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Effects of land use on the water quality of Ladner Slough Still, Gerald William 1979

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9% EFFECTS OF LAND USE ON THE WATER QUALITY OF LADNER SLOUGH by Gerald William St i l l B.S.F. (Honours), University of British Columbia, 1974 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE in THE FACULTY OF GRADUATE STUDIES (Department of Soil Science) We accept this thesis as conforming to the required standard THE UNIVERSITY OF BRITISH COLUMBIA October, 1979 . 0 Gerald William S t i l l , 1979 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 i t 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 representatives. It is understood that copying or publication of this thesis for financial gain shall not be allowed without my written permission. G. W. St i l l Department of Soil Science The University of British Columbia / i i ABSTRACT The purpose of this study was to quantify the effects of land use on water quality in Ladner Slough, and in the major drainages feeding Ladner Slough. Water samples were collected monthly during the winter of 1976 up until the month of Apri l , 1977. Samples were also collected in August 1976 and August 1977. Soil and sediment samples were collected twice throughout the sampling period in order to aid in determining the net effect of various land uses on water quality. Sampling sites were located on Ladner Slough, Cohilukthan Slough, Crescent Slough, and Deas Slough. In that context, they were located wi/thin various different land use areas, and within transition zones between land use areas. Concentrations of metals, nutrients, and major cations in water samples were determined. Analogous determinations were made on the soil and sediment samples taken. The results of numerous statistical analyses suggested that iron and total nitrogen were the water quality parameters that are most sensitive to land use in the Ladner area. Some water quality parameter magnitudes in every slough were found to exceed guideline objectives for domestic use in one or more months throughout the study period. Sloughs draining or adjoining urban zones were observed to exhibit generally the highest concentrations of metals. A site near the sanitary landfill area, on the periphery of Burns Bog, also / i i i exhibited consistently high metal concentrations. High nutrient concentrations were most often found in conjunction with agricultural land, and probably resulted from point sources. The highest concentrations of major cations were found in the slough which was closest to the Strait of Georgia. Soil and sediment data did not correlate closely with water quality data. Relatively high concentrations of lead were found in the sediment from Ladner Slough. This was thought to result from the heavy marine traffic on that slough, and could represent a potential sink for that metal. The water quality in Ladner Slough did not differ significantly from the water quality of Deas Slough. This implies that the Fraser River may flush both of the above sloughs periodically. The effects of land use on water quality in the Ladner area are discernable, and often pronounced. Moreover, some water quality problems were found to exist. This report recommends that a surface water and groundwater monitoring network be established in the area in order to provide a greater data base, and to better define specific deleterious activities. Emphasis should be placed on nutrients draining from agricultural land, and metals draining from both urban land, and the sanitary landfill area on the periphery of Burns Bog. / iv ACKNOWLEDGEMENTS I wish to gratefully acknowledge the funding of this study by Agriculture Canada (Research Grant OG-4041). I would also like to thank the members of my committee: Dr. C. A. Rowles, Dr. L. M. Lavkulich, Dr. J . Wiens and Dr. R. P. Willington, for their measured advice, and for their encouragement. I extend a special thanks to.Dr. H. Schreier for his assistance with the statistical work, and to Ms. Bev Herman, who not only assisted me with the lab work, but also offered many timely suggestions in that regard. Mr. Don Digby contributed some of his valuable time, for which I am extremely grateful. The assistance of Mr. Verne Kucy and the cooperation of the Corporation of Delta is also gratefully ackn'olwedged. Finally, I would thank my wife, Roxanne, for her warm encouragement and understanding throughout the period of this study. / V TABLE OF CONTENTS Page ABSTRACT i ± ACKNOWLEDGEMENTS i v TABLE OF CONTENTS T LIST OF TABLES. . x LIST OF FIGURES s i i i : LIST OF PLATES 1. INTRODUCTION 1 2. LITERATURE REVIEW 2 2.1 Introduction . . 2 2.2 Pollutants 4 2.2.1 Sediment 4 2.2.2 Organic Matter 5 2.2.3 Nutrients 5 a. Nitrogen 5 b. Phosphorus. 6 c. Others 7 2.2.4 Heavy Metals 7 2.2.5 Pesticides 8 2.2.6 Pathogens 8 2.3 Land Use Practices 9 2.3.1 Agricul ture 9 a. Feedlots 9 b. Combined Housing 10 /vi Page c. Fertilizers and Manures 11 d. Range and Pasture Operations 12 e. Irrigated Cropland 14 tV Non-irrigated Cropland 15 2.3.2 Urban/Industrial Land Use 17 2.3.3 Forest Related Land Use 22 a. Undisturbed Forest Land 22 b. Disturbed Forest Land 23 2.4 The Effects of Soil on Water Quality 26 2.5 The Effects of Bottom Sediments on Water Quality 29 3. STUDY AREA DESCRIPTION 31 3.1 Location and Extent 31 3.2 Climate 31 3.3 Soils and Surficial Geology 36 3.4 Biota 39 a. Wetlands. 39 b. Burns Bog 40 c. Developed Land 41 3.5 Hydrology 42 a. Surface Waters 42 b. Groundwater 44 3.6 Land Use 45 a. Land Use History 45 b. Present Land Use 46 /vi i Pa^ e i . Land Classification System. 46 i i . Distribution and Extent of Present Land Uses 47 4. EXPERIMENTAL DESIGN 51 4.1 Criteria for Selection of Study Area 51 4.2 Sampling Design 51 4.2.1 Criteria for Selection of Sampling Points 51 4.2.2 Sample Collection Methods and Sampling Frequency . . . . 52 a. Water Samples 52 b. Sediment Samples . . . . 53 c. Soil Samples 54 4.3 Analytical Methods 55 4.3.1 Parameter Selection 55 a. Water 55 b. Soils and Sediments 56 4.3.2 Field Methods . 56 4.3.3 Laboratory Methods 57 a. Water 57 b. Soils and Sediments 59 5. DATA ANALYSIS TECHNIQUES 60 5.1 Statement of Rationale 60 5.2 Percent Coefficient of Variation 63 5.3 Correlations ' 64 5.4 Parameter Magnitudes Per Slough 65 5.5 Independence Testing 65 5.6 Curve Analysis 66 /vi i i Page 6. RESULTS AND DISCUSSION . 67 6.1 Study Area 67 6.1.1 Percent Coefficient of Variation 72 6.1.2 Correlations 74 6.1.3 Curve Analysis 76 6.2 Sloughs 80 6.2.1 Sites Per Slough . 80 6.2.2 Slough Descriptions 95 a. Slough 1 95 b. Slough 2 95 c. Slough 3 100 d. Slough 4 100 e. Slough 5 100 f. Slough 6 105 6.2.3 Slough Parameter Magnitudes 105 a. General Water Quality of Sloughs 105 b. Comparative Analysis 110 6.2.4 Independence Testing 116 a. Independent Sets of Slough Parameter Values . . . . 116 b. Dependent Slough Parameters 121 c. Frequency of Individual Parameter Differences Between Sloughs . . . . . . . 124 6.2.5 Percent Coefficient of Variation 124 a. Slough 1 126 / ix Page b. Slough 2 126 c. Slough 3. . . 126 d. Slough 4 131 e. Slough 3 and 5 131 f. Slough 6 132 ;6:.^ 2.6 Curve Analysis 133 a. Slough 1 137 b. Slough 2 137 c. Slough 3 137 d. Slough 4 137 e. Slough 5 139 f. Slough 6 139 6.3 Integration of Soil and Sediment Data. 139 7. SUMMARY 145 8. CONCLUSIONS 153 9. RECOMMENDATIONS 156 . 10. LITERATURE CITED 158 /X LIST OF TABLES Pa^ e Table 1. (Results) Means, Standard Deviations and Ranges by Month for All Sixteen Sites 68 Table 2 Percent Coefficient of Variation for Parameters in Study Area 73 Table 3 Summary of Correlation Matrix and Months in which Correlations Occurred 75 Table 4 Means and Standard Deviations of Parameters in Slough 1 (Sites 1, 2, 3, and 4) per Month 81 Table 5 Means and Standard Deviations of Parameters in Slough 2 (Sites 5 , 6 , and 7) per Month 83 Table 6 Means and Standard Deviations of Parameters from Slough 3 (Sites 8, 9, 10, and 11) per Month 85 Table 7 Means and Standard Deviations of Parameters Slough 3 and 5 (Sites 8, 9, 10, 11, 13, and 14) per Month . . . 87 Table 8 Parameter Values from Slough 4 (Site 12) per Month . . . 89 Table 9 Means of Parameters from Slough 5 (Sites 13 and 14) per Month 90 Table 10 Means of Parameters from Slough 6 (Sites 15 and 16) per Month 91 Table 11 Results of Mann-Whitney U Test as Applied to Sets of Parameter Values from: (a) Slough 3 and Slough 5 (b) Site 11 and Site 13 94 /xi Page Table 12 Water Quality Standards 108 Table 13 Relative Concentration of Parameters per Slough, per Month I l l Table 14 Sites and/or Slough with Highest Concentration of Specific Nutrient Parameter in Given Month 115 Table 15 Total Number of Significantly Different Sets of Parameter Values Between any Two Sloughs (a = J05) . . 117 Table 16 Specific Significantly Different Sets of Parameters Values Between any Two Sloughs (a = .05) 119 Table 17 Summary of Table 16 in Terms of Major Parameters . . . . 120 Table 18 Equivalent Sets of Parameter Values Derived from Table 16 122 Table 19 Relative Sensitivity of Parameters and Major Parameters, Derived from Table 16. 125 Table 20 Percent Coefficient of Variation for Parameters in Slough 1 (Sites 1 , 2 , 3 , 4 ) 127 Table 21 Percent Coefficient of Variation for Parameters in Slough 2 (Sites 5, 6, 7) 128 Table 22 Percent Coefficient of Variation for Parameters in Slough 3 (Sites 8, 9, 10, 11) 129 Table 23 Percent Coefficient of Variation for Parameters in Slough 3 + 5 (Sites 8, 9, 10, 11, 13, 14) 130 Table 24 Peaks and Dips per Slough 134 Table 25 Trends in Sloughs 138 Table 26 Concentration of Elements in Seawater of Salinity 34-33% (Source: Deacon, 1962) 143 /xi i Page Table 27 Ratios of Concentrations of Major Cations in Seawater and in Collected Samples 1 4 4 / xi i i LIST OF FIGURES Page. Figure 1 Location of Study Area 32 Figure 2 Average Annual Precipitation and January Mean Temperature for the Lower Fraser Delta 33 Figure 3 Monthly and Annual Average Temperature and Precipitation for the Ladner CIimatological Station, Delta, B.C. (Source: B.C.D.A., 1965) 34 Figure 4 Monthly Precipitation and Monthly Mean Temperatures for the Study Period (Source: Environment Canada, 1978) 35 Figure 5 Surficial Geology of Study Area 37 Figure 6 Drainage Map of Study Area 43 Figure 7 Study Area Land Use 48 Figure 8 Total Peaks and Dips per Parameter per Month (Refer to Table 1 for Abbreviations). . . 77 Figure 9 Total Peaks and Dips per Month over Entire Study Area . . 79 Figure 10 Sampling Site Locations 93 Figure 11 Peaks and Dips per Slough (From Table 14) 136 /xiv LIST OF PLATES Page Slough 1 96 • 1. View of Ladner Slough and Marina, From Site 1, looking East . . 96 2. Confluence of Cohilukthan Slough and Ladner Slough, from Site 2, looking North . . . . . . . . 96 3. Pumphouse at Site 3, on Cohilukthan Slough 97 4. View of Ladner Slough and Marina, from Site 4, looking West . . 97 Slough 2 98 5. Cohilukthan Slough from Site 5, looking North 98 6. Cohilukthan Slough from Site 6, looking North - Urban/ Agricultural Transition . . . . 98 7. Near Headwater of Cohilukthan Slough, from Site 7, looking West 99 Slough 3 101 8. Outlet of Crescent Slough, from Site 8 looking Northeast -Pumphouse is Behind Viewer 101 9. Near Outlet of Crescent Slough, from Site 9, looking South -Pumphouse is to Right of Viewer 101 10. Crescent Slough from Site 10,looking North - Agricultural Land on East, Urban Land on West 102 11. Crescent Slough from Site 11, looking East 102 /xv Page Slough 4 "103 12. Crescent Slough from Site 12, looking South - Burns Bog in Left Background 103 Slough 5 104 13. Crescent Slough from Site 13,looking East - Burns Bog in Background 104 14. Crescent Slough from Site 14, looking Northeast - Agricultural land .104 Slough 6 106 15. Deas Slough from Site 15, looking Southwest 106 16. Deas Slough and Marina, from Site 16, looking East 106 /I 1. INTRODUCTION The quality of water draining an area can be affected by the ways in which land in that area is used. Different kinds of land uses have often been found to affect water quality in characteristic ways. Sediment and soil chemistry have also often been found to affect water quality. The purpose of this study is to quantify such effects and relate them to the proportion and distribution of land areas in the Ladner region of Delta Municipality, British Columbia. The Ladner Slough area has recently been the subject of much environmental research. This study is intended to quantify the relationship between water quality draining into Ladner Slough and the water quality as a whole in Ladner Slough itself. In this regard, an attempt is made to discern the degree of attenuation of concentrations of materials along the lengths of channels draining the study area. In order to achieve the above objectives, water samples were taken monthly along the lengths of two major drainage ditches, and from Lander Slough itself, into which one of the above two ditches empties. Samples were., also taken from Deas Slough, on the north of the study area. It was felt that the water quality in this latter slough could usefully be compared with the water quality of Ladner Slough, because both sloughs are surrounded by radically different proportions of land use area. Deas Slough is surrounded predominantly by forested and agricultural land, while Ladner Slough is surrounded more by urban residential and industrial land. Sampling sites were located so as to provide for a representation of different land uses in Ladner. Hence, samples were taken from sites adjacent /2 to urban land, agricultural land, and urban-agricultural land. The area was further stratified on the basis of soil parent material. Soil and sediment samples were taken twice throughout the twelve month study period. These samples aided in differentiating between the effects of land use on water quality, and the effects of sediment and soil on water quality. The data thus obtained was used to determine the extent to which land use degraded the quality of water draining the study area. Concentrations of metals, nutrients and major cations in the water samples were determined. This data was used to characterize all sloughs of interest in the area. It was also compared to certain water quality standards, as outlined by two different agencies, in order to determine i f there were any water quality problems. Land use activities that were found to degrade water quality significantly were noted. Recommendations are made with regard to the minimization of land use impacts on water quality in the study area. 2. LITERATURE REVIEW 2.1 Introduction Land use practices can affect the quality of water running through or within a land area in many ways. Some of the ways in which water quality is affected by a land use, is characteristic of that given land /3 use. For example, the effects of the agricultural practices of tillage and fertilization might be found to change a stream's characteristics in different ways than might the urban practice of paving. The same could be said of a comparison between logging and grazing. The reason for this is clearly because each kind of land use practice either affects the water quality in some direct, characteristic fashion, or affects the land in some characteristic fashion, which subsequently affects water quality. For the purpose of this report, a "point source" of pollution is defined as a small area of land, relative to the size of the water unit under study, whose inputs to the water unit are concentrated. Such inputs are often direct, but this is not always the case. A "non-point" source is defined as a relatively larger area of land whose inputs to the system are not concentrated, but diffuse. Non-point pollutants often interact with the land prior to entry into an aquatic system, but again, this need not always be the case. It is important to note that a modification of any one water quality parameter often has implications as regards other parameters. For example, a change in the chemical status of water, in a given system, may induce changes in the biological status. The purpose of this part of this report is to describe the pollutants of most concern to environmentalists, and to outline some of the characteristic water quality changes brought about as a'result of specific land uses. /4 2.2 Pol lutants 2.2.1 Sediment Sediment has been described as the only pollutant that consistently results from almost all land use activities (Peavy, 1977). By itself, it can degrade the aesthetic quality of an aquatic system. Most important, i t can act as a carrier of other pollutants. Phosphorus in particular has been noted to travel predominantly in association with sediment, rather than of itself in dissolved form (Johnson et al_., 1976; Branson et a l . , 1975; Munn et al_., 1973; Ryden et_ al_., 1973). Ammonium has also been noted to travel in the same fashion, although it is also soluble in water, and can. therefore, travel through the ecosystem in dissolved form as well. In addition, in urban/industrial systems the greatest relative quantities of trace metals have been found to occur in association with bottom sediments (Dorcey, 1976; Wilber and Hunter, 1977; Bhoojedhur, 1975). In some aquatic systems, sediment can detrimentally influence fish spawning grounds by settling over gravel in which fish eggs (roe) have been deposited,thereby inhibiting the exchange of gases between the roe and the water. This can, i f severe enough, result in the suffocation- of many of the eggs, and hence the demise of many yet to be born fish (Forest Club, 1971). Sediment, by decreasing the albedo of an aquatic system, can cause the system to absorb more energy than i t otherwise might. Such a process may result in temperature extremes quite different from those normally found in that system (McGriff, 1972). This is especially true of the shallower aquatic systems. /5 2.2.2 Organic Matter Organic matter complements to an aquatic system may result in many of the same effects as does inorganic sediment. It can result in turbidity i f in particulate form, which as stated above, might affect the energy balance of the ecosystem. In addition, organic matter generally has a higher cation exchange capacity (C.E.C.) than does most mineral matter (Buckman and Brady, 1969). This implies that it is capable of carrying with it ions with a positive charge, such as some trace metals and ammonium ions. That i t has a higher C.E.C. than mineral matter indicates that i t has a greater potential for carrying such cations. Substances bound to cation exchange sites can represent a source of pollutants to a system. This aspect will be discussed at length later in this report. Organic matter constituents are composed of many or all of the nutrients necessary for l i fe . Therefore, the addition of. organic matter to a system inherently increases the nutrient status of that system. This may or may not be desirable, depending upon other circumstances, but i f introduced in great enough quantities, can result in eutrophication (McGriff, 1972). The introduction of biodegradeable matter into aquatic systems can cause oxygen to be utilized for decomposition by organisms in the detritus food chain, hence possibly causing oxygen deficiencies for other aquatic biota. 2.2.3 Nutrients a. Nitrogen High concentrations of nitrogen in available forms can result in eutrophication of aquatic systems (Dorcey, 1976). In addition, excess /6 nitrate in water consumed by infants-< can prevent the blood from supplying an adequate amount of oxygen, resulting in a blue baby condition (methemo-globinemia) (Branson;et'al_., 1975). Nitrogen is generally highly soluble in the forms in which it is avail-able to plants for growth, specifically as nitrate and ammonium. Because of the positive charge of the ammonium ion, some of i t may adhere to soil particles and therefore be relatively less mobile within the system than is nitrate (Giles et al_., 1973). As stated previously, however, i t is also subject to movement through the process of erosion. Nitrate is easily solubilized, and because of its negative charge can be transported easily and quickly to stream channels or groundwater in dissolved form. b. Phosphorus Phosphorus is often the element or nutrient most limiting to growth in an aquatic ecosystem (Kormondy, 1969; Allen and Kramer, 1972). For that reason, any additions of phosphorus to a system are more likely to result in eutrophication than would additions of most other nutrients. Phosphates are relatively insoluble in water. Many researchers have shown that movement of phosphorus to stream channels occurs largely through the process of adhesion to soil particles and subsequent soil' erosion, rather than by dissolution and transport through groundwaters or in surface runoff (Johnson et al_., 1976; Munn et_ al_., 1973). Some phosphorus may be in particulate form and hence, rather than adhering to soil particles, may erode directly into aquatic systems (Johnson et al_., 1976; Ryden et a l . , 1973). II Phosphorus is also combined with iron and aluminum in acid soils, and with calcium in alkaline soils, so that erosion of those soil particles may result in a "sink" of phosphorus in the bottom sediments of some aquatic systems (Allen and Kramer, 1972). In addition, i t is often a component of organic matter in the soil (Ryden et al_., 1973). Such organic phosphorus is generally readily available for use by aquatic biota, and hence represents a more immediate source of phosphorus than does inorganically bound phosphorus (Allen and Kramer, 1972). c. Others Any addition of a g.iven nutrient, or nutrients, may increase the probability of eutrophication in an aquatic system. As stated previously, phosphorus is most often the limiting nutrient, but when this is not the case, complements of miscellaneous nutrients may affect the system adversely. Even when phosphorus is found to be most limiting to growth in general, growth of certain specific biota may be limited by some other less abundant nutrient (Kormondy, 1969). 2.2.4 Heavy Metals Certain metals can be very toxic in relatively small concentrations. Most important in this regard are the metals: lead, cadmium, mercury and nickel. Heavy metals have a tendency to accumulate within organisms, even when in very small concentrations, so that i f the input of metal is maintained, the build up within an organism continues (Dorcey, 1976; /8 Larkin, 1974). In addition, because they do accumulate within an organism, the concentration of heavy metals can be magnified along the food chain. 2.2.5 Pest ic ides Pesticides can prove detrimental to organisms other than those at which its use is intended, i f used inappropriately, or in higher concentrations than are warranted. However, i f applied in favorable climatic conditions, and in appropriate quantities, such use need not result in any severe environmental pollution. If the pesticide applied is one of the more persistant varieties (e.g. DDT), i t can be concentrated along the food chain through the process of biomagnification, and therefore prove toxic to non-target organisms (Peavy, 1977). However, use of many of the more persistant varieties has recently become subject to strict legislation, so that often such pesticides cannot be utilized without the express permission of the abiding government, and under well-controlled conditions (Dorcey, 1976). 2.2.6 Pathogens Any change in water quality will directly affect its microbial population. Peavy (1977) reports that such changes are generally restricted to saprophytic bacteria which use dead organic matter as substrate. High concentrations of pathogenic organisms in an aquatic system may prove detrimental to both terrestrial and aquatic l i fe . Geldreich (1972) cited in Dorcey (1976), found pathogens such as Salmonella in storm water with high fecal coliform counts. Pathogens may be introduced directly into /9 aquatic systems by way of such facilities as waste-water treatment plants, sanitary sewer systems and animal feedlots. Non-point sources may also contribute significantly. 