AN INTERACTWE MODELING ENVIRONMENT FOR NON-POINT SOURCE POLLUTION CONTROL1

ABSTRACT: Non-point source pollution cuntinues to be an important environmental and water quality management problem. For the moat part, analysis of non-point source pollution in watersheds has depended on the use of distributed models to identify potential problem areas and to assess the effectiveness of alternative management practices. To effectively use these models for watershed water quality management, users depend on integrated geographic information systems (GIS)-based interfaces for input/output data management. However, existing interfaces are ad-hoc and the utility of GIS is limited to organization of input data and display of output data. A highly interactive water quality modeling interface that utilizes the functional components and analytical capability of GIS is highly desirable. This paper describes the tight coupling of the Agricultural Non-point Source (AGNPS) water quality model and ARC/INFO GIS software to provide an interactive hybrid modeling environment for evaluation of non-point source pollution in a watershed. The modeling environment is designed to generate AGNPS input parameters from user-specified GIS coverages, create AGNPS input data files, control AGNPS model simulations, and extract and organize AGNPS model output data for display. An example application involving the estimation of pesticide loading in a southern Iowa agricultural watershed demonstrates the capability of the modeling environment. Compared with traditional methods of watershed water quality modeling using the AGNPS model or other ad-hoc interfaces between a distributed model and GIS, the interactive modeling environment system is efficient and significantly reduces the task of watershed analysis using tightly coupled GIS databases and distributed models.     

STORM RUNOFF PREDICTION BASED ON A SPATIALLY DISTRIBUTED TRAVEL TIME METHOD UTILIZING REMOTE SENSING AND GIS1

ABSTRACT: In this study, remotely sensed data and geographic information system (GIS) tools were used to estimate storm runoff response for Simms Creek watershed in the Etonia basin in northeast Florida. Land cover information from digital orthophoto quarter quadrangles (DOQQ), and enhanced thematic mapper plus (ETM+) were analyzed for the years 1990, 1995, and 2000. The corresponding infiltration excess runoff response of the study area was estimated using the U.S. Department of Agriculture (USDA), Natural Resources Conservation Service Curve Number (NRCS‐CN) method. A digital elevation model (DEM)/GIS technique was developed to predict stream response to runoff events based on the travel time from each grid cell to the watershed outlet. A comparison of predicted to observed stream response shows that the model predicts the total runoff volume with an efficiency of 0.98, the peak flow rate at an efficiency of 0.85, and the full direct runoff hydrograph with an average efficiency of 0.65. The DEM/GIS travel time model can be used to predict the runoff response of ungaged watersheds and is useful for predicting runoff hydrographs resulting from proposed large scale changes in the land use.     

MODELING DEVELOPED COASTAL WATERSHEDS WITH THE AGRICULTURAL NON-POINT SOURCE MODEL1

ABSTRACT: Many coastal states are facing increasing urban growth along their coast lines. The growth has caused urban non-point source nitrogen runoff to be a major contributor to coastal and estuarine enrichment. Water resource managers are responsible for evaluating the impacts from point and non-point sources in developed watersheds and developing strategies to manage future growth. Non-point source models provide an effective approach to these management challenges. The Agricultural Non-Point Source Model (AGNPS) permits the incorporation of important spatial information (soils, landuse, topography, hydrology) in simulating surface hydrology and nitrogen non-point source runoff. The AGNPS model was adapted for developed coastal watersheds by deriving urban coefficients that reflect urban landuse classes and the amount of impervious surface area. Popperdam Creek watershed was used for model parameter development and model calibration. Four additional watersheds were simulated to validate the model. The model predictions of the peak flow and total nitrogen concentrations were close to the field measurements for the five sub-basins simulated. Measured peak flow varied by 30 fold among the sub-basins. The average simulated peak flow was within 14 percent of the average measured peak flow. Measured total nitrogen loads varied over an order of magnitude among the sub-basins yet error between the measured and simulated loads for a given sub-basin averaged 5 percent. The AGNPS model provided better estimates of nitrogen loads than widely used regression methods. The spatial distribution of important watershed characteristics influenced the impacts of urban landuse and projecting future residential expansion on runoff, sediment and nitrogen yields. The AGNPS model provides a useful tool to incorporate these characteristics, evaluate their importance, and evaluate fieldscale to watershed-scale urban impacts.     

