WATER QUALITY TRENDS IN THE BLACKWATER RIVER WATERSHED CANAAN VALLEY, WEST VIRGINIA. Jessica M. Smith

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1 WATER QUALITY TRENDS IN THE BLACKWATER RIVER WATERSHED CANAAN VALLEY, WEST VIRGINIA Jessica M. Smith Thesis submitted to the Davis College of Agriculture, Forestry and Consumer Sciences at West Virginia University in partial fulfillment of the requirements for the degree of Master of Science in Wildlife and Fisheries Resources Stuart A. Welsh, Ph.D., U.S. Geological Survey, West Virginia Cooperative Fish and Wildlife Research Unit James T. Anderson, Ph.D. West Virginia University Division of Forestry Ronald H. Fortney, Ph.D. West Virginia University Department of Civil and Environmental Engineering Division of Forestry 004 Keywords: Akaike Information Criterion, Blackwater River, Canaan Valley, seasonal Kendall analysis, water quality, West Virginia

2 ABSTRACT WATER QUALITY TRENDS IN THE BLACKWATER RIVER WATERSHED CANAAN VALLEY, WEST VIRGINA JESSICA M. SMITH The Blackwater River, historically an excellent brook trout (Salvelinus fontinalis) fishery, has been affected by logging, fires, coal mining, acid rain, and land development. Trends in water quality data from sites in the Blackwater River watershed were examined for a 4-year period (980 99) using the information-theoretic method and the seasonal Kendall with correlation correction analysis. For most sites (except Beaver Creek), downward trends in acidity and upward trends in alkalinity, conductivity, and hardness were consistent with decreases in hydrogen ion concentration. Dissolved oxygen trended downward possibly due to natural conditions, but remained above biological thresholds. The seasonal Kendall trend analysis provided similar results to the information-theoretic analysis, however, the information theoretic approach detected a higher number of trends. The seasonal Kendall analysis may have lacked the power to detect all trends present in the watershed. Additional comparisons of the seasonal Kendall, information theoretic, and other trend analyses are needed to further evaluate methodologies used for water quality trend assessments. Despite the trends supported by this data, water quality changed only slightly within the Blackwater watershed from 980 to 99, possibly owing to relatively minimal changes in development and landuse during this time period. These results have greatest potential as a baseline for future water quality assessments.

3 iii Dedication For my wonderful roommate Elayne, who was an endless source of encouragement throughout this project. Thank you for having the patient to listen when I needed to talk, for motivating me continually to work on this project, and for believing in me even when I doubted myself.

4 iv Acknowledgements I thank the following agencies that funded this project: the Canaan Valley Institute and West Virginia University. I thank each of my committee members for their contribution to this project. I thank Stuart Welsh, for his support and assistance. I also thank James Anderson and Ronald Fortney for their advice throughout this project. A special thank you to all those who proof read the reams and reams of data that were used in this project, Stuart Welsh, Dave Wellman, Steve Hammond, Ben Lenz, and Lara Hedrick.

5 v TABLE OF CONTENTS: CHAPTER I. LIST OF TABLES.... vi CHAPTER I. LIST OF FIGURES... vi CHAPTER II. LIST OF TABLES...vi CHAPTER II. LIST OF FIGURES.....vi CHAPTER III. LIST OF TABLES...vi CHAPTER III. LIST OF FIGURES.....vi LIST OF APPENDICES... vi CHAPTER I... A REVIEW OF THE LITERATURE CONCERNING FACTORS INFLUENCING THE WATER QUALITY OF THE BLACKWATER RIVER IN TUCKER COUNTY, WEST VIRGINIA INTRODUCTION... STUDY AREA... NATURAL INFLUENCES... HISTORICAL INFLUENCES... INFLUENCES ON WATER QUALITY PARAMETERS OBJECTIVES... 6 WORKS CITED... 7 CHAPTER II...9 WATER QUALITY TRENDS (980 99) IN THE BLACKWATER RIVER WATERSHED, WEST VIRGINIA...9 INTRODUCTION... METHODS... RESULTS... 7 DISCUSSION MANAGEMENT IMPLICATIONS... 0 ACKNOWLEDGMENTS... LITERATURE CITED... CHAPTER III...0 TREND ANALYSES OF WATER QUALITY DATA FROM BLACKWATER RIVER, TUCKER COUNTY, WEST VIRGINIA: A COMPARISON OF TWO METHODS...0 INTRODUCTION... 0 METHODS... RESULTS... 4 DISCUSSION... 5 ACKNOWLEDGMENTS... 6 LITERATURE CITED... 6

6 vi CHAPTER II. LIST OF TABLES Table. Summary of evidence ratios supporting models of monotonic (T) or land use (L) trends of 0 water quality parameters at sites (980-99) separated by spring (March - May) and summer (July - September) seasons...4 Table. Summary of model selection statistics from trend analyses of precipitation and flow from at the USGS gaging station at the Blackwater River at Davis... 7 CHAPTER III. LIST OF TABLES Table. Comparison of seasonal Kendall (SK) significance with information theoretic (IT) trend analysis for 0 water quality Blackwater River watershed parameters at sites in the Upper Blackwater River watershed during the spring and summer seasons Table. Breakdown of the number of sites that contain trends for the seasonal Kendall (SK) the information theoretic (IT) or both analyses... 4 Table. Number of sites with trends detected by the seasonal Kendall method (SK, p<0.0), the information theoretic approach (IT, evidence ratio = ), and both methods...4 CHAPTER II. LIST OF FIGURES Figure. Bedrock geology and locations of water quality collection sites within the upper Blackwater River watershed... 9 CHAPTER III. LIST OF FIGURES Figure. Bedrock geology and locations of water quality collection sites within the upper Blackwater River watershed Figure. Log transformed Akaike evidence ratios correlated to log- transformed seasonal Kendall p-values calculated for 0 water quality parameters during spring and summer at sites in the Blackwater River watershed LIST OF APPENDICES APPENDIX I. Summary Statistics sample size (n), mean, and standard error (SE) for 0 water quality constituents sampled from by site and season: spring (March April, May) and summer (July August, September) APPENDIX II. Comparison of seasonal Kendall (SK) significance p-values with information theoretic (IT) evidence ratios for 0 water quality parameters in the Blackwater River watershed parameters at sites...7