2.3 Land Use Practices 2.3.1 Agr icu l ture Agricultural practices may vary considerably depending upon such things as topography, soil depth, drainage, socio-economic status of the area, etc. A detailed dissertation concerning many of said practices is beyond the scope of this report. However, many of the activities most prevalent in North America are considered briefly. a. Feedlots The animals in feedlots produce large volumes of concentrated organic waste. Livingstone (1963) cited in Giles et_al_. (1973) states that "half the 1.8 billion metric tons of livestock waste produced annually in the U.S. originates from confined feeding establishments". This waste has been shown to contain generally high concentrations of bacteria, organic carbon, nitrogen, and sometimes phosphorus. Miner and Wil1 rich (1970) found that waste from cattle can contain as much as 57.9 kilograms of nitrogen per year, per head and 7.2 kilograms of phosphorus per year, per head. Stewart (1970) determined concentrations of nutrients in cores taken from irrigated fields and in those taken from cattle feedlots, and found that concentrations of ammonium and organic carbon were higher in all cases for the feedlot cores, than for the cores from the irrigated fields. In addition, Peavy no (1977) states that the greatest biodegradeable contaminant from agricultural watersheds is the residue from animal waste. Such compliments of organic matter can cause the biological oxygen demand (BOD) within an aquatic system to increase. It is apparent, then, that i f wastes are not dealt with appropriately, they, or some of their constituents, may find their way into aquatic systems through surface runoff, adhesion to eroding soil particles, and infiltration into the groundwater system. b. Combined Housing The pollution problems to be dealt with in managing waste products from combined housing establishments are much the same as those encountered in managing cattle feedlots. Solid waste materials from combined housing establishments are often stockpiled until they can conveniently be spread on the land. The liquid and semi-solid wastes may be transported to a sewage lagoon for anaerobic treatment, and then spread on the land or discharged directly into waterways. Emphasis is to be placed on the word "management", because the volume of waste to be dealt with, while an integral part of the problem, is not as important in causing or not causing pollution, as is the way in which it is managed (Barber, 1975; Giles et al_., 1973). The spreading of waste onto land surfaces may be done without harm to the environment in many instances. However, i f spread on the land at an inappropriate time of the year, or in inappropriate quantities, it may find its way into a receiving aquatic system and cause water quality problems (Ryden et al_., 1973). Effluent from sewage /II lagoons discharged directly into waterways can also have detrimental effects on the aquatic environment unless treated properly, and discharged at appropriate times of the year and in appropriate quantities (Peavy, 1977). c. F e r t i l i z e r s and Manures The general consensus amongst researchers is that the nutrients, nitrogen and phosphorus are of the most importance when considering pollutants originating from agricultural land. Commercial fertilizers and livestock wastes are considered to be the two primary sources of nutrient overloads to streams (Peavy, 1977; Dorcey, 1976). Approximately 75% of all commercial fertil izer and a large proportion of livestock waste is concentrated on cropland and pasture/range!and agricultural areas (Peavy, 1977). In a study by Chichester (1976) in a watershed on the Alleghany-Cumberland plateau in east-central Ohio, i t was reported that measured nitrogen contents of spring flow were related to fertilizer-nitrogen regimes of the different agricultural practices investigated. Changes in management practices were reflected by changes in nitrogen concentrations of water flowing through and within that land. Also, the changes in concentrations of nitrogen, in surface water, correlated highly with an increase in water percolating through the overlying soil and shale. Peavy (1977) estimates that as much as 10% to 15% of nitrogen applied to agricultural land is lost to water. Commoner's (1968) findings were much the same. Olness (1975), however, from a study of eleven watersheds in central Oklahoma, found that losses of fertil izer nitrogen and phosphorus did not exceed 5% of the most recent applications, /12 although surface runoff was four to ten times greater than in the previous year. However, most researchers agree that a significant proportion of nitrogen finds its way from fertilized agricultural land areas into proximate aquatic systems. Peavy (1977) estimated that only 10% to 30% of the phosphorus applied to f agricultural lands is used by the current crop. However, phosphorus, because it is less soluble than many of the nitrogen compounds, is generally less mobile within a system, and hence is likely to persist longer in the soi l . Therefore, less phosphorus is often lost in proportion to the amount applied, than is lost of nitrogen. Of the phosphorus that is lost, Munn e_t a]_. (1973) found that a much larger proportion (75% of phosphorus applied) was lost at high flow periods of the year, which occurred about 10% of the time. They also found that less than 1% of the phosphorus applied to the landscape in chemical fertilizers and manure was lost from the watershed in dissolved form. The use of manures as fertilizers can also cause water quality problems. As stated previously, the contribution of manure to an aquatic system may be of both a biological and nutritional nature. Excesses of either may cause eutrophication and lower concentrations of dissolved oxygen. In this regard, researchers caution against the spreading of animal waste on frozen ground, or at times of high precipitation and runoff (Barber, 1975; Giles et a l . , 1973; Ryden et al_., 1973). d. Range and Pasture Operations Nitrogen, phosphorus and sediment are the pollutants of most concern stemming from range and pasture operations. Pasture land is at times fertilized, and when this is done in an inappropriate fashion the same water /13 quality problems will likely arise as do for land that is fertilized regularly and intensively (e.g. cropland). Wastes from grazing animals are generally evenly distributed over the landscape, rather than being concentrated, as is the case with feedlots and confined housing establishments. To a large extent the wastes and waste by-products are utilized by resident vegetation, and hence a smaller proportion of it is transported into proximate aquatic systems than might otherwise be the case (Giles et al_., 1973). Of importance also is the fact that in utilizing the additional nutrients provided by the grazing animals, vegetation will grow more quickly. This in turn helps mitigate against erosion of mineral soil from the grazed area. Giles et al_. (1973) point out that nutrient losses from range and pasture operations are less than from intertilled soils. They suggest that high intensity precipitation events can cause surface runoff from grazing land, but also say that wastes are generally sufficiently diluted by the time they enter any aquatic system so as not to cause any serious water quality problems. An accelerated rate of erosion can result from areas that have been or are being overgrazed. Such a condition will come about as a consequence of too much exposure of mineral soil by animal hooves and animal grazing habits. Olness (1975) in a study of both grazed and cultivated watersheds in Oklahoma, found that sediment losses from continuously grazed rangeland watersheds ranged from 18 to 23 metric tons per hectare during the period of the study. None of the sediment losses from other cultivated watersheds exceeded 10 metric tons per hectare. This need not always be the case, however, as Giles et_ al_. (1973) point out. If the land and animals are managed properly, so as to preclude overgrazing, loss of soil through erosion will likely be less from range and pasture lands than from intertilled soils. /14 e. Irr igated Cropland The practice of irrigation on agricultural land can yield water quality problems. As with most of the other agricultural practices discussed thus far, nitrogen, phosphorus and sediment all have a tendency to find their way into aquatic systems draining irrigated land. The accumulation of salts in the soil and in water, is an additional possible problem that must often be dealt with by irrigationists (Giles ejt al_., 1973; Branson et al_., 1975). With regard to increased sediment yields in irrigated watersheds, the quantity of water added as irrigation is generally in excess of the amount used consumptively by crops and stored in the soil . The excess drains away by surface runoff and deep percolation (Branson ejt al_., 1975). Increased surface runoff yields a corresponding increase in sediment removed by erosion. Nitrogen, phosphorus, and sometimes pesticides often adhere to the eroding soil particles. Thus, they may ultimately end up as part of the bed sediment of an aquatic system, and possibly act as a sink with regard to those pollutants. The quality of the irrigation water itself can have implications as regards the water quality of receiving aquatic systems. In many arid or semi-arid climates, the water used has a,high initial salt content. Under conditions of repeated irrigation, often necessary under such climatic conditions, the concentration of soluble salts in soils increases because most of the applied water is removed by evaporation and transpiration, leaving salts behind (Branson e_t al_., 1975). Increased concentrations of salts can also come about through the pickup of residual salts from manures and fertil izers. Branson et a l . (1975) suggest that, in order to prevent /15 salt damage to crops, irrigationists should increase, the leaching fraction of applied irrigation water. If this advice is followed, the salts as well as other soluble constituents, may be leached out of the rooting zone, and possibly down into the groundwater table. This practice can result in groundwater pollution, and possibly pollution of surface waters downstream or even kilometers away. Nitrate pollution of the groundwater table is currently of much concern to environmentalists, because consumption of water polluted with nitrates can bring about methehemglobinemia in babies (Viets and Hageman, 1971; Branson et_ al_., 1975). Phosphates, pesticides and trace elements have been found to move only very slowly, or not at a l l , into groundwater systems from irrigated land. This has been attributed to the relative insolubility of phosphorus and to the affinity that many pesticides and trace elements exhibit towards soil particles (Carter et al_., 1971; Muir et aj_., 1976). f. Non- irr igated Cropland Movement of pollutants out of non-irrigated cropland and into receiving aquatic systems has been found to depend upon such factors as: soil parent material and permeability, crop type and percent ground cover, percent of area t i l led and when t i l l ed , rainfall intensity, degree of slope, and the application of fertilizers and manures (Neilson and MacKenzie, 1977). Most of the above factors affect either water movement within a system, or sediment movement within a system, or both. Fertilizers and manures clearly affect the nutrient status of the system. /16 The major pollutants stemming from non-irrigated cropland are nitrogen, phosphorus and sediment. There is some indication that organic carbon can be of importance as a pollutant as well (Ritchie et al_., 1975). A study carried out in southwestern Quebec and southeastern Ontario to determine factors influencing nitrogen movement from agricultural areas, indicated that spring melt runoff alone brought about the loss of from 56% to 100% of annual soluble nitrogen lost. Also, the crop type and soil permeability were found to influence soluble nitrogen loss. Watersheds with more organic soils lost less soluble nitrogen than did watersheds with more mineral soils. Sediment was found to be a major agent of transport of nitrogen, moving from 22% to 67% of total watershed nitrogen. Land with a greater percentage of cultivated area was found to lose more sediment nitrogen (Neilson and MacKenzie, 1975). In another study carried out to determine nitrogen, phosphorus and potassium losses in surface runoff water and sediment in west-central Minnesota, i t was found that much of the annual sediment nutrient losses occurred during what was called a "critical erosion period". This corresponded to a period of time between the planting of a corn crop and two months after, indicating that tillage and cultivation may expose and lossen mineral soi l , making it susceptible to erosion. A "critical runoff period" caused by melting snow and ice, was found to be responsible for much of the annual soluble nutrient losses (Burwell et al., 1975). - ' -Another study where three soils were treated with phosphorus at 25 ug/g soi l , 125 ug/g soi l , and 625 ug/g soil in bare and cropped micro-plots, indicated that quantity of runoff water, eroded solids, and phosphorus in /17 runoff, increased with the degree of slope and r a i n f a l l in tens i ty . A high cor re la t ion (r = .997) was found between to ta l phosphorus in the runoff from bare plots and the quantity of s o i l eroded. Vegetation, or plant coyer, was found to be very effect ive in reducing runoff volume and s o i l erosion by increasing the quantity of water percolat ing into the s o i l (Munn e_t al_. , 1973). 2 . 3 . 2 U r b a n / I n d u s t r i a l Land Use Urbanization has been defined as the process of change in land occupancy and use resu l t ing from conversion of rural lands to suburban, indus t r i a l and urban communities (McGriff, 1972). I t i s generally characterized 'by an increase in population densi ty, and by increases in areas occupied by r e s i d e n t i a l , indus t r i a l and commercial establishments. As a r e su l t , the percentage of impervious area increases because of blacktopping and cementing of roads, sidewalks and parking l o t s . McGriff (1972) suggests that the two factors governing flow regimen in urban areas are the percentage of area rendered impervious and the rate at which runoff i s transmitted across the land to stream channels. The percentage of land that becomes impervious, i s a function of the land use pattern, while the overland t ravel time depends upon the densi ty, s i z e , and morphological features of t r ibu ta ry channels, therefore making i t dependent upon the provision of storm sewerage. The volume of runoff i s governed pr imar i ly by the i n f i l t r a t i o n cha rac t e r i s t i c s , and i s related to slope, s o i l type and vegetative cover. The increase in impervious surface area /18 in urban areas, as well as the use of storm sewers to collect and direct flow, intensifies runoff quantities. The above factors also serve to decrease the "staying time" of water within an urban area (i.e. decrease the lag time). In addition, the increase in impervious area inhibits the recharging of groundwater systems, so that urban areas, as well as experiencing higher peak flows are also likely to experience lower low flows. The frequency of the higher and lower flows will increase, as well, for the same reasons. Because of more rapid hydrologic response, and because surface runoff quantities are larger, the likelihood of heavy erosion of soil from vulner-able areas is increased. During urban development, particularly on the fringes of urban areas, large tracts of land are frequently stripped of vegetation, and graded, maximizing the possibility of erosion should surface runoff occur. Shopping centers, housing developments and industrial parks are largely the objects of such construction (Ryden et al_., 1973). Storm waters discharged into or in proximity to stream channels can increase the sediment load as well as the organic matter load. Urban runoff may contain significant quantities of such biodegradeable materials as lawn clippings, leaf sweepings, street l i t ter and oil (Peavy, 1977). As well as degrading the aesthetic quality of streams, such material often increases the BOD of the water. The dissolved oxygen content may already be less than it was or would be under natural conditions because of the removal of shading vegetation from stream banks, and the subsequent greater exposure of the stream to incoming solar radiation. Therefore the removal of such vegetation often yields an increase in stream temperatures, and a resultant decrease in the dissolved oxygen content of the water (McGriff, 1972). /19 In a study dealing with the water quality of an urbanized watershed in Burnaby, B.C. , Hall et al_. (1976), cited in Dorcey (1976), found that streams draining areas believed to have no fecal coliform contamination averaged less than 1000 organisms/100 ml of water during dry conditions. This number increased to over 4000 organisms/100 ml water during wet weather. Where there was an apparent cross-connection between storm and sanitary sewers, numbers increased significantly, and dry weather values were found to be as high as 23,000 organisms/100 ml of water. Wet weather figures were only about half of this for the same site. Because of this seemingly anomolous decrease in coliform concentration during wet weather, Hall deduced a point source as being responsible, and implicated faulty sanitary sewer installation as the cause. Animal wastes accompanying runoff may also to some extent be responsible for coliforms in storm water. Septic tanks in urban areas may pollute groundwaters with fecal coliforms as well. Urban/industrial land use has been found to contribute significant quantities of trace metals to aquatic systems (Wilber and Hunter, 1977; Hall et_ al_., 1976). Accumulations of metals may be manifest in the bottom sediments of such systems. Many metal ions have a positive charge and can be adsorbed onto sediment particles by virtue of the C.E.C. of the sediment. For this reason, Dorcey (1976) states that sediments tend to present an integrated history of the generation of toxic substances, including heavy metals, and their distribution in a drainage basin. As such, they often prove useful in defining source areas. The accumulation of heavy metals may also represent a sink, so that even after the input of heavy metal has \ /20 ceased, their presence in sediments and slow release, may s t i l l affect water quality for a long time thereafter. Lead, zinc and copper are those metals most often found in high concentrations in urban/industrial areas (Dorcey, 1976). Nickel, chromium and cadmium have also been found, but generally in lesser quantities (McCreight and Schroeder, 1977; Hall ejt al_., 1976). Lead in particular is often associated with roadways because it is a by-product of the combustion of gasoline. As well as having been detected in the sediments adjacent to thoroughfares, this metal has also been noted to occur in the soils and biota adjacent to thoroughfares (Mills and Zwarich, 1975; Getz ejt al_., 1977a; Getz et aj_., 1977b; McCreight and Schroeder, 1977; Bhoojedhur, 1975). The heavy metals, in general, are associated more with industrial land use than with residential or greenspace (Wilber and Hunter, 1977; Dorcey, 1976). Hall et al_. (1976) cited in Dorcey (1976) found much higher average concentrations of chromium, copper, mercury, nickel, lead and zinc in those sediments collected adjacent to industrial sites than in those collected adjacent to residential sites. He also found that in his study area, illegal sewer connections accounted for some high concentrations of nickel in stream water, and attributed this to the discharge of effluent by electroplaters. Wilber and Hunter (1977) found that the majority of heavy metals in the environment are associated with the combustion of fossil fuels and processing of metals. They indicate that industrial processes such as electroplating, oil and coal refining, and the manufacture of paints and biocides can complement the heavy metal content of aquatic systems. They conclude that metal loadings per unit area are generally much higher for industrial areas than for residential. /21 Nutrient loads from urban areas are most often traceable to mini-agricultural activities such as gardening and lawn fertilization. Sewage effluent can contribute to the nutrient status of an aquatic system, as can leachate from organic materials such as leaf l i t ter (McGriff, 1972; Ryden et al_., 1973). Phosphorus additions to aquatic systems in urban/ industrial areas are often closely related to sediment load and erosion. Hence, the major factors affecting surface runoff and erosion will also affect the input of phosphorus. Allen and Kramer (1972) also state that detergents from some areas can represent an important source of phosphorus. Dorcey (1976) noted that some pesticides may accumulate in bottom sediments of streams draining urban/industrial areas. Drawing from Hall et al_. (1976), he states that most of the pesticides found in the study area (i.e. Burnaby and New Westminster, B.C.) were mainly DDT and its degradation products. The highest concentrations of pesticides in sediments were found to occur in areas of extensive industrial land use, although some were also found in residential areas. The concentrations of pesticides in street surface materials did not reach those found in sediments, however, residential and greenspace street surface materials contained concentrations of DDT two to three times those found in industrial areas. This was attributed to the use of pesticides in parks, and on lawns and gardens. This also emphasizes the point that the flow characteristics of a stream may influence the distribution of substances within the watershed. Therefore, the occurrence of a given substance in the water or sediment from a given land use area, does not necessarily implicate that land use as the 722 contributor. The entire drainage area above a sampling site can have an impact on the quality of water at that site. 2.3.3 Forest Related Land Use a. Undisturbed Forest Land Some generalizations concerning the quality of water draining forested ecosystems can be made, although site specific factors often affect the water in any given system in unique and unpredictable ways. The water quality in undisturbed forested ecosystems is less affected by potentially polluting activities than are ecosystems that are disturbed by man. Streams flowing through these areas frequently have a lower nutrient concentration relative to other land uses (Giles et al_., 1973). Phosphorus concentrations are typically low as are nitrogen concentrations. A recent United States Environmental Protection Agency study concluded that streams draining forested watersheds had considerably lower nutrient concentrations than those draining agricultural watersheds. The same data also indicated that nutrient concentrations vary directly with the percentage of area under cultivation (United-States;Environmental Protection Agency, 1976). Under natural conditions, sediment load is relatively small because less mineral soil is exposed than is exposed by many of man's active land use activities. Biodegradeable material in such an undisturbed system generally decomposes at a relatively slow rate. It is , therefore, not often likely to cause significant water degradation (Peavy, 1977). /23 Various studies show the concentrations of nutrients in streams flowing through forested systems to vary negatively with stage height (Giles et al_., 1973). This is thought to possibly reflect the longer retention time of water in the soil during low flow periods. Other researchers contradict this observation, having recorded similar concentrations at both high and low flows (Likens et al_., 1967). The time of year has been found to relate to total nutrient loads carried by streams draining forested ecosystems. In one study, more than 96% of all nutrients in surface runoff were transported by snowmelt. Organic nitrogen comprised 80% of the total nitrogen load, and organic and hydrolyzable phosphorus comprised 45% of the total phosphorus load (Timmons et al_., 1977). This indicates that the nutrients picked up by the snowmelt runoff were taken from organic matter in or on the soi l , and indicates further that most of the nutrients flowing out of the system were organically complexed. Since, in many forested ecosystems the organic layers and surface mineral horizons are largely responsible for determining the nutrient status of that system, i t is likely that a disturbance of those layers might radically affect the energetics within that system, thereby affecting types and quantities of nutrients moving out. b. Disturbed Forest Land Any kind of logging method, especially clearcutting, can result in increased erosion. To a large extent, this can be attributed to greater exposure of mineral soil to surface flow and the force of falling 724 raindrops. After logging, sediment loads in streams may be as much as seven thousand times greater than sediment loads under natural conditions (Brown, 1974). This increase in sediment load is generally seen as the most serious problem associated with timber harvesting. Roads and road-building are seen as the major cause of erosion in harvested,watersheds. In this regard Brown (1974) states that the depth of roadbed and number and placement of roads influences the extent of erosion associated with construction. Nutrient losses also tend to increase because of forest harvesting. Be-cause erosion often increases, quantities -of nutrients-associated"with sediment moving out of the system will also increase. The organic debris left behind by logging eventually becomes nitrified, yielding a resultant increase in the concentration of nitrates in receiving aquatic systems (Giles et_ al_., 1973). The rate at which the nitrate concentrations decrease thereafter varies, ranging from one month to as much as six years (Brown et al_., 1973; Giles et al_., 1973). In conjunction with the nitrate concentration increases, concentrations of the major cations may also increase. Phosphorus concentration increases have been noted as well, but seldom are they as great as for those of nitrate (Peavy, 1977). Biological oxygen demand is liable to increase as a result of organic debris left in and adjacent to streams. Water temperatures may be affected by logging in proximity to stream channels. Because of its albedo, which may range from 10% to 20% (Barry and Chorley, 1968), a forest canopy prevents temperatures underneath i t from climbing as high as they otherwise might during the.day. Besides reflecting energy, the forest canopy traps energy underneath i t . This is largely a result of the fact that energy absorbed and re-radiated up to the forest /25 canopy by the forest floor, can be reabsorbed by the canopy, and again re-radiated back to the forest floor. Hence, the canopy can act quite l i terally as a "blanket", by serving to retain the energy underneath i t . The effect of the canopy on water temperature then, is often to mitigate against extremes of heat and cold. During the day, water temperatures will not rise as high as they might were the canopy not there, and at night time, because of the blanketing effect of the canopy, temperatures will not drop as low. Clearing of trees, therefore, results in more solar energy reaching the aquatic system during the daytime, causing temperatures to rise higher and more rapidly. In the night time, without the moderating influence of the canopy, water temperatures will drop further than they otherwise might (Barry and Chorley, 1968). Sediment in the aquatic system, brought about by logging will reduce the albedo of the stream itself, and hence cause i t to absorb relatively more solar radiation. Therefore, temperatures during the day will rise even higher (McGriff, 1972). The practice of slashburning can have important implications as regards water quality. It effectively removes much of the vegetation s t i l l remaining after harvesting. Therefore, erosion may be accelerated because of greater exposure of mineral soil . Hence, turbility in streams will increase. Slashburning also destroys organic matter debris on the ground, solubilizing or volatilizing many nutrients (Smith, 1970). Hence, erosion is further augmented, as well as are nutrient concentrations. /26 2.4 The Effects of Soil on Water Quality The effects that a soil may have on the quality of water draining that soil can be many and varied. Moreover, the ways in which soil does affect water quality are not always clearly understood, so that site specific factors preclude any definitive universal statements concerning the same. As expressed by Jenny (1941) soil is a function of climate, biota, parent material, relief, and time. Extending this concept, ,the chemical constituents of water are also a function of these same parameters along with the inclusion of soil as another dependent variable (Walmsley and Lavkulich, 1975). Soil texture, as well as reflecting the C.E.C. of a soil to some extent, also affects a soil's moisture regime. The C.E.C. is an important determinant of water quality, because i t can be responsible for the fixation or release of some soil nutrients, trace metals and pesticides. It therefore influences the avail-ability of some substances for leaching. The soil moisture regime is influenced by texture and structure in that together they largely determine the soil water storage capacity, as well as the flow rates of water through soi l . The amount of water stored in the so i l , and the duration of its stay there, clearly affects the degree to which soil water will reflect soil chemical characteristics. The longer the stay, the greater the potential for dissolution of soil minerals. In connection with this, the aeration status of the soil is reflected, as well, by texture and structure. The solubility and availability of some substances is dependent upon soil aeration (Devitt et al_., 1976). For example, Branson e_t aj_. (1975) state that information developed thus far shows nitrate concentration of tile drain effluents to be closely related to the soil profile characteristics that influence the aeration status of 727 the soil . Profiles that have textural discontinuities restrict water movement with the result that nitrate can be denitrified in the saturated zones. Slope position affects the movement of water on site, the aeration status of that site, and possibly the cation concentration of the soil water on that site. The cation concentration of soil water is important because i t can influence exchange reactions on cation exchange sites (Institute for Environmental Studies, 1972-1974). This is because some cation exchange sites exhibit an affinity for cations of a given charge, or of a given hydrated size, and may, therefore, exchange an ion that is currently occupying a site, for another that has been introduced from the water draining another site. This process can affect the quantities and kinds of cations available for leaching. Soil organisms directly affect the status of organic matter in the soil (Department of the Environment, 1972). They are primarily responsible for the form of nitrogen to be found in the soi l , which in turn may influence the mobility of nitrogen. They have been found to influence the movement of pesticides from a site. Laboratory studies have shown repeatedly that pesticides persist longer in soils that have been sterilized (Oloffs, 1975). In addition, soil organisms can directly or indirectly affect soil structure, either by turbation, or by encouraging granulation (Buckman and Brady, 1969). Soil structure can in turn affect the moisture and aeration status of the soil . /28 Soil organic matter can be of importance in determining the water quality of receiving aquatic systems (Devitt et_ al_., 1976; Viets and Hageman, 1975; Oloffs, 1975). In the form of humus, soil organic matter can have a high C.E .C. , and therefore affect the fixation or release of some substances in the soi l . In addition, i t can contribute to the nutrient status of an aquatic system. Organic matter, as well, has been shown