MODELING ACTUAL EVAPOTRANSPIRATION FROM FORESTED WATERSHEDS ACROSS THE SOUTHEASTERN UNITED STATES1

ABSTRACT: About 50 to 80 percent of precipitation in the southeastern United States returns to the atmosphere by evapotranspiration. As evapotranspiration is a major component in the forest water balances, accurately quantifying it is critical to predicting the effects of forest management and global change on water, sediment, and nutrient yield from forested watersheds. However, direct measurement of forest evapotranspiration on a large basin or a regional scale is not possible. The objectives of this study were to develop an empirical model to estimate long‐term annual actual evapotranspiration (ART) for forested watersheds and to quantify spatial AET patterns across the southeast. A geographic information system (GIS) database including land cover, daily streamflow, and climate was developed using long term experimental and monitoring data from 39 forested watersheds across the region. Using the stepwise selection method implemented in a statistical modeling package, a long term annual AET model was constructed. The final multivariate linear model includes four independent variables—annual precipitation, watershed latitude, watershed elevation, and percentage of forest coverage. The model has an adjusted R² of 0.794 and is sufficient to predict long term annual ART for forested watersheds across the southeastern United States. The model developed by this study may be used to examine the spatial variability of water availability, estimate annual water loss from mesoscale watersheds, and project potential water yield change due to forest cover change.     

Predicting Debris Yield From Burned Watersheds: Comparison of Statistical and Artificial Neural Network Models1

Abstract: Alluvial fans in southern California are continuously being developed for residential, industrial, commercial, and agricultural purposes. Development and alteration of alluvial fans often require consideration of mud and debris flows from burned mountain watersheds. Accurate prediction of sediment (hyper‐concentrated sediment or debris) yield is essential for the design, operation, and maintenance of debris basins to safeguard properly the general population. This paper presents results based on a statistical model and Artificial Neural Network (ANN) models. The models predict sediment yield caused by storms following wildfire events in burned mountainous watersheds. Both sediment yield prediction models have been developed for use in relatively small watersheds (50‐800 ha) in the greater Los Angeles area. The statistical model was developed using multiple regression analysis on sediment yield data collected from 1938 to 1983. Following the multiple regression analysis, a method for multi‐sequence sediment yield prediction under burned watershed conditions was developed. The statistical model was then calibrated based on 17 years of sediment yield, fire, and precipitation data collected between 1984 and 2000. The present study also evaluated ANN models created to predict the sediment yields. The training of the ANN models utilized single storm event data generated for the 17‐year period between 1984 and 2000 as the training input data. Training patterns and neural network architectures were varied to further study the ANN performance. Results from these models were compared with the available field data obtained from several debris basins within Los Angeles County. Both predictive models were then applied for hind‐casting the sediment prediction of several post 2000 events. Both the statistical and ANN models yield remarkably consistent results when compared with the measured field data. The results show that these models are very useful tools for predicting sediment yield sequences. The results can be used for scheduling cleanout operation of debris basins. It can be of great help in the planning of emergency response for burned areas to minimize the damage to properties and lives.     

PARAMETER IDENTIFICATION IN A TWO‐MULTIPLIER SEDIMENT YIELD MODEL1

ABSTRACT: A process based, distributed runoff erosion model (KINEROS2) was used to examine problems of parameter identification of sediment entrainment equations for small watersheds. Two multipliers were used to reflect the distributed nature of the sediment entrainment parameters: one multiplier for a raindrop induced entrainment parameter, and one multiplier for a flow induced entrainment parameter. The study was conducted in three parts. First, parameter identification was studied for simulated error free data sets where the parameter values were known. Second, the number of data points in the simulated sedigraphs was reduced to reflect the effect of temporal sampling frequency on parameter identification. Finally, event data from a small range‐land watershed were used to examine parameter identifiability when the parameter values are unknown. Results demonstrated that whereas unique multiplier values can be obtained for simulated error free data, unique parameter values could not be obtained for some event data. Unique multiplier values for raindrop induced entrainment and flow induced entrainment were found for events with greater than a two‐year return period (～25 mm) that also had at least 10 mm of rain in ten minutes. It was also found that the three‐minute sampling frequency used for the sediment sampler might be inadequate to identify parameters in some cases.     

A WINDOWS‐BASED GIS‐AGNPS INTERFACE1

ABSTRACT: ArcView Nonpoint Source Pollution Modeling (AVNPSM), an interface between ArcView GIS and AGNPS (Agricultural Nonpoint Source Pollution Model) is developed in support of agricultural watershed analysis and nonpoint source pollution management. The interface is PC‐based and operates in a Windows environment. It consists of seven modules: AGNPS utility, parameter generator, input file processor, model executor, output visualizer, statistical analyzer, and land use simulator. Basic input data to the interface include: soil, digital elevation model, land use/cover, water features, climate, and information on management practices. Application of the AVNPSM to a sample watershed indicates that it is user friendly, flexible, and robust, and it significantly improves the efficiency of the nonpoint source pollution modeling process.     

