DIFFERENCES BETWEEN MODELED SURPLUS AND USGS-MEASURED DISCHARGE IN LAKE PONTCHARTRAIN BASIN,LOUISIANA1

ABSTRACT: A one-layer decreasing-availability monthly water balance model is used to estimate monthly surplus that flows into the Lake Pontchartrain Basin from the Amite, Tickfaw, Natalbany, Tangipahoa, and Tchefuncte Rivers for water years 1949 through 1990. The modeled annual surplus for each drainage basin is compared to gauged annual discharge obtained from the United States Geological Survey. This provides an estimate of the differential success of the model over watersheds of various sizes, and also suggests appropriate adjustment factors to be used in future water balance analyses of similar basins in humid subtropical climate regions. Results show that annual surplus values agree well with the USGS values, after an annual adjustment of about 140 mm (11 to 28 percent of the basin surplus) is subtracted from the annual modeled totals to compensate for overestimation by the model. However, inter-annual variability is high in the annual cycles. Winter and spring discharges can also be modeled successfully.     

Modeling Hydrology in a Small Rocky Mountain Watershed Serving Large Urban Populations1

Abstract: This article describes the development of a calibrated hydrologic model for the Blue River watershed (867 km²) in Summit County, Colorado. This watershed provides drinking water to over a third of Colorado’s population. However, more research on model calibration and development for small mountain watersheds is needed. This work required integration of subsurface and surface hydrology using GIS data, and included aspects unique to mountain watersheds such as snow hydrology, high ground‐water gradients, and large differences in climate between the headwaters and outlet. Given the importance of this particular watershed as a major urban drinking‐water source, the rapid development occurring in small mountain watersheds, and the importance of Rocky Mountain water in the arid and semiarid West, it is useful to describe calibrated watershed modeling efforts in this watershed. The model used was Soil and Water Assessment Tool (SWAT). An accurate model of the hydrologic cycle required incorporation of mountain hydrology‐specific processes. Snowmelt and snow formation parameters, as well as several ground‐water parameters, were the most important calibration factors. Comparison of simulated and observed streamflow hydrographs at two U.S. Geological Survey gaging stations resulted in good fits to average monthly values (0.71 Nash‐Sutcliffe coefficient). With this capability, future assessments of point‐source and nonpoint‐source pollutant transport are possible.     

COMPARISON OF PROCESS‐BASED AND ARTIFICIAL NEURAL NETWORK APPROACHES FOR STREAMFLOW MODELING IN AN AGRICULTURAL WATERSHED1

ABSTRACT: The performance of the Soil and Water Assessment Tool (SWAT) and artificial neural network (ANN) models in simulating hydrologic response was assessed in an agricultural watershed in southeastern Pennsylvania. All of the performance evaluation measures including Nash‐Sutcliffe coefficient of efficiency (E) and coefficient of determination (R²) suggest that the ANN monthly predictions were closer to the observed flows than the monthly predictions from the SWAT model. More specifically, monthly streamflow E and R² were 0.54 and 0.57, respectively, for the SWAT model calibration period, and 0.71 and 0.75, respectively, for the ANN model training period. For the validation period, these values were ?0.17 and 0.34 for the SWAT and 0.43 and 0.45 for the ANN model. SWAT model performance was affected by snowmelt events during winter months and by the model's inability to adequately simulate base flows. Even though this and other studies using ANN models suggest that these models provide a viable alternative approach for hydrologic and water quality modeling, ANN models in their current form are not spatially distributed watershed modeling systems. However, considering the promising performance of the simple ANN model, this study suggests that the ANN approach warrants further development to explicitly address the spatial distribution of hydrologic/water quality processes within watersheds.     

WATERSHED SCALE MODELING OF CRITICAL SOURCE AREAS OF RUNOFF GENERATION AND PHOSPHORUS TRANSPORT1

ABSTRACT: A curve number based model, Soil and Water Assessment Tool (SWAT), and a physically based model, Soil Moisture Distribution and Routing (SMDR), were applied in a headwater watershed in Pennsylvania to identify runoff generation areas, as runoff areas have been shown to be critical for phosphorus management. SWAT performed better than SMDR in simulating daily streamflows over the four‐year simulation period (Nash‐Sutcliffe coefficient: SWAT, 0.62; SMDR, 0.33). Both models varied streamflow simulations seasonally as precipitation and watershed conditions varied. However, levels of agreement between simulated and observed flows were not consistent over seasons. SMDR, a variable source area based model, needs further improvement in model formulations to simulate large peak flows as observed. SWAT simulations matched the majority of observed peak flow events. SMDR overpredicted annual flow volumes, while SWAT underpredicted the same. Neither model routes runoff over the landscape to water bodies, which is critical to surface transport of phosphorus. SMDR representation of the watershed as grids may allow targeted management of phosphorus sources. SWAT representation of fields as hydrologic response units (HRUs) does not allow such targeted management.     