7 Smith et al. CHAPTER I A REVIEW OF THE LITERATURE CONCERNING FACTORS INFLUENCING THE WATER QUALITY OF THE BLACKWATER RIVER IN TUCKER COUNTY, WEST VIRGINIA Water chemistry is often used as a measure of aquatic ecosystem health. A single water quality sample, however, provides a snapshot of conditions of a single moment. Trend analysis of data collected over a long period of time is necessary to understand factors operating on a watershed-wide scale. This analysis makes it possible to see what factors from the past are currently impacting the watershed and more importantly, what the condition of the watershed may be in the future. In this thesis, I report on water quality trends in the Blackwater River in Tucker County, West Virginia. This watershed has been affected by logging, fires, acid mine drainage, acid rain, and land development of recreational areas. The Blackwater River and its major tributaries were sampled by the Allegheny Power Company from to support the Davis Power Project. This project, proposed in 970, would have constructed a,8 hectare lake in Canaan Valley to generate electricity via a pumped storage hydroelectric plant (U. S. Fish and Wildlife Service 979, Michael 00). In 977 the Federal Power Commission issued a license to Allegheny Power to construct this project (Michael 00). However, one year later in 978 the project was denied a Clean Water Act Permit by the U. S. Army Corps of Engineers, due to the project s adverse impacts on wetlands (Michael 00). Court cases continued for the next 0 years but the project was never constructed. During the litigation, water quality was sampled monthly throughout the watershed. This sampling included sites throughout the Upper Blackwater watershed beginning in 978 and

8 Smith et al. continuing until the summer of 99. This time series of water quality data is the basis for research reported in Chapters and. STUDY AREA The upper Blackwater River is located in Tucker County, in northern West Virginia (Figure ). The nearest population center, Davis, is located 5 kilometers (km) to the west and it is 58 km south of Pittsburgh and 90 km west of Washington, D. C. (U. S. Fish and Wildlife Service 979). The Blackwater River begins in Canaan Valley between Cabin, Brown, and Canaan Mountains, flows west to join with Dry Fork forming the Black Fork River, and drains eventually into the Cheat River (U. S. Fish and Wildlife Service 979). Water from the Blackwater River is a dilute calcium magnesium bicarbonate type that is typically soft and low in alkalinity and dissolved solids (Waldron and Wiley 996). NATURAL INFLUENCES The stream gradient of the Blackwater River in Canaan Valley is low causing numerous wetlands to occur (U. S. Fish and Wildlife Service 979). The gradient of the Blackwater River in Canaan Valley is about 0.7 meters per km with the gradient between Canaan Valley and Davis rising to approximately. meters per km (U. S. Fish and Wildlife Service 979). Due to this low stream gradient and the underlying geology, Canaan Valley contains the single largest wetland area (about,8 hectares) in the central and southern Appalachians, and comprises 9% of all wetlands in West Virginia (U. S. Fish and Wildlife Service 979). The climate in this region is typically cold and humid with temperatures ranging between 5 o C and o C and a mean annual temperature of 6.7 o C (Weedfall 965, U. S. Fish and Wildlife Service 979). Subfreezing temperatures have been recorded during every month of the year and snow has been recorded during every month except July and August (U. S. Fish and

9 Smith et al. Wildlife Service 979). The snow is usually very heavy and averages 04.8 centimeters (cm) per season (Weedfall 965). Precipitation is evenly distributed throughout the year and averages 6 cm per year (Weedfall 965). West Virginia receives some of the most highly acidic precipitation in the United States. Mean hydrogen ion concentrations of precipitation measured at nearby Fernow Experimental Forest from 978 to 99 were 7.58E-05 to 4.90E-05 (Adams et al. 994). The Blackwater River is influenced by several underlying geologic groups, the Pottsville, Mauch Chuck, Greenbrier, and Price (Fortney 975). The resistant sandstone rocks of the Pottsville Group form persistent mountain rims protecting the easily erodable underlying Mauch Chunk, and Greenbrier groups below (Fortney 975). In Canaan Valley these layers are exposed giving the Blackwater River its stained color and its name from organic acids from the wetlands mixing with iron oxide leached from the Mauch Chunk formation (Fortney 975, West Virginia Division of Natural Resources 000). Below the Greenbrier Group, an important source of alkalinity for the Blackwater River, is the more resistant layer of the Price Group (Fortney 975, Kozar 996). HISTORICAL INFLUENCES Logging began in Canaan Valley in the late 800s and continued until the 90s, clearcutting most of the virgin timber, primarily red spruce (Fansler 96, Fortney 975, Fortney 99). Prior to logging, the water quality of the Blackwater River was good, given records of an excellent brook trout (Salvelinus fontinalis) fishery (Kennedy 85). However, following the extensive timbering of the Valley, fires consumed the leftover logging slash, and also the organic soils removing the soil mantle in drier areas (Fansler 96, U. S. Fish and Wildlife Service 979). After the destruction of the forest, much of the cleared land was put into agriculture use

