EFFECT OF WATERSHED SUBDIVISION ON SWAT FLOW,SEDIMENT, AND NUTRIENT PREDICTIONS1

ABSTRACT: The size, scale, and number of subwatersheds can affect a watershed modeling process and subsequent results. The objective of this study was to determine the appropriate level of subwatershed division for simulating flow, sediment, and nutrients over 30 years for four Iowa watersheds ranging in size from 2,000 to 18,000 km² with the Soil and Water Assessment Tool (SWAT) model. The results of the analysis indicated that variation in the total number of subwatersheds had very little effect on streamflow. However, the opposite result was found for sediment, nitrate, and inorganic P; the optimal threshold subwatershed sizes, relative to the total drainage area for each watershed, required to adequately predict these three indicators were found to be around 3, 2, and 5 percent, respectively. Decreasing the size of the subwatersheds below these threshold levels does not significantly affect the predicted levels of these environmental indicators. These threshold subwatershed sizes can be used to optimize input data preparation requirements for SWAT analyses of other watersheds, especially those within a similar size range. The fact that different thresholds emerged for the different indicators also indicates the need for SWAT users to assess which indicators should have the highest priority in their analyses.     

WATER QUALITY MODEL OUTPUT UNCERTAINTY AS AFFECTED BY SPATIAL RESOLUTION OF INPUT DATA1

ABSTRACT: Resolution of the input GIS data used to parameterize distributed‐parameter hydrologic/water quality models may affect uncertainty in model outputs and impact the subsequent application of model results in watershed management. In this study we evaluated the impact of varying spatial resolutions of DEM, land use, and soil data (30 × 30 m, 100 × 100 m, 150 × 150 m, 200 × 200 m, 300 × 300 m, 500 × 500 m, and 1,000 × 1,000 m) on the uncertainty of SWAT predicted flow, sediment, NO₃‐N, and TP transport. Inputs included measured hydrologic, meteorological, and watershed characteristics as well as water quality data from the Moores Creek watershed in Washington County, Arkansas. The SWAT model output was most affected by input DEM data resolution. A coarser DEM data resolution resulted in decreased representation of watershed area and slope and increased slope length. Distribution of pasture, forest, and urban areas within the watershed was significantly affected at coarser resolution of land use and resulted in significant uncertainty in predicted sediment, NO₃‐N, and TP output. Soils data resolution had no significant effect on flow and NO₃‐N predictions; however, sediment was overpredicted by 26 percent, and TP was underpredicted by 26 percent at 1,000 m resolution. This may be due to change in relative distribution of various hydrologic soils groups (HSGs) in the watershed. Minimum resolution for input GIS data to achieve less than 10 percent model output error depended upon the output variable of interest. For flow, sediment, NO₃‐N, and TP predictions, minimum DEM data resolution should range from 30 to 300 m, whereas minimum land use and soils data resolution should range from 300 to 500 m.     

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

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

APPLICATION OF AN ENVIRONMENTAL AND ECONOMIC MODELING SYSTEM FOR WATERSHED ASSESSMENTS1

ABSTRACT: A National Pilot Project (NPP) on Livestock and the Environment was initiated in 1992 to help provide solutions to environmental problems associated with livestock production. A major development of the NPP was the Comprehensive Economic and Environmental Optimization Tool‐Livestock and Poultry (CEEOT‐LP), an integrated modeling system designed to produce economic and environmental indicators for alternative policy scenarios applied to intensive livestock production watersheds. The system consists of a farm‐level economic model (FEM) and two environmental models: the field‐scale APEX model and the watershed‐level SWAT model. To date, CEEOT‐LP has been applied to two watersheds in Texas and one in Iowa. Predicted reductions in P losses for two P‐based manure application rate scenarios, relative to baseline conditions, ranged from ?4 to ?54 percent across the three watersheds; however, N loss impacts ranged from a decrease of 34 percent to an increase of 79 percent. For five other alternative scenarios that were simulated for only one watershed, N and P loss impacts ranged between a reduction of 78 percent to an increase of 20 percent. Aggregate watershed‐level economic impacts of the seven scenarios spanned a spectrum of a 27 percent decrease to a 25 percent increase in profit, relative to the baseline.     

Large‐Scale Fine‐Resolution Hydrological Modeling Using Parameter Regionalization in the Missouri River Basin

This study simulated crop and water yields in the Missouri River Basin (MRB; 1,371,000 km²), one of the largest river basins in the United States, using the Soil and Water Assessment Tool (SWAT) at a fine resolution of 12‐digit Hydrological Unit Codes (HUCs) using the regionalization calibration approach. Very few studies have simulated the entire MRB, and those that have developed were at a coarser resolution of 8‐digit HUCs and were minimally calibrated. The MRB was first divided into three subbasins and was further divided into eleven regions. A “head watershed” was selected in each region and was calibrated for crop and water yields. The parameters from the calibrated head watershed were extrapolated to other subwatersheds in the region to complete comprehensive spatial calibration. The simulated crop yields at the head watersheds were in close agreement with observed crop yields. Spatial validation of the aggregated crop yields resulted in reasonable predictions for all crops except dryland corn in a few regions. Simulated and observed water yields in head watersheds and also in the validation locations were in close agreement in naturalized streams and poor agreement in streams with high groundwater‐surface water interactions and/or reservoirs found upstream of the gauges. Overall, the SWAT model was able to reasonably capture the hydrological and crop growth dynamics occurring in the basin despite some limitations.     