RASTER-BASED HYDROLOGIC MODELING OF SPATIALLY-VARIED SURFACE RUNOFF1

ABSTRACT: The proliferation of watershed databases in raster Geographic Information System (GIS) format and the availability of radar-estimated rainfall data foster rapid developments in raster-based surface runoff simulations. The two-dimensional physically-based rainfall-runoff model CASC2D simulates spatially-varied surface runoff while fully utilizing raster GIS and radar-rainfall data. The model uses the Green and Ampt infiltration method, and the diffusive wave formulation for overland and channel flow routing enables overbank flow storage and routing. CASC2D offers unique color capabilities to display the spatio-temporal variability of rainfall, cumulative infiltrated depth, and surface water depth as thunderstorms unfold. The model has been calibrated and independently verified to provide accurate simulations of catchment response to moving rainstorms on watersheds with spatially-varied infiltration. The model can accurately simulate surface runoff from flashfloods caused by intense thunderstorms moving across partial areas of a watershed.     

INTEGRATION OF GEOGRAPHIC INFORMATION SYSTEMS AND A COMPUTER MODEL TO EVALUATE IMPACTS OF AGRICULTURAL RUNOFF ON WATER QUALITY1

ABSTRACT: This study integrates an Agricultural Non-Point Source Pollution Model (AGNPS), the Geographic Resource Analysis Support System (GRASS) (U.S. Army Corps of Engineers, 1987), and GRASS WATERWORKS (a hydrologic modeling tool box being developed at the Michigan State University Center for Remote Sensing) to evaluate the impact of agricultural runoff on water quality in the Cass River, a subwatershed of Saginaw Bay. AGNPS is used to estimate the amounts, origin, and distribution of sediment, nitrogen (N), and phosphorus (P) in the watershed. GRASS and GRASS WATERWORKS are used to generate parameters needed for AGNPS from digital maps, which include soil association, land use, watershed boundaries, water features, and digital elevation. Outputs of the model include spatially distributed estimates of volume and peak runoff, overland and channel erosion, sediment yields, and concentrations of nitrogen and phosphorus. Management scenarios are explored in the AGNPS model to minimize sedimentation and nutrient loading. Scenarios evaluated include variations in crop cover, tillage methods, and other agricultural management practices. In addition, areas vulnerable to erosion are identified for best management practices.     

ACCURACY AND PRECISION OF NRCS MODELS FOR SMALL WATERSHEDS1

ABSTRACT: In the last 30 years, the National Resource Conservation Service's TR‐55 and TR‐20 models have seen a dramatic increase in use for stormwater management purposes. This paper reviews some of the data that were originally used to develop these models and tests how well the models estimate annual series peak runoff rates for the same watersheds using longer historical data record lengths. The paper also explores differences between TR‐55 and TR‐20 peak runoff rate estimates and time of concentration methods. It was found that of the 37 watersheds tested, 25 were either over‐ or under‐predicting the actual historical watershed runoff rates by more than 30 percent. The results of this study indicate that these NRCS models should not be used to model small wooded watersheds less than 20 acres. This would be especially true if the watershed consisted of an area without a clearly defined outlet channel. This study also supports the need for regulators to allow educated hydrologists to alter pre‐packaged model parameters or results more easily than is currently permitted.     

Mitigating the Effects of Landscape Development on Streams in Urbanizing Watersheds

This collaborative study examined urbanization and impacts on area streams while using the best available sediment and erosion control (S&EC) practices in developing watersheds in Maryland, United States. During conversion of the agricultural and forested watersheds to urban land use, land surface topography was graded and vegetation was removed creating a high potential for sediment generation and release during storm events. The currently best available S&EC facilities were used during the development process to mitigate storm runoff water quality, quantity, and timing before entering area streams. Detailed Geographic Information System (GIS) maps were created to visualize changing land use and S&EC practices, five temporal collections of LiDAR (light detection and ranging) imagery were used to map the changing landscape topography, and streamflow, physical geomorphology, and habitat data were used to assess the ability of the S&EC facilities to protect receiving streams during development. Despite the use of the best available S&EC facilities, receiving streams experienced altered flow, geomorphology, and decreased biotic community health. These impacts on small streams during watershed development affect sediment and nutrient loads to larger downstream aquatic ecosystems such as the Chesapeake Bay.     