to often complex with metal ions causing such ions to become more soluble in water, where they might otherwise be relatively immobile precipitates in the soil (Institute for Environmental Studies, 1972-1974). Hence, they may thus be made susceptible to leaching. Soil pH can affect water quality directly and indirectly (Institute for Environmental Studies, 1972-1974). Soil pH affects the solubility and mobility of many elements. The metals in particular may be affected by pH. The kinds and distributions of soil organisms can be affected by pH, and hence, so can the status of organic matter in the soil (Buckman and Brady, 1969). Finally, basic or acidic ions can be contributed directly to aquatic systems from the soi l , so that soil pH may directly account for the pH of receiving aquatic systems. The mineralogical composition of soil can affect water quality. Larkin (1974) points out that in the north of Canada, on the slowly dissolving granitic rocks of the Canadian Shield, lake waters are generally low in dissolved minerals, and in the acid range of pH. On the sedimentary deposits of the prairies, lakes are relatively high in dissolved minerals, and are /29 alkaline. Further, Warren (1975) indicates that the natural concentrations of metal ions in the soil may be relatively high in any given location. The water draining such soils may reflect this. 2.5 The Effects of Bottom Sediments on Water Quali ty The bottom sediments of aquatic systems can have a profound influence on the water quality of that system. Clay and organic matter in the sediment often cause i t to have a significant cation exchange capacity. Therefore, i t is capable of accumulating pollutants such as trace metals and chlorinated hydrocarbons (Dorcey, 1976). In addition, any positive ion is capable of being adsorbed onto the surfaces of the sediment particles, so that the concentrations of such nutrients as calcium, magnesium and ammonium in the water may be thus affected. An affinity for phosphates is also often displayed by bed sediments. The phenomenon of phosphate accumulation within bed sediments is well documented (Duffy e_t al_., 1978; Schuman e_t al_., 1973; Ritchie et al_., 1975; Gill et al_., 1976). Such accumulations can often be attributed to the presence of ferric and aluminum oxides and hydrous oxides as a component of the sediments (Ryden ejt al_., 1973; Allen and Kramer, 1972). The phosphates are generally thought to be either associated with the surfaces of such oxides and hydrous oxides, or within the matrices of such materials (Ryden et al_., 1973). Also, since clay sized particles, and much of the organic sediment, are of a relatively fine size, they tend to settle out only under very quiet water conditions. Hence, they are more likely to be found on the bottoms of backwaters within aquatic systems (Dorcey, 1976). This means that accumulations of pollutants and nutrients in bottom sediments is likely to be more pronounced in the less turbulent areas of aquatic systems, where fine sediments can settle out of suspension more readily. /30 Another important characteristic of sediments with regard to water quality, is their mineralogical composition. As is the case with soi l , the minerals in sediments may be subject to solubilization, especially under varying pH conditions. As a consequence, the water chemistry may change accordingly. Wilber and Hunter (1977) in an evaluation of urban water quality in New Jersey found that the scouring of bed sediments was a secondary source of trace elements. It is important then to consider sediment as both a potential source of pollutants, as well as a potential sink for pollutants (Allen and Kramer, 1972). Other factors such as pH and aeration will determine its behavior in that regard, at any given time. Agitation of sediment/water suspensions has been found to cause sediments to release greater quantities of minerals, nutrients and other potential pollutants into aquatic systems than might otherwise come about under undisturbed conditions (Allen and Kramer, 1972). Therefore, any physical disturbance of sediments under natural conditions may cause the same effect. This is of greatest significance in the backwater areas of natural systems, for the reasons stated above. The nature of the sediment/water interface can also influence water quality (Allen and Kramer, 1972). For the purpose of defining nutrient exchange mechanisms in aquatic systems, bed sediments can be divided into at least two main types. This division is based on the presence or absence of a well defined sediment/water interface. In the former case, nutrient exchange may be limited by rates of diffusion, the presence of an oxidized surface layer, and the activities of burrowing animals. In the latter /31 case, considerable exchange may be effected by wind generated currents and turbulence, causing the sediment to become more thoroughly mixed with the water. 3. STUDY AREA DESCRIPTION 3.1 Location and Extent The study area is situated in the southern extremity of British Columbia, on the Fraser River Delta. It is fully within the Municipality of Delta, B.C. (Figure 1). It is bounded on the north by the south arm of the Fraser River, and on the west by the Strait of Georgia. On the south and east, the study area boundaries are less well defined because there are no distinct geomorphic discontinuities determining the direction of flow of water into the area. Most of the study area exhibits l i t t l e or no relief, hence proximity to water courses must dictate the south and east boundaries. Therefore, the south boundary is defined approximately by the Roberts Bank Railway, which runs east-west from Georgia Strait to about 68th Street, then north to about 44th Avenue, and then east-west again. The eastern boundary is defined by about 80th Street. 3.2 Climate The climate of the study area has been described alternately as West Coast Maritime (Terris, 1973), Maritime (Queen's Printer, 1975), and Marine (Luttmerding and Sprout, 1969). Because of the influence of the Pacific Ocean, the area generally experiences moderate to high average annual rain-f a l l , and a small annual range of temperature?. Average annual precipitation Figure 1. Location of study area-/33 SOURCE: HOOS 8 PACKMAN, 1974 AVERAGE ANNUAL PRECIPITATION (mm) JANUARY MEAN TEMPERATURE (°C) Figure 2. Average annual precipitation and January mean temperature for the Lower Fraser Delta. /34 20. i s ! 16. 14. ? 12. uJ 10. < oc LU Q_ 8. 6. 4. 2. 6. A B TEMPERATURE (45 Yrs.) PRECIPITATION (45 Yrs.) 1 JAN FEB MAR APR MAY JUN JUL AUG SEPT OCT NOV DEC ANN. ? 4 3.9 5.6 8.9 11.7 14.4 16.7 16.1 13.3 9.4 6.1 T 9 126 97 77 51 47 40 28 32 61 98 \6f \6t "931 200 180 160 _I40 J 2 0 _I00 I 80 I 60 I 40 I 20 .1 0 E E O < Q_ O UJ CC Q_ A MONTHLY AND ANNUAL AVERAGE TEMPERATURE B. MONTHLY AND ANNUAL AVERAGE PRECIPITATION (°C) (mm) Figure 3. Monthly and annual average temperature and p r e c i p i t a t i o n f o r the Ladner C I ima to l og i c a l S t a t i o n , D e l t a , B.C. (Source: B.C.D.A., 1965). /35 20. 15. o UJ rr < r r Ld Q_ LU 10. 5. -200 PRECIPITATION / / LI50 ~ E E _ioo 2 i— < Q_ O UJ 50 £ AUG OCT DEC FEB APR JUN AUG '76 SEPT NOV JAN MAR MAY JUL '77 A — 15 10 6 5 2 7 6 10 II 15 16 18 B 63 50 72 42 100 41 42 56 29 28 7 24 54 0 A. MONTHLY MEAN TEMPERATURE FOR STUDY PERIOD B. MONTHLY PRECIPITATION FOR STUDY PERIOD Figure 4. Monthly precipitation and monthly mean temperatures for study period (Source: Environment Canada, 1978) /36 is about 940 mm, of which 70% is generally received between the months of October and March (Taylor, 1950). The mean annual temperature is about 10°C, seldom exceeding 32°C, and seldom falling below -12°C (Queen's Printer, 1975). The summer months can be droughty, the severity of which can vary considerably (Taylor, 1950). The normal length of the frost free season is 183 days. The growing season, based on a temperature of 16°C, is 243 days (Luttmerding and Sprout, 1969). Figures 2 and 3 indicate the average climatic conditions generally experienced in the study area. Figure 4 shows the temperature and rainfall conditions throughout the period of this study. While temperatures were generally normal for this period, the amount of precipitation received was considerably below normal. These conditions are likely to have affected study results, as is explained in more detail later in this report. 3.3 Soi l s and S u r f i c i a l Geology Soils in the study area have developed from recent unconsolidated deposits of Fraser alluvial and organic material (Figure 5). The land upon which the alluvial material was deposited is nearly level to gently undulating. The main organic deposit in the study area is known as Burns Bog, and is primarily a sphagnum bog. According to Luttmerding and Sprout (1969) the study area is located entirely within the lowland section of Delta Municipality. In this area, elevations above sea.level seldom exceed 6 meters. Drainage is poor, and therefore artif icial drainage is often necessary in order to ensure high crop yields from the agricultural lands in that part of the municipality. /37 SOURCE•« ENVIRONMENT CANADA , 1977 FIGURE 5: Surficial Geology of Study Area 738 All the mineral soils in the study area have developed from mixed marine and non-marine deltaic deposits. They are comprised mainly of s i l t loams, silty clay loams, or silty clays, 0.15 meters to 3.5 meters thick, overlying 15 meters or more of fine to medium sand (Luttmerding and Sprout, 1969). Organic deposits occupy about one third of the lowlands in Delta and Richmond Municipalities map area, and vary in thickness from 0.6 to 6 meters (Luttmerding and Sprout, 1969). Luttmerding and Sprout (1969) conducted a detailed soil survey of Delta and Richmond Municipalities. The information contained in this part of this report is derived from that British Columbia Department of Agriculture (B.C.D.A.) publication. The reader is also refered to the soils map which accompanies the B.C.D.A. report for information concerning the distribution and extent of the various soil series in the study area. The mineral soils in the study area are moderately poorly to very poorly drained, and are all Gleysols. Owing to the recent nature of the parent material, profile development is often not well advanced, so that most of the soils are either Rego Humic Gleysols or Rego Gleysols. Saline conditions are encountered at various depths in most soils in the study area. These saline conditions result from seawater entering sandy lenses in the so i l , under hydrostatic pressure. Some soils are strongly saline to the surface, although most are not strongly saline in the uppermost meter. The organic soils are all located in, or in association with Burns Bog on the eastern extremity of the study area. Of the four organic soil series in the study area, three; the Annacis series (Typic Humisol), the Lumbum /39 series (Typic Mesisol), and the Triggs series (Sphagno-fibrisol), are deep (i.e. greater than 1 m). The fourth, the Richmond series (Terric Humisol), is shallow. All of the above are very poorly drained. Detailed descriptions of all of the soil series found in the study area, as well as soil chemical data may be found in the afforementioned B.C.D.A. publication 3.4 Biota The study area can be broadly subdivided into three ecological areas: a. Wetlands b. Burns Bog c. Developed land Each of these three categories possess some unique biotic elements, and each possess some elements in common. a. Wetlands The marshy areas surrounding Ladner Slough and Deas Slough constitute the major portion of this ecological class. Bourque and Adams (1975) have carried out a thorough environmental assessment of Ladner Slough and its immediately surrounding environment. Little information of the same sort is available as regards Deas Slough. It is likely that some of the character-istics of Ladner Slough are characteristic of Deas Slough as well, but this remains unverified. Detailed analysis of Ladner Marsh in December 1974 by Bourque and Adams identified at least ten microcommunities of terrestrial and emergent vegetation. For the most part, vegetation in this area consists of Black Cottonwood (Populus Trichocarpa), Red Alder (Alnus Rubra), and Willow (Salix spp.) in /40 the overstories of the drier sites. Cattails, Bullrushes, sedges, fescues, water plantain and duckweed constitute the major vegetative types in the wetter areas. Ladner Slough accommodates a variety of fish species, including such fish as the redside shiner, carp and sturgeon. Some have also been found to occur in Cohilukthan Slough. Many other species are assumed to feed or take shelter in Ladner Slough. There is also some indication that Chinook and chum salmon may frequent the area near the sewage lagoon outlet. There is very l i t t l e information on the number of bird species that frequent Ladner Marsh. The Willow, Alder., and Mixed Brush and tree commun-ities west of the sewage lagoon appear to be heavily used for nesting. Litt le is known of the other forms of wildlife found west of the sewage lagoon. Opossum (Didelphis marsupial is virginiana), shrews (Sorex spp.), muskrat (Ondatra zibethica osoyoosensis), mink (Mustela vison energumenous), skunk, racoons (Procyon lotor pacificus), rabbits, and red rox (Vulpes fulva  cascadensis) have all been observed west of the sewage lagoon. Beak Consultants (1977) indicate that various different species of frogs and toads, as well as other species of amphibians and reptiles inhabit the marshland in proximity to Roberts Bank Superport. Bourque and Adams (1975) postulate the probable occurrence of similar species as components of the Ladner Marsh environment. b. Burns Bog A comprehensive ecological inventory of Burns Bog was carried out by Biggs (1976). He classified the area into eight ecological zones. He found that species' diversity and plant growth increase from the center of /41 the bog, which is "heathland", to the perimeters, which include the more woody vegetation such as birch, alder and pine. The heathland was found to have no significant tree overstory. Avian inventories and consultation with ornithologists with experience in the Burns Bog area, accounted for the recording of 145 bird species. Biggs estimates that over 10,000 dabbling ducks use the "lakes", which are a result of peat cutting operations in the bog. Mixed coniferous/deciduous woodlands at the eastern edge of the bog are believed to be important nesting and feeding habitats for most passerine bird species found within the bog. Large trees at the perimeter of the bog are believed to be an important natural refuge for a number of raptorial birds. A total of twenty species of mammal were recorded by Biggs from sightings and signs. Columbian blacktailed deer (Odocoileus hemionus columbianus), and black bear (Ursus americanus) were noted amongst these. Many of the floral and faunal species found in Burns Bog have also been reported by Bourque and Adams (1975) in and around Ladner Marsh. c. Developed Land This is the land in the study area that has been developed by man into either urban or agricultural land. No ecological inventories are available with regard to this area, but i t is most widespread, and adjoins both of the other ecological areas. Elements of either of the first two ecological areas probably penetrate into this third ecological zone. Hence, Biggs (1976) suggests that, wherease raptorial birds might take refuge in the trees at the edge of Burns Bog, they probably do much of their hunting in the treed areas. /42 The land use pattern of this third area will be discussed at length later in this report. 3.5 Hydrology a. Surface Waters The Ladner area is , for the most part, art i f ic ial ly drained. Ditches constructed for this purpose are widespread throughout the region, most of which drain ultimately into either Crescent Slough or Cohilukthan Slough (see Figure 6). Both Crescent Slough and Cohilukthan Slough are natural channels that have been improved, and equipped with pumps at their outlets. Bourque and Adams (1975) state that Cohilukthan Slough acts as a storage and drainage channel for a large area of agricultural land south of Ladner town center. The only time significant quantities of watenare discharged from this drainage system, is during the winter months when precipitation amounts are high. The discharge rates from the combined pump and floodbox system vary considerably, and are dependent upon precipitation, soil water storage, and tidal ranges. From May to September inclusive, discharge from this slough is generally insignificant due to irrigation, evaporation and available storage in the soil and ditches (Bourque and Adams, 1975). Detailed information of the same sort is not available for Crescent Slough, however i t too is equipped with combined pump and floodbox systems. One of these is at the southern outlet of Crescent Slough, and empties into a channel that feeds Deas Slough primarily, and possibly, to some extent, Ladner Slough. The second of these systems is located at the northern outlet of Crescent Slough, and empties into the Fraser River via Tilbury Slough. Crescent Slough drains a relatively larger area of agricultural /43 NATURAL SURFACE DRAINAGE PATTERNS ARTIFICIAL DRAINAGE DITCHES FIGURE 6: Drainage Map of Study Area /44 land than does Cohilukthan Slough. As with Cohilukthan Slough, it too drains some urban land. Urban stormflow is generally routed into the underground urban stormflow system f irst , and then is directed to either of the above two sloughs. The drainage system is all ultimately interconnected by way of the numerous smaller ditches criss-crossing the study area. These smaller ditches were observed to be often dry during periods of low rainfall , but were functional in wet weather. The major sloughs, however, were functional throughout the study period. During the usual summer drought period (July to August), irrigation of crops is often necessary. Irrigation water in Delta is obtained mainly from the surface drainage system, although water from the Fraser River is available to farms along the river margins (Luttmerding and Sprout, 1975). b. Groundwater No detailed information concerning the groundwater system in the study area could be obtained. Luttmerding and Sprout (1975) have noted that all soils in the study area are poorly drained, as a result of high water tables, slow infiltration and slow surface runoff. In addition, the area receives some seepage from the upland regions on the.periphery of the study area. Water tables are highest during the wet winter months, when they have been observed to rise to the surface in many places. They are likely to be lowest during the summer months, when precipitation is low, and the practice of irrigation is ongoing. There is no information concerning the time response of the groundwater system to precipitation events. 745 There is also no information concerning the time response of the groundwater system to ocean tides. Luttmerding and Sprout (1969) have noted that seawater does infiltrate into the soil through sandy lenses. They also indicate that most mineral soils in the area are salty at some depth in their profile. Hence, i t might be inferred that seawater affects the groundwater system throughout the entire study area, to some extent. No artesian systems are known to intrude into the study area (Halstad, 1978). 3.6 Land Use a. Land Use History Terris (1973) has written a comprehensive review of the settlement and development of the Ladner area. This part of this report is derived largely from that review. Agriculture and fishing have played an important part in the settlement and development of the Ladner area. Much of the land first occupied by settlers was used for agriculture, because of the fertile soils and the~mild climate of the region. The earliest crops of importance were: timothy hay, oats, potatoes, tree fruits and berries. Livestock was the principal source of income (Curator, 1978). Prior to the completion of the Canadian Pacific Railroad in 1886, most trading was carried out with the urban center of New Westminster. Transportation to and from New Westminster was by boat only, via the Fraser River. 746 The first fishermen settled in three main areas: Ladner's Landing, Port Guichon, and Canoe Pass. Salmon canning was the first important form of manufacturing in Ladner. Due to its close proximity to metropolitan Vancouver, Ladner has rapidly changed in the past three decades to include large-scale urban, commercial and industrial development (Luttmerding and Sprout, 1969). The land use history of Burns Bog is not well documented. Various attempts to clear and manage the periphery of the bog have been initiated by agriculturalists attempting to bring the shallower peat deposits into production. Such attempts have served to reduce the size of the bog from 4856 ha to its present size of approximately 4000 ha (Biggs and Hebda, 1976). b. Present Land Use i . Land C l a s s i f i c a t i o n System For the purposes of this report, land use in the study area was classified into four categories: Urban, Agricultural, Forested and Bogs. Urban land was deemed to be that which is occupied by either residential, commercial or industrial concerns. Roads and road right-of-ways were included as a part of urban industrial land. Agricultural land was considered to be that which is occupied primarily by any form of agriculture. Hence, no differentiation was made between crop farming and dairy farming, or poultry farming, etc. Forested land was considered to be land, other than bogs and marshes, which is essentially treed. This does not imply that it is unused by man, but that i t is unused directly for either agricultural or urban concerns. /47 Bogs and marshes were classified as such on the basis of soils, drainage and, to some extent, vegetation. This class includes poorly drained, organic soils, that are unused for either agricultural or urban concerns. i i . D i s t r i b u t i o n and Extent of Present Land Uses As stated previously, the boundaries of the study area are not well defined. Relief is functionally insignificant as regards the determination of the direction of water flow. Soils are, texturally, quite homogeneous, so that the determination of watershed boundaries on the basis of inferred hydraulic conductivities is extremely difficult and unreliable. The situation is made more complex by the fact that the entire drainage system in, and in proximity to, the study area is totally interconnected due to the extensive network of smaller drainage ditches throughout. In addition, drainage outlets occur not.only in association with Crescent Slough and Cohilukthan Slough, but also to the west of the study area, and to the south of the study area. Therefore, determination of study area boundaries on the basis of surface water potential gradients is impossible. , Study area boundaries, then, were delineated very roughly on the basis of proximity to given sloughs and outlets. For this reason, land use areas stated herein, must be considered as approximate. Land use boundaries were discerned by aerial photo-interpretation (see Figure 7). The study area is roughly 5300 ha in extent. Various kinds of urban land use comprise about 700 ha of the area. Urban residential land is located predominantly around the urban center /48 FIGURE 7: Study Area Land Use /49 of Ladner and makes up about 550 ha of the total study area. The urban center itself is about 20 ha and borders on the south shore of Ladner Slough. The immediate area bordering on the south side of Ladner Slough is zoned for light industrial, family residential, and comprehensive development (Bourque and Adams, 1975). The north side of Ladner Slough is zoned exclusively for public recreational use. (Bourque and,Adams, 1975). This does not-appear--to-affect the operation of the Ladner sewage lagoon, which is situated immediately adjacent to Harbour Park on that side of Ladner Slough. It receives sewage from the urban area via an underground sanitary sewer system, which is independent of the storm sewer system draining the area (Municipality of Delta, 1978). It serves about 4200 people, occupies about 6.5 ha, and is 2 m deep (Kucy, 1977). The sanitary landfill area on the southwest corner of Burns Bog was also classified as urban land. It occupies about 50 ha. There is a strict set of guidelines governing the dumping and burning of refuse in this area (Biggs, 1976). With regard to drainage of this landfill area, Golder, Brawner and Associates Ltd. (1973), cited in Biggs (1976), discovered that about 95% of the landfill seepage rises to the ground surface within 3 m of the toe of the landfi l l . Thereafter, i t is generally intercepted by the peripheral ditching system. There are approximately another 60 ha of urban land in the study area, that are comprised primarily of roads and road right-of-ways. The majority of this land is occupied by Highway 99 and Highway 17. The remainder is interspersed throughout. /50-Agricultiiral land is by far the most widespread in the area. It comprises about 3500 ha of the total. Dairying, once the dominant agricultural activity, has declined in recent years. Now, the majority of dairy farmers are located in the eastern portion of Delta (Curator, 1978). In these areas, grass-clover forage mixes and silage corn are the main crops (Luttmerding and Sprout, 1969). Cash cropping has essentially replaced dairy farming in the western portion. Crops include: potatoes, sugar beet seed, cereal grains, strawberries, corn, canning peas, and beans (Curator, 1978). Drainage of agricultural land is accomplished by way of the extensive network of ditches throughout the area. Homes on agricultural land generally make use of septic tanks and sub-surface drainfields to deal with sewage. (Municipality of Delta, 1978) Forest land is not widespread throughout the study area. This land type occurs in small patches, and makes up about 100 ha of the total study area. Marshes and bogs occupy about 1000 ha in the study area. Approximately 900 ha of Burns Bog contributes water to the area. Ladner marsh makes up most-of the remaining 100 ha. of this land use type. Burns Bog is approximately 85% privately owned. Peat extraction is the most widespread land use in this area, and goes on actively 24 hours a day, and 7 days a week. Various kinds of transportation and communication corridors are restricted to the periphery of Burns Bog. These include roads, railways, radio towers, and service corridors. An integrated system of open drainage ditches, culverts and pump stations drain the peripheral lands (Biggs, 1976). /51 4. EXPERIMENTAL DESIGN 4.1 C r i t e r i a for Select ion of Study Area The area was selected for study for the following reasons: a. The area combines a variety of land uses b. It possesses an extensive drainage network throughout the various kinds of land uses c. Parent material, climate and topography are all quite homogeneous over the entire study area, hence limiting the number of variables to be considered in the analysis of results. d. Some parts of the area are of environmental interest to other agencies. This is especially true of Ladner Slough and Ladner Marsh, with which the Westwater Research Center and the Municipality of Delta are s t i l l concerned. e. Access to sampling sites was facilitated by numerous roads and highways within the area. 4.2 Sampling Design 4.2.1 C r i t e r i a for Select ion of Sampling Points The study area was observed first from the ground, with reference to available maps'. Appropriate sampling sites were tentatively chosen. Sites were selected so as to provide the maximum potential for discerning land use contributions to water quality. In this regard, an attempt was made to locate them both within land use areas, and within transition zones between land use areas. /52 Only Cohilukthan Slough, Crescent Slough, Ladner Slough, and Deas Slough were chosen for sampling. The former two were selected because of their intimate association with the land. Ladner Slough was selected because Cohilukthan Slough empties into i t , and also because i t has been the object of much environmental study in the recent past. Deas Slough was selected in order to provide a basis for comparison of water quality in Ladner Slough. Land use around Deas Slough is not as intensive as i t is around Ladner Slough. The numerous smaller ditches throughout the study area were not sampled because i t was felt that their influence, i f profound, would be reflected in the water quality of the receiving slough (i.e. Cohilukthan or Crescent Sloughs). Also, time did not permit any more extensive sampling procedure. Subsequent aerial photo-interpretation revealed that the sites chosen were appropriately placed for the purposes of the study. Specific site locations and characteristics are discussed in greater detail in section 6.2.2 of this report. 