Forecasting land use change and its environmental impact at a watershed scale

Urban expansion is a major driving force altering local and regional hydrology and increasing non-point source (NPS) pollution. To explore these environmental consequences of urbanization, land use change was forecast, and long-term runoff and NPS pollution were assessed in the Muskegon River watershed, located on the eastern coast of Lake Michigan. A land use change model, LTM, and a web-based environmental impact model, L-THIA, were used in this study. The outcomes indicated the watershed would likely be subjected to impacts from urbanization on runoff and some types of NPS pollution. Urbanization will slightly or considerably increase runoff volume, depending on the development rate, slightly increase nutrient losses in runoff, but significantly increase losses of oil and grease and certain heavy metals in runoff. The spatial variation of urbanization and its impact were also evaluated at the subwatershed scale and showed subwatersheds along the coast of the lake and close to cities would have runoff and nitrogen impact. The results of this study have significant implications for urban planning and decision making in an effort to protect and remediate water and habitat quality of Muskegon Lake, which is one of Lake Michigan's Areas of Concern (AOC), and the techniques described here can be used in other areas.     

Effects of calibration on L-THIA GIS runoff and pollutant estimation

Urbanization can result in alteration of a watershed's hydrologic response and water quality. To simulate hydrologic and water quality impacts of land use changes, the Long-Term Hydrologic Impact Assessment (L-THIA) system has been used. The L-THIA system estimates pollutant loading based on direct runoff quantity and land use based pollutant coefficients. The accurate estimation of direct runoff is important in assessing water quality impacts of land use changes. An automated program was developed to calibrate the L-THIA model using the millions of curve number (CN) combinations associated with land uses and hydrologic soil groups. L-THIA calibration for the Little Eagle Creek (LEC) watershed near Indianapolis, Indiana was performed using land use data for 1991 and daily rainfall data for six months of 1991 (January 1-June 30) to minimize errors associated with use of different temporal land use data and rainfall data. For the calibration period, the Nash-Sutcliffe coefficient was 0.60 for estimated and observed direct runoff. The calibrated CN values were used for validation of the model for the same year (July 1-December 31), and the Nash-Sutcliffe coefficient was 0.60 for estimated and observed direct runoff. The Nash-Sutcliffe coefficient was 0.52 for January 1, 1991 to December 31, 1991 using uncalibrated CN values. As shown in this study, the use of better input parameters for the L-THIA model can improve accuracy. The effects on direct runoff and pollutant estimation of the calibrated CN values in the L-THIA model were investigated for the LEC. Following calibration, the estimated average annual direct runoff for the LEC watershed increased by 34%, total nitrogen by 24%, total phosphorus by 22%, and total lead by 43%. This study demonstrates that the L-THIA model should be calibrated and validated prior to application in a particular watershed to more accurately assess the effects of land use changes on hydrology and water quality.     

Long-Term Impacts of Land-Use Change on Non-Point Source Pollutant Loads for the St. Louis Metropolitan Area, USA

A land-use-change simulation model (LEAM) and a non-point-source (NPS) water quality model (L-THIA) were closely coupled as LEAMwq in order to determine the long-term implications of various degree of urbanization on NPS total nitrogen (TN), total suspended particles (TSP), and total phosphorus (TP) loads. A future land-use projection in the St. Louis metropolitan area from 2005 to 2030 using three economic growth scenarios (base, low, and high) and a long-term precipitation dataset were used to predict the mean annual surface runoff and mean annual NPS pollutant loads in the region. Results show mean annual TN increases of 0.21%, 0.13%, and 0.14% by 2030 compared to 2000 under the base, high, and low scenarios, respectively. TSP and TP showed similar trends with different magnitudes. Corresponding changes in annual mean surface runoff were shown to be lower than expected, which might be attributed to the small-scale conversion pattern of land uses. In the most dramatic change (high growth) scenario, the runoff would increase across time but at varying rates, and temporal pollutant loads would result in a more complicated pattern than in the other scenarios. This is attributed to the complex interactions between event mean concentrations of pollutants and the magnitude of changes in land-use acreages. By integrating L-THIA with LEAM, LEAMwq was found to be a useful planning tool to illustrate in a quick and simple manner how future water quality is connected to decision-making on future land-use change.     