10 Smith et al. 4 and used for livestock grazing but was not sustainable, consequently the land has regenerated back into northern hardwood forests (Fortney 975, Fortney 99). Coal mining became a significant industry in the late 890s (Fansler 96). The early mining activity was highly detrimental to the water quality of the watershed. As early as 99, 8 coal mines were found to be discharging about 5,00 kiloliters of water per day with an average hydrogen ion concentration of.58e-0 into the Blackwater River drainage (Carpenter and Herndon 99). Coal mining continued to be an important industry in Tucker County peaking in 95 but eventually diminished in importance (Fansler 96). In our study area one tributary, Beaver Creek, is still highly polluted from both strip and deep mines (Phares 97, Scott and Bennett 98). Development of Canaan Valley for recreation has increased in recent history. Because of its proximity to large eastern population centers Canaan Valley is a popular tourist attraction with over million people visiting Canaan Valley each year (Michael 00). Since limestone treatment of acid mine drainage from Beaver Creek began in 994 (West Virginia Division of Natural Resources 000) the Blackwater downstream of Davis has developed into a popular trout fishery. The possibility of future development has caused some concern over the quality of the water in the Blackwater watershed. One constraint on growth is no centralized wastewatertreatment facility in the Valley (Waldron and Wiley 996). Domestic wastes are treated in septic systems or small package plants that discharge directly into the Blackwater River or its tributaries (Waldron and Wiley 996, McCabe 998). Increased discharge of sewage effluent is a concern because the Blackwater River has been cited for not meeting the dissolved oxygen

11 Smith et al. 5 standard required by the Environmental Protection Agency (McCabe 998) and may not be able to assimilate more sewage without a decrease in oxygen available for aquatic life. INFLUENCES ON WATER QUALITY PARAMETERS Hydrogen ion concentration, a measure of the acidity of a stream, is generally determined in the field. Acidity similar to hydrogen ion concentrations is a measure of the amount of acid producing ions in a sample and is determined in a laboratory setting. Inputs of acidity to the Blackwater River come from acid rain, organic acids from wetlands (Kozar 996, Waldron and Wiley 996), and acid mine drainage (Phares 97). Additional acid increases the hydrogen ion concentration of a stream unless a stream contains enough alkalinity to neutralize the effects of the acid. Alkalinity is a measure of the buffering capacity of a stream. A buffer allows a stream to maintain approximately the same hydrogen ion concentration as more acid is added. The amount of alkalinity in a stream is most strongly dependent the amount of calcium a stream contains. Hardness is a measure of the amount of calcium and magnesium available as free ions in a stream. The source of calcium for the Blackwater River watershed is the underlying Greenbrier limestone formation (Welsh and Perry 997). Conductivity, unlike alkalinity, is a measure of the total dissolved ions in a solution and is performed in the field. Dissolved solids is a measure of the total dissolved solids similar to conductivity but is performed in the laboratory. Dissolved oxygen (DO) is a measure of the amount of oxygen dissolved in solution in a stream. DO diffuses from the atmosphere into the stream until it reaches a saturation point. Warmer water has a lower saturation point for DO than cooler water. Water that is flowing at higher velocities can hold more DO than slower water (Waldron and Wiley 996). DO is utilized in the processes of respiration and decomposition. Levels of DO must be high enough to

12 Smith et al. 6 support the health and well being of aquatic organisms or species may become stressed or disappear from a stream. Precipitation is likely an important source of sulfate in the Blackwater River drainage as the concentrations of sulfate are similar in precipitation and surface water (Kozar 996, McCabe 998). The most likely source of iron is leached minerals from the bedrock (Kozar 996). The acid mine drainage from Beaver Creek has been shown to be a source of both iron and sulfate (Phares 97). Fecal coliform bacteria is a measure of the number of colonies counted per 00 milliliter of water sampled. The presence of fecal bacteria in a stream indicates that the water has been contaminated with the feces of warm-blooded animals, which may include human waste (Waldron and Wiley 996). There are fifteen wastewater treatment plants operating in Canaan Valley and with the exception of an aerated lagoon, all are package plants (McCabe 998). Most facilities in the Valley release treated wastewater into polishing ponds that discharge by overflowing to dilute the wastes before they enter the Blackwater River (Waldron and Wiley 996). OBJECTIVES Our study examined changes in the water quality from and flow from of the Blackwater River at sites in the Blackwater River watershed, and considered possible causes of these changes. Our analysis used the information theoretic method (Burnham and Anderson 998) and a multiple working hypothesis approach (Chamberlin 965). Models were based on historic and present land use in the Valley. Due to the relative newness of this approach we chose in the final chapter to assess the data with a more traditional seasonal Kendall

13 Smith et al. 7 test (Hirsh et al. 98, Hirsh and Slack 984) to determine what differences could be found between the results of the methods. LITERATURE CITED ADAMS, M. B., J. N. KOCHENDERFER, F. WOOD, T. R. ANGRADI, AND P. EDWARDS Forty years of hydrometeorological data from Fernow Experimental Forest, West Virginia. U. S. Forest Service General Technical Report. NE-84. BURNHAM, H. P., AND D. R. ANDERSON Model selection and inference: a practical information-theoretic approach. Springer-Verlag, New York, New York. CARPENTER, L. V. AND L. K. HERNDON. 99. Report on pollution survey of Cheat River basin. State Water Commission. CHAMBERLIN, T. C. 965 (890). The method of multiple working hypotheses. Science 48: (Reprint of 890 paper in Science). FANSLER, H. F. 96. History of Tucker County. McClain Printing Company, Parsons, West Virginia, USA. FORTNEY, R. H A vegetation survey of Canaan Valley, West Virginia. Ph.D. dissertation, West Virginia University, Morgantown, West Virginia. FORTNEY, R. H. 99. Canaan Valley An area of special interest within the upland forest region. Pages in S. L. Stephenson, editor. Upland forests of West Virginia, McClain Print Company, Parsons, West Virginia, USA. HIRSH, R. M., J. R. SLACK, AND R. A. SMITH. 98. Techniques of trend analysis for monthly water quality data. Water Resources Research 8():07-. HIRSH, R. M. AND J. R. SLACK A nonparametric trend test for seasonal data with serial dependence. Water Resources Research 0(6): KENNEDY, P. P. 85. The Blackwater Chronicle A narrative of an expedition in to the land of Canaan in Randolph County, Virginia. Redfield Publishing, New York, New York, USA. Reprinted 978, McClain Printing Company, Parsons, West Virginia, USA. KOZAR, M. D Geohydrology and ground-water quality of southern Canaan Valley, Tucker County, West Virginia. U. S. Geological Survey Water Resources Investigations Report MCCABE, W. M Total maximum daily load, upper Blackwater River, West Virginia. Established by the U.S. Environmental Protection Agency Region III and developed in