Modeling of Sediment Yield From Anjeni-Gauged Watershed,Ethiopia Using SWAT Model1

Setegn, Shimelis G., Bijan Dargahi, Ragahavan Srinivasan, and Assefa M. Melesse, 2010. Modeling of Sediment Yield From Anjeni-Gauged Watershed, Ethiopia Using SWAT Model. Journal of the American Water Resources Association (JAWRA) 46(3):514-526. DOI: 10.1111/j.1752-1688.2010.00431.x Abstract: The Soil and Water Assessment Tool (SWAT) was tested for prediction of sediment yield in Anjeni-gauged watershed, Ethiopia. Soil erosion and land degradation is a major problem on the Ethiopian highlands. The objectives of this study were to evaluate the performance and applicability of SWAT model in predicting monthly sediment yield and assess the impacts of subbasin delineation and slope discretization on the prediction of sediment yield. Ten years monthly meteorological, flow and sediment data were used for model calibration and validation. The annual average measured sediment yield was 24.6 tonnes/ha. The annual average simulated sediment yield was 27.8 and 29.5 tones/ha for calibration and validation periods, respectively. The study found that the observed values showed good agreement with the simulated sediment yield with Nash-Sutcliffe efficiency (NSE) = 0.81, percent bias (PBIAS) = 28%, RMSE-observations standard deviation ratio (RSR) = 0.23, and coefficient of determination (R²) = 0.86 for calibration and NSE = 0.79, PBIAS = 30%, RSR = 0.29, and R² = 0.84 for validation periods. The model can be used for further analysis of different management scenarios that could help different stakeholders to plan and implement appropriate soil and water conservation strategies.     

SENSITIVITY CONSIDERATIONS WHEN MODELING HYDROLOGIC PROCESSES WITH DIGITAL ELEVATION MODEL1

ABSTRACT: The purpose of this paper is to investigate the sensitivity of a hydrologic models to the type of DEM used. This was done while modeling basin water quality with 1:24,000 and 1:250,000 U.S. Geological Survey DEMs as input to model hydro‐logical processes. The manner in which the model results were sensitive to the choice of raster cell size (scale) is investigated in this study. The Broadhead watershed, located in New Jersey, USA, was chosen as a study area. Curve numbers were estimated by a trial and error to match simulated and observed total discharge. Monthly runoff for the watershed was used in the calibration process. Higher runoff volumes were simulated by the model when the 1:24,000 DEM were used as input data, probably due to the finer resolution which simulated increased average slope and hence higher estimated runoff from the watershed. As the simulated slope of the watershed is flatten with the 1:250,000 DEM, the response of stream flow was delayed and simulated less runoff volume.     

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.     

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.     

LOS ALAMOS FOREST FIRE IMPACT MODELING1

ABSTRACT: A controlled burn at Bandelier National Monument got out of control and burned about 43,000 acres (17,400 hectares) near Los Alamos, New Mexico, in May 2000. The wildfire caused dramatic changes in infiltration capacity and wettability of soils in many of the watersheds above Los Alamos National Laboratory (LANL) and destroyed the duff layer, dramatically reducing the interception and infiltration capacity of the formerly forested watersheds. These sudden changes in basin hydrology necessitated a rapid assessment of hydrology and hydraulics for the canyons running through LANL property to evaluate flood risk, plan emergency flood protection measures, and assess potential sediment and actinide transport. This paper presents the results of hydrologic and hydraulic modeling of Los Alamos Canyon following the wildfire. The large scale modeling effort, with over 13,000 cross sections for the hydraulic model (5,000 for Los Alamos Canyon, 8,000 for Guaje Canyon), relied heavily on a geographic information system (GIS) for model input and floodplain delineation. The HEC‐geoRAS model provided good integration between the hydraulic model (HEC‐RAS, Version 3.0.1) and the GIS (ArcView, v. 3.3). These modeling results are being used in drainage master planning efforts at LANL and in the development of sediment transport models using HEC‐6T. Sediment transport modeling results will be used to develop actinide transport models for the canyons at LANL.     

