EXPORT COEFFICIENT MODELING TO ASSESS PHOSPHORUS LOADING IN AN URBAN WATERSHED1

ABSTRACT: An export coefficient modeling approach was used to assess the influence of land use on phosphorus loading to a Southern Ontario stream. A model was constructed for the 1995–1996 water year and calibrated within ± 3 percent of the observed mean concentration of total phosphorus. It was found that runoff from urban areas contributed most to the loading of phosphorus to the stream. When the model was assessed by running it for the 1977–1978 water year, using water quality and land use data collected independently, agreement within ± 7 percent was obtained. The model was then used to forecast the impact of future urban development proposed for the watershed, in terms of phosphorus loading, and to evaluate the reduction in loading resulting from several urban best management practices (BMP). It was determined that phosphorus removal will have to be applied to all the urban runoff from the watershed to appreciably reduce stream phosphorus concentration. Of the BMP designs assessed, an infiltration pond system resulted in the greatest phosphorus load reduction, 50 percent from the 1995–1996 baseline.     

A LONG‐TERM,WATERSHED‐SCALE,EVALUATION OF THE IMPACTS OF ANIMAL WASTE BMPs ON INDICATOR BACTERIA CONCENTRATIONS1

ABSTRACT: Driven by increasing concerns about bacterial pollution from agricultural sources, states such as Virginia have initiated cost sharing programs that encourage the use of animal waste best management practices (BMPs) to control this pollution. Although a few studies have shown that waste management BMPs are effective at the field scale, their effectiveness at the watershed scale and over the long term is unknown. The focus of this research was to evaluate the effectiveness of BMPs in reducing bacterial pollution at the watershed scale and over the long term. To accomplish this goal, a 1,163 ha watershed located in the Piedmont region of Virginia was monitored over a ten‐year period. Fecal coliforms (FC) and fecal streptococci (FS) were measured as indicators of bacterial pollution. A pre‐BMP versus post‐BMP design was adopted. Major BMPs implemented were manure storage facilities, stream fencing, water troughs, and nutrient management. Seasonal Kendall trend analysis revealed a significant decreasing trend during the post‐BMP period for FC concentrations at the watershed outlet, but not at the subwatershed level. Implementation of BMPs also resulted in a significant reduction in the geometric mean of FS concentrations. FC concentrations in streamflow at the watershed outlet exceeded the Virginia primary standard 86 and 74 percent of the time during pre‐BMP and post‐BMP periods, respectively. Corresponding exceedances for the secondary standard were 50 and 41 percent. Violations decreased only slightly during the post‐BMP period. The findings of this study suggest that although BMP implementation can be expected to accomplish some improvement in water quality, BMP implementation alone may not ensure compliance with current water quality standards.     

Modeling Watershed‐Scale Impacts of Stormwater Management with Traditional versus Low Impact Development Design

Stormwater runoff and associated pollutants from urban areas in the greater Chesapeake Bay Watershed (CBW) impair local streams and downstream ecosystems, despite urbanized land comprising only 7% of the CBW area. More recently, stormwater best management practices (BMPs) have been implemented in a low impact development (LID) manner to treat stormwater runoff closer to its source. This approach included the development of a novel BMP model to compare traditional and LID design, pioneering the use of comprehensively digitized storm sewer infrastructure and BMP design connectivity with spatial patterns in a geographic information system at the watershed scale. The goal was to compare total watershed pollutant removal efficiency in two study watersheds with differing spatial patterns of BMP design (traditional and LID), by quantifying the improved water quality benefit of LID BMP design. An estimate of uncertainty was included in the modeling framework by using ranges for BMP pollutant removal efficiencies that were based on the literature. Our model, using Monte Carlo analysis, predicted that the LID watershed removed approximately 78 kg more nitrogen, 3 kg more phosphorus, and 1,592 kg more sediment per square kilometer as compared with the traditional watershed on an annual basis. Our research provides planners a valuable model to prioritize watersheds for BMP design based on model results or in optimizing BMP selection.     

