, under the designation of the Salmon River as a demonstration watershed by the Fraser River Management Board. The relatively good quality of the Salmon River and the large body of 29 scientific data, including an Environmentally Sensitive Areas Assessment conducted for the entire Township (Cook, et al. 1993), are factors favoring the development of a cooperative management plan. 30 3. Streamwater quality 3.1 Indicators of water quality While it is not feasible to completely characterize the health of a stream, various streamwater constituents may be chosen to serve as general indicators of water quality and overall ecosystem function and health. Indicators are measurable features which provide information about the state of ecosystem health, undesirable changes or potential for change in health, and factors which affect health (Water Quality Guidelines Task Group 1994). The indicators themselves may not negatively affect the aquatic environment. They may, however, suggest the presence of harmful constituents or the potential for future degradation. The water quality indicators used for this study were chosen on the basis of historical studies so that trends may be described, and to further determine the current health of the Salmon River and its tributaries. They are easily measured and can be linked to human activities in the watershed. Included are measures which indicate anthropogenic inputs; nitrate, orthophosphate, and chloride are all naturally occurring, but elevated levels may be evidence of human influence. Health and Welfare Canada (1989) has set national guidelines for drinking water and livestock, while the Canadian Council of Resource and Environment Ministers (1987) has set guidelines for the protection of freshwater aquatic life . The British Columbian Ministry of Environment has set provisional objectives for freshwater aquatic life on a stream by stream basis (Swain and Holmes 1985). The guidelines and objectives for indicators measured in this study are summarized in Table 3.1. 31 Table 3.1 Canadian guidelines and British Columbian water quality objectives for drinking water, livestock and freshwater aquatic life (Health and Welfare Canada 1989, Canadian Council of Resource and Environment Ministers 1987, and Swain and Holmes 1985). All units are mg L"1 unless otherwise noted. Canadian Water Quality Guidelines B.C. Obiectives Water quality Drinking water Live- Freshwater stock aquatic life Freshwater aquatic life in the Salmon River indicator concentration comments concent-ration comments pH(log scale) 6.5-8.5 6.5-9.0 6.5-8.5 outside dilution zone of effluent dissolved oxygen 9.5 cold water biota: early life stages 6 all times 6.5 other life stages 8 11.2 alevin, larvae, fish not in eye-to-hatch fish eggs in eye-to-hatch stage total dissolved solids 500 3000 Chloride 250 Ammonia, total 2.2 at pH 6.5, temperature 10 °C 0.03 unionized, maximum per sample 1.5 at pH 6.5, temperature 20 °C 0.007 unionized, mean value for 5 weekly samples during 30 d period Nitrite 1 10 0.06 0.02 continuous exposure of salmonids Nitrite + nitrate 10 100 avoid concentrations that stimulate weed growth 40 protection of aquatic life Total coliform MPN/100 mL 10 presence no more than 10% of samples in 30 d period no more than two consecutive samples Faecal coliform MPN/100 mL 0 4000 1000 maximum, for irrigation and livestock watering geometric mean over 30 H ppr inH f n r i r r igat ion 32 3.1.1 Nitrate and Ammonia Nitrogen is an essential nutrient in aquatic systems and is naturally occurring. Typical values for nitrate-N range from 0.07 to 2.3 mg L"1, and for total ammonia-N, from 0.03 to 0.41 mg L"1 (Stednick 1991). Domestic sewage, inorganic fertilizer and animal manure may also contribute nitrogen directly to streams. Indirectly, they may result in the build up of organic nitrogen in the soil which may release nitrogen over a considerable period of time (Addiscott 1988). Excessive inputs of nitrogen into natural systems is of concern because they upset the natural cycling of the nutrient and other streamwater constituents (Waite 1984). Dissolved oxygen may be depleted through either the addition of ammonia from domestic sewage or nitrogen enrichment which stimulates excess aquatic plant growth. Oxygen is consumed in the nitrification of the ammonia, or the oxidation of organic matter when the plants begin to decompose. The nitrate ion is conservative, and can pass through the soil without loss due to adsorption onto soil particles. This makes nitrate a significant contaminant of groundwater. High concentrations of nitrate-N in drinking water have been identified as a health risk, in particular for infants under the age of six months. The digestive tract of an infant is more acidic than that of an adult and therefore behaves as a reducing environment in which nitrate is converted to nitrite. Once the nitrite is absorbed into the bloodstream, it binds to haemoglobin. The product of this reaction, methaemoglobin, is unable to carry oxygen to the rest of body, which may ultimately result in death (Keeney 1986). The Canadian drinking water standard has been set at 10 mg L ' 1 of nitrogen as nitrate, which is equivalent to 44 mg L"1 nitrate. No deaths have been reported from water with less than this amount of nitrogen. Ammonia occurs in two forms in water: N H 4 + and NH 3 . Above a pH of 9.2 NH 3 predominates (Dojlido and Best 1993). It is this free-ammonia form which is toxic to aquatic 33 organisms. Water quality standards may be set in terms of total ammonia (NH4+ + NH3) or free or un-ionized ammonia forms (NH3). The most common way for ammonical-N to enter streams is through domestic waste discharge and runoff from agricultural fields (Stednick 1991). The presence of free ammonia or nitrite is evidence of recent contamination with sewage or other organic matter (Hem 1985). These two nitrogen forms are unstable in well aerated waters, however. Nitrate, conversely, is stable over a wide range of conditions and may also be evidence of contamination: however, the site or time of contamination would be considerably removed from the water sample site (Hem 1985). 3.1.2 Orthophosphate Phosphorus occurs in nature primarily in the form of orthophosphate weathered from rocks. Once released from the source mineral and dissolved in water, orthophosphate occurs mainly in one of three forms, depending on the pH; in neutral waters, H2P04" and HP042" predominate, and in acidic environments H3P04 is more abundant. Human sources of phosphorus in the aquatic environment include human wastes, household detergents and runoff from agricultural fields on which animal manure or inorganic fertilizers have been spread (Stednick 1991). Once dissolved, orthophosphate can enter one of two pathways. Phosphate can complex with aqueous cations like iron, aluminum, or calcium to form insoluble molecules which precipitate out into the sediments (Waite 1984). These phosphates are therefore no longer available for plant uptake until such time as the sediments are disturbed and phosphate released through chemical degradation (under reducing contitions). Dissolved orthophosphate may also be absorbed by plants and converted into polyphosphate. Phosphorus in plant tissues is released back into solution when bacteria degrade polyphosphate back into orthophosphate (Waite 1984). 34 Orthophosphate levels in naturally occurring waters range between 0.001 and 0.024 mg L ' 1 . In some of the more polluted rivers in the world, concentrations as high as 2.5 mg L" 1 have been recorded (Meybeck 1982). Phosphate itself is not harmful to health in naturally occurring concentrations (Dojlido and Best 1993). The primary concern about excessive phosphate is eutrophication. In freshwater aquatic systems, phosphorus is the limiting factor for plant productivity. With phosphorus enrichment comes excess aquatic plant growth and greater potential for oxygen depletion (Sharpley, et al. 1994). Most water quality guidelines are set in terms of the levels at which eutrophication is accelerated. For example the European Economic Community (EEC) has set water quality guidelines depending on the sensitivity of the aquatic organism to changes in oxygen levels. The guideline for salmonids has been set at 0.065 mg L" 1 of total phosphorus while a higher guideline of 0.13 mg L~ l total phosphorus has been set for cyprinids. The drinking water guideline has been set at 0.176 mg L" 1, and the maximum allowable concentration is 2.2 mg L" 1 (Dojlido and Best 1993). There are no water quality criteria for phosphorus in Canada. 3.1.3 Dissolved organic carbon Dissolved organic carbon is an important indicator of the overall productivity of a system; increasing amounts of organic matter may indicate that the system is moving toward a more mature state. However, if the build up of organic matter occurs too quickly, the oxygen pool may be depleted through the decomposition or oxidation of the organic matter. Such a disturbance is usually human induced, and can occur by excessive inputs of organic carbon or by the addition of "contaminants which accelerate overall productivity" of the system (Waite 1984). Dissolved organic carbon ranges between 1 mg L" 1 and 20 mg L" 1 in unpolluted streams; maximum concentrations, about 25 mg L" 1, are observed in streams draining swamps or poorly 35 drained soils (Meybeck 1982). There is no water quality standard for dissolved organic carbon. 3.1.4 Chloride Chloride is present in all natural waters. The concentration of chloride in streams is usually less than one mg L"1. However, the concentration may be much greater due to: sedimentary rocks which have been infused with sea salts; high chloride groundwater; industrial waste; road salting during the winter; or, salt water intrusion of the ocean (Stednick 1991). Domestic waste can also be a significant source of chloride in water (Dojlido and Best 1993). High chloride concentration is not toxic to humans, but it may corrode metal pipes and will kill various aquatic plants. Drinking water standards are usually set at 250 mg L"1 for aesthetic reasons; at this concentration, chloride makes water taste "salty". Typical values range from O.nmgL'toMOmgL" 1 . Chloride is a conservative ion; it does not enter into any oxidation or reduction reactions, complex with other ions, or adsorb onto mineral surfaces (Hem 1985). For this reason, and the fact that humans excrete about 5.6 mg per day, chloride can be a useful tracer for septic system effluent (Canter and Knox 1985). However, in an area with highly mixed land uses, including animal and crop production, chloride may not be a useful indicator of solely human wastes. 3.1.5 Dissolved oxygen Oxygen is an essential element for higher forms of aquatic life and, therefore, is a useful indicator of stream health. Molecular oxygen is continuously dissolving from the atmosphere into water. The physical movement of water, such as from the wind or rapids, promotes the dissolving of oxygen into water. Aquatic plants, both algae and macrophytes, also contribute oxygen to the water through photosynthesis. The concentration of oxygen in water is usually at 36 an equilibrium, governed by temperature and atmospheric pressure (Hem 1985). The equilibrium concentration of dissolved oxygen can range from 12.75 mg L'1 at 5°C to 7.54 mg L"1 at 30°C. As discussed previously, however, oxygen may be consumed to the point of depletion when oxidizable constituents are added to the water. Oxygen may also be "super saturated" above the equilibrium concentration due to the vigorous photosynthetic activity of aquatic plants during the daytime; conversely, oxygen depletion may occur during the night when plants are respiring and consuming oxygen (Waite 1984). Water quality guidelines for dissolved oxygen vary, depending on the life stage of the organism. Earlier stages require higher concentrations of at least 9.5 mg L"1. For all other stages, the guideline is 6.5 mg L'1. In terms of percent saturation, 90% is the optimum level for salmonids (Chilibeck, et al. 1993). 3.1.6 Specific conductance Conductivity refers to a body's ability to conduct electricity. This ability is usually measured and reported in terms of specific conductance, which is the conductance of a body of unit length and unit cross section at constant temperature (Hem 1985). The conductivity of water is determined by the ionic activity, and gives a good indication of the amount of salts dissolved in the water; more ions means greater conductivity. Specific conductance, itself, has no significance for health. However, it may be used to estimate the salinity, total solids and total dissolved solids in a body of water, which may have implications for domestic and agricultural use (Dojlido and Best 1993). 37 3.1.7 pH pH is important because it "is a determining factor in almost every natural process, a critical component of biologic systems" (Stednick 1991). pH is a measure of the hydrogen ion activity in water; some water molecules, H20, even in water containing few other ions, normally dissociate into H + and OH". The degree to which water molecules dissociate depends on the other ions in solution. The pH of natural waters is primarily established by the reaction of dissolved carbon dioxide with water, in which hydrogen ions and aqueous carbonate (H2C03) are the products. In natural waters, pH can range from 6.5 to 8.5. A value of over 9 may be reached during the daytime when vigorously photosynthesizing plants are actively removing carbon dioxide from the water (Hem 1985). The reaction of water molecules with carbon dioxide plays an important role in the buffering capacity of a water body. Buffering capacity refers to the amount the pH of water changes when an acid or base is added to the water; a water body is well buffered if the change in pH is only slight (Hem 1985). 3.1.8 Temperature Temperature controls many reactions affecting the chemical characteristics of water. As previously discussed, temperature determines the solubility of various gasses, such as oxygen and carbon dioxide, in water. As temperature increases, the oxygen requirement for fish increases due to increased metabolic rate; at the same time the dissolved oxygen saturation decreases (Chilibeck, et al. 1993). Streamwater temperatures between 12 and 14°C are optimum for young fish, while temperatures above 25°C are lethal (Chilibeck, et al. 1993). Streamwater temperature may be evidence of groundwater influence. "Gaining" streams, or those which receive a contribution to stream flow from groundwater, tend to have lower temperatures than "losing" streams which contribute to groundwater recharge (Kalkhoff 1993). 38 3.1.9 Micro-organisms A group of microbes, the coliforms, are used as indicator organisms. Coliforms are not necessarily pathogenic themselves, but because they are associated with the gut of warm-blooded animals, they indicate the presence of faecal material, either human or animal. Faecal coliforms, in particular, indicate recent faecal waste contamination and potential presence of pathogenic organisms (Stednick 1991). The number of faecal streptococci in the water gives further information regarding the source of the faecal contamination. The proportion of faecal coliforms is greater in humans than other warm-blooded animals, while the proportion of faecal streptococci is greater in non-human warm-blooded animals. The ratio of faecal coliforms to faecal streptococci can be calculated to determine the more likely source (Stednick 1991). If the ratio is greater than 4.0, then the source is likely human. A ratio of less than 0.7 signifies that the source is likely non-human. Ratios in between 0.7 and 4.0 indicate that the source is mixed and cannot be established with this method. These ratios are appropriate to use when the faecal streptococci count is >100 colonies/100 mL, and the pH is between 4.0 and 9.0 The highest microbial densities are often found in agricultural areas. This may be due to either animal faecal contamination or to naturally occurring bacteria attached to soil particles which are carried from agricultural fields in runoff (Stednick 1991). Bacterial densities range from 50/100 mL in wildlands to greater than 10,000/1OOmL, and typically increase during higher stream flow (Stednick 1991). 39 3.2 Methodology 3.2.1 Water sample collection Water samples were collected on eight different dates through 1994-1995: 2 March 1994, 9 May 1994, 29 June 1994, 26 July 1994, 24 August 1994, 3 October 1994, 24 November 1994, and 1 February 1995. Water for microbial analysis was collected on 26 July 1994, 24 August 1994 and 1 February 1995 only. Temperature, dissolved oxygen, conductivity, and pH were measured in situ. Table 3.2 shows the analyses performed for each sampling date. Streamwater was collected from eleven monitoring stations (Figure 3.1) in acid-washed polyethylene bottles. The samples were transported on ice, and stored over night in a laboratory refrigerator prior to chemical analysis. Water for microbial analysis was collected in separate glass bottles provided by EVS Environmental Consultants, the laboratory which did the analysis. Table 3.2 Matrix of water quality measurements made for each sampling date. Water quality indicator 2-03-94 9-05-94 29-06-94 26-07-94 24-08-94 3-10-94 24-11-94 1-02-95 Nitrate-N X X X X X X X X Ammonia-N X X X X X X X Ortho- X X X X X X X X phosphate Dissolved organic X X X X X X carbon Chloride X X X X X X X X Dissolved oxygen X X X X X X Specific X X X X X X X X conductance pH X X * X * X X * X X X Temperature X X X X X X X Microbes(FC+FS) X X X * pH measured in lab, not in situ 41 In situ measurements were made with the following instruments: pH and temperature: Hanna instruments HI 9025 microcomputer with HI 1230 probe (calibrated with pH 4.0 and 7.0 standards); specific conductance: Yellow Springs Instrument Co., Inc. Model 33; and, dissolved oxygen: Yellow Springs Instrument Co., Inc. Model 57 More intensive monitoring was done for three separate storm events: 20 October to 26 October, 1994; 29 October to 9 November, 1994; and 29 November to 30 November 1994. A l l storm samples were collected from Station 6, the location of an Environment Canada hydrometric gauge (station 08MH090), at several times during each storm. The height of the stream was also recorded from a fixed gauge at the site at the time the sample was taken. The samples were stored over night in a refrigerator prior to being transported to the laboratory for chemical analysis. Specific conductance and pH were measured in the laboratory. Detailed sampling of a section of Coghlan Creek, just upstream of its confluence with the Salmon River, was carried out in August 1994. Samples were collected from springs and seeps which drained into the stream channel. Results of the chemical analysis of water collected from springs and seepage sites along the creek are shown in Appendix 1. 3.2.2 Laboratory analysis The collected streamwater was analyzed on a LaChat X Y Z QuikChem A E autoanalyzer. Samples were filtered with 41 Whatman ashless filter paper prior to chemical analysis if the samples were turbid with silt or organic matter. Dissolved nitrate+nitrite-N was determined with the LaChat autoanalyzer using method number 12-107-04-1-B which was supplied by the manufacturer. Nitrate is reduced to nitrite as it passes through a copperized cadmium colum. The nitrite (consisting of both the originial 42 nitrite and the reduced nitrate) is then diazotized with sulfanamide and coupled with N-(l-naphthyl)ethylinediamine dihydrochloride. The resulting dye is read at 520 nm (LaChat Instruments 1989). Nitrate+nitrite-N is referred to as nitrate-N or N03-N for the remainder of this thesis. Dissolved ammonia was measured with the LaChat autoanalyzer using method 10-107-06- 2-D which was supplied by the manufacturer. Samples are digested in sulfuric acid and then a mecuric oxide catalyst is used ot the convert the sample to ammonium. The ammonium cation is converted to ammonia by raising the pH to a known, basic pH with a concentrated buffer. The ammonia is heated with salicylate and hypochlorite and the product is colorimetrically determined at 660 nm (LaChat Instruments 1989). Dissolved orthophosphate was determined with the LaChat autoanalyzer using method 12-115-01-1-A supplied by the manufacturer. The orthophosphate ion (P043~) reacts with ammonium molybdate and antimony potassium tartrate under acidic conditions and forms a complex. The complex is reduced with ascorbic acid and colorimetrically determined at 660 nm (LaChat Instruments 1989). Dissolved chloride was determined with the LaChat autoanalyzer using method 10-117-07- 1-A supplied by the manufacturer. The chloride is reacted with mercuric thiocyanate, rusulting in the displacement of thiocyanate. The free thiocyante that is produced reacts with aqueous iron(III) to produce hexacyanoferrate(III) which is read at 480 nm (LaChat Instruments 1989). Dissolved organic carbon was determine on a Shimadzu (TOC-500) Total Organic Carbon Analyzer. All of the water samples were filtered with 41 Whatman ashless filter paper and stored in a freezer prior to analysis. Total dissolved carbon and dissolved inorganic carbon are measured and the dissolved organic carbon calculated from the difference between the total 43 and inorganic components (K. Hall, pers. comm.). Quality control for the determination of water quality was performed in the laboratory. Reference standards, replicated samples and blanks are used for every set of samples. Accuracy is controlled for through the use of certified water references obtained from the U.S. National Bureau of Standards (H. Schreier, pers. comm.). pH was measured in the laboratory, with either the Orion pH metre Model 420A, or the Fisher Accumet pH metre model 810 for the May, July and August samples. Microbial analysis by EVS Environmental Consultants was done using the membrane filtration method with m-FC agar for the faecal coliform, and mEnterococcus agar for the faecal streptococci, using procedures described in "Standard methods for the Examination of Water and Wastewater", 18th ed. 1992, APHA. 3.2.3 Statistical analysis Descriptive statistics, mean, median and range, were calculated with the software package SPSS for Windows Release 6.1.2. A Spearman rank correlation was also calculated with SPSS to determine the relationship between water quality indicators. 33 Results and discussion The results of the field and laboratory analyses of streamwater nitrate-N, ammonia-N, orthophosphate, dissolved organic carbon, chloride, specific conductance, dissolved oxygen, pH, temperature and faecal coliforms and streptococci are presented in Appendices 2 through 13. The spatial and temporal variability in each of the water quality indicators is graphically illustrated by mean high and low flow values. Error bars indicate the range of values. The average daily discharge on the date of water sampling was used to determine which values were 44 included in the averages presented in the graphs. High flow data are represented by an average of the November, February and March values, while the low flow data are an average of the June, July and August measurements. 33.1 Spatial and temporal variation in nitrate-nitrogen Throughout the 1994-95 sampling season, nitrate-N values ranged from 0 to 6.76 mg L'1, with a median of 2.19 mg L"1. The highest value was measured in May at Station 5, on Coghlan Creek near where it joins the Salmon River. The lowest values were measured consistently at station 17, with the exception of November, at which time the lowest nitrate-N concentration occurred at Station 1. All values measured in the streamwater are below the Canadian Water Quality Guidelines for both drinking water and aquatic habitat. A similar spatial pattern occurred along both the mainstem Salmon River and in Coghlan Creek (Figure 3.2). The headwaters tended to have low nitrate-N levels. As both streams flow through the Hopington Aquifer towards the middle section of the watershed, the nitrate-N concentration increased. This increase was more pronounced in Coghlan Creek. The nitrate-N then decreased slowly from Station 6 to the mouth. Davidson Creek at Station 14 also tended to have elevated nitrate-N. Davidson Creek flows through the northern tip of the Hopington Aquifer. Groundwater discharge may be partly responsible for the relatively high concentration of ntirate-N measured at Station 14. There is also a marked seasonal trend in nitrate-N concentration. In most streams, nitrate-N values are higher in the winter months and lower in the summer months, and correspond to the level of biological uptake of nitrogen in the water. In the River Rhine, for example, summer concentrations are about half of those measured in the winter (Dojlido and Best 1993). In the Salmon River, however, the trends in nitrate-N concentration are reversed in 45 o 2 cF 2 E " c d) CO -I • to XJ C CD •= co E CO > S> o M la CD H CO CD J2 £ t= •E E z 2 £ w ro s c - i CD « O 1 < 2 CO XJ CO (D C ^ i: CO "CD CO >, (j) i 0) o > c w O D XJ co £ C 1 SJ o c co co ro c ® c •- 2* ro c 2 Z O CD O) -~ > O .5 co o co 2 co > co .® •j? CD -2 CO 3 ^ N £ CO > i= c o « to "5. E co CO 6LU) N-QiBJjm jaiBAAiueaJis CM CO CD O) 46 the middle of the watershed: peak values are measured in the summer, and lower values are measured in the winter (Figure 3.3). During summer months, the Salmon River and its tributaries are fed primarily by groundwater. The Hopington Aquifer is susceptible to nitrogen leaching from land activity; the groundwater concentration of nitrate-N is high in many areas of the aquifer. The amount of nitrate-N in the streamwater can, therefore, be directly attributed to groundwater contribution. In the winter months, when surface runoff is the main source of water in the stream, nitrate-N levels are lower and relatively uniform throughout the headwaters, middle and lower setions of the river. The concentration of nitrate-N has been measured at the same stations in 1974-75, and in 1991-93 (Figure 3.4). Nitrate-N values are very similar in both the Salmon River and Coghlan Creek headwaters. The primary differences occur in the middle of the watershed. At Station 7, the 1974-75 values are higher than either the 1991-93 or current values. This is most likely due to a slightly different sampling location in the 1970's study. Both the 1991-93 and current samples were collected above Union Creek, a tributary in which Cook (1994) measured high (~6 mg L"1) nitrate-N concentrations. The 1974-75 samples may have been taken downstream from the confluence of this tributary with the Salmon River. From station 6 downstream to the mouth, the 1991-93 values were higher than both the 1974-75 and current samples. In Coghlan and Davidson Creek, the 1991-93 values are also higher than the 1974-75 and 1994-95 values. These differences are the results of one or more of the following reasons: spatial and temporal variability of nitrate-N; differences in sampling intensity; variations of nitrogen inputs into the system; and, variability in precipitation and stream flow. In a comparison of data from the early 1970s and early 1990s, Cook (1994) found that there was no obvious temporal trend in nitrate-N values, with the exception of at Stations 5 and 14. Nitrate-N increased at both of these stations. There is no obvious temporal trend when the 1994-95 data is also considered. 