Development of a SWAT Patch for Better Estimation of Sediment Yield in Steep Sloping Watersheds1

Abstract: The watershed scale Soil and Water Assessment Tool (SWAT) model divides watersheds into smaller subwatersheds for simulation of rainfall‐runoff and sediment loading at the field level and routing through stream networks. Typically, the SWAT model first needs to be calibrated and validated for accurate estimation through adjustment of sensitive input parameters (i.e., Curve Number values, USLE P, slope and slope‐length, and so on). However, in some instances, SWAT‐simulated results are greatly affected by the watershed delineation and Digital Elevation Models (DEM) cell size. In this study, the SWAT ArcView GIS Patch II was developed for steep sloping watersheds, and its performance was evaluated for various threshold values and DEM cell size scenarios when delineating subwatersheds using the SWAT model. The SWAT ArcView GIS Patch II was developed using the ArcView GIS Avenue program and Spatial Analyst libraries. The SWAT ArcView GIS Patch II improves upon the SWAT ArcView GIS Patch I because it reflects the topographic factor in calculating the field slope‐length of Hydrologic Response Units in the SWAT model. The simulated sediment value for 321 subwatersheds (watershed delineation threshold value of 25 ha) is greater than that for 43 subwatersheds (watershed delineation threshold value of 200 ha) by 201% without applying the SWAT ArcView GIS Patch II. However, when the SWAT ArcView GIS Patch II was applied, the difference in simulated sediment yield decreases for the same scenario (i.e., difference in simulated sediment with 321 subwatersheds and 43 subwatersheds) was 12%. The simulated sediment value for DEM cell size of 50 m is greater than that for DEM cell size of 10 m by 19.8% without the SWAT ArcView GIS Patch II. However, the difference becomes smaller (3.4% difference) between 50 and 10 m with the SWAT ArcView GIS Patch II for the DEM scenarios. As shown in this study, the SWAT ArcView GIS Patch II can reduce differences in simulated sediment values for various watershed delineation and DEM cell size scenarios. Without the SWAT ArcView GIS Patch II, variations in the SWAT‐simulated results using various watershed delineation and DEM cell size scenarios could be greater than those from input parameter calibration. Thus, the results obtained in this study show that the SWAT ArcView GIS Patch II should be used when simulating hydrology and sediment yield for steep sloping watersheds (especially if average slope of the subwatershed is >25%) for more accurate simulation of hydrology and sediment using the SWAT model. The SWAT ArcView GIS Patch II is available at http://www.EnvSys.co.kr/~swat for free download.     

INTEGRATION OF A BASIN-SCALE WATER QUALITY MODEL WITH GIS1

ABSTRACT: Geographic Information Systems (GIS) have been successfully integrated with distributed parameter, single-event, water quality models such as AGNPS (AGricultural NonPoint Source) and ANSWERS (Areal Nonpoint Source Watershed Environmental Response Simulation). These linkages proved to be an effective way to collect, manipulate, visualize, and analyze the input and output date of water quality models. However, for continuous-time, basin large-scale water quality models, collecting and manipulating the input data are more time-consuming and cumbersome due to the method of disaggregation (subdivisions are based on topographic boundaries). SWAT (Soil and Water Assessment Tool), a basin-scale water quality model, was integrated with a GIS to extract input data for modeling a basin. This paper discusses the detailed development of the integration of the SWAT water quality model with GRASS (Geographic Resources Analysis Support System) GIS, along with an application and advantages. The integrated system was applied to simulated a 114 sq. km upper portion of the Seco Creek Basin by subdividing it into 37 subbasins. The average monthly predicted streamflw is in agreement with measured monthly streamflw values.     

Hydrologic Modeling Uncertainty Resulting From Land Cover Misclassification1

Abstract: A stochastic, spatially explicit method for assessing the impact of land cover classification error on distributed hydrologic modeling is presented. One‐hundred land cover realizations were created by systematically altering the North American Landscape Characterization land cover data according to the dataset’s misclassification matrix. The matrix indicates the probability of errors of omission in land cover classes and is used to assess the uncertainty in hydrologic runoff simulation resulting from parameter estimation based on land cover. These land cover realizations were used in the GIS‐based Automated Geospatial Watershed Assessment tool in conjunction with topography and soils data to generate input to the physically‐based Kinematic Runoff and Erosion model. Uncertainties in modeled runoff volumes resulting from these land cover realizations were evaluated in the Upper San Pedro River basin for 40 watersheds ranging in size from 10 to 100 km² under two rainfall events of differing magnitudes and intensities. Simulation results show that model sensitivity to classification error varies directly with respect to watershed scale, inversely to rainfall magnitude and are mitigated or magnified by landscape variability depending on landscape composition.     