4.2.2 Sample Collection Methods and Sampling Frequency a. Water Samples Water samples were collected on the following dates: August 24, 1976; October 8, 1976; November 2, 1976; December 8, 1976; January 12, 1977; February 15, 1977; March 10, 1977; April 4, 1977; August 3, 1977. /53 It was felt that, by sampling approximately once a month throughout the winter, and once near the end of each summer, water quality in all of the chosen sloughs could be adequately characterized with regard to the normal annual hydrograph. This, however, did not prove to be the case because the climate throughout the study period was atypical of that normally experienced? (see Section 3.2). Water samples were collected in acid washed, distilled-water rinsed, 500 ml plastic bottles. When all samples had been obtained on a given sampling date, they were immediately taken back to the pedology laboratory at the University of British Columbia, and refridgerated, to await analysis. A second water sample was collected at each site, on each sampling date, in 125 ml acid washed and distilled-water rinsed bottles. These samples were for the analysis of phosphorus'content. They were immediately-taken back to the pedology laboratory at the University of British Columbia, and frozen until enough had been accumulated to facilitate efficient analysis. b. Sediment Samples Bottom sediment samples were-collected- twice throughout the twelve month study period, on the following dates: -October 8.,- 1976;. MaVeh-10, 1977. Sediment samples were collected so as to aid in differentiating between the effects of land use on water quality, and the effects of sediment on water quality. Land use effects on sediment were also of interest. A grab sample was taken at each water collection site on the dates mentioned above. An attempt was made to acquire the material from the top 754 5 to 8 cm of the streambed. Samples were then placed in plastic bags, numbered for future identification, and taken immediately back to the pedology laboratory. There, they were set out to air dry. When dry, the samples were crushed and sieved through a 2 mm sieve. They were subsequently placed in plastic bags, labelled and stored to await analysis. c. Soi l Samples Soil samples were collected at the same times as were sediment samples. It was felt that these samples would allow for the differentiation between land use effects on water quality, and the effects of soil on water quality. Samples were taken from the top mineral horizon (A horizon) adjacent to each water sampling site. In addition, samples from each of the two parent materials (alluvial and cumulose) were taken at three depths, on each of the sampling dates. Samples from the A, B, and C horizons of the alluvial material were collected at 15 cm, 30 cm and 65 cm depths respectively, from Site 6 on Cohilukthan Slough. These samples represented the Crescent soil series. Samples from the Of, 0ml and 0f2 horizons of the cumulose material were also collected at 15 cm, 30cm, and 65 cm depths from within 200 m of site 12 on Crescent Slough. These samples represented the Lumbum soil series. The samples were placed in plastic bags and transported back to the pedology laboratory. They were subsequently treated in the same fashion as were the sediment samples. /55 4.3 Analy t i ca l Methods 4.3.1 Parameter Select ion a. Water The water quality parameters selected for study were those whose presence and effects have been previously documented by other researchers, and have been found to be of potential environmental significance. Therefore, attention was paid to the presence of: cadmium, lead, zinc, copper and aluminum. Iron and manganese were also studied because they had previously been reported to occur in the area as a result of drainage from the sanitary landfill area near Burns Bog (Biggs, 1976). Mercury was not studied because there was not thought .to be a source of this metal in the area. Mercury pollution has been found most often in association with pulp mill operations (Larkin, 1974). Water samples were analysed for nutrients including: total nitrogen, soluble nitrogen, and phosphorus. Percent carbon was included. These parameters have often been found in high concentrations in runoff from agricultural land. Water samples were analysed for the major cations: potassium, sodium, calcium, and magnesium. This was done partially to aid in defining the extent to which seawater intruded into the study area. Also, certain land use activities, such as fertilization, can affect the concentrations of some major cations in receiving waters. Potassium especially is often a primary constituent of many commercial fertil izers. 756 Water temperature, dissolved oxygen, and pH were measured, as well. Dissolved oxygen is related to water temperature and atmospheric pressure (which was also noted on each sampling date). Water pH can affect the solubility and availability of many materials, as well as, affecting the quality of the aquatic environment itself. An attempt was made to measure suspended sediment. Its affects on water quality have been well documented, and relate to both the chemical and physical status of water. b. So i l s and Sediments Wherever possible, the same soil and sediment parameters were measured with the same analytical techniques, as were for the water samples. Hence, all of the aforementioned metals, nutrients and major cations were measured. In addition, a particle size analysis was carried out for each soil and sediment sample, as well as a determination of cation exchange capacity. 4.3.2 F ie ld Methods Water temperature and dissolved oxygen were measured in the field. Both measurements were made with a Yellow Springs Instrument Co. Inc. Model 54 Oxygen Meter, at a depth of about 5 to 8 cm below the water surface. No soil or sediment analyses were conducted in the field. 57 4.3.3 Laboratory Methods Unless otherwise indicated, all laboratory analyses were carried out in accordance with methods outlined by Lavkulich (1977). Specific procedures used are identified in this report by the tit le used in that publication. Unless otherwise specified, Black et al_. (1965) is another reference for all such procedures. a. Water The 500 ml water samples were filtered through individual pre-weighed Whatman No. 4 f i l ter papers. The f i l ter papers and any accompanying sediment were then air dried, and re-weighed. The results thus obtained were extremely variable because large pieces of organic matter and numerous kinds of small aquatic biota interfered with this determination. The results were not thought to accurately reflect differences in suspended sediment loads on and between the various sampling dates. The pH of the water samples was measured directly with a Model 245 Instrumentation Labotatory Inc. pH/Mv Electrometer. Major cations and all metals, except lead, were measured directly with a Perkin-Elmer Model 306 Atomic Adsorption Spectrophotometer. Lead in samples was measured on the same machine, after the samples were concentrated by first evaporating to dryness, and then redissolving the residue in a smaller amount of 10% H^ SO^  solution. The spectrophotometer, however, was init ial ly found to be extremely insensitive to lead at low concentrations. This was subsequently determined to be a result of the specific lamp used for lead with the spectrophotometer. When the lamp was replaced by a new lamp, in the later stages of the study, more consistent and accurate results were obtained. 758 Specific conductance was measured directly with a radiometer type CMD 2e conductivity meter, and a CDC 104 ce l l . Total nitrogen concentrations were determined according to the method entitled "Total Nitrogen Determination--Colourimetric by Auto Analyser--For Soils and Plant Material". One modification was made to the method so as to accommodate water samples. Rather than weighing out a given quantity of soil or plant material, 100 ml of sample water was used, and evaporated to near-dryness. It was then digested as outlined in Lavkulich (1977). After digestion was complete, the samples were made up to a volume of 25 ml, and the concentration of total nitrogen was read from a {technicon Auto Analyser II. Calculations were adjusted accordingly. Soluble nitrogen was measured as soon as possible after collection and filtration of water samples. Analysis was conducted according to the procedure entitled, "Nitrate-N Determination in Water or Soil Extracts". Results were read from a Turner Model 330 Colourimeter. West and Ramachandran (1966) is another reference for this procedure. Percent carbon was determined by the Walkley-Black titrimetric procedure described in Lavkulich (1974). Lavkulich (1977) subsequently indicated a modification to this procedure, whereby water samples are first evaporated to dryness before any analysis is carried out. This was not indicated in Lavkulich (1974) and hence, the values shown in The Appendix, may be in error. However, they can be assumed to reflect the easily oxidizable fraction of organic matter in water and may therefore also be valid as indicators of water quality. /59 Samples for phosphorus determination were thawed and filtered through Whatman No. 42 f i l ter paper. Total phosphorus was then measured according to the method entitled "Phosphorus: Total Phosphate", which is described in McQuaker (1973). It is also described by Strickland and Parsons (1968). b. Soi l s and Sediments The pipette method was used to determine particle size distributions for all of the mineral soil and sediment samples. A 5% sodium hypochlorite solution was used to destroy any organic matter in the samples. The sodium acetate method (pH 8.2) was used to determine cation exchange capacities of all soil and sediment samples. The pH of all soil and sediment samples was measured in water, and in 0.01 M CaCl 2 . A 1:2 soil to water ratio was used for mineral samples, and a 1:7 soil to water ratio was used for organic samples. Available metals and major cations were extracted from soil and sediment samples with a 0.1 N HC1 solution. Concentrations of these constituents were read from a Perkin-Elmer Model 306 Atomic Adsorption Spectrophotometer. Analysis for specific conductance proceeded generally according to the "Saturated Soil Paste Extract" method. However, a 1:10 soil to water ratio was used, rather than a saturated paste extract. This allowed for the determination of sample conductivities relative to one another, which was adequate for the purposes of this study. A Radiometer Type CDM 2e conductivity meter and CDC 104 conductivity cell were used to measure conductivities. Jackson (1958) is a reference for the "Saturated Soil Paste Extract" method. /60 Total nitrogen determinations were done using the method entitled, "Total Nitrogen Determination—Colourimetric by Auto Analyser--For Soils" and soluble nitrogen determinations were done using the method entitled, "Nitrate-N Determination in Water or Soil Extracts". Results were read from a Turner Model 330 Colourimeter. West and Ramachandran (1966) is a reference for this method. Percent carbon was determined using the Walkley-Black Titrimetric Method. Phosphorus contents in soil and sediment samples were determined using the method entitled, "Phosphorus Determination in Soil". Results were read from a Turner Model 330 Colourimeter. 5. DATA ANALYSIS TECHNIQUES 5.1 Statement of Rationale Data in this report is dealt with in two ways. Many of the analyses that follow are of a statistical nature, and hence, are quantitative, or objective analyses. Others are of a subjective or qualitative nature, and are not designed to characterize data concisely. These latter are used more for general comparative purposes. The data was used to determine which water quality parameters might best be relied'upon to reflect the effects of land use on water quality in the study area, and which water quality parameters behaved in fashions similar to others. In this latter regard, an attempt has been made, /61 whenever possible, to indicate trends over time, with respect to the study area as a unit, the various sloughs within the study area, and the water quality parameters measured. Such trends were considered important insofar as they might relate to climatic trends. Also, many land use practices are carried out in accordance with season (e.g. agriculture), and it was thought that such seasonal practices might be discernable on the basis of water quality. Data was first considered with respect to the entire study area as an experimental unit. A percent coefficient of variation analysis was carried out by month, in order to determine those water quality parameters that were most likely to be of use as estimators of land use effects on water quality. It was felt that those water quality parameters whose concentrations were the most variable throughout the study period might include those that respond most readily to land use practices. It was recognized, however, that a conservative estimator, such as titanium for example, might show l i t t l e variability relative to other parameters, but also that such variability might be of significance relative to that parameter. Attention was paid to the pattern of variability of each of the parameters with time, because of possible seasonal influences, as discussed above. A monthly correlation matrix was calculated for all of the parameters, in order to aid in determining which might be responding to the same factors. The months in which a given significant correlation occurred were noted so as to further aid in evaluating seasonal influences. Finally, a subjective curve analysis technique was originated and employed in order to determine i f the concentrations of any water quality /62 parameters followed some seasonal trend, and which parameters, i f any, exhibited similar patterns over time. This technique, which will be discussed in detail later in this report, is analogous to the super-imposition of curves, each representing a given parameter concentration versus time, and the noting of differences and similarities in respective curve shapes. The data was evaluated so as to group those sampling sites whose monthly water quality values were most similar. This, coupled with reference to sampling site locations, allowed for the grouping of sites into representative sloughs. Such a process could have been carried out without the aid of a statistical analysis. However, owing to the inter-connected nature of the drainage system within the study area, i t was felt that as unbiased an approach as possible should be taken. Having determined how many sloughs there were, and of which sampling sites they were comprised, the water quality data from each was compared to current water quality standards, this allowed for a determination of the suitability of water from any slough, for various uses. In addition, the magnitudes of concentrations of water quality parameters were compared subjectively between all sloughs in order to determine which of the sloughs were most or least polluted relative to the others. It was thought that these results could be related to the land use type drained by each slough. Independence tests were carried out using the set of values for each parameter from each slough in order to determine how any one slough differed from any and all others. For example, the set of values representing dissolved oxygen for one slough over the entire study period, /63 was tested for independence against the set of values for the same parameter for each of the other sloughs. Likewise, the set of values for each of the other parameters from that slough were tested against the set of values for the same parameter from all of the other sloughs. In this fashiona matrix of independent sets of values for each parameter, across all sloughs, was derived. This allowed for the characterization of sloughs relative to one another. It also indicated which parameters varied significantly most often, hence possibly indicating which were most sensitive to land use. Percent coefficient of variation analyses were carried out, when possible, for all water quality parameters by slough, so as to further aid in determining those parameters which might be useful as estimators of land use effects on water quality. Time trends were also noted. Finally, a subjective curve analysis was carried out, identical to the one described previously, except with reference to the sloughs as experi-mental units, rather than the entire study area. This was done so as to determine i f any parameters in a given slough exhibited similar trends. Results from this analysis were also compared between sloughs, to determine i f any two or more appeared to be responding in the same fashion. 5.2 Percent Coef f i c i ent of Variat ion The water quality data was used to find the percent coefficient of variation for each water quality parameter, per month: /64 % CV = a/x x 100; a' = Standard deviat ion 'x = Mean This calculation was carried out in two ways: a. For the parameters over the study area as an experimental unit, b. For the parameters over each slough as an experimental unit. Any parameter whose percent coefficient of variation averaged less than 50 over the entire study period was considered to be either a conservative estimator of land use effects on water quality, or generally insensitive to land use. Those whose percent coefficients of variation averaged 50 or more, were considered to be potentially useful as indicators. This was applied to the parameters both over the study area as a unit, and over each slough as a unit. The monthly percent coefficients of variation for a parameter were considered together over the entire study period, in order to determine i f there were any seasonal trends in the variability of that parameter. This was done for both the study area as a unit, and for the sloughs as separate units. 5.3 Corre lat ions A correlation matrix for the water quality parameters was calculated monthly over the entire study area, irrespective of slough. The number of times one water quality parameter was correlated significantly with another ( « = .01), was noted. Because sampling took place once in each of 765 nine months, the maximum possible number of correlations with regard to any two water quality parameters, was nine. However, i t should be noted that data for phosphorus was only available for eight of those nine months, and hence, the maximum number of correlations possible with that parameter was eight. Parameters that correlated with one another four or more times were noted, and considered as being^possibly related. ; 5.4 Parameter Magnitudes Per Slough The magnitudes of parameter values per slough were compared monthly. The results were tabulated with respect to the slough or sloughs exhibiting the highest values for a given parameter in that month. The slough or sloughs with the lowest values were noted in the same fashion. 5.5 Independence Testing The entire set of nine monthly values for each water quality parameter for each slough was compared, by slough, so as to determine those sets of values that were independent of others for that water quality parameter. This was accomplished with the aid of two analytical techniques: 1. Curve analysis: From curves showing average parameter values per slough, per month, i t was often possible to ascertain, by visual examination, whether or not a set of values for a parameter from one slough was independent of that from another. 2. Mann-Whitney U test: If it was not possible to determine independence on the basis of curve analysis alone, the Mann-Whitney U test (Siegel, 1956) was used. This test is also known as the Wilcoxon Two-Sample test (Walpole, /66 1968). It is a simple non-parametric test, requiring only a few observations in order to determine independence. The level of significance used was = .05. A summation of significantly different sets of values for all parameters, between all combinations of two sloughs, was carried out. From this summation emerged the best elucidation of land use effects on water quality, as well as all of the parameters whose sets of values over the study period were significantly different between any two sloughs. This technique also allowed similar, or not significantly different, sets of values to be grouped. 5.6 Curve Analysis Average individual parameter values per slough, per month, were calculated, and the values plotted against the sampling date for each slough. The resultant curves indicated the ways in which each parameter varied with time in each slough. The curves were then subjectively analysed in order to determine when each parameter "peaked" in each slough, and when they reached extreme low values ("djpped"). The results were tabulated in three ways: 1. Total number of peaks versus total number of dips, over the entire study area, per month. This allowed seasonal trends over the entire study area, irrespective of slough to be discerned. 2. Total number of peaks versus total number of dips per parameter, per month. This facilitated analysis of (1) above. It also indicated seasonal trends with regard to the individual parameters, irrespective of slough. 767 3. Total number of peaks versus total number of dips per slough, per month. As well as facilitating analysis of (1) above, this also allowed a comparative analysis of seasonal trends, between sloughs, to be made. Because the year in which sampling took place was climatically atypical, seasonal trends were not expected to be overtly manifest. In addition, since the data collected was only representative of one twelve month period, i t was expected that any discerned trends would not be well defined, or easily definable. However, this analysis was considered valid as an aid in defining various roles that individual sloughs arid parameters played with regard to variability throughout the entire study area. 6. RESULTS AND DISCUSSION ''f 6.1 Study Area Water quality data for the study area is summarized in Table 1. It was derived from the detailed water quality data presented in The 'Appendix. Standard deviations in Table 1 have been rounded off from those used in the percent coefficient of variation analysis, following. The reader is also referred to Table 1 for an explanation of the symbols used to represent water quality parameters in all subsequent tables and figures. 768 TABLE 1: (Results) Means, Standard Deviations and Ranges by Month for All Sixteen Sites Parameter Function Al 0 N D J Water Temp °C X 20 15 10 7 2 S.D. 2 3 1 1 1 Range 17-24 10-20 8-12 5-8 0-5 PH X 7.47 7.08 7.25 6.71 7.21 S.D. 0.89 0.54 0.54 0.34 0.38 Range 6.12-9.92 5.31-7.61 5.58-7.89 6.00-7.15 6.10-7.70 DO ppm X 6.4 5.5 5.2 6.7 5.8 S.D. 3.2 2.7 2.8 2.4 2.0 Range 0.7-12.0 0.6-10.0 0.4-9.2 2.6-11.3 3.2-9.4 Cd ppm X n <0.0l , <0.01 0.01 <0.01 <0.01 o . u. Range - - <0.01-0.02 _ _ Cu ppm X 0.06 0.04 0.23 0.09 0.87 S.D. 0.22 0.12 0.68 0.32 0.31 Range <0.01-0.87 <0.01-0.49 0.03-2.76 <0.01-1.3 <0.01-1.24 Pb ppm X 0.06 0.04 0.03 <0.05 0.05 S.D. 0.01 0.01 0.01 0.0 0.01 Range <0.05-0.09 0.02-0.06 0.02-0.05 <0.05-0.05 <0.03-0.07 Zn ppm X 0.01 0.04 0.03 0.03 0.04 S.D. 0.03 0.06 0.02 0.03 0.04 Range <0.01-0.02 <0.01-0.24 0.01-0.07 <0.01-0.10 <0.01-0.11 Al ppm X 0.1 0.4 0.2 0.4 0.2 S.D. 0.0 1.1 0.1 0.4 0.1 Range - <0.1-4.6 <0.1-0.6 O.1-0.2 <0.1-0.5 Fe ppm X 0.3 2.8 2.1 1.2 4.0 S.D. 0.3 4.3 2.9 0.8 4.1 Range 0.1-1.2 0.2-15.0 0.2-12.3 0.3-2.8 0.3-15.0 Mn ppm X 0.07 0.22 0.27 0.25 0.54 S.D. 0.11 0.35 0.27 0.28 0.44 Range 0.01-0.48 <0.01-1.13 0.02-0.77 <0.01-0.85 <0.01-1.40 S.C. umho/cm X 282. 772. 713. 1260. 1380. S.D. 183. 725. 630. 1360. 1070. Range 115.-790. 134.-2230. 175.-2120. 64.0-2420. 115.-3600 K ppm X 10.7 21.5 10.9 12.1 16.7 S.D. 19.4 37.5 8.6 6.9 11.6 Range 0.05-69.0 1.1-150. 2.2-27.5 2.3-23.0 1.2-50.0 Ca ppm X 13.4 22.6 20.8 27.4 28.1 S.D. 3.5 15.8 6.8 15.6 15.4 Range 10.3-21.9 6.9-49.1 13.8-33.6 10.4-54.7 10.9-67.1 Mg ppm X 7.8 12.0 23.6 42.0 50.0 S.D. 5.0 10.1 20.2 36.2 43.1 Range 2.8-21.9 3.1-35.4 5.1-72.0 4.0-112. 7.4-156. continued. /69 TABLE 1: (continued) Parameter Function Al 0 N D J Na ppm X 19.2 83.1 96.7 210. 267. S.D. 11.0 96.0 108. 200. 232. Range 5.7-33.3 4.7-287. 9.8-336. 4.0-512. 8.0-740. P ppm X - 0.117 0.048 0.084 0.017 S.D. - 0.212 0.056 0.192 0.017 Range - 0.009-0.670 0.010-0.223 0.010-0.795 0.007-0.076 N.T. ppm X 1.25 1.99 1.79 2.55 3.38 S.D. 1.07 3.11 2.66 1.99 4.00 Range 0.4-4.5 0.28-12.3 0.31-11.44 0.63-7.65 0.29-11.25 N.S. ppm X 0.45 0.48 0.71 3.10 1.58 S.D. 0.46 0.42 0.59 1.89 2.07 Range 0.05-1.74 0.09-1.58 0.11-2.13 0.40-5.57 <0.05-8.80 % C ppm X 0.003 0.003 0.001 0.001 0.001 S.D. 0.002 0.003 0.001 0.000 0.001 Range 0.001-0.009<0.001-0.001<0.001-0.005<0.001-0.002<0.001-0.004 KEY 1. DO = Dissolved oxygen S.C. = Specific conductance N.T. = Total nitrogen N.S. = Soluble nitrogen All other parameter symbols specified by elemental symbols, or standard symbols (e.g. pH). Al - August/1976 0 - October/1976 N - November/1976 D - December/1976 J - January/1977 F - February/1977 M - March/1977 A - Apri1/1977 A2 - August/1977 x = Mean value S.D. = Standard deviation 770 TABLE 1: (continued) Parameter Function F M A A2 Water Temp °C X 7 7 12 23 S.D. 1 1 2 2 Range 5-10 5-10 8-17 21-28 pH X 6.82 7.41 7.58 7.29 S.D. 0.42 0.45 0.26 0.21 Range 6.31-7.54 6.42-8.02 6.86-7.98 7.00-7.75 DO ppm X 6.0 7.1 6.6 4.6 S.D. 2.5 2.6 3.4 1.4 Range 1.2-9.5 2.3-11.0 2.5-12.0 2.5-7.3 Cd ppm X <0.01 <0.01 <0.01 <0.01 S.D. Range <0.01-0.01 <0.01-0.01 <0.01-0.01 -Cu ppm X 0.15 0.22 0.09 <0.01 ;S.D. 0.42 0.58 0.30 0.0 Range 0.02-1.73 0.04-2.40 <0.01-1.23 <0.01-0.01 Pb ppm X 0.05 <0.03 0.04 <0.02 S.D. 0.02 0.0 0.01 0.0 Range 0.03-0.08 - <0.03-0.07 <0.02-0.02 Zn ppm X 0.03 0.02 0.02 <0.01 S.D. 0.03 0.01 0.02 0.0 Range <0.01-0.09 0.01-1.4 <0.01-0.11 -Al ppm X 0.3 0.5 0.1 <0.1 S.D. 0.4 0.4 0.1 0.0 Range 0.1-1.7 <0.1-1.4 <0.1-0.4 -Fe ppm X 2.2 1.9 3.2 0.2 S.D. 2.1 1.6 3.3 0.0 Range <0.1-6.7 0.2-4.5 .2-10.7 -Mn ppm X 0.46 0.13 0.74 <0.01 S.D. 0.37 0.15 0.42 0.0 Range <0.01-1.10 <0.01-0.42 0.15-1.38 -S.:C. ymho/cm X 1707. 772. 2510. :222. S.D. 1390. 560. 2270. 316. Range 178.-4550 96.0-1900. 121.-8200 96.0-1345 K ppm X 12.4 8.0 21.6 5.7 S.D. 7.6 4.7 14.2 15.4 Range 1.9-29.0 2.1-17.0 1.2-49.0 0.7-61.0 Ca ppm X 30.8 19.1 41.2 15.7 S.D. 18.2 6.8 23.0 8.1 Range 11.7-74.5 8.4-31.6 8.8-;87.6 11.7-443. Mg ppm X 51.4 26.3 75.3 6.0 S.D. 44.7 18.6 72.1 6.8 Range 10.0-156. 5.8-66.0 6.3-244. 2.9-30.0 continued. 771 TABLE 1: (continued) Parameter Function F M A A2: Na ppm X 246. 114. 412. 10.0 S.D. 235. 109. 417. 7.6 Range 9.0-750. 6.1-380. 7.4-1390. 