Modeling the relationship between land use and surface water quality

It is widely known that watershed hydrology is dependent on many factors, including land use, climate, and soil conditions. But the relative impacts of different types of land use on the surface water are yet to be ascertained and quantified. This research attempted to use a comprehensive approach to examine the hydrologic effects of land use at both a regional and a local scale. Statistical and spatial analyses were employed to examine the statistical and spatial relationships of land use and the flow and water quality in receiving waters on a regional scale in the State of Ohio. Besides, a widely accepted watershed-based water quality assessment tool, the Better Assessment Science Integrating Point and Nonpoint Sources (BASINS), was adopted to model the plausible effects of land use on water quality in a local watershed in the East Fork Little Miami River Basin. The results from the statistical analyses revealed that there was a significant relationship between land use and in-stream water quality, especially for nitrogen, phosphorus and Fecal coliform. The geographic information systems (GIS) spatial analyses identified the watersheds that have high levels of contaminants and percentages of agricultural and urban lands. Furthermore, the hydrologic and water quality modeling showed that agricultural and impervious urban lands produced a much higher level of nitrogen and phosphorus than other land surfaces. From this research, it seems that the approach adopted in this study is comprehensive, covering both the regional and local scales. It also reveals that BASINS is a very useful and reliable tool, capable of characterizing the flow and water quality conditions for the study area under different watershed scales. With little modification, these models should be able to adapt to other watersheds or to simulate other contaminants. They also can be used to study the plausible impacts of global environmental change. In addition, the information on the hydrologic effects of land use is very useful. It can provide guidelines not only for resource managers in restoring our aquatic ecosystems, but also for local planners in devising viable and ecologically-sound watershed development plans, as well as for policy makers in evaluating alternate land management decisions.     

ESTIMATION OF STREAMFLOW,BASE FLOW,AND NITRATE‐NITROGEN LOADS IN IOWA USING MULTIPLE LINEAR REGRESSION MODELS1

Nineteen variables, including precipitation, soils and geology, land use, and basin morphologic characteristics, were evaluated to develop Iowa regression models to predict total streamflow (Q), base flow (Qb), storm flow (Qs) and base flow percentage (%Qb) in gauged and ungauged watersheds in the state. Discharge records from a set of 33 watersheds across the state for the 1980 to 2000 period were separated into Qb and Qs. Multiple linear regression found that 75.5 percent of long term average Q was explained by rainfall, sand content, and row crop percentage variables, whereas 88.5 percent of Qb was explained by these three variables plus permeability and floodplain area variables. Qs was explained by average rainfall and %Qb was a function of row crop percentage, permeability, and basin slope variables. Regional regression models developed for long term average Q and Qb were adapted to annual rainfall and showed good correlation between measured and predicted values. Combining the regression model for Q with an estimate of mean annual nitrate concentration, a map of potential nitrate loads in the state was produced. Results from this study have important implications for understanding geomorphic and land use controls on streamflow and base flow in Iowa watersheds and similar agriculture dominated watersheds in the glaciated Midwest.     

Models of total and presumed wildlife sources of fecal coliform bacteria in coastal ponds

Models that accurately predict fecal coliform bacteria (FCB) concentrations, one of the most widely used measures of estuarine water quality, are needed to improve land use decision-making. Rapidly occurring changes in coastal land uses and the influence on water quality increases the urgency of having improved decision tools. For this study, samples were collected monthly from six coastal ponds, two tidal creeks and four shallow water wells for up to 212 years. These data were used along with other measures of environmental conditions and land classes within each watershed to construct quantitative relationships between combinations of variables and both total and presumed wildlife sources of FCB. Linear regression, bootstrapping and generalized additive modeling that incorporates both linear and nonlinear terms were used. Results of repeated simultaneous sampling on the same tide stage of ponds and downstream estuarine creeks suggest that most FCB come from wildlife and that the ponds effectively remove these bacteria except immediately following heavy rainfall. Predictive models for concentrations of total and presumed wildlife bacteria are provided along with simple measures to estimate watershed boundaries. It is proposed that these tools can be used to minimize impacts on receiving water body quality. The models can be used to test alternative development approaches within coastal watersheds similar to that found in the southeastern USA coastal zone as well as to evaluate specific proposed landscape alterations.     