GIS BASED LONG TERM HYDROLOGIC IMPACT EVALUATION FOR WATERSHED URBANIZATION1

ABSTRACT: To adequately manage impacts of ongoing or future land use changes in a watershed, the magnitude of their hydrologic impacts needs to be assessed. A grid based daily streamflow model was calibrated with two years of observed streamflow data, using time periods when land use data are available and verified by comparison of model predictions with observed streamflow data. Streamflow data were separated into direct runoff and baseflow to estimate the impacts of urbanization on each hydrologic component. Analysis of the ratio between direct runoff and total runoff from 30 years of simulation results and the change in these ratios with urbanization shows that estimated annual direct runoff increased from 49.2 percent (1973) to 63.1 percent (1984) and 65.0 percent (1991), indicating the effects of urbanization are greater on direct runoff than on total runoff. The direct runoff ratio also varies with annual rainfall, with dry year ratios larger than those for wet years. This suggests that the impact of urbanization on areas that are sensitive to runoff ratios, such as stream ecosystems, might be more serious during drier years than in wetter years in terms of water quality and water yield. This indicates that sustainable base‐flow is important to maintaining sound stream ecosystems.     

Modeling Agricultural Nonpoint Source Pollution Using a Geographic Information System Approach

Agricultural non-point source (NPS) pollution, primarily sediment and nutrients, is the leading source of water-quality impacts to surface waters in North America. The overall goal of this study was to develop geographic information system (GIS) protocols to facilitate the spatial and temporal modeling of changes in soils, hydrology, and land-cover change at the watershed scale. In the first part of this article, we describe the use of GIS to spatially integrate watershed scale data on soil erodibility, land use, and runoff for the assessment of potential source areas within an intensively agricultural watershed. The agricultural non-point source pollution (AGNPS) model was used in the Muddy Creek, Ontario, watershed to evaluate the effectiveness of management strategies in decreasing sediment and nutrient [phosphorus (P)] pollution. This analysis was accompanied by the measurement of water-quality parameters (dissolved oxygen, pH, hardness, alkalinity, and turbidity) as well as sediment and P loadings to the creek. Practices aimed at increasing year-round soil cover would be most effective in decreasing sediment and P losses in this watershed. In the second part of this article, we describe a method for characterizing land-cover change in a dynamic urban fringe watershed. The GIS method we developed for the Blackberry Creek, Illinois, watershed will allow us to better account for temporal changes in land use, specifically corn and soybean cover, on an annual basis and to improve on the modeling of watershed processes shown for the Muddy Creek watershed. Our model can be used at different levels of planning with minimal data preprocessing, easily accessible data, and adjustable output scales.     

Stream Nitrogen Sources Apportionment and Pollution Control Scheme Development in an Agricultural Watershed in Eastern China

A modeling system that couples a land-use-based export coefficient model, a stream nutrient transport equation, and Bayesian statistics was developed for stream nitrogen source apportionment. It divides a watershed into several sub-catchments, and then considers the major land-use categories as stream nitrogen sources in each sub-catchment. The runoff depth and stream water depth are considered as the major factors influencing delivery of nitrogen from land to downstream stream node within each sub-catchment. The nitrogen sources and delivery processes are lumped into several constant parameters that were calibrated using Bayesian statistics from commonly available stream monitoring and land-use datasets. This modeling system was successfully applied to total nitrogen (TN) pollution control scheme development for the ChangLe River watershed containing six sub-catchments and four land-use categories. The temporal (across months and years) and spatial (across sub-catchments and land-use categories) variability of nonpoint source (NPS) TN export to stream channels and delivery to the watershed outlet were assessed. After adjustment for in-stream TN retention, the time periods and watershed areas with disproportionately high-TN contributions to the stream were identified. Aimed at a target stream TN level of 2 mg L^?1, a quantitative TN pollution control scheme was further developed to determine which sub-catchments, which land-use categories in a sub-catchment, which time periods, and how large of NPS TN export reduction were required. This modeling system provides a powerful tool for stream nitrogen source apportionment and pollution control scheme development at the watershed scale and has only limited data requirements.     

Modeling Watershed‐Wide Bioretention Stormwater Retrofits to Achieve Thermal Pollution Mitigation Goals

Stream ecosystems are increasingly at risk for thermal impairment as urbanization intensifies, resulting in more heated runoff from impervious cover that is less likely to be cooled naturally. While several best management practices, including bioretention filters, have been able to reduce thermal pollution, success has been limited. The extent of thermal mitigation required to prevent ecological damage remains unknown. A calibrated runoff temperature model of a case study watershed in Blacksburg, VA was developed to determine the cumulative treatment volume of bioretention filters required to reduce thermal impacts caused by runoff from development in the watershed to regulated biologically acceptable levels. A future build out scenario of the study watershed was also analyzed. Results from this study established that runoff thermal pollution cannot be fully reduced to goal thresholds during all storms using bioretention filter retrofits. While retrofitting significantly decreased temperatures and heat exports relative to the controls, increasing treatment volumes did not really enhance mitigation. Alternate thermal mitigation methods that actively remove runoff volume should be considered where more thermal mitigation is required.     