14 Smith et al. 8 cooperation with the West Virginia Division of Environmental Protection. U.S. Environmental Protection Agency, Philadelphia, Pennsylvania, USA. MICHAEL, E. D. 00. A Valley Called Canaan: First Edition. McClain Printing Company. Parsons, West Virginia, USA. PHARES, D. P. 97. Sources of AMD in the Blackwater River watershed with recommended reclamation procedures. West Virginia Department of Natural Resources, Division of Wildlife Resources, Elkins, West Virginia, USA. SCOTT, R. B. AND L. BENNETT. 98. Estimated cost for abatement of abandoned mine drainage on the Cheat River. West Virginia Department of Natural Resources. Elkins, West Virginia, USA. U. S. FISH AND WILDLIFE SERVICE Final Environmental Impact Statement, acquisition of lands for the Canaan Valley National Wildlife Refuge West Virginia. Department of the Interior. March 0, 979. WALDRON, M. C., AND J. B. WILEY 996. Water quality and processes affecting dissolved oxygen concentratio ns in the Blackwater River, Canaan Valley, West Virginia. Water- Resources Investigations Report U.S. Geological Survey, Charleston, West Virginia, USA. WELSH, S. A., AND S. A. PERRY Acidification and Fish Occurrence in the Upper Cheat River Drainage, West Virginia. Journal of the American Water Resources Association. :4-49. WEST VIRGINIA DIVISION OF NATURAL RESOURCES Blackwater River Limestone Treatment of AMD. Report submitted to West Virginia Division of Environmental Protection. Wildlife Resources Section, Elkins, West Virginia, USA. WEEDFALL, R. O. AND W. H. DICKERSON The Climate of the Canaan Valley and Blackwater Falls State Park, West Virginia. West Virginia University Water Research Institute Report 4.

15 Smith et al. 9 WATER QUALITY TRENDS (980 99) IN THE BLACKWATER RIVER WATERSHED, WEST VIRGINIA By Jessica M. Smith West Virginia Cooperative Fish and Wildlife Research Unit, West Virginia University Morgantown, WV 6506 Stuart A. Welsh U.S. Geological Survey, West Virginia Cooperative Fish and Wildlife Research Unit, Morgantown, WV 6506 James T. Anderson West Virginia University Division of Forestry Morgantown, WV 6506 Ronald H. Fortney West Virginia University Department of Civil and Environmental Engineering Morgantown, WV 6506

16 Smith et al. 0 September 4, 00 Stuart A. Welsh U.S. Geological Survey, West Virginia Cooperative Fish and Wildlife Research Unit Morgantown, WV ; swelsh@wvu.edu RH: Blackwater River WQ Trends. Smith et. al. WATER QUALITY TRENDS (980 99) IN THE BLACKWATER RIVER WATERSHED, WEST VIRGINIA JESSICA M. SMITH, West Virginia Cooperative Fish and Wildlife Research Unit, West Virginia University, Morgantown, WV 6506, USA STUART A. WELSH, U.S. Geological Survey, West Virginia Cooperative Fish and Wildlife Research Unit, Morgantown, WV 6506, USA JAMES T. ANDERSON, West Virginia University, Division of Forestry, Morgantown, WV 6506, USA RONALD H. FORTNEY, West Virginia University, Department of Civil and Environmental Engineering, Morgantown, WV 6506, USA Abstract: An understanding of historic and current water quality is needed to manage and improve aquatic communities within the Blackwater River watershed, West Virginia. The Blackwater River, historically an excellent brook trout (Salvelinus fontinalis) fishery, has been affected by logging, coal mining, off road vehicle activities, and land development. Trends in water quality data from sites in the Blackwater River watershed were examined for a 4-year period (980 99) using information-theoretic methods. For most sites (except Beaver Creek), decreasing trends in acidity and increasing trends in alkalinity, conductivity, and hardness were consistent with decreases in hydrogen ion concentration. Water quality trends for Beaver Creek were typically inconsistent with those of other sites within the drainage, and reflect previous

17 Smith et al. mining influences. Dissolved oxygen trended downward possibly due to natural conditions, but remained above biological thresholds. Despite trends supported by the data, water quality changed only slightly within the Blackwater watershed from 980 to 99, possibly owing to relatively minimal changes in development and landuse during this time period. These data have the greatest potential as a baseline for future water quality assessments. Keywords: Blackwater River watershed, Canaan Valley, water quality trends The Blackwater River experienced large changes over the last hundred years. According to a pre-settlement account by Kennedy (85), the Blackwater River watershed supported an excellent brook trout (Salvelinus fontinalis) fishery. However, logging and repeated burning within the watershed during late 800s and early 900s (Michael 00) caused wider and shallower stream channels, increased siltation and summer temperatures, decreased watershed storage capacity, and losses of buffering capacity (Zurbuch 96). Coal mining during the first half of the twentieth century led to acid mine drainage (AMD) and degraded water quality of Beaver Creek and the Blackwater River below the confluence of Beaver Creek (Phares 97, U.S. Environmental Protection Agency 97). In recent years, recreational activities have increased within the watershed. The use of off-road vehicles (ORVs), although banned from many areas within the watershed, occurs commonly, and previously included the Blackwater 00 cross-country motorcross race (975 99) which degraded vegetation and increased sedimentation and fecal coliform (Hudgins 99, U.S. Environmental Protection Agency 994). Other common recreational activities include bird watching, camping, fishing, golfing, horseback riding, hunting, hiking, mountain biking, and skiing (Hudgins 99, Waldron and Wiley 996). Most of the recreational activities within the Blackwater watershed have minimal environmental impacts, but cumulative effects can result