47 CD 0 CD CO g> . CD [0 CO - I c > CD ? E £ CD 1 10 8 ° w c fl> ® fc I -2 o CO > o -D * CD O CO J -CD c CO k. CD 1c CD ? ° 1 CD ^ TJ > . C _ C i_ £ CD CO o E X) co ^ 2 W I UJ 5 8 ^ E i2 z S | CO < 3 ~ co C m <D CD " E | " » CO co Jj) 2 " « « C ~ CO .Q o 5 •1 8>;§ co ra LL > CD i-~ m > <» 2 CO - Q o c E CO (0 CD 820 CO CO CO CD l _ 3 BUI) N-9JBJHU JaiBMLUB8JJS 48 S2 CO . 1 £ 5 TJ CO © C C © CD E $ £ i— —j Q- Lo P (0 CD .52 E *£ CD T >. z 5 2 & CO T -l— •ti TJ C C i_ CO CD -CO CO > CO 1 g > CD O — -J ~ CO CO (0 OJ CO ~ OI CD co v E - _ CD E | § CD C t -~ CD CD E E £ t CD 2>3 5 CD TJ ° E c co CD l _ D O) L L s IO CO m cn cn r-o> cn o *~ t— *~ •4 • r-cn cn o> i— 1 < • T T CO CN ^ ( H 6w) N-91BJ1IU jaiBMUieaJis 49 However, the nitrate-N concentrations measured at Stations 5 and 14 continue to be a concern. The land activity in the watershed is dynamic and sources of nitrogen have changed. The increasing input of nitrogen from septic systems may be cancelling out the decrease in loading from other sources like agriculture (Keeney and DeLuca 1993). 3.3.2 Spatial and temporal variation in ammonia-nitrogen Overall, ammonia-N ranged from below detection limit to 1.44 mg L"1, with a median of 0.035 mg L"1. Values below detection limit were recorded during the summer, throughout the middle and lower sections of the river. The highest values were consistently recorded at station 17; the maximum value of 1.44 mg L"1 was recorded here in August. June was also high at this station. Seasonally, the pattern of ammonia-N generally follows the same trend observed in streams throughout the world (Figure 3.5). Concentrations are low in the summer because ammonia is being absorbed by plants, and because higher water temperatures favour nitrification (conversion of ammonia to nitrate). The bacteria which are reasponsible for this oxidation reaction function best at higher temperatures (Brady 1990). In the winter, concentrations are higher because lower water temperatures inhibit plant uptake and nitrification (Dojlido and Best 1993). The exceptions are at station 17, where the highest values occur in the summer, and at station 2, for which the June measurement is highest. Station 17 is near the headwaters of the Salmon River, and is adjacent to the Vancouver Zoological Centre, which houses a large number of exotic animals. During the summer, this station is typically stagnant; there is little or no movement of water, and a thick mat of algal growth. All the total ammonia-N concentrations were below the maximum permissible concentration for the protection of aquatic life. However, at Station 17 in August, the ammonia concentration was near the maximum acceptable average - 5 j s 5 « o > CD i 3 0) O O CD CD J . H z g XJ © XJ i : H -CO CO CO C - ° > CO ^ > E S CD 2 U J > c O CD I a CD C E <D E ~ E 15 3 £ CO cn =3 ^ 52 <f CO CD .E? E _ co r Z . o CO CO s ^ s 1 E § co co CD ® § 2 O CD CD 5? *-C CO CD CO CD -9 E co i § o5 I ra CD J= CO CO > CD c CD -= A, o E CD CO CO i— ijs 03 E > <!> CO eg 8 ECD _ ^ , co co co CO Li-CD 1 I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I ( O I - C M O C O l O i J - C N O ^ o o d o o 6w) N -BWOIUIUB jaiBMiueaJis 51 30-day concentration of total ammonia-N (1.65 mg L 1 at ph = 7.1 and temperature = 16°C). It is possible that ammonia concentrations exceed guidelines for the protection of aquatic life at times during the summer. 3.3.3 Spatial and temporal variation in orthophosphate Orthophosphate values ranged from below detection limit to 0.17 mg L 1 , with a median value of 0.038 mg L"1. The highest value occurred at station 17 in February. The lowest value occurred at station 2 in May. Seasonally, orthophosphate values are higher in the winter, and lower in the summer, similar to the temporal patterns expected for nitrate and ammonia (Figure 3.6). Orthophosphate is also absorbed by plants during the summer. In the winter, when plant productivity slows, less orthophosphate is removed from the water. Spatially, orthophosphate decreases from the headwaters to the middle of the watershed, and remains relatively constant through the aquifer area. In the winter, there is another sharp decrease between stations 2 and 1. 3.3.4 Spatial and temporal variation in dissolved organic carbon Dissolved organic carbon ranged from 1 to 110 mg L 1 . The highest value was recorded at station 14 in August. The lowest values were also measured in August, throughout the middle portion of the Salmon River. Dissolved organic and inorganic carbon may be highest in late summer and early fall, because this is the time when soil organic matter is being decomposed and may be carried into streams via runoff (Hem 1985). However, there does not really appear to be a trend in the Salmon River (Figure 3.7). Some of the highest values are actually measured early in the summer. This may be due to agricultural runoff of animal manure into the stream. 2 "JS CD £ & o 2* . -c 2 co •C CD c ° m <» ° c £ CO CO c 5 s 1 5 co g > CO C > CD fc 5 3 0 -= O CO -1 > & 0 > c — O CO CD 5= *~ £ r (D H g ) £ "d ^ -2 5 £ 8 co I- xj CD • <= •s to -- jo > CD CO l- E - ° 1 £ 15 ^ | L U r— CO O ® E E 2 CO CO CD CO 3 E CD §> <5 £ < a) c5 co <-Q . 3 O CO - i |s 0 - .2 r (D S 1 • I O JO ^ C ~ CO c o 2 o <i> -S ~ O) ,co CO CO LL 3 COCO CD E  > ro CD i-> CD ro .a c E CO CD S. £ S co ro z co co CD k. D) L L 53 ° * CD O CD GO C CO O CD ° J2 c CD E CD CD S TJ C CO CO XJ CD XZ to 3 to CO - CD 2 E CO - ~ £ 3 CD g > < a: XJ c CO CD UJ c o J= CO D co -> CD CD" c © o £ o tn c CD E 2 to CO CD E o aj | s ^ to XJ CD C XZ CO ~* 3 .2 s CD CO CD O CD c 2 CO CD CO > I " > 2 O CO 0 o CJ .55 co }= co 1 "S o ^ to o ro 52 CD *2 CO XJ cd CD i_ CO i_T o CD fc X) CD E CD ^- x: CD ~ x: to — CD o g col 2 -CD OOO > CO to 2 E CO © CO ZJ CD CO D CO — CD 5 1 8 ? 8 8 2 6lU) OOQ J91BMLUB8J1S 54 Spatially, DOC decreases from the headwaters, and remains relatively constant through the middle sections of both the Salmon mainstem and in Coghlan Creek. The higher low-flow value of dissolved organic carbon at Station 17 may be due to inputs from the Vancouver Zoological Centre. An exception in the Coghlan is for July, when dissolved organic carbon increased from the headwaters to downstream. 3.3.5 Spatial and temporal variation in chloride Overall, the concentration of chloride ranged from 3.6 to 31.6 mg L"1, with a median of 7.3 mg L"1. The highest value was measured at station 17 in August, and the lowest values in February at station 6. The higher values occurred during the summer months, when the groundwater influence is greatest, and also when the dilution effect is least (Figure 3.8). In the summer months, the chloride concentration is highest in the upper stream area, at station 17, and then decreases sharply to the next station. Chloride increases slightly through the aquifer area, and then increases more sharply where the river once again flows through glacial-marine sediments. In the winter, the chloride concentration is relatively constant from the headwaters to the middle section of the river, and then increases below the aquifer area. All measurements made in the 1994-1995 study season are well below the recommended drinking water criterion for chloride. Chloride can be a useful indicator of human waste (Canter and Knox 1985). In the Salmon River, however, the concentration of chloride in the streamwater is highly influence by several factors. Firstly, the presence of marine sediments up and downstream from the aquifer contribute chloride. Secondly, the highly mixed land use in the watershed results in several other sources related to land use activities. Animal wastes and inorganic fertilziers may also be significant chloride sources. CO CO 3 CO > CO o> CO CO > CO CO I c CO E c CO 0) $ 2 .3 E co co ^ CD $ £ 2 o f ^ « 5 5 r h ra O) g o » o O c £ CO I £ CO O « s *= CD I ^ | « 2 > 3 C i_ O) CD . > < CD a -o ^ c £ co o co to C ^ CD — — E ra 3 w -» -g CD CD" J= - C C J - D 2 •— ~ 5 "D CD CO C -g £ co 'jr *- > -P ° ra TJ c ra TJ CD JO tn C CO C a> CD L L ra E CD | ra * o c . © z ra o £ ,® Z £ CO O o c o ra > ( H Dill) 8pjJ0|U0 J8JBMLUB9JJS 00 CO CD i_ 3 D) 56 3.3.6 Spatial and temporal variation in dissolved oxygen The concentration of dissolved oxygen varied from 2.2 to 13.3 mg L"1. The highest values occurred in November in the middle section of the river; the lowest values occurred in the summer at station 17. Seasonally, dissolved oxygen is highest during the winter, when increased flows and lower water temperatures favour the dissolving of oxygen in water (Figure 3.9). In the summer, dissolved oxygen levels are lower due to higher water temperatures and increased biological activity. The percent saturation of oxygen was calculated from standard saturation concentration tables (APHA 1985). Figure 3.10 shows the calculated percent saturation of oxygen in the streamwater. While the concentration of oxygen appeared to be highest during the winter months, the percent saturation values were actually higher during the summer at four stations. All of the oxygen measurements were taken during the afternoon, the time at which photosynthectic activity was near its peak. The low-flow oxygen measurements at Stations 16 and 2 suggest that oxygen is super saturated as a result. The dissolved oxygen concentrations in the Salmon River during the daytime are generally acceptable at all times of year to support all life stages of aquatic organisms. However, nighttime concentrations were not measured. It is possible that dissolved oxygen decreased at night when plants are consuming oxygen rather than producing it. The optimum dissolved oxygen saturation for salmonids is greater than 90% (Chilibeck, et al. 1993), which is achieved at most stations in both winter and summer. The exception is station 17, at which dissolved oxygen was depressed to 2 mg L"1. During the summer months, this station is often stagnant; there is little or no water movement, and a thick mat of algae, stimulated by elevated input of nutrients from the Vancouver Zoological Centre consumes much of the oxygen in the water. This is of concern due to the presence of critical Salish Sucker habitat in the vicinity. 57 CP ~o cn CD co 8 « 5 S 5 | O S 3 CO CO CO CD M CO co 3 E o > CO I— © CD • D H 8 c CD CD {2 ro E co -e a) 1 2 I P 0 to c 1 O l | 1 0 3 Si co < 2 " I c * 8 •- > E £ ® 5 ° § J XJ —i XJ 5 a g O ~ >N CO *r £: (O O CO XJ CD 2 CO XI .E CO CD C CD .9 > v.--j- CO CD .ro c XJ « " I > 0) CD ro ro o c o CO ro CD CO CD CD 8*6 OJ CO CD l _ 3 CO 58 > O) c o r to V CD I- H T J CO ® C £ cl CD (j) £ ra 58 lo c => 0 °> 1 < 0 5 T J CO g CD CO C 3 Si 3 co ra .c w £ tr CO . ra © 5 °> ra x c o co "D A) 0> £ > ra o c CO CD .52 o) •° £ c o c "° .2 > ra o •c CO ra » > T J ra «s O CO co CD ro 3 ® ro CO > CD CD T J c CO i— ra n L _ o k_ I— L U _co c CD E CD k_ 3 CO ra CD E ra 3 k . .Q CD LL T J C ra k . CD E CD > O z CD O CD ra CD > ra c ra CO —^< c CD £ E ra © CO 3 CD CO 3 CO -= CD 5 E I I I I T I I I I I I (UOjlBJnjBS %) uaBAxo paA|ossip J8}BMLUB8J}S co CD k -3 O) L L 59 3.3.7 Spatial and temporal variation in specific conductance Specific conductance ranged from 41 to 230 //S/cm. The highest values were measured at station 17 and near the mouth of the Salmon River during the summer. The lowest values were observed during the winter, between the headwaters and middle section of the river. Spatially, specific conductance was relatively constant throughout the river in the winter (Figure 3.11). In the summer, values were high in the mainstem headwaters and decreased sharply to just upstream of the aquifer. Through the aquifer area, specific conductance increased and peaked again at the mouth. On the Coghlan, values increased from the headwaters to where the creek joins the Salmon mainstem. Specific conductance is a measure of the total ionic activity in the water (Hem 1985). The increase in specific conductance through the aquifer area may suggest increasing concentrations of dissolved solids in the streamwater. Orthophosphate and ammonia-N are relatively constant throught the aquifer area, however, both nitrate-N and chloride increase in concentration. 3.3.8 Spatial and temporal variation in pH In situ pH was not measured for the following sampling dates because of technical difficulties: May, June, Aug. For these dates, the pH was measured in the lab the following day and the values used in the calculation of the average low-flow pH level. pH ranged from 6.32 to 8.80. The lowest pH was measured at Station 1 in February, while the highest occurred at Station 14 in Davidson Creek during July. Seasonally, pH values were higher during the low-flow period (Figure 3.12). The pH of natural waters usually decreases with increasing temperature, which is opposite to the seasonal variation measured in the Salmon River. This is likely due to the influence of rainwater (Hem 1985). In the Lower o 60 CL co to (D O CO W W . CD CD "S £ £ 2 o o ^; > * * 0 .2) CD — f— M > to CD CD 1 I "CO < CO XJ cu £ £ ro c to CO o UJ «j c CD E 2 to CO CD E xz o ~ 2 (0 8 C CD CO c XJ CD C -C 8* o o CD CL CD O CD CO CO X> c CO CO -3 i_ Xi CD CO C c o > ca c CO _ 2 .ro co 5 8 _ c co ro c t3 O 3 « X J CO c CD o CO O CD Xi E CD > O CD J2 4 £ o E CD 2 CO to CO CD CD co E ( uio srl) aouepnpuoo oupads J 8 } B M U I B 8 J } S co CD l_ D CO L L CD CO sz 3 I— _Q o CD CD L L rag nd CD CO > 1— CD CD an mb CD ve CO X QL CD <•— O « t CO O CD CD 3 O) CO f° > t_ CD > o CO >*— c CO o CD CD CO CO CO c h - CD CD 3 E ~b CO £ CD > . c -flow CO ters -flow nea CO sz O) M— o Lc CD CD CD O) > x: c h - CO 1_ c Mj* CD o SI E C ' CD CD Sa em cat the sur c pH in st mea r bars i c 3 o ! uo!: Aug Em CO CO al vari uly, an ement on l_ 3 eas CD" c 3 leas CO - 3 t CN CO CD i_ 3 g> L L 61 62 Fraser Basin, rainwater has a pH ranging from 4.5 to 5.5 (Hall, et al. 1991). Spatial variability was related to the season. pH increased from neutral at Station 17 to greater than 8 at Station 16, in the Salmon mainstem. pH then decreased from Station 16 to the mouth. During the high-flow period, pH increased slightly from headwaters to aquifer area, and then decreased. In Coghlan Creek, the pH was consistent from headwaters to the confluence with the Salmon River, with low-flow values, 7.6-7.7, being greater than high-flow, 7.2. The high-flow and low-flow pH values, 6.7 and 8.3 respectively, were very different in Davidson Creek. The minimum allowable criterion for pH of drinking water and the protection of aquatic life was not met at Station 1 in February. The maximum allowable criterion for drinking water was exceeded in July at Stations 16 and 14. 3.3.9 Spatial and temporal variation in temperature Temperature varied from 4 and 5°C at all stations in November to 25°C at Station 1 in July, following several days of maximum air temperature of 30°C. During the months of November and February, the water temperature stayed constant between stations (Figure 3.13). In the summer months of June, July and August, the water temperature decreased as the stream flowed through the Hopington Aquifer area. The temperature then increased sharply toward the mouth of the Salmon River. The variability in temperature is governed by canopy cover over the stream, and to a greater extent, groundwater discharge into the stream. The decrease in low-flow temperature in Coghlan Creek through the Hopington Aquifer was greater for all sampling dates than it was for the portion of the Salmon River mainstem through the aquifer. This may reflect a larger relative groundwater contribution to Coghlan Creek than to the Salmon mainstem. 64 Water temperatures are sufficiently low during the winter for fish. The solubility of oxygen in water is governed by temperature. At temperatures below 20°C, there is adequate dissolved oxygen to support salmonids (Chilibeck, et al. 1993). In the summer, however, the temperature often approaches 25°C the temperature above which there is insufficient dissolved oxygen. Stations located in the Hopington Aquifer area remained below 20° C; the groundwater contribution to the stream during the summer not only maintains stream flow, but provides the cool water necessary for fish viability. 3.3.10 Spatial and temporal variation in faecal coliforms and faecal streptococci Faecal coliform and streptococci counts varied considerably between each of the three sample dates. Figure 3.14 shows the measurements made in July, August and February. In July, both faecal coliforms and streptococci were consistently below 200/100 mL with the exception of station 16. This station is adjacent to Trinity Western University, which until July, 1994, discharged their waste water into the Salmon River. The ratio of coliforms to streptococci is 3.8 (Figure 3.14B), which indicates that the source of these microbes is likely of human origin. In August, the highest counts were taken from station 17, and while the ratio is between 0.7 an d 4.0, the origin is likely animal; this station is adjacent to the Vancouver Zoological Centre (Figure 3.14 C and D). The ratio of coliforms to streptococci at station 4 indicate that animals are the likely source. The counts are much higher in February (Figure 3.14 E), which was expected, because microbe counts generally increase with increasing stream discharge (Stednick 1991). The ratios for stations upstream from station 6 (Figure 3.14 F) indicate that the microbes are mainly of animal origin, which is reasonable since there is greater runoff from agricultural fields during the rainy season. 65 Figure 3.14 Seasonal variation in faecal coliform and faecal streptococci counts in the Salmon River Watershed. The left graphs show colonies per 100 mL and the right graphs show the FC/FS ratio. 1000 _J E -o o —^ 800 -per 600 -W CO -' c o 400 -Col 200 -August Faecal coliforms Faecal streptococci FC/FS ratio 17 9 7 4 6 16 2 1 19 5 14 H 1 h - \ 1 1 1 H 17 9 7 4 6 16 2 1 19 5 14 17 9 7 4 6 16 2 1 19 5 24 H 1 1 H H 1 H H 1 H 17 9 7 4 6 16 2 1 19 5 14 O V* „ to 4 s 8 3 O 3 Q . 8> CD ^ 1 | 8 ° 8 0) CO LL 4 H h- -i 1 h H h H 1 h 17 9 7 4 6 16 2 1 19 5 14 34 —I 1 1 1 1 1 1 h 17 9 7 4 6 16 2 1 H 1 1 h 19 5 14 Sampling station 66 3.4 Relationship between water quality indicators A Spearman Rank Correlation analysis was used to analyze the relationship between selected water quality indicators measured in this study (Table 3.3). The null hypothesis was that there is no relationship between the water quality indicators. A one-tailed test was used because there was an a priori assumption that there is, in fact, a relationship between the indicators. Table 3.3 Spearman Rank Correlation coefficients for selected water quality indicators for the Salmon River Watershed. Ammonia-N n=70 Ortho-phosphate n=80 Nitrate-N n=80 Chloride n=81 Dissolved organic carbon n=65 Specific conductance n=81 pH n=49 Ammonia-N 1 Ortho-phosphate 0.606** 1 Nitrate-N -0.400** -0.171 1 Chloride 0.001 -0.051 0.271* 1 Dissolved organic carbon 0.365** 0.056 -0.103 0.055 1 Specific conductance -0.412** -0.561** 0.355** 0.102 0.102 1 PH -0.730** -0.608** 0.325** 0.225 0.209 0.690** 1 * significant correlation at a=0.05, for one-tailed test ** significant correlation at cx=0.01, for one-tailed test There are two general groups of significant relationships, which are linked to the seasonal behavior of the various water quality indicators. Indicators pairs in which both are higher or lower during the same flow regime (high or low) are positively correlated. For example, conductivity is positively correlated with nitrate-N at a significance level of a=0.01. 67 The highest values of both are typically measured during the low-flow period, when the groundwater contribution to streamflow is also highest. Ammonia-N and orthophosphate are also positively correlated at a significance level of cx=0.01. Conversely to the nitrate-N/conductivity indicator pair, ammonia-N and orthophosphate are typically highest during the high-flow period, when precipitation and surface runoff are greatest. The second general group is that of negative correlations. Indicators such as ammonia-N and orthophosphate are negatively correlated with nitrate-N and specific conductance, which is directly related to their peaking in different seasons. 3.5 Storm monitoring Streamwater was collected throughout three separate storm events at the beginning of the winter rainy season (Appendix 15). When plotted against stream height, ammonia-N and orthophosphate concentrations appear to be correlated to stream flow (Figure 3.15). Stream gauge height was used as a measure of discharge because the discharge data shown in Figure 2.5 was reported as the average daily discharge and did not reflect the actual flow at the time the water samples were collected. During storm two, there was a sharp rise in stream height over a twenty-four hour period and both ammonia-N and orthophosphate concentrations increased. Ammonia-N levels tended to be higher than those of orthophosphate at higher gauge heights. A Spearman Rank Correlation was used to further analyze the relationship between water quality indicators (Table 3.4). The null hypothesis was that there is no relationship between water quality indicators and stream discharge. A one-tailed test was used because there was an a priori assumption that the water quality indicators and stream discharge are related. As the correlation coefficients show, both ammonia-N and orthophosphate are positively correlated to stream discharge, while nitrate-N and chloride concentrations were negatively correlated. 68 co •4—* 'co CD C D ZJ CO C O o CD E o k_ T 3 CO c g 'to CO CO CD CO J Z C L co o S-"° O CD t CO ° CD CO ^ Z CD CO > c ir o E E co c o E k. 0 5 CD CO 1 1 E c S <2 CO CO > CO c o CO E o _ CO CO co > CO § . i E I ,CD =J LO CO CD L_ 3 CO ( 1 6ui) 8iBL)dsoqdoujjo JO ( -| BLU) N-BIUOUIWV l o o i n o i o o i n o m o • ^ ^ m c o c M C M i - i - o q 0 0 0 0 0 0 0 0 0 0 V ".!.!!.!<4...L 00:i2t>6/0e/U 1 " * " m.:::.:::.:.::. 00:01^ 6/06/11 1 <* ' " • 00:22*6/62/11 00:11^ 6/62/11 HI 3 1 1 m * E B i E m m H U M mm E S S H 1 00: LL t-6/6/W 00: LI *6/8/U 00:01 t&l/ll 00:6*6/9/U 0e:e2*6/e/U 00:8*6/l/U 00:Zl*6/Le/0l 00:8*6/ie/0L 00:L*6/ie/0L 00: *6/62/0L 00:/L *6/92/0L 00: H *6/92/0l 00:£2*6/22AH 00:8*6/12/01 00: G2 *6/02/0l 00:Z 1*6/02/01 00:6*6/02/01 CM O CO CO CM O .-' d d d o' o (ill) iqBlSLl LUB8JJS 0 E T J C co 0 15 T J O J c Q. E co CO 69 Ammonia-N and orthophosphate are typically delivered to the stream via overland runoff, and large inputs occur during the first few storms of the wet season. Nitrate-N and chloride behave in an opposite way because the groundwater contribution that supplies these contaminants is diluted with the increased flow from higher precipitation. Conductivity is negatively correlated with stream discharge and ammonia-N and orthophosphate because the increased flow is diluting the overall concentration of ions in the water. Table 3.4 Spearman Rank Correlation coefficients showing the relationship between water quality indicators during a storm event at Station 6 (hydrometric gauge site) in the Salmon River Watershed. Dissolved Specific Ammonia- Ortho- Nitrate- organic Conduc- Gauge N phosphate N Chloride carbon tance pH height n=21 n=21 n=21 n=21 n=17 n=21 n=21 n=21 Ammonia-N 1.000 Ortho-phosphate 0.709** 1.000 Nitrate-N -0.726** -0.823** 1.000 Chloride -0.658** -0.677** 0.693** 1.000 Dissolved organic carbon -0.288 0.493 -0.712** -0.386 1.000 Specific Conduc-tance -0.773** -0.774** 0.872** 0.902** -0.597** 1.000 pH -0.184 -0.522** 0.252 0.078 -0.413 0.074 1.000 Gauge height 0.804** 0.797** -0.838** -0.719** 0.457* -0.875** 0.053 1.000 significant correlation at a= 0.05, for one-tailed test significant correlation at a= 0.01, for one-tailed test To further illustrate the relationship between discharge and water quality, nitrate-N, ammonia-N and orthophosphate measured at Station 6 (location of the hydrometric station) were 70 plotted against average daily discharge (Figure 3.16). Both regular and storm data were used so the behavior of the indicators could be observed over a wider range of flow levels. All three water quality indicators were strongly correlated with stream discharge. As the previous analyses showed, ammonia-N and orthophosphate were positively correlated with stream discharge while nitrate-N was negatively correlated. The greater variability of ammonia-N and orthophosphate at higher flows is due to multiple samples collected on the same day during storm events. Discharge for the same sampling dates were reported as average daily discharge and therefore did not reflect the actual discharge at time of water sample collection. 71 Figure 3.16 Relationship between three water quality indicators, ammonia-N, orthophosphate, and nitrate-N, and stream discharge at Station 6 (hydrometric gauge site) in the Salmon River Watershed. (** indicates a significant Spearman Rank Correlation at alpha=0.01) 4. Land use From the time of European settlement, agriculture has been an important land use in the Salmon River Watershed (Waite 1977, Crawford 1993). More recently, large-scale commercial agricultural operations have moved eastward, rural residential areas have expanded and the number of small estates or hobby farms have increased (Corporation of the Township of Langley 1993). In order to measure the current land use in the watershed, and to quantify the changes that have occurred in recent years, information from a number of sources has been collected and compared: 1. A series of digital land use maps, which show the spatial distribution of the various land uses for 1980,1989, and 1994; 2. A septic system database compiled from health permit and building records; 3. Agricultural census data for 1986 and 1991, which provides more specific information about the intensity of land use; and, 4. An agricultural waste management survey of some of the larger farms in the watershed, and a "windshield" survey of horse locations. 4.1 Land use maps 4.1.1 Methods 1979-1980 The earliest land use map used in this study was based on Agricultural Land Reserve and Ministry of Agriculture land use maps (DeLeeuw and Stuart 1981, cited in Watts 1992). Watts (1992) verified and corrected the land use map using aerial photographs, and completed some gaps left by DeLeeuw and Stuart. Land use for this map was categorized into eight general 73 classes: agriculture, no perceived use, commercial/industrial, residential, extraction, recreation, transportation/communication and institutional. The land use maps consist of activities only, as a land cover map was not generated. 