3.0-167. P ppm x 0.019 0.033 0.029 0.021 S.D. 0.008 0.030 0.017 0.034 Range 0.008-0.035 0.009-0.133 0.005-0.069 0.005-0.141 N.T. ppm X 2.71 2.40 6.54 0.30 S.D. 2.93 2.56 10.21 0.65 Range 0.36-8.54 0.30-7.50 0.15-27.29 <0.10-2.58 N.S. ppm x 2.23 2.61 1.48 0.28 S.D. 2.78 3.28 1.80 0.52 Range 0.25-12.16 0.39-14.34 0.20-7.91 <0.05-2.13 % C ppm X 0.001 0.002 0.001 <0.001 S.D. 0.001 0.002 0.000 0.000 Range <0.001-0.003<0.001-0.008<0.001 -0.0020.001-0.001 i n 6.1.1 Percent Coef f i c i ent of Variat ion Results of the percent coefficient of variation analysis, computed for the entire study area irrespective of slough, are summarized in Table 2. These results were obtained from the means and standard deviations of the water quality parameters as outlined in Table 1. The parameters whose percent coefficients of variation were found to be less than 50 included: water temperature, pH, dissolved oxygen, lead and calcium. Water temperature and dissolved oxygen were probably more closely associated with climatic factors than with land use, while pH could more easily have been affected by such factors as soil parent material, than by land use. Calcium is the most abundant major cation in most of the soils throughout the area, so that the extent to which land use affected its abundance in drainage waters was probably minimal in relation to the amounts that naturally occurred. Difficulty was experienced in measuring lead concentrations throughout the study period, and accuracy was not good. Its relative constancy could have been a result of that, or could have resulted from other factors. Water quality parameters whose percent coefficients of variation were greater than 50, include: copper, zinc, aluminum, iron, manganese, phosphorus, specific conductance, potassium, sodium, total nitrogen, soluble nitrogen, and carbon. The variability of these parameters is discussed in terms of slough parameter equivalences and magnitudes in sections 6.2.3 and 6.2.4. No seasonal trends in the variability of any of the water quality parameters were evident. /73 TABLE 2: Percent Coefficient of Variation for Parameters in Study Area Al 0 N D J F M A A2 Mear % C\ Water Temp. 12 17 12 17 66 16 20 20 9 21 pH 12 8 7 5 5 6 6 3 3 6 DO 51 50 55 35 34 42 36 50 30 43 Cu 337 286 298 357 354 279 267 328 0 278 Pb 20 32 30 0 31 38 0 35 0 21 Zn 24 142 84 84 102 100 53 121 0 79 Al 0 290 77 96 74 122 86 67 0 90 Fe 94 154 140 71 105 98 84 103 0 94 Mn 164 156 101 111 82 80 114 56 \o 96 S.C. 65 94 88 108 77 81 78 90 142 91 K 181 175 79 57 70 61 59 66 270 113 Ca 26 70 33 57 55 59 36 56 52 49 Mg 64 85 85 86 86 87 71 96 114 86 Na 57 116 112 95 87 95 96 101 76 93 P - 181 117 229 98 42 91 58 160 122 N.T. 86 156 149 78 118 108 107 156 213 130 N.S. 102 87 83 61 131 125 126 121 187 114 % C 70 121 77 24 67 44 115 30 0 61 774 6.1.2 Correlat ions A correlation matrix was calculated monthly for all the water quality parameters, irrespective of slough. This matrix was derived from the data using the U.B.C. Triangular Regression Package (TRP) (1977). Table 3 lists the water quality parameters that were significantly correlated with one another (<*= 0.1) four or more times (i.e. in four or more months) throughout the study period. Specific conductance was correlated with all of the major cations in six or more months, depending upon the cation in question. These correlations probably have l i t t l e to do with land use, because the major cations are also largely those responsible for the conductivity of water. Lead, zinc, manganese and soluble nitrogen were correlated with one or more of the major cations in four or more months. Generally, a large majority of correlations involved a major cation, or specific conductance. Most of the mineral soils in the area have been found to contain relatively large quantities of major cations (Luttmerding and Sprout, 1969). As a result, concentrations of major cations in surface waters may come about more through the process of leaching, than for other reasons. Hence, the para-meters that are correlated with any of the major cations, or specific conductance, may be responding as a result of the same process. Iron and dissolved oxygen were correlated negatively, five times. The oxidation status of iron is known to affect its solubility, such that its reduced state is more soluble. This fact may explain the above correlation. /75 TABLE 3: Summary of Correlation Matrix and Months in which Correlations Occurred Number of Correlations* Parameters (a = .01) Al 0 .: N D J F M A A2 DO & Fe 5 • / • / / Cu & C 4 / / / / Cu & P 4 / / / / Pb & S.C. 4 / / / / Pb & Ca 4 / / / / Pb & Mg 4 / / / / Pb & Na 4 / / / / Zn & Ca 5 / / / / / Zn & Mg 5 / / / / Fe & N.T. 8 / / / / / / / / Mn & Ca 4 / / / / Mn & Mg 6 / / / / / / S.C. & K 6 / / / / / / S.C. & Ca 8 / / / / / / / / S.C. & Mg 7 / / / / / / / S.C. & Na 6 / / / / / / N.S. & K 6 • / / / / / N.S. & Mg 4 / / / / N.S. & Ca 4 / / / / *Maximum possible number of correlations between two parameters = 9; except with phosphorus, maximum number of correlations = 8. 776 Iron was also correlated eight times with total nitrogen. This may reflect an association with organic matter, although iron was not correlated significantly with percent carbon. Copper was correlated with both percent carbon and phosphorus four times, but with each in different months. Again, this may reflect an association with organic matter, but since the correlations were intermittant throughout the study period, and not synchronized with one another, they may also have been spurious. Phosphorus andtcarbon were seldom found to be correlated with one another. Despite the numerous correlations outlined above, no consistent seasonal trends were evident. Soluble nitrogen was found to correlate less frequently with other parameters during the winter, than i t did during the spring and fa l l . However, there is insufficient data to define this possible trend with any confidence. 6.1.3 Curve Analysis Figure 8 was derived from the curve analysis technique previously described, and is representative of the total number of peaks and dips per parameter, per month, over the entire study area. There were found to be six different sloughs in the study area, as will be explained later, in Section 6.2.1 of this report. Therefore, the number of peaks plus dips for any one water quality parameter in a given month cannot be more than six. There was, in addition, no data for phosphorus in August, 1976, because the laboratory analytical technique for that parameter was being tested. Results from this test run were found to be inaccurate, and hence, 3! DIPS PEAKS DIPS PEAKS DIPS PEAKS ro co HHJHHI '= H H p OCT ro ro ro ro ro cu cr ro ro < AUG '76 NOV DEC , JAN 77 FEB MAR APR AUG LU 778 were not recorded. No data exists for one of the sloughs (Slough 4) in August, 1977, as i t was dry on the sampling date. Figure 8 indicates that there might be some seasonal trends with regard to some water qua l i ty parameters. Water samples in the d r i e r months appeared to exhibi t lower concentrations of major cations than they did in the wetter winter months. This i s also true of some of the other water qua l i ty parameters, such as manganese and soluble nitrogen. These resul ts are d i f f i c u l t to expla in , because higher concentrations of the above parameters would be expected to occur i n the d r i e r months. The water table in the area i s generally lowest during the summer, as i s the amount of p rec ip i ta t ion received. Hence, most drainage would l i k e l y be a resu l t of slow groundwater flow. Residence time of water wi thin the s o i l would probably therefore be longer, and quanti t ies of the major cations picked up by such water, greater. The above resul ts could be a function of t i d a l influences, however i n su f f i c i en t data prohibi ts any further e luc ida t ion . Figure 9 was derived from Figure 8. I t i s representative of the to ta l number of peaks and dips , per month, i r respect ive of slough and parameter. This figure indicates more c l ea r l y some of the seasonal trends in the study area. In the f i r s t sampling month, most water qua l i ty parameter values were extremely low r e l a t i ve to the i r values throughout the remainder of the sampling period. This trend was duplicated in August, 1977. In contrast , values for water co l lec ted in March, 1977, indicated only a s l i gh t downward trend, which was followed by a d i s t i n c t upward trend in A p r i l , 1977. No re la t ionship between amounts of p rec ip i t a t ion received, and upward or downward trends could be discerned. 40-i 779 30-< UJ CL 20-< r -O r - 10. AUG '76 NOV OCT DEC JAN '77 MAR AUG FEB APR IO-C/5 QL Q < O 20. 30. 40-M0NTH F i g u r e 9. Tota l peaks and d ips per month over e n t i r e study a rea . 780 6.2 Sloughs Water quality data for each of the sloughs in the area is presented in Tables 4 through TO. It was derived from the detailed water quality data presented in The Appendix. There were found to be six individual sloughs in the study area, as explained in the section following. Some sloughs were represented by one or two sampling sites, hence, no attempt was made to calculate standard deviations for those sloughs. Standard deviations, as presented in Tables 4, 5, 6 and 7 have been rounded off from those used in the percent coefficient of variation analysis, in Section 6.2.5. Data from Slough 3 and Slough 5 was combined (Table 7). in order to facilitate analysis of water quality in Slough 5. This is explained in more detail in the next section. 6.2.1 Sites Per Slough Because the drainage system within the study area is totally inter-connected, i t was necessary to determine which groups of sampling sites belonged together as part of the same slough. To that end, a grouping program was run (U.B.C. C Group (1973)) using the water quality data as input. This program grouped those sites whose parameter values were most similar every month. Analysis of the computer output showed that there were effectively six different sloughs in the study area (see Figure 10). This was as expected. However, on the basis of the results, Sites 13 and TABLE 4: Means and Standard Deviations of Parameters in Slough 1 (Sites 1, 2, 3, and 4) per Month Parameters Function Al O N D J F M A A2 Water Temp (°C) X SD PH X SD DO (ppm) X SD Cd (ppm) X SD Cu (ppm) X SD Pb (ppm) X SD Zn (ppm) X SD Al (ppm) X SD Fe (ppm) X SD Mn (ppm) X SD S.C. (ymho/cm) X SD K (PPm) X SD Ca (ppm) X SD Mg (ppm) X SD 17 13 11 0 2 0 7.09 7.22 7.67 0.17 0.06 0.22 7.0 6.1 7.9 1.6 1.5 1.1 <0.01 <0.01 0.02 <0.01 0.01 0.06 0.0 0.0 0.03 0.07 0.05 0.02 0.01 0.02 0.01 0.01 0.03 0.01 0.0 0.04 0.01 <0.1 0.1 0.1 0.0 0.1 0.0 0.2 0.8 0.8 0.1 1.0 l. i; 0.05 0.06 0.20 0.04 0.10 0.21 178. 455. 515. 69.1 340. 256. 1.0 3.5 4.3 1.1 2.9 2.4 11.3 14.9 16.1 0.5 1.5 4.0 5.1 10.5 13.9 2.4 8.0 8.2 7 4 6 1 1 0 6.78 7.19 6.94 0.33 0.16 0.41 9.2 8.6 8.0 2.0 0.7 1.5 <0.01 <0.01 0.01 <0.01 <0.01 0.03 0.0 0.0 0.01 <0.05 0.05 0.06 0.0 0.01 0.0 0.05 0.01 0.01 0.04 0.01 0.0 <0.1 <0.1 0.5 0.0 0.0 0.8 0.7 1.1 1.2 0.6 1.6 1.9 0.32 0.19 0.40 0.33 0.35 0.47 1300. 2090. 2300. 635. 131. 223. 14.0 18.7 13.9 7.0 0.7 1.8 30.0 29.9 31.1 16.8 5.1 6.5 56.3 62.5 57.8 39.0 9.5 9.7 5 10 22 0 1 1 7.43 7.65 7.29 0.25 0.06 0.06 9.8 8.9 5.6 1.6 1.3 0.6 0.01 0.01 <0.01 0.07 0.02 <0.01 0.01 0.01 0.0 <0.03 0.04 <0.02 0.0 0.01 0.0 0.02 0.01 <0.01 0.01 0.0 0.0 0.2 <0.1 <0.1 0.3 0.0 0.0 0.5 1.2 0.2 0.4 1.2 0.0 0.07 0.63 <0.01 0.11 0.59 0.0 658. 3320. 100. 342. 967. 1.8 5.1 23.4 0.8 1.9 5.8 0.1 15.8 43.1 13.0 2.1 11.9 1.1 19.9 95.5 3.2 10.3 36.3 0.3 TABLE 4: (continued) Parameters Function A 1 0 N D J F M A A 2 Na (ppm) X 18.2 49.8 72.5 335. 444. 345. 102. 596. 3.8 SD 13.1 44.4 38.2 195. 24.7 43.5 48.4 204. 0.6 P (ppm) X - 0.018 0.014 0.018 0.014 0.019 0.025 0.034 0.008 SD - 0.004 0.005 0.009 0.009 0.008 0.014 0.024 0.002 N.T. (ppm) X 0.55 0.42 0.51 1.25 0.93 0.82 0.70 0.61 <0.10 SD 0.12 0.12 0.17 0.70 0.49 0.73 0.51 0.56 0.0 N.S. (ppm) X 0.98 0.14 0.21 1.67 0.18 0.79 0.81 0.44 0.11 SD 0.04 0.07 0.09 1.30 0.26 0.50 0.67 0.33 0.06 % C X 0.002 0.001 <0.001 O.001 <0.001 <0.001 0.003 <0.001 <0.001 SD 0.001 0.0 0.0 0.0 0.0 0.0 0.004 0.0 0.0 TABLE 5: Means and Standard Deviations of Parameters in Slough 2 (Sites 5, 6 and 7) per Month Parameters Function A 1 0 N D J F M A A 2 Water Temp (°C) X SD PH X SD DO (ppm) X SD Cd (ppm) X SD Cu (ppm) X SD Pb (ppm) X SD Zn (ppm) X SD Al (ppm) X SD Fe (ppm) X SD Mn (ppm) X SD S.C. (ymho/cm) X SD K (ppm) X SD Ca (ppm) X SD Mg (ppm) X SD 21 14 10 1 3 1 8.01 7.41 7.13 1.65 0.15 0.24 6.9 7.2 6.5 2.0 2.7 1.6 <0.01 <0.01 0.01 <0.01 <0.01 0.04 0.0 0.0 0.01 0.06 0.03 0.04 0.01 0.01 0.01 0.01 <0.01 0.04 0.0 0.0 0.03 <0.1 0.1 0.2 0.0 0.0 0.1 0.2 1.2 1.0 0.1 0.9 0.4 0.05 0.08 0.59 0.03 0.08 0.19 271. 1660. 1910. 20.1 410. 182. 3.1 16.8 18.7 1.3 0.2 2.9 11.6 21.4 30.4 0.6 1.5 3.0 7.5 12.0 61.0 0.3 13.2 12.1 8 3 7 1 0 0 6.52 7.25 7.04 0.32 0.27 0.40 7.4 5.9 7.5 0.2 1.3 0.8 <0.01 <0.01 0.01 <0.01 O.01 0.05 0.0 0.0 0.01 <0.05 0.06 0.07 0.0 0.01 0.01 0.05 0.10 0.07 0.04 0.01 0.03 0.4 <0.1 0.4 0.4 0.0 0.2 0.5 1.4 0.2 0.2 1.2 0.1 0.62 0.89 0.85 0.25 0.22 0.32 2290. 2880. 4020. 140. 858. 515. 21.8 32.1 24.5 1.4 15.5 4.3 51.9 53.1 61.7 2.1 16.3 15.7 93.7 122. 131. 20.3 38.0 31.2 7 13 22 1 1 1 6.98 7.30 7.21 0.22 0.40 0.13 7.4 10.5 4.2 ' 0.8 1.4 1.1 <0.01 0.01 <0.01 0.08 0.03 <0.01 0.02 0.01 0.0 <0.03 0.06 <0.02 0.0 0.02 0.0 0.03 0.05 <0.01 0.01 0.05 0.0 0.9 <0.1 <0.1 0.6 0.0 0.0 0.9 0.9 0.2 0.6 0.9 0.0 0.34 1.09 <0.01 0.04 0.14 0.0 730. 5980. 153. 162. 2280. 38.0 13.8 39.0 1.8 3.5 8.7 0.9 30.4 75.4 12.9 1.3 17.7 0.9 60.3 191. 5.0 6.7 67.7 1.6 continued. TABLE 5: (continued) Parameters Function A 1 0 N D J F M A A 2 Na (ppm) X 28.9 242. 305. 476. 567. 640. 314. 1040. 11.9 SD 3.8 72.2 32.0 44.0 199.0 101. 64.6 388. 6.4 P (ppm) X - 0.084 0.027 0.037 0.011 0.017 0.033 0.030 0.013 SD - 0.023 0.006 0.028 0.003 0.008 0.026 0.023 0.007 N.T. (ppm) X 0.75 1.06 1.14 1.80 1.14 1.01 1.89 1.75 <0.10 SD 0.0 0.20 0.03 1.04 0.59 0.55 0.35 1.19 0.0 N.S. (ppm) X 0.18 0.39 0.58 4.56 4.19 6.00 6.74 3.61 0.12 SD 0.02 0.12 0.12 0.73 4.00 5.34 6.59 3.73 0.10 % C X 0.002 0.001 <0.001 <0.001 <0.001 <0.001 0.001 <0.001 <0.001 SD 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 TABLE 6: Means and Standard Deviations of Parameters from Slough 3 (Sites 8, 9, 10 and 11) per Month Parameters Function Al 0 N D J F M A A 2 Water Temp (°C) X SD pH X SD DO (ppm) X SD Cd (ppm) X SD Cu (ppm) X SD Pb (ppm) X SD Zn (ppm) X SD Al (ppm) X SD Fe (ppm) X SD Mn (ppm) X SD S.C. (urnho/cm) X SD K (ppm) X SD Ca (ppm) X SD Mg (ppm) X SD 21 15 10 2 1 2 8.09 7.38 7.30 0.60 0.18 0.11 8.4 3.1 1.7 5.2 2.7 1.3 <0.01 <0.01 0.01 <0.01 0.02 0.07 0.0 0.01 0.02 0.06 0.04 0.03 0.01 0.01 0.01 0.01 1.00 0.03 0.0 0.10 0.03 <0.1 <0.1 0.2 0.0 0.0 0.1 0.3 3.1 2.2 0.1 3.5 1.0 0.03 0.46 0.28 0.03 0.51 0.02 476. 1130. 605. 218. 862. 107. 27.4 60.8 17.3 27.9 64.0 7.7 16.4 40.8 25.1 3.1 23.6 3.0 10.7 19.6 18.6 4.0 13.0 1.5 7 2 8 0 1 1 6.72 7.62 6.90 0.16 0.07 0.43 4.5 5.1 4.0 0.6 1.2 1.1 <0.01 <0.01 0.01 <0.01 <0.01 0.07 0.0 0.0 0.01 <0.05 0.03 0.04 0.0 0.01 0.01 0.03 0.03 0.01 0.01 0.02 0.01 0.8 0.2 0.2 0.3 0.2 0.1 2.2 9.3 3.9 0.5 4.4 1.3 0.14 0.90 0.49 0.06 0.46 0.28 1680. 777. 1040. 2420. 179. 130. 10.5 14.4 12.0 3.3 5.9 2.3 21.9 24.3 28.1 2.3 2.8 4.9 23.8 27.3 31.8 1.7 5.1 4.3 7 12 23 1 2 2 7.81 7.81 7.34 0.18 0.12 0.27 5.0 2.5 3.1 1.1 0.6 0.4 0.01 <0.01 <0.01 0.09 0.02 <0.01 0.01 0.01 0.0 <0.03 0.03 <0.02 0.0 0.0 0.0 0.03 0.02 0.01 0.01 0.01 0.0 0.8 <0.1 <0.1 0.2 0.0 0.0 4.1 8.1 0.2 0.4 1.8 0.0 0.05 0.98 <0.01 0.05 0.28 0.0 588. 1730. 490. 81.0 251. 575. 11.6 28.4 18.1 2.4 , 7.3 28.7 21.8 39.6 22.9 1.9 7.4 14.4 24.5 44.8 11.8 3.7 7.2 12.2 continued. TABLE 6: (oontinued) Parameters Function Al 0 N D J F M A A 2 Na (ppm) X 24.3 91.0 65.3 80.5 120. 117. 77.0 211. 17.1 SD 11.6 65.6 15.9 12.4 37.8 16.1 6.8 15.8 9.1 P (ppm) X 0.196 0.069 0.048 0.01:3 0.021 0.031 0.030 0.049 SD - 0.296 0.047 0.032 0.008 0.007 0.006 0.007 0.063 N.T. (ppm) X 1.86 4.18 1.54 4.90 7.96 6.71 7.18 22.50 0.87 SD 0.73 5.48 0.45 1.90 3.11 1.82 0.35 7.95 1.18 N.S. (ppm) X 0.78 0.92 0.72 4.93 1.41 1.71 2.64 1.44 0.69 SD 0.19 0.49 0.94 0.74 0.59 0.40 0.10 0.08 0.96 % C X 0.002 0.004 0.001 0.001 0.001 0.001 0.001 0.001 <0.001 SD 0.001 0.005 0.0 0.0 0.0 0.0 0.0 0.0 0.0 TABLE 7: Means and Standard Deviations of Parameters Slough 3 and 5 (Sites 8, 9, 10, 11, 13 and 14) per Month Parameters Function Al 0 N D J F M A A2 Water Temp (°C) X 21 16 9 7 2 8 7 13 24 SD 1 2 1 1 1 1 1 2 2 PH X 7.73 6.92 7.17 6.70 7.44 6.75 7.67 7.66 7.25 SD 0.74 0.84 0.22 0.23 0.29 0.41 0.35 0.25 0.26 DO (ppm) X 7.0 3.5 2.3 4.7 4.9 4.0 5.3 3.3 3.7 SD 4.6 2.5 1.4 0.6 1.0 0.9 1.3 1.5 1.3 Cd (ppm) X cn <0.01 <0.01 0.01 <0.01 <0.01 0.01 0.01 <0.01 <0.01 Cu (ppm) X <0.01 <0.01 0.07 <0.01 <0.01 0.06 0.09 0.02 <0.01 SD 0.0 0.01 0.01 0.0 0.0 .0.02 0.01 0.01 0.0 Pb (ppm) X 0.06 0.04 0.03 <0.05 0.03 0.04 <0.03 0.03 <0.03 SD 0.01 0.01 0.01 0.0 0.01 0.01 0.0 0.0 0.0 Zn (ppm) X 0.01 0.08 0.03 0.02 0.02 0.02 0.02 0.01 <0.01 SD 0.0 0.09 0.03 0.01 0.02 0.01 0.01. .0.01 0.0 Al (ppm) X <0.'l <0.'Ti 0.2 : 0.7 0.3 ; 0.2 0.6 0.2 <0.1 SD 0.0 0.0 0.1 0.4 0.2 0.1 0.29 0.13 0.0 Fe (ppm) X 0.3 4.7 2.3 1.8 7.3 3.5 3.5 6.6 .2 SD 0.1 5.8 0.8 0.8 4.6 1.2 1.0 2.7 0.0 Mn (ppm) X 0.04 0.46 0.07 0.10 0.74 0.42 0.07 0.76 <0.01 SD 0.04 0.48 0.08 0.08 0.43 0.25 0.06 0.39 0.0 S.C. (ymho/cm) X 368. 845. 469. 1150. 558. 766. 433. 1190. 377. SD 239. 807. 226. 2050. 365. 442. 250. 850. 478. K (PPm) X 18.6 43.5 12.5 8.1 10.1 8.9 8.6 19.3 12.6 SD 25.5 56.6 9.5 4.5 8.0 5.2 5.0 15.1 23.8 Ca (ppm) X 15.0 34.0 21.6 18.6 19.9 23.1 18.1 29.6 20.0 SD 3.4 21.4 5.8 5.5 7.3 8.7 6.1 16.6 12.1 Mg (ppm) X 9.0 16.7 16.3 18.0 20.8 24.8 19.1 32.2 9.3 SD 4.1 11.7 3.8 9.1 10.8 11.2 8.9 20.3 10.2 continued. TABLE 7: (continued) Parameters Function Al 0 N D J F M A A 2 Na (ppm) X 19, .2 64 -.1 50 .0 55. 6 83, .0 82, .3 53, .9 143. 15 .2 SD 12, .0 65 .7 30 .9 39. 8 64, .7 55, .6 36, .1 105. 8 .0 P (ppm) X 0. 245 0 .062 0. 054 0, .013 0, .018 0, .028 0. 026 0 .040 SD 0. 318 0 .041 0. 032 0, .006 0, .007 0, .011 0. 008 0 .051 N.T. (ppm) X 1, .60 3. 61 1 .79 3. 89 5. .78 4, .90 4, .94 15. 51 0 .61 SD 0, .70 4. 55 0 .53 2. 21 4. .15 3, .16 3. .10 12. 49 0 .99 N.S. (ppm) X 0, .71 0. 82 1 .13 4. 29 1. ,54 1. .75 2. ,55 1. 49 0 .52 SD 0, .23 0. 47 0 .65 1. 55 0. .51 0. .32 0. .18 0. 11 0 .79 % C X 0, .002 0. 004 0 .001 0. 001 0. ,001 0. .001 0. ,001 0. 001 <0 .001 SD 0, .001 0. 005 0 .000 0. 0 0. .0 0. .0 0. .0 0. 0 0 .0 TABLE 8: Parameter Values from Slough 4 (Site 12) per Month Parameter Al 0 N D J F M A Water Temp (°C) 24 20 9 7 2 8 10 14 pH 6.12 6.85 5.58 6.00 6.10 5.98 6.42 7.42 DO (ppm) 0.7 4.0 2.8 3.6 3.2 1.2 2.3 3.2 Cd (ppm) <0.01 <0.01 <0.01 <0.01 <0.01 0.01 0.01 <0.01 Cu (ppm) 0.87 0.49 2.76 1.30 1.24 1.73 2.40 1.23 Pb (ppm) 0.09 0.03 0.03 <0.05 0.03 0.03 <0.03 0.03 Zn (ppm) 0.02 0.04 0.06 0.04 0.06 0.03 0.03 0.03 Al (ppm) <0.1 4.6 0.6 0.4 0.2 0.3 0.3 0.1 Fe (ppm) 1.2 9.4 12.3 1.9 7.6 6.7 3.8 3.1 Mn (ppm) 0.48 0.32 0.70 0.20 0.63 0.63 0.42 0.64 S.C. (umho/cm) 535. 203. 372. 161. 278. 304. 175. 260. K (ppm) 46.0 15.9 20.9 10.9 21.7 7.5 6.0 7.6 Ca (ppm) 21.9 6.9 19.2 14.9 17.8 17.6 13.8 49.1 Mg (ppm) 21.9 7.0 29.0 17.0 17.0 22.0 16.0 21.0 Na (ppm) 17.7 6.9 15.4 8.0 10.0 9.0 6.8 10.7 P (ppm) - 0.055 0.223 0.795 0.076 0.035 0.133 0.053 N.T. (ppm) 4.50 4.70 11.44 5.21 11.25 6.63 1.96 3.23 N.S. (ppm) 1.74 0.66 1.46 2.19 1.74 2.59 1.58 1.43 % C 0.009 0.004 0.005 0.002 0.003 0.003 0.003 0.002 TABLE 9: Means of Parameters from Slough 5 (Sites 13 and 14) per Month Parameters Al 0 N D J F M A A2 Water Temp (°C) 22 18 9 6 1 7 7 15 24 PH 6 .99 6. .02 6. 91 6. 66 7. 08 6, .46 7. 38 7. 37 7. 07 DO (ppm) 4 .2 4. .2 3. 7 5. .2 4. 7 4, .0 5. 9 5. 1 5. 1 Cd (ppm) <0 .01 <0. .01 0. 01 <0. 01 <0. 01 0, .01 0. 01 <0. 01 <0. 01 Cu (ppm) <0 .01 <0, .01 0. 06 <0. 01 <0. 01 0, .04 0. 07 0. 01 <0. 01 Pb (ppm) 0 .06 0, .03 <0. 03 <0. 05 0. 04 0, .03 <0. 03 <0. 03 <0. 03 Zn (ppm) 0 .01 0. .05 0. 03 0. 02 0. 01 0, .02 0. 01 0. 01 <0. 01 Al (ppm) <0 .1 <0, .1 0. 2 0. 5 0. 4 0, ,3 0. 3 0. 4 <0. 1 Fe (ppm) 0 .3 7. .9 2. 6 1. 0 3. 3 2. .8 2. 3 3. 6 0. 2 Mn (ppm) 0 .08 0. .45 0. 16 0. 01 0. 43 0, ,27 0. 11 0. 34 <0. 01 S.C. (umho/cm) 150 268, 198. 94. 5 122. 212. 121. 123. 153. K-(ppm) 1 .1 8. !9 3. 0 3. 5 1. 6 2, .6 2. 6 1. 2 1. 4 Ca (ppm) 12 .1 20, .5 14. 7 11. 9 10. 9 13, ,1 10. 7 9. 5 14. 1 Mg (ppm) 5 .6 10, .9 11. 6 6. 5 7. 9 11. .0 8. 4 7. 0 4. 3 Na (ppm) 9 .0 10, .4 10. 4 5. 8 8. 5 12. ,4 7. 8 8. 3 11. 4 P (PPm) 0. ,343 0. 047 0. 067 0. 012 0. .014 0. 022 0. 018 0. 022 N.T. (ppm) 1 .08 2. .47 2. 31 1. 87 1. 42 1. ,27 1. 57 1. 48 <0. 10 N.S. (ppm) 0 .53 0, ,63 1. 95 3. 02 1. 81 1. ,84 2. 36 1. 60 0. 20 % C 0 .003 0. .007 0. 002 0. 001 0. 001 0. ,001 0. 001 0. 002 <0. 001 CO o TABLE 10: Means of Parameters from Slough 6 (Sites 15 and 16) per Month Parameters Al 0 N D J F M A A2 Water Temp (°C) 19 16 10 5 0 6 7 14 27 PH 7.31 6.88 7.63 7.03 7.11 6.91 7.71 7.73 7.53 DO (ppm) 5.5 8.2 7.4 8.5 4.4 8.3 9.2 8.1 6.3 Cd (ppm) <0.01 <0.01 0.02 <0.01 <0.01 0.01 0.01 <0.01 <0.01 Cu (ppm) <0.01 <0.01 0.06 <0.01 <0.01 0.04 0.05 <0.01 <0.01 Pb (ppm) 0.06 0.02 0.03 <0.05 0.05 0.03 0.03 <0.03 <0.02 Zn (ppm) 0.01 <0.01 0.01 0.01 0.02 0.02 0.01 0.01 <0.01 Al (ppm) <0.1 <0.1 0.1 0.1 <0.1 0.2 0.1 <0.1 <0.1 Fe (ppm) 0.1 0.2 0.4 0.7 1.9 0.8 0.8 0.5 0.2 Mn (ppm) 0.03 <0.01 0.29 0.04 0.09 0.05 0.01 0.43 <0.01 S.C. (ymho/cm) 125. 137. 217. 527. 759. 565. 489. 780. 101. K (ppm) 0.2 1.2 2.4 6.4 7.0 4.2 4.4 5.8 0.9 Ca (ppm) 11.6 13.1 14.2 18.2 16.9 13.8 14.9 17.4 12.2 Mg (ppm) 3.2 3.3 6.2 20.5 20.8 13.5 14.5 17.2 3.0 Na (ppm) 7.7 5.9 23.3 129. 139. 67.0 75.0 104. 3.8 P (ppm) - 0.012 0.020 0.017 0.020 0.015 0.015 0.015 0.075 N.T. (ppm) 0.70 0.30 0.47 0.92 0.53 0.49 0.46 ,0.30 <0.10 N.S. (ppm) 0.18 0.18 0.26 0.70 0.49 0.68 0.71 0.40 0.11 % C 0.002 0.002 <0.001 <0.001 0.003 <0.001 <0.001 <0.001 <0.001 /92 14 were found to comprise a slough by themselves, rather than comprising a part of the Crescent Slough total. Also, Site 12 alone was found to be so distinctly different as to warrant being classified as a slough. Since statistical analysis on the basis of one or two observations is often unreliable or impossible, an attempt was made to determine whether or not the data from Sites 13 and 14 (Slough 5) could legitimately be combined with the data from Sites 8, 9, 10, and 11 (Slough 3). It was felt that l i t t l e could be done in the same fashion for Site 12 because of its uniqueness. The Mann-Whitney U Test, and curve analysis were both used to make the above determination. Results suggested that most sets of parameter values from Slough 5 could statistically also have been drawn from Slough 3 (see Table 11). However, specific conductance and the major cations, total nitrogen, and pH values were found to be statistically different ( « = .05). The sets of parameter values from Site 11 were then compared to those from Site 13, using the Mann-Whitney U Test. This was attempted in recognition of the possibility that differences between analogous sites on the two sloughs might provide a good basis for determining whether or not the two sloughs could be dealt with as one. The only sets of values found to be statistically different (oc = .05) between Site 11 and Site 13, were specific conductance and the major cations. It was concluded that the two sloughs might legitimately be considered as one, i f necessary, but caution in so doing was warranted. /93 APPROXIMATE WATERSHED BOUNDARIES SLOUGH ^ FIGURE 10: Sampling Site Locations TABLE 11: Results of Mann-Whitney U Test as Applied to Sets of Parameter Values from: (a) Slough 3 and Slough 5 (b) Site 11 and Site 13 a = .05 Slough 3 Site 11 and and Parameter* Slough 5 Site 13 PH X / D.O. / / Cu / / Pb / / Zn / / Al / / Fe / / Mn / / S.C. X X P / / N.T. X / N.S. / / % C / / *H 0 : y i = y 2 H-j: y-j f y 2 / - Accept HQ x - Reject H N 795 6.2.2 Slough Descriptions As explained earlier, the physiographic nature of the area, coupled with the modifications that man has made to the drainage network, prevent the precise definition of watershed boundaries for the area, and for any of the sloughs studied. For these reasons, no attempt is herein made to quantify the area drained by any of the six sloughs. However, relative areas drained can be roughly inferred, as depicted in Figure 10. a. Slough 1 Slough 1 is Ladner Slough, and is comprised of Sites 1, 2, 3 and 4 (see Plates 1, 2, 3, and 4). Only Sites 1, 2, and 4 were init ial ly meant to characterize Ladner Slough. Site 3, however, was subsequently found to be more similar to those sites, than it was to Sites 5, 6 and 7 (Cohilukthan Slough). Site 3 is positioned immediately behind the pumping station, at the confluence of Slough 2 and a tributary ditch from Slough 3. The land areas that surround Ladner Slough were previously described in Section 3.6. b. Slough 2 Slough 2 is Cohilukthan Slough. It is comprised of Sites 5, 6 and 7 (see Plates 5, 6, and 7). Site 7 is closest to the headwaters of this slough, and receives water predominantly from agricultural land. Site 6 is near the border between agricultural and urban land, but receives most or all of its water from the agricultural land upstream of i t . Site 5 is surrounded by urban residential land. PLATE 2: Confluence of Cohiluktahn Slough and Ladner Slough, from Site 2, looking North. SLOUGH 1 /97 PLATE 4: View of Ladner Slough and Marina, from Site 4, looking West (Marina shown is not the same as, and lies East of, that shown in Figure 1). PLATE 6: Cohilukthan Slough from Site 6, looking North -Urban/Agricultural Transition. SLOUGH 2 PLATE 7: Near Headwaters of Cohilukthan Slough, from Site 7, looking West. /TOO c. Slough 3 Slough 3 is the southern section of Crescent Slough. It is comprised of Sites 8, 9, 10, and 11 (see Plates 8, 9, 10, and 11). Sites 8, 9, and 10 drain urban residential land on the west, and agricultural land on the east. Site 11 is closest to the headwaters of this slough, and drains agricultural land. Slough 3 drains relatively more agricultural land than does Slough 2. In addition, Slough 3 receives some drainage from Burns Bog and the sanitary landfill area in the southwest corner of Burns Bog. d. Slough 4 Slough 4 is at the headwaters of Slough 3. It is comprised of Site 12 (see Plate 12) only. It receives drainage from agricultural land on the west, and Burns Bog on the east. It also receives some drainage water from the sanitary landfill area to the south and slightly east. This slough is l i t t l e more than a shallow ditch at the sampling point. e. Slough 5 Slough 5 is the northern portion of Crescent Slough. It was sampled from Sites 13 and 14 (see Plates 13 and 14). It receives water from Burns Bog to the east, and from agricultural land to the north and south. It appears to drain a relatively smaller area of agricultural land than does Slough 3 or Slough 2. It may receive some drainage from the sanitary landfill area, but not1 likely as much as is received by Slough 3. SLOUGH 3 PLATE 8: Outlet of Crescent Slough,from Site 8, looking Northeast - Pumphouse is behind Viewer. r l PLATE 9: Near Outlet of Crescent Slough, from Site 9, looking South - Pumphouse is to Right of Viewer. /102 SLOUGH 3 PLATE 1 1 : Crescent Slough from Site 1 1 , looking East. /103 SLOUGH 4 PLATE 12: Crescent Slough, from Site 12, looking South -Burns Bog in Left Background. /104 SLOUGH 5 PLATE 14: Crescent Slough from Site 14, looking North-west - Agricultural Land. /105 Most published maps show Sloughs 3, 4 and 5 to be topographically connected on the east side of Crescent Slough, near Slough 4. On-site inspection revealed this not to be the case. As stated previously, Slough 4 represents the headwaters of Slough 3. There was found to be a distance of about 150 to 200 m between Slough 4 and Slough 5. However, because of the close proximity of their headwaters to one another, Slough 3 and Slough 5 are probably fed from much the same source or sources at that point. f. Slough 6 Slough 6 is Deas Slough. It is comprised of Sites 15 and 16 (see Plates 15 and 16). It is an extension of the Fraser River, but receives some drainage from the study area via the pumping station at the south end of Crescent Slough. 