DETERMINING NUTRIENT EXPORT COEFFICIENTS AND SOURCE LOADING UNCERTAINTY USING IN‐STREAM MONITORING DATA1

ABSTRACT: Over a three‐year period, flow and nutrients were monitored at 13 sites in the upper North Bosque River watershed in Texas. Drainage areas above sampling sites differed in percent of dairy waste application fields, forage fields, wood/range, and urban land area. A multiple regression approach was used to develop total phosphorus (TP) and total nitrogen (TN) export coefficients for the major land uses in these heterogeneous drainage areas. The largest export coefficients were associated with dairy waste application fields followed by urban, forage fields, and wood/range. An empirical model was then established to assess nutrient contribution by major sources using developed export coefficients and point source loadings from municipal wastewater treatment. This model was verified by comparison of estimated loadings to measured in‐stream data. Monte Carlo simulation techniques were applied to provide an uncertainty analysis for nutrient loads by source, based on the variance associated with each export coefficient. The largest sources of nutrients contributing to the upper North Bosque River were associated with dairy waste application fields and forage fields, while the greatest relative uncertainty in source contribution was associated with loadings from urban and wood/range land uses.     

Application of a Multi-Objective Optimization Method to Provide Least Cost Alternatives for NPS Pollution Control

Nonpoint source (NPS) pollutants such as phosphorus, nitrogen, sediment, and pesticides are the foremost sources of water contamination in many of the water bodies in the Midwestern agricultural watersheds. This problem is expected to increase in the future with the increasing demand to provide corn as grain or stover for biofuel production. Best management practices (BMPs) have been proven to effectively reduce the NPS pollutant loads from agricultural areas. However, in a watershed with multiple farms and multiple BMPs feasible for implementation, it becomes a daunting task to choose a right combination of BMPs that provide maximum pollution reduction for least implementation costs. Multi-objective algorithms capable of searching from a large number of solutions are required to meet the given watershed management objectives. Genetic algorithms have been the most popular optimization algorithms for the BMP selection and placement. However, previous BMP optimization models did not study pesticide which is very commonly used in corn areas. Also, with corn stover being projected as a viable alternative for biofuel production there might be unintended consequences of the reduced residue in the corn fields on water quality. Therefore, there is a need to study the impact of different levels of residue management in combination with other BMPs at a watershed scale. In this research the following BMPs were selected for placement in the watershed: (a) residue management, (b) filter strips, (c) parallel terraces, (d) contour farming, and (e) tillage. We present a novel method of combing different NPS pollutants into a single objective function, which, along with the net costs, were used as the two objective functions during optimization. In this study we used BMP tool, a database that contains the pollution reduction and cost information of different BMPs under consideration which provides pollutant loads during optimization. The BMP optimization was performed using a NSGA-II based search method. The model was tested for the selection and placement of BMPs in Wildcat Creek Watershed, a corn dominated watershed located in northcentral Indiana, to reduce nitrogen, phosphorus, sediment, and pesticide losses from the watershed. The Pareto optimal fronts (plotted as spider plots) generated between the optimized objective functions can be used to make management decisions to achieve desired water quality goals with minimum BMP implementation and maintenance cost for the watershed. Also these solutions were geographically mapped to show the locations where various BMPs should be implemented. The solutions with larger pollution reduction consisted of buffer filter strips that lead to larger pollution reduction with greater costs compared to other alternatives.     

Evaluating agricultural best management practices in tile-drained subwatersheds of the Mackinaw River, Illinois

Best management practices (BMPs) are widely promoted in agricultural watersheds as a means of improving water quality and ameliorating altered hydrology. We used a paired watershed approach to evaluate whether focused outreach could increase BMP implementation rates and whether BMPs could induce watershed-scale (4000 ha) changes in nutrients, suspended sediment concentrations, or hydrology in an agricultural watershed in central Illinois. Land use was >90% row crop agriculture with extensive subsurface tile drainage. Outreach successfully increased BMP implementation rates for grassed waterways, stream buffers, and strip-tillage within the treatment watershed, which are designed to reduce surface runoff and soil erosion. No significant changes in nitrate-nitrogen (NO-N), total phosphorus (TP), dissolved reactive phosphorus, total suspended sediment (TSS), or hydrology were observed after implementation of these BMPs over 7 yr of monitoring. Annual NO-N export (39-299 Mg) in the two watersheds was equally exported during baseflow and stormflow. Mean annual TP export was similar between the watersheds (3.8 Mg) and was greater for TSS in the treatment (1626 ± 497 Mg) than in the reference (940 ± 327 Mg) watershed. Export of TP and TSS was primarily due to stormflow (>85%). Results suggest that the BMPs established during this study were not adequate to override nutrient export from subsurface drainage tiles. Conservation planning in tile-drained agricultural watersheds will require a combination of surface-water BMPs and conservation practices that intercept and retain subsurface agricultural runoff. Our study emphasizes the need to measure conservation outcomes and not just implementation rates of conservation practices.     