Test of APEX for nine forested watersheds in East Texas

Hydrologic/water quality models are increasingly used to explore management and policy alternatives for managing water quality and quantity from intensive silvicultural practices with best management practices (BMPs) in forested watersheds due to the limited number of and cost of conducting watershed monitoring. The Agricultural Policy/Environmental eXtender (APEX) model was field-tested using 6 yr of data for flow, sediment, nutrient, and herbicide losses collected from nine small (2.58 to 2.74 ha) forested watersheds located in southwest Cherokee County in East Texas. Simulated annual average stream flow for each of the nine watersheds was within +/- 7% of the corresponding observed values; simulated annual average sediment losses were within +/- 8% of measured values for eight out of nine watersheds. Nash-Sutcliffe efficiency (EF) values ranged from 0.68 to 0.94 based on annual stream flow comparison and from 0.60 to 0.99 based on annual sediment comparison. Similar to what was observed, simulated flow, sediment, organic N, and P were significantly increased on clear-cut watersheds compared with the control watersheds. APEX reasonably simulated herbicide losses, with an EF of 0.73 and R(2) of 0.74 for imazapyr, and EF of 0.65 and R(2) of 0.68 for hexazinone based on annual values. Overall, the results show that APEX was able to predict the effects of silvicultural practices with BMPs on water quantity and quality and that the model is a useful tool for simulating a variety of responses to forest conditions.     

Curve Number Derivation for Watersheds Draining Two Headwater Streams in Lower Coastal Plain South Carolina,USA

The objective of this study was to assess curve number (CN) values derived for two forested headwater catchments in the Lower Coastal Plain (LCP) of South Carolina using a three‐year period of storm event rainfall and runoff data in comparison with results obtained from CN method calculations. Derived CNs from rainfall/runoff pairs ranged from 46 to 90 for the Upper Debidue Creek (UDC) watershed and from 42 to 89 for the Watershed 80 (WS80). However, runoff generation from storm events was strongly related to water table elevation, where seasonally variable evapotranspirative wet and dry moisture conditions persist. Seasonal water table fluctuation is independent of, but can be compounded by, wet conditions that occur as a result of prior storm events, further complicating flow prediction. Runoff predictions for LCP first‐order watersheds do not compare closely to measured flow under the average moisture condition normally associated with the CN method. In this study, however, results show improvement in flow predictions using CNs adjusted for antecedent runoff conditions and based on water table position. These results indicate that adaptations of CN model parameters are required for reliable flow predictions for these LCP catchments with shallow water tables. Low gradient topography and shallow water table characteristics of LCP watersheds allow for unique hydrologic conditions that must be assessed and managed differently than higher gradient watersheds.     

WATERSHED SCALING EFFECT ON BASE FLOW NITRATE,VALLEY AND RIDGE PHYSIOGRAPHIC PROVINCE1

ABSTRACT: A study of stream base flow and NO₃‐N concentration was conducted simultaneously in 51 subwatersheds within the 116‐square‐kilometer watershed of East Mahantango Creek near Klingerstown, Pennsylvania. The study was designed to test whether measurable results of processes and observations within the smaller watersheds were similar to or transferable to a larger scale. Ancillary data on land use were available for the small and large watersheds. Although the source of land‐use data was different for the small and large watersheds, comparisons showed that the differences in the two land‐use data sources were minimal. A land use‐based water‐quality model developed for the small‐scale 7.3‐square‐kilometer watershed for a previous study accurately predicted NO₃‐N concentrations from sampling in the same watershed. The water‐quality model was modified and, using the imagery‐based land use, was found to accurately predict NO₃‐N concentrations in the subwatersheds of the large‐scale 116‐square‐kilometer watershed as well. Because the model accurately predicts NO₃‐N concentrations at small and large scales, it is likely that in second‐order streams and higher, discharge of water and NO₃‐N is dominated by flow from smaller first‐order streams, and the contribution of ground‐water discharge to higher order streams is minimal at the large scale.     