6.2.3 Slough Parameter Magnitudes a. General Water Quality of Sloughs Table 12 presents a summary of acceptable water quality standards, depending upon intended use. Information regarding water quality standards for agricultural use, and for fish and other aquatic l i f e , is scarce. Standards for drinking water are the same as those for bathing, swimming and recreation. Water from all six sloughs proved to be unfit for domestic and recreational use at some time throughout the twelve month study period. SLOUGH 6 PLATE 16: Deas Slough and Marina, from Site 16, looking East. /107 Slough 1 occasionally, though infrequently, exhibited high metal contents. Manganese and iron were the two metals that most often exceeded recommended levels. Because of the heavy marine traffic in this slough, and because of the slough's proximity to the urban centre, lead was expected to be found in higher concentrations as well. However, lead concentrations did not exceed recommended levels as frequently as iron and manganese. Slough 2, as well as frequently exhibiting high metal contents relative to the domestic use standards, often exhibited a high enough specific conductance to make i t unsuitable for irrigation. Iron, and manganese-were the two • metals most often found to exceed recommended limits in this slough. Lead also occasionally exceeded recommended levels. The frequent extreme values of conductivity that this slough exhibited may have resulted from the intrusion of seawater through the groundwater system. Slough 3 also frequently proved unsuitable for domestic use by virtue of its metal content. Again, iron and manganese were the two metals that most often exceeded recommended limits. The above three sloughs are those in the study area which drain, or receive drainage water from, urban land. As a result, higher metal contents were expected to be found in those than in the remaining" three: sToughs. This was generally the case, with the exception of Slough 4. This slough was the most polluted, often exhibiting metal concentrations that were orders of magnitude higher than in any of the other sloughs. The water in this slough was consistently unfit for domestic use. In addition, high copper concentrations made i t consistently unfit for agricultural use. The close TABLE 12: Water Q u a l i t y Standards Gu i d e l i n e l e v e l Dept. of the Environment, 1972 Bathing, swimming, r e c r e a t i o n Resources Agency of C a l i f o r n i a , 1963 A g r i c u l t u r a l water supply, i r r i g a t i o n , stock watering, truck farming F i s h and other aquatic l i f e pH - 6.5-8.3 - -DO Obje c t i v e - - -Maximum - - -Acceptable - - -Pb Obj e c t i v e Not det e c t a b l e - -Maximum .05 mg/1 - • -Acceptable <.05 mg/1 - .1 mg/1 Cu Obje c t i v e <.01 mg/1 - -Maximum - - -Acceptable 1.00 mg/1 .1 mg/1 .05 mg/1 Zn Obj e c t i v e <1.0 mg/1 - -Maximum - - -Acceptable 5.0 mg/1 - 1.0 mg/1 A l O b j e c t i v e <.l mg/1 - -Maximum •5 mg/1 - -Acceptable .1 mg/1 - -Fe Obj e c t i v e <.05 mg/1 - -Maximum - - -Acceptable .30 mg/1 - -Mn Objective .01 mg/1 - -Maximum - - -Acceptable .05 mg/1 .5 mg/1 1.0 mg/1 S.C. Obj e c t i v e - <250 micro mhos/cm -Maximum - -Acceptable - 750-2000 micro mho/cm -continued. . TABLE 12: (continued) Guideline l e v e l Dept. of the Environment, 1972 Bathing, swimming, r e c r e a t i o n Resources Agency of C a l i f o r n i a , 1963 A g r i c u l t u r a l water supply, i r r i g a t i o n , stock watering, truck farming F i s h and other aquatic l i f e K Obj e c t i v e -Maximum 1000-2000 mg/1 Acceptable -Ca Obj e c t i v e <75 mg/1 Maximum -Acceptable 200 mg/1-Mg Obje c t i v e <50 mg/1 Maximum -Acceptable 150 mg/1 Na Obj e c t i v e -Maximum -Acceptable -P Obj e c t i v e .065 mg/1 Maximum -Acceptable .065 mg/1 N.T. Obj e c t i v e -Maximum -Acceptable -N.S. Objective <10.0.mg/l Maximum 10.0 mg/1 Acceptable <10.0 mg/1 % C Objective -Maximum -Acceptable -/ n o proximity of this slough to the sanitary landfill area on the eastern extremity of the study area may account for these high metal concentrations. Slough 5 exhibited some high metal concentrations at times, as did Slough 6, but the occurrence of same, was extremely infrequent, relative to that in the other four sloughs. Slough 5 and Slough 6 drain, or adjoin, agricultural land, primarily. For this reason, higher concentrations of the nutrient parameters were expected in these sloughs. To some extent this was found to be the case, although as will be explained later, nutrients appeared to relate more closely to sampling sites, than to sloughs. Iron and manganese were the two water quality parameters that were most consistently above acceptable domestic limits in all six sloughs. Manganese concentrations were also often high enough to make the water in all sloughs unfit for agricultural use. No explanation is offered for the widespread occurrence of these two parameters in such high concentrations. b. Comparative Analysis A comparative analysis of parameter magnitudes per slough, per month, was carried out, and the results summarized in Table 13. The major cations were omitted from this analysis because of their close correlation with specific conductance throughout the study period. Water temperature, pH, dissolved oxygen and lead were also omitted because of their probable insensi-tivity. Table 13 shows that the relative magnitudes of the various parameters for Slough 1 and Slough 6 were generally low, although specific conductance was high at times in the former. Slough 5 also exhibited relatively low / I l l TABLE 13: Relative Concentration of Parameters per Slough, per Month A 1 0 N D J F M A A 2 A 1 0 N D J F M A A 2 SLOUGH 1 Cu / / / / / / / / / Zn / / / / / / / / / Al / / / Fe / / Mn / / S.C. / / / / / P / / N.T. / / / / / N.S. / / / / / %C / / / / / / SLOUGH 2 Cu / / / / / / / / / Zn / / / / / Al ¥ / Fe / / / Mn / / / S.C. / / / / / / / P N.T. N.S. %C / / / / / SLOUGH 3 Cu • • / / / / / / • / Zn / / Al / / / / Fe / / / / / Mn / / / / S.C. / P N.T. / . ' / • ' / / / / / N.S. %C continued.. /112 TABLE 13: (continued) Highest Magnitude Lowest Magnitude Al 0 N D J F M A A 2 Al 0 N D J F M A A 2 SLOUGH 4 Cu / / / / / / / / Zn Al / / Fe / / / / / / « 3 Mn / / 2 & S.C, Q o p = N.T. / / / / / / N.S. / / %G / / / / / / SLOUGH 5 Cu / / / / / / / / / Zn Al Fe Mn / / S.C. • / / / / / / / P N.T. N.S. %C / / SLOUGH 6 Cu / / / / / / / / / Zn 7 / / / / / / / / Al / / Fe / / / / / Mn / / / / / S.C. / / / / P / / N.T. / / / / / / / N.S. / / / / / %C / / / / / 7113 magnitudes, but somewhat higher than those in Sloughs 1 and 6. These results may be a function of the fact that Sloughs 1 and 6 are extensions of the Fraser River. As such, they may periodically be subjected to a "flushing" process, depending upon the stage height of the river..Slough 5 drains agricultural land and Burns Bog, to some extent. Any water i t receives, other than as precipitation, has interacted with the proximate land, and probably carries with it materials characteristic of the various land use areas that it drains. Regular, and/or thorough-flushings therefore, may not occur to the-same extent. Slough 2 and Slough 3 exhibited relatively higher population magnitudes. Both had the highest metal concentrations at times, which may reflect the urban land that they drain. They differed from one another in that Slough 2 exhibited high specific conductance for the most part; whereas Slough 3 exhibited high total nitrogen concentrations. These results are difficult to explain. Slough 2 is closer to the ocean than is Slough 3, and as a result, its groundwater may be affected to a greater extent by intruding seawater. Slough 3 drains a greater proportion of agricultural land than does Slough 2. In addition, i t drains some agricultural land all along its length, whereas Slough 2 does so for about half its length, draining urban land only, nearer its outlet. Domestic sewage from agricultural land in the study area is dealt with by septic tanks. Urban sewage is piped to the Ladner Sewage Lagoon for treatment. In addition, the water table in the study area is generally quite high. These facts indicate that Slough 3 may be receiving nitrogen from residual fertilizers and/or domestic and agricultural organic matter at points or continuously along, its length. ' Slough 2 only re-/114 eeives the same sort of inputs "for about half its length, and from a relatively smaller area. This may explain the difference in total nitrogen concentrations. Slough 4 was generally the most polluted of the six sloughs. It did not exhibit a parameter population of low magnitude, and was consistently highest in copper, iron, and total nitrogen. Other parameter concentrations were high in this slough intermittantly throughout the study period. Slough 4 had less water in i t than any of the other sloughs, and drained a smaller area. The area immediately surrounding it is used extensively for grazing. Burns Bog is in close proximity. The sanitary landfill area is also in close proximity. Parameter concentrations were high in this slough probably because l i t t l e or no dilution occurred. Wastes from dairy cattle, as well as some organic input from Burns Bog via subsurface drainage, may account for the high total nitrogen concentrations. The high metal concentrations may be a result of drainage received from the sanitary land-f i l l area. Magnitudes of the nutrient parameters in the study area, were often found to be more effectively described in terms of sites, rather than as slough entities, although this was not always the case (see Table 14). Sites 11, 13, and 12 (Slough 4) were often found to have the highest phosphorus concentrations. Slough 3, along with Sites 12, 13, and 14, often had the highest total nitrogen concentrations. Sites 7, 10, 11, 12, and 13 exhibited the highest soluble nitrogen concentrations. These results suggest that nutrient inputs in the area are often a result of point sources because they appear to become diluted along the lengths of the sloughs. TABLE 14: Sites and/or Slough with Highest Concentration of Specific Nutrient Parameter in Given Month Al 0 N D J F M A A 2 P No Data 11,13 8,10,12 12 12 12 12 12 11 N.T. Slough 3 Slough 3 Slough 3 Slough 3 Slough 3 Slough 3 Slough 3 11 12 12,13 12,13,14 12 12 12 N.S. 10,12 10,11 ,13 12,13,14 7 7 7 7 11 /116 6.2.4 Independence Testing The Mann-Whitney U Test and curve analysis were both used in order to determine independent sets of parameter values between sloughs. Table 15 represents a summation: of ."the total significantly different • • ' (a = .05) sets of parameter values between all combinations of two sloughs. Table 16 outlines those specific sets of parameter values that were significantly different between any two sloughs. The maximum possible number of different sets of parameter values between any two sloughs, is thirteen. The most probable insensitive parameters, as determined by the percent coefficient of variation analysis for the entire study area (Section 6.1.1) are omitted from this summation. However, their sets of values were tested. a. Independent Sets of Slough Parameter Values Table 15 indicates that a comparison of Slough 4 with Slough 6 would yield the best elucidation of land use effects on water quality. These two sloughs were found to differ significantly insofar as all of the sensitive metals were concerned, as well as with regard to all of the nutrients. As stated previously, Slough 6 is Deas Slough. The area around it is used primarily for agriculture, but much of the drainage from this land flows into either portion of the Crescent Slough. Flushing of Deas Slough probably occurs in conjunction with high water in the Fraser River. The drainage characteristics of Slough 4 have been discussed previously. 7117 TABLE 15: Total Number of Significantly Different Sets of Parameter Values Between any Two Sloughs (a = .05) Slough 1 Slough 3 7 6 Slough 4 5 7 Slough 6 1 0 Slough , 5 J Slough 6 /118 A comparison of Slough 4 with Slough 1 also yielded a good elucidation of land use effects on water quality. These two sloughs exhibited significantly different sets of nutrient values. In addition, some of the sets of metal values were significantly different. Slough 1 and Slough 6 exhibited no significantly different sets of parameter values. Therefore, even though the land use surrounding both is quite different, the quality of water in each appears to be much the same. In relation to the quality of the other sloughs studied, the water in both is quite "pure". This would seem to indicate that the Fraser River is the primary factor affecting their water quality. The sediment data from these two sloughs, however, shows an abundance of lead (see The. Appendix), which probably originates as a result of the heavy marine traffic. In addition, the soils data from the March, 1977 sampling shows high concentrations of lead around Slough 1. Therefore, even though the quality of water in both sloughs appears to be relatively unaffected by land use, the quality of the sediment does not. This could ultimately affect water quality in both, depending upon such things as whether or not the sediment remains undisturbed. Table 15 indicates that Slough 2 differs from Slough 6 to the same extent that Slough 3 differs from Slough 6. Table 16 shows that they do so in a different fashion. Whereas Slough 3 and Slough 6 have significantly different sets of nutrient values, the major difference between Slough 2 and Slough 6 is that their specific conductance and major cation concentrations are not the same. This may reflect the greater area of agricultural land drained by Slough 3, and the intrusion of seawater into the area drained by Slough 2. TABLE 16: Specific Significnatly Different Sets of Parameters Values Between any Two Sloughs (a = .05) Slough 1 N.T. Ee 'P ,T. ,S. Cu S.C. Al Na Fe P N.T. N.S. % C Fe S.C. N.T. Mg N.S. Na Slough 2 Fe Na . N.T. Slough 3 Cu S.C. Fe Na Cu S.C. Na P N.T. % C Fe S.C. K Mg Na S.C. K Mg Na % C N.T. Zn S.C. Mn K Mg Na Zn K Fe Mg N.T P N.T N.S Slough 4 Cu K Zn Mg Cu K Zn Al Fe Mn P N.T N.S % C Slough 5 Fe N.T N.S Slough 6 TABLE 17: Summary of Table 16 in Terms of Major Parameters Specific significantly Specific significantly Slough Different Different inequalities Sets of Parameter Values Sets of Parameter Values 1 / 2 (N.T.) 1 j. 3 (P,N.T. ,N.S.) Nutrients 1 / 4 (Cu,Al,Fej + (P,N.T. ,N.S.) + (S.C.Na) Nutrients, Metals 1 / 5 (Fe) + (N.T.,N.S.) + (S.C.,Mg,Na) Major cations 2 / 3 (Fe) + (N.T.) + (Na) 2 / 4 (Cu,Fe) + (P,N.T.) + ( S . C , Na) 2 / 5 (Fe) + (S.C.,K,Mg,Na) Major cations 2 / 6 (Zn,Mn) + (N.T.) + (S.C.,K,Mg,Na) Major cations 3 / 4 (Cu) + (P) + (S.CNa) 3 / 5 (N.T.) + (S.C.,K,Mg,Na) Major cations 3 / 6 (Zn,Fe).+ (P,N.T.,N.S.) + (K,Mg) Nutrients 4 / 5 (Cu,Zn) + (P,N.T.) + (K,Mg) 4 / 6 (Cu,Zn,Al,Fe,Mn) + (P,N.T.,N.S.) + (K) Metals, Nutrients 5 / 6 (Fe) + (N,T.,N.S.) ro o /121 Slough 2 and Slough 3 differ from Slough 5 to the same extent, and in the same fashion. They both differ from Slough 5 insofar as specific conductance and the major cations are concerned. A comparison of Slough 1 with Slough 3 shows that phosphorus, total nitrogen, and soluble nitrogen concentrations are different between the two. Again, this probably reflects the agricultural land that Slough 3 drains. Also, since the metal concentrations are not significantly different, the urban land use that these two sloughs drain, probably affects them both in much the same fashion. b. Dependent Slough Parameters A knowledge of all the sets of values for all the parameters that differed significantly between all combinations of two sloughs, allowed a determination of equivalencies between sloughs to be made (Table 18). This determination showed that Slough 4 had unique copper and phosphorus values. All other sloughs had copper values that were not significantly different from one another. The remaining sloughs, with regard to phosphorus, could be divided into two sets. It was found that phosphorus values in Sloughs 1, 2, 5, and 6 were all equal to one another (i.e. P: Slough 1 = Slough 2 = Slough 5 = Slough 6). At the same time, P: Slough 2 = Slough 3 = Slough 5. It would appear, then, that copper inputs into the area were generally diffuse, or at least equivalent^throughout the study area, except in the case of Slough 4, which probably received quantities of that metal from a point source. As suggested previously, that point source was most likely the sanitary landfill area. Inputs of phosphorus, on the other hand, cannot be stratified as simply. . It would appear that Sloughs 2, 3, and 5 received /122 TABLE 18: Equivalent Sets of Parameter Values Derived from Table 16, Parameter Equivalent slough populations Cu (1=2=3=5=6); (4) Zn (1=2=3=4); (1=2=3=5); (1=5=6) Al (1=2=3=5=6); (2=3=4=5) Fe (1=2=6); (3=4=5) Mn (1=2=3=4=5); (1=3=5=6) S.C. (1=2=3); (1=3=6); (4=5=6) K (1=2=3=4); (1=5=6) Mg (1=2=3=4); (1=4=6); (5=6) Na (1=2); (1=3=6); (4=5=6) P (1=2=5=6); (2=3=5); (4) N.T. (1=6); (2=5); (3=4) N.S. (1=2=6); (2=3=4=5) %C (1=2=3=6); (1=3=5=6); (3=4=5) /123 more or less equivalent amounts of phosphorus, but also that Sloughs 2 and 5 received somewhat less than Slough 3. This latter, because phosphorus in Sloughs 2 and 5 cannot be distinctly separated from that in Sloughs 1 and 6. Iron was found to have two totally different regimes. For this metal, Fe: Slough 1 = Slough 2 = Slough 6; and, Fe: Slough 3 = Slough 4 = Slough 5. Sloughs 3, 4, and 5 effectively make up the Crescent Slough total. No explanation for this behavior can be offered at present. Total nitrogen was found to have three totally independent regimes; N.T.: Slough 1 = Slough 6; N.T.: Slough 2 = Slough 5; and, N.T.: Slough 3 = Slough 4. Slough 1 and Slough 6 are less intimately associated with the land than are the other sloughs. In addition, they may both be flushed, to some extent, as a result of their association with the Fraser River estuary. It is therefore reasonable that they might exhibit the same tendencies. In fact, the results from this study indicate that values obtained for all parameters measured were more or less equivalent between these two sloughs. Slough 3 and Slough 4would be expected to have somewhat similar nitrogen concentrations because of their topographical connection. This was the case with most other water quality parameters measured for these two sloughs. No explanation is offered as to why Slough 2 and Slough 5 exhibited similar total nitrogen concentrations. These two sloughs are somewhat removed from one another topographically, and drain different proportions of land use areas. The equalities in Table 18, coupled with the relative magnitudes of parameter values (Table 13), prove useful in analysing the variability of /124 some parameters. This is especially true with regard to the results of the percent coefficient of variation analysis described previously. In particular, the variability of iron, copper, and total nitrogen is thus further explained, which lends credence to the suggestion that all may have been sensitive to land use practices. The equalities in Table 18 may also indicate causal relationships between sloughs. c. Frequency of Individual Parameter Differences Between Sloughs Table 16 was tabulated in another fashion in order to show those parameters that were most often: significantly different between sloughs (Table 19). Total nitrogen was found to differ significantly twelve times between all sixteen various combinations of two sloughs. Iron differed significantly nine times. These two parameters, then, proved to be the most sensitive throughout the period of the study. 6.2.5 Percent Coef f i c i ent of Var iat ion Results of the percent coefficient of variation analysis for all sloughs are summarized in Tables 20 through 23. The relevant means and standard deviations used in this calculation are shown in Table 4 through 7. /125 TABLE 19: Relative Sensitivity of Parameters and Major Parameters, Derived from Table 16 Parameter Metals Cu 5 Zn 4 Al 2 4.4 Fe 9 Mn 2 Major cations S.C. 7 K 6 Mg 6 Na 8 Nutrients P 7 N.T. 12 N.S. 6 % C 4 6.8 7.3 x = Number of times specific parameter exhibits significantly different sets of values between all combinations of two sloughs (maximum = 16)a = .05. x = Frequency of significantly different sets of values regards major parameters. /126 a. Slough 1 Water quality parameters found to have an average percent coefficient of variation greater than 50 for this slough were: iron, manganese, total nitrogen and soluble nitrogen. Site 3 on this slough generally showed the highest concentrations of the above parameters. Water accumulates at this site because of its position behind the pumping station, and hence, various materials may accumulate with i t . Total nitrogen exhibited possibly the only seasonal trend, as its variation within Slough 1 increased in the winter and spring months. b. Slough 2 Iron, phosphorus and soluble nitrogen were all found to have average percent coefficients of variation greater than 50 in Slough 2. Phosphorus and soluble nitrogen are nutrients, and their variability may have arisen as a result of the agricultural land that this slough drains nearer its head waters. No consistent seasonal trends were evident in this slough. c. Slough 3 Manganese, phosphorus, specific conductance, potassium and total nitrogen were all found to have average percent coefficients of variation greater than 50 in Slough 3. /127 TABLE 20: Percent Coefficient of Variation for Parameters in Slough 1 (Sites 1, 2, 3, 4) Mean Al 0 N D J F M A A2 % C\ Water Temp 0 18 0 23 .29 7 5 15 3 11 pH 2 1 3 5 2 6 3 1 1 3 D.O. 23 25 14 22 8 19 16 15 10 17 Cu 0 0 49 0 0 35 20 67 0 19 Pb 20 32 22 0 18 0 0 12 0 12 Zn 0 133 40 86 40 0 38 0 0 37 Al 0 40 0 0 0 160 111 0 0 35 Fe 29 124 135 78 144 156 82 105 0 95 Mn 90 165 105 102 189 119 161 94 0 114 S.C. 39 75 50 49 6 10 52 29 2 35 K 104 83 55 50 4 13 38 25 10 42 Ca 4 10 25 56 17 21 13 28 9 20 Mg 47 76 59 69 15 17 52 38 8 42 Na 72 89 53 58 6 13 47 34 17 43 P - 24 35 51 64 44 59 72 25 47 N.T. 22 29 33 56 53 89 72 94 0 50 N.S. 45 51 44 78 144 63 83 76 55 71 % C 41 0 0 0 0 0 127 0 0 19 /128 TABLE 21: Percent Coefficient of Variation for Parameters in Slough 2 (Sites 5, 6, 7) Mean Al 0 N D J F M A A2 % C\ Water Temp 6 19 10 7 10 4 11 5 5 9 PH 21 2 3 5 4 6 3 5 2 6 D.O. 29 38 25 2 22 11 10 14 26 20 Cu 0 0 16 0 0 11 20 22 0 8 Pb 9 17 25 0 18 16 0 29 0 13 Zn 0 0 66 80 10 38 35 92 0 36 Al 0 0 50 109 0 57 69 0 0 32 Fe 25 71 40 43 84 49 68 105 0 54 Mn 75 100 31 41 25 37 12 13 0 37 S.C. 7 25 9 6 30 13 9 38 25 18 K 42 1 16 6 48 17 26 22 52 26 Ca 6 7 10 4 31 26 4 23 7 13 Mg 4 no 20 22 31 24 11 35 33 32 Na 13 30 11 9 35 16 21 37 54 25 P - 27 23 75 24 47 78 75 58 51 N.T. 0 19 3 58 52 55 18 68 0 30 N.S. 12 31 20 16 96 89 98 103 87 61 % C 0 0 0 0 0 0 0 0 0 0 /129 TABLE 22: Percent Coefficient of Variation for Parameters in Slough 3 (Sites 8, 9, 10, 11) Mean Al 0 N D J F M A A2 % C\ Water Temp 7 8 15 0 50 15 9 15 9 14 PH 7 2 1 2 1 6 2 2 4 3 D.O. 61 86 76 14 23 28 23 23 13 39 Cu 0 55 33 0 0 20 5 29 0 16 Pb 19 13 13 0 13 13 0 0 0 9 Zn 0 107 94 23 77 40 27 38 0 45 Al 0 0 67 44 7 43 27 0 0 21 Fe 23 114 46 21 47 33 9 22 0 35 Mn 120 110 55 47 51 58 105 29 0 64 S.C. 46 76 18 144 23 12 14 15 117 52 K 102 105 44 32 41 19 20 26 158 61 Ca 19 58 12 12 12 17 9 19 63 25 Mg 37 67 8 7 19 13 15 16 103 32 Na 48 72 24 15 31 14 9 7 53 30 P - 151 67 68 57 27 21 25 129 61 N.T. 39 131 29 39 39 27 5 35 136 . 53 N.S. 24 53 13 15 42 23 4 5 141 36 % c 22 119 0 0 0 0 0 0 0 16 /I30 TABLE 23: Percent Coefficient of Variation for Parameters in Slough 3 + 5 (Sites 8, 9, 10, 11, 13, 14) Al 0 N D J F M A Meai % Z\ Water Temp 6 11 15 8 63 18 10 18 8 17 PH 10 12 3 3 4 6 5 3 4 6 D.O. 65 73 63 14 21 22 24 44 34 40 Cu 0 56 28 0 0 34 16 37 0 19 Pb 17 16 24 0 15 16 0 0 0 10 Zn 0 108 84 35 84 37 52 39 0 49 Al 0 0 49 57 57 35 47 73 0 35 Fe 31 125 35 47 64 34 28 41 0 45 Mn 92 105 106 152 58 59 91 51 0 79 S.C. 65 96 48 178 65 58 58 71 127 85 K 137 130 76 55 80 59 58 78 190 96 Ca 23 63 27 30 37 38 34 56 60 41 Mg 45 70 23 51 52 45 47 63 110 56 Na 62 103 66 72 78 68 67 73 53 71 P - 130 66 59 49 42 38 32 128 60 N.T. 44 126 30 72 72 64 63 81 163 79 N.S. 33 58 58 57 33 18 7 7 150 47 % C 22 100 24 36 0 0 0 35 0 24 /131 Manganese concentrations were consistently highest at Site 11. The concentrations of all other of the above parameters were found to be intermittantly high and low at various times throughout the sampling period, but in no consistent fashion. In October, 1976, the percent coefficients of variation for all of the aforementioned water quality parameters in this slough, and those for the remainder of the major cations, were greater than 50. These results may indicate a common factor, or common factors, whjch influenced the behavior of that slough at that time. Insufficient data was available with which to infer anything more. d. Slough 4 There was insufficient data from this slough to conduct this analysis. e. Slough 3 and 5 Because Slough 5 only yielded two observations per month, per water quality parameter, the percent coefficient of variation analysis could not be carried out on it ail.one. As a result, the data from Slough 5 was combined with the data from Slough 3, and the percent coefficients of variation were calculated on that basis. It was felt that the results of this analysis could be interpreted in two ways: 1. The results could be considered as applying to one slough (i.e. Slough 3 + Slough 5 = Slough 3 and 5). /132 2. The results could be compared to those from Slough 3. Any significant difference would be a result of the data included from Slough 5. Hence, something might possibly be inferred concerning the water quality in Slough 5. It was found that manganese, phosphorus, specific conductance, potassium, and total nitrogen all had percent coefficients of variation greater than 50, as was the case with Slough 3 alone. However, magnesium and sodium also exhibited markedly higher percent C.V.'s in Slough 3 and 5. Therefore, the magnitude of the variability of the above two parameters was affected significantly by the combining of data. This implies that the concentrations of magnesium and sodium were of a different magnitude in Slough 5. There appeared to be no obvious seasonal trends in Slough 3 and 5. However, a comparison of the percent coefficients of variation from Slough 3 with those from Slough 3 and 5 indicated that the seasonal distribution of the variabilities of specific conductance, potassium, sodium, and total nitrogen had all been affected by the combination. Whereas, the variability was intermittantly high for these parameters in Slough 3, i t was consistently high in Slough 3 and 5. These results largely confirm what the Mann-Whitney U Test had already shown when applied to Sloughs 3 and 5 in Section 6.2.1.and Section 6.2.4. f. Slough 6 There was insufficient data to conduct this analysis for Slough 6. /133 6.2.6 Curve Analysis Average parameter values per slough, per month, were calculated and the values plotted against the sampling date for each slough. Probable insensitive parameters, as discerned in Section 6.2.5 of this report, were omitted from this analysis. The parameter, "specific conductance", was also omitted because of its close correlation with the major cations. Any distinct upward trends (peaks) and downward trends (dips) were noted, and recorded against the month in which they occurred, for that parameter in that slough. Total peaks versus total dips were then calculated every month for every slough. An upward or downward trend in a slough was considered to be one whereby a net difference between peaks and dips in any given month, was five or more. For example, i f there were eight parameters that peaked in a given month, in a given slough, and two that dipped, then the net difference would be six peaks, and the slough would be considered to exhibit an upward trend in that month. A summary of the data, in the above format is presented in Table 24 and Figure 11. Any discerned trend in a slough was analysed primarily in terms of major parameters (i.e. major cations, nutrients, and metals). If a majority of the parameters that make up a major parameter exhibited the same trend as was exhibited by the slough in that month, then that parameter was considered as having contributed significantly to the trend within the slough itself (see Table 25). No attempt was made to explain the causes of any of the various TABLE 24: Peaks and Dips per Slough Slough 1 Slough 2 Slough 3 Parameter Al 0 N D J F M A A2 Al 0 N D J F M A A2 Al 0 N D J F M A A2 Cu Zn * (*) * (*) (*) (*) (*) * (*) * (*) (*) * (*) * (*) (*) Al * * (*) * * (*) (*) * Fe (*) * * (*) (*) * * (*) * (*) Mn (*) (*) * (*) * (*) * (*) (*)' (*) * (*) * (*) (*) * (*) * (*) * (*) K (*) * (*) * (*) (*) * (*) * (*) * (*) (*) * (*) Mg (*) * (*) * (*) (*) * (*) * (*) (*) * (*) Na (*) * (*) * (*) {*) * (*) * (*) (*) * (*) P * (*) * (*) N.T. (*) (*) (*) * (*) N.S. (*) * (*)'. * * (*) (*) (*) * (*) (*) * (*) * (*) %C * (*) * (*) * (*) * (*) * * (*) Totals: * 1 1 0 4 2 3 2 4 0 1 2 0 1 4 2 2 6 0 1 6 0 2 2 0 3 6 0 (*) 5 1 2 0 3 0 4 2 6 6 3 1 0 2 1 5 0 7 6 0 4 1 3 3 3 1 8 * - Peak (*) - Dip continued. TABLE 24: (continued) Slough 4 Slough 5 Slough 6 Parameter Al 0 N D J F M A A2 Al 0 N D J F M A A2 Al .0 N D J . F M A A2 Cu ( * ) * ( * ) * ( * ) Zn ( * ) * ( * ) * * {*) ( * ) * ( * ) * ( * ) * Al ( * ) * * ( * ) ( * ) * Fe ( * ) * * ( * ) * ( * ) ( * ) ( * ) * ( * ) * ( * ) * ( * ) ( * ) ( * ) * Mn * ( * ) ( * ) * ( * ) * ( * ) * • ( * ) * ( * ) ( * ) * ( * ) ( * ) * ( * ) K * ( * ) * ( * ) • * ( * ) ( * ) IT) +J ( * ) * ( * ) ( * ) * * ( * ) Mg ( * ) * O • ( * ) ( * ) ( * ) * * ( * ) Na ( * ) ( * ) ( * ) * ( * ) P ( * ) * * ( * ) * ( * ) * ( * ) N.T. ( * ) * ( * ) * ( * ) N.S. * ( * ) * ( * ) * ( * ) * * ( * ) ( * ) ( * ) * * * ( * ) %C * ( * ) * ( * ) * ( * ) * ( * ) * ( * ) Totals: * 3 2 9 2 4 1 2 1 - 0 6 0 2 2 1 1 3 0 1 2 2 4 2 1 2 0 (*) 4 6 0 6 2 1 4 5 - 5 1 1 3 2 0 2 2 4 5 5 3 2 0 0 1 0 5 / 1 3 6 8-CO S 4-o. co 4 Q_ 8-SLOUGH SLOUGH 2 < UJ 4-9: 4-Q 8 -SLOUGH 3 SLOUGH 4 < SLOUGH 5 H > o o o UJ O 2 O Z (D CC < UJ < CC 0. < o < SLOUGH 6 J 8 < h- > o z m 9; o c O O U J < UJ < QL O Z Q ^5 U . 