Agricultural BMP Effectiveness and Dominant Hydrological Flow Paths: Concepts and a Review

We present a conceptual framework that relates agricultural best management practice (BMP) effectiveness with dominant hydrological flow paths to improve nonpoint source (NPS) pollution management. We use the framework to analyze plot, field and watershed scale published studies on BMP effectiveness to develop transferable recommendations for BMP selection and placement at the watershed scale. The framework is based on the location of the restrictive layer in the soil profile and distinguishes three hydrologic land types. Hydrologic land type A has the restrictive layer at the surface and BMPs that increase infiltration are effective. In land type B1, the surface soil has an infiltration rate greater than the prevailing precipitation intensity, but there is a shallow restrictive layer causing lateral flow and saturation excess overland flow. Few structural practices are effective for these land types, but pollutant source management plans can significantly reduce pollutant loading. Hydrologic land type B2 has deep, well‐draining soils without restrictive layers that transport pollutants to groundwater via percolation. Practices that increased pollutant residence time in the mixing layer or increased plant water uptake were found as the most effective BMPs in B2 land types. Matching BMPs to the appropriate land type allows for better targeting of hydrologically sensitive areas within a watershed, and potentially more significant reductions of NPS pollutant loading.     

Assessment of manure phosphorus export through turfgrass sod production in Erath County, Texas

A best management practice (BMP) for exporting manure phosphorus (P) in turfgrass sod from the North Bosque River (NBR) watershed in central Texas was assessed using a geographic information system (GIS). The NBR watershed has a mandate to reduce the total annual P load to the NBR by 50% as a result of total maximum daily load regulation. Since dairy waste applications to fields are identified as the major nonpoint source of P to the river, innovative BMPs, such as export of manure P in turfgrass, will be needed to achieve the 50% reduction. However, methods are needed to evaluate the feasibility of these innovative management practices prior to their implementation. A geospatial database of suitable turfgrass production sites was developed for Erath County using GIS. Erath County largely encompasses the upper portion of the NBR watershed. Information from field experiments, production practices, and ground-truthing was used to search, analyze, and verify a geospatial database developed from national and regional sources. The integration and analyses of large databases supports the search by turf producers for sites suitable for turfgrass sod production in Erath County. In addition, GIS enables researchers and regulators to estimate manure P exports and reduced P loading due to implementation of the manure export BMP on a county scale. Under optimal conditions 198,000 kg manure P yr(-1) could be used and 114,840 kg manure P yr(-1) exported from the NBR watershed through implementation of a system using dairy manure to produce turfgrass sod. This is the equivalent of the manure P applied from 10,032 dairy cows yr(-1) and exported from 5808 dairy cows yr(-1). Application of GIS to large-scale planning and decision-making transcends traditional field-scale applications in precision agriculture.     

A systematic approach for the comparative assessment of stormwater pollutant removal potentials

This paper describes the development of a methodology to theoretically assess the stormwater pollutant removal performances of structural best management practices (BMPs). The method combines the categorisation of the relative importance of the primary removal processes within 15 different BMPs with an evaluation of the ability of each process to remove a pollutant in order to generate a value representing the pollutant removal potential for each BMP. The methodology is demonstrated by applying it separately to a set of general water quality indicators (total suspended solids, biochemical and chemical oxygen demand, nitrates, phosphates and faecal coliforms) to produce a ranked list of BMP pollutant removal efficiencies. Given the limited amount of available monitoring data relating to the differential pollutant removal capabilities of BMPs, the resulting prioritization will support stakeholders in making urban drainage decisions from the perspective of pollutant removal. It can also provide inputs to existing urban hydrology models, which aim to predict the treatment performances of BMPs. The level of resilience of the proposed approach is tested using a sensitivity analysis and the limitations in terms of BMP design and application are discussed.     