STATISTICAL LOW FLOW ESTIMATION USING GIS ANALYSIS IN HUMID MONTANE REGIONS IN PUERTO RICO1

ABSTRACT: Statistical analysis of watershed parameters derived using a Geographical Information system (GIS) was done to develop equations for estimating the 7d–10yr, 30d–10yr, and 7d–2yr low flow for watersheds in humid montane regions of Puerto Rico. Digital elevation models and land use, geology, soils, and stream network coverages were used to evaluate 21 geomorphic, 10 stream channel, 9 relief, 7 geology, 4 climate, and 2 soil parameters for each watershed. To assess which parameters should be used for further investigation, a correlation analysis was used to determine the independence and collinearity among these parameters and their relationship with low flows. Multiple regression analyses using the selected parameters were then performed to develop the statistical models of low flows. The final models were selected in the basis of the Mallow Cp statistic, the adjusted R², the Press statistic, the degree of collinearity, and an analysis of the residuals. In the final models, drainage density, the ratio of length of tributaries to the length of the main channel, the percent of drainage area with northeast aspect, and the average weighted slope of the drainage were the most significant parameters. The final models had adjusted standard errors of 58.7 percent, 59.2 percent, and 48.6 percent for the 7d–10yr, 30d–10yr, and 7d–2yr low flows respectively. For comparison, the best model based on watershed parameters that can be easily measured without a GIS had an adjusted standard error of 82.8 percent.     

Incorporating Uncertainty Into the Ranking of SPARROW Model Nutrient Yields From Mississippi/Atchafalaya River Basin Watersheds1

Abstract: Excessive loads of nutrients transported by tributary rivers have been linked to hypoxia in the Gulf of Mexico. Management efforts to reduce the hypoxic zone in the Gulf of Mexico and improve the water quality of rivers and streams could benefit from targeting nutrient reductions toward watersheds with the highest nutrient yields delivered to sensitive downstream waters. One challenge is that most conventional watershed modeling approaches (e.g., mechanistic models) used in these management decisions do not consider uncertainties in the predictions of nutrient yields and their downstream delivery. The increasing use of parameter estimation procedures to statistically estimate model coefficients, however, allows uncertainties in these predictions to be reliably estimated. Here, we use a robust bootstrapping procedure applied to the results of a previous application of the hybrid statistical/mechanistic watershed model SPARROW (Spatially Referenced Regression On Watershed attributes) to develop a statistically reliable method for identifying “high priority” areas for management, based on a probabilistic ranking of delivered nutrient yields from watersheds throughout a basin. The method is designed to be used by managers to prioritize watersheds where additional stream monitoring and evaluations of nutrient‐reduction strategies could be undertaken. Our ranking procedure incorporates information on the confidence intervals of model predictions and the corresponding watershed rankings of the delivered nutrient yields. From this quantified uncertainty, we estimate the probability that individual watersheds are among a collection of watersheds that have the highest delivered nutrient yields. We illustrate the application of the procedure to 818 eight‐digit Hydrologic Unit Code watersheds in the Mississippi/Atchafalaya River basin by identifying 150 watersheds having the highest delivered nutrient yields to the Gulf of Mexico. Highest delivered yields were from watersheds in the Central Mississippi, Ohio, and Lower Mississippi River basins. With 90% confidence, only a few watersheds can be reliably placed into the highest 150 category; however, many more watersheds can be removed from consideration as not belonging to the highest 150 category. Results from this ranking procedure provide robust information on watershed nutrient yields that can benefit management efforts to reduce nutrient loadings to downstream coastal waters, such as the Gulf of Mexico, or to local receiving streams and reservoirs.     

SEDIMENT AND WATER YIELDS FROM MANAGED FORESTS ON FLAT COASTAL PLAIN SITES1

ABSTRACT: Sediment losses and water yields were measured for five years on nine forested watersheds in the Gulf Coastal Plain of Arkansas. After one year of pretreatment measurements, three watersheds were clearcut and mechanically site prepared, three were selectively harvested, and three control watersheds were left undisturbed. Sediment losses and water yields were similar for the selectively harvested and cohtrol watersheds during all four post-treatment years. However, clearcutting with mechanical site preparation significantly increased sediment losses and water yields above levels measured on other watersheds. Increased sediment losses persisted for two years, while water yields increased for one year. Although sediment losses from clear-cutting were greater than for other treatments, actual losses averaged only 264 kg/ha and 63 kg/ha for the first and second post-treatment years, respectively. The relatively low sediment losses are attributed to the flat terrain and the relatively low flow discharge rates that typify these sites.     