GIS‐Based Predictive Models of Hillslope Runoff Generation Processes1

Abstract: Successful nonpoint source pollution control using best management practice placement is a complex process that requires in‐depth knowledge of the locations of runoff source areas in a watershed. Currently, very few simulation tools are capable of identifying critical runoff source areas on hillslopes and those available are not directly applicable under all runoff conditions. In this paper, a comparison of two geographic information system (GIS)‐based approaches: a topographic index model and a likelihood indicator model is presented, in predicting likely locations of saturation excess and infiltration excess runoff source areas in a hillslope of the Savoy Experimental Watershed located in northwest Arkansas. Based on intensive data collected from a two‐year field study, the spatial distributions of hydrologic variables were processed using GIS software to develop the models. The likelihood indicator model was used to produce probability surfaces that indicated the likelihood of location of both saturation and infiltration excess runoff mechanisms on the hillslope. Overall accuracies of the likelihood indicator model predictions varied between 81 and 87% for the infiltration excess and saturation excess runoff locations respectively. On the basis of accuracy of prediction, the likelihood indicator models were found to be superior (accuracy 81‐87%) to the predications made by the topographic index model (accuracy 69.5%). By combining statistics with GIS, runoff source areas on a hillslope can be identified by incorporating easily determined hydrologic measurements (such as bulk density, porosity, slope, depth to bed rock, depth to water table) and could serve as a watershed management tool for identifying critical runoff source areas in locations where the topographic index or other similar methods do not provide reliable results.     

Combined monitoring and modeling indicate the most effective agricultural best management practices

Although water quality problems associated with agricultural nonpoint source (NPS) pollution have prompted the rapid and widespread adoption of a variety of so called "best management practices" (BMPs), there have been few realistic efforts to assess their combined effectiveness in reducing NPS pollution. This study used the Variable Source Loading Function (VSLF) model, a distributed watershed model, to simulate phosphorus (P) loading from an upstate New York dairy farm before and after the implementation of a suite of BMPs. With minimal calibration, the model calculates the dissolved P (DP) losses from impervious surfaces (e.g., barnyards), the plant/soil complex, field-applied manure, and loads associated with baseflow conditions. The simulated DP loads agreed well with measured loads for both the pre-BMP and post-BMP periods. More importantly, results showed that BMPs reduced DP loads by 35%, which is over half of the expected reduction if all manure was removed from the watershed, i.e., approximately 50% reduction. The model results indicate that had no BMPs been installed DP loads would be approximately 37% greater than observed at the watershed outlet. The most effective BMPs were those that disassociated pollutant loading areas from areas prone to generating runoff, i.e., hydrologically sensitive areas. By contrast, attempts to reduce P content in manure were somewhat less effective. This study demonstrates that a combination of distributed, mechanistic modeling and long-term monitoring provides better insights into the effectiveness of water quality protection efforts than either individually.     

A SPATIAL DECISION SUPPORT SYSTEM FOR ASSESSING AGRICULTURAL NONPOINT SOURCE POLLUTION1

ABSTRACT: A spatial decision support system (SDSS) was developed to assess agricultural nonpoint source (NPS) pollution using an NPS pollution model and geographic information systems (GIS). With minimal user interaction, the SDSS assists with extracting the input parameters for a distributed parameter NPS pollution model from user-supplied GIS base layers. Thus, significant amounts of time, labor, and expertise can be saved. Further, the SDSS assists with visualizing and analyzing the output of the NPS pollution simulations. Capabilities of the visualization component include displays of sediment, nutrient, and runoff movement from a watershed. The input and output interface techniques/algorithms used to develop the SDSS, along with an example application of the SDSS, are described.     