HYDROLOGIC PARAMETERIZATION OF WATERSHEDS FOR RUNOFF PREDICTION USING SWAT1

ABSTRACT: The use of continuous time, distributed parameter hydrologic models like SWAT (Soil and Water Assessment Tool) has opened several opportunities to improve watershed modeling accuracy. However, it has also placed a heavy burden on users with respect to the amount of work involved in parameterizing the watershed in general and in adequately representing the spatial variability of the watershed in particular. Recent developments in Geographical Information Systems (GIS) have alleviated some of the difficulties associated with managing spatial data. However, the user must still choose among various parameterization approaches that are available within the model. This paper describes the important parameterization issues involved when modeling watershed hydrology for runoff prediction using SWAT with emphasis on how to improve model performance without resorting to tedious and arbitrary parameter by parameter calibration. Synthetic and actual watersheds in Indiana and Mississippi were used to illustrate the sensitivity of runoff prediction to spatial variability, watershed decomposition, and spatial and temporal adjustment of curve numbers and return flow contribution. SWAT was also used to predict stream runoff from actual watersheds in Indiana that have extensive subsurface drainage. The results of this study provide useful information for improving SWAT performance in terms of stream runoff prediction in a manner that is particularly useful for modeling ungaged watersheds wherein observed data for calibration is not available.     

THE CONCEPT OF HYDROLOGIC LANDSCAPES1

ABSTRACT: Hydrologic landscapes are multiples or variations of fundamental hydrologic landscape units. A fundamental hydrologic landscape unit is defined on the basis of land‐surface form, geology, and climate. The basic land‐surface form of a fundamental hydrologic landscape unit is an upland separated from a lowland by an intervening steeper slope. Fundamental hydrologic landscape units have a complete hydrologic system consisting of surface runoff, ground‐water flow, and interaction with atmospheric water. By describing actual landscapes in terms of land‐surface slope, hydraulic properties of soils and geologic framework, and the difference between precipitation and evapotranspiration, the hydrologic system of actual landscapes can be conceptualized in a uniform way. This conceptual framework can then be the foundation for design of studies and data networks, syntheses of information on local to national scales, and comparison of process research across small study units in a variety of settings. The Crow Wing River watershed in central Minnesota is used as an example of evaluating stream discharge in the context of hydrologic landscapes. Lake‐research watersheds in Wisconsin, Minnesota, North Dakota, and Nebraska are used as an example of using the hydrologic‐land‐scapes concept to evaluate the effect of ground water on the degree of mineralization and major‐ion chemistry of lakes that lie within ground‐water flow systems.     

Assessing Parameter Uncertainty of a Semi‐Distributed Hydrology Model for a Shallow Aquifer Dominated Environmental System

This paper examines the performance of a semi‐distributed hydrology model (i.e., Soil and Water Assessment Tool [SWAT]) using Sequential Uncertainty FItting (SUFI‐2), generalized likelihood uncertainty estimation (GLUE), parameter solution (ParaSol), and particle swarm optimization (PSO). We applied SWAT to the Waccamaw watershed, a shallow aquifer dominated Coastal Plain watershed in the Southeastern United States (U.S.). The model was calibrated (2003‐2005) and validated (2006‐2007) at two U.S. Geological Survey gaging stations, using significant parameters related to surface hydrology, hydrogeology, hydraulics, and physical properties. SWAT performed best during intervals with wet and normal antecedent conditions with varying sensitivity to effluent channel shape and characteristics. In addition, the calibration of all algorithms depended mostly on Manning's n‐value for the tributary channels as the surface friction resistance factor to generate runoff. SUFI‐2 and PSO simulated the same relative probability distribution tails to those observed at an upstream outlet, while all methods (except ParaSol) exhibited longer tails at a downstream outlet. The ParaSol model exhibited large skewness suggesting a global search algorithm was less capable of characterizing parameter uncertainty. Our findings provide insights regarding parameter sensitivity and uncertainty as well as modeling diagnostic analysis that can improve hydrologic theory and prediction in complex watersheds. Editor's note : This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.     