DETERMINING SIGNIFICANCE AND PRECISION OF ESTIMATED PARAMETERS FOR RUNOFF FROM SEMIARID WATERSHEDS1

ABSTRACT Significant parameters for predicting thunderstorm runoff from small semiarid watersheds are determined using data from the Walnut Gulch watershed in southern Arizona. Based on these data, thunderstorm rainfall is dominant over watershed parameters for predicting runoff from multiple linear regression equations. In some cases antecedent moisture added significantly to the models. A technique is developed for estimating precision of predicted values from multiple linear regression equations. The technique involves matrix methods in estimating the variance of mean predicted values from a regression equation. The estimated variance of the mean predicted value is then used to estimate the variance of an individual predicted value. A computer program is developed to implement these matrix methods and to form confidence limits on predicted values based on both a normality assumption and the Chebyshev inequality.     

PRIORITIZING NONPOINT SOURCE PHOSPHORUS LOADING USING A GRASS-MODELING SYSTEM1

ABSTRACT: A UNIX-based windows application was developed to integrate a phosphorus transport model with the Geographic Resources Analysis Support System (GRASS). The system prioritizes potential phosphorus loading from fields or cells in a watershed and can evaluate the effects of alternate management practices on phosphorus yield. The model simulates phosphorus loading by using a daily mass balance on a unit-area basis and incorporates the effects from rainfall, topography, soil properties, fertilizer and animal waste application, and management. Model predictions include dissolved and sediment-bound phosphorus yield, runoff volume, and sediment yield. Within the integrated GRASS-modeling system, the user can obtain model input data, execute the model using various options, rank model input and out. put data, and display them as GRASS-based maps or data tables. All functions are menu driven, developed using C language and X-window tools to run on a SUN workstation platform. The system provides a powerful and efficient tool for prioritizing phosphorus loading from nonpoint sources.     

Effect of the Spatial Variability of Land Use,Soil Type,and Precipitation on Streamflows in Small Watersheds1

Abstract: The spatial variability of the data used in models includes the spatial discretization of the system into subsystems, the data resolution, and the spatial distribution of hydrologic features and parameters. In this study, we investigate the effect of the spatial distribution of land use, soil type, and precipitation on the simulated flows at the outlet of “small watersheds” (i.e., watersheds with times of concentration shorter than the model computational time step). The Soil and Water Assessment Tool model was used to estimate runoff and hydrographs. Different representations of the spatial data resulted in comparable model performances and even the use of uniform land use and soil type maps, instead of spatially distributed, was not noticeable. It was found that, although spatially distributed data help understand the characteristics of the watershed and provide valuable information to distributed hydrologic models, when the watershed is small, realistic representations of the spatial data do not necessarily improve the model performance. The results obtained from this study provide insights on the relevance of taking into account the spatial distribution of land use, soil type, and precipitation when modeling small watersheds.     

CALIBRATION OF A WATER-BALANCE MODEL FOR SMALL WATERSHEDS IN EASTERN OREGON1

ABSTRACT: The BURP water-balance model was calibrated for 13 small (0.46 to 7.00 mi²), forested watersheds in the Blue Mountains of eastern Oregon where snowmelt is the dominant source of runoff. BURP is the model name and is not an acronym. Six of the 16 parameters in BURP were calibrated. The subsurface recession coefficient and three subsurface water-storage parameters were most sensitive for simulating monthly flow. Calibrated subsurface recession coefficients ranged from 0.988 to 0.998. The subsurface-water storage parameters were calibrated at between 20 to 120 percent of their initial values obtained from a category III soil survey. That reconnaissance-level survey was apparently too broad to accurately reflect subsurface-water storage in small watersheds. Tests of model performance showed BURP is capable of producing accurate simulations of monthly flow for mountainous, snow-dominated watersheds with shallow (< 4 ft) soils when calibrated with 2 to 4 years of streamflow data. A regression of observed versus simulated monthly flows with data from all watersheds combined showed that BURP accounted for 85 percent of the variability in observed flows, which ranged from 0.01 to 20.8 inches, but underpredicted high flow months, with a slope of 1.15 that is significantly different from 1.0 (p = 0.05). Without prior calibration, subsurface-water storage parameters appeared to be the greatest source of potential error.     

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.     

A DYNAMIC SYSTEM MODEL FOR SIMULATING SEDIMENT DISCHARGE1

ABSTRACT: A dynamic sediment discharge model was developed and proposed for the simulation of watershed systems. It war developed from an expansion of splash and flow erosion relationships under steady state conditions. It was described as a general erosion model that can be reduced to forms comparable to many conceptual soil erosion and sediment yield models. The model incorporates eight parameters such as rainfall intensities, runoff rates, and previous sediment discharges. The model was tested with two small watersheds with simulation results which were very satisfactory compared to the data.