18 Smith et al. from a large number of visitors. Canaan Valley in the upper Blackwater watershed attracts over million visitors each year (Hudgins 99). Without a centralized wastewater-treatment facility within the Blackwater watershed, septic systems or small package plants treat domestic wastes (Waldron and Wiley 996), and package plants discharge directly into the Blackwater River or its tributaries (McCabe 998). The microbial water quality of rivers, often indicated with fecal coliform counts, is degraded by sewage effluent. Further development within the Blackwater watershed will likely increase sewage effluents and lead to lower levels of dissolved oxygen in the Blackwater River. Additionally, fecal effluents from wildlife may degrade water quality of the Blackwater River (Waldron and Wiley 996), given large population sizes of whitetailed deer (Odocoileus virginianus) and Canada geese (Branta canadensis). Land development for tourism and residential purposes in Canaan Valley increased dramatically during the 970s, with a slower rate of increase during the 980s and less activity during the early 990s, particularly during economic recession from 989 to 99. Herein we examine monthly water quality data collected from sites during Land development and previous land use practices (as described above) undoubtedly influenced water quality of the Blackwater River. The time series, however, occurred after major developments within the 970s, and before an increased developmental period in recent years. Our overall objective was to examine water quality data for trends during METHODS The Blackwater River begins on Canaan Mountain, flows through the Monongahela National Forest, the Canaan Valley National Wildlife Refuge, and Blackwater Falls State Park. Canaan Valley, the highest valley of its size east of the Rocky Mountains (McCabe 998),

19 Smith et al. contains the headwaters of the Blackwater River and the largest freshwater wetland (,8 ha, U.S. Environmental Protection Agency 994) in the central and southern Appalachians (Hudgins 99). The river flows 47 km, drops 457 m, and joins the Dry Fork at Hendricks (Phares 97). The dark reddish-brown color of the Blackwater River is produced by tannic acid from wetland vegetation and iron oxide from sedimentary deposits (West Virginia Division of Natural Resources 000). Water from the Blackwater River is generally soft and low in alkalinity and dissolved solids (Waldron and Wiley 996), and is influenced by several geologies, Conemaugh, Greenbrier, Mauch Chunk, Price, and Pottsville (Fig., Waldron and Wiley 996). During , the Allegheny Power Company collected water quality data from the following 5 mainstem sites and 7 tributaries of the Blackwater River watershed as baseline data for a proposed hydropower dam; () Blackwater River near Davis, WV, at the U.S. Geological Service (USGS) gauging station, () Blackwater River,,000 m downstream from mouth of Yellow Creek, () Blackwater River at Camp Seventy, river kilometers (rkm) downstream from mouth of Little Blackwater River, (4) Blackwater River.6 rkm upstream from mouth of Little Blackwater River, (5) Beaver Creek at bridge near Davis, WV, 0 m upstream from mouth, (6) Yellow Creek at culvert, 90 m upstream from mouth, (7) Little Blackwater River near Camp Seventy-two, (8) Glade Run,. rkm upstream from mouth, (9) Sand Run at bridge,. rkm upstream from mouth, (0) Blackwater River at bridge, 40 m downstream from mouth of Yoakum Run, () North Branch at bridge in Cortland, WV, () Unnamed tributary to North Branch, Route, South of Mirror Lake (Fig. ). We examined unadjusted or flow-adjusted trends of 0 water quality parameters; acidity, alkalinity, conductivity, dissolved oxygen (DO), dissolved solids, fecal coliform, hardness, iron, ph (hydrogen ion concentration, H + ), and sulfate. Flow, H +, and conductivity were determined in the field. All other water quality parameters

20 Smith et al. 4 were determined through laboratory analysis. Two years (978 and 979) were excluded from the time series because of changes in methods of water quality measurements. We reduced seasonal variation by conducting separate analyses of seasonal periods. The first set of analyses included a time series of data from summer months (July, August, and September), whereas the second set included spring months (March, April, and May). This seasonal separation also reduced flow-related variation by separate analyses of periods of low (summer) and high (spring) stream flows. We fit linear, log-linear, inverse, and quadratic models to determine a relationship between stream flow and water quality data to further reduce variation in water quality variables (Crawford et al. 98). The R values of the quadratic and log-linear models were comparable and higher than other models, but only indicated a flow relationship for 4 parameters (conductivity, hardness, dissolved solids, and alkalinity). Flowadjustments for these 4 constituents were based on the log-linear model (except for sites without flow data). Data analyses were based on Kullback-Leibler information and likelihood theory (Burnham and Anderson 998) and a multiple working hypotheses approach as suggested by Chamberlin (965). A set of candidate models was selected a priori based on careful consideration of land use changes and anthropogenic impacts to Canaan Valley during 980 through 99. The first hypothesis (hereafter called the land use model) reflects a positive or negative trend in water quality constituents from 980 to 989 and no trend for the remainder of the time series (990 through 99). This model (based on land use history) reflects an increase in development during the first part of the time series followed by reduced development. The second hypothesis (hereafter called the monotonic trend model) reflects a positive or negative trend throughout the entire time series from 980 to 99. The final hypothesis (referred to as