1989 Sawicki and Runka (1990) used 1984 aerial photographs and extensive field checking to generate the 1989 land use map of the Salmon River Watershed. The classification system used is much more detailed than the categories used for the 1979-1980 map (Sawicki and Runka 1986). This system uses a series of activity and cover classes to describe some 180 different land uses. The headwaters area of the Salmon River, in rural City of Abbotsford, and a small section in the northwest portion of the watershed were not covered by Sawicki and Runka. 1992 aerial photographs were used to delineate polygons and assign land activity and cover codes for these areas. 1994 A combination of aerial photographs and field checking was used to update the 1989 land use map first generated by Sawicki and Runka. 1992 aerial photographs were used initially to determine where changes had occurred. The photo interpretation was verified through extensive field checking. Changes were marked on paper copies of the 1:10,000 1989 map, and coded according to the British Columbia land use classification system (Sawicki and Runka 1986). All three land use maps were digitized, using the 1:20,000 TRIM (Terrain Resource Inventory Mapping) digital topographic map as a base. TerraSoft was the GIS program used for digitizing and overlays. For the purposes of comparison, the 1989 and 1994 maps were generalized into the same eight categories used in the 1979-1980 map. Table 4.1 summarizes 74 the categories and the land uses included in each. Finally, a GIS raster overlay with contributing areas was done so that spatial distributions of land activity may also be analyzed. The contributing areas were delineated by Cook (1994) on the basis of topography (Figure 4.1). Table 4.1 General categories of land uses, summarized based on B.C. Land Use Classification (Sawicki and Runka 1986). Category Land uses included: Agriculture No perceived use Commercial/Industrial Residential Extraction Recreation Transportation/Communication Institutional used for providing for the growing, producing and harvesting of agricultural products, including mushrooms and nurseries and the housing of animals and birds. land for which no use was designated, includes forested areas and idle land. used for the manufacture, transportation and selling of goods and services. used for the accommodation of persons in single and multiple family dwellings. used for the extraction, grading, crushing, screening and storage of sand, gravel, minerals and peat. used for outdoor recreation and open space including golf courses, parks and fishing and hunting areas. transportation and communication corridors used for providing government functions and services, including schools, hospitals, prisons and community centres. 4.1.2 Land use dynamics The current land activity in the Salmon River Watershed is depicted in Figure 4.2. A large proportion of the watershed remains agricultural and open space. Within the agricultural sector, land activities encompass crop production to greenhouses, and poultry to livestock operations. Residential areas range from being sparsely populated "estates" to dense urban communities such as Fort Langley and the Salmon River Uplands, also known as the Hopington 75 76 77 Aquifer area. In the Hopington Aquifer the residential areas are interspersed with fragments of agricultural and forested land. The dominant agricultural activity in this area appears to be small estate or hobby farms. Horses, in particular, are a common sight in many backyards. As recent as fifteen years ago, the watershed was much less residential in nature, and more agricultural. Figure 4.3 shows the overall change in land use type for the entire watershed. The most notable change was the decrease in the area of land used for agricultural purposes and an increase in residential area, from 1980 to 1989. Agricultural land decreased by about 800 ha. Former agricultural land was converted to such uses as residential, recreational and idle land. Residential land increased by about 600 ha. There has also been a significant, though smaller, increase in the amount of recreational land. The comparison of land use types between the different years yields more interesting results when based on the contributing area. As Figure 4.4A shows, agriculture has decreased in almost all of the contributing areas, but not by the same amount. The most significant changes have occurred in the middle of the watershed and near the mouth of the Salmon River. The headwaters of the Salmon River mainstem, Coghlan Creek and Davidson Creek have experienced the least changes in agriculture. Some contributing areas, for example S01, C04 and D02, appear to have increased in agricultural land. This most likely reflects the conversion of idle or forested land into crop or livestock production. All contributing areas show an increase in the amount of residential area (Figure 4.4B). The most significant increases have been in the middle of the watershed in the same contributing areas in which the agricultural land has decreased, S07 in particular. The increases have occurred mostly between 1980 and 1989. There are two contributing areas in which residential area appears to have decreased. This is most likely due to difference in interpretation of the land use. Area that was classified as residential in 1989 has probably been classified as agricultural in 78 Figure 4.3 The area of land use activities in the Salmon River Watershed for 1980 (Watts 1992), 1989 (Watts 1992) and 1994. B Year 79 80 1994. This was due to hobby farm activity, which often occurs in the backyards of rural residential areas. 4.2 Septic system database 4.2.1 Database construction Cook (1994) initiated the construction of a septic system database for the Salmon River Watershed. She retrieved records for about half of the septic systems in the watershed based on information provided by the Central Fraser Valley Health Unit (CFVHU). Information regarding address (including legal lot and plan numbers), date of final permit issue, volume of the septic tank and length of lateral fields, was transcribed and then entered into the computer database. The location of each septic system was first marked on the 1:4000 Address/Roll Legal Maps, and then digitized onto the GIS base map. In 1994, the Township of Langley (ToL) gave permission for the retrieval of information regarding the remaining septic systems from their building permit records, which are stored in a microfiche library. The street name and number of all properties for which there were no CFVHU records were compiled from the Address/Roll Legal Maps and looked up in the ToL building records, which are filed according to address. Date of final inspection, tank size and the length of laterals (tile field) were transcribed from the microfiche and entered into the computer database. The locations of these septic systems were marked on the 1:4000 Address/Roll maps, and then digitized onto the GIS map. The building records did not contain information for about 100 properties which do have addresses and therefore likely do have buildings and septic systems. The headwaters of the Salmon River are outside of the Township of Langley, and access to building permit records was not available. The City of Abbotsford services only a small 81 portion of the Salmon River headwaters with sanitary mains (A. Tsou, pers. comm.). City of Abbotsford Master Legal maps were used to estimate the number of properties in the watershed; it was assumed that all properties outside of the sewered area had on-site septic systems. Information regarding year of installation, size of tank and lateral fields was not obtained. The septic systems were analyzed by GIS vector overlay with the contributing area theme and with surficial geology. 4.2.2 Distribution of septic systems Overall, the CFVHU and Township of Langley building records indicate that 3147 septic systems have been installed in the Salmon River watershed from the 1930s to early 1994 (Figure 4.5) . In the Abbotsford portion of the watershed there are another 93 septic systems, for which installation records have not been accessed. There are 497 septic systems outside of the watershed, on the Hopington Aquifer. The majority of the septic systems are concentrated in Fort Langley and the Salmon River uplands, the primary urban centres in the watershed (Figure 4.6) . There are also other, smaller, concentrations of septic systems. Table 4.2 shows the number of septic systems installed per decade, both in the watershed, and outside of the watershed but on the Hopington Aquifer. The most vigorous septic system installation occurred in the 1970s, peaking just prior to the establishment of the Agricultural Land Reserve. The 1991 Population Census reports that there are an average of 3.3 people per household in the Salmon River Watershed (Statistics Canada 1991c). Therefore, assuming that each septic system represents one household, about 10,000 people live in the watershed. This is probably an underestimate of the actual population, however, given that the septic system database does not contain 100% of the records, and that the actual density of people per household varies throughout the watershed from 3 to 3.8. When the census data is fitted to the 83 CD CO l_ Zf CD LL 84 watershed, the population is closer to 13,000. Table 4.2 Number of septic systems installed in the Salmon River Watershed and Hopington Aquifer area, separated into decade of installation. Number of seotic svstems Decade of installation In watershed Over aquifer5 pre 1950 12 6 1950-1959 88 26 1960-1969 424 84 1970-1979 1507 268 1980-1989 891 95 1990 + 159 18 Total 3147t 497 f includes the 93 septic systems in Abbotsford for which there were no records added to the GIS database. 5 these septic systems are not in the watershed but are on the Hopington Aquifer which is hydrologically linked to the Salmon River. Canter and Knox (1985) have defined a density scale for septic systems, with a low, medium and high range based on pollution potential (Table 4.3). Overall, the density of septic systems in the Salmon River Watershed is 0.38 septic system per hectare, which is about double Canter and Knox's high density. For some areas, such as over the Hopington Aquifer, the actual density is much higher, reaching greater than 1.6 septic systems per hectare. In other areas, the density is much lower; contributing area S03 has a density of 0.04 septic systems per hectare. 85 Table 4.3 Ranges for septic system density, based on pollution potential (from Canter and Knox 1985). Density Range Low less than 0.038/ha Medium 0.038 to 0.15/ha High greater than 0.15/ha 4.3 Agricultural Census The land use maps described in Section 4.1 are useful in showing the spatial distribution of agricultural activities. They do not, however, provide information about the intensity of activity. More detailed information about land use in the Salmon River Watershed can be found in the Agricultural Census data. Statistics Canada undertakes a census of farm operators who produce for sale one or more crops, livestock, poultry, or products from greenhouses, mushroom houses and sod farms. While boundaries do not conform to the watershed boundary very well, conclusions regarding intensity of agricultural land use and dynamics can be made. 4.3.1 Data collection and analysis Data from the 1991 and 1986 Agriculture Census were collected for animal types and numbers, crop types and areas, and selected management practices. The data is grouped for given geographical units, usually for an enumeration area, which is the smallest unit for which census data is available. In rural areas, an enumeration area contains a minimum of 125 dwellings (Statistics Canada 1991b). In order to protect the privacy of individual farm operators and still provide the data at a reasonably small scale, Statistics Canada clustered some enumeration areas in the Salmon River Watershed into larger geographical units (Appendix 16). In some cases, most notably with pig farms, some data was suppressed; for enumeration areas 86 with fewer than two farms, the number of animals, or hectares of crops was not given. The census boundaries were digitized using the 1:20,000 TRIM as a base, from map sheets provided with the data. Because these maps are not intended to provide precise location of boundaries, the census boundaries were digitized for display purposes only. Figure 4.7 shows the boundaries of the enumeration areas or clustered enumeration areas which are wholly or partly within the Salmon River watershed. Through the remainder of this document, the individual and clustered enumeration areas will be referred to as census areas. The census data was analyzed to determine stocking densities and the change in agricultural intensities from 1986 to 1991. 4.3.2 Agricultural intensity and dynamics One measure of land use intensity is animal stocking density, which is the ratio of animal units to farm area. The animal unit equivalents used in this study are based on the nitrogen pollution potential from the manure produced (Table 4.4). In some cases, an average animal unit equivalent was used because the type and age of the animals was not known. For example, the number of poultry for each enumeration area is given; however, what is not known is if they are laying or broiler chickens, turkeys or pullets. Therefore, an average value of 475 chickens per animal unit, and 9.5 pig per animal unit were used for the general census data. Table 4.5 shows the overall number of animal unit equivalents for census areas partly or wholly in the Salmon River Watershed for both the 1986 and 1991 census years. Between 1986 and 1991, the number of farms increased and farm area decreased. While the total number of animal units decreased by 264, some animal types actually increased in number and overall stocking density did not decrease significantly. The decrease in pig numbers is not conclusive due to the suppression of data by Statistics Canada. Six of the fourteen census units in the 87 88 Salmon River Watershed have only one or two farms reporting pigs in 1991, and therefore, the number of pigs is not given. The stocking density of 1.50 is likely an underestimate due to the suppression of pig numbers. Cattle and poultry decreased in number, and horses and sheep increased in number. Table 4.4 Animal Unit Equivalents used to determine stocking density (Ontario Ministry of Agriculture and Food 1976). Annual Basis Market Basis 1 cow (plus calf) 15 hogs 1 horse 1000 broiler chickens 4 sheep (plus lambs) 300 turkeys 4 sows (plus litter) 125 laying hens Table 4.5 Total animals numbers for 1986 and 1991, and calculated animal units and stocking density. 1986 1991 Change Number of farms 556 654 98 Total farm area 6454 6362 -92 Total Animal Unit Equivalents 9793 9529 -264 Total stocking density 1.52 1.50 -0.02 Number of cattle 5946 5318 -628 Number of sheep 1590 1620 30 Number of pigs 4986 4177 -809 Number of horses 1036 1538 502 Number of poultry 814 637 788 610 -26 027 89 Animal stocking density is commonly regulated in European countries in an attempt to ensure that the assimilative capacity of farm land is not exceeded. Values for stocking density range from country to country and often depend on the animal type. For example, two Lander in West Germany limit animal units to 4.5 per hectare, and in Denmark, dairy operations are restricted to 2.3 animal units per hectare, and hog operations to 1.7 animal units per hectare, where one animal unit is equivalent to 1 cow, 10 pigs or 100 poultry (Anderson, et al. 1990). For the purposes of this study, a value of 2.5 animal units per hectare will be used to evaluate the pollution potential of livestock and poultry operations in the Salmon River Watershed. This is a conservative value which corresponds to regulations in countries with similar climatic conditions, and yet is not unreasonably restrictive. For the overall watershed, the animal stocking density is 1.5, which is well below any critical level. However, as Figure 4.8 shows, at the census area level, stocking densities range from 0.49 to 2.53. One census unit is above the 2.5 critical limit, and three are between 2.0 and 2.5. The overall change does not necessarily represent the dynamics in the individual census areas. For example, even though the overall animal unit equivalents has declined, the number of animals in several census areas has increased (Figure 4.9). The total animal unit equivalents also disguise the dynamics of different animal types. Only cows and poultry decreased in numbers. There has actually been a significant increase in the numbers of horses. Sheep numbers changed only slightly. Enumeration areas which showed an increase in stocking density also tended to show an accompanying increase in horse units. 4.3.3 North Langley study area A recent study on fertilizer use has summarized agricultural land use for an area approximating the area of the Salmon River Watershed. Brisbin (1995) collected Statistics CO 3 C L = S CL C C 3 © - = C D CO o §. ~ c c= CO *fc » ° CM CO o CD CD 0) x: c o E JS co C° n i CO CO cn co © =1 o CO CD to 5 c o "D © x: ccl I © £ 1 CD CO > CO v. C CD © > "CJ C D C 1^  o 2 co C O C O T3 » « = © O CO £ 5 0 C O C O CO ^ © C O C O S — "£< •co i f B 2 D © •— o C D o co j= co C ( D C O < x: Q 00 CD i _ ZJ C D > < co CM cn oo co 10 c O CD i o 00 CM ( L . B H nv) Mjsuap 6U|>|OOJS 92 Canada data for what he calls the North Langley waste management zone (Figure 4.10). He has partitioned the data for this area into small and large farms (Table 4.6). The "size" of the farm was determined by the gross receipts; a large farm earns >$40,000 in annual gross receipts, and a small farm <$40,000. He further subdivided the large farms into livestock and non-livestock farms, on the basis of the number and kind of animals they have (Table 4.7). Table 4.6 Agricultural Census data showing animal numbers in the North Langley study area, partitioned into small and large farms (based on Brisbin 1994a). Total Small Large Total number of farms 557 426 131 Total farm area 6136 3329 2806 Animals Cattle - farms 238 197 41 Cattle - number 5733 2279 3454 Poultry - farms 144 119 25 Poultry - number 523 000 61 000 462 000 Pigs - farms 34 24 10 Pigs - number 4436 183 4253 Sheep - farms 82 72 10 Sheep - number 1471 1237 234 Horses - farms 199 161 38 Horses - numbers 1443 915 528 The data for the North Langley waste management zone shows that overall, about 75% of the farms are "small". The distribution of animals on large versus small farms varies depending on animal type. Cattle are almost equally distributed between large and small farms, while poultry and pigs are predominantly on large farms. Sheep and horses are mostly found on 93 94 small farms. A stocking density calculation shows that small farms have 1.1 animal units per hectare, while large farms have 1.95 animal units per hectare. Overall, the North Langley study area has a stocking density of 1.49, which is analogous to the stocking density of 1.5 calculated the smaller census area over the Salmon River Watershed. These data reflect the prominence of small estate or hobby farms in this urban-rural fringe area. The change in animal numbers from 1986 to 1991 show that there has been a trend in increasing numbers of farms with fewer numbers of animals, particularly evident with horses and sheep. Table 4.7 Criteria for large livestock farm (based on Brisbin 1994b) Animal type minimum number of animals total hens and chickens 150 or more turkeys 150 or more total cattle and calves 6 or more total sheep and lambs 10 or more total pigs 10 or more total horses and ponies 6 or more 4.4 Agricultural Waste Management Survey In 1994, an agricultural waste management survey was conducted in the Salmon River Watershed and Hopington Aquifer area, under contract to the provincial Ministry of Environment and federal Environment Canada. The purpose of the survey was to collect data that indicated the number of animals on individual farms in the watershed, and what kind of waste management practices farmers follow. 95 4.4.1 Methods Respondents were selected from membership lists of marketing boards representing various commodity groups (Appendix 17). They were first contacted via a letter written on Ministry of Environment letterhead, and then telephoned in order to make an appointment, during which time an on-site interview could be done. The interview consisted of a questionnaire completed by the interviewer (Appendix 18). Horse farm operators were interviewed over the telephone and asked an abridged set of questions (Appendix 19). The data were coded and entered into a relational database (Appendix 20). The farm locations were digitized into the GIS database, using 1:4000 Township of Langley Master Legal map sheets on which the farm boundaries had been drawn and following land use lines on the digital map. All farmers contacted by letter were included in the GIS database, even if they were not interviewed. Figure 4.11 shows the locations of the survey farms. The data were used to determine the stocking densities on individual farms, and were combined with the agricultural census data to determine stocking densities for the contributing areas (Section 4.4.3). The survey data were also used in the calculation of a nitrogen mass balance (Section 6.3). 4.4.2 Survey analysis Of the 127 farm operators which were sent letters, a total of 86 participated in the survey. This number represents between an estimated 50 and 75% of large farms in the Salmon River Watershed. Sixty-five operators reported having animals; of these sixty-one were livestock or poultry farms. Stocking densities were calculated for the livestock farms. Figures 4.12 A to F show the results, grouped into six basic commodity groups: broiler chicken, laying chicken, turkey, dairy, horse and sheep operations. 96 97 Figure 4.12 Animal unit densities for individual livestock farms in the Salmon River Watershed. A Broiler chickens B Laying chickens 17 19 21 22 23 24 25 26 36 42 43 44 45 C Turkeys D Dairy cows Individual farm Individual farm 98 The poultry operations tended to have large numbers of animal units per farm area, with stocking densities considerably above the 2.5 criterion outlined in Section 4.3.2. These numbers should not cause undo alarm, however. All of the poultry farms reported that between 65 and 100% of the manure produced was exported from the immediate farm area. For dairy operations, only one of seven farms had a stocking density greater than 2.5. About 70% of horse farms and 40% of sheep farms have stocking densities greater than 2.5. Only four of the fifteen horse farms with more than 2.5 animal units per hectare export manure. None of the sheep farms export their manure. These results may be cause for concern. The Agriculture Census data shows that both the horse and sheep sectors are growing, most likely on both commercial and hobby farms. 4.43 Watershed stocking density The data collected in the waste management survey described above only represent a fraction of the large farms in the watershed, and an even smaller proportion of all of the farms in the watershed. In order to calculate the stocking density for each contributing area, and for the watershed as a whole, a combination of the survey and agricultural census data were used. The survey data was subtracted from the census data for the census area in which it was located. The remaining census data was applied evenly to the census area, and then a proportion taken for the contributing area which overlapped it. Animal units were calculated on the basis of the equivalents shown in Table 4.4. The stocking density was determined in two ways: firstly, on the basis of the agricultural land area calculated from the survey and census information; and secondly, on the basis of the agricultural land area derived by a GIS raster overlay of contributing areas on the 1994 land use map. Figure 4.13 shows the two sets of stocking densities by contributing area. When the land area derived 99 from the surveys and census data is used to determine the stocking density, one contributing area had an animal unit density of greater than 2.5 A U ha"1 (Figure 4.13A). The contributing area, SOI, is in the headwaters area of the Salmon River. Two other contributing areas, S07 and C02, had densities of between 2.0 and 2.5 A U ha"1. The remainder varied from 0.4 to 2.0 A U ha"1. Figure 4.13B shows stocking densities calculated on the basis of agricultural land area determined by GIS overlay of the 1994 land use map. A contributing area in the Coghlan headwaters, C02, has the greatest stocking density in the entire watershed, 4.7 A U ha"1. Three other contributing areas also have densities of greater than 2.5 A U ha"1. These CAs, S06, S07, and S08 are all in the Hopington Aquifer area. The animal unit density in the remaining contributing areas range from 0.4 to 2.3 A U ha'1. The actual stocking densities in the watershed are likely somewhere between the two calculations presented here. The census area calculation shows that the highest stocking densities occur near the headwaters of both the Salmon River and Coghlan Creek, and that other higher density areas exist in the Hopington Aquifer region. 4.5 Survey of horse locations The horse industry in the Township of Langley has grown rapidly during the past decade (The Corporation of the Township of Langley 1993). According to a 1990 industry profile conducted by the Ministry of Agriculture, Fisheries and Food, Langley is the "horse capital of British Columbia", with a total of 6,500 horses housed throughout the township (The Corporation of the Township of Langley 1994a). Of these horses, about forty percent are on large farms. The remainder are on smaller, hobby farms. During the 1994 land use map update, a survey of horse locations was also completed. The purpose of the survey was to determine the spatial distribution of horses in the watershed by creating a georeferenced database of horse locations. Horse locations were determined through 100 co co co <z co E 2 £ Zl co .9 co CO CO CO _ co 2 SZ ZJ +-> cn 3 0 u cn -c: ZJ co < 0 5 CD -ri £ JO cn JZ CO cn to CD =» co m  CD C o E co CO CD rr CD o. "D CO 2 E co * •? CO cn £ *"' CZ CD . E i 3 .5 " D CO £Z JS .E co co 3 CD ® £ £ CD >. J Z c co *-- Q E >, 81 « CD CD CD £ o ^ = CO cfl E < co CD i _ ZJ CO Z) ZJ O O "co o ± 3 o (0 in m X o Cvi in 0 o 0 o iri o o ri o cvi I 20a 10a zoo 900 900 K O COO 200 LOO 9 IS SIS MS GIS 2LS LIS OLS 60S 80S ZOS 90S SOS *0S GOS 20S LOS OOS cd CD CO c '•5 £1 c o O o 0 (ajBj03L) jad sjiun lewme) Aijsuap Duopojs 101 extensive field checking and marked on a paper copy of the 1989 1:10,000 land use map, with either the number of horses that were seen, or with an "E" for evidence of horses being present on the property. Evidence was considered to be housing, trailers or training facilities designed for horses. The markings were digitized as points into the GIS database. Locations were compared with the 1994 land use map to ensure that the digitized markings were located in reasonable spots, according to the surrounding land activity. The horse location theme was then used in a vector overlay analysis with the contributing areas. Horses are located throughout the Salmon River Watershed (Figure 4.14). During the survey, about 450 horses were seen at most of the 260 locations determined to have horses. This survey, in combination with the agricultural census data and the horse industry profile, provides evidence of the growing importance of horse farms in the Salmon River Watershed. 