MODELING FRAMEWORK FOR MANAGING COPPER RUNOFF IN URBAN WATERSHEDS1

ABSTRACT: A modeling framework was developed for managing copper runoff in urban watersheds that incorporates water quality characterization, watershed land use areas, hydrologic data, a statistical simulator, a biotic ligand binding model to characterize acute toxicity, and a statistical method for setting a watershed specific copper loading. The modeling framework is driven by export coefficients derived from water quality parameters and hydrologic inputs measured in an urban watershed's storm water system. This framework was applied to a watershed containing a copper roof built in 1992. A series of simulations was run to predict the change in receiving stream water chemistry caused by roof aging and to determine the maximum copper loading (at the 99 percent confidence level) a watershed could accept without causing acute toxicity in the receiving stream. Forecasting the amount of copper flux responsible for exceeding the assimilation capacity of a watershed can be directly related to maximum copper loadings responsible for causing toxicity in the receiving streams. The framework developed in this study can be used to evaluate copper utilization in urban watersheds.     

Assessment of a turfgrass sod best management practice on water quality in a suburban watershed

The disposal of manure on agricultural land has caused water quality concerns in many rural watersheds, sometimes requiring state environmental agencies to conduct total maximum daily load (TMDL) assessments of stream nutrients, such as nitrogen (N) and phosphorus (P). A best management practice (BMP) has been developed in response to a TMDL that mandates a 50% reduction of annual P load to the North Bosque River (NBR) in central Texas. This BMP exports composted dairy manure P through turfgrass sod from the NBR watershed to urban watersheds. The manure-grown sod releases P slowly and would not require additional P fertilizer for up to 20 years in the receiving watershed. This would eliminate P application to the sod and improve the water quality of urban streams. The soil and water assessment tool (SWAT) was used to model a typical suburban watershed that would receive the sod grown with composted dairy manure to assess water quality changes due to this BMP. The SWAT model was calibrated to simulate historical flow and estimated sediment and nutrient loading to Mary's Creek near Fort Worth, Texas. The total P stream loading to Mary's Creek was lower when manure-grown sod was transplanted instead of sod grown with inorganic fertilizers. Flow, sediment and total N yield were the same for both cases at the watershed outlet. The SWAT simulations indicated that the turfgrass BMP can be used effectively to import manure P into an urban watershed and reduce in-stream P levels when compared to sod grown with inorganic fertilizers.     

EFFECTS OF BEST MANAGEMENT PRACTICES ON FOREST STREAMWATER QUALITY IN EASTERN KENTUCKY1

ABSTRACT: Forest land managers are concerned about the effects of logging on soil erosion, streamflow, and water quality and are promoting the use of Best Management Practices (BMPs) to control impacts. To compare the effects of BMP implementation on streamwater quality, two of three small watersheds in Kentucky were harvested in 1983 and 1984, one with BMPs, the other without BMPs. There was no effect of clearcutting on stream temperatures. Streamflow increased by 17.8 cm (123 percent) on the BMP watershed during the first 17 months after cutting and by 20.6 cm (138 percent) on the Non-BMP watershed. Water yields remained significantly elevated compared to the uncut watershed 8 years after harvesting. Suspended sediment flux was 14 and 30 times higher on the BMP and Non-BMP Watersheds, respectively, than on the uncut watershed during treatment, and 4 and 6.5 times higher in the 17 months after treatment was complete. Clearcutting resulted in increased concentrations of nitrate, and other nutrients compared to the uncut watershed, and concentrations were highest on the non-BMP watershed. Recovery of biotic control over nutrient losses occurred within three years of clearcutting. The streamside buffer strip was effective in reducing the impact of clearcutting on water yield and sediment flux.     

CONSIDERATIONS IN CHOOSING THE APPROPRIATE MIX OF URBAN AND AGRICULTURAL NONPOINT POLLUTION CONTROL1

ABSTRACT: In developing strategies for nonpoint pollution control in designated 208 areas, one of the issues facing planners is the relative emphasis which should be placed upon urban versus agricultural non-point control. Five criteria which should be considered in designing an appropriate BMP strategy mix are discussed: 1) BMP cost effectiveness; 2) information and administrative cost; 3) flexibility, which relates to the cost of reversibility given substantial uncertainties; 4) associated effects, both direct and indirect; and 5) acceptability to local jurisdictions and groups. Whatever an evaluation on the basis of the first four criteria may suggest, acceptance of agricultural BMPs will be difficult to achieve, thus favoring urban oriented strategies, unless local revenue sources are developed to offer payments to farmers for BMP adoption.     