Weighting Nitrogen and Phosphorus Pixel Pollutant Loads to Represent Runoff and Buffering Likelihoods

Watershed models often estimate annual nitrogen (N) or phosphorus (P) pollutant loads in rural areas with export coefficient (EC) (kg/ha/yr) values based on land cover, and in urban areas as the product of spatially uniform event mean concentration (EMC) (mg/L) values and runoff volume. Actual N and P nonpoint source (NPS) pollutant loading has more spatial complexity due to watershed variation in runoff likelihood and buffering likelihood along surface and subsurface pathways, which can be represented in a contributing area dispersal area (CADA) NPS model. This research develops a CADA NPS model to simulate how watershed properties of elevation, land cover, and soils upslope and downslope of each watershed pixel influence nutrient loading. The model uses both surface and subsurface runoff indices (RI), and surface and subsurface buffer indices (BI), to quantify the runoff and buffering likelihood for each watershed pixel, and generate maps of weighted EC and EMC values that identify NPS pollutant loading hotspots. The research illustrates how CADA NPS model maps and pixel loading values are sensitive to the spatial resolution and accuracy of elevation and land cover data, and model predictions can represent the lower and upper bounds of NPS loading. The model provides managers with a tool to rapidly visualize, rank, and investigate likely areas of high nutrient export.     

INTEGRATING LANDSCAPE ASSESSMENT AND HYDROLOGIC MODELING FOR LAND COVER CHANGE ANALYSIS1

ABSTRACT: Significant land cover changes have occurred in the watersheds that contribute runoff to the upper San Pedro River in Sonora, Mexico, and southeast Arizona. These changes, observed using a series of remotely sensed images taken in the 1970s, 1980s, and 1990s, have been implicated in the alteration of the basin hydrologic response. The Cannonsville subwatershed, located in the Catskill/Delaware watershed complex that delivers water to New York City, provides a contrast in land cover change. In this region, the Cannonsville watershed condition has improved over a comparable time period. A landscape assessment tool using a geographic information system (GIS) has been developed that automates the parameterization of the Soil and Water Assessment Tool (SWAT) and KINEmatic Runoff and EROSion (KINEROS) hydrologic models. The Automated Geospatial Watershed Assessment (AGWA) tool was used to prepare parameter input files for the Upper San Pedro Basin, a subwatershed within the San Pedro undergoing significant changes, and the Cannonsville watershed using historical land cover data. Runoff and sediment yield were simulated using these models. In the Cannonsville watershed, land cover change had a beneficial impact on modeled watershed response due to the transition from agriculture to forest land cover. Simulation results for the San Pedro indicate that increasing urban and agricultural areas and the simultaneous invasion of woody plants and decline of grasslands resulted in increased annual and event runoff volumes, flashier flood response, and decreased water quality due to sediment loading. These results demonstrate the usefulness of integrating remote sensing and distributed hydrologic models through the use of GIS for assessing watershed condition and the relative impacts of land cover transitions on hydrologic response.     

WATERSHED OPTIMIZATION OF AGRICULTURAL BEST MANAGEMENT PRACTICES: CONTINUOUS SIMULATION VERSUS DESIGN STORMS1

ABSTRACT: Nonpoint source (NPS) models and expert opinions are often used to prescribe best management practices (BMPs) for controlling NPS pollution. An optimization algorithm (e.g., a genetic algorithm, or GA) linked with a NPS model (e.g., Annualized AGricultural Nonpoint Source pollution model, or AnnAGNPS), can be used to more objectively prescribe BMPs and to optimize NPS pollution control measures by maximizing pollutant reduction and net monetary return from a watershed. Pollutant loads from design storms and annual loads from a continuous simulation can both be used for optimizing BMP schemes. However, which strategy results in a better solution (in terms of providing water quality protection) for a watershed is not clear. The specific objective of the study was to determine the differences in watershed pollutant loads, in an experimental watershed in Pennsylvania, resulting from optimization analyses performed using pollutant loads from a series of five 2‐yr 24‐hr storm events, a series of five 5‐yr 24‐hr storm events, and cumulative pollutant loads from a continuous simulation of five years of weather data. For each of these three different event alternatives, 100 near optimal solutions (BMP schemes) were generated. Sediment (Sed), sediment nitrogen (SedN), dissolved N (SolN), sediment organic carbon (SedOC), and sediment phosphorus (SedP) loads from a different five‐year period (an evaluation period) suggest that the optimal BMP schemes resulting from the use of annual cumulative pollutant loads from a continuous simulation of five years of weather data provide smaller cumulative NPS pollutant loads at the watershed outlet.     