102 103 5. Linking water quality to land use 5.1 Methods Nitrate concentrations are at elevated levels in localized areas of the Salmon River and its associated aquifers. In order to determine the importance of likely sources, which include septic systems, commercial agriculture and hobby farms, a series of land use indicators were graphically and statistically linked to streamwater and groundwater nitrate-N. Cook (1994) first attempted to relate land use indicators such as septic system density and percentage of intensively used agricultural land use to water quality. While relationships were evident, Cook concluded that indicators which more closely simulated intensity of use, such as septic system density or nitrogen loading, would show even stronger relationships. This study, therefore, extends Cook's analysis, using the updated septic system database, and animal unit densities described in Section 4.4.3. In order to compare the results of this study with Cook's land use-water quality relationship analysis, the same contributing area groupings (Table 5.1) and 1991-1993 low-flow nitrate-N data were used. Cook also compared land use indices to well water quality. The median nitrate-N concentrations for a set of well data supplied by the Groundwater Section of the BCMOELP presented in Cook (1994), were compared to the land use indicators described above. Septic system and animal unit densities were calculated for the contributing areas in two manners. The first was for individual, or independent, contributing areas. This provided an index of the land activities in the immediately adjacent area. Secondly, cumulative contributing area density indices were calculated. The cumulative contributing area comprises the total watershed area upstream of a given sampling station, and provides a measure of the cumulative effects of land use. In other words, water quality at a given station is influenced by the land use that occurs farther upstream than just the immediate contributing area. Because septic systems 104 Table 5.1 Contributing areas grouped for examining the relationship between land use and water quality (based on Cook 1994) Contributing area area (ha) cumulative area upstream (ha) Independent contributing areas SO 1-02 328 S03 447 S04-05 548 S06-07 598 Salmon River mainstem (not including S00 orS16) S08-09 259 S10-11 630 S12-14 1204 S15 1142 C01-03 592 Coghlan Creek subwatershed C04-05 460 C06-07 435 Davidson Creek D01-02 403 subwatershed Watershed total 7047 Cumulative contributing areas SOI 188 188 S01-02 140 328 S03 447 775 S04-05 548 1324 Salmon River watershed (including the Coghlan and S06-07 598 1922 Davidson Creek S08-09 260 2181 subwatersheds) C01-S10 1633 3814 Sll 484 4298 S12-14 1204 5502 D01-S15 1545 7047 C01-03 592 592 Coghlan Creek subwatershed C04-05 460 1052 C06-07 435 1487 105 are georeferenced in the GIS database and could be overlain with the digital surficial deposits map, septic system densities were calculated for septic systems on all surficial materials as well as on glacial outwash materials only. Animal units are not geographically fixed in the GIS database and so there is no way to determine on which surficial material they are located. The use of contributing areas is based on four important assumptions: 1. the land use activities affect only the water quality in that contributing area; 2. all the runoff from land use activities drains to the water quality sampling station associated with that contributing area; 3. there are no other sources of water to the stream from outside the contributing area; and 4. the land use activities are uniformly distributed in the contributing area. The statistical analysis consisted of the calculation of Spearman Rank Coefficients using the software program SPSS for Windows Release 6.1.2. A statistical analysis was performed for the independent density indices only, due to the spatial autocorrelation and lack of independence of the cumulative density indices. The Figures presented in the following sections are composed of sets of four graphs. The left side of each graph contains either the independent or cumulative density index scale, and the right side, the nitrate-N concentration scale. For the independent density index graphs, the contributing areas for each of the three subwatersheds, the Salmon River mainstem, Coghlan Creek and Davidson Creek, are arranged from upstream to downstream. The overall watershed, including Coghlan Creek, and the separate Coghlan Creek subwatershed are also arranged from upstream to downstream for the cumulative density index analysis. 5.2 Land use and surface water quality The density of all septic systems installed in the watershed from the early 1930's to 1994 has been calculated and compared to streamwater nitrate-N. The numbers and densities of septic 106 systems for each contributing area were discussed in Section 4.2, and are shown in Figure 4.6. Figure 5.1 shows four graphs. The top two graphs show the density of all septic systems in each contributing area, and the bottom two graphs show the density of septic systems on outwash material only. 5.2.1 Septic systems on all surficial materials Figure 5.1 A shows that the greatest density of septic systems, 1.1 ha"1, occurs in the aquifer area of the watershed, S08-09; the second greatest density, 0.88 ha'1, occurs in the Coghlan subwatershed near where it joins the Salmon River. The pattern of increasing density is similar to the pattern of increasing streamwater nitrate-N in both the Salmon mainstem and Coghlan Creek. Streamwater nitrate-N continues to increase in the Salmon mainstem downstream from its confluence with Coghlan Creek, between S08-09 and S10-11. This is due to the contribution of the high streamwater nitrate-N from Coghlan Creek. There does not appear to be a strong relationship between septic system density and nitrate-N in Davidson Creek, and the high nitrate-N in the creek does not appear to have an effect on nitrate-N in the Salmon mainstem downstream of where they join. There is a difference in the magnitude of septic system density versus streamwater nitrate-N between the Salmon mainstem and Coghlan Creek. There are two likely explanations for this. Firstly, septic systems in Coghlan Creek are closer in proximity to the stream channel than they are in the Salmon mainstem near their confluence (Figure 5.2). Approximately 26% of the septic systems in the contributing area C07 are within a 100 m buffer zone of the stream. Of these septic systems, the ten closest to the stream channel (~20 m away) are on the south bank of Coghlan Creek only 550 m upstream of Station 5, which typically shows the highest streamwater nitrate-N levels in the watershed. In S09, only 10% of the septic system are within the 100 m co © •B co • - T5 co .E g « * f o < o 0 1 < ™ c C ^ "I c? • D C L cox 5 CO ( I BLU) N - a j B J j | U j a i B M a o B j j n s 107 0 o co ZJ cz o CO CO CO 0 .g co Z c? 0 v= £5 _Q +-• " l _ E = P CO 0 CO C TJ 0 " C J _ CO E 0 > ST « E .2 CO « • co 0 CO 0 0 CZ CO S B © > Q. co co "F > 3 w rr 5 o c ~ .2 O 0 JS I CD CD CO J= DC CO $ LO 0 ( eu SLuajsAs) xapuj Ajjsuap aAue|nwno ( I Bui) N-ajBJJiu j a j B M aoBjjns 3 C O (_ei| suiajsAs) xapui Ajjsuap juapuadapui 108 109 buffer; the closest to the water quality sampling station, Station 4, are 1.5 km upstream and on the south bank of the Salmon mainstem. Secondly, groundwater discharge probably makes up a larger proportion of stream flow in Coghlan Creek than in the Salmon mainstem. A temperature profile of the streamwater in the Salmon River and its tributaries for the month of August shows that Coghlan Creek is colder than the Salmon mainstem (Figure 5.3). As the Salmon flows through the Hopington Aquifer, the stream temperature decreases from 17.5 to 16°C. Along approximately the same distance, stream temperature in Coghlan Creek decreases from 16.5 to 14.4°C. As well, the temperature in the Salmon mainstem varies more widely than in the Coghlan during summer months. This suggests that while both streams are influenced by groundwater, there is a larger relative volume of groundwater discharge into the Coghlan, which is less affected by the ambient streamwater temperature. The cumulative density of septic systems also increases in the Hopington Aquifer area (Figure 5.1B). The cumulative density index peaks at 0.47 ha"1 in S08-09, just upstream from the highest nitrate-N concentration observed in the Salmon River mainstem, with a pattern similar to the increase in nitrate-N concentration. 5.2.2 Septic systems on outwash material A similar pattern between septic system density and streamwater nitrate-N occurs when septic systems on outwash only are used (Figure 5.1C). The densities are much higher, however, with the highest density of 2.0 ha"1 occurring in S15. This contributing area contains about half of the large outwash deposit over which the dense community of Fort Langley is built. There is very little outwash material in the watershed downstream from the Hopington Aquifer, which is reflected in small densities in S10-11 and S12-14. The large increase in streamwater nitrate-N in Ill Coghlan Creek corresponds with the increase in density on the outwash material. Due to the general absence of outwash material in Davidson Creek, the independent density is very low. The cumulative density index of septic systems on outwash follows a similar pattern, increases in the aquifer area, decreasing downstream from the aquifer, and increasing again in the Fort Langley area (Figure 5.ID). 5.23 Overall animal units and agricultural land Agricultural land uses can be measured in terms of the proportion of land under agricultural use (literally hectares per hectare), or in terms of animal unit densities (see Section 4.4.3 for an explanation of how animal units were calculated). Figure 5.4 shows a comparison of agricultural land use densities. The top two graphs show animal units per agricultural hectare. The bottom two show agricultural hectares per overall contributing area hectares. The left side of each graph contains the independent density or cumulative density scale, and the right side, the streamwater nitrate-N scale. The data in the two left graphs are broken down into the three subwatersheds. The data in the two right graphs are grouped for the watershed as a whole (on the left) and for the Coghlan Creek subwatershed. Figure 5.4A shows that animal unit densities vary throughout the watershed, and that the highest densities, 2.96 and 3.01 ha"1, occur on the Hopington Aquifer, just upstream from where the highest nitrate-N concentration in the Salmon River mainstem was observed. The animal unit densities in S06-07 and S08-09 are above the "critical" value of 2.5 AU ha"1. The animal unit densities in Coghlan Creek are comparable for each contributing area, with all about 1 ha"1. The cumulative density index for animal units does not vary as much as the independent density index (Figure 5.4B). There is, however, an increase in the cumulative density index in CD l l CO c c o 1 1 X J .9 v- C L CD O to I CD i = co 5 t ° " cS — CO Z c? CD .9 CO ZJ ~ -9 c "4= ? § f ^ E c £ © XJ ._ c CO CO CO CD CZ ^ CO t —: CD CD 5 < rr 3 = .9 xi £ e<B ^ B CD CD -r .9 7 3 CD .9, *= > CO § rr CD T= c co CO o SOT"-5 e: CD If f 9-9 9 lc ±i TJ co XJ c c c — o o co iS > o CD 5 t cr £ < to* CD ZJ CO ( I Bui) N-ajBJiju jaiBM aoBuns 112 ( BU eq JO T BU, nv) xspuj Ajjsuap aAijeinuinQ ( I 6ui) jg-aiBjjju J 3 ; B M aoBpns zo-voa co CD k_ CO CO c ZJ CZ o o CO CD t_ CO CO c ZJ n c o O ( BU, BL| jo L_Bi| nv) X S P U ! Aijsuap a iBjpauiui i 113 the Hopington Aquifer area, upstream of the Salmon-Coghlan confluence. Once again, the cumulative density index in the Coghlan Creek subwatershed is similar to the independent density index. While the independent density index for total agricultural area varies throughout the watershed as the animal unit index did, there appears to be little relationship between this land use indicator and the streamwater nitrate-N (Figure 5.4C). The cumulative density index for agricultural area is relatively consistent throughout the watershed and does not appear to relate to streamwater nitrate-N either (Figure 5.4D). This indicates that an animal density index is a better way of measuring land use with respect to contaminant loading in the stream, just as septic system density gives a better indication of nitrogen loading into the aquifer than does residential hectares (Cook 1994). 5.2.4 Agricultural subtypes and streamwater nitrate-N Cook (1994) further subdivided the agricultural land use into different animal type categories: horses, poultry, and all other animals. The following graphs compare animal unit densities and streamwater nitrate-N for the selected agricultural sub-types to animal area densities and the same streamwater nitrate-N. Horses Figure 5.5 shows four graphs, comparing various density indices with streamwater nitrate-N. The top two graphs show the independent and cumulative density of horse units per agricultural hectare. The bottom two graphs show the independent and cumulative density indices of proportion of land used for horse activities. The density of horses increases from the headwaters to S08-09, where the largest density, 6111) N-9lBJj|u JBIBM a o B j j n s 1 1 4 ( eu, B i | JO t _ B q nv) x a p u j Ajjsuap a A ! ; B |n iuno ( I Bui) N - 9 i e j j j u j a j B M a o B J j n s ZO-900, S0-t'0O» SO IOQ CD CD CO CO c '•+—' ZJ c o O CO c 3 C o O 3 CO ( BL| Bi) JO BL| nv) * 3 P U ! A4|suap iuapuadapii | 115 1.02 ha"1, is observed (Figure 5.5A). The density of horse units is somewhat smaller downstream from the Hopington Aquifer. The pattern is similar to the increase in streamwater nitrate-N and the horse density peaks prior to the Salmon-Coghlan confluence. The density of horses in the Coghlan Creek subwatershed varies little from the headwaters towards downstream and is similar to the density in the lower portion of the Salmon River mainstem. The cumulative density of horse units increases from the headwaters towards downstream and peaks in S08-09, at 0.41 ha"1 (Figure 5.5B). The cumulative density decreased in C01-S10 due to low densities throughout Coghlan Creek and in the Salmon River mainstem downstream of the aquifer. The independent density index shows that the largest proportion of horse areas occur in the aquifer area of the watershed (Figure 5.5C). The density of horse area peaks in S04-05, which is farther upstream from the peak unit density. The horse area density in Coghlan Creek is highest in the headwaters and where the Coghlan joins the Salmon River. The independent density shows that the proportion of horse area is similar in Coghlan Creek and the upper reaches of the Salmon mainstem, unlike the independent unit density index which shows that the density of horse units in the Coghlan are much lower than in the upper Salmon River mainstem. The cumulative density index for horse area also peaks farther upstream than for horse units, and remains relatively high towards the mouth of the Salmon River (Figure 5.5D). Poultry The relationship between the density of poultry units and streamwater nitrate-N was compared with that of density of poultry area. The highest density of poultry units, 1.16 ha"1, occurred in S06-07, which is upstream from other intense animal activities (Figure 5.6A). The strongest similarity in patterns exists in the Coghlan Creek subwatershed, where there is a continual increase in both poultry unit density and streamwater nitrate-N from the headwaters to * E - 0 -*—• CO C CC Is co "cb .9 c zJ "5. CO - c * c CD O | a 5 £ CO CO c C O z 5 cb _Q cO 4= c c o c © fc § to S >.o 0) .9 Lr CD CO C XJ ^ o co -g E 2 © "co CO ti) (7) 3 XJ ~ O CD .9 C L J Z o co —> &s 8 o> ^ ZJ 7 3 CD -9 ~ > i= § cc © £ o xz 3 E «: 0 CO CD e-w to S i? "-5 1 - « g. g 5z 'xz ~ < CO XJ c c ^ ° ° fli IS 5 ' 5 tr £ < CO IO CD k— ZJ C D ( I BLU) |s|-a}Bj;!u JBJBM aoBLins 1 1 6 CO CD i _ CO C O e ZJ xi c o O ( ei| B q JO L _ B q nv) xapuj Ailsuap a A j i B i n i u n Q ( I 6LU) N -a jBj ; |u JBIBM a o B u n s so-ioa ID CM O O O O O O O O O CO CD CO C O C '-*—< ZJ XI c o o ( eq Bq JO t_eq nv) xapuj Ajjsuap iuapuadapu| 117 where Coghlan Creek joins the Salmon River. The cumulative density of poultry is highest, 0.55 ha"1, in the headwaters of the Salmon River and decreases in subsequent contributing areas (Figure 5.6B). However, the poultry unit density then increases in the region of the Hopington Aquifer. There is a similar increase in Coghlan Creek. The pattern of change in the independent density of area of poultry activity is inconsistent with the pattern of streamwater nitrate-N, except in Coghlan Creek (Figure 5.6C). Unlike the poultry unit density, the greatest poultry area density occurs in Davidson Creek, D01-02. The cumulative density index for poultry area decreases from the headwaters to the eastern edge of the Hopington Aquifer (Figure 5.6D). Towards the middle of the aquifer, the density increases and then remains constant to the mouth of the Salmon River. The cumulative density increases from Coghlan headwaters to where the tributary joins the Salmon mainstem. Other Animals Other animal types in the watershed include cattle, sheep and swine, which have been consolidated into one category for comparison with streamwater quality. Figure 5.7 shows the comparison of animal unit and area densities with streamwater nitrate-N. The overall density of the combined animal types is greater than the individual animal types previously discussed, indicating that other types of animals are also important in the watershed. The independent density of animal units increased consistently from the Salmon headwaters to the confluence with the Coghlan, with the highest density, 1.48 ha"1, occurring in S08-09 (Figure 5.7A). The independent density then dropped to half that of S08-09 and continued to increased toward the mouth of the Salmon River. In the Coghlan subwatershed, the trend is reversed; the independent density index decreased from 0.78 to 0.34 ha"1. A similar pattern is observed for the cumulative animal units densities (Figure 5.7B). ( LJ 6LU) |sj -3)ej}ju J B I B M eoepns 118 ( t_eu, BL| JO t . B L | nv) x a p u | A41.s1.ap aA|iB|nujno ( I 6iu) N -a jeJ i iu J B I B M a o B j j n s zo-Loa Z J CO CD i _ CO C O c *+-» ZJ c o O B u , B i | JO L , B U nv) xapui Aifsuap ;uapuadapu| 119 The relationship between land area density and streamwater nitrate-N is weak, but shows that there is a significant amount of agricultural area used for livestock other than horses or poultry (Figure 5.7C). The largest area density for other animal types occurred in C01-03, 0.089 ha"1, and D01-02, 0.071 ha"1. The cumulative density for area is consistent from contributing area to contributing area, for the overall watershed (Figure 5.7D). The cumulative density of area is higher in the Coghlan Creek subwatershed and decreases from headwaters to where the creek joins the Salmon River. 5.2.5 Comparison of land use components The spatial distribution of septic systems and animals in the watershed have resulted in different relationship patterns of each with streamwater nitrate-N. Both septic system and animal unit densities increase through the middle of the watershed, over the Hopington Aquifer. Both also decrease downstream from the aquifer, as does the nitrate-N concentration. From this method of comparison, it is reasonable to conclude that both septic systems and agriculture are having an effect on the concentration of nitrate-N in the Salmon River mainstem. The results in the Coghlan Creek subwatershed are slightly different, however. While animal unit densities do not vary from upstream to downstream, septic system densities almost triple. This suggests that septic systems are the primary source. For Davidson Creek, agriculture is the likely source. The relationship between increasing horse unit and all other animal unit densities and increasing streamwater nitrate-N upstream of the aquifer suggest that both commercial and smaller farms contribute to nitrogen loading. 120 5.3 Land use and groundwater nitrate-N 5.3.1 Septic systems Septic system densities (based on the completed septic system database) and animal unit densities were compared with median well water nitrate-N calculated by Cook (1994). Septic system density was compared to wells on all surficial materials, shallow (< 100 ft) wells, and wells on outwash material only (Figure 5.8). The median well-water N03-N values for wells on all surficial materials increase in the Hopington Aquifer area, in both the Salmon mainstem and Coghlan Creek (Figure 5.8A). Unlike the spatial pattern observed in the land use versus streamwater nitrate-N, well-water nitrate-N does not continue to increase below the Salmon-Coghlan confluence. Rather, the well nitrate-N decreases, though not as much as the septic system density index. Septic system density appears to be unrelated to the well-water nitrate-N in the Salmon headwaters and Davidson Creek, where concentrations are higher than 4 mg L"1. Near the mouth of the Salmon River, well-water nitrate-N is low relative to septic system density. These results are similar to Cook's (1994), however, septic system densities in the present study were found to be greater. The relationship between septic system densities and well water nitrate-N on outwash materials resemble that of the same land use indicator with streamwater nitrate-N (Figure 5.8B). One exception is that of Davidson Creek, where the median well-water concentration is higher than that of wells in other contributing areas. Because the density of septic systems in DOI-02 is relatively low, it is likely that some other source is responsible for the elevated nitrate-N concentrations. 121 Figure 5.8 Relationship between septic system density and nitrate-N in groundwater from wells on all surficial materials and well on outwash only, in the Salmon River Watershed. Contributing area groundwater nitrate-N groundwater nitrate-N septic systems on all surficial materials septic systems on outwash materials only 122 5.3.2 Animals The spatial variation in animal unit density, including all animals, resembles the spatial variation in median well-water nitrate-N in the Salmon mainstem (Figure 5.9A). The contributing areas with the highest animal densities also have the highest median well-water nitrate-N. In Coghlan Creek, the animal units do not vary from upstream to downstream, while the median well-water nitrate-N increases by almost 5 mg L" 1 . Poultry densities in the Salmon mainstem do not appear to be related to median well nitrate-N, except in S06-07, where both are high (Figure 5.9B). In Coghlan Creek, both poultry density and median well nitrate-N increase. The well nitrate-N in Davidson Creek is not related to poultry density. Horse and all other animal unit densities increase in a pattern similar to well nitrate-N in the Salmon mainstem (Figures 5.9C and D). Both animal unit densities also decrease in Coghlan Creek. The other animal unit densities show a stronger relationship with median wel l nitrate-N than do horse unit densities in Davidson Creek. 5.4 Statistical evaluation of land use-water quality interaction A s an additional test of the association between land use and water quality indicators in the Salmon River watershed, Spearman Rank correlation coefficients were calculated based on the independent density indices for each contributing area (Table 5.4). The null hypothesis was that land use, as measured by the independent density indices, has a positive or no effect on water quality. A one-tailed test is used because there is an a priori assumption that land use does, in fact, have a negative effect on water quality. There is a significant relationship between streamwater nitrate-N and well water nitrate-N , for wells on outwash material only. The correlation coefficients for stream and well water nitrate-N versus the land use indicators do not show any significant relationships, with the (L_| 6w) N-ajBJiju j a j B M punojB CO in - t - -+-CO —I— CM - 4 -3- 20- lOd ZO-900, 3- so-f oo, co-100 9LS U - O L S 60-80S* Z0-90S* so-ws* COS 20- 10S T - ^ T - T - O 3 CO in -4-J2 CD .5 c ( t eg. BU. JO T BU. nv) xapuj Ajjsuap aAj jBinoino ( I 6LU) N-BIBJIJU J9JBM punojB CM co" o co' in o in o CM »— i— m d o d io —f-to 0) o 3: O -4 -co -4-i I i i i i I • i i i I i o co ^ d co d CM - t -d ( t B q BLJ JO T BU. nv) xapuj Ajjsuap }uapuadapu| m - zo- LOO •EZIZr ZO-900, so-wo» co-too S I S n-sis U - O L S 60-80S* Z0-90S. S0-fr0S* ^ cos 3 1 - 20-10S CM d o d 124 exception of proportion of agricultural land on outwash material and well water nitrate-N. Table 5.4 Spearman Rank correlation coefficients illustrating the association between selected land use and water quality indicators in the Salmon River Watershed. well water well water streamwater well water N03-N N03-N on NCyN NCyN <=100 ft outwash Land use n=12 n=12 n=ll n=10 streamwater N03-N 1.000 well water N03-N 0.399 1.000 well water NQ3-N, <=100 ft 0.300 0.600* 1.000 well water NCyN, on outwash 0.830** 0.746** 0.268 1.000 Land use on all surficial materials septic system density 0.308 0.238 0.318 total animal unit density -0.168 -0.021 0.082 agricultural area density 0.266 -0.322 0.209 horse unit density -0.266 0.133 0.409 horse area density -0.014 0.315 0.418 poultry unit density 0.105 0.133 0.064 poultry area density 0.452 0.470 0.165 other animal unit density -0.315 0.035 0.155 other animal area density -0.161 0.098 0.146 Land use on outwash material only septic system density 0.109 0.100 0.018 -0.091 agricultural area densitv 0.238 0.497* 0.582* 0.018 significant correlation at a = 0.05 for a one-tailed test significant correlation at a = 0.01 for a one-tailed test A number of factors make the utility of statistical analysis in this study questionable. 