EVALUATION OF Ann AGNPS NITROGEN LOADING IN AN AGRICULTURAL WATERSHED1

ABSTRACT: Pollutants entering a water system can be very destructive to the health of that system. Best Management Practices (BMPs) are used to reduce these pollutants, but understanding the most effective practices is very difficult. Watershed models are an effective tool to aid in the decision‐making process of selecting the BMPs that are most effective in reducing the pollutant loading and are also the most cost effective. The Annualized Agricultural Nonpoint Source Pollution model (AnnAGNPS 2.0) is a technological tool that can be used to estimate watershed response to agricultural management practices. The main purpose of this paper is to test the performance of AnnAGNPS 2.0 on nitrogen loading using comparisons with measurements from the Deep Hollow watershed of the Mississippi Delta Management Systems Evaluation Area (MDMSEA) project. Previous work has demonstrated the capability of the model to simulate runoff and sediment. From sensitivity analyses in this study, initial nitrogen concentration in the soil and crop nitrogen uptake had the most impact on the nitrogen loadings. AnnAGNPS simulations of monthly nitrogen loadings are poor. However, statistical test (t‐test) showed that the predicted nitrogen loading is not significantly different from observed nitrogen loading at the 95 percent level of confidence.     

BMP IMPACTS ON WATERSHED RUNOFF,SEDIMENT, AND NUTRIENT YIELDS1

ABSTRACT: To quantify the effectiveness of best management practice (BMP) implementation on runoff, sediment, and nutrient yields from a watershed, the Nomini Creek watershed and water quality monitoring project was initiated in 1985, in Westmoreland County, Virginia. The changes in nonpoint source (NPS) loadings resulting from BMPs were evaluated by comparing selected parameters from data series obtained before, during, and after periods of BMP implementation. The results indicated that the watershed-averaged curve number, sediment, and nutrient (N and P) concentrations were reduced by approximately 5, 20, and 40 percent, respectively, due to BMP implementation. The nutrient yield model developed by Frere et al. (1980) was applied to the water quality parameters from 175 storms, but it failed to adequately describe the observed phenomena. Seasonal changes in nutrient availability factors were not consistent with field conditions, nor were they significantly different in the pm- and post-BMP periods. An extended period of monitoring, with intensive BMP implementation over a larger portion of the watershed, is required to identify BMP effectiveness.     

Cost‐Effective Placement of Best Management Practices in a Watershed: Lessons Learned from Conservation Effects Assessment Project

This article reviews the key, cross‐cutting findings concerning watershed‐scale cost‐effective placement of best management practices (BMPs) emerging from the National Institute of Food and Agriculture Conservation Effects Assessment Project (CEAP) competitive grants watershed studies. The synthesis focuses on two fundamental aspects of the cost‐effectiveness problem: (1) how to assess the location‐ and farmer‐specific costs of BMP implementation, and (2) how to decide on which BMPs need to be implemented and where within a given watershed. Major lessons learned are that (1) data availability remains a significant limiting factor in capturing within‐watershed BMP cost variability; (2) strong watershed community connections help overcome the cost estimation challenges; (3) detailing cost components facilitates the transferability of estimates to alternative locations and/or economic conditions; and (4) implicit costs vary significantly across space and farmers. Furthermore, CEAP studies showed that (5) evolutionary algorithms provide workable ways to identify cost‐effective BMP placements; (6) tradeoffs between total conservation costs and watershed‐scale cost‐effective water quality improvements are commonly large; (7) quality baseline information is essential to solving cost‐effectiveness problem; and (8) systemic and modeling uncertainties alter cost‐effective BMP placements considerably.     