GROUPWISE MODELING STUDY OF BACTERIALLY IMPAIRED WATERSHEDS IN TEXAS: CLUSTERING ANALYSIS1

ABSTRACT: Under the Clean Water Act (CWA) program, the Texas Commission on Environmental Quality (TCEQ) listed 110 stream segments in the year 2000 with pathogenic bacteria impairment. A study was conducted to evaluate the probable sources of pollution and characterize the watersheds associated with these impaired water bodies. The primary aim of the study was to group the water bodies into clusters having similar watershed characteristics and to examine the possibility of studying them as a group by choosing models for total maximum daily load (TMDL) development based on their characteristics. This approach will help to identify possible sources and determine appropriate models and hence reduce the number of required TMDL studies. This in turn will help in reducing the effort required to restore the health of the impaired water bodies in Texas. The main characteristics considered for the classification of water bodies were land use distribution within the watershed, density of stream network, average distance of land of a particular use to the closest stream, household population, density of on‐site sewage facilities (OSSFs), bacterial loading from different types of farm animals and wildlife, and average climatic conditions. The climatic data and observed instream fecal coliform bacteria concentrations were analyzed to evaluate seasonal variability of instream water quality. The grouping of water bodies was carried out using the multivariate statistical techniques of factor analysis/principal component analysis, cluster analysis, and discriminant analysis. The multivariate statistical analysis resulted in six clusters of water bodies. The main factors that differentiated the clusters were found to be bacterial contribution from farm animals and wildlife, density of OSSFs, density of households connected to public sewers, and land use distribution.     

INTEGRATING DIFFUSEINONPOINT POLLUTION CONTROL AND WATER BODY RESTORATION INTO WATERSHED MANAGEMENT1

ABSTRACT: The objective of water quality/watershed management is attainment of water quality goals specified by the Clean Water Act. The Total Maximal Daily Load (TMDL) planning process is a tool to set up watershed management. However, TMDL methodologies and concepts have several problems, including determination of Loading Capacity for only low flow critical periods that preclude consideration of wet weather sources in water quality management. Research is needed to develop watershed pollutant loading and receiving waters Loading Capacity models that will link wet and dry weather pollution loads to the probability of the exceedence of water quality standards. The long term impact of traditional Best Management Practices as well as ponds and wetlands, must be reassessed to consider long term accumulation of conservative toxic compounds. Socioeconomic research should focus on providing information on economic and social feasibility of implementation of additional controls in water quality limited watersheds.     

THE EFFECTS OF CLIMATE CHANGE ON STREAM FLOW AND NUTRIENT LOADING'

ABSTRACT: This study assesses the potential impact of climate change on stream flow and nutrient loading in six watersheds of the Susquehanna River Basin using the Generalized Watershed Loading Function (GWLF). The model was used to simulate changes in stream flow and nutrient loads under a transient climate change scenario for each watershed. Under an assumption of no change in land cover and land management, the model was used to predict monthly changes in stream flow and nutrient loads for future climate conditions. Mean annual stream flow and nutrient loads increased for most watersheds, but decreased in one watershed that was intensively cultivated. Nutrient loading slightly decreased in April and late summer for several watersheds as a result of early snowmelt and increasing evapotranspiration. Spatial and temporal variability of stream flow and nutrient loads under the transient climate scenario indicates that different approaches for future water resource management may be useful.     

Statistical Models to Predict and Assess Spatial and Temporal Low‐Flow Variability in New England Rivers and Streams

In the northern hemisphere, summer low flows are a key attribute defining both quantity and quality of aquatic habitat. I developed one set of models for New England streams/rivers predicting July/August median flows averaged across 1985–2015 as a function of weather, slope, % imperviousness, watershed storage, glacial geology, and soils. These models performed better than most United States Geological Survey models for summer flows developed at a statewide scale. I developed a second set of models predicting interannual differences in summer flows as a function of differences in air temperature, precipitation, the North Atlantic Oscillation (NAO) index, and lagged NAO. Use of difference equations eliminated the need for transformations and accounted for serial autocorrelations at lag 1. The models were used in sequence to estimate time series for monthly low flows and for two derived flow metrics (tenth percentile [Q10] and minimum 3‐in‐5 year average flows). The first metric is commonly used in assessing risk to low‐flow conditions over time, while the second has been correlated with increased probability of localized extinctions for brook trout. The flow metrics showed increasing trends across most of New England for 1985–2015. However, application of summer flow models with average and extreme climate projections to the Taunton River, Massachusetts, a sensitive watershed undergoing rapid development, projected that low‐flow metrics will decrease over the next 50 years.     