5 < N CD 3 < Figure 11. Peaks and Dips per Slough, (from Table 14-). /137 trends thus discerned, because it was felt that insufficient supportive data was available. a. Slough 1 Slough 1 exhibited a downward trend in August, 1977. This trend was largely attributable to the major cations. Soluble nitrogen, carbon, and manganese also contributed. b. Slough 2 Slough 2 exhibited a significant downward trend in August, 1976, and in August, 1977. Both of these trends were attributable to the major cations, as well as to soluble nitrogen and manganese. An upward trend occurred in Apri l , 1977, which was again largely attributable to the major cations. Manganese and zinc also contributed. c. Slough 3 Slough 3 showed a downward trend in August, 1976, as a result of down-ward trends in both the major cations and the metals. An upward trend in October, 1976 was attributable primarily to the metals. An upward trend in Apri l , 1977, occurred because the major cations all peaked. There was a distinct downward trend in August, 1977, because all the major parameters dipped. d. Slough 4 Slough 4 exhibited one distinct upward trend in November, 1976. All of the metals except aluminum peaked in this month. The major cations and nutrients also peaked. /138 TABLE 25: Trends in Sloughs Slough Month Trend Attributable to: 1 August/77 Down Major cations + (Zn, Mn, N.S.) 2 August/76 Down Major cations + (Fe, Mn, N.S.) April/77 Up Major cations + (Mn, Zn) August/77 Down Major cations + (Mn, Zn, N.S.) 3 August/76 Down Major cations, metals October/76 Up Metals + (P, K) ApriT/77 Up Major cations + (Mn, Fe, N.T.) August/77 Down Major cations, metals, nutrients 4 November/77 Up Major cations, metals, nutrients 5 August/76 Down Metals + (K, N.S.) 6 August/76 Down Major cations + (Fe, N.S.) October/76 Down Major cations, metals August/77 Down Major cations + (Mn, N.S.) /i 39 e. Slough 5 Slough 5 showed a downward trend in August, 1976, which was attributable to the metals, and to potassium and soluble nitrogen. It also exhibited an upward trend in October, 1976, as a result of the metals, some nutrients, and potassium. f. Slough 6 Slough 6 exhibited two downward trends throughout the study period. They occurred in October, 1976, and August, 1977. The former was attributable to the major cations and metals, and the latter to the major cations only. 6.3 Integration of Soi l and Sediment Data Soil and sediment data is presented in The-Appendix. Insufficient: data was available with which to conduct any rigorous statistical analyses, hence, most observations contained herein are of a subjective nature. Few soil and sediment parameter values were found to correlate strongly with those of water quality. Concentrations of lead and zinc in soils appeared to correspond roughly to urban land. Soils from Sloughs 1 and 2 generally possessed the highest concentrations of the above two parameters. Lead in sediments was concentrated around the marinas in both Slough 1 and Slough 6. Zinc was most concentrated in sediments from Slough 2. Lead concentrations in drainage waters were generally found to be highest in Sloughs 1 and 2. Zinc concentrations were generally insignificant and presented few water quality problems. These results may indicate that /140 some metals are entering the environment in the study area as a resul t of urban land use pract ices . In add i t ion , marina a c t i v i t y may also be contributing subs tan t ia l ly to lead contents in sediments. S igni f ican t quanti t ies of some metals appear to be associated with sediments. This circumstance could represent a sink of such metals which may current ly be r e l a t i v e l y inact ive as regards water q u a l i t y , per se. However, no extensive analyses were done on any of the sediment samples, and i t may therefore be that some b i o t i c elements, espec ia l ly bottom feeding organisms, are suffering the effects of metals associated with sediments. In add i t ion , l i t e r a t u r e indicates that , should the sediments in these sloughs become agi ta ted, or otherwise disturbed, metal concentrations in the water could r i s e sharply. A l s o , other modifications to water q u a l i t y , such as changes in pH, could d r a s t i c a l l y affect the s o l u b i l i t i e s of metals current ly associated with sediments. Copper concentrations in s o i l were found to be highest at S i te 12 (Slough 4) . This was more apparent in the s o i l s data from March, 1977, than in the data from October, 1976. Iron was also found in higher concentrations in s o i l s from Sloughs 3 and 4, than in sloughs elsewhere. Sediment data indicates much the same thing. Copper was extremely concentrated in sediment from slough 4, and iron was generally high in sediments from Sloughs 3, 4, and 5 . 1 Water qua l i ty data appears to r e f l ec t these f indings . Water from Slough 4 often exhibited the highest concentrations of copper, and Sloughs 3, 4, and 5 showed the highest values, cons i s ten t ly , for i ron . These resul ts are somewhat d i f f i c u l t to interpret with confidence. Whether water qua l i ty /141 in these sloughs is affecting sediment quality, or vice versa, is impossible to determine without further and more detailed data. However, the proximity of these sloughs to the sanitary landfill area, suggests that area as a source for the above metals. These metals, then, may be arriving at the sloughs via surface and subsurface drainage, and may subsequently be adhering to sediment particles in suspension, and at the bottoms of those sloughs. Concentrations of nutrients in sediments were generally found to be lower than in soils. Nutrients in soils and sediments did not relate strongly to those found in water, although concentrations were generally higher in soils and sediments taken from agricultural, which was also the case for water samples. The magnitudes of nutrient concentrations in soils and sediments taken from sloughs draining agricultural land were approximately equivalent between sloughs. Hence, soils and sediments from Slough 3 did not exhibit consistently higher concentrations of total nitrogen than soils and sediments from Slough 2 or Slough 5. The effects of the organic parent material from Burns Bog appeared to be manifest in the waters of Sloughs 4 and 5. Organic matter contents in the waters from these two sloughs was generally higher than elsewhere. This was not reflected in the sediment data. Water<i pH was also consistently lowest in Slough 4, which is the slough that is closest to Burns Bog. This may be a reflection of the effects of organic parent material on water quality in the area. /142 The proportion of major cations in soils and sediments did not reflect those found in water samples. Water samples exhibited higher concentrations of sodium, and potassium was most often found in lowest concentrations. Soils and sediments exhibited higher concentrations of calcium than of other major cations, and lower concentrations of sodium. This circumstance appears to indicate that saltwater intruding into the study area from the ocean may have more of a significant effect on the concentrations of major cations in sample water than does soil or sediment. Table 26 indicates the average composition of seawater. The values given in that table are also supported by Odum (1971). It should be noted that, even though seawater too, exhibits highest concentrations of sodium, and lowest concentrations of potassium, the proportions of those cations relative to one another are quite different than those exhibited generally by the water samples analysed in this study (Table 27). Hence, i t is possible that seawater is affecting water quality in the sloughs draining the study area. However, other factors appear to be amending water quality in that regard. Such factors could include the preferential retention of specific cations by soil and sediment, or the release of certain cations with weathering. In addition, various materials which contain significant quantities of such cations (e.g. fertilizers) could be entering the drainage systems throughout the study area, by way of surface runoff, groundwater flow, or erosion. The Fraser River may also exert an influence in this regard, perhaps explaining the afforementioned Na:K disparity. TABLE 26: Concentration of Elements in Seawater of Salinity 34-33% (Source: Deacon, 1962) Concentration (ppm) CI 18980 Na 10561 Mg 1272 S 884 Ca 400 K 380 Br 65 C 28 St 13 B 4.6 Si 0-4.0 Fl 1.4 /144 TABLE 27: Ratios of Concentrations of Major Cations in Seawater and in Collected Samples Samples Ratio Seawater (Derived from Table 1) Na:Mg 8.3 5.0 Na:Ca 26.4 6.7 Na:K 27.8 12.2 Mg:Ca 3.2 1.3 Mg: K 3.3 2.5 Ca:K 1.1 1.0 /145 7. SUMMARY The study area, located at and around the Ladner urban center, occupies about 5300 ha, of which 3500 ha is agricultural land, 700 ha is urban residential and urban industrial, 1000 ha is comprised of bogs and marshes, and the remainder is forested. The climate throughout is marine, hence temperatures are not extreme, and rainfall is moderate to high. However, rainfall during the study period was low relative to the norm. Soils in the study area are primarily developed on alluvial materials, although some organic soils also exist within study area boundaries. Owing to the proximity of the study area to the Fraser River estuary and to the Strait of Georgia, water tables are generally shallow, and most mineral soils, salty. Drainage is generally poor, so that much of the area is dyked and drained art i f ic ial ly . Crescent Slough and Cohilukthan Slough are the two major drainage channels. Most other drainage ditches empty into either one, or both. Hence, the two are interconnected. Both are also equipped with pumps and flood boxes at their outlets. Crescent Slough empties into Deas Slough on the south, and into the Fraser River on the north. Cohilukthan Slough empties into Ladner Slough. Sampling points were located on Ladner Slough, Deas Slough, Crescent Slough and Cohilukthan Slough. Water samples were collected approximately once a month during the f a l l , winter and spring, and once near the end of /146 each summer. Soil and sediment samples were collected twice throughout that twelve month period. The water quality parameters studied were: water temperature, pH, dissolved oxygen, cadmium, copper, lead, zinc, iron, aluminum, manganese, specific conductance, potassium, calcium, magnesium, sodium, total phosphorus, total nitrogen, soluble nitrogen, percent organic carbon and suspended solids. Dissolved oxygen and water temperature were measured in the field. Data from the analysis for suspended solids was extremely variable. It was also found to be inaccurate and was therefore not included in the analysis of results. Lead measurements were also found to be inaccurate, but were included in the analysis of results. Soil and sediment samples were analysed for particle size distribution and cation exchange capacity, as well as for all parameters measured in water samples, except those parameters that are peculiar to water alone (e.g. dissolved oxygen). Most laboratory analytical methods used are described by Lavkulich (1977). A percent coefficient of variation analysis was carried out with the water quality data, over the study area as an experimental unit. Values were low for water temperature, pH, dissolved oxygen, lead, and calcium, which suggests that these parameters were relatively insensitive to land use. Water temperature, pH, and dissolved oxygen were thought to depend more on climatic factors, than on land use. Calcium is prevalent in the soi l , throughout the study area, and hence is unlikely to have reflected land use practices to any great extent. In addition, seawater, which contains significant quantities of that cation, is known to intrude into the area underground. Lead measurements were found to be inaccurate in the /147 initial stages of this study. This may explain its apparent insensitivity to land use. Alternatively, i t may indeed have been relatively unaffected by land use practices in the study area. All other parameters were found to be potentially sensitive. Of these other parameters, copper, potassium, total and soluble nitrogen, and total phosphorus exhibited the highest percent coefficients of variation. No seasonal trends in the variability of any of the water quality parameters were evident. A correlation analysis was conducted with the water quality data. Most correlations were found to involve specific conductance and/or one of the major cations. Correlations between specific conductance and any of the major cations were not thought to imply anything as regards land use, because the major cations are also those that are largely responsible for the conductivity of water. Since most of the soils in the area exhibit relatively high concentrations of major cations, i t was felt that many correlations relating any of the major cations of specific conductance, to some other water quality parameter, may have resulted from the process of soil leaching. Iron was correlated significantly and negatively with dissolved oxygen five times, and positively with total nitrogen eight times. The former may relate to the oxidation status of iron as it affects its solubility, and the latter may indicate that iron is related to the movement of organic matter within the system, although iron was not correlated significantly with percent carbon. Copper.was correlated with both percent carbon and phosphorus four times. No consistent seasonal trends were evident as regards any of the above correlations. /148 Water samples in the drier months were observed to exhibit lower concentrations of major cations than they did in the wetter winter months. These results are contrary to what was expected, because the longer residence time of groundwater within the soil during summer would imply higher concentrations of such parameters. No explanation for the observed phenomenon is offered. Because of the interconnected nature of the drainage system within the study area, a grouping analysis was conducted with the water quality data in order to determine which groups of sampling sites most accurately characterized specific sloughs. The results suggested that the sixteen sampling sites characterized six different sloughs. Crescent Slough was found to be comprised of three "sub-sloughs". In this study, Ladner Slough is called Slough 1; Cohilukthan Slough, Slough 2; the southern portion of Crescent Slough, Slough 3; the one site at the headwaters of Slough 3, Slough 4; the northern portion of Crescent Slough, Slough 5; and Deas Slough, Slough 6. Further analysis of the data in this regard, indicated that Slough 3 and Slough 5 might legitimately be considered as one, i f necessary. Caution in so doing was warranted because specific conductance and, to some extent, total nitrogen were found to behave somewhat differently between the two sloughs. Water quality parameter magnitudes in each slough were compared to water quality standards as outlined by the Department of the Environment (1972), and the Resources Agency of California (1963). Some parameter magnitudes in every slough were found to exceed the guideline objectives /149 for domestic use in one or more months throughout the study period. Those sloughs draining or adjoining urban zones were observed to exhibit generally higher concentrations of metals than those draining or adjoining agricultural zones. This was expected, because other research indicates that many metals in the environment are by-products of industrial operations and other urban-oriented activities. Slough 4, which is situated fully in agricultural land, consistently exhibited the highest concentrations of metals. This was attributed to its proximity to the sanitary landfill area on the eastern extremity of the study area. Nutrient concentrations were seldom found to exceed recommended levels in any of the sloughs. Iron and manganese were the two water quality parameters that most often exceeded recommended levels. No explanation for this is offered. A comparative analysis of parameter magnitudes per slough, per month was carried out. The relatively low magnitudes with respect to Slough 1 and Slough 6 were attributed to a probable occasional flushing which occurs as a result of the association of both sloughs with the Fraser River estuary. Sloughs 2 and 3 had the highest metal concentrations at times, which was felt to reflect their association with urban land. Whereas Slough 2 also frequently exhibited high specific conductance, Slough 3 exhibited high total nitrogen concentrations. Slough 2, therefore, may be affected to a larger extent by intruding seawater, whereas Slough 3 may be receiving nitrogen from residual fertilizers and/or domestic and agricultural organic matter. 7150 Slough 4 was the most p o l l u t e d o f the s i x s loughs, e x h i b i t i n g c o n s i s t e n t l y high concent ra t i on s o f copper, i r o n , and t o t a l n i t r o g e n . Other parameter concent ra t i on s were f r equen t l y high i n t h i s s lough as w e l l . These r e s u l t s were p a r t i a l l y a t t r i b u t e d to the c l o s e p rox im i t y o f t ha t s lough to both Burns Bog and the s a n i t a r y l a n d f i l l a rea . P r ox im i t y to Burns Bog, i n con junc t ion w i t h the g raz ing t ha t occurred around t ha t s lough may have accounted f o r g ene r a l l y high t o t a l n i t rogen concen t r a t i on s . Surface and subsurface drainage from the s a n i t a r y l a n d f i l l area probably c on t r i bu ted to high metal c oncen t r a t i on s . In a d d i t i o n , Slough 4 i s at the headwaters o f Slough 3, and i s represented by one sampling s i t e on l y . Hence, l i t t l e o r no d i l u t i o n occurred i n t h i s s lough. Further a long the length o f Slough 3, parameter values were gene r a l l y found to be much l e s s concent ra ted . Magnitudes o f the n u t r i e n t parameters were o f t en more a p t l y desc r ibed i n terms o f s i t e s , r a the r than e n t i r e s loughs. In a d d i t i o n , those s i t e s which dra ined a g r i c u l t u r a l land gene r a l l y e x h i b i t e d the h ighest concent ra t i on s of such n u t r i e n t s . These r e s u l t s suggest that n u t r i e n t inputs may l a r g e l y r e s u l t from po i n t sources on a g r i c u l t u r a l l a n d . Parameter values between a l l s i x t een combinations o f two sloughs were te s ted f o r independence. Gene r a l l y , those sloughs d r a i n i n g o r a d j o i n i n g predominantly a g r i c u l t u r a l land e x h i b i t e d s i g n i f i c a n t l y d i f f e r e n t n u t r i e n t values than d i d those d r a i n i n g o r a d j o i n i n g urban l and . Those d r a i n i n g urban land showed h igher values f o r the meta l s . Slough 4, however, was anomalous i n that i t showed s i g n i f i c a n t l y d i f f e r e n t values between most other sloughs f o r both the n u t r i e n t s and the meta l s . As has been noted, t h i s i s probably /151 attributable to land use (i.e. grazing), and proximity to both Burns Bog. and the sanitary landfill area. From the independence test results, equivalences between sloughs, with respect to parameter values, were discerned. Slough 4 had copper and phosphorus values that were independent of those in any of the other sloughs. Hence this slough may be receiving point source inputs of these two water quality parameters. Iron was found to have two independent regimes over the study area. For this metal, Fe: Slough 1 = Slough 2 = Slough 6; and, Fe: Slough 3 = Slough 4 = Slough 5. Total nitrogen had three independent regimes, N.T.: Slough 1 = Slough 6; N.T.: Slough 2 = Slough 5; N.T.: Slough 3 = Slough 4. The frequency of individual parameter differences between sloughs indicated that iron and total nitrogen were possibly the parameters most sensitive to land use. The dependence and independence testing procedures also suggested that copper might be sensitive as well. These results were supported by the percent coefficient of variation analysis carried out over the study area, as an experimental unit. A percent coefficient of variation analysis was carried out whenever possible for all water quality parameters, per slough, per month, in order to discern which parameters might be sensitive to land use in each of the three sloughs that proved amenable to this analysis. Iron, manganese, phosphorus, total nitrogen and soluble nitrogen proved to be potentially sensitive. Also, most water quality parameters in Slough 3 showed considerable variability in the month of October, 1976, indicating a possible seasonal effect. /152 Slough parameter values were analysed with a curve analysis technique in order to discern possible trends over time, for each of the sloughs. Owing to the atypical climatic nature of the study period, and the relatively short duration of the study period, no trends were definable with any confidence. An attempt was made to relate soil and sediment data, to water quality data for the study period. Few soil and sediment parameter values were found to correlate strongly with those of water quality. Lead and zinc were found to be most abundant in soils and sediments from urban areas. Also, marina activity appeared to relate to the concentration of lead in sediments. Hence sediments may be acting to retain some metal ions. This situation may have implications as regards water quality in the future. In particular, should these sediments become agitated, a release of metal ions into the water could come about. Copper concentrations were found to be highest in the soil and sediment from Slough 4. Iron concentrations were, highest in the soils and sediments from Sloughs 3, 4, and 5. Water quality data reflected these results. The sanitary landfill area was suggested as a possible source of these metals. Concentrations of nutrients in sediments were generally found to be lower than in soils. Nutrient concentrations in either did not relate strongly to those found in water, except that they were higher in agricultural areas. The water quality in Slough 4 and 5 may have reflected the organic parent material in Burns Bog insofar as the organic matter contents in both sloughs /153 was often high, relative to that in other sloughs. Also the pH of water from Slough 4 was consistently lowest. The proportion of major cations in soils and sediments did not reflect those found in water samples. Water samples exhibited higher concentrations of sodium, and potassium was most often found in lowest concentrations. Soils and sediments exhibited higher concentrations of calcium than of other major cations, and lower concentrations of sodium. Owing to the fact that seawater is characterized by somewhat the same relative proportions of major cations, and also to the fact that seawater is known to intrude into the area underground, i t was suggested that seawater may therefore affect water quality in the area to some extent. However, the proportions of major cations in seawater relative to one another, were not the same as those found in sample water. Hence, seawater was not thought to affect water quality in the study area to the extent that it alone was responsible for major cation concentrations. Other factors, such as the spreading of potassium fertil izers, may also influence water quality. 8. CONCLUSIONS The effects of land use on water quality in the Ladner area are discernable, and often pronounced. Moreover, some water quality problems appear to exist. In this regard, some of the heavy metals, nutrients, and major cations occurred, intermittantly throughout the period of this study, /154 in concentrations which exceeded recommended levels. High concentrations of heavy metals were most often found in association with urban land use activities. High concentrations of nutrients were most often found in association with agricultural land. High concentrations of major cations appeared to relate primarily to underground intrusions of seawater. Iron and manganese were the two metals whose concentrations most often exceeded recommended domestic levels. Sites adjacent to the sanitary landfill area on the southwest corner of Burns Bog generally exhibited higher concentrations of iron, manganese and copper than were found elsewhere. This suggests that the sanitary landfill area may be largely responsible for inputs of those metals into proximate sloughs. It is probable that such inputs come about as a result of surface and subsurface flow from that area. High concentrations of lead were found in association with sediments taken from Ladner and Deas Sloughs. The water quality data for these two sloughs did not exhibit high concentrations of lead. Both sloughs do experience heavy marine traffic, however, thereby suggesting a source for lead in those local environments. Lead in the bottom sediments of these two sloughs, while possibly not being released quickly at present, may be so in the future should the sediment itself be disturbed. In addition, this study did not in any way evaluate the effects of land use on any of the biotic elements in the area. It is therefore possible that bottom feeding organisms may currently be suffering the effects of high lead concentrations in those sediments. /155 Drainage from some agricultural land was shown to often exhibit high concentrations of the nutrient parameters, although they did not often exceed recommended domestic levels. Total nitrogen concentrations were most evident in this regard, and may have reflected not only residual amounts of ferti l izers, but possibly also the effects of septic tanks installed in medium to fine textured, poorly drained parent material. With the exception of total nitrogen, nutrient concentrations were often quite variable at any one time between sites on the same slough. This probably indicates that their occurrence in surface waters comes about as a result of point sources, rather than from diffuse sources. Major cation concentrations in some sloughs occasionally exceeded recommended levels for use as irrigation. This was most often true for Cohilukthan Slough. Such high concentrations may, to some extent, result from land use practices, but i t is likely,that seawater intruding underground is primarily responsible for this. Concentrations of major cations were found to decrease in an easterly direction, away from the ocean. Water quality in Ladner Slough was not found to be significantly different from that in Deas Slough, but the land use patterns around both are quite different. This suggests that the Fraser River is probably the primary factor affecting water quality in both. It is probable that periodic flushing occurs in the above two sloughs, as the Fraser River responds to tidal cycles and the seasonal meltwater cycle. The municipal sewage lagoon, adjacent to Ladner Slough, was not shown in this study to significantly affect the water quality of Ladner Slough. /156 However, all parameters relevant to such a determination were not measured in this study. 