AN EXPERIMENT IN DETERMINISTIC WATERSHED MODELING1

An experimental three-dimensional finite-difference watershed model in the form of a Fortran IV program was constructed. The model was an oversimplified one which divided the watershed volume into layers of cells which represented the overland flow, the vadose, and the phreatic zones. Water budget equations which utilized such formulas as Darcy's law and Manning's equation were applied to each interior cell. The resulting set of simultaneous equations was solved for heads at the end of successive time increments. This information was transformed to streamflow and other hydrologic output. Input was weather data, which effected appropriate adjustments in the cells representing the surface-water and vadose zones. After testing the model, it was concluded that this type of model is undesirably sensitive to cell size and length of time increment. In spite of the deficiencies of this primitive model, this general kind of approach to modeling seems promising, but it may be necessary to devise new transport equations which apply to more natural divisions of watersheds.     

Using SWAT to Model Streamflow in Two River Basins With Ground and Satellite Precipitation Data1

Abstract: Both ground rain gauge and remotely sensed precipitation (Next Generation Weather Radar – NEXRAD Stage III) data have been used to support spatially distributed hydrological modeling. This study is unique in that it utilizes and compares the performance of National Weather Service (NWS) rain gauge, NEXRAD Stage III, and Tropical Rainfall Measurement Mission (TRMM) 3B42 (Version 6) data for the hydrological modeling of the Middle Nueces River Watershed in South Texas and Middle Rio Grande Watershed in South Texas and northern Mexico. The hydrologic model chosen for this study is the Soil and Water Assessment Tool (SWAT), which is a comprehensive, physical‐based tool that models watershed hydrology and water quality within stream reaches. Minor adjustments to selected model parameters were applied to make parameter values more realistic based on results from previous studies. In both watersheds, NEXRAD Stage III data yields results with low mass balance error between simulated and actual streamflow (±13%) and high monthly Nash‐Sutcliffe efficiency coefficients (NS > 0.60) for both calibration (July 1, 2003 to December 31, 2006) and validation (2007) periods. In the Middle Rio Grande Watershed NEXRAD Stage III data also yield robust daily results (time averaged over a three‐day period) with NS values of (0.60‐0.88). TRMM 3B42 data generate simulations for the Middle Rio Grande Watershed of variable qualtiy (MBE = +13 to ?16%; NS = 0.38‐0.94; RMSE = 0.07‐0.65), but greatly overestimates streamflow during the calibration period in the Middle Nueces Watershed. During the calibration period use of NWS rain gauge data does not generate acceptable simulations in both watersheds. Significantly, our study is the first to successfully demonstrate the utility of satellite‐estimated precipitation (TRMM 3B42) in supporting hydrologic modeling with SWAT; thereby, potentially extending the realm (between 50°N and 50°S) where remotely sensed precipitation data can support hydrologic modeling outside of regions that have modern, ground‐based radar networks (i.e., much of the third world).     

Analyzing the Water Budget and Hydrological Characteristics and Responses to Land Use in a Monsoonal Climate River Basin in South China

Hydrological models have been increasingly used by hydrologists and water resource managers to understand natural processes and human activities that affect watersheds. In this study, we use the physically based model, Soil and Water Assessment Tool (SWAT), to investigate the hydrological processes in the East River Basin in South China, a coastal area dominated by monsoonal climate. The SWAT model was calibrated using 8-year (1973–1980) record of the daily streamflow at the basin outlet (Boluo station), and then validated using data collected during the subsequent 8 years (1981–1988). Statistical evaluation shows that SWAT can consistently simulate the streamflow of the East River with monthly Nash–Sutcliffe efficiencies of 0.93 for calibration and 0.90 for validation at the Boluo station. We analyzed the model simulations with calibrated parameters, presented the spatiotemporal distribution of the key hydrological components, and quantified their responses to different land uses. Watershed managers can use the results of this study to understand hydrological features and evaluate water resources of the East River in terms of sustainable development and effective management.     