125 This study assumes that land use activities are evenly distributed throughout a contributing area. A s Figure 5.2 shows, this is not necessarily the case. The complexity of the underlying geology results in the influence of groundwater transport of land applied contaminants and may result in a spatial lag between the activity and the location at which the streamwater is affected. For example, preferred pathways or macropores in soils may result in the transport of contaminated soil water more rapidly or over a greater distance than expected (McCoy, et al. 1994). The groundwater contributing area may be either a different shape or a different size than the streamwater contributing areas used in this analysis. The statistical significance of any relationships change depending on the manner in which the contributing areas are combined (Cook 1994). Furthermore, an accurate delineation of the contributing areas in the Salmon River Watershed is difficult due to the low topographic relief of the area. 126 6. Nitrogen mass balance The previous chapter attempted to link water quality to land use using indicators such as septic system and animal stocking densities to represent the intensity of land use. While relationships are visible in a graphical analysis, the conclusion was that a nitrogen mass balance calculation may provide more refined information regarding the relative impact of the various sources of nitrogen in the watershed. To this end, the following chapter describes a nitrogen mass balance calculated for the watershed, and shows the spatial relationship between nitrogen loading on the land compared to what is coming out in the streamwater. 6.1 The nitrogen mass balance calculation 6.1.1 The model The nitrogen balance calculated for this study is based on an agricultural inventory and nutrient management study done for the Lower Fraser Valley (Brisbin 1994a). The mass balance quantifies the sources and sinks of nitrogen in a simplified model of a typical nitrogen cycle (see Section 1. for discussion of nitrogen cycle). The flow diagram in Figure 6.1 represents the sources and sinks accounted for in the model. Nitrogen sources, in boxes, include manure, inorganic fertilizers, septic systems and the atmosphere. Sinks, in circles, include management losses from and exports of manure, crop uptake, and denitrification. There is also a small feedback loop between management losses from manure, volatilized nitrogen specifically, and the atmosphere. The remaining surplus(deficit) of nitrogen is available for leaching into the groundwater or for surface runoff. 127 Figure 6.1 Flow diagram of model used to calculate nitrogen mass balance for the Salmon River Watershed. • P - - - - - - - - - - -| Surplus(deficit) i -available for leaching 128 The original model consists of a spreadsheet, into which a number of input variables are added: 1. a livestock inventory. The numbers and types of animals are based on the 1991 Agricultural Census data, and supplemented by inventories done for various commodity groups in the Lower Fraser Basin. 2. unit livestock nutrient production, which is the amount of nitrogen per unit of manure (Table 6.1). The values used for this study are locally derived. 3. manure management practices and associated nutrient losses. The type of housing, manure storage and handling all affect the amount of nitrogen lost to the atmosphere, to runoff, and to infiltration into the ground (Table 6.2) 4. agricultural land base inventory. This includes the amount of agricultural land, and land used for various crops, and is based on the 1991 Agricultural Census data. 5. unit crop nutrient uptake. The amount of nitrogen assimilated by various plant types were based on locally derived information (Table 6.3). 6. inorganic fertilizer use. The amount of nitrogen applied to various crop types has been estimated from fertilizer sales in the Lower Fraser Valley (Table 6.3). 7. soil-atmosphere nitrogen exchange factors. The atmosphere contributes a background amount of nitrogen to the soil, as well as returning some of the nitrogen lost from manure through volatilization. Denitrification results in an additional loss of nitrogen after application of manure to the soil. These numbers have been estimated from local data and from the literature (Table 6.4). 129 Table 6.1 Unit livestock nutrient production. The values are based on locally derived data (from Brisbin 1994a). The values were averaged by livestock category for use with the Agricultural Census data. unit nutrient production (kg-N animal1 year"1) Actual values Average used for Livestock category (used for survey data) Census data Dairy bulls 112 72.5 cows 116 heifers 42 calves 20 Beef bulls 112 60.8 cows 78 heifers 44 steers 50 calves 20 Poultry (meat) chickens 0.6 0.69 turkeys 0.86 other 0.6 Poultry pullets 0.34 0.57 (layers) layers 0.8 Swine boars 24.3 16.6 sows 18.3 other 7.2 Horses 45.5 45.4 Sheep rams 11 8.8 ewes 11 lambs 4.4 130 Table 6.2 Manure management nutrient loss factors (based on Brisbin 1994a). Livestock Management loss factor (% of total N produced) category to air to runoff to infiltration total losses Dairy 42 2.1 0.8 44.9 Beef 33 0 0 33 Poultry (meat) 38.7 0.8 0.8 40.3 Poultry (layers) 70.2 0.9 0.9 72 Swine 44.5 1.5 0.4 46.4 Horse 40 0 0 40 Modification to the values used by Brisbin were made for the unit livestock nutrient production and to the management loss factors. Because the census data obtained for this study was not as detailed as that used by Brisbin, the age and type of some of the animals were unknown. Therefore, average values were applied (Table 6.1). The averages are reasonable, compared to more generalized unit nutrient production values presented in Kowalenko (1987). Neither the census nor waste management survey data provided detailed information regarding housing and manure handling strategies. Rather than apply the complex set of factors which Brisbin used, overall average percentage losses were derived from Brisbin's factors (Table 6.2). These losses are generally greater than those reported in the Manure Management Guidelines (Bertrand and Bulley 1985) or the various Environmental Guidelines developed by the BCMAFF (BCMAFF 1995, 1993, 1992). However, these guidelines present data for recommended minimum loss management systems. 131 Table 6.3 Unit crop nutrient uptake and inorganic fertilizer application rate (based on Brisbin 1994a). Crop Nitrogen u (kg ha ptake rate 1 vr1) Inorganic nitrogen fertilizer application (kg ha"1 yr1) Grass hay 300 240 Improved pasture 200 120 Unimproved pasture 100 0 Silage corn 185 140 Grain 80 180 Vegetables potatoes 230 90 peas 20 20 corn 160 130 beans 45 45 cole crops 120 200 other 130 100 Berries raspberries 70 75 strawberries 70 75 blueberries 75 70 other 15 15 Other field crops 100 132 Tree fruits 70 75 Nursery crops 50 60 Sod 60 70 Summer fallow 0 0 The fertilizer application rates in Table 6.3 were used for both the 1986 and 1991 calculations. Brisbin (1994b) determined that fertilizer application increased from 1986 to 1988 and then decreased back to 1986 usage levels by 1991. • 132 Table 6.4 Soil-atmosphere nitrogen exchange factors (based on Brisbin 1994a). Soil-atmosphere exchange Exchange factor From atmosphere to soil background deposition 9 kg-N ha"1 yr"1 return flow 30% of N lost to air during handling and storage From soil to atmosphere denitrification (after manure 10% application) Other assumptions in this model include: 1. the nitrogen pool in the soil is at steady state. 2. biological fixation is not accounted for. 3. fertilizer inputs do not include those used on home lawns and gardens. 4. mushroom houses and greenhouses are not included. Brisbin (1994a) states that a surplus application of 100 kilograms of nitrogen per cropped hectare is likely acceptable, depending on the sensitivity of the area. The number of 100 kg of nitrogen was chosen because at this rate, 100 kg of nitrogen diluted in one meter of water (i.e. . If all the wptecipitation), the resulting concentration of the water would be 10 mg-N L"1 were to leach into the ground, the resulting groundwater recharge would also have a concentration of 10 mg-N L"1, the drinking water standard for nitrate. Because the Brisbin study focuses on agricultural wastes, the contribution of nitrogen from septic systems has not been accounted for. Land use in the Salmon River Watershed is highly mixed and septic systems are an important source of leachable nitrogen and therefore, the contribution from septic systems was added to the mass balance calculation for this study. 133 Walker et al. (1973) determined that an average of 8 kg of nitrogen is supplied to the septic tank per person. In order to account for the retaining of nitrogen bound in solids in the septic tank and for denitrification, which can vary from zero in well aerated soils to 80% in soils with high organic contents, it was assumed that fifty percent of the nitrogen introduced into the septic tank is available for leaching to the groundwater. It was assumed that all septic systems are functioning at an optimum level of effectiveness. Malfunctioning and improperly installed septic systems may result in a greater amount of nitrogen reaching the groundwater from the leach field. 6.1.2 Data Sources A nitrogen balance was calculated for three different data sets: 1986 and 1991 Agricultural Census data; a survey of individual farms in the watershed; and a combination of the two. This was done in order to assess the temporal variability of nitrogen loading, farm to farm variability of nitrogen loading, and spatial variability of nitrogen loading in relation to streamwater quality in the watershed. Census data The model was first applied to the Agricultural Census data for 1986 and 1991. Section 4.3 provides a discussion of the data, and Figure 4.7 shows the boundaries of the census enumeration areas. The human contribution of nitrogen to the system is based on the Population Census for both the 1986 and 1991 census years. The data provided for the census areas is not geographically referenced, and therefore it is not possible to determine where the activities are occurring. Because the surplus nitrogen is assumed to be evenly distributed on agricultural land through out the enumeration area, which in some cases extend beyond the watershed, it is 134 possible that the surplus is being overestimated in some parts of the watershed, and underestimated in others. Waste management survey The nitrogen mass balance model was also applied to the data collected in the Agricultural Waste Management Survey for the Salmon River Watershed (Section 4.4). For the calculation of individual farm balances, the assumption that only 30% of broiler manure is exported was not used. Rather, the export rates reported in the survey were used (Appendix 21). The survey data was also combined with the census data to determine a nitrogen balance for contributing areas (see Section 4.4.3 for explanation of how data was combined). Human inputs were calculated based on the septic system database described in section 4.2., and assuming that each septic system represents an average of 3.5 people. 6.2 Nitrogen budget with census information 6.2.1 1986 Census data The nitrogen mass balance for the 1986 census data is summarized in Appendix 22. Figure 6.2A shows the surplus(deficit) nitrogen loading for each census area, including contributions from both agriculture, shown in light grey bars, and septic systems, in the dark grey bars. The nitrogen loading from septic systems (kilograms of nitrogen per residential hectare) were not reported for four of the census areas because the census boundaries extended beyond the coverage of the 1989 land use map, and the amount of residential area in these census areas could not be determined through GIS raster overlay. The average nitrogen loading from agriculture was 113 kg-N ha"1; septic systems contributed an average of 42 kg-N ha"1. Based on agricultural inputs and losses, two census 1 3 5 Figure 6.2 Surplus(deficit) nitrogen loading by census areas in the Salmon River Watershe 1986 and 1991. Asterisks indicate census areas on the Hopington Aquifer. Nitrogen source j j Agriculture (kg-N per cropped ha) l l l l Septic systems (kg-N per residential ha) -50 1 2 3 4 5* 6 7* 8* 9* 10 11 12 13 14 Avg Census area 136 areas, 6 and 12, show a deficit of nitrogen; however, when the septic system contribution is accounted for, only 6 has an overall deficit. A deficit occurs when the nitrogen application are not sufficient to meet crop nutrient requirements. Eight of the fourteen census areas receive surplus nitrogen from agriculture alone, in excess of 100 kg-N ha"1. Of these eight, three census areas are on the Hopington Aquifer, including census area 9 which received the largest surplus nitrogen loading, 601 kg-N ha"1 from agriculture alone in 1986. Interestingly, in four census areas, 2, 4, 5 and 12, the contribution of nitrogen from septic systems surpassed that of agricultural contributions. This is because of the relatively low level of agricutural activity in these census areas. 6.2.2 1991 Census data The nitrogen mass balance for the 1991 census data is summarized in Appendix 23. Figure 6.2B shows the surplus(deficit) nitrogen loading for each census area, including contributions from both agriculture, shown in light grey bars, and septic systems, in the dark grey bars. As for the 1986 data, the nitrogen loading from septic systems (kg-N per residential hectare) for four census areas were not reported. The average nitrogen loading from agriculture was 87 kg-N ha"1; septic systems contributed an average of 46 kg-N ha'1. In five of the fourteen census areas, nitrogen loading from agriculture alone surpassed 100 kg-N ha"1. In 1991 the census area with the greatest loading was 14, which is in the headwaters of the Salmon River in a rural area of the City of Abbotsford. In the Hopington Aquifer area, the greatest loading occurred in census area 8. 6.2.3 Comparison Between Census Years Table 6.5 summarizes the total nitrogen inputs for the two census years. For septic 137 system inputs, census area 3 is not included because the census boundaries changed significantly from 1986 to 1991 and the data suggested that the number of households in the area decreased, which is incorrect. The overall inputs decreased from 1986 to 1991. The decreases in manure nitrogen and fertilizer reflect the decreasing numbers of animals in the area, cows and poultry in particular, and the decrease in atmospheric contributions reflects the smaller agricultural land base. Atmospheric inputs are based on a background of 9 kg-N ha"1 and a portion of nitrogen volatilized from manure. Therefore, the smaller land base and fewer animals results in a smaller input of nitrogen from the atmosphere. The only input which did not decrease was that of septic systems. Table 6.5 Summary of nitrogen inputs into the Salmon River Watershed for the Census years 1986 and 1991. Census year Nitrogen source Manure Inorganic fertilizer Atmosphere Septic systems 1986 1991 (in kilograms, with percentage in brackets) 1 134 367 (64) 453 223 (25) 131 079 (7) 67 008 (4) 1 003 528 (61) 418 946 (26) 129 549 (8) 76 868 (5) Total 1 785 677 1 628 891 The change in nitrogen loading from agriculture and septic systems separately, as well as from the combined loading, is shown in Figure 6.3A to 6.3C. Combined loading was calculated by dividing the sum of septic system plus agricultural surplus N, by the sum of residential plus cropped area hectares. Census areas 1, 3, 11, 13 and 14 are not included in the septic system 1 3 8 Figure 6.3 Change in surplus(deficit) nitrogen loading by census area in the Salmon River Watershed from 1986 to 1991. Asterisks indicate census areas on the Hopington Aquifer. m 1986 m 1991 700 600 500 400 300 200 100 0 -100 A Agriculture (kg-N per cropped ha) i W 1 2 3 4 5* 6 7* 8* 9* 10 11 12 13 14 CO c T J CO o c CO o CO Q. i 100 B Septic system (kg-N per residential ha) 1 2 3 4 5* 6 7* 8* 9* 10 11 12 13 14 200 150 100 -100 1 2 3 4 5' 139 component or for the combined loading. The most significant change occurred in census area 9, where the agricultural surplus loading decreased from 601 kg-N ha"1 in 1986 to 107 kg-N ha"1 in 1991 (Figure 6.3A). This sizeable change is likely due to a combination of decreased animal unit density, increased cropped area to which nitrogen was applied, and decreased proportion of crop nutrient needs met by inorganic fertilizers. Despite the large decrease in census area 9, the overall nitrogen loading for the watershed from agriculture increased from 67 to 75 kg-N ha"1. While the overall inputs decreased, so too did the land base to which nitrogen is being applied. The overall nitrogen loading from septic systems also increased from 42 to 46 kg-N ha"1. As Figure 6.3B shows, septic system loading increased in every census area for which loading could be calculated, which was expected. The combined surplus(deficit) loading increased in four census areas for which loading could be calculated (Figure 6.3C). The most significant increase occurred in census area 6, in which the loading changed from a deficit to a surplus. The change is likely due to increased numbers of animal units, decreased cropped area to which nitrogen is applied, and an increase in the proportion of crop nutrient needs met by inorganic fertilizers. One of the census areas showing an increase is on the Hopington Aquifer census area 8 increased from 94 to 120 kg-N ha1. Overall, the changes in combined surplus nitrogen loading confirm some of the trends in land use dynamics described in Chapter 4. Large agricultural operations are moving east in the watershed, and are being replaced in the Hopington Aquifer area by rural residential and hobby farm activities. While these changes have resulted in substantial decreases in nitrogen loading, some areas, most notably the Hopington Aquifer, are experiencing increases. 140 6.3 Nitrogen budget with waste management survey data 6.3.1 Individual farm nitrogen balances A nitrogen mass balance was calculated for the individual farms which responded to the Agricultural Waste Management Survey (Appendix 24 contains a summary of the calculation). The atmospheric return flow of nitrogen volatilized from manure is not included in the individual farm calculations because the volatilized nitrogen is spread to a much wider area than the individual farm. Septic system contributions are not included in the individual farm nitrogen calculations. The results were grouped according to commodity type; Table 6.6 summarizes surplus loading by commodity type. The minimum surplus(deficit) loading, -71 kg-N ha'1, was calculated for a broiler chicken operation. A horse operation had the maximum surplus loading for all the farms surveyed, 546 kg-N ha'1. The non-livestock operations include twelve nurseries (one of which does maintain sheep), five berry farms, and one sod farm. As Figures 6.4 shows, all of the individual farms have a surplus nitrogen loading of less than 100 kg-N ha"1. Poultry operations included broiler chicken, laying chicken, and turkey farms. Broiler chicken farms tended to have a deficit nitrogen loading, while one layer chicken farm had a surplus (Figure 6.5). This reflects the practice of broiler chicken farmers to export almost 100% of the animal wastes. Turkeys are not shown because the lack of crop data for the individual farms made a loading calculation impossible. The surplus loading for the livestock operations, including dairy, sheep and horse farms, is shown in Figure 6.6A to C. Almost half of the dairy, one-third of the sheep, and one-fourth of the horse operations had surplus loadings in excess of 100 kg-N ha"1. None of dairy farms had a deficit while one-third of sheep and almost one half of horse farms did have deficit nitrogen loadings. Horse and sheep operations, by far, had the highest surplus nitrogen loadings. 1 4 1 CD I s B 3. CD < £5 CD CD •- i XJ CD CD -o — o i a E . 2 co "co H — l _ • CD O CL o O to CD - d > 0 CO I— CD to CD > Lr i | - E c oc; "co ZJ TD > XJ c co CO CD O -C c CD CO o c o 0 i I S=f CO © 0 H . E —j CO o co =J CL cz XJ =1 « 2 CO ^ CL CD 0 k_ ZJ CO : m 8 3 CO c I— > TJ 8 CT) o CM (BL|-CIOJO/6>() ua6oj}iu sn|djng 142 c CO E CO CO CO rz CO • CO ^ >. CO © t o ^ CO j2 <: £ _ c CO CO £ CO ZJ OJ .2 >> i- CO co — < co-co CD i5 "O CD CD -o •§ _-— o ci-E i " E .2 CO 3 ° a | CO o •g°-T J CD C J Z co rt .g ^ T J i_ C0 CD o > c a: © c CO o M cz rt CO CD "o CD ._ O H — 3 >, -5 co e- 2: ZJ ZJ CO CO 3 CM E ca 75 XJ > co ^ CM C in CM in (Bu-doJO/B>|) uaBojjju (;p!iep)sn|djns LO CD CD ZJ g> LL 143 Figure 6.6 Surplus nitrogen for individual farms included in the Agricultural Waste Management Survey for the Salmon River Watershed. Operations include dairy, sheep and horses. 150 100 H 50 + CD i _ CO t5 300 T CD XZ TD 250 • CD L C L 200 • O t_ O 150 '• Z C O — C O c 50 \ XJ CO o 0 • CO ZJ CL -50 ; I_ CO 10 11 12 B Sheep production I rai 1 121 XL 55 56 57 59 60 61 62 63 64 65 66 69 71 73 600 500 400 300 200 100 0 -100 Horse production l m l I I KM I I MM I 14 77 83 84 86 89 90 91 92 94 96 97 98 99 100 102 105 108 109 120 Individual farm 144 Table 6.6 Summary statistics for the surplus(deficit) nitrogen loading for individual farms, by commodity type. Surplus(deficit) loading (kg ha1) No. of Commodity farms Minimum Maximum Median Nursery 12 1 57 21 Berry 5 9 21 18 Sod 1 -- -- 20 Poultry (broiler) 9 -71 9 -26 Poultry (layer) 3 -26 13 13 Dairy 6 33 143 76 Sheep 15 -31 270 47 Horse 20 -69 546 21 A comparison of nitrogen loading with the animal unit densities discussed in Section 4.4.2 shows that farms with higher loadings were more likely to have stocking densities greater than 2.5 animal units per hectare. Some farms with less than 2.5 AU ha1 (two dairies and one sheep farm), had surpluses greater than 100 kg-N ha"1, while several farms with greater than 2.5 AU ha"1, most notably horse farms, had small surpluses only, or deficits. The discrepancy is due to one or more of the following reasons: 1. Animal unit densities were calculated on the basis of total farm area, whereas the loading was calculated on the basis of cropped area, where the nitrogen would actually be applied; 2. Crop type plays a significant role in the uptake of nitrogen. For example, grass hay will use more nitrogen than will the same area of corn. Therefore, the crop to which a farmer applies animal manure without considering the crop's nutrient requirements will affect the level of surplus loading; 145 3. Several farms, most notably poultry and horse operations, export their manure. All of the horse farms with a deficit nitrogen loading, two of which have more than 2.5 AU ha1, export one hundred percent of their manure. 63.2 Nitrogen balance for contributing areas The results of the nitrogen mass balance calculation are summarized in Appendix 25. Figure 6.7 shows the total nitrogen inputs (in kilograms of nitrogen) into the Salmon River Watershed by contributing area. The nitrogen sources include septic systems, the atmosphere, fertilizers and manure. The total input of nitrogen ranges from <1,000 kg-N in contributing area C02 to >237,000 kg-N in S15. Manure is the largest input of nitrogen for almost every contributing area. Fertilizers and the atmosphere are also important inputs for some of the more agriculturally dominated contributing areas. Septic system appear to be the smallest input. Table 6.7 shows the relative nitrogen inputs for the overall watershed. After losses of nitrogen (crop uptake, management losses and denitrification) are taken into account, septic systems become a more important component of surplus nitrogen (Figure 6.8). This graph shows nitrogen sources grouped into agriculture and septic systems (the atmospheric and fertilizer components are included in agriculture). The surplus(deficit) nitrogen from agriculture ranges from -51 kg-N in C06 to >29,000 kg-N in S15. Overall, agriculture remains the primary source of surplus nitrogen. However, in at least four of the contributing areas, septic systems have surpassed the agricultural input of nitrogen. The largest nitrogen surpluses due to septic systems occur in S15 and S16 which include Fort Langley, and C07 and S07 which are in the Hopington Aquifer area, the major urban centres in the Salmon River Watershed. 146 co CO c '•4—' co 8 © E o co J= o CD I— XJ > c DC x i c ° -o 2 E co co 9-CO 2 co CO 0 -*—' CO < 0 0 c CO ° 2 1 C O SZ E w 3 g -9 co c o © 0 0 *o XJ o 1 -9 CO > 0 « to 2 i _ CO ^ CO cc Z c OJ o o E O co "9 0 co .9 co +-* CO E CO 0 X J _ZJ o c X J ez CO E CO 0 I— -»—* CO u. C 0 o f E 2 CO co 0 . CO  C L o %=• E ° o 4= c X J ° 0 CO 0 5 £ C CD 5 co co cp Q. O CO E c» 5 ' CO E "3 o . E 5 C cj) © x : C O 2 c ~ o «= c O £ h- co CD 0 zz C O 0 t_ CO CO CO 0 zz X i - ° CO O o CO urc tern o CO CO >> CO c o o o -4—' C L o 0 k - co z m ZJ c i Davidson Cr. Hill" ' Davidson Cr. • • H I II HI • l r i o n i r ™ c Cogh 1 1 1 1 1 1 1 1 8 8 h 8 8 8 co 8 CM 8 8 o 8 o co o 8 o CD o 8 o o 8 o D 0) > c o E co cn i i . . . i o o o 8 8 8 o o o m o m CM CM «-o w S) 0 O i _ w CO C O fa E 8 3 o w o w in o co o w co o w CM o co o (0 c o o o 8 o o o 8 o in (N 6>j) sindui U96OJIJU |B;OI 147 co SZ co I" > c cc E ™ to o co sz += I- C . o CO c CO o •4= CD += C CD O CD to - o TJ CO CD TJ sz > « co CD Q CO TJ > B °= c i c o O O i= TJ CO co CD x f sz a. ~ CO •E CD co CD CO CO o E o t : o CD CD C0 +-© o CD (Z .1 I =J CD to "co .E 00 CO CD i_ Z J CD CD SZ c o co CO CD CO CD C "•4—' Z J cz o o CD CO o TJ tz CO CO CD -4—' CO < E CO CD ' CO cz o TJ E CO CD t— •*-» CO CL ZJ E o **— TJ CD CD C • CO I— k _ CO CD L_ CO Jo 4 a, - 5 co c r CD < c c =1 2 £ g» c ° -o .9 o X CD o 3 0 CO 1 co E CD to £ >» ZJ CO ^ O ZJ += o CL C CD CD CO < CM 8 S 8 & 8 8 8 co 8 CM 8 8 8 8 8 8 8 8 8 8 8 ° 8 o o o o o o o o o o c n o o h ~ - c o i n i - < o c M i - r -c o E co W CD co CO CO co CO CM CO r h r h O CO * CO 8 co w co CD s, E CO 3 o CO h o CO in o co o co co o CO CM o CO o co o o CO o o o o o o o 8 8 8 8 8 8 8 o in o m o in o T CO CO CM CM T -8 o in CZ o O (N 6>j) US6OJIJU sn|djns |E;OI Table 6.7 Summary of nitrogen inputs for the Salmon River Watershed. 148 Nitrogen source kg-N % of total Manure 726 991 62.5 Inorganic fertilizer 297 356 25.6 Atmosphere 93 719 8.1 Septic systems 44 436 3.8 Total 1 162 502 Table 6.8 shows the relative surplus nitrogen from each source. The model is simplistic and does not reflect from which source losses like crop uptake occur. For the purposes of this comparison, it was assumed that crop uptake comes primarily from manure-N. The surpluses from manure, the atmosphere and septic systems are shown both "before" and "after" crop uptake. The surplus nitrogen from manure, therefore, is anywhere between 58 and 25% of the total surplus available for leaching. Atmospheric-N constitutes between 29 and 51% of the total surplus, and septic systems between 13 and 24%. After losses are factored in, sources of nitrogen other than manure become more important. Initially, septic systems, for example, accounted for about 4% of the total nitrogen inputs into the system. At the end of the calculations, septic systems may account for anywhere between 13 and 24% of the total surplus nitrogen in the system. The most substantial indication of potential environmental impact is nitrogen loading, or the kilograms of nitrogen applied per hectare. Figure 6.9 shows the surplus(deficit) loading by contributing area. Once again, the nitrogen sources are grouped into agriculture and septic systems. 