Nonpoint Source Pollution Responses Simulation for Conversion Cropland to Forest in Mountains by SWAT in China

Several environmental protection policies have been implemented to prevent soil erosion and nonpoint source (NPS) pollutions in China. After severe Yangtze River floods, the “conversion cropland to forest policy” (CCFP) was carried out throughout China, especially in the middle and upper reaches of Yangtze River. The research area of the current study is located in Bazhong City, Sichuan Province in Yangtze River watershed, where soil erosion and NPS pollution are serious concerns. Major NPS pollutants include nitrogen (N) and phosphorus (P). The objective of this study is to evaluate the long-term impact of implementation of the CCFP on stream flow, sediment yields, and the main NPS pollutant loading at watershed level. The Soil and Water Assessment Tool (SWAT) is a watershed environmental model and is applied here to simulate and quantify the impacts. Four scenarios are constructed representing different patterns of conversion from cropland to forest under various conditions set by the CCFP. Scenario A represented the baseline, i.e., the cropland and forest area conditions before the implementation of CCFP. Scenario B represents the condition under which all hillside cropland with slope larger than 25° was converted into forest. In scenario C and D, hillside cropland with slope larger than 15° and 7.5° was substituted by forest, respectively. Under the various scenarios, the NPS pollution reduction due to CCFP implementation from 1996–2005 is estimated by SWAT. The results are presented as percentage change of water flow, sediment, organic N, and organic P at watershed level. Furthermore, a regression analysis is conducted between forest area ratio and ten years’ average NPS load estimations, which confirmed the benefits of implementing CCFP in reducing nonpoint source pollution by increasing forest area in mountainous areas. The reduction of organic N and organic P is significant (decrease 42.1% and 62.7%, respectively) at watershed level. In addition, this study also proves that SWAT modeling approach can be used to estimate NPS pollutants’ impacts of land use conversions in large watershed.     

STORMFLOW SIMULATION USING A GEOGRAPHICAL INFORMATION SYSTEM WITH A DISTRIBUTED APPROACH1

ABSTRACT: With the increasing availability of digital and remotely sensed data such as land use, soil texture, and digital elevation models (DEMs), geographic information systems (GIS) have become an indispensable tool in preprocessing data sets for watershed hydrologic modeling and post processing simulation results. However, model inputs and outputs must be transferred between the model and the GIS. These transfers can be greatly simplified by incorporating the model itself into the GIS environment. To this end, a simple hydrologic model, which incorporates the curve number method of rainfall‐runoff partitioning, the ground‐water base‐flow routine, and the Muskingum flow routing procedure, was implemented on the GIS. The model interfaces directly with stream network, flow direction, and watershed boundary data generated using standard GIS terrain analysis tools; and while the model is running, various data layers may be viewed at each time step using the full display capabilities. The terrain analysis tools were first used to delineate the drainage basins and stream networks for the Susquehanna River. Then the model was used to simulate the hydrologic response of the Upper West Branch of the Susquehanna to two different storms. The simulated streamflow hydrographs compare well with the observed hydrographs at the basin outlet.     

THE APPLICATION OF HYDROLOGIC MODELS TO SMALL WATERSHEDS HAVING MILD TOPOGRAPHY1

ABSTRACT: The application of hydrologic models to small watersheds of mild topography is not well documented. This study evaluates the applicability of hydrologic models described by Huggins and the Soil Conservation Service to small watersheds by comparing the simulated and actual hydrograph for both gaged and ungaged situations. The annual maximum rainfall events plus storms exceeding 2.5 inches from 25 years of rainfall and runoff data for two small watersheds were selected for the model evaluations. These storms had a variety of patterns and occurred on many different watershed conditions. Simulated and actual hydrographs were compared using a parameter which contained volume, peak, and shape factors. One-half of the selected storms were used to calibrate the models. For both models, there were no significant differences between the simulated and actual runoff volumes and peak runoff rates. Parameters obtained during the calibration process and relationships developed to estimate antecedent moisture and to modify tabulated runoff curve numbers were used to simulate the runoff hydrograph from the remaining storms. These remaining storms or test storms were simulated only once in order to imitate an ungaged situation. In general, both the Huggins and SCS model performed similarly on the test storms, but the level of model performance was lower than that for the calibration storms. For both models, the two-day antecedent rainfall was more important than the five-day in determining antecedent moisture and modifying tabulated curve numbers. The time of concentration which resulted in good hydrograph simulations was about three times larger than that estimated using published empirical relationships.     