Modeling Flow,Nutrient, and Sediment Delivery from a Large International Watershed Using a Field‐Scale SWAT Model

A large international watershed, the St. Clair‐Detroit River System, containing both extensive urban and agricultural areas, was modeled using the Soil and Water Assessment Tool (SWAT) model. The watershed, located in southeastern Michigan, United States, and southwestern Ontario, Canada, encompasses the St. Clair, Clinton, Detroit (DT), Sydenham (SY), Upper, and Lower Thames subwatersheds. The SWAT input data and model resolution (i.e., hydrologic response units, HRUs), were established to mimic farm boundaries, the first time this has been done for a watershed of this size. The model was calibrated (2007–2015) and validated (2001–2006) with a mix of manual and automatic methods at six locations for flow and water quality at various time scales. The model was evaluated using Nash–Sutcliffe efficiency and percent bias and was used to explore major water quality issues. We showed the importance of allowing key parameters to vary among subwatersheds to improve goodness of fit, and the resulting parameters were consistent with subwatershed characteristics. Agricultural sources in the Thames and SY subwatersheds and point sources from DT subwatershed were major contributors of phosphorus. Spatial distribution of phosphorus yields at HRU and subbasin levels identified locations for potential management targeting for both point and nonpoint sources and revealed that in some subwatersheds nonpoint sources are dominated by urban sources.     

Introduction to SWAT+, A Completely Restructured Version of the Soil and Water Assessment Tool

SWAT+ is a completely restructured version of the Soil and Water Assessment Tool (SWAT) that was developed to face present and future challenges in water resources modeling and management and to meet the needs of the worldwide user community. It is expected to improve code development and maintenance; support data availability, analysis, and visualization; and enhance the model's capabilities in terms of the spatial representation of elements and processes within watersheds. The most important change is the implementation of landscape units and flow and pollutant routing across the landscape. Also, SWAT+ offers more flexibility than SWAT in defining management schedules, routing constituents, and connecting managed flow systems to the natural stream network. To test the basic hydrologic function of SWAT+, it was applied to the Little River Experimental Watershed (Georgia) without enhanced overland routing and compared with previous models. SWAT+ gave similar results and inaccuracies as these models did for streamflow and water balance. Taking full advantage of the new capabilities of SWAT+ regarding watershed discretization and landscape and river interactions is expected to improve simulations in future studies. While many capabilities of SWAT have already been enhanced in SWAT+ and new capabilities have been added, the model will continue to evolve in response to advancements in scientific knowledge and the demands of the growing worldwide user community. Editor's note: This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.     

Hydrologic Calibration and Validation of SWAT in a Snow‐Dominated Rocky Mountain Watershed,Montana, U.S.A.1

Abstract: The Soil and Water Assessment Tool (SWAT) has been applied successfully in temperate environments but little is known about its performance in the snow‐dominated, forested, mountainous watersheds that provide much of the water supply in western North America. To address this knowledge gap, we configured SWAT to simulate the streamflow of Tenderfoot Creek (TCSWAT). Located in central Montana, TCSWAT represents a high‐elevation watershed with ～85% coniferous forest cover where more than 70% of the annual precipitation falls as snow, and runoff comes primarily from spring snowmelt. Model calibration using four years of measured daily streamflow, temperature, and precipitation data resulted in a relative error (RE) of 2% for annual water yield estimates, and mean paired deviations (Dv) of 36 and 31% and Nash‐Sutcliffe (NS) efficiencies of 0.90 and 0.86 for monthly and daily streamflow, respectively. Model validation was conducted using an additional four years of data and the performance was similar to the calibration period, with RE of 4% for annual water yields, Dv of 43% and 32%, and NS efficiencies of 0.90 and 0.76 for monthly and daily streamflow, respectively. An objective, regression‐based model invalidation procedure also indicated that the model was validated for the overall simulation period. Seasonally, SWAT performed well during the spring and early summer snowmelt runoff period, but was a poor predictor of late summer and winter base flow. The calibrated model was most sensitive to snowmelt parameters, followed in decreasing order of influence by the surface runoff lag, ground water, soil, and SCS Curve Number parameter sets. Model sensitivity to the surface runoff lag parameter reflected the influence of frozen soils on runoff processes. Results indicated that SWAT can provide reasonable predictions of annual, monthly, and daily streamflow from forested montane watersheds, but further model refinements could improve representation of snowmelt runoff processes and performance during the base flow period in this environment.     