149 Table 6.8 Summary of surplus nitrogen before and after crop uptake. Nitrogen source surplus nitrogen (in kilograms, with percentage in brackets) before crop uptake after crop uptake Manure 192 603 (58) 43 936(25) Atmosphere 93 719(29) 93 719 (51) Septic systems 44 436 (13) 44 436(24) Total 330 758 182 088 The nitrogen loading from agriculture ranged from a deficit of 2 kg-N ha-1 in C06, to a surplus of 212 kg-N ha"1 in SOI. Only two contributing areas were above the "critical" 100 kg-N ha"1 level. For the overall watershed the nitrogen loading was 57 kg-N ha"1. Spatially, the nitrogen varies throughout the watershed, with the highest occurring in the headwaters. Through the aquifer area, the loading remained about 60-70 kg-N ha"1. The exception was for S06, a small tributary draining north into the Salmon River mainstem, which had a surplus loading of 25 kg-N ha"1. In the Coghlan Creek headwaters, the agricultural loading is consistently around 40 kg-N ha"1. In the aquifer area of Coghlan Creek, the nitrogen loading increases sharply, from a deficit to a surplus of almost 75 kg-N ha"1. Septic system loading of nitrogen varied from 11 kg-N ha"1 in C02, to 62 kg-N ha'1 in C01. The nitrogen loading from septic systems for the overall watershed was 43 kg-N ha"1. Spatially, septic system loading varied throughout the watershed, though, not as much as agricultural loading did. In the Hopington Aquifer area, the loading was consistently between 40 and 50 kg-N ha"1, with the exception of S06. The loadings from agriculture and septic systems were combined into a weighted average to determine overall loading in the watershed (Figure 6.10). The highest rate of combined • - c CO o c o T J CO CO o CO Z J o CO o T J _tz cn cn CO CD CD £ CO JS CO o CD c o c CD o 5 TJ" Z w -* CD •— CO X J s I > ir cz o E $ T J 1 / 3 CO 0 E cn co c CD >^ ' Z J cr < c _ o 'a O J CD J Z -»— -«—• CO CD .E T J T J „ , CO CD -°- M o . C JO o O J -*-» O O CO t- CD -CZ ^ T J § O Q . T J Lfz Q . CD -g 2 co 3 Z — Q - 05 CO !=j 0 co .E co CO CD 0 l _ Z J co CD U 3 O t o c CO cn E CD -*—» cn 0 i _ >» ZJ cn ' o 3 +-» O D_ CD CO to < (T BL) N-B>i) BujpBO| uaBojjm (ipjiapjsnidjns 151 co to i CD CO < CO CD l _ CO CD c ZJ XI ' c o o >. XI T J CD x: CO w_ CD to CD > ^ LT C ' 3 O c r E < "cc c CO o CD 2> x: .E CL c o C O 1 C CD XJ £ CO o c o C T J CD CD 2 o . t i O ^ » •4-" CO O CD CO 0 T J CO CL XI 3 CO T J 0 C x> c o o 0 to E .2 O T J O .£ CO 0 l _ 3 O J O) c TI CO o TJ 0) C !5 E o o CO - C 15 k_ 0 O •c *kZ D D) CO co + + CO em x : E •55 CO > to to >> 0 co *^ 0 a 0) a . w (0 CO > c o E co CO CO W CO co CO CM CO o co cn o w CO o CO o co co o (O co o co CM o CO o co o o co g o o g o g o o 9 CM O 55 CO * CM (T BL| N-BM) Buipeoi ua6ojj|u sn|djns 152 loading occurred in contributing area SOI, the only contributing area in which the 100 kg-N ha1 level was surpassed. The remaining contributing areas ranged from 7 kg-N ha1 in C05 to 90 kg-N ha1 in S00. Through the Hopington Aquifer area, the nitrogen loadings ranged from 7 kg-N ha1 in C05 to 55 kg-N ha1 in C07. The agriculture component tended to be the larger contributor of nitrogen for contributing areas with the highest values of combined loading. 6.3.3 The relationship between nitrogen loading and water quality The surplus(deficit) nitrogen loading results were combined into the same contributing area groups used to examine the relationship between water quality and land use indicators in Chapter 5. Low-flow streamwater nitrate-N was graphed with the surplus(deficit) results in order to determine if loading could be related to the output of nitrogen into the stream, and Spearman Rank Correlation coefficients were calculated. Figure 6.11 shows agricultural and septic system nitrogen loading in relation to low-flow streamwater nitrate-N and Figure 6.12 shows the combined nitrogen loading in relation to stream nitrate-N. There does not appear to be a clear relationship between nitrogen loading and streamwater quality. Rather, there is a greater spatial lag between nitrogen loading and streamwater nitrate-N than there was for the other land use indicators used in this study. In the Coghlan Creek subwatershed, there is an increase in both agricultural and septic system loading from headwaters to mouth. When the interaction was examined through the use of statistics, the conclusions were again that no clear relationship exists. The nitrogen mass balance calculated with the census data clearly shows that some of the highest nitrogen loading has occurred, and continues to, in the Hopington Aquifer area where the streamwater nitrate-N values are highest (Section 6.2.3). Therefore, the lack of a clear relationship between the contributing area nitrogen loading and streamwater quality cannot 153 CO CO CD t— CO CO •I © c ° o co O co . sz TJ O s z f CO > in CO CO CD £ CO CD > ix CO c E £ Q E ° "CO cz o E co CO © c o CD CO CO r o r - TJ -— E E Z J2 "° CD co co + ± c . © 2 CD b *= t i CO ~ CO -t; CD CO 5 <| © CD CO <2 $ £ I © CO O CO TJ CO ZJ CO © > CO o O TJ ' c E co © CO CD «^ ' Z J cr TJ CL < i j • c o © £ co ^ o ^ < • p CD CZ c E o « 5 rj, 75. co -E zJ © o CO CO X ( 1 6LU) N-SIBJIJU J31BMLUB8JJS a> u i_ 3 O CO c 0) o .eg +—> c a> •g "co CD CD O-CO SZ 73 CD CL Q . O . CD D) a. CO E to cn CD CO £i O 3 CL z: <D cn CO < zo-ioa Z0-90O, so-t>oo* eo-ioo sis CO CD L _ CO cn e '•s M-2LS i= O O L L-0 IS 60-80S* Z0-90S* so-t>os» eos 20-LOS CO © ZJ CD ( Bi| N_6>|) 6uipBO| uaBoJim sn|dins 154 - i CD cn to 2 $ | H § 2 -8 tn o S E CO CO CD 2 > to -cTT 2-0 3 co E t> 2 0 H -J = X J s g "8 5 c d < 8 2 c * - CO o c co 0 2 co B cp 3 -E £ 03*-CD CO CD ^ CD • § . 0 ' • £= O  O "O 0 CO CO co 0 C " c 0 T J CO O CO l l £ CO CO 0 CO CO = CO •— r-— 0 .2 c ^co o o cz o c E co CO fl) 2 CO I 2- g> 8 3 CO TJ 0 += TJ C .2 -r CO CO 5 J2 £ E co 0 O -t; CO O c < .( "1 Bill) N -^JBJJjU J 3 ) B M LUB9JJ3 20- LOQ 20-1 OS CM CO 2 ZJ CO LL ( _BL| N-6>0 6u | p B O | uaBojjiu sn|djns 155 necessarily be used to conclude that land use is not having an effect on water quality. There are several reasons for this. The first, and most important, reason arises from the way in which the animal numbers for the contributing areas were derived (Section 4.4.3). Because the census data was not geographically fixed within each census area, it was assumed that both animals and crops were evenly distributed throughout the census area, perhaps resulting in either over or underestimations of nitrogen sources and sinks. Brisbin (1994a) did a sensitivity analysis for the Abbotsford waste management zone and determined that the results were most sensitive to changes in animal numbers. Remedies include overlaying the census areas with the Agricultural Land Reserve boundaries to determine where the majority of agricultural land is within each census area. A more comprehensive farm survey database would also result in a more accurate loading calculation. Septic systems are geographically fixed, and so the location of the nitrogen inputs is not in question. Rather, the manner in which the loading was calculated is. Essentially, the loading from each septic system is similar, based on the assumption of 3.5 people per household and the same sized tile fields. However, in medium to high density residential areas, the combined effluent plumes from the septic systems overwhelm the soil's natural purification capability and may also result in a nitrogen build up in the groundwater. A loading calculation which takes this into account may be more appropriate. An alternate way in which to calculate the nitrogen loading from both septic systems and agriculture is to use the entire contributing area, rather than the subsets of either cropped or residential area. This calculation would reflect the animal unit and septic system densities shown in Chapter 4. While the loadings are now much smaller, Figure 6.13 shows that the nitrogen loading more closely resembles the septic system and animal unit density, as well as the spatial pattern of nitrate-N in the stream. The combined nitrogen loading shown in Figure 6.14 156 ( H Bui) N-a;BJjiu jaiBMiuBajjs CD 1 E CD i _ CD J Z CD to o TJ C 0) p 0) CO 1 1 > o E -o CO o CD i= cz CO 0 ZJ ^ 3 Jfl to 0 o rt ^ 2 CO -*- c CO fO 0 tz co « co 2 _ CZ CO 0 "ZJ cr < c o •*—• CO c "a. o X 0 J Z CO CO0 k_ CO CO c 3 J 3 c o o rt ZJ o 5 +-» i_ § 1 TJ O 0 CO _ : rt m co e c 0 — •*-f TJ CO CO > o > C 0 0 > c | CO — 3 CO Q. CO 3 © co £ 0 c o 0 CO J Z o CO CO 0 1— CO CO > .E CC -*—< 3 CZ -a o "5 E o « 8 co 0 0 CO -t-1 .2 c 1:° CO 0 3 to 5 < i= ca denl ha) resi ped rce per crop 3 z i» O CD CL 0 ) z en ms 1 OJ o CD — ' o t« >i (/) > z o O CL 'k_ CD CD 05 < <0 • ; • ' 1 CD ' > • o ' 1 ' c ' • 1 CO • • i x : o • • o ; CM •+-o 2o-ioa ZO-900. 9 0 - f 0 0 » GO-1-00 CO CD S I S J, cz 1 f 1-2 IS O O U - O L S 60-80S* Z0-90S* 90-fOS» EOS 2O-10S 00 T — co" 0 fc_ 3 CO LL (L_BL| N-6>1) BujpBO| ueBoJim sn|djns 157 also shows a better relationship with the streamwater nitrate-N. These results are corroborated by the nitrogen loadings calculated with the census data. One final method by which to relate nitrogen to surface water quality is to calculate the amount of nitrogen in the streamwater as a measure of output from the system. Data from the eight regular sampling dates and the storm monitoring at Station 6 (hydrometric gauge site) were used to determine an annual weighted nitrogen loading in the stream. The 1994 median total loading at Station 6 was 98,000 kg-N per year or 23 kg-N ha1, based on the cumulative watershed area upstream from Station 6. The average total loading at Station 6 was 274,500 kg-N per year, or 64 kg-N ha'1. Because the measurements were more intensive during the high flow period the real value is likely between the median and mean values, and closer to the median. The surplus nitrogen inputs available for leaching, also based on the cumulative contributing area upstream from station 6, was 89,000 kg-N, or 21 kg-N ha"1. The nitrogen inputs and outputs in the Salmon River Watershed for 1994 are remarkably similar. However, there are several reasons why this may be coincidental. Firstly, the calculations are based on one year of data only. A series of yearly measurements would provide a statistical base from which to evaluate the apparent similarity between the two numbers. Secondly, the calculations were based on the assumption that any nitrogen which leaches into the groundwater ultimately flows into the Salmon River and its tributaries, and a related assumption that any nitrogen which reaches the stream comes from land use activities within the watershed. The Hopington Aquifer is situated only partly (two-thirds) within the Salmon River Watershed. It is possible that either nitrogen applied in the watershed leaves the watershed via the aquifer, or that activities on the aquifer outside the watershed contribute nitrogen to the Salmon River. Thirdly, this calculation does not consider the residence time of groundwater in the 1 5 8 d) J2 f | J= i— »— 5*5. Is* CO +-> fi 0 cn £ 4 0 § CD 3 -8 CD > E CD 0 W - . ° . ® c > c? c? •t- 0 t_ i _ c O CO O - 58 ^ CO JO c CD "7^ ( H BLU) N-aie-Uiu J a i B M i u e a J i s co vu c — CD -5 O !- Q-CO o c co X ° g 0 T J t; r Q) 2 ^ cn 5 c o ~ ° c ? 0 co CO 0 C J2 0 0 g | C i -8 I w § TJ J= CD CO .E OO -Q © O .E o J Z cn co 0 i _ CO OJ 1 E - Q *-< •— cn c CO E c o o 0 to o _ TJ 73 .E CO c o E 20-LOQ 20-lOS io o m o ( BL| N-6H) BUJPBOI uaBojjiu snjdjns co 0 i _ ZJ CO LL 159 Hopington Aquifer, or nitrogen contributions to the groundwater from years past. Finally, more intensive sampling of both discharge and nitrate-N concentrations in the stream would provide better data regarding nitrogen loading in the stream, as well as the variability throughout the watershed. 6.4 Partitioning nitrogen sources The land use dynamics in the Salmon River Watershed are such that residential areas are increasing, and agriculture is slowly shifting from commercial enterprises to small estate or hobby farms (Chapters 1 and 4). In order to determine the relative importance of various nitrogen sources, the surplus(deficit) nitrogen application was partitioned into septic systems and two components of agriculture, hobby and commercial farms. Based on the census data presented by Brisbin (1994a) for the North Langley waste management zone (Section 4.3.3), it was determined that hobby farms could be simulated by horse and sheep data, while commercial farms could be simulated by cattle, poultry and swine data, from now on referred to as all-other farms. This calculation did not include non-livestock operations. The manure nitrogen production, management losses and exports were calculated individually for the two agricultural components. Fertilizer application and atmospheric inputs were assigned to each component based on the ratio of their manure production. The final result was surplus(deficit) nitrogen, in kg-N, partitioned into septic systems and the two agricultural components by contributing area (Figure 6.15). Overall, septic systems account for 20% of the surplus(deficit) nitrogen, horse/sheep farms account for 12%, and all-other livestock farms for 68%. The ratio of sources varies more widely than this from one contributing area to the next. The septic system contribution ranges from 6 (in S00 and SOI) to 100% (in C06) of the total surplus. The horse/sheep contribution 160 CD J Z .E H O ZJ = -Q. CO TJ C CO C L CO "0" CZ CD o o o 0 no CO Ui o indi qen CO o tn i _ + ^ " i _ CD cn cn E < 0 CO "O >, 0 cn J Z o 2 += CD C L o .> =3 CC o c cn o o E f 5 2 5 CZ ~ — c TJ — 0 CO C 0 g CO V C O 3 £ ^ a-15 CD CZ J D ~ 0 "d —' 2 o < ± f o c ^ -Q b) 5-o cn H = 0 0 cn 5. § ZJ ~ £ 2 - £ ZJ co cn .—. cn cn co p co O I 2 H- 45 LO O x c o CO cn E « £ cn I 8- 5 cn 0 > r L cn cn CD .2 a) £ n 2 o 0 o = GO X < CO • 1 ' laffffi o m idson _ _ _ _ Davi H 1 mini ! ! o , , c ' cc • Cogh o i I S to CD 0 i _ ZJ cn (N-6>|) ua6ojt|U (uouap)sn|djns 161 ranges from 0 (in C06) to 25% (in S14) of the total. The all-other farms component, by far the largest contributor overall, ranged from 0 (in C06) to 88% (in S00) of the total surplus. Brisbin partitioned surplus(deficit) nitrogen for small and large farms (but not for septic systems) for the North Langley study area. Small farms contributed 17% of the total surplus(deficit), while large farms contributed the remaining 83%. These numbers are comparable to the relative contributions from horse/sheep farms and all-other farms, excluding septic systems. Horse/sheep farms contributed 15% of the total surplus, while all-other farms contributed 85%. 6.5 Comparison between data sets Brisbin (1994a) divided the Lower Fraser Valley into twenty waste management zones for which the inventory and nutrient balances were calculated (Brisbin 1994a). One of the zones, North Langley, approximates the Salmon River Watershed study area (Figure 4.3.3). The overall nitrogen loading calculated for the North Langley zone was 55 kg-N ha"1, which is comparable to the results of this study (Figure 6.16). The nitrogen mass balance calculated with the Agricultural Census data for the Salmon River Watershed resulted in the largest overall nitrogen loading from agricultural sources, 75 kg-N ha"1. This was expected because the unit nutrient production values (Table 6.1) had to be averaged, and were weighted towards the animal age and types which produced greater amounts of nitrogen. The contributing area mass balance result, 57 kg-N ha"1, was between the census mass balance and the North Langley mass balance. Septic system loading was determined to be 43 kg-N ha"1 for the contributing area mass balance, and 46 kg-N ha"1 for the census area mass balance. 162 Figure 6.16 Comparison of results from nitrogen mass balance calculation from three different data sets. Nitrogen Source • Septic system (kg-N per residential ha) • Agriculture (kg-N per cropped ha) — 1 0 0 1 7« Contributing area Census area North Langley Data set 163 6.6 Evaluation of the nitrogen mass balance calculation The model used in this study has a number of strengths as well as weaknesses. Because the model is essentially a simplified nitrogen cycle, the primary sources and sinks of nitrogen are easily quantified with reasonably accessible data. However, the simplification of the nitrogen cycle may result in the omission of significant nitrogen pathways. Specifically, the mineralization of organic nitrogen in the soil was not counted as a nitrogen source in this model. In the autumn soil conditions become ideal for the microbial breakdown of organic nitrogen in the soil into nitrate, the time at which nitrate is most susceptible to leaching (Addiscott 1988, Francis 1992). Even a field on which no crop has been grown, nor any nitrogen applied, can "leak" nitrate during the autumn (Addiscott 1988). The rate of mineralization and leaching is governed by rainfall and soil temperature (Gold, et al. 1990) Further to the above argument, because the model does not account for mineralization of organic nitrogen, it does not account for the contribution of nitrogen to the system from years past. Addiscott (1988) calculated the "half-life" of organic nitrogen in the fields at Rothamsted agricultural research station in England to be about 40 years. The possibility exists that the elevated streamwater nitrate-N levels are related to land activities of one decade or more ago. For example, the nitrogen loading calculated from the 1986 census data was considerably higher in the aquifer area than it was in 1991 (the agricultural loading decreased in one census area from 600 to 107 kg-N ha"1). It is possible that the current water quality is more strongly related, or soon will be, to the land activities of the mid 1980s rather than those of 1994. The assumption that only broiler chicken operations export manure, and only 30% at that, may be appropriate at the scale of the waste management zones used by Brisbin. However, the loadings calculated from the waste management survey data show that using the export rates reported in the survey can significantly lessen the loading of some individual farms. For the 164 Salmon River Watershed, this was most noticeable with all poultry farms, and with horse operations. The 100 kg-N ha'1 critical loading value for agriculture proposed by Brisbin (1994a) may not be appropriate in areas with highly permeable soils, high rates of irrigation or if septic systems contribute a large proportion of the surplus nitrogen. Soil texture can affect the rate of leaching due to its influence on the amount and rate at which water percolates, on rate of denitrification, and on ammonia retention (Muchovej and Rechcigl 1994). Cook (1994) suggested that nitrogen loading would be a more accurate indicator to use for determining land use-water quality relationships. The animal stocking densities calculated from the census data do not appear to be spatially related to water quality at nearby stream sampling stations (NB indicators derived from census data were not correlated to streamwater nitrate-N because the census boundaries do not coincide with contributing area boundaries). However, the nitrogen mass balance results show that the highest nitrogen loadings occurred in the Hopington Aquifer area where the highest streamwater nitrate-N values are measured. The results from the contributing area analysis show the opposite; animal densities were spatially related to streamwater nitrate-N while the nitrogen loadings were not. These differences are partly due to the way the animal numbers were derived for the contributing areas and to the differences in analysis boundaries (i.e. census area versus contributing area). Theoretically, a nitrogen mass balance calculation would provide a more accurate land use indicator because it takes into account factors such as crop uptake and export of nitrogen while animal stocking densities alone do not. In practice, a combination of the two kinds of indicators, animal and septic system densities and nitrogen loading, would contribute the most managerially useful information. Using both types of indicators, calculated from more than one data source, may supply a range of results which encompass what is really happening in the system and show areas which require more detailed investigation. 166 7. Summary and recommendations 7.1 Summary of research findings The goal of this study was to examine how the type, intensity and changes in urban and rural land use activities have affected streamwater quality in the Salmon River Watershed, Langley, B.C. The watershed has been experiencing non-point source nitrogen pollution of both stream and groundwater from the highly mixed land uses of residential, hobby farm and commercial farm activities. The following sections summarize the water quality and land use activities in the watershed as well as the link between them. 7.1.1 Spatial and temporal variability in water quality Water quality indicators were measured at eleven stations located throughout the watershed at eight times during 1994-1995. The results for each indicator were averaged for low-flow and high flow conditions. Low-flow was represented by the June, July and August measurements, and high flow by the November, February and March measurements. The overall quality of water in the Salmon River and its tributaries is good. Microbial counts were the only indicator which exceeded maximum allowable levels. The behavior of the indicators measured in this study are related to seasonal precipitation and stream flow patterns and spatial variability of the underlying geology and land use activities. The highest values for nitrate-N, chloride and specific conductance were typically measured during low-flow conditions when the groundwater contribution to the stream was greatest. Nitrate-N increased from headwaters to the Hopington Aquifer and then decreased further downstream. This pattern is related to intensifying land use from up to downstream and the contribution of nitrogen polluted groundwater through the aquifer. Chloride is higher up and 167 downstream of the aquifer due to the presence of glacial marine parent materials. However, the concentration of chloride increased through the aquifer, indicating the contribution of chloride from mixed land use activities in the aquifer area. Specific conductance showed a similar pattern as that of chloride. Conversely, ammonia-N and orthophosphate were highest during high-flow conditions at which time runoff from agricultural fields was greatest. Faecal coliform and streptococci counts were also greatest at high-flow. 7.1.2 Land use dynamics Land use in the watershed was characterized from four different sources: 1. land use maps; 2. a septic system database; 3. census data; and, 4. a waste management survey of individual farms and a survey of horse locations. Land use maps from 1979-1980,1989-1990 and 1994 were compared to determine changes in the spatial distribution of eight general land use categories. Currently, the watershed is fifty percent agriculture, twenty-seven percent undeveloped and 12 percent residential. The remaining 11% of the watershed is used for recreation, institutions, transporation and industry. Between 1979 and 1994, agricultural land decreased by 800 ha and residential areas increased by about 600 ha. Changes within each contributing area varied. The largest changes occurred in the Hopington Aquifer area and near the mouth of the Salmon River. The intensity of agricultural activities was measured in terms of animal numbers from the 1986 and 1991 Agricultural Census data and a survey of individual farms in the watershed. Between 1986 and 1991 the number of farms increased while the agricultural area decreased. The overall number of animal units in the watershed area decreased, while the animal unit density did not change significantly. The most significant change in animal numbers was related to animal type. Animals typically associated with larger commercial operations, such as cattle, 168 swine and poultry, decreased, while horses and sheep increased in number. These changes reflect a shift in land use activity from commercial to smaller hobby farms. Poultry farms had the highest animal stocking densities (up to sixty-five animal units per hectare) while dairy farms had consistently lower densities (all below three animal units per hectare). Horse and sheep farms had highly variable stocking densities which ranged from less than one to twenty animal units per hectare. The census and survey data were combined to derive stocking densities for the watershed as a whole and for individual contributing areas. The overall stocking density of the watershed was about 1.5 animal units per hectare. Individual contributing areas ranged from less that 0.5 to greater than 4.5 animal units per hectare. The higher densities were located in the headwaters and in the Hopington Aquifer area. Septic system density varies throughout the watershed with the highest densities located in the Hopington Aquifer area and near the mouth of the Salmon River in Fort Langley. The density of septic systems on outwash material reaches as high as 2 systems per hectare on the basis of contributing areas. The most vigorous septic system installation occurred in the mid-1970s at which time the number of septic systems grew by 1,000. By 1994 there were 3200 septic systems in the Salmon River Watershed and 500 on the Hopington Aquifer. 7.1.3 Spatial relationships between land activities and water quality There is a strong relationship between septic system and animal unit densities and streamwater nitrate-N in the upper half of the Salmon River mainstem, while the pattern of land use indicators does not match nitrate-N concentrations downstream from the Hopington Aquifer. In Coghlan Creek, septic system densities closely match the increase in streamwater nitrate-N, whereas animal unit densities did not vary at all in the subwatershed. Overall, when animal units 169 were partitioned into selected animal types, stronger relationships were found with livestock (i.e. horses, sheep and cattle) than with poultry. In Davidson Creek, the streamwater nitrate-N is most closely related to "other" animal unit densities. This suggests that agriculture, including both commercial and small farms, and septic systems are responsible for the deterioration of water quality in the Salmon River mainstem, while septic systems are the dominant source responsible for the elevated nitrate-N levels in Coghlan Creek. There was a difference in magnitude Of septic system density versus streamwater nitrate-N between the Salmon mainstem and Coghlan Creek. Possible explanations include the proximity of septic systems to the respective stream channels and to surface water monitoring stations, and the relative proportion of groundwater in each stream. A temperature profile of the two streams in the aquifer area shows that Coghlan Creek is colder than the Salmon mainstem in August. While both receive groundwater discharge, there is a greater proportion of groundwater contribution to streamwater in the Coghlan and therefore a greater contribution of nitrate-N from the aquifer. There were no statistically significant relationships between land use-water quality. However, due to the complexity of the underlying geology which influences the hydrology of the system and to the homogeneity of land use in the aquifer area a statistical analysis may not be appropriate. Land use indices which reflect the intensity of use are better indicators than type and area of use. This was demonstrated through the comparison of animal unit densities used in this study and the proportion of agricultural land in a contributing area used in a previous study. 