Land-use forecasting and hydrologic model integration for improved land-use decision support

This paper develops a methodology for integrating a land-use forecasting model with an event scale, rainfall-runoff model in support of improving land-use policy formulation at the watershed scale. The models selected for integration are loosely coupled, structured upon a common GIS platform that facilitates data exchange. The hydrologic model HEC-HMS is calibrated for a specific storm event that occurred within central Washington State. The land-use forecasting model, What If? is implemented to forecast future spatial distributions of low-density residential land-uses under low and high population growth estimates. Forecasted land-use distribution patterns for the years 2015, 2025, and 2050 are then used as land-use data input for the calibrated hydrologic model, keeping all other parameters constant. Impacts to the stream discharge hydrograph are predicted as the study area becomes increasingly developed as forecasted by What If?. The initial results of this integration process demonstrate the synergy that can be generated through the linkage of the selected models. The ability to quantifiably forecast the potential hydrologic implications of proposed land-use policies before their implementation offers land-use decision-makers a valuable tool for discerning which proposed land-use alternatives will be effective at minimizing storm water runoff.     

IDENTIFICATION OF CRITICAL NONPOINT POLLUTION SOURCE AREAS USING GEOGRAPHIC INFORMATION SYSTEMS AND WATER QUALITY MODELING1

n integrated approach coupling water quality computer simulation modeling with a geographic information system (GIS) was used to delineate critical areas of nonpoint source (NPS) pollution at the watershed level. Two simplified pollutant export models were integrated with the Virginia Geographic Information System (VirGIS) to estimate soil erosion, sediment yield, and phosphorus (P) loading from the Nomini Creek watershed located in Westmoreland County, Virginia. On the basis of selected criteria for soil erosion rate, sediment yield, and P loading, model outputs were used to identily watershed areas which exhibit three categories (low, medium, high) of non-point source pollution potentials. The percentage of the watershed area in each category, and the land area with critical pollution problems were also identified. For the 1505-ha Nomini Creek watershed, about 15, 16, and 21 percent of the watershed area were delineated as sources of critical soil erosion, sediment, and phosphorus pollution problems, respectively. In general, the study demonstrated the usefulness of integrating GIS with simulation modeling for nonpoint source pollution control and planning. Such techniques can facilitate making priorities and targeting nonpoint source pollution control programs.     

ESTIMATING NONPOINT SOURCE POLLUTION LOADS WITH A GIS SCREENING MODEL1

ABSTRACT: The St. Johns River Water Management District (SJR-WMD) is using a Geographic Information System (GIS) screening model to estimate annual nonpoint source pollution loads to surface waters and determine nonpoint source pollution problem areas within the SJRWMD. The model is a significant improvement over current practice because it is contained entirely within the district's GIS software, resulting in greater flexibility and efficiency, and useful visualization capabilities. Model inputs consist of five spatial data layers, runoff coefficients, mean runoff concentrations, and stormwater treatment efficiencies. The spatial data layers are: existing land use, future land use, soils, rainfall, and hydrologic boundaries. These data layers are processed using the analytical capabilities of a cell-based GIS. Model output consists of seven spatial data layers: runoff, total nitrogen, total phosphorous, suspended solids, biochemical oxygen demand, lead, and zinc. Model output can be examined visually or summarized numerically by drainage basin. Results are reported for only one of the SJRWMD's ten major drainage basins, the lower St. Johns River basin. The model was created to serve a major planning effort at the SJRWMD; results are being actively used to address nonpoint source pollution problems.     

A Water Quality Model for Regional Stream Assessment and Conservation Strategy Development

Non-point-source (NPS) pollution remains the primary source of stream impairment in the United States. Many problems such as eutrophication, sedimentation, and hypoxia are linked with NPS pollution which reduces the water quality for aquatic and terrestrial organisms. Increasingly, NPS pollution models have been used for landscape-scale pollution assessment and conservation strategy development. Our modeling approach functions at a scale between simple landscape-level assessments and complex, data-intensive modeling by providing a rapid, landscape-scale geographic information system (GIS) model with minimal data requirements and widespread applicability. Our model relies on curve numbers, literature-derived pollution concentrations, and land status to evaluate total phosphorus (TP), total nitrogen (TN), and suspended solids (SS) at the reach scale. Model testing in the Chesapeake Bay watershed indicated that predicted distributions of water quality classes were realistic at the reach scale, but precise estimates of pollution concentrations at the local scale can have errors. Application of our model in the tributary watersheds along Lake Ontario suggested that it is useful to managers in watershed planning by rapidly providing important information about NPS pollution conditions in areas where large data gaps exist, comparisons among stream reaches across numerous watersheds are required, or regional assessments are sought.