ADAPTING EXISTING MODELS TO EXAMINE EFFECTS OF AGRICULTURAL CONSERVATION PROGRAMS ON STREAM HABITAT QUALITY1

Annual expenditures by the federal government in the United States for agricultural conservation programs increased about 80 percent with passage of the 2002 Farm Bill. However, environmental benefits of these programs have not been quantified. A national project is under way to estimate the effect of conservation practices on environmental resources. The watershed models intended for use in that project are focused on water quantity and quality and have minimal habitat assessment capability. Major impairments to aquatic ecosystems in many watersheds consist of physical habitat degradation, not water quality, suggesting that current models for this national initiative do not address one of the most significant aspects of aquatic ecosystem degradation. Currently used models contain some components relevant to aquatic habitat, and this paper describes specific components that should be added to allow rudimentary stream habitat quality assessments. At least six types of variables could be examined for ecological impact: land use, streamflow, water temperature, streambed material type, large woody debris, and hydraulic conditions at base flow. All of these variables are influenced by the presence, location, and quality of buffers. Generation of stream corridor ecological or habitat quality indices might contribute to assessments of the success or failure of conservation programs. Additional research is needed to refine procedures for combining specific measures of stream habitat into ecologically meaningful indices.     

Modeling Nutrient Export From Coastal California Watersheds

Nitrate and phosphate export coefficient models were developed for coastal watersheds along the Santa Barbara Channel in central California. One approach was based on measurements of nutrient fluxes in streams from specific land use classes and included a watershed response function that scaled export up or down depending on antecedent moisture conditions. The second approach for nutrient export coefficient modeling used anthropogenic nutrient loading for land use classes and atmospheric nutrient deposition to model export. In an application of the first approach to one watershed, the nitrate and phosphate models were within 20% of measured values for most storms. When applied to another year, both nitrate and phosphate models generally performed adequately with annual, storm‐flow, and base‐flow values within 20% of measured nutrient loadings. Less satisfactory results were found when applied to neighboring watersheds with difference percentages of land use and hydrologic conditions. Application of the second approach was less successful than the first approach.     

Assessing BMP Effectiveness and Guiding BMP Planning Using Process‐Based Modeling

There is an increasing need for improved process‐based planning tools to assist watershed managers in the selection and placement of effective best management practices (BMPs). In this article, we present an approach, based on the Water Erosion Prediction Project model and a pesticide transport model, to identify dominant hydrologic flow paths and critical source areas for a variety of pollutant types. We use this approach to compare the relative impacts of BMPs on hydrology, erosion, sediment, and pollutant delivery within different landscapes. Specifically, we focus on using this approach to understand what factors promoted and/or hindered BMP effectiveness at three Conservation Effects Assessment Project watersheds: Paradise Creek Watershed in Idaho, Walnut Creek Watershed in Iowa, and Goodwater Creek Experimental Watershed in Missouri. These watersheds were first broken down into unique land types based on soil and topographic characteristics. We used the model to assess BMP effectiveness in each of these land types. This simple process‐based modeling approach provided valuable insights that are not generally available to planners when selecting and locating BMPs and helped explain fundamental reasons why long‐term improvement in water quality of these three watersheds has yet to be completely realized.     

Surface‐Water Nutrient Conditions and Sources in the United States Pacific Northwest1

Wise, Daniel R. and Henry M. Johnson, 2011. Surface‐Water Nutrient Conditions and Sources in the United States Pacific Northwest. Journal of the American Water Resources Association (JAWRA) 47(5):1110‐1135. DOI: 10.1111/j.1752‐1688.2011.00580.x Abstract: The SPAtially Referenced Regressions On Watershed attributes (SPARROW) model was used to perform an assessment of surface‐water nutrient conditions and to identify important nutrient sources in watersheds of the Pacific Northwest region of the United States (U.S.) for the year 2002. Our models included variables representing nutrient sources as well as landscape characteristics that affect nutrient delivery to streams. Annual nutrient yields were higher in watersheds on the wetter, west side of the Cascade Range compared to watersheds on the drier, east side. High nutrient enrichment (relative to the U.S. Environmental Protection Agency’s recommended nutrient criteria) was estimated in watersheds throughout the region. Forest land was generally the largest source of total nitrogen stream load and geologic material was generally the largest source of total phosphorus stream load generated within the 12,039 modeled watersheds. These results reflected the prevalence of these two natural sources and the low input from other nutrient sources across the region. However, the combined input from agriculture, point sources, and developed land, rather than natural nutrient sources, was responsible for most of the nutrient load discharged from many of the largest watersheds. Our results provided an understanding of the regional patterns in surface‐water nutrient conditions and should be useful to environmental managers in future water‐quality planning efforts.     