7.1.4 Nitrogen mass balance The nitrogen sources and sinks in the watershed were quantified to determine the potential of nitrate-N leaching from the excess nitrogen application. The 1986 and 1991 170 Agricultural Census data were used to determine the dynamics of nitrogen loading, while farm survey data was used to determine the nitrogen loading on individual farms. The septic system database was used to determine nitrogen loading in residential areas. A combination of the data sources provided a measure of nitrogen loading by contributing area which could be related to streamwater nitrate-N. There was an overall increase in surplus nitrogen application from 1986 to 1991 even though one census area experienced a large decrease (from 600 to 100 kg-N ha1). A loading of 100 kg-N ha-1 is the level above which water moving below the rooting zone may be expected to have a concentration of 10 mg-N L'1, the drinking water standard for nitrogen. Other census areas on the Aquifer increased in surplus loading. The nitrogen loading from septic systems increased in all census areas. Spatially, the greatest surplus nitrogen loading occurred in contributing areas in the headwaters and in the Hopington Aquifer area. Agricultural sources contributed much greater surplus nitrogen in the headwaters, while both agriculture and septic systems were important in the aquifer area and toward the mouth of the Salmon River. Septic systems were more important than agriculture in two contributing areas of Coghlan Creek. For individual farms, sheep and horse operations had the highest surplus nitrogen loading. Dairy and non-livestock operations had acceptable surplus nitrogen loadings (<100 kg-N ha1) while poultry operations had deficit nitrogen loadings. In order to determine the relative importance of the contribution of various land use activities, the surplus nitrogen application was partitioned into septic systems and two components of agriculture, hobby farms and commercial farms. Hobby farms were represented by horse and sheep operations and commercial farms by all other animal types. Overall, septic systems accounted for twenty percent of the surplus nitrogen, hobby farms account for twelve percent and commercial farms for 68 percent. 171 There was no clear statistical relationship between surplus nitrogen loading and streamwater nitrate-N. However, the graphical analysis shows that while some of the highest surplus nitrogen loadings do occur in the Hopington Aquifer area, there is a considerable spatial lag before nitrate-N concentrations in the stream increase. A comparison of nitrogen loading with the other land use indicators used in this study showed that for the census areas, the nitrogen loading was spatially more closely related to streamwater nitrate-N that were animal unit densities. Coversely, animal unit and septic system densities calculated for contributing areas were more closely related to streamwater nitrate-N than was surplus nitrogen loading. The ideal study of land use impacts on water quality would, therefore, make use of both kinds of indicators calculated from more than one data source. The range of results determined in this way would likely encompass what is actually happening in the natural system. 7.2 Recommendations 7.2.1 Further research Comprehensive farm database The farm survey conducted in this study was focused toward large and commercial operations, and documented between fifty and seventy-five percent of the large farms in the Salmon River Watershed. According to Agricultural Census data for the North Langley waste management zone (Brisbin 1995) as many as forty-five percent of farms are small. These smaller, hobby, farms should be sampled and geographically referenced in order to determine their effect on streamwater quality. 172 Horticultural and mushroom industries This study focussed on the contribution of non-point source nitrogen from livestock and crop production in the watershed. The horticultural (greenhouse) and mushroom industries are growing in the Township of Langley. Greenhouses and mushroom houses may experience leakage of nitrogen from facilities which are poorly designed and built. Improper storage of manure piles at mushroom operations may be another source of nitrogen to stream and groundwater. Home fertilizers In this study, only the use of inorganic fertilizers by the agricultural industry was determined. The residential area on the Hopington Aquifer is increasing, therefore, the use of fertilizers for home lawns and gardens may also be an important source due to over-use and mishandling. Groundwater hydrology The sources and fate of nitrogen in the Salmon River Watershed may be more effectively documented if the groundwater flow patterns in the Hopington Aquifer and contribution to stream flow were better known. Tracer experiments would be useful for documenting groundwater flow patterns. Hydrometric measurements to establish base flow of Salmon and Coghlan will assist in determining the groundwater contribution to the stream. Detailed study on Coghlan Creek Coghlan Creek near its confluence with the Salmon River mainstem has been identified as the area in Salmon River Watershed most affected by land use activities related to non-point 173 source nitrogen pollution. Further investigation of nitrogen sources in this portion of the watershed may help in reducing nitrogen inputs into the system, and in the long term result in improving stream and groundwater quality. 7.2.2 Management recommendations Residential and agricultural activities are the primary sources of non-point source nitrogen pollution in the urban-rural fringe. In order to prevent further stream and groundwater degradation a number of management strategies for different activities may be used. Residential activities Septic systems are a significant source of excess nitrogen loading in the Salmon River Watershed. From an environmental perspective, the connection of all the houses on the Hopington Aquifer to municipal sewer mains is likely the best course of action. However, practical considerations, such as the expense of installing sewer mains, the reduced recharge to the aquifer, and increasing stormwater management problems, dictate that other alternatives also be available. For example: -the restriction of septic system density would help ensure that the natural capacity of the soil to treat septic effluents is not overloaded. -a septic system maintenance program, in which home owners are required to pump solids out of septic tanks regularly would minimized the number of malfunctioning septic systems. -alternative septic system technologies which remove nitrogen, may be more appropriate for highly permeable soils than traditional designs (Whitmyer, et al. 1991). -while distance between septic systems and water courses is prescribed by the Ministry of 174 Health, the regulation should be reassessed for areas like the Hopington Aquifer, which is comprised of coarsely textured outwash. Greater setbacks may help prevent untreated septic effluents from reaching stream courses. Agricultural activities The Agricultural Waste Management Code should be enforced on both commercial agricultural and hobby farms. Environmental guidelines for various agricultural activities have been produced (BCMAFF 1995, BCMAFF 1994, BCMAFF 1992). Encouraging farmers to follow the environmental guidelines will help minimizes losses of nitrogen to stream and groundwater through overuse and mis-handling of animal wastes and inorganic fertilizers. Because of the growing importance of hobby farms in the urban-rural fringe, small farm owners should be made aware of the Code and their responsibility to abide by it. Community manure composting facilities may help decrease the surplus nitrogen loading on farms with a smaller land base than that required to absorb the manure nitrogen produced by their animals. Watershed management plan The quality and quantity of water in the Salmon River Watershed and associated aquifers are affected by land use activities. Therefore, any efforts to protect the water resources and aquatic habitat should be integrated with a comprehensive land use plan. The Environmentally Sensitive Areas assessment of the Township of Langley (Cook, et al. 1993) should be incorporated into the watershed management plan. The most highly sensitive (ESA 1) areas should have restrictions on development, including maximum housing densities, alternate sewage and animal waste disposal. 175 8. L I T E R A T U R E C I T E D Addiscott, T. 1988. Farmers, fertilisers and the nitrate flood. New Scientist (8 October 1988): 50-54. American Public Health Association. 1985. Standard Methods for the Examination of Water and Wastewater. 16th ed. American Public Health Association, American Water Works Association, Water Pollution Control Federation, Washington, D.C. 1268 p. Anderson, G.D., A.E. de Bossu and P.J. Kuch. 1990. Control of Agricultural Pollution by Regulation, in J.B. Braeden and S.B. Lovejoy (eds). Agriculture & Water Quality: International Perspectives. Lynne Rienner Publishers, Inc., Boulder, CO. 224 p. Barry, D.A.J., D. Goorahoo, and M.J. Goss. 1993. Estimation of Nitrate Concentrations in Groundwater Using a Whole Farm Nitrogen Budget. J. Environ. Qual. 22:767-775. Bauder, J.W., K.N. Sinclair and R.E. Lund. 1993. Physiographic and Land Use Characteristics Associated with Nitrate-Nitrogen in Montana Groundwater. / . Environ. Qual. 22:255-262. BCMAFF. 1995. Environmental Guidelines for Horse Owners in British Columbia. B.C. Ministry of Agriculture, Fisheries and Food, Victoria, B.C. 83 p. BCMAFF. 1993. Environmental Guidelines for Dairy Producers in British Columbia. B.C. Ministry of Agriculture, Fisheries and Food, Soils and Engineering Branch. Abbotsford, B.C. 77 p. BCMAFF. 1992. Environmental Guidelines for Poultry Producers in British Columbia. B.C. Ministry of Agriculture, Fisheries and Food, Soils and Engineering Branch. Abbotsford, B.C. 70 p. Beale, R.L. 1976. Analysis of the Effects of Land Use and Soils on the Water Quality of the Salmon River Watershed, Langley. M.Sc. Thesis, Department of Soil Science, University of British Columbia, Vancouver, B.C., 243 p. Berka. CS. 1996. Relationships Between Agricultural Land Use and Water Quality in the Sumas River Watershed, Abbotsford, B.C. M.Sc. Thesis, Resource Management and Environmental Studies, University of British Columbia, (in press). Bertrand and Bulley. 1985. Manure Management Guidelines. B.C. Ministry of Agriculture and Food, Victoria, B.C. 39 p. Brady, N.C. 1990. The Nature and Property of Soils. 10th ed. MacMillan Publishing Company, New York. 621 p. 176 Brisbin, P.E. 1994. Application of Inorganic Fertilizers in the Fraser Valley. Prepared for the B.C. Ministry of Environment, Lands and Parks, Environment Canada-Fraser River Action Plan, B.C. Ministry of Agriculture, Fisheries and Food, and Department of Fisheries and Oceans. Brisbin, P.E. 1994. Agricultural Nutrient Management in the Lower Fraser Valley. Prepared for B.C. Ministry of Environment, Lands and Parks, Environment Canada-Fraser River Action Plan, B.C. Ministry of Agriculture, Fisheries and Food, and Department of Fisheries and Oceans. Burrough; P. A. 1986. Principle of Geographical Information Systems for Land Resource Assessment. Reprinted 1990. Clarendon Press, Oxford, England. 194 p. Burt, T.P. and N.E. Haycock. 1992. Catchment planning and the nitrate issue: a UK perspective. Progress in Physical Geography 16(4):379-404. Canadian Council of Resource and Environment Ministers. 1987. Canadian Water Quality Guidelines. Prepared by the Task Force on Water Qualtiy Guidelines, Ottawa, ON. Canter, L.W. and R.C. Knox. 1985. Septic Tank System Effects on Ground Water Quality. Lewis Publishers, Inc., Chelsea, Michigan. 336 p. Cherry, J.A. 1987. Groundwater Occurrence and Contamination in Canada, in M.C. Healey and R.R. Wallace (eds.). Canadian Aquatic Resources. Canadian Bulletin of Fisheries and Aquatic Sciences 215:387-426. Department of Fisheries and Oceans. Chilibeck, B., G. Chislett and G. Norris. 1993. Land Development Guidelines for the Protection of Aquatic Habitat. Department of Fisheries and Oceans, Habitat Management Division and B.C. Ministry of Environment, Lands and Parks, Integrated Management Branch. 128 p. Cook, K.E. 1994. An Evaluation of Water Quality and Land Use in the Salmon River Watershed, Langley, BC, using GIS Techniques. M.Sc. Thesis, Department of Soil Science, University of British Columbia, Vancouver, B.C., 252 p. Cook, K, A. Faulkner, P. Mooney, K. Hall, M. Healey, D. Watts, S. Brown, and H. Schreier. 1993. An Evaluation of Environmentally Sensitive Areas in the Township of langley. Volume I. ESA Analysis. Prepared for the Corporation of the Township of Langley. Westwater Research Centre, University of British Columbia, Vancouver, B.C. 86 p. and appendices. Corporation of the Township of Langley. 1994a. 1993/94 Langley Horse Industry Directory. Township of Langley, Economic Development Department. 45 p. Corporation of the Township of Langley. 1994b. Population and Growth. The Corporation of the Township of Langley, Community Development Department. Langley, B.C. 35 p. 177 Corporation of the Township of Langley. 1993. Langley Official Community Plan Bylaw 1979 No. 1842 Amendment (Rural Plan) Bylaw 1993 No. 3250. The Corporation of the Township of Langley, Community Development Department. Langley, B.C. 35 p. Crawford, P. 1993. Preserving rural character in an urban region, rural planning in the Township of Langley. Plan Canada (March 1993):16-23. Dakin, A. 1994. Groundwater resources of the basins, lowlands, and plains, in Groundwater Resources of British Columbia. B.C. Environment, Water Management Division, Hydrology Branch, Groundwater Section. Victoria, B.C. -. 9.1-9.78. Dojlido, J.R. and G.A. Best. 1993. Chemistry of Water and Water Pollution. Ellis Horwood Limited, Chichester, England. 363 p. Francis, D.D. 1992. Control mechanisms to reduce fertilizer nitrogen movement into groundwater. / . Soil Wat. Cons (Nov/Dec):444-448. Freeze, R.A. and J.A. Cherry. 1979. Groundwater. Prentice-Hall, Englewood Cliffs, NJ. 604 P-Gartner-Lee Limited. 1992. Final Report, Fraser Valley Ground Water/Drinking Water Study. Prepared for the Ministry of Health, Environmental Health Protection, Victoria, B.C. 51 p. and appendices. Gold, A.J., W.R. DeRagon, W. Sullivan, and J.L. Lemunyon. 1990. Nitrate-nitrogen losses to groundwater form rural and suburban land uses. J. Soil Wat. Cons. Mar/Apr:305-311. GVRD Strategic Planning. 1996. Greater Vancouver Key Facts: Statistical Profile of Greater Vancouver, Canada. Greater Vancouver Regional District, Strategic Planning Department, Vancouver, B.C. 127 p. GVRD Strategic Planning. 1995. Greater Vancouver Key Facts: Statistical Profile of Greater Vancouver, Canada. Greater Vancouver Regional District, Strategic Planning Department, Vancouver, B.C. 127 p. Hall, K.J., H. Schreier, and S.J. Brown. 1991. Water Quality in the Fraser River Basin, in A.H.J. Dorcey and J.R. Griggs (eds.). Water in Sustainable Development: Exploring Our Common Ruture in the Fraser River Basin. Westwater Research Centre, University of British Columbia, Vancouver, B.C. 288 p. Halliday, S.L. and M.L. Wolfe. 1991. Assessing Ground Water Pollution Potential from Nitrogen Fertilizer using a Geographic Information System. Water Res. Bull. 27(2):237-245. Halstead, E.C. 1986. Groundwater Supply; Fraser Lowland, British Columbia. National Hydrology Research Institute. Paper # 26,1 WD Scientific Series # 146. NHRI, Saskatoon, SK, 80 p. 178 Harper, C.R., W.J. Goetz and C.E. Willis. 1992. Groundwater Protection in Mixed Land-Use Aquifers. Environmental Management 16(6):777-783. Health and Welfare Canada. 1989. Guidelines for Canadian Drinking Water Quality. Prepared by the Federal-Provincial Subcommittee on Drinking Water of the Federal-Provincial Advisory Committee on Environmental and Occupational health. Ministry of Supply and Services. Ottawa, Canada. He, C , J.F. Riggs and Y.-T. Kang. 1993. Integration of geographic information systems and a computer model to evaluate impacts of agricultural runoff on water quality. Water Res. Bull. 29(6):891-900. Hem, J.D. 1985. Study and Interpretation of the Chemical Characteristics of Natural Water. 3rd ed. US Geological Survey Water Supply Paper 2254. Washington, DC. 263 p. Howard Paish & Associates. 1980. Cooperative Management of Watershed andSalmonid Production, prepared for Department of Fisheries and Oceans, Salmonid Enhancement Program. Vancouver, B.C. 38 p. Kalkhoff, S.J. 1993. Using a geographic information system to determine the relation between stream quality and geology in the Roberts Creek Watershed, Clayton County, Iowa. Water Res. Bull. 29(6):989-996. Keeney, D. 1986. Sources of nitrate to ground water. CRC Critical Reviews in Environmental Control 16: 257-304. Keeney, D.R. and T.H. DeLuca. 1993. Des Moines River Nitrate in Relation to Watershed Agricultural Practices: 1945 Versus 1980s. J. Environ. Qual. 22:267-272. Kerr, A.M. 1984. A Survey ofWellwater Quality in the Hopington Area of Langley with Regard to the Health Hazard of Nitrate Induced Methemoglobinemia. Report prepared for Central Fraser Valley Health Unit, B.C. 17 p. and appendices. Kowalenko, C.G. 1987. An evaluation of nitrogen use in British Columbia agriculture. Technical Bulletin 1987-3E. Agriculture Canada, Research Branch. Ministry of Supply and Services. Ottawa, ON. 37 p. Kwong, J.C. 1986. Groundwater Quality Monitoring and Assessment Program - The Occurrence of Nitrate-Nitrogen in Groundwater in the Langley-Abbotsford Area. Memorandum Report, B.C. Ministry of Environment, Water Management Branch, internal report to Mr. A.P. Kohut, Groundwater Section. File 0329563. Volume 4, 7 p. and attachments. Libby. L.W. and W.G. Boggess. 1990. Agriculture and Water Quality: Where are We and Why? in J.B. Braeden and S.B. Lovejoy (eds). Agriculture & Water Quality: International Perspectives. Lynne Rienner Publishers, Inc., Boulder, CO. 224 p. 179 Luttmerding, H.A. 1980. Soils of the Langley-Vancouver Map Area. Volume 1 Soil Map Mosaics and Legend, Lower Fraser Valley (Scale 1:25 000). Report No. 15 British Columbia Soil Survey. British Columbia Ministry of Environment. McCallum, D.W. 1995. An Examination of Trace Metal Contamination and Land Use in an Urban Watershed. M.Sc. Thesis, Department of Civil Engineering, University of British Columbia. McCoy, E .L . , C.W. Boast, R.C. Stenhouwer and E.J. Kladivko. 1994. Macropore Hydraulics: Taking a Sledgehammer to Classical Theory, in R. Lai and B.A. Stewart (eds.). Soil Processes and Water Quality. Lewis Publishers, Boca Raton, Florida. 398 p. Meybeck, M. 1982. Carbon, nitrogen, and phosphorus transport by world rivers. American J. Sci. 282(4):401-452. Ministry of Health and Ministry Responsible for Seniors. 1993. from the Health Files. Number 5, March 1993. B.C. Ministry of Health and Ministry Responsible for Seniors, Victoria, B.C. 1 p. Muchovej, R.M.C. and J.E. Rechcigl. 1994. Impact of Nitrogen Fertilization of Pastures and Turfgrasses on Water Quality, in R. Lai and B.A. Stewart (eds.). Soil Processes and Water Quality. Lewis Publishers, Boca Raton, Florida. 398 p. Ontario Ministry of Agriculture and Food. 1976. Agricultural Code of Practice. Ontario Ministry of Agriculture and Food, Ontario Ministry of the Environment, and Ontario Ministry of Housing. Toronto, ON, ??p. Osborne, L.L. and M.J. Wiley. 1988. Empirical Relationships Between Land Use/Cover and Stream Water Quality in an Agricultural Watershed. J. Environ. Management 26:9-27. Piteau & Associates. 1991. Hydrogeological assessment of Aldergrove Aquifer, Aldergrove, B.C. Report to the Corporation of the Township of Langley. 38 p. and maps. Salmon River Watershed Management Partnership. 1995. Cooperative Watershed Management for the Salmon River in Langley - the Ecosystem Approach. Salmon River Management Partnership, Langley, B.C. 2 p. Sawicki, J. and G. Runka. 1990. Soil Degradation and and Rural Land Use Change, Uplands of Langley and Matsqui Municipalities - Fraser Valley. ARDSA Project 23010. 96 p. Sawicki, J. and G. Runka. 1986. Land use classification in British Columbia. Prepared for the Ministry of Agriculture and Food, Soils Branch and Ministry of Environment, Surveys and Resources Mapping Branch. Victoria, B.C. MOE Manual 8. 33 p. 180 Schreier, H. 1995. Hopington Aquifer, Langley, B.C. Preliminary Report on the Groundwater Survey. Prepared for the Engineering Department, Corporation of the Township of Langley. Sharpley, A.N., S.C. Chapra, R. Wedepohl, J.T. Sims, T.C. Daniel, and K.R. Reddy. 1994. Managing agricultural phosphorus for protection of surface waters: issues and options. /. Environ. Qual. 23:435-451. Spalding, R.F. and M.E. Exner. 1993. Occurrence of Nitrate in Groundwater - A Review. / . Environ. Qual. 22:392-402. Statistics Canada. 1991a. Agricultural Census Data for 1991. Statistics Canada, Ottawa, ON. Statistics Canada. 1991b. GEO: User Guide for Enumeration Areas Reference Map Series. Statistics Canada, Ottawa, ON. 8 p. Statistics Canada. 1991c. Population Census for 1991. Statistic Canada, Ottawa, ON. Statistics Canada. 1986. Agricultural Census Data for 1986. Statistics Canada, Ottawa, ON. Stednick, J.D. 1991. Wildland Water Quality Sampling and Analysis. Academic Press, San Diego, CA. 217 p. Swain, L.G., B. Phippen, H. Lewis, S. Brown, G. Bamford and D. Walton. 1995. Water Quality Assessment and Objectivies for the Fraser River From Hope to Sturgeon and Roberts Banks, First Update. Technical Appendix. B.C. Ministry of Environment, Lands and Parks. 418 p. and figures and tables. Swain, L.G. and G.B. Holms. 1985. Fraser-Delta Area. Fraser River Sub-basin from Hope to Kanaka Creek Water Quality Assessment and Objectives. Technical Appendix. Water Management Branch, Ministry of the Environment, Province of British Columbia. 193 p. Waite, T.D. 1984. Principles of Water Quality. Academic Press, Inc., Orlando Florida. 289 p. Waite, D.E. 1977. The Langley Story: An Early History of the Municipality of Langley. Don Waite Publishing, Maple Ridge, BC. 280 p. Walker, W.G., J. Bouma, D.R. Keeney, and P.G. Olcott. 1973. Nitrogen Transformations During Subsurface Disposal of Septic Tank Effluent in Sands: II. Ground Water Quality. J. Environ. Quality. 2(4):521-525. Water Quality Guidelines Task Group. 1994. A Framework for Developing Goals, Objectives and Indicators of Ecosystem Health: Tools for Ecosystem-Based Management. Prepared by the Water Quality Guidelines Task Group of the Canadian Council of Ministers of the Environment. 30 p. 181 Watts, R.D. 1992. A GIS Evaluation of Land Use and Fish Habitat in the Salmon River Watershed - Langley, B.C. M.Sc. Thesis, Resource Management Sciences, University of British Columbia, Vancouver, B.C. 156 p. Westwater Research Centre and Sustainable Development Research Institute. 1994. The Basin Ecosystem Study: An Integrated Ecosystem Study of the Lower Fraser River Basin Annual Report 1993-1994. The Westwater Research Centre and The Sustainable Development Research Institute, University of British Columbia, Vancouver, B.C. 57 p. Wylie, B.K., M.J. Shaffer, M.K. Brodahl, D. Dubois, and D.G. Wagner. 1994. Predicting spatial distributions of nitrate leaching in northeastern Colorado. / . Soil Water Conserv. 49(3):288-293. Personal Communication Dr. Ken Hal Professor, Civil Engineering, University of British Columbia, Vancouver, B.C. Pete Scales Environmental Manager, Township of Langley Dr. Hans Schreier Professor, Soils Department, University of British Columbia, Vancouver, B.C. Adrienne Tsou GIS Technician, City of Abbotsford r 182 A P P E N D I C I E S 183 Appendix 1 Determination of water quality for detailed sampling of Coghlan Creek near where it joins the Salmon River mainstem, August 1994. Portion of stream sampled Stream Watershed boundary Aquifer boundary Stream sampling station 3 p jhate CD L _ co O tz B ° Z o f— t \ CO CO CO 1 CD \J SE o C J Sample Nitra Orth (mg/ Spec cond CO 3 Tern (deg 1 (Station 5) 6.948 0.049 140 15.5 2 (seepage) 0.000 0.057 125 13.9 3 (seepage) 2.595 0.028 140 15.9 4 (seepage) 6.124 0.043 130 11.4 5 (seepage) 3.599 0.048 130 16.6 6 (seepage) 36.440 0.050 340 15.1 184 in o o CO ZJ u. JZ! 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D W t -CD a> b. O c co o O CD CD O o io T J ' i a T J CD C 'E a> CD T J •5 c T J C 191 ca n CD T* co CO o I (0 0) > Lr c o E CO CO CD -C 0 O to *-E as CO -Q CD 4= co co o (0 o S ! i ? co c c CD Q . 