21 Smith et al. 5 the no trend model) indicates relatively no change across the time series and is a regression model with zero slope. Candidate models were fit to the data using SAS (PROC REG; Littell et al. 00), and the best approximating model was selected based on a second order (small sample size) adjustment to Akaike s information criterion (AICc; Burnham and Anderson 998), ( ( θˆ ) K(K + ) AICc = - log l + K +, (n - K -) where log ( ( θˆ ) = - n/ log ( σˆ ) l, σ ˆ = RSS / n (RSS is the residual sum of squares), K = number of model parameters, and n = sample size. The sign (+ or -) of the regression slope indicated direction of trend, whereas the likelihood of the trend was determined by comparing Akaike model weights (as described below). The AICc values were rescaled as simple differences, where Then the likelihood of model i, given the data, is and normalized to sum to, as i = AICci - minaic c. ( M ) exp( ) l, i x = i w i = R r= exp ( ) exp ( ) i i. The w i values can be interpreted as probabilities (i.e., evidence ratios), where the relative likelihood of model i versus model j is w i /w j. For example, given model weights of 0.9 for the monotonic trend model and 0. for the no trend model, then the monotonic trend model is 9 times more likely than the no trend model. This is a strength of evidence approach that

22 Smith et al. 6 allows one to determine the model (i.e., hypothesis) that is supported by the data (Anderson et al. 000). Support for the no trend model does not mean no variation exists for a water quality constituent across the time series, but suggests that year-to-year variation is small relative to information within the sample data (Burnham and Anderson 00). The total monthly precipitation (mm) between May 9 and August 990 was analyzed for temporal changes using information theoretic methods. Precipitation data prior to 945 were primarily used from the National Oceanographic and Atmospheric Administration (NOAA) weather station at Parsons, West Virginia with missing values filled in with precipitation data from the NOAA weather station at Elkins, West Virginia and data after 945 the data primarily obtained from the weather station in Canaan Valley. The analysis compared a monotonic trend to a no trend model. Flow data from the Blackwater River at the USGS gaging station at Davis also were analyzed for changes using the monthly mean flows (feet per second) from May 9 (when recording began) through August 000. All flow data were left in feet per second (cfs) to be comparable with USGS gaging data. The monotonic trend, no-trend models and additional models were fit to the flow data. One model, a land use model, is characterized by no trend until 970 followed by a positive or negative trend thereafter. This represents changes in land use due to the economic development of the valley. The second model (hereafter called the beaver model) reflects a positive or negative flow change after the reintroduction of beavers (castor canadensis) in 95 (Bailey 954).

23 Smith et al. 7 RESULTS Two hundred forty time series (comprised of 0 water quality variables at sites for a spring and summer series) were examined for trends. We provide evidence ratios for 55 water quality trends (summed across sites and seasons; Table ), where 40 data series fit the trend model, fit the land use model, and supported both trend and land use models. Trends in unadjusted and flow-adjusted data were typically consistent, but flow-adjusted trends occurred in cases when unadjusted data did not support a trend. Trends in flow, however, were unsupported by spring and summer time series from In general, negative trends occurred for DO, acidity, H +, iron, and sulfate, whereas positive trends occurred for conductivity, alkalinity, and hardness. Support for trends (based on evidence ratios) differed between spring and summer seasons for several water quality constituents. Strongest support for negative trends of acidity, iron, and DO occurred primarily for the summer time series. Negative trends in H + typically received strongest support for spring data. Seasonal patterns among sites were not observed for trends of sulfate, conductivity, alkalinity, and hardness. Trends of conductivity, hardness, and dissolved solids for Beaver Creek (a mine impacted watershed) were inconsistent with those of other sites. Negative trends of conductivity occurred for summer data of Beaver Creek, with stronger support for flow-adjusted data. Flow-adjusted spring data from Beaver Creek supported a negative trend of hardness. Trends in dissolved solids received strong support only for Beaver Creek, where support was strongest for negative trends for the flow-adjusted spring and summer time series. Negative trends of conductivity, hardness, and dissolved solids for Beaver Creek were not reflected in trends of Blackwater River (at Davis) below the confluence of Beaver Creek.

24 Smith et al. 8 Trends in precipitation were not supported for the time series (Appendix II); therefore, flow data from were not adjusted for precipitation. This is consistent with precipitation data (95 990) at the U. S. Forest Service Fernow Experimental Forest in nearby Parsons, West Virginia, in which amount of measured precipitation remained approximately the same for the time period (Adams et al. 994). An upward trend for the monotonic trend model was found in flow data during the spring season from (Table ); however, all the trends in flow were of a relatively small magnitude. None of the other models considered in the flow analysis had high enough evidence ratios to be considered supported by the data. DISCUSSION Water quality trends during were not attributable exclusively to specific influences or land use changes in the watershed. We were unable to model for many land use changes because most dramatic changes predated the time series, such as timbering, mining, acidic precipitation, anthropogenic pollution, dams following beaver introductions (Bailey 954), and recreational use and development. Previous and ongoing events (including the list above) probably influenced water quality during the time series, as well as motorcross races and development. Many of these land uses synergistically influence water quality within the Blackwater drainage, and causal factors are difficult to separate. Only land use model was biologically-reasonable given our knowledge of events within Blackwater watershed during , but this model was rarely supported by the data. Low Akaike weights for the land use model, particularly at sites near developed areas within Canaan Valley, probably reflect the relatively slow increase in development during the 980s.