WATER QUALITY IN AGRICULTURAL WATERSHEDS: IMPACT OF RIPARIAN VEGETATION DURING BASE FLOW1

ABSTRACT: Water quality was monitored for 17 months during base flow periods in six agricultural watersheds to evaluate the impact of riparian vegetation on suspended solids and nutrient concentrations. In areas without riparian vegetation, both instream algal production and seasonal low flows appeared to be major determinants of suspended solids, turbidity, and phosphorus concentrations. Peak levels of all parameters were reached during the summer when flows were reduced and benthic algal production was high. Similar summer peaks were reached in streams receiving major point inputs but peaks occurred downstream from the input. Instream organic production was less important in regulating water quality in areas with riparian vegetation and permanent flows. Concentrations of suspended solids remained relatively constant, while phosphorus and turbidity increased in association with leaf fall in autumn. Intermittent flow conditions in summer increased the importance of instream organic production in controlling water quality, even when riparian vegetation was present. Efforts to improve water quality in agricultural watersheds during base flow should emphasize maintenance of riparian vegetation and stable flow conditions.     

IMPLICATIONS OF CLIMATIC VARIABILITY FOR REGULATORY LOW FLOWS IN THE SOUTH PLATTE RIVER BASIN,COLORADO1

ABSTRACT: The maximum concentration of a regulated substance that is allowed in a wastewater effluent usually is determined from the amount of dilution provided by the receiving water. Dilution flow is estimated from historical data by application of statistical criteria that define low flow conditions for regulatory purposes. Such use of historical data implies that the past is a good indicator of future conditions, at least for the duration of a discharge permit. Short records, however, introduce great uncertainty in the estimation of low flows because they are unlikely to capture events with recurrence frequencies of multiple years (e.g., ENSO events or droughts). We conducted an analysis of daily flows at several gages with long records in the South Platte River basin of Colorado. Low flows were calculated for successive time blocks of data (3‐, 5‐, 10‐, and 20‐years), and these were compared with low flows calculated for the entire period of record (> 70 years). In unregulated streams, time blocks of three or five years produce estimates of low flows that are highly variable and consistently greater than estimates derived from a longer period of record. Estimates of low flow from 10‐year blocks, although more stable, differ from the long term estimates by as much as a factor of two because of climate variation. In addition, the hydrographs of most streams in Colorado have been influenced by dams, diversions, or water transfers. These alterations to the natural flow regime shorten the record that is useful for analysis, but also tend to increase the calculated low flows. The presence of an upward trend in low flows caused by water use represents an unanticipated risk because it fails to incorporate societal response to severe drought conditions. Thus, climate variability poses a significant risk for water quality both directly, because it may not be represented adequately in the short periods of the hydrologic record that are typically used in permits, and indirectly, through its potential to cause altered use of water during time of scarcity.     

ECOSYSTEM MODELING OF A FORESTED RIVER BASIN1

ABSTRACT: A present concern in decision making processes for forest land use is the environmental effects of land use activities on water, air, and the land itself. Criteria for evaluating the magnitude and detriment of environmental impacts are not definite since it is often difficult to isolate a particular activity as the cause of a particular impact. Instead, interactions between various forest practices must be considered along with their integrated impacts. In order to provide an effective decision tool, the College of Forest Resources, University of Washington, is modeling the forest ecosystem of the Snohomish River Basin located in the Cascade Mountains of western Washington. The project consists of a general system model comprised of subsystem models dealing with product conversion processes, forest production processes, recreation supply processes, wildlife and fisheries supply processes, and the interactions of these processes with water and the atmosphere. The system model is interfaced with a computerized multiple player management game which enables land managers, manufacturing managers, and regulation agency personnel to make management decisions and respond to indications of lack of environmental control. Responses of the hydrologic system to various management decisions are simulated by the water subsystem model. The responses being considered include surface flow quantity and water quality. The model emphasizes the monitoring of non-point as well as point source impacts rather than predicting short-term hydrographs. The significance of impacts vary with land use patterns and the goals of the game player. Therefore, the model has flexible resolution and is able to predict hydrologic conditions for both large and small scale. The water subsystem model responds to management decisions by interpreting the effects of management options selected by game players for 40-acre cells within the Basin. The model then determines which streams are immediately affected, defines the watersheds contributing to these streams, and extracts from a resource data bank the information needed to define model parameters. Using these parameters and precipitation inputs, mean flow discharge on a montly and annual basis is calculated for the impactcd sub watersheds as well as 21 major watersheds of the Basin. Water quality responses predicted for these watersheds include suspended sediment concentration, temperature increases due to stream exposure, dissolved oxygen concentrations, the effects of fertilization on nitrogen content, biocide and herbicide effects, and residues from product conversion processes.