INCREASED BASEFLOW IN IOWA OVER THE SECOND HALF OF THE 20TH CENTURY1

ABSTRACT: Historical trends in annual discharge characteristics were evaluated for 11 gauging stations located throughout Iowa. Discharge records from nine eight‐digit hydrologic unit code (HUC‐8) watersheds were examined for the period 1940 to 2000, whereas data for two larger river systems (Cedar and Des Moines Rivers) were examined for a longer period of record (1903 to 2000). In nearly all watersheds evaluated, annual base flow, annual minimum flow, and the annual base flow percentage significantly increased over time. Some rivers also exhibited increasing trends in total annual discharge, whereas only the Maquoketa River had significantly decreased annual maximum flows. Regression of stream discharge versus precipitation indicated that more precipitation is being routed into streams as base flow than as storm flow in the second half of the 20th Century. Reasons for the observed stream flow trends are hypothesized to include improved conservation practices, greater artificial drainage, increasing row crop production, and channel incision. Each of these reasons is consistent with the observed trends, and all are likely responsible to some degree in most watersheds.     

Effects of Spatial Distribution of Prairie Vegetation in an Agricultural Landscape on Curve Number Values

The curve number (CN) method is used to calculate runoff in many hydrologic models, including the Soil and Water Assessment Tool (SWAT). The CN method does not account for the spatial distribution of land cover types, an important factor controlling runoff patterns. The objective of this study was to empirically derive CN values that reflect the strategic placement of native prairie vegetation (NPV) within row crop agricultural landscapes. CNs were derived using precipitation and runoff data from a seven‐year period for 14 small watersheds in Iowa. The watersheds were planted with varying amounts of NPV located in different watershed positions. The least squares and asymptotic least squares methods (LSM) were used to derive CNs using an initial abstraction coefficient (λ) of 0.2 and 0.05. The CNs were verified using leave‐one‐out cross‐validation and adjustment for antecedent moisture conditions (AMC) was tested. The asymptotic method produced CN values for watersheds with NPV treatment that were 8.9 and 14.7% lower than watersheds with 100% row crop at λ = 0.2 and λ = 0.05, respectively. The derived CNs produced Nash‐Sutcliffe efficiency values ranging from 0.4 to 0.7 during validation. Our analyses show the CNs verified best for the asymptotic LSM, when using λ of 0.05 and adjusting for AMC. Further, comparison of derived CNs against an area weighted CN indicated that the placement of vegetation does impact the CN value. Editor's note : This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.     

Estimation of Daily Streamflow of Southeastern Coastal Plain Watersheds by Combining Estimated Magnitude and Sequence

Commonly used methods to predict streamflow at ungauged watersheds implicitly predict streamflow magnitude and temporal sequence concurrently. An alternative approach that has not been fully explored is the conceptualization of streamflow as a composite of two separable components of magnitude and sequence, where each component is estimated separately and then combined. Magnitude is modeled using the flow duration curve (FDC), whereas sequence is modeled by transferring streamflow sequence of gauged watershed(s). This study tests the applicability of the approach on watersheds ranging in size from about 25‐7,226 km² in Southeastern Coastal Plain (U.S.) with substantial surface storage of wetlands. A 19‐point regionalized FDC is developed to estimate streamflow magnitude using the three most selected variables (drainage area, hydrologic soil index, and maximum 24‐h precipitation with a recurrence interval of 100 years) by a greedy‐heuristic search process. The results of validation on four watersheds (Trent River, North Carolina: 02092500; Satilla River, Georgia: 02226500; Black River, South Carolina: 02136000; and Coosawhatchie River, South Carolina: 02176500) yielded Nash‐Sutcliffe efficiency values of 0.86‐0.98 for the predicted magnitude and 0.09‐0.84 for the predicted daily streamflow over a simulation period of 1960‐2010. The prediction accuracy of the method on two headwater watersheds at Santee Experimental Forest in coastal South Carolina was weak, but comparable to simulations by MIKE‐SHE.     