25 Smith et al. 9 Bedrock geology, a well-documented influence on water quality (Bricker and Rice 989, Welsh and Perry 997), differs geographically within the Blackwater River watershed, including Conemaugh, Greenbrier limestone, Mauch Chunk, Price, and Pottsville. Positive trends in conductivity occurred primarily in streams influenced by Greenbrier limestone. Support for positive trends in alkalinity and hardness was also strongest at sites downstream of Greenbrier limestone, but this support was less than that found for conductivity. Pottsville bedrock (within Yellow Creek watershed and upper Beaver Creek) has low buffering capacity (Welsh and Perry 997), and likely influenced the negative trends in alkalinity of Yellow Creek. Multiple bedrock types influenced most sites, such as Little Blackwater, Sand Run, Glade Run, and the mainstem Blackwater River, and prevented inference of geology-based trends. Trends from Beaver Creek were often inconsistent with those of other sites owing possibly to annual variation in AMD production. Negative trends (spring and summer) in H + at the Beaver Creek site were supported with large evidence ratios. Strong support for decreases in dissolved solids, sulfate, and iron in Beaver Creek may be linked to reduction in H +. Negative trends for conductivity at Beaver Creek were likely associated with the decrease in dissolved solids. Beaver Creek is typically more affected by AMD at low flows (summer) due to a uniform amount of acid production (Phares 97). The decreasing trend in acidity received highest support for summer data, and likely influenced decreasing trends of conductivity and sulfate. The decrease in H + during was unexpected given acidic precipitation within the region (Baker et al. 990), but this trend occurred within a narrow range of ph values. Streams within Blackwater drainage were limed recently to increase ph, but we are unaware of mitigation efforts before or during the time series. Because H + typically increases

26 Smith et al. 0 from snowmelt (Sharpe et al. 984), and strongest support for negative trends in H + occurred for the time series of spring months, we explored trends in precipitation and air temperature within the time series during winter months (December, January, and February). Data did not support a trend for precipitation, but did support a slight upward trend in temperature. Consequently, we hypothesize that the higher winter temperatures causing earlier spring snowmelt in the latter part of the time series influenced negative trends in H + during Negative trends of DO received highest support for the summer time series, but all values were above biological threshold levels for regional fauna. Negative trends of DO occurred in watersheds with and without development, and likely resulted from annual changes in natural processes, such as amounts of aquatic vegetation, decomposition of wetland plants, canopy cover influences on stream temperatures, and reduced flow due to beaver dams. Fecal coliform, another possible influence on DO, increased at mainstem sites near Davis and Camp Seventy. Trends of fecal coliform could result from human or wildlife sources, but were not observed at sites near developed areas. Given the likelihood of synergistic influences, we do not speculate specific causes for trends of DO and fecal coliform. Values of DO and fecal coliform were generally within a narrow range, and are more useful as baseline data for future assessment. MANAGEMENT IMPLICATIONS Future development, population growth (human and wildlife), and disturbance of mineimpacted areas are expected within the Blackwater River watershed. An understanding of previous water quality (as reported herein) will be useful for current and future management of aquatic resources. The increase in flow of the Blackwater River although small in scale is encouraging as it means that development has not decreased the flow of the Blackwater thus far. Most water quality trends occurred within a narrow range of water quality values, and do not

27 Smith et al. support large improvements or degradation of water quality within the time series. Because development and other land use changes within the watershed were relatively minimal during , the data reported herein have the greatest potential as a baseline for future water quality assessments. A current assessment of water quality within the Blackwater River is needed, and we suggest long-term monitoring of sites (representative of the watershed). Future analyses of recent data with those from will provide additional insights into changes of water quality within the Blackwater River watershed, and will allow managers to make informed decisions based on current and previous conditions. ACKNOWLEDGMENTS The Canaan Valley Institute provided research funds. Many assisted and contributed to our efforts including, C. A. Anderson, D. B. Chambers, B. H. Collins, L. Cooper, E. D. Michael, J. S. Rodd, B. S. Smith, P. K. Worden, and P. E. Zurbuch. This is manuscript number 800 of the West Virginia University Agricultural and Forestry Experiment Station. LITERATURE CITED ANDERSON, D. R., K. P. BURNHAM, AND W. L. THOMPSON Null hypothesis testing: problems, prevalence, and an alternative. Journal of Wildlife Management 64:9-9. BAILEY, R. W Status of beaver in West Virginia. Journal of Wildlife Management 8: BAKER, L.A., P.R. KAUFMANN, A.T. HERLIHY, AND J.M. EILERS Current status of surface water acid-base chemistry, National Acid Precipitation Assessment Program, State of Science and Technology, Volume II, Washington D.C., USA. BRICKER, O.P. AND K.C. RICE Acidic deposition to streams: a geology-based method predicts their sensitivity. Environmental Science and Technology : BURNHAM, K. P. AND D. R. ANDERSON. 00. Model selection and multimodel inference: a practical information-theoretic approach. Second Edition. Springer-Verlag, New York, New York, USA.