An Open Source GIS‐Based Decision Support System for Watershed Evaluation of Best Management Practices

Economic costs, water quantity/quality benefits, and cost effectiveness of agricultural best management practices (BMPs) at a watershed scale are increasingly examined using integrated economic‐hydrologic models. However, these models are typically complex and not user‐friendly for examining the effects of various BMP scenarios. In this study, an open source geographic information system (GIS)‐based decision support system (DSS), named the watershed evaluation of BMPs (WEBs), was developed for creating BMP scenarios and simulating economic costs and water quantity/quality benefits at farm field, subbasin, and watershed scales. This DSS or WEBs interface integrated a farm economic model, the Soil and Water Assessment Tool (SWAT), and an optimization model within Whitebox Geospatial Analysis Tools (GAT), an open source GIS software. The DSS was applied to the 14.3‐km² Gully Creek watershed, a coastal watershed in southern Ontario, Canada that drains directly into Lake Huron. BMPs that were evaluated included conservation tillage, nutrient management, cover crop, and water and sediment control basins. In addition to assessing economic costs, water quantity/quality benefits, and cost effectiveness of BMPs, the DSS can be also used to examine prioritized BMP types/locations and corresponding economic and water quantity/quality tradeoffs in the study watershed based on environmental targets or budget constraints. Further developments of the DSS including interface transfer to other watersheds are also discussed. Editor's note : This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.     

Flood Risk Reduction from Agricultural Best Management Practices

Best management practices (BMPs) play an important role in improving impaired water quality from conventional row crop agriculture. In addition to reducing nutrient and sediment loads, BMPs such as fertilizer management, reduced tillage, and cover crops could alter the hydrology of agricultural systems and reduce surface water runoff. While attention is devoted to the water quality benefits of BMPs, the potential co‐benefits of flood loss reduction are often overlooked. This study quantifies the effects of selected commonly applied BMPs on expected flood loss to agricultural and urban areas in four Iowa watersheds. The analysis combines a watershed hydrologic model, hydraulic model outputs, and a loss estimation model to determine relationships between hydrologic changes from BMP implementations and annual economic flood loss. The results indicate a modest reduction in peak discharge and economic loss, although loss reduction is substantial when urban centers or other high‐value assets are located downstream in the watershed. Among the BMPs, wetlands, and cover crops reduce losses the most. The research demonstrates that watershed‐scale implementation of agricultural BMPs could provide benefits of flood loss reduction in addition to water quality improvements.     

Nitrogen Removal by Stormwater Management Structures: A Data Synthesis

A comprehensive synthesis of data from empirically based published studies and a widely used stormwater best management practice (BMP) database were used to assess the variability in nitrogen (N) removal performance of urban stormwater ponds, wetlands, and swales and to identify factors that may explain this variability. While the data suggest that BMPs were generally effective on average, removal efficiencies of ammonium (NH₄), nitrate (NO₃), and total nitrogen (TN) were highly variable ranging from negative (i.e., BMPs acting as sources of N) to 100%. For example, removal of NO₃ varied from (median ±1 SD) ?15 ± 49% for dry ponds, 32 ± 120% for wet ponds, 58 ± 210% for wetlands, and 37 ± 29% for swales. Across the same BMP types, TN removal was 27 ± 24%, 40 ± 31%, 61 ± 30%, and 50 ± 29%. NH₄ removal was 9 ± 36%, 29 ± 72%, 31 ± 24%, and 45 ± 34%. BMP size, age, and location explained some of the variability. For example, small and shallow ponds and wetlands were more effective than larger, deeper ones in removing N. Despite well‐known intra‐annual variation in N fluxes, most measurements have been made over short time periods using concentrations, not flow‐weighted N fluxes. Urban N export is increasing in some areas as large storms become more frequent. Thus, accounting for the full range of BMP performance under such conditions is crucial. A select number of long‐term flux‐based BMP studies that rigorously measure rainfall, hydrology, and site conditions could improve BMP implementation.     

LAND COVER AS A FRAMEWORK FOR ASSESSING RISK OF WATER POLLUTION1

ABSTRACT: A survey of numerous field studies shows that nitrogen and phosphorous export coefficients are significantly different across forest, agriculture, and urban land‐cover types. We used simulations to estimate the land‐cover composition at which there was a significant risk of nutrient loads representative of watersheds without forest cover. The results suggest that at between 20 percent and 30 percent nonforest cover, there is a 10 percent or greater chance of N or P nutrient loads being equivalent to the median values of predominantly agricultural or urban watersheds. The methods apply to environmental management for assessing the risk to increased nonpoint nutrient pollution. Interpretation of the risk measures are discussed relative to their application for a single watershed and across a region comprised of several watersheds.