HYDROLOGICAL MODELING OF THE IROQUOIS RIVER WATERSHED USING HSPF AND SWAT1

ABSTRACT: The performance of two popular watershed scale simulation models — HSPF and SWAT — were evaluated for simulating the hydrology of the 5,568 km² Iroquois River watershed in Illinois and Indiana. This large, tile drained agricultural watershed provides distinctly different conditions for model comparison in contrast to previous studies. Both models were calibrated for a nine‐year period (1987 through 1995) and verified using an independent 15‐year period (1972 through 1986) by comparing simulated and observed daily, monthly, and annual streamflow. The characteristics of simulated flows from both models are mostly similar to each other and to observed flows, particularly for the calibration results. SWAT predicts flows slightly better than HSPF for the verification period, with the primary advantage being better simulation of low flows. A noticeable difference in the models' hydrologic simulation relates to the estimation of potential evapotranspiration (PET). Comparatively low PET values provided as input to HSPF from the BASINS 3.0 database may be a factor in HSPF's overestimation of low flows. Another factor affecting baseflow simulation is the presence of tile drains in the watershed. HSPF parameters can be adjusted to indirectly account for the faster subsurface flow associated with tile drains, but there is no specific tile drainage component in HSPF as there is in SWAT. Continued comparative studies such as this, under a variety of hydrologic conditions and watershed scales, provide needed guidance to potential users in model selection and application.     

HYDROLOGIC SIMULATION OF THE BRANDYWINE BASIN1

ABSTRACT: A deterministic hydrologic model, encompassing the hydrologic regime and all water uses, is developed by integrating empirical hydrologic relationships. The Brandywine Basin, located in southeastern Pennsylvania and northern Delaware, is used as an example to demonstrate this modeling effort. The basin is divided into 19 subwatersheds to account for the spatial variation of resource characteristics. The output of the model is the response of the hydrologic system to various inputs such as precipitation, land use characteristics and policy decisions. This modeling effort is applicable to watersheds similar to the Brandywine Basin in size, and once the model is developed and validated, can be applied continuously in the management and planning of water resources such as predicting the hydrologic effects of proposed projects and simulating hydrologic information.     

Evaluation of Existing and Modified Wetland Equations in the SWAT Model

The ability to accurately simulate flow and nutrient removal in treatment wetlands within an agricultural, watershed‐scale model is needed to develop effective plans for meeting nutrient reduction goals associated with protection of drinking water supplies and reduction of the Gulf of Mexico hypoxic zone. The objectives of this study were to incorporate new equations for wetland hydrology and nutrient removal in Soil and Water Assessment Tool (SWAT), compare model performance using original and improved equations, and evaluate the ramifications of errors in watershed and tile drain simulation on prediction of NO₃‐N dynamics in wetlands. The modified equations produced Nash‐Sutcliffe Efficiency values of 0.88 to 0.99 for daily NO₃‐N load predictions, and percent bias values generally less than 6%. However, statistical improvement over the original equations was marginal and both old and new equations provided accurate simulations. The new equations reduce the model's dependence on detailed monitoring data and hydrologic calibration. Additionally, the modified equations increase SWAT's versatility by incorporating a weir equation and an irreducible nutrient concentration and temperature coefficient. Model improvements enhance the utility of SWAT for simulating flow and nutrients in wetlands and other impoundments, although performance is limited by the accuracy of inflow and NO₃‐N predictions from the contributing watershed. Editor's note : This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.     

HYDROLOGIC MODELING AT THE WATERSHED SCALE USING NPSM1

ABSTRACT: The Nonpoint Source Model (NPSM) was chosen for nonpoint source pollutant modeling within three different watersheds. The first step in using NPSM, hydrologic calibration, is discussed here for three 8‐digit Hydrologic Unit Codes (HUCs) from the White River Basin in Indiana (Driftwood HUC), the Albemarle‐Pamlico River Basin in Virginia and North Carolina (Contentnea HUC), and the Apalachicola‐Chattahoochee‐Flint River Basin in Alabama, Georgia, and Florida (Ichawaynochaway HUC). Model predicted flows were compared statistically with USGS gauge data at the HUC outflow points for an uncalibrated and calibrated model run for the period from January 1, 1990, through December 31, 1992, and a validation run for the period from January 1, 1993, through December 31, 1995. Least squares regression of NPSM predicted flows versus USGS gauge data were 0.75, 0.44, and 0.69 for the calibration runs and 0.71, 0.69, and 0.64 for the validation runs in the Driftwood, Contentnea, and Ichawaynochaway HUCs, respectively. Nash Sutcliffe coefficient values were not as strong, ranging from ?0.66 to 0.45 for the calibration runs and 0.31 to 0.37 for the validation runs of the model. The Ichawaynochaway HUC proved the most difficult to calibrate indicating that the model may not be as useful in some geographic locations.