2 O (O C CO 0 © CO 1 < CD LO Q 2 X TJ c CD CL o_ < Tf Cf) Tt CM CM O ) c 3 co S3 a> CO o O £ 55 .2 - O 13 E CO 1 T J T J T J T J T J T J T J T I T J T J T J | C C C C C C C C C C c l • D T 3 T 3 T J T 3 T 3 T 3 T 3 T3 T J T D C C C C C C C C C C c l T J - O T S T J T J T J T J T J C C C C C C C C * CM s T - i - n in to ^ o oi * co s s N - h - h -O T f C M L O C O O J C M C O i - C O T f l f i C D i - N W S N S S N f f l N N C O C O C O L O i - L O C O C M i - m t o N O c o L O W T J T J T J T I T J T J T J T J C C C C C C C C T 3 T 3 T 3 T 3 T 3 T 3 T 3 T ! C C C C C C C C CM IO O O CO CO + + T - Tf s ro i - n o o o O T - T -CO CO CO CO CO CO + + + + + + O C O C O C O O C M T f L O O O O O T - * - T - ^ COCOCOCOCOCOCOCO co T -CO CO CM CO LO m co CO T J T3 c c T J T J C C Tf o O + co h-o o O O + + CM CO O O a o + + T - in o o O O LO O cd 5 00 00 CM I N O N T f t D C O C N T -CJ) a> h_ O c re j= co o O OJ LO a; a> 6 c o CO •g '5 Q T J CJ) C 'E CJ) •55 T3 •5 c T3 C 192 L O C O C O to ZS \ _Q CD L L T * O ) O ) O \ (0 CD > Lr tz o E (0 CO CD CD to . I? CO CD CD CO •i= CO CO JD T ? - 2 . CD C ^- t: x o 3 & c o to c CO +-> c CD E CD fc 3 i— (/) Q) CO QJ CD Q E X T3 c CD C L C L < T t O) 5" CO CO c 1 « ja o> ' C ;= •J2 CD O O .2 ja « E CO c L O T t c o e o e o N c o N Is- co O) o co oo cq cq c b c o ' c o s c D c d c o c o o ) c o c M o o < t 5 n s c M c o L O c o c o c o T t e M o o o o o o o o c c c o L O i n c o s n i n T J T J T J T J T J T J T J T J C C C C C C C C s - o o o o o o o s i n c o N c o c o o i n CD N N N N CO CO N • O T J T J T J T J T J T J T J C C C C C C C C T J T J T J T J T J T J T J T J C C C C C C C C T J T J T J T J C C C C co r--co co co co CM I O o o CO CO + + io co O O) co co O co TJ-o o 0 - L O T J T J c c o o LO r~-T J T J C C T J T J c c T J T J C C T t o O + co r-_ O O O + + CM CO O O o o Tt i— O J T — co O O O O r - i -CO CO CO CO CO CO + + + + + + + + O C O C D O O O C M T t L O TT LO O O O O i - i - i - T - O O C O C 0 C 0 C 0 C O C O C O C O O O co 00 CO So ° l o 00 CO •c LO co CM S O J N T f C O C O N f -CD CD o c JS J Z C D o o CD CD o c o CO T J •« Q T J CD c 'E £ QJ T J o c . II T J 193 LO CO CO cr-ee 3 I— JQ CD O) CO o I CO CD > ir c o E co CO CD SZ CD E CO ZJ _ CD co O 2 co CD CD CO — CD CD CD • t i C CD CL T3 CD o CO E _ 2> a. CD CO o g E CD E 3 2 co 7D CD Q E X T J c CD CL CL < 3 < I t CM CO g =j X I *t_ •E o O .2 xi to E CO I co o T - CM T - o co co oi q S C O C O C O C O C O N S co i - l O C O C N ' t C O C M i - i n CM T t T f i r i i n i r i i n i n i n co ^ I O q c q N o c q c q c o T-T - ' i - ' c M ' i - ' i - ' c M ' c M l r i C\i T-" O l C O ' t O C O ^ O l N i r i c d i ^ c b c o ' i ^ c d o o o o o o o o o 0 0 ) 0 " c 3 > C 3 > C ) C M L r i C M I - C M T - T - C N C M C N o i n o m o i n c o i n d CO C D t f l / i L f i N c d C M T - T - I - I - 1 - 1 - 1 -m O m O O T J CO S CO IO N C i n o N " c d • O T 3 T J T S T J T 3 T 3 T 3 C C C C C C C C CM in o o CO CO + + O O CO CO + + o c o o o CO CO N O l r - O O O T~ T-CO CO CO CO + + + + c o c o o C M ' t m O O T- T- T- T-CO CO CO CO CO CO E CO to c E DC c o E co CO m co o o c d c b o o i n c d o o i n c d X J T J c c 1^-o o + co r» o o O O + + CM CD O O O O + + i - i n o o O O 0 0 i n CM i n in" °\ c o o It i n CM O Q N O ) N * C O < O W T -CO CO o c CO o O co i n XL co OJ O c o CO T J "15 Q 194 L O C D C D CO ZJ I J D CD L L I r f o> O) O CO CD > Lr c o E CO oo CD CD —I | E E § CO CD CO c CO E CD C L CO CD c o o C J o .g ° X J S 5 CD O CO C L ° CO C + i •2 g 03 E .g CD E r5 Q CD Q E CM X T J C CD o_ C L < T f CO < I Tf <M CO CM CJ) c J 3 OJ - = is cd o O .2 J 2 td E CO g o o o o o o o t O O o l C M L O L O O C J J C O C M C O O S CM Tf CO CD LT) i - O) N CO Tf T J T J T J T J T J T J T J T J T J T J T J C C C C C C C C C C c l T J T J T J T J T J T J T J T J C C C C C C C C O O CO LO Tj- r- Tf co CO -i-s01 co T J T J C C O CO CO OJ O O CO CM O LO CO O T f T f CM T - CO T J T J T J T J T J T J T J T J C C C C C C C C T J T J T J T J T J T J T J T J C C C C C C C C T J T J T J T J T J T J T J T J C C C C C C C C CM LO o o CO CO + + T " T f N O l T - CO O O O O T - i -CO CO CO CO CO CO + + + + + + O C O C O C O O C M T f L O O O O O i - i - i - i -C 0 C 0 C 0 C 0 C 0 C 0 C 0 C 0 E CD to c cd E cd c o E cd CO CM CM co h-O OJ N- O T J T J c c TJ TJ c c T f o o + co r-O o o o + + CM CO o o o o + + i - LO o o o o o co CM £1 -2 •8 CM o Q §1 S O J N T f C O C D O j T -CO CO k. o c j d J Z CO o o O) LO CD CD o c o CO T J '1 Q T J CD c "E a> aS T J o c T J c 195 CD u CO o CD O to T: = 8. O CO U 0 O -p o 5 CD U j= CO CD O t z 2 o CO CL o 2 c £ •s § .! § £ 8 0 CD Q E CO CNJ C M CO . c X I (1) • = !5 •g CO o O .2 xi to E CO | O O O O O O O T - O O O I C O C M N C O O N n N T - T - o a co C D s oo m co " • " C M C O i - l T J T J T J T J T J T J T J T J T J T J T J I c c c c c c c c c c c l T J T J T J T J T J T J T J T J C C C C C C C C O co CM O T - C O T - T J L O C O i - C O C O C T -o s o n m o s T j co f <t i - N c T J T J T J T J T J T J T J T J C C C C C C C C T J T J T J T J T J T J T J T J C C C C C C C C T J T J T J T J T J T J T J T J C C C C C C C C CM in O O C O C O + + 1 - T j -O o C O C O + + o co o o C O C O I"- CO r- CO O O i - T -C0 C O C O C O + + + + C O C O O C M O O 1 - T - T - T -C O C O C O C O C O C O in T J T J c c C O C O C O T J -O 1 -co r--T J T J c c T J T J c c T J T J c c o o + co Is* o o o o + + CM CO o o o o + + T - in o o o o o CM C O C O CM o Q + T— o Q N O ) S ^ C D ( O W T -cu cu o c IS x: CO o o co m cu cu O c o CO T J ' c l Q T J cu c 'E d) cu T J •s c T J c Appendix 15 Determination of water quality for streamwater samples collected during three storm events in the Salmon River Watershed. CO E CD E F 2> "t» 8 E CO E 6 CO E. Z i a Z I o 3 I CL CO CO o T J Storm 1 20-Oct-94 9:00 0.31 0.024 0.018 9.4 3.860 145 7.10 8.6 20-Oct-94 17:00 0.35 0.013 0.029 9.8 3.400 150 7.12 8.4 20-Oct-94 23:00 0.38 0.025 0.041 10.1 3.170 153 7.02 11.7 21-Oct-94 8:00 0.38 0.016 0.034 10.3 2.840 142 7.04 26.2 22-Oct-94 23:00 0.40 0.013 0.037 9.6 2.840 144 7.15 10.5 26-Oct-94 11:00 0.43 0.012 0.059 10.8 3.030 146 7.10 12.8 26-Oct-94 17:00 0.45 0.048 0.047 10.5 2.420 144 7.11 11.8 torm2 29-Oct-94 23:00 0.36 0.037 0.048 9.1 2.362 124 7.11 14.4 31-Oct-94 1:00 0.39 0.000 0.044 9.2 2.243 124 7.14 35.7 31 -Oct-94 8:00 0.70 0.083 0.088 8.8 2.035 106 6.71 15.6 31-Oct-94 17:00 1.00 0.404 0.242 7.8 1.963 93 6.55 15.3 l-Nov-94 8:00 0.58 0.160 0.131 6.4 2.249 98 6.68 17.8 3-Nov-94 23:30 0.39 0.021 0.058 7.8 2.351 116 6.91 12.2 6-Nov-94 9:00 0.41 0.004 0.071 6.8 2.358 104 6.99 13.1 7-Nov-94 10:00 0.52 0.068 0.102 6.6 2.261 98 6.93 14.4 8-Nov-94 11:00 0.55 0.057 0.089 6.4 2.144 97 6.85 14.5 9-Nov-94 11:00 0.85 0.139 0.146 6.3 2.196 90 6.92 13.5 torm 3 29-Nov-94 11:00 1.40 0.271 0.115 7.6 2.032 80 7.09 nd 29-Nov-94 22:00 1.58 0.287 0.121 6.4 1.950 70 7.13 nd 30-Nov-94 10:00 1.65 0.235 0.084 5.8 2.063 65 7.18 nd 30-Nov-94 21:00 1.20 0.215 0.054 5.8 2.328 86 7.23 nd Appendix 16 Enumeration areas in the Salmon River Watershed for which 1986 and 1991 Agricultural Census data was collected 1986 1991 Census enumeration enumeration area area(s) area(s) 1 009-003 008-072 009-251 2 009-253 009-204 3 009-010 008-206 009-016 008-217 4 009-255 008-216 5 009-053 008-253 009-064 008-256 6 009-018 008-254 7 009-060 008-255 8 009-262 008-258 009-263 008-259 9 009-062 008-260 009-063 008-261 10 009-256 008-402 009-259 008-403 009-301 008-404 008-405 008-406 11 009-306 008-409 009-323 008-410 009-324 008-458 12 009-264 008-451 13 009-269 008-453 009-270 008-457 009-303 14 009-368 008-507 198 to 3 ±i 3 ,o < T J 0> J Z (0 I QJ •co-co > if c o E CO CO 0> CD C L T3 O E E o o >% J3 t/T k_ 0) E L _ to T J 'CO E CD *3 CD .2 £ O CO (1) E Z J c c 0) E cu CO to c CO co E °J E " C O $ >< T J CZ CD Q _ C L < CO c CD E E o O CD to e c£ o C L tn CD o3 16 oc L. T J CD •*—< o O to z tz o o To " C CO C L T J 0 C 75 CD Q T J 0 CD ' £ CD •*—< _c T J CD o k_ ' « be E E to i Z J QJ Z ti CD o T J k - (— g . l CO CD 2 CO t QJ J2 O CO CD k _ O E c CO C O CZ to o CZ to c o 'in to "E E o O CO o X CD > ir c o E to C O to CD to to CD k. T J T J CO o o e- o co o m co co to co io o o o CO o S co co o o CO C O T - 1 - 1 - Tf i - CM C N T— i — L O i - T - c O T - l f l T - T - 0 ! O f M L O ( O N O C M C M L O C M C O C M C O O ( N CO CM C O O 3 T— C M TJ -| to CO CD S2 to S co 2 1 CD 1 •4—« C O 2 CD CO "o S CO rn -a 9 J= c CO 2 k - CD "S •= -S oj <q o •-CD = 2 J = > IE CQ O to k _ CD o Z J T J 10 O > > Q -0) t>< i co CD • 3 co k -3 C O J Z CO O O - L U C O Q X I CO C D C O C M CM CM 199 Appendix 18 Survey used for the 1994 Agricultural Waste Management Survey of the Salmon River Watershed. Date: GENERAL INFORMATION Farm Name: Address: ', Telephone No.: Owner: ; Operator: Type of Operation: Total Size: Acres. Leases Acres to . , Rents Acres From Area Used for: Crop Production (Specify crops) -Crop Area (in Acres) Yield and Protein Levels Grazing: Acres. Feedlots: Acres. Buildings: Acres. Number of Animals (type, and annual range or average): Comments: 200 Appendix 18 continued (ii of iv) MANURE APPLICATION INFORMATION Manure Production per Year: Import of Manure per Year: Yes No Amount Export of Manure per Year: Yes No Amount Manure Storage: Permanent (concrete) Covered Uncovered Concrete Earthen Under-cage Storage Under-pen Storage Capacity of Facility (tons or months): Physical Dimensions: Field Storage Covered Uncovered Application (Specify amount, area, method and crop): Disposal Season: From To On-Farm Acres Amount: Crop: Method: 201 Appendix 18 continued (iii of iv) Off-Farm (Specify location): Acres Amount: Crop Method: Contingency Site (Specify location): Acres Amount: Crop Method: MISCELLANEOUS INFORMATION Handling of Mortalities: On-Farm Off-Farm (Specify Location): Location: Method: : Composting Facility: Covered Uncovered Materials Composted (list them): Silage Milk Parlour Yard Runoff To Tile Field To Manure Pit To Surface (No Collection) To Drainage Ditch 202 Appendix 18 continued (iv of iv) Chemical Fertilizer Application: Type: Crop: Amount: Frequency: Type: Crop:. Amount: Frequency: Pesticide Application: Yes No Disposal of Containers (Specify where): Irrigation System: Type: Water Source: Area Irrigated: Acres. Frequency: Sewage Disposal: Sewer Connection Tile Field Date Installed: Drinking Water: Municipal Well - Depth: Fuel Tanks: Above Ground Underground Installed in 19 . If underground, is it >250 L volume? Yes No Are your tanks registered with the fire department? Yes No Diagram and Rough Dimensions of Facilities (use reverse if necessary): Appendix 19 Survey used for Agricultural Waste Management Survey of Horse Operations in the Salmon River Watershed Date . . G E N E R A L INFORMATION Farm name: . ,. Address: Owner: ' Operator: . _ . . Operation: . . . . ,• Total s ize: Acres Leases Acres to: . . . . Rents Ac res from: Areas used for: Grazing: Acres. Feedlots: Acres Buildings: Acres. Animals: Type Number Annual range/average Comments: M A N U R E APPL ICAT ION INFORMATION Manure production per year ,. . . . Export? ^ _ _ Y e s _ _ N o Amount: To whom/where? , Manure storage: Permanent Field . Covered Uncovered Concrete Earthen Under-pen Capacity (tons/month) . Physical dimensions Appendix 19 continued (ii of ii) Application: Disposal season: From: To: On-farm Acres Amount: Location: Crop: Method: Off-farm Acres Amount: Location: Crop: Method: Contingency: Acres Amount: Location: Crop: Method: M I S C E L L A N E O U S INFORMATION Handling of mortalities: On-farm Off-farm Location: Method: Composting facility: Covered Uncovered Materials: Pesticide application: Yes _ _ No Disposal of containers (where): Irrigation system: Type: Water source Area: Acres Frequency: 205 Appendix 20 Agricultural Waste Management Survey database structure. Structure for database C : \ S A L _ G E N . D B F Number data records: 126 Name Type Width Dec Description F A R M ID Character 6 N Farm number, unique identifier 1 ML NUM Character 15 N Master Legal map number 2 F A R M N A M E Character 35 N Farm name 3 OWN1 LN Character 25 N Owner 1, last name 4 0 W N 1 F N Character 10 N Owner 1, first name 5 O W N 2 LN Character 15 N Owner 2, last name 6 O W N 2 FN Character 10 N Owner 2, first name 7 O P E R 1 LN Character 15 N Operator 1, last name 8 O P E R 1 FN Character 10 N Operator 1, first name 9 O P E R 2 LN Character 15 N Operator 2, last name 10 O P E R 2 F N Character 10 N Operator 2, first name 11 H O U S E Character 10 N House number 12 S T R E E T Character 20 N Street name 13 R R B O X Character 8 N Rural route or postal box number 14 CITY Character 15 N City 15 P O S T A L C O D E Character 7 N Postal code 16 P H O N E Character 8 N Phone number 17 W A T E R S H E D Numeric 2 N Watershed 18 O P E R T Y P E Numeric 2 N Operation type 19 S IZE Numeric 8 2 S ize (ha) 20 L E A S E A R E A Numeric 6 2 Area leased to others (in hectares) 21 L E A S E T O Character 25 N Area leased to 22 R E N T A R E A Numeric 6 2 Area rented from others (in hectares) 23 R E N T F R O M Character 30 N Area rented from 24 B L D G A R E A Numeric 8 2 Area with buildings (in hectares) 25 S E W E R Numeric 2 N Connected to municipal sewer? 26 INST D A T E Numeric 4 N Septic system installation date 27 W A T S O U R C E Numeric 2 N Water source 28 W E L L _ D E P T H Numeric 8 2 Well depth (in feet) 29 F U E L T A N K S Numeric 2 N Above or below ground fuel tanks? 30 F U E L INST Numeric 4 N Fuel tank installation date 31 F U E L C A P A C Numeric 2 N Fuel tank capacity 32 R E G W FD Numeric 2 N Fuel tank registered with fire department? 33 C O M P F A C Numeric 2 N Composting facilities, covered or uncovered 3 4 C O M P M A T Character 40 N Material composted 35 C O M M E N T S Character 150 N 36 ** 540 Total Appendix 20 continued (ii of iii) Structure for database: C : \SAL_ANIM.DBF Number of data records: 74 . Name Type Width 1 F A R M ID Character 6 2 G R A Z A R E A Numeric 8 3 F D L O T A R E A Numeric 8 4 A N I M TYPE1 Numeric 3 5 A N I M NUM1 Numeric 10 6 ANIM T Y P E 2 Numeric 3 7 A N I M NUM2 Numeric 10 8 ANIM T Y P E 3 Numeric 3 9 ANIM_NUM3 Numeric 10 10 M A N U R P R O D Numeric 13 11 UNITS P R O D Character 10 12 M A N IMPORT Numeric 13 13 UNITS IMP Character 10 14 M A N E X P O R T Numeric 13 15 UNITS E X P Character 10 16 M A N S T O R E Numeric 5 17 M A N C A P A C Numeric 10 18 UNITS C A P Character 10 19 M A N DIMEN Numeric 10 20 UNITS DIME Character 10 21 DISP S E A S Character 30 22 O N O F F F A R Numeric 3 23 O N SITE Numeric 10 24 O F F SITE Numeric 10 25 DISP A M T Numeric 10 26 DISP UNIT Character 10 27 DISP C R O P 1 Numeric 3 28 DISP C R O P 2 Numeric 3 29 DISP C R O P 3 Numeric 3 30 DISP M E T H Numeric 3 31 C O N T I N G E N C Character 35 32 M O R T L O C Numeric 3 33 O F F L O C Character 35 34 M E T H O D Character 20 35 S I L A G E Numeric 3 36 MILK P A R L Numeric 3 37 Y A R D R U N Numeric 3 38 C O M M E N T S Character 150 ** 513 Dec Description N Farm number, unique identifier 2 Grazing area (in hectares) 2 Feedlot area (in hectares) N Animal type 1 N Number of animal type 1 N Animal type 2 N Number of animal type 2 N Animal type 3 N Number of animal type 3 2 Manure produced N Units for manure produced 2 Manure imported N Units for manure imported 2 Manure exported N Units for manure exported N Type of manure storage facility 2 Capacity of manure storage facility N Units for capacity 2 Dimension of facility N Units for dimension N Disposal season N Manure disposal on or off farm 2 Amount manure disposed on farm 2 Amount manure disposed off farm N Amount disposed N Unit for amount disposed N Crop type 1 on which manure disposed N Crop type 2 on which manure disposed N Crop type 3 on which manure disposed N Manure disposal method N Contingency location N Mortalities disposed of on or off farm N Location for disposal of mortalities N Method of mortality disposal N Location of runoff from silage N Location of runoff from milk parlor N Location of runoff from yard N Appendix 20 continued (iii of iii) Structure for database: C : \ S A L _ C R O P . D B F Number of data records: 49 Field Name 1 F A R M J D 2 C R O P _ T Y P E 1 3 C R O P _ A R E A 1 4 CROP_YIEL1 5 YIEL1_UNIT 6 P R O T _ L E V E 1 7 C R O P _ T Y P E 2 8 C R O P _ A R E A 2 9 C R O P _ Y I E L 2 10 YIEL2_UNIT 11 P R O T _ L E V E 2 12 C R O P _ T Y P E 3 13 C R O P _ A R E A 3 14 C R O P _ Y I E L 3 15 YIEL3_UNIT 16 P R O T _ L E V E 3 17 F E R T _ T Y P E 1 18 F E R T C R O P 1 19 FERT_AMT1 20 F E R T J J N M 21 F E R T _ F R E Q 1 22 F E R T _ T Y P E 2 23 F E R T _ C R O P 2 24 F E R T _ A M T 2 25 F E R T J J N I 2 26 F E R T _ F R E Q 2 27 F E R T _ T Y P E 3 28 F E R T _ C R O P 3 29 F E R T _ A M T 3 30 F E R T J J N I 3 31 F E R T _ F R E Q 3 32 P E S T _ T Y P E 1 33 PEST_DISP1 34 P E S T _ T Y P E 2 35 P E S T _ D I S P 2 36 IRRIG_TYPE 37 IRRIG_SOUR 38 IRRIG_AREA 39 I R R I G _ F R E Q 40 C O M M E N T S Total ** Type Character Numeric Numeric Numeric Character Numeric Numeric Numeric Numeric Character Numeric Numeric Numeric Numeric Character Numeric Character Numeric Numeric Character Character Character Numeric Numeric Character Character Character Numeric Numeric Character Character Character Character Character Character Numeric Numeric Numeric Character Character 657 Width Dec Description 6 t* 3 6 15 15 15 3 6 15 15 15 3 6 15 15 15 20 3 6 15 15 20 3 6 15 15 20 3 6 15 15 20 40 20 40 3 2 6 30 150 N N N N Farm number, unique identifier Crop type 1 2 Area of crop type 1 2 Yield of crop type 1 Unit for yield of crop type 1 2 Protein level of crop type 1 Crop type 2 2 Area of crop type 2 2 Yield of crop type 2 Unit for yield of crop type 2 2 Protein level of crop type 2 Crop type 3 2 Area of crop type 3 2 Yield of crop type 3 Unit for yield of crop type 3 2 Protein level of crop type 3 Fertilizer type 1 Crop on which fertilizer type 1 is used 2 Amount of fertilizer type 1 used Unit for amount of fertilizer type 1 Frequency of use of fertilizer type 1 Fertilizer type 2 Crop on which fertilizer type 1 is used 2 Amount of fertilizer type 2 used Unit for amount of fertilizer type 2 Frequency of use of fertilizer type 2 Fertilizer type 3 Crop on which fertilizer type 3 is used 2 Amount of fertilizer type 3 used Unit for amount of fertilizer type 3 Frequency of use of fertilizer type 3 Pesticide type 1 Disposal method for pesticide type 1 Pesticide type 2 Disposal method for pesticide type 2 Irrigation type Irrigation source 2 Irrigation area Irrigation frequency Appendix 21 Animal and crop data collected in the Agricultural Waste Management Survey of the Salmon River Watershed. 208 in CO •§ c CO c in 10 c Q jg c 0) 8-• 3 x i § -S $ iS s FARMJD Operation Size (ha) Area with Area for gi Sheep Lambs 1 & Beef cows Horses Turkeys Broiler chi Layer chic Pullets/ch Pigs Donkeys % manure 7 Dairy 54.60 2.00 12.14 85 0 8 Dairy 80.90 1.20 10.12 100 100 0 9 Dairy 121.40 1.21 0.00 200 30 10 Dairy 40.50 0.80 16.19 55 15 0 11 Dairy 37.87 2.02 0.00 100 0 12 Dairy 80.93 2.02 21.04 170 30 0 13 Mushrooms 0.63 0.13 0.00 0 14 Horses 2.43 0.81 1.62 4 0 15 Turkeys 2.83 1.21 0.00 9000 26 16 Turkeys 2.08 0.61 0.00 4 30000 37 17 Broilers 2.02 0.81 0.00 54000 37 19 Broilers 4.05 2.02 0.00 50000 37 20 Broilers 16.19 1.62 1.21 4 100000 24 21 Broilers 2.02 1.42 1.42 48000 37 22 Broilers 7.69 0.40 0.00 15000 37 23 Broilers 1.70 0.40 1.70 2 2 1 45000 500 8 37 24 Broilers 7.08 1.62 4.05 10 90000 37 25 Broilers 3.44 1.42 0.00 77000 37 26 Broilers 11.33 -1.00 1.21 32000 37 27 Nursery 10.12 0.20 0 28 Nursery 3.64 0.81 0.00 0 29 Nursery 10.52 1.42 0 30 Nursery 3.44 1.01 0 31 Nursery 14.16 0.91 10.12 120 0 32 Nursery 16.19 0.00 0 33 Nursery 18.21 0.81 0.00 0 34 Nursery 3.21 0.81 0.00 0 36 Horses 36.66 1.62 4.86 4 0 37 Nursery 2.43 -1.00 0 39 Nursery 2.02 1.21 0 40 Nursery 19.83 1.21 0.00 0 41 Nursery 6.07 1.21 0 42 Layers 7.69 2.02 2.02 15 10000 5000 24 43 Layers 2.02 0.81 0.00 11000 10760 0 44 Layers 8.09 2.02 0.00 17000 8000 37 45 Layers 2.02 0.40 0.00 14000 7000 37 47 Layers 2.02 0.81 0.00 18000 10000 37 49 Berries 8.09 0.40 0 51 Sod 11.33 0.40 0 53 Sheep 2.02 0.81 1.21 50 4 0 55 Sheep 2.02 0.40 1.62 30 0 56 Sheep 0.40 0.08 0.30 14 0 IS T3 209 Appendix 21 continued (ii of iv) cc < 8. o to 9! c - 3 CO 0) 1 Ol .8 <a Q. a) 1 2 a> ! c3 0 1 1 5 '5 m I I 3 43 io fa. c o 9 1 I 3 E S? 57 Sheep 2.02 0.20 1.82 30 2 1 0 59 Sheep 1.82 0.40 1.42 13 14 0 60 Sheep 2.02 0.40 1.41 7 2 0 61 Sheep 2.02 0.40 1.62 8 6 0 62 Sheep 1.21 0.20 0.81 16 0 63 Sheep 1.21 0.40 0.81 22 30 0 64 Sheep 0.40 0.13 0.13 2 12 0 65 Sheep 2.10 0.10 1.82 17 1 0 66 Sheep 1.94 0.81 1.21 10 17 0 68 Sheep 4.86 1.42 3.64 30 30 0 69 Sheep 2.02 1.01 1.01 50 2 0 71 Sheep 2.02 0.10 1.52 16 18 0 73 Sheep 0.40 0.10 0.10 2 20 0 77 Horses 2.02 0.20 1.21 2 16 40 79 Horses 1.82 0.20 0.81 7 0 80 Horses 2.27 0.40 0.00 9 40 81 Horses 1.86 0.40 0.00 31 40 82 Horses 4.13 0.40 2.43 12 40 83 Horses 1.62 0.20 1.21 13 0 84 Horses 2.47 0.40 2.43 9 0 86 Horses 0.81 0.40 0.40 6 40 87 Horses 0.61 0.20 0.00 12 0 89 Horses 4.05 0.20 2.83 5 9 0 90 Horses 3.76 0.20 1.21 6 40 91 Horses 4.05 0.81 3.24 8 30 0 92 Horses 2.02 0.40 1.62 1 40 94 Horses 2.02 0.40 1.62 5 0 96 Horses 2.02 0.20 1.42 6 0 97 Horses 1.92 0.20 1.42 3 40 98 Horses 1.92 0.30 1.62 6 0 99 Horses 2.02 0.81 1.21 8 0 100 Horses 32.38 0.81 20.23 9 85 0 102 Horses 12.95 0.81 10.12 20 10 0 105 Horses 202.35 2.02 20.23 X 50 0 108 Horses 2.07 0.20 1.82 15 0 109 Horses 3.24 1.21 0.40 9 0 111 Berries 4.05 0.40 0 113 Berries 44.52 0.81 0 116 Nursery 10.12 2.02 0 117 Berries 2.43 0.81 0 119 Berries 1.78 0.20 0.00 0 120 Horses 4.05 0.40 1.62 3 0 121 Dairy 9.31 0.40 7.69 15 1 0 127 Horses 2.53 0.20 1.62 7 0 Appendix 21 continued (iii of iv) 210 FARMJD Pasture Corn Hay Grass Mushrooms Raspberries Blueberries Strawberries Fieldstock Root stock Rowers Vegetables Bamboo Ornamental plants Sod/turf Rowers and vegetables Trees and shrubs Cranberries Total cropped area 7 0 8 20 8 0 18 61 9 0 20 101 10 0 40 11 0 38 12 0 15 45 13 0 3 14 1.62 15 0 16 0.00 28.3 78.9 121.4 40.5 37.9 59.9 3.0 1.6 0.0 0.0 17 0 19 0.00 2 20 0 12 21 1 22 0.00 4 23 1.7 24 0.00 4 25 0 26 1.21 27 0 0.0 2.0 12.1 1.4 4.0 1.7 4.1 0.0 1.2 10.12 10.1 28 0 29 0 30 0 31 0.00 10 32 0.00 33 0.00 34 0 36 0 16 37 0 39 0 3.64 1.21 0.81 1.01 4.45 2.43 3.6 1.21 0.81 2.0 " 1.0 12.1 -1.00 -1.0 1.15 1.2 1.62 1.6 20.6 2.4 1.62 1.6 40 0 41 0 42 0 4 43 0 44 0 45 0 47 0 49 0 51 0 53 0 1 55 0 2 56 0 10.12 4.05 2.43 10.12 0.61 10.7 2.4 4.1 0.0 4.1 0.0 0.0 5.26 5.3 10.1 1.2 1.6 0.3 211 Appendix 21 continued (iv of iv) FARMJD Pasture Corn Hay Grass Mushrooms Raspberries Blueberries Strawberries Fieldstock Root stock Rowers Vegetables Bamboo Ornamental plants Sod/turf Rowers and vegetables Trees and shrubs Cranberries Total cropped area 57 1 1 59 1 60 1.41 61 1.62 62 0.81 63 0.81 64 0.13 65 0.61 1 0.13 1.8 1.4 0.10 1.5 1.6 0.8 0.8 0.3 1.8 66 1.21 68 3.64 69 0 1 71 1.52 73 0.1 77 1.21 79 0.81 80 0 1.2 3.6 1.0 1.5 0.1 1.2 0.8 0.0 81 0 82 2.43 83 1.21 84 2.43 86 0.4 87 0 89 2.83 90 1.21 91 3.24 92 1.62 0.0 2.4 1.2 2.4 0.4 0.0 2.8 1.2 3.2 1.6 94 1.62 96 1.42 97 1.42 98 1.62 99 1.21 100 20.23 102 10.12 105 20.23 108 1.82 109 0.4 111 0 0.40 0.40 1.21 1.6 1.4 1.4 1.6 1.2 20.2 10.1 20.2 1.8 0.4 2.0 113 0 116 _ 0 117 ' 0 119 0 120 1.62 121 7.69 127 1.62 12.14 0.81 12.14 1.21 1.21 1.21 25.1 8.09 8.1 2.4 1.2 1.6 7.7 1.6 (BI|/6>0 sn|dins | B ; O J | oS 8 s ? 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S 5 8 CM R co co R CO in co co i n 10 CO CO co co 8 R 3 in CO co CO CM s a 3 5! CO 3 8 5 CO ^ O I i - ^ o co co r - s n in 0> CM CM S CO r - O t- Tf If) 8 ^  T - CO T J -m oo T -3 SI ro = § * - Si Bq paddojo/B^ eq eseq |Bjrqjno;j6B/6>( (|\|-6>|) iJ3ysp/sn|djns pai|ddv (N-6>() suirqai O/M induj ouaqdsowiy 3 2 CM co g o> co co co N >t • - • - N N CM T - • • 8 § co co o m T~ co co cn CM a) CO 8 2 8 co 8 3 8 fj' 2 CM 8 oo r -CO CO CD >* r -m r- oo r~ t r r~ TT co i - O) 9 8 8 8 2 R 3 5 2 CO CO CM CO 1— CM TJ" * ± CM 1 1 S 5 S co co r -co 1 CD CO CO CO (|\|-6>l) jezjijvia^dojo ;ON (N-6>l) pe;|dde jezwije-j (N-6>() siueaisjinbsj dojQ co o CM O O O CM R ° 0) m o CM g o o co GO CO CO CO r - co CO CM h- co in CT) t CM co i — f «9 CM CM <? SP. CO CO ^ co CO 8 o> v— r - O m r -i — r -CM 0) 0> CM <Q cn CD m tn 8 •* 8 o CM h - 3 CM CO CM *-m r - T y- 0) CM up • • 8 8 8 in •* in in i -<o co T (N-6>|) uoneonddv ejnuByvj ISN (N-6>() SSSSOI IUSOISBBUBUI (N-6>() poijodxg (N-6>|) peonpojd ejnuB^ 5 2 CM m y- CO 2 3 CM 0) co co 8 ° CM 8 8 8 >- co •* O) CM O O y-CO CO CM in CD CD in r -cp in co CO CM CO o o o co in CM o o o 8 8 R co co S CO T t CM yf y- CD y* y- O) m oo co £ 8 8 - — 0) CM 5 m cnco -•CO CO CO E: 2 3 CO CO CM p~ r~ i> co cn o o y- co co in o> 8 8 8! 0) T -CD CO i -CM CM in CO y-8 8 8 Si 3 3 CM 8 *t CD CM T - CM 8 2 o o g o o o CO S o o o o CO r - CM cn co y- CM o o 8 8 y- CM T - CM o o o o o o o 8 8 3 Si 8 8 S N CO If) CM y- • - CO T3 0) C 8 •* CM X 73 C 8. (Bq) BSJB paddojo-uoN (Bq) esjB paddojQ (Bq) aseq puB| |BjnynouBv adAi uojiBjedo Ql wed CO * CM T f CM CO CM >- t O <* O O O CO CM CO CM CO CM to w to in c c c c es co co co . c . c . c . c CO jo to D) D) D) CU D) c c c c c fi fi 'JS- 'sf 'sP '5P "a? 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CO CL 0) CL CO CO 1 co CD CO CD CO 0) CO CO w CO W V) W W w w 8 8 175 8 8 CO Si 8 3 216 eq paddojo/6>| eq sseq |ejn4|nouBe/6y| (6>|) (ipijep) sn|djns (N-&0 uorieo^iuaa 14 23 11 13 11 20 11 17 35 273 135 270 15 34 17 23 2 12 29 115 11-9-4-6 0 -79 -39 -65 35 237 146 196 25 49 20 20 0 -25 -31 -62 28 61 15 22 0 -63 -17 -52 133 975 241 301 0 -111 -55 -69 14 11 6 7 16 52 26 37 0 -96 -50 -68 16 35 18 22 22 118 58 97 238 815 25 40 55 -200 -15 -20 137 1431 7 71 41 242 117 133 25 218 67 546 8 -19 -5 -12 eq paddojo/6>| eq eseq |Bjru|nou6e/6>( (N-BH) ip!jsp/sn|djns pailddy (N-B>i) sujnjsj O / M jndin ouaqdsounv 19 37 18 20 17 32 16 26 18 308 152 305 18 50 25 33 4 13 33 133 22 1 1 1 18 -79 -39 -65 15 273 168 225 22 74 30 30 7 -25 -31 -62 36 89 22 31 34 -63 -17 -52 36 1109 274 342 18 -111 -55 -69 18 25 12 15 18 68 34 48 17 -96 -50 -68 17 51 27 32 18 140 69 116 291 1053 33 52 117 -145 -11 -14 1821 1568 8 77 19 283 136 155 29 243 75 607 36 -11 -3 -7 (N-6>() J9Z||!P8j-doJo ;9N (N"6>() ps;|dde jazwijgj (|\|-6>|) S}uauJ9J|nb9j dojQ 485 364 -121 242 145 -97 303 242 -61 304 162 -122 20 12 -8 324 194 -130 242 145 -97 242 145 -97 486 292 -194 80 48 -32 566 340 -226 242 145 -97 648 389 -259 324 194 -130 324 . 194 -130 284 170 -114 284 170 -114 324 194 -130 242 145 -97 4046 2428 -1618 2024 1214 -810 4046 2428 -1618 364 218 -146 80 48 -32 324 194 -130 (f\|-6>() uoQBOtiddv ajnueyvj ja^ (N"B>() S S S S O | iU3ius6eueiu (N-B>|) paijodxg (N"6>() paonpojd ejnue^ 233 0 93 140 185 0 74 111 587 0 236 350 255 0 102 1 53 38 0 20 18 182 0 73 109 750 300 450 0 592 0 237 355 410 0 164 246 273 109 164 0 465 0 186 279 273 109 1 64 0 2293 0 962 1331 46 18 27 0 228 0 91 137 273 0 1 09 164 137 55 82 0 273 0 1 09 164 364 0 1 46 218 3967 0 1587 2380 918 0 370 548 2275 0 910 1365 683 0 273 410 410 0 164 246 137 0 55 82 (eq) B9JB paddojo-uo|\| (eq) B9ie paddojo (eq) aseq pue| |ejni^nou6v edAj uopjado Ql UJJBj 65 Sheep 2 2 0 66 Sheep 2 1 1 69 Sheep 2 1 1 71 Sheep 2 2 1 73 Sheep 0 0 0 14 Horses 2 2 1 77 Horses 2 1 1 83 Horses 2 10 84 Horses 2 2 0 86 Horses 1 0 0 89 Horses 4 3 1 90 Horses 4 1 3 91 Horses 4 3 1 92 Horses 2 2 0 94 Horses 2 2 0 96 Horses 2 1 1 97 Horses 2 1 1 98 Horses 2 2 0 99 Horses 2 1 1 100 Horses 32 20 12 102 Horses 13 10 3 105 Horses 202 20 182 108 Horses 2 2 0 109 Horses 3 0 3 120 Horses 4 2 2 217 (BL|/6>|) (iooi;ep)sn|djns|B;OJJ 8 55 3 8 " 8 8 8 8 co 8 3 co 8 8 BL| |B!lU8piS9J/6>(l (6n) swaisAs 3|ldasl8 Too § § 8 oo Tf CM T-Tf T- T- Tf CO CM CO 2 8 OJ CM R 8 co cn R So 8 2 * fs. 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CO oo CM co Tf in Tf CM CO CM cn Tf ts. in co CM Is. o Q in fs Tf r- T - in T - CM O O Tf r - r -N r - CM oo oo r- co Tf rs. o co o co in CM CM 00 Tf CO r-(eq) eaje paddojo | B J O I (eq) aseq pue| |BJtinno|jBv (eq) eaje |e|iuap|say (eq) azis vo 8 m 8 3 CO 1— to 8 CO oo co Tf 8 CM 8 3 Tf 3 R Tf fs 8 CM Tf cn CD 8 ^ 8 3 2 CM CM CO i - CO T- CM CO 2 8 8 3 T f 8 8 1- y- PJ CO c8 cB cS 8 8 8 P TJ in T -8 8 8 S 8 & r N •• in to. CO fs. CO oo fs. Tf CM o CM CM CM CM Tf CM CO 8 Tf 9 O 8 8 S 8 CO LO T^  CM Tf in in T - co 5 8 8 S 8 o o o o o 8 & 5 8 8 O O Q Q 10 5 8 8 S 8 co to co to to 8 & 8 8 S to to to to to t- CM CO Tf LO CO co w tn to to to 

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