9. RECOMMENDATIONS Inputs of metals, nutrients, and major cations a l l , to some extent, degrade the quality of water draining the Ladner area. While this currently does not appear to have significantly degraded the quality of water in Ladner and Deas Sloughs, there is great potential for it to do so. In addition, the water in some sloughs has been shown to be occasionally unfit for agricultural use. Wi th these facts in mind, some recommendations are herein made: 1 . Monitor groundwater quality, and response to climatic changes tidal cycles, and flow of. the Fraser River.~.No detailed information,of this nature is yet available. ..With this i nformati on,. more accurate accounts.;: of - ground-water effects ,on surface water quality.would be possible. 2. Monitor surface water quality in all major sloughs, year-round. This information in conjunction with the information derived from (1) above, would allow for a better elucidation of land use effects on water quality. In addition, monitoring of surface water quality would aid in determining the suitability of given surface waters for various uses. 3. Control drainage from the sanitary landfill area. There is l i t t l e doubt that this area is largely responsible for high metal concentrations /157 in proximate sloughs. Controlling this drainage could prove difficult and expensive, but i t is necessary. At the very least, drainage from this area should be monitored on all sides, and the most polluted drainage systems controlled. 4. Monitor seepage from agricultural land in order to determine the effects that septic tanks have on groundwater quality. This would likely entail the installation of sampling stations in proximity to the low density or scattered housing that occupies this land. In order to determine the effects on surface water quality, a network of groundwater sampling stations could be located in such a fashion so as to determine direction of groundwater flow into drainage channels. These, coupled with sampling stations along the drainage channels themselves, would likely allow for a very good elucidation of groundwater quality, movement, and effects on surface water quality. 5. The results from this report indicate that total nitrogen, iron, copper, and perhaps a few other water quality parameters, may be very sensitive to land use. These parameters are probably most amenable *.: to the above sorts of monitoring programs, not only because they appear to respond to land use practices, but also because they, by their very nature, represent possibly the greatest sources for concern. 6. Conduct studies designed to characterize the bottom sediments in Ladner Slough. Lead has been shown to be present in this sediment in high concentrations, as a result of unknown but assumed sources. Before anything is done to disturb the Ladner Slough environment further, a knowledge of how the sediment will respond to such disturbances should be acquired. /158 10. LITERATURE CITED Allen, Herbert E . , and James R. Kramer, Editors. 1972. Nutrients in natural waters. John Wiley and Sons, New York. 457 pp. Barber, E.M. 1975. Livestock manure and manuring practices in British Columbia. Fifth Brit. Col. Soil Sci. Workshop Report. 32-41 pp. Barry, R.G. and R.J. Chorley, 1968. Atmosphere, weather and climate. Methven and Co., Ltd. , London, England. 379 pp. Beak Consultants Ltd. 1977. Environmental impact assessment of Roberts Bank Port Expansion--Volume 4, Appendix B: The Existing Biological Environment. National Harbours Board, Port of Vancouver. Bhoojedhur, Seewant. 1975. Adsorption and heavy metal partitioning in soils and sediments of the Salmon River area, British Columbia. Unpub. Ph.D. thesis, Dept. of Soil Sc i . , U . B . C , Vancouver. 157 pp. Biggs, Wayne Griffin. 1976. An ecological and land use study of Burns Bog, Delta, British Columbia. Unpub. M.Sc. thesis, Dept. of Plant Sc i . , U . B . C , Vancouver. Biggs, W.G. and R.J. Hebda. 1976. 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Bull. 13 (4). /164 A P P E N D I X SITE tt AUG/76 OCT/76 NOV 76 DEC/76 JAN/77 FEB/77 MAR/77 APR/77 AUG/77 1 17 15 H 6 3 6 5 8 22 2 17 13 11 8 5 7 5 10 22 3 17 10 11 8 3 7 5 12 22 4 17 15 11 5 5 7 6 10 23 5 20 11 11 8 3 7 8 12 21 6 20 16 10 7 3 8 6 13 23 7 22 15 9 8 3 7 7 13 23 8 22 15 12 7 1 10 7 11 23 9 20 i a 9 7 2 8 7 11 21 10 22 15 9 7 3 7 6 10 25 11 19 17 9 7 3 8 8 i a 25 12 2a 20 9 7 2 8 10 i a • 13 22 19 8 6 1 7 8 16 26 i a 21 16 9 6 1 6 6 i a 23 15 20 16 10 5 0 7 8 17 28 16 17 15 9 5 1 5 7 10 27 TABLE A l , WATER QUALITY DATA WATER TEMPERATURE (*C) AUG/76 SITE * I 7.35 2 7.00 3 7.00 4 7.02 5 7.01 6 7.10 7 9.92 8 8,62 9 8.08 10 8,42 11 7.25 12 6.12 13 6.90 14 7.08 15 7.31 16 7.30 OCT/76 NOV/76 7.15 7.89 7.20 7.70 7.28 7,37 7.25 7.71 7.24 7.00 7.48 6,99 7,51 7.41 7.31 7.40 7.18 7.39 7.61 7.21 7.41 7.21 6.85 5.58 5.31 6,82 6,72 6,99 6.85 7.51 6.90 7.75 OEC/76 JAN/77 6,97 7.03 6.38 7.13 7,03 7.41 7,10 7.20 6,32 7,52 6.35 7.25 6.88 6.98 6,95 7.63 6.65 7,70 6.65 7.60 6.62 7.53 6.00 6.10 6,35 7.02 6.97 7.13 6.91 7.00 7.15 7.21 FEB/77 MAR/77 6,85 7,30 6.72 7.59 7,54 7,14 6.63 7.68 7,32 7.10 6.58 7.12 7.21 6.73 7.45 7.58 7,02 7.81 6.52 8,02 6.61 7.83 5.98 6.42 6.31 7.75 6.60 7.01 6.71 7.70 7.10 7.72 APR/77 AUG/77 7,69 7.20 7,56 7,30 7.65 7,33 7,68 7.31 7,42 7,35 7,63 7.18 6,86 7,10 7,72 7.24 7,98 7.10 7.81 7.28 7.72 7.73 7.42 m 7.42 7,00 7.31 7.14 7,64 7,31 7,81 7.75 TABLE A2, WATER QUALITY DATA PH AUG/76 SITE n 1 9.2 a 6.2 3 5.6 a 6.9 5 a.9 6 6.9 7 8.9 S 11.2 9 9.6 10 12.0 11 0.8 12 0.7 13 3.7 i a 4.6 15 5.a 16 5.6 OCT/76 NOV/76 6.0 9.2 7.2 8,0 a.o 6.5 7.3 7.9 4.6 7.1 10.0 7.8 7.0 4.7 6.4 1.4 4.1 3.4 1.3 0.4 0.6 1.4 4.0 2.8 2.1 3.2 6.3 a . l 6.B 7.0 9.6 7.8 DEC/76 JAN/77 11.3 9.4 7,2 9.0 7.8 7.8 10.a 8.2 7,2 5,9 7.5 7.2 7.4 4,6 5.3 6.3 4.2 5.4 a.5 5.0 3.8 3.5 3.6 3.2 5,4 4.0 5.0 5.3 7.0 3.5 10.0 5.2 FEB/77 MAR/77 9.1 10.0 8.4 11.0 5,8 7.5 8.6 10,8 6.6 6.7 7.8 7,4 8.2 8.2 5.5 6.5 4.1 a.7 3.3 4.8 3.0 3.8 1.2 2.3 3.7 a.7 4.3 7,1 7,1 8.4 9,5 9.9 APR/7? AU6/77 10.0 6.4 9.7 5.3 7,0 5.1 8.9 5.5 12,0 4,8 10.2 4,8 9,2 2.9 2.2 3.3 1.9 3.2 3.2 3.3 2.5 2.5 3.2 m 4.5 a.o 5.6 6.1 7.1 5.2 9.1 7.3 TABLE A3, WATER QUALITY DATA DISSOLVED OXYGEN (PPM) AUG/76 SITE a 1 <0.01 2 <0.01 3 <0.01 4 <o.oi 5 <0.01 6 <0.01 7 <0,01 8 <0,01 9 <0.01 10 <0,01 11 <0.01 12 <0.01 13 <0.01 14 <0.01 15 <0.01 16 <0.01 OCT/76 NOV/76 <0,01 0.02 <0.01 0.02 <0.01 0.01 «0.0l 0.01 <0.0l 0.01 <0.01 0.01 <0.01 0.01 <0.01 0,01 <0.01 0,01 <0,01 <0,01 <0.01 <0.01 <0.01 <0.01 <0.01 0.01 <0.01 0,01 <0.01 0,01 <0.01 0.02 DEC/76 JAN/77 <0.01 <0.01 <0.01 <0.01 <0.01 <0,01 <0.01 <o.oi <0.01 <0,01 <0.01 <0,0l <o,oi <0.01 <0,01 <0,01 <0,01 <0,01 <0,01 «0.01 <0,01 <0,01 <0,01 <0.0t « o , o i <0,01 <0,01 «0.0l <0.01 <0,0l <0,01 <0,01 FEB/77 MAR/77 0,01 0.01 0,01 0,01 0,01 <0.01 0.01 <0.01 <0,01 <0.01 0.01 0,01 o.oi <0,01 0.01 0,01 0.01 0,01 0.01 0,01 0,01 0,01 0.01 0,01 0,01 0.01 0.01 0.01 o.oi o.oi 0,01 0.01 APR/77 AUG/77 0,01 <Q,01 0.01 <0,01 0.01 <0,01 0.01 <0,01 0,01 <0,01 O.OI «0,01 0,01 <0,01 <o.oi <0,01 <0.01 <0.01 <0.01 <0,01 <0.01 <0,01 <0.01 m <0,01 <0,01 <0.01 <0,01 <0,01 <0.0t <0 .01 <0,01 TABLE A4, WATER QUALITY DATA CADMIUM (PPM) AUG/76 3ITE * 1 <0.01 2 <0.01 3 <0.01 a «0.01 5 <0.01 6 <0.01 7 <0.01 8 <0.01 9 <0.01 10 <0.01 11 <0.01 1? 0.87 13 <0.01 14 <0.01 15 <0.01 16 <0.01 OCT/76 NOV/76 <0.0i 0,08 <0.01 0,09 0.01 0,03 0.01 0.04 0.01 0.03 <0.01 0.04 <0.01 0.04 <0.01 0.07 <0.01 0.09 0.03 0,09 0,02 0,04 0,49 2.76 <0.01 0.06 <0.0l 0.06 <0.01 0.07 <0.01 0.04 OEC/76 JAN/77 <0.01 <0.01 <0.01 <0,01 <0.01 <o,oi <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0,0t <0.0i <0,01 <0.01 <0,01 <0.01 <0.01 <0.01 1.30 1.24 <0.01 <o.oi <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 FEB/77 MAR/77 0,03 0.05 0.02 0,07 0,02 0.08 0.04 0.06 0,05 0,08 0.06 0.09 0.05 0.06 0.06 0.10 0.07 0,09 0.08 0.09 0.05 0.09 1.73 2.40 0,03 0.08 0,04 0.06 0.04 0.05 0,04 0.04 APR/77 AUG/77 0,01 «0,01 0,01 «0.01 0,03 «0,01 <0,01 <0,01 0,03 «0,01 0,03 <0,01 0.02 «0,01 0,02 <0.01 0.02 0,01 0,01 <0,01 0.02 <0.01 1,23 m <0.01 <0.01 0.01 <0.01 «0.01 <0,01 «0.0! «0,0i TABLE A5, WATER QUALITY DATA COPPER (PPM) AUG/76 SITE n 1 <0.05 2 0.08 3 0,08 a 0.07 5 0.06 6 0.07 7 0.06 8 0.07 9 0.05 10 0.07 11 0.05 12 0.09 13 0.06 14 0.05 15 0.07 16 0.05 OCT/76 NOV/76 0,06 0,02 0.06 0.02 0.04 0.02 0.03 0.03 0.04 0.03 0.03 0.05 0.03 0,04 0.03 0.04 0.04 0.03 0.04 0.03 0.04 0.03 0.03 0.03 0.03 t> 0.03 0.02 0.02 0.03 0.02 0.02 DEC/76 JAN/77 <0.05 0,04 <0.05 0.06 <0.05 0,05 <0.05 0.06 <0.05 0,07 <0.05 0.07 <0,05 0.05 <0.05 0,03 <0.05 <0.03 <0.05 0.04 <0.05 <0.03 <0,05 0.03 <0.05 0.04 <0,05 <0,03 <0,05 0.04 <0,05 0,05 FEB/77 MAR/77 0,06 «0,03 0.06 «0.03 0,06 «0,03 0,06 <0,03 0,08 <0.03 0.08 «0.03 0.06 <0.03 0.04 <0.03 0,04 <0.03 0.04 <0,03 0.03 <0.03 0,03 <0,03 0.03 <0.03 0.03 <0,03 0,03 «0.03 0,03 <0,03 APR/77 AUG/77 0.04 «0,02 0.05 «0.02 0,04 «0,02 0,04 «0.02 0,07 <0,02 0,07 «0,02 0,04 «0,02 0,01 «0,02 0,01 «0,02 <0,03 <0,02 0,03 0.02 0,03 m <0,03 0,02 <0,03 <0,02 <0,03 «0,02 <0,03 <0.02 TABLE A6. WATER QUALITY DATA LEAD (PPM) AUG/76 SITE n 1 <0 . 01 2 <0.01 3 0.01 4 0.01 5 0.01 6 0,01 7 <0.0l 8 0.01 9 0.01 10 0.01 11 0.01 12 0.02 13 0.01 14 0,01 15 0.01 16 0.01 OCT/76 NOV/76 0.09 0.01 <0.01 0.01 <0.01 0.01 0.01 0.02 <0.01 0.05 <0.01 0.06 0.01 0.01 <0.01 0.01 0.09 0.01 0.2« 0,07 0.04 0,03 0.04 0.06 0.09 0.05 <0.0t 0.01 <0.01 0.01 <0.01 0.01 DEC/76 JAN/77 0.04 <o.oi 0.10 «0.01 0.03 0.02 <0.01 <0.01 0.05 0.09 0.09 0.11 <0.01 0.10 0.02 0.03 0,03 0.01 0.03 0.05 0,02 0.01 0.04 0.06 0.02 0.01 <0.01 0,01 <0,01 <0.01 <0.01 0.02 FEB/77 MAR/77 0.01 0.01 0.01 0.01 0.01 0.02 0.01 0.02 0.09 0.04 0.08 0.04 0,04 0.02 0.01 0.02 0,01 0.03 0.02 0.03 <0,01 0,04 0.03 0.03 0.02 0,01 0.02 0.01 0.01 0.01 0.02 0.01 APR/77 AUG/77 <0,01 <0,01 0,01 «0.01 0.01 «0,01 <0.01 <0,01 0.03 <0,01 0.02 <0.01 0.11 «0,01 0,02 <0.01 0.02 <0,01 0,01 <0,01 0.01 «0,01 0.03 • 0.01 <0,01 0.01 <0,01 0.01 «0,01 <0.01 <0,0I TABLE A7, WATER QUALITY DATA ZINC (PPM) AUG/76 OCT/76 NOV/76 DEC/76 JAN/77 FEB/77 MAW/77 APR/77 AUG/77 SITE * 1 <0.1 «o,t 0.1 «0.1 <0.i 0.1 <0.1 <0.1 «0,1 2 <0.1 <0.1 <0.1 <0,1 <0,1 0.1 0.1 <0.1 <0,1 3 <0.1 0.2 0.1 <0,1 <0,1 1 .7 0.6 <0.1 <0,1 4 <0.1 <0.l <0.1 <0.1 «0.l 0.1 0.1 <0.1 «0.1 5 <0.1 0.1 0.2 0.2 <0.1 0.3 1.1 «0,1 <0.1 6 <0.1 0.1 0.3 0,9 <0.1 0.6 1 <0,1 <0.l 7 <0.1 <0,l 0.1 <0.1 <0.1 0,2 0.2 <0,1 <0.1 8 <0.1 <0.1 <0.1 0.5 0.3 0.3 1.0 «0,l <0.1 9 <0,1 <0.1 <0.1 0.5 <0.1 0.2 0.9 <0,1 «0.1 10 «0,1 <0.1 «0.1 0.9 0.4 0.3 0,6 <0,1 «0.1 11 «0.1 <0.1 0.3 1.2 <0.1 0.1 0.6 <0,l <0,1 12 <0.1 4.6 0.6 0.4 0.2 0.3 0.3 0.1 • 13 <0.1 <0.1 0.2 0.9 0.5 0.2 0.3 o.a <0,1 14 <0.1 <0.l 0.2 «0.1 0.3 0.3 0.3 0.3 <0,1 15 <0.1 <0,1 0.1 <0.1 0.1 0,2 0.1 <0,1 «0,1 16 <0.1 <o.i <0.l <0.1 <0.1 0,1 0.1 <0,1 «0,1 TABLE A8, WATER QUALITY DATA ALUMINUM (PPM) AUG/76 OCT/76 NOV/76 DEC/76 SITE n 1 0.2 0.2 0.2 0.3 2 0,2 0.5 0.3 0,6 3 0.2 2.2 2.5 1.5 a 0.1 0.2 0.3 0,4 5 0.2 2.1 1.4 0.4 6 0.2 1.1 1.0 0,8 7 0.3 0.4 0.6 0.4 8 0.2 0.5 2.2 1.7 9 0.2 1.3 0.9 2.1 10 0.3 2,3 3.3 2.3 11 0.3 8.2 2.2 2.8 12 1.2 9.4 12.3 1.9 13 0.4 15.0 2.6 1 .7 14 0.2 0.7 2.6 0.3 15 0.1 0.2 0.5 0.9 16 0.1 0.2 0.3 0.5 JAN/77 FEB/77 MAR/77 APR/77 AUG/77 0.3 0.2 0.2 0.3 0.2 0.3 0.4 0,3 1.2 0.2 3.4 4.0 1.0 2.9 0.2 0.3 0.2 0,3 0.3 0,2 2.7 0.3 1.1 1.9 0.2 1.3 0.3 1.3 0,5 0.2 0,3 <0.1 0.2 0.2 0.2 7.0 2.3 3.6 8,0 0.2 10.1 3.7 4.0 6,6 0.2 4.9 5.4 «.t 7,2 0.2 15.0 4.1 4.5 10,7 0.2 7.6 6.7 3.8 3.1 • 2.6 2.2 2.4 3,6 0.2 3.9 3.3 2.1 3,6 0.2 2.6 1.4 0.9 0.4 0,2 1.1 0.2 0.6 0,5 0.2 TABLE A9. WATER QUALITY DATA IRON (PPM) TE tt AUG/76 OCT/76 NOV/76 OEC/76 JAN/77 FEB/77 MAR/77 APR/77 AUG/7 1 0.02 <0.01 0,02 0,03 <o.ot 0.10 <0.01 0,15 <0,01 2 0.10 <0.01 0,32 0,69 <0.01 0.24 0.01 0.85 <0.01 3 0.05 0.20 0.42 0.50 0.71 1.10 0.23 1 .37 <0,0l 4 0.01 <0.01 0,02 0,06 <0.01 0.15 0.02 0,15 <0.01 5 0.05 0.16 0.61 0.85 0,94 1,07 0.38 1.24 <0,01 6 0.08 0.06 0.77 0,67 1 .08 1.00 0.30 1.08 <0,01 7 0,01 < o . o i 0,40 0,35 0.64 0.49 0.34 0,96 <0,01 8 0.01 0.04 0.02 0,10 0.57 0.13 0.01 0.88 <0.01 9 0,01 0.10 0.02 0,09 1.17 0,48 0.05 0,90 <0,01 10 0,07 0.57 0.05 0,13 0.45 0,52 <0,01 0.74 <0.01 11 0,01 1.13 0.02 0,23 1.40 0,82 0,11 1.38 <0,01 12 0.48 0.32 0.70 0,20 0.63 0.63 0,42 0.64 • 13 0,05 0.89 0.11 0,01 0.39 0.30 0,16 0.32 <0,01 14 0.10 <0,01 0.21 <0.01 0.47 0.24 0,05 0.36 <0,01 15 0,02 <0.0l 0.07 0,07 0.16 0.09 0.01 0.65 « o , o i 16 0.04 <0.0l 0.50 <0.01 <0.01 <0,01 <0.01 0.21 <0.01 TABLE A10. WATER QUALITY DATA MANGANESE (PPM) AUG/76 OCT/76 NOV/76 DEC/76 JAN/77 FE8/77 MAR/77 APR/77 AUG/77 SITE n 1 115 266 345 1550 1920 2120 350 3240 102 2 241 308 400 1930 2050 2605 420 4600 98 3 235 965 895 435 2190 2340 1090 2250 99 4 122 280 418 1275 2195 2150 770 3200 101 5 250 1900 1810 2300 3105 4000 1580 6100 115 6 273 1900 2120 2420 3600 4550 1700 8200 153 7 290 1190 1800 2140 1930 3520 1900 3650 191 8 290 330 700 532 900 940 518 1900 140 9 385 575 509 425 512 975 560 1960 165 10 790 1400 695 468 830 1230 570 1420 309 11 440 2230 514 523 865 1030 705 1625 1345 12 535 203 372 161 278 304 175 260 13 125 380 193 125 115 245 146 121 130 14 175 155 202 64 128 178 96 125 175 15 135 134 258 517 467 529 615 880 105 16 115 140 175 537 1050 600 363 680 96 TABLE All, WATER QUALITY DATA -4 cn AUG/76 SITE * 1 <0.1 a 2.0 3 1.9 4 <0.1 5 2.0 6 2.8 7 4.6 6 10.6 9 12.0 10 69. 11 18.0 12 46, 13 1.3 14 0.9 15 0.3 16 <0.1 OCT/76 NOV/76 1 .8 2.8 2.3 3.2 7.8 7.8 2.0 3.3 16.6 15.7 16,7 18.8 17,0 21.5 9.3 27.5 19.9 9.5 64. 18.0 150, 14.1 15,9 20.9 16,4 3.5 1.4 2.5 1.3 2.5 1.1 2.2 DEC/76 JAN/77 14.8 18.0 23,0 18.5 5.9 18.7 12.7 19.7 20.3 22.3 23.0 24.0 22.0 50.0 9.7 20.5 7,6 6.5 9.3 16.3 15.2 14.1 10.9 21.7 4.6 1.2 2.3 1.9 6.2 4.5 6.5 9.4 FEB/77 MAR/77 13.0 3.1 16,5 3.8 12.5 7.0 13.5 6.5 20.5 10.0 24.0 14.5 29.0 17.0 10.5 11.5 12.5 10.0 15.0 10.0 10.0 15.0 7.5 6.0 3.2 3.1 1.9 2.1 4.0 5.5 4.4 3.3 APR/77 AUG/77 25.0 0.8 28.9 0.8 15.2 0.7 24,4 0.9 34.8 1.0 49,0 1.5 33,1 2.8 34,4 2.3 28,5 1.9 18.1 7.3 32,6 61. 7.6 • 1.2 1.2 1.2 1.6 6.7 0.9 4.9 0.8 TABLE A12, WATER QUALITY DATA POTASSIUM (PPM) AUG/76 SITE n 1 10.6 2 1 1.6 3 11.4 a 11.7 5 12.1 6 11.9 7 10.9 6 13,0 9 18.3 10 19.6 11 14.7 12 21.9 13 10.3 14 13,9 15 11.1 16 12.0 OCT/76 NOV/76 13.9 13.8 15.5 14.2 16.7 22,0 13.6 14.2 22.4 29.7 22.1 33.6 19.7 27,8 18,4 28,3 25,4 26,1 49,1 24,7 70.1 21,1 6.9 19,2 26,9 14,9 14.1 14.5 13.2 14.5 12.9 13.9 DEC/76 JAN/77 25.0 26.6 54.7 26.9 16.7 37.5 23.7 28.7 54.1 56.9 51.5 67.1 50.0 35.2 21 .7 27,3 20.8 22.1 19.9 21.7 25.1 26.2 i«.9 17.8 13.4 10,9 10.4 10.9 18.6 12.7 17.7 21.1 FEB/77 MAR/77 24,9 13.6 33.0 t«.4 39,4 18.0 26,9 17,0 66,4 29,1 7«,5 30,4 44.1 31.6 21,8 21,4 26.8 20.4 31.1 20,8 32.6 24.5 17,6 13.8 14.4 12.9 11.7 8.4 12.8 15.9 1«.7 13.8 APR/77 AUG/77 36,3 14.7 60.9 12.1 38,9 12.9 36,3 12.3 83,4 12.8 87,6 13,9 55,1 12,1 41.2 13,9 45,5 14,9 28.8 18,4 42,9 44,3 49,1 m 10,2 13,6 8,8 14,6 18,1 11.7 16,7 12.6 TABLE A13, WATER QUALITY DATA CALCIUM (PPM) AUG/76 OCT/76 NOV/76 DEC/76 SITE U 1 2.8 5.9 8.5 48. 2 7.8 7.6 10.4 112. 3 6.3 22.4 26. 21. a 3.4 6,1 10.5 44. 5 7.4 4.5 63. 110. 6 7.8 4.3 72. 100. 7 7.2 27,3 48. 71. 8 7.2 6.7 20.0 24. 9 9.9 11.4 19.2 22. 10 16.4 24.7 18.8 23. 11 9.4 35.4 16.5 26. 12 21.9 7.0 29. 17. 13 4.9 16.9 11.9 9. 14 6.3 4.8 11.3 4. 15 3.3 3.5 7.3 19. 16 3.1 3.1 5.1 22. AN/77 FEB/77 MAR/77 APR/77 AUG/77 55. 48, 10,5 83, 3.5 57. 64. 13,0 149, 2.9 76. 68. 33. 68, 3.0 62. 51. 23, 82. 3.2 129. 141. 53. 215, 3.5 156. 156. 62. 244, 4.7 81. 96, 66, 115. 6.7 33. 27. 30. 48. 4.4 22. 30, 22, 48, 5.0 24. 37. 23, 34, 7.9 30. 33, 23. 49, 30. 17. 22. 16, 21. m 7.4 12. 11. 7.6 4.2 8.3 10. 5.8 6.3 4.4 14.5 12. 18. 19, 3.1 27. 15. 11. 15,4 2.9 TABLE A14. WATER QUALITY DATA MAGNESIUM (PPM) AUG/76 OCT/76 NOV/76 DEC/76 SITE n 1 6.2 25.3 45. 450. 2 30.0 34.0 57. 512. 3 29.2 116. 129. 72. a 7.5 23.9 59, 305. 5 25.0 287. 272. 491. 6 29.1 281 . 336, 510. 7 32.5 159. 306. 426. 8 24.2 21.9 70. 90. 9 31 .6 49.0 48. 67, 10 7.9 136. 85. 73. 11 33.3 157. 58. 92. 12 17.7 6.9 15.4 8.0 13 8.6 12.9 11.0 7.6 14 9.3 7.8 9.8 4. 15 9,7 7.1 30.7 121 . 16 5,7 4.7 15.9 136. AN/77 FEB/77 MAR/77 APR/77 AUG/77 415. 320. 56. 577, 3.9 432. 410. 67, 870.. 3.4 465. 320, 156. 377, 3.3 464. 331, 130, 560, 4.7 612. 620, 251, 1 120, 5.7 740. 750, 310, 1390, 11.5 350. 550, 380. 624, 18.4 150, 122, 73. 218. 10.0 65. 105, 70. 224, 11.6 137. 138. 80. 188. 30. 129, 104, 85, 212, 167, 10. 9,0 6.8 10,7 • 8. 15.3 9,5 9.2 7,6 9. 9.4 6.1 7.4 15,2 79. 53. 97, 119. 4.6 199. 81. 53. 89, 3.0 TABLE A15, WATER QUALITY DATA SODIUM (PPM) AUG/76 OCT/76 NOV/76 DEC/76 SITE n 1 0.012 0.010 0.012 2 0.021 0.010 0,030 3 0.017 0.020 0,010 a 0,021 0.017 0,020 5 0.097 0,031 0.014 6 0.097 0.020 0,068 7 0.058 0,030 0.029 8 0.018 0.107 0,052 9 0.024 0.031 0.022 10 0.106 0.112 0.025 11 0,635 0.027 0.092 12 0.055 0.223 0.795 13 0,670 0.070 0,094 14 0.015 0.024 0,040 IS 0.015 0.022 0,018 16 0.009 0,018 0,015 AN/77 FEB/77 MAR/77 APR/77 AUG/77 0,012 0,010 0.013 0.027 0.009 0.007 0,022 0.011 0.069 0.005 0.026 0.028 0.037 0.020 0.007 0.009 0.014 0.037 0.018 0,009 0.013 0.022 0,022 0.049 0.007 0.008 0.022 0.063 0.036 0.010 0.011 0.008 0,015 0,005 0,021 0,024 0.024 0.037 0,028 0.008 0.007 0.029 0.031 0,027 0,013 0,013 0.018 0.022 0,040 0.032 0,009 0.012 0.034 0,023 0,141 0.076 0,035 0.133 0.053 m 0.009 0.019 0.035 0.018 0,031 0.014 0.018 0.009 0.018 0,013 0.012 0.014 0.016 0.012 0.007 0,027 0.015 0.014 0.017 0,008 TABLE A16, WATER QUALITY DATA PHOSPHORUS (PPM) oo o AUG/76 SITE 0 1 0.40 2 0.65 3 0.65 a 0.50 5 0.75 6 0.75 7 0.75 S 1.75 9 1.60 10 2.90 11 1.20 12 4,50 13 1 .25 ia 0.90 15 .0.70 16 0,70 OCT/76 NOV/76 0.35 0.56 0.35 0.46 0.60 0,71 0.38 0,31 1.25 1,13 1,08 1,17 0,85 1.11 0.55 1.96 1.20 1.06 2.68 1.88 12.30 1.25 4.70 11.44 4.65 2.17 0.28 2.44 0.30 0.56 0.30 0.38 DEC/76 JAN/77 0,63 1.46 2.02 0,86 1,65 1.11 0.69 0.29 1.29 1.67 3,00 1.25 1.11 0.50 4,31 10.83 3.31 3.83 4,31 9.79 7.65 7.40 5.21 11.25 2.69 1,44 1.04 1 .40 1.11 0.65 0,73 0.40 FEB/77 MAR/77 0.36 0,30 0,65 0.48 1,90 1 ,44 0,38 0,58 1.25 1,83 1,40 2,27 0.38 1 ,58 4.36 7.25 7,67 7,50 8.54 6.81 6,27 • 6.63 1.96 1.65 1 .96 0.88 1.17 0,58 0.58 0.40 0.33 APR/77 AUG/77 0.19 «0,10 1,38 «0.10 0,73 «0,10 0,15 <0,10 2,25 <0,10 2,61 <0.10 0,40 <0,10 26,35 «0,10 27,29 <0,10 10,63 0.68 25,83 2.58 3.23 1,44 <0 . 1 0 1,52 <0,10 0.33 «0.10 0.27 <0,10 TABLE A17, WATER QUALITY DATA TOTAL NITROGEN (PPM) co AUG/76 SITE n 1 0.07 2 0.13 3 0.14 4 0.05 5 0.17 6 0.20 7 0.16 8 0.64 9 0.83 10 1.06 11 0.66 12 1.74 13 0.69 14 0.36 15 0.11 16 0.25 OCT/76 NOV/76 0.09 0.11 0.10 0.22 0,24 0.33 0.12 0.18 0.51 0.69 0.38 0.60 0.27 0.46 0.52 0.70 0.59 0.63 1.00 0.69 1.58 0.85 0.66 1.46 1.01 1.76 0.24 2,13 0.17 0,34 0.18 0,18 DEC/76 JAN/77 0.69 <0,05 3.17 0,05 2.33 0.57 0.48 0,05 3.96 1.69 4.34 2,07 5.37 8,80 5.21 1 .70 3.87 0.72 5.06 2,06 5.57 1.15 2.19 1,74 4.68 1 ,96 1.35 1 .66 0,99 0.76 0.40 0,22 FEB/77 MAR/77 0,38 0,39 0.81 0,43 1 .49 1.80 0.48 0.61 2.61 2,64 3.24 3,25 12.16 14,34 1 .66 2,59 1.95 2,53 2.06 2,74 1.17 2.71 2.59 1.58 1 .88 2.46 1.79 2.25 1.11 0.91 0.25 0.50 APR/77 AUG/77 0.20 0,15 0.92 0,18 0.39 «0.05 0.24 0,07 1,33 <0,05 1.58 0,07 7,91 0,24 1.42 0.15 1,46 0,19 1,35 0.27 1,53 2,13 1.43 9 1.53 0.21 1.66 0.19 0.47 0.09 0,33 0,12 TABLE A18, WATER QUALITY DATA SOLUBLE NITROGEN (PPM) co ro TE U AUG/76 OCT/76 NOV/76 DEC/76 JAN/77 FEB/77 MAR/77 APR/77 AUG/77 1 0.001 0.001 <0.001 <0.001 <0.001 •50,001 <0.001 <0.001 <0,00t 2 0.002 <0.001 <0.001 <0,001 < o . o o i <0,001 <0.00l «0.001 «0.001 3 0.002 0.001 «0.001 <0.001 <0.001 <0,00l 0.001 <0.001 «0,00i a 0.003 <0.001 <0,001 «0,001 <0.001 <0,001 0.008 <0,001 <0,00l 5 0.002 0.001 <0.001 <0,001 <0.001 <0,001 0.001 0,001 <0,00i 6 0.002 0.001 <0.001 «0.001 < o . o o i <0,00l 0,001 <0,001 «0,00i 7 0.002 0.001 <0.001 <0,001 <0,001 <0,001 <0.001 <0.001 «0.001 8 0.002 0.001 0.001 0,001 0.001 0,001 0.001 0.001 <0,001 9 0.002 0.001 <0.001 0,001 <0.00l 0.001 0.001 0,001 <0,001 10 0.003 0.003 0,001 0,001 0.001 0.001 0.001 0.001 <0,00l 11 0.002 0.011 <0,001 0,001 0.001 <0,001 0,001 0.001 0,001 12 0,009 0.004 0.005 0,002 0.003 0,003 0,003 0.002 -13 0.003 0.011 0,002 0,001 0.001 0.001 0.001 0,002 <0,001 14 0,002 0.002 0,001 <0,001 0.001 0.001 0.001 0.001 «0,00l 15 0.002 0.002 <0,001 <0.00l 0.004 <o .oo i <0.001 <0,001 <0,001 16 0,002 0.002 <0.001 <0,001 <0.001 <0.001 <o .oo i «0.00l <0.001 TABLE A19. WATER QUALITY DATA CARBON (X) co CO SITE * TEXTURE C.E.C. ME/1006 PH (H20) PH (C AClg) CO (PPM) CU (PPM) PB (PPM) (PPM) AL (PPM) FE (PPM) 1 SIL 13.59 5,65 4,80 0.10 11.3 6.5 9.5 1135 375 2 S 5.U3 6,53 5.77 0,90 1.9 8.5 «1.4 1575 6 3 SIL 21. 46 5,32 4,91 0,25 30.3 18.5 17,8 1250 190 a LS 11.41 4,82 5.12 0,05 4.8 65.5 18.0 395 220 5 SIL 53.26 6.46 6,05 0,90 2.2 11.5 29,9 1750 7 6A SIL 25.00 5.23 4.80 0,35 11.6 7.0 14,9 1875 125 6B SIL 19.02 5.36 4,82 0,20 13,0 5.0 10.4 1360 215 6C SIL 18.21 6.48 6.00 «0.01 13.7 3.5 6.2 1145 255 7 SIL 33.15 5.27 4,90 0,05 3.3 2.5 20,7 940 210 8 LS 9.06 6.30 5.76 0.25 6,0 3.5 8.4 825 380 9 S 5,99 6.30 5,63 0,10 3.4 2.0 4,9 1015 300 10 SIL 20.11 5.50 4,80 0,45 6.6 3.0 9.8 905 285 11 SIL 23,64 5,50 5.00 0.40 10,4 4.5 10,5 1020 280 12 SIL 32.34 5,48 4.95 0.40 9.4 3.5 6.2 1045 100 12A * 199,76 3.40 2.59 0.20 0.5 12.0 2.5 700 240 12B 204.35 3,35 2.62 0.10 0.5 3.0 8,8 90 50 12C - 193,48 3,45 2.60 0.10 0.6 3.0 9,8 320 120 13 SIL 32.88 4,85 4.31 0.45 11.5 4.5 19,7 1435 180 ia SIL 23.10 5,02 4.75 0.40 U.l 3.0 7.6 1095 205 15 LS 9.96 5,55 4.80 0.15 3.1 1.5 2.0 750 225 16 S 5,99 5.60 4.98 <0.01 2.9 4.0 15,2 475 280 TABLE Bl. SOIL DATA OCTOBER, 1976 3ITE U MN (PPM) SPEC COND J*MHO/CM) K (PPM) CA (PPM) MG (PPM) NA (PPM) TTL N (PPM) SOL N (PPM) TTL P (PPM) C (X) 1 95 38 58 765 575 235 739 3.9 6.2 1.35 2 130 15 98 2115 1020 255 125 2.7 25.8 0.16 3 80 58 230 1295 440 60 1302 6,7 20.6 2.31 a 30 3a 76 380 115 25 958 a.3 31.5 2.11 5 120 119 87 1870 995 245 55a7 21.2 15.2 7,23 6A 60 59 aas 1005 435 54 !9a8 9,6 21.5 2.56 6B 60 45 99 1130 585 60 729 5.6 7.5 1.13 6C 60 33 a6 1235 745 82 625 5.2 3.9 0.85 7 85 131 680 1770 520 43 aos i 49,4 257,a a,91 8 100 26 95 665 260 60 a n a,8 17.1 o,5a 9 55 19 90 240 165 45 89 2.4 35,0 0.21 10 90 as a7 965 560 170 1141 5,8 a.7 1.50 11 100 60 218 1715 465 66 2031 17.1 18,3 2.89 12 205 113 6ao 2315 460 39 a656 29 , a 30,2 5.65 12A 3. 6 157 301 263 930 125 11960 56,9 19,8 100. 12B 1. a i a a ao 175 153 56 120a5 30.7 10.8 100. 12C 5 . 9 157 133 a77 710 222 12375 23,3 12,8 100. 13 100 52 355 ia95 415 63 3672 10,7 32,8 5.46 14 115 57 3a5 1565 425 49 1870 7.a 18,0 2.29 15 90 23 6a 400 215 65 a70 5,5 21.1 1.20 16 65 11 89 575 170 as loa 1.5 4.8 o . i a TABLE B2, SOIL DATA OCTOBER, 1976 SITE n TEXTURE C ^E-C . ME/100G PH (H20) PH (C ACLg) 5° (PPM) CU (PPM) PB (PPM) ZN (PPM) AL (PPM) FE (PPM) 1 L 27.99 5.98 4,72 0.05 24,0 63.5 25,3 1160 300 2 S 7.07 6.06 4,68 <0.01 2.5 1.0 0,6 515 165 3 su 17,93 6.28 4,75 0.05 15,3 25.0 11.9 1220 240 a US 12.50 5.88 4,75 0.15 8.6 104.0 14,6 510 215 5 SIL 28.80 6.02 4,97 0.25 a.a 14,0 22.9 945 125 6A L 23.64 5.55 4.40 0,20 8.6 37.5 36,4 1520 165 6B SIL 19,29 5.40 4.43 0.05 12.5 7,0 10,2 1300 250 6C SIL 18.21 6.33 5,00 0,15 12.1 1.0 7.4 1200 310 7 SIL 37,50 5.09 4,59 0.10 2.8 3,0 62,9 1160 165 8 L 14.13 5,74 4,73 0,15 11.0 1.5 11.2 1055 305 9 S 7,07 5.30 5.10 <0.01 6,4 2,0 15,7 1180 230 10 SIL 18.75 5,40 4,49 <0,01 8.2 1.0 3,0 1180 280 11 SIL 26,63 5,25 4.68 0.20 9,4 5.0 6,6 1090 215 12 SIL 26.63 5.33 4.13 0,20 164.8 1.5 17,6 1080 505 12A • 172,28 3.60 2,80 0.20 1.6 10,0 10,0 550 170 12B • 178.26 3,70 2.65 <o.ot 0.5 3.0 0,7 540 100 12C o 200,54 3.43 2.72 <0.01 2.5 9.0 22,9 310 100 13 SIL 22.55 5,73 4.86 0,25 14.4 14,0 13,0 1090 285 14 SIL 24,57 5,24 4.17 0.25 11.3 3.0 7.1 1255 205 15 S 13.77 5,24 4,59 <0,0i 6.6 1.5 1.8 765 405 16 S 5.25 5.18 4.77 <0,01 4.3 0,5 2.0 530 340 TABLE B3, SOIL DATA co MARCH, 1977 SITE * MN (PPM) SPEC COND .^MHO/CM) K (PPM) CA (PPM) M6 (PPM) NA (PPM) TTL N (PPM) SOL N (PPM) TTL P (PPM) 1 330 167 154 1545 810 510 2188 5.2 17.2 4,52 2 30 20 54 135 62 30 112 1.0 35,4 0.12 3 75 164 510 1100 325 101 1178 11.3 28,3 1.92 a 40 44 129 625 140 39 1086 6.9 33.4 2.46 5 80 122 950 3720 475 98 2668 16.6 24,8 4,83 6A 65 61 25 930 310 44 2496 13.3 47,8 4.16 6B 40 47 155 1120 460 51 954 8,6 10,1 1.44 6C 120 52 54 1480 820 175 587 5.4 4.9 0,79 7 85 105 650 1500 505 38 5591 24,3 439,4 6,86 8 100 69 168 1100 445 117 665 12.5 9.1 0,89 9 40 83 81 154 135 39 194 2.7 52,0 0.30 10 75 46 54 1010 710 125 1028 4.8 3.3 1.64 11 110 65 198 2000 420 65 2294 6,9 26,8 3,52 12 85 65 455 1520 515 49 1726 6.7 12.8 3.04 12A 222 232 435 1900 870 119 12430 33.5 24,2 100, 12B 43 160 212 530 950 130 11325 14.2 2.0 100. 12C 82 255 125 830 650 141 8015 20,4 5.6 100, 13 140 75 35 1745 635 70 1489 12,0 9.9 2.68 14 100 64 215 1625 375 56 1726 5,9 59,6 2,28 15 90 56 80 395 230 91 498 3.6 9.1 0.97 16 70 71 85 550 195 55 132 3,6 1.6 0,14 TABLE B4, SOIL DATA MARCH, 1977 SITE * TEXTURE ME/1006 PH (H20) PH (CACL^  CD (PPM) CU (PPM) PB (PPM) ZN (PPM) AL (PPM) FE (PPM) 1 LS 7,25 5.50 4,12 0,20 8.7 49, 10.2 685 630 2 SICL 24.46 6,74 6.20 0,25 12,2 7, 21.7 1325 255 3 SIL 32.61 5,48 5,02 0,85 22,2 7, 47,9 1775 1450 4 SICL 30.16 5,63 5.22 2,4 22,8 23. 21.9 965 420 5 L 42,66 5,70 5.46 1.2 7.8 «.5 66,9 1970 500 6 SIL 44.57 6.12 5,70 0,65 6,8 3.0 34,4 1860 250 7 SICL 36.86 5,40 5.20 0.55 11,8 1.0 20,7 960 205 a SIL 32.06 5.89 5.60 0,40 21.1 3.0 42,9 1000 850 9 S 6.34 6,91 6.41 0.10 4.3 1.5 7.7 395 440 10 SIL 14,95 6,78 6.03 0,15 11.8 1.5 5.3 740 800 11 SIL 26.36 6,10 5.50 0.50 15,9 3.0 17.1 1080 1150 12 SIL 29,35 4,80 4.46 0.45 609,6 2.0 12.8 1030 1350 13 SIL 46.74 4.94 4.60 0.55 19,3 3.0 20,4 1035 1750 14 LS 10.69 5.11 4,62 0,30 7.5 o.o 8.7 645 1000 15 S 8.68 6.00 5.36 0.10 5.0 2.0 7.4 630 355 16 SIL 25,26 5.37 4.76 0.45 17.2 69. 26.9 1125 550 TABLE CI. SEDIMENT DATA OCTOBER, 1976 co CO MN 3PEC COND K CA (PPM) UMHO/CM) (PPM) (PPM) SITE U ~ 1 60 54 62 645 2 330 108 144 1675 3 115 211 110 1030 4 225 126 130 1225 5 80 565 Ul 1605 6 125 530 198 1375 7 40 890 145 580 8 210 272 330 2295 9 55 70 85 995 10 90 93 165 2885 11 95 211 435 2030 12 75 168 310 1205 13 150 141 117 2215 14 100 63 62 1065 15 65 40 45 645 16 255 87 105 1580 MG (PPM) NA (PPM) TTL N (PPM) SOL N (PPM) TTL P (PPM) C (X) 275 96 250 5.3 4,3 0,37 645 190 1906 8.7 12.1 2.46 455 225 1906 9,0 8,2 2,81 450 155 2390 10,6 11.6 4.17 760 340 3531 13,9 13.0 5.59 945 745 3469 1«,9 13.9 5.43 415 290 2922 13.2 25,4 4.64 735 195 3797 15.3 15,1 3.67 210 84 188 12.3 13,1 0,47 1230 245 375 9.6 4.5 0.74 800 455 1016 9.7 11.3 1,82 430 100 1859 9.1 9.3 3.22 500 93 2375 10,9 7.1 5.72 270 72 578 8,7 7.0 1.16 195 61 391 8.1 13,2 2.17 535 102 1701 10,2 9.0 3,47 TABLE C2. SEDIMENT DATA OCTOBER, 1976 co SITE * TEXTURE C.E.C, ME/100G PH (H20) PH (C ACL*) CO (PPM) CU (PPM) PB (PPM) 2N (PPM) AL (PPM) FE (PPM) 1 S 8,70 5.59 4,51 0,25 9,0 53,5 20.3 725 550 2 SIL 29.62 6.10 5.22 0,70 16.5 8,0 30,9 1830 235 3 SL 24,18 5,35 4,54 0.65 32,3 9.5 31.9 2090 700 4 SL 14,40 5.90 4,38 0,35 10.3 54, 9.8 910 500 5 SIL 41,84 6,12 4,99 0.85 6,2 5.0 53,9 2225 45 6 SIL 39,67 6,20 4.96 0,65 6,0 3.0 15.2 2425 50 7 SIL 43,75 6.16 4.89 0.50 10,9 1.5 IT,4 1730 330 8 L 25,00 6.14 5.01 0,35 20.8 5.0 26.4 905 575 9 S 6.70 6,12 5.05 0.30 3.5 3.5 8.3 510 530 10 SIL 16.03 6.37 5.23 0,35 16.8 1.5 10,7 835 1000 11 SIL 22.83 6,18 4.69 0.45 18.1 3.0 15.4 1095 800 12 SIL 27,17 5,45 3,99 0,40 155,8 1.5 12,0 1165 750 13 SIL 63.86 5,85 4.60 0.45 11.0 3.0 15,6 710 330 14 SIL 51,90 5,71 4,68 0,45 15,5 5.5 83,9 700 470 15 S 9.60 6,11 4,78 0.15 4.1 2.0 5.2 530 420 16 L 15.22 6,29 5,02 0,25 12.8 19. 15,2 1095 510 TABLE C3, SEOIMENT OATA MARCH, 1977 S I T E n MN (PPM) S P E C COND JAMHO/CM) K (PPM) CA (PPM) * MG (PPM) NA (PPM) T T L N (PPM) SOL N (PPM) T T L P (PPM) C ( X ) 1 6 5 9 3 82 6 8 0 2 7 5 170 2 0 7 2.3 9,0 0.48 2 4 5 0 2 4 0 2 3 0 1 0 0 0 8 9 0 5 4 5 1 8 7 4 2 2 . 5 16,1 2 . 9 2 3 1 0 5 2 5 7 131 5 3 5 5 1 0 350 1328 4.2 2 7 , 8 2 . 9 5 4 40 9 6 9 5 440 310 190 9 3 0 1.8 31,0 1.98 5 1 5 5 3 7 8 179 1 2 6 5 7 1 5 6 2 5 3 2 5 8 7.1 3 1 , 6 5 , 3 4 6 165 2 8 6 2 0 0 750 8 1 0 57 2051 7.7 2 5 . 3 4 . 3 9 7 155 5 3 5 4 1 5 1 6 3 5 1 0 3 0 1 1 6 5 3 1 8 3 12.0 2 3 . 5 5 , 8 9 8 6 4 0 125 1 9 9 1 6 3 0 6 3 0 2 1 0 1 9 7 6 14.9 16.7 3.21 9 7 5 45 6 5 750 2 5 5 7 9 156 6.4 10.6 0.24 10 1 0 5 187 146 2 6 6 5 1 2 5 0 2 5 5 540 7.2 2,8 1.06 11 130 164 2 0 5 1 8 9 0 8 8 0 2 9 5 1049 11.6 5.5 2 , 1 6 12 50 160 1 1 6 1 5 9 5 7 1 0 81 1 5 2 6 2.9 5,7 2 . 1 7 13 4 6 0 138 1 5 3 3 9 9 5 820 128 4 3 5 8 10,8 8,6 9,98 14 3 8 0 166 145 4 1 9 5 7 9 5 103 3 5 3 9 9,4 10.5 8.80 15 125 9 9 6 5 5 9 0 2 5 5 130 2 9 9 3,6 11.7 0.80 16 190 78 132 1 0 4 5 6 7 5 250 5 9 8 3,6 7.1 1.15 T A B L E C 4 , SEDIMENT DATA MARCH, 1977 

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