28 Smith et al. CHAMBERLIN, T. C. 965 (890). The method of multiple working hypotheses. Science 48: (Reprint of 890 paper in Science). CRAWFORD, C. G., J. R. SLACK, AND R. M. HIRSCH. 98. Tests for trends in waterquality data using the statistical analysis system: U.S. Geological Survey Open-File Report HUDGINS, J. E. 99. Off-road use and impact in Canaan Valley, Tucker County, West Virginia. Special Project Report 9-, West Virginia Field Office, U.S. Fish and Wildlife Service, Elkins, West Virginia, USA. KENNEDY, P. P. 85. The Blackwater Chronicle A narrative of an expedition in to the land of Canaan in Randolph County, Virginia. Redfield Publishing, New York, NY. Reprinted 978, McClain Printing Company, Parsons, West Virginia, USA. LITTELL, R.C., W.W. STROUP, AND R.J. FREUND. 00. SAS for linear models, fourth edition, SAS Institute Inc., Cary, North Carolina, USA. MCCABE, W. M Total maximum daily load, upper Blackwater River, West Virginia. Established by the U.S. Environmental Protection Agency Region III and developed in cooperation with the West Virginia Division of Environmental Protection. U.S. Environmental Protection Agency, Philadelphia, Pennsylvania, USA. MICHAEL, E. D. 00. A valley called Canaan: First Edition. McClain Printing Company. Parsons, West Virginia, USA. PHARES, D. P. 97. Sources of AMD in the Blackwater River watershed with recommended reclamation procedures. West Virginia Department of Natural Resources, Division of Wildlife Resources, Elkins, West Virginia, USA. SHARPE, W.E., D.R. DEWALLE, R.T. LEIBFRIED, R.S. DINICOLA, W.G. KIMMEL, AND L.S. SHERWIN Causes of acidification of four streams on Laurel Hill in southwestern Pennsylvania. Journal of Environmental Quality :69-6. U.S. ENVIRONMENTAL PROTECTION AGENCY. 97. Summary report Monongahela River mine drainage remedial project. Division of Field Investigations Cincinnati Center, Cincinnati, Ohio, USA. U.S. ENVIRONMENTAL PROTECTION AGENCY Short-term effects of off-road vehicle activity on the quality of the Blackwater River above Davis, West Virginia. E.P.A. Region III, Philadelphia, Pennsylvania, USA. WALDRON, M. C. AND J. B. WILEY Water quality and processes affecting dissolved oxygen concentrations in the Blackwater River, Canaan Valley, West Virginia. Water- Resources Investigations Report U.S. Geological Survey, Charleston, West Virginia, USA.

29 Smith et al. WELSH, S. A. AND S. A. PERRY Acidification and Fish Occurrence in the Upper Cheat River Drainage, West Virginia. Journal of the American Water Resources Association :4-49. WEST VIRGINIA DIVISION OF NATURAL RESOURCES Blackwater River Limestone Treatment of AMD. Report submitted to West Virginia Division of Environmental Protection. Wildlife Resources Section, Elkins, West Virginia, USA. ZURBUCH, P. E. 96. Notes on the Blackwater River fishery and water quality. West Virginia Department of Natural Resources, Division of Game and Fish, Elkins, West Virginia, USA.

30 Smith et al. 4 Table. Summary of evidence ratios supporting models of monotonic (T) or land use (L) trends of 0 water quality parameters at sites (980-99) separated by spring (March - May) and summer (July - September) seasons. The land use model fits a monotonic trend during the first part of the time series ( ) and no trend during the last 4 years (990-99). An evidence ratio of 0 indicates that the trend model is 0 times more likely than the "no trend" model. The directions (+ or -) of trend for the monotonic (T) and land use (L) trend models are given for unadjusted and flow-adjusted (F) data. A blank space indicates no support for trend, and a (*) indicates no flow data. Water Quality Blackwater Blackwater Blackwater Blackwater Parameter (at Davis) (near Yellow Cr.) (at Camp Seventy) (near L. Blackwater) Spring Summer Spring Summer Spring Summer Spring Summer Acidity - T - T -T -T/L -T / 67 4 Alkalinity + T +T +T 5 6 Alkalinity (F) + T +T * * 86 6 Conductivity + T +T +T +T +T +T Conductivity (F) + T +T +T +T +T * * Dissolved Solids +T Dissolved Solids (F) +T * * DO - T - T -T -T -T -T Fecal coliform +T/L +L +T/L 4 / / 8 Hardness +T +T/L 9 / 0 Hardness (F) +T * * 6 Hydrogen ion - L - T/L -T/L -T -T -T -T -T / / Iron - L - T -T -T/L -T -T/L -T -T / 78 8 / Sulfate - T - T - T 4 4

31 Smith et al. 5 Table. Continued. Water Quality Beaver Creek Yellow Little Glade Run Parameter Creek Blackwater Spring Summer Spring Summer Spring Summer Spring Summer Acidity - T - T -T -T -T Alkalinity -T -T 5 Alkalinity (F) -T -T * * * * 5 4 Conductivity - T +T +T + T + T +T +T Conductivity (F) - T +T +T * * * * Dissolved Solids - T - T 60 7 Dissolved Solids (F) - T - T * * * * DO - T - T -T - T - T -T Fecal coliform Hardness +T Hardness (F) - T +T * * * *. Hydrogen ion - T - T -T -T - T - T -T -T Iron - T - T -T - T -T -T.5E Sulfate - T 85

32 Smith et al. 6 Table. Continued. Water Quality Sand Run Blackwater North Branch Unnamed Parameter (near Yoakum Run) Blackwater Tributary Spring Summer Spring Summer Spring Summer Spring Summer Acidity -T - T/L - T/L -T -T 70 4 / / Alkalinity + T + T 5 8 Alkalinity (F) + T + T 4 68 Conductivity +T +T + T + T + T + T +T +T Conductivity (F) +T + T + T + T + T +T +T Dissolved Solids + T 6 Dissolved Solids (F) +T + T 6 4 DO -T - T - T -T -T Fecal coliform - T - T 7 Hardness + T + T 0 9 Hardness (F) + T + T + T Hydrogen ion -T -T - T/L - T - T - T -T/L -T 9 4.7E+8 / 4 4 / E+8 Iron -T -T - T - T - T -T Sulfate +T 7

33 Smith et al. 7 Table. Summary of model selection statistics from trend analyses of precipitation and flow from at the USGS gaging station at the Blackwater River at Davis. Data were analyzed by spring (March, April, May), summer (July, Aug. Sept.) and winter (Dec. Jan. and Feb.) seasons and include the direction of trend (Slope), model, the Akaike model weights, and evidence ratios. All evidence ratios were calculated by dividing the model by the no slope model. Constituent Slope Model Akaike weight Evidence Ratio Precipitation + Trend Winter No trend Precipitation + Trend Spring No trend Precipitation + Trend Summer No trend Trend Flow + Beaver Winter + Land use No Trend Trend Flow + Beaver Spring + Land use No Trend Trend Flow + Beaver Summer + Land use No Trend 0.8