ROLE OF WATERSHED SUBDIVISION ON MODELING THE EFFECTIVENESS OF BEST MANAGEMENT PRACTICES WITH SWAT1

Distributed parameter watershed models are often used for evaluating the effectiveness of various best management practices (BMPs). Streamflow, sediment, and nutrient yield predictions of a watershed model can be affected by spatial resolution as dictated by watershed subdivision. The objectives of this paper are to show that evaluation of BMPs using a model is strongly linked to the level of watershed subdivision; to suggest a methodology for identifying an appropriate subdivision level; and to examine the efficacy of different BMPs at field and watershed scales. In this study, the Soil and Water Assessment Tool (SWAT) model was calibrated and validated for streamflow, sediment, and nutrient yields at the outlet of the Dreisbach (623 ha) and Smith Fry (730 ha) watersheds in Maumee River Basin, Indiana. Grassed waterways, grade stabilization structures, field borders, and parallel terraces are the BMPs that were installed in the study area in the 1970s. Sediment and nutrient outputs from the calibrated model were compared at various watershed subdivision levels, both with and without implementation of these BMPs. Results for the study watersheds indicated that evaluation of the impacts of these BMPs on sediment and nutrient yields was very sensitive to the level of subdivision that was implemented in SWAT. An optimal watershed subdivision level for representation of the BMPs was identified through numerical simulations. For the study watersheds, it would appear that the average subwatershed area corresponding to approximately 4 percent of total watershed area is needed to represent the influence of these BMPs when using the SWAT model.     

Integration of SWAT and HSPF for Simulation of Sediment Sources in Legacy Sediment‐Impacted Agricultural Watersheds

A total maximum daily load for the Chesapeake Bay requires reduction in pollutant load from sources within the Bay watersheds. The Conestoga River watershed has been identified as a major source of sediment load to the Bay. Upland loads of sediment from agriculture are a concern; however, a large proportion of the sediment load in the Conestoga River has been linked to scour of legacy sediment associated with historic millpond sites. Clarifying this distinction and identifying specific segments associated with upland vs. channel sources has important implications for future management. In order to address this important question, we combined the strengths of two widely accepted watershed management models — Soil and Water Assessment Tool (SWAT) for upland agricultural processes, and Hydrologic Simulation Program FORTRAN (HSPF) for instream fate and transport — to create a novel linked modeling system to predict sediment loading from critical sources in the watershed including upland and channel sources, and to aid in targeted implementation of management practices. The model indicates approximately 66% of the total sediment load is derived from instream sources, in agreement with other studies in the region and can be used to support identification of these channel source segments vs. upland source segments, further improving targeted management. The innovated linked SWAT‐HSPF model implemented in this study is useful for other watersheds where both upland agriculture and instream processes are important sources of sediment load.     

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.     

Effects of soil data resolution on SWAT model stream flow and water quality predictions

The prediction accuracy of agricultural nonpoint source pollution models such as Soil and Water Assessment Tool (SWAT) depends on how well model input spatial parameters describe the characteristics of the watershed. The objective of this study was to assess the effects of different soil data resolutions on stream flow, sediment and nutrient predictions when used as input for SWAT. SWAT model predictions were compared for the two US Department of Agriculture soil databases with different resolution, namely the State Soil Geographic database (STATSGO) and the Soil Survey Geographic database (SSURGO). Same number of sub-basins was used in the watershed delineation. However, the number of HRUs generated when STATSGO and SSURGO soil data were used is 261 and 1301, respectively. SSURGO, with the highest spatial resolution, has 51 unique soil types in the watershed distributed in 1301 HRUs, while STATSGO has only three distributed in 261 HRUS. As a result of low resolution STATSGO assigns a single classification to areas that may have different soil types if SSURGO were used. SSURGO included Hydrologic Response Units (HRUs) with soil types that were generalized to one soil group in STATSGO. The difference in the number and size of HRUs also has an effect on sediment yield parameters (slope and slope length). Thus, as a result of the discrepancies in soil type and size of HRUs stream flow predicted was higher when SSURGO was used compared to STATSGO. SSURGO predicted less stream loading than STATSGO in terms of sediment and sediment-attached nutrients components, and vice versa for dissolved nutrients. When compared to mean daily measured flow, STATSGO performed better relative to SSURGO before calibration. SSURGO provided better results after calibration as evaluated by R(2) value (0.74 compared to 0.61 for STATSGO) and the Nash-Sutcliffe coefficient of Efficiency (NSE) values (0.70 and 0.61 for SSURGO and STATSGO, respectively) although both are in the same satisfactory range. Modelers need to weigh the benefits before selecting the type of data resolution they are going to use depending on the watershed size and level of accuracy required because more effort is required to prepare and calibrate the model when a fine resolution soil data is used.     

RUNOFF VOLUME ESTIMATION USING GIS TECHNIQUES1

ABSTRACT: Rainfall runoff of six watersheds was modeled via the Soil Conservation Service runoff curve number model in two ways: conventionally (manually) and via a geographic information system (GIS). Input data (elevation, soils, and landcover) were digital for the latter method. In contrast to previous studies, the GIS was ised for all phases of the modeling process, including watershed delineation and routing of runoff. A comparison between the two methods was consistent with results reported by others and indicates that the use of a GIS is an acceptable alternative to the conventional method for watersheds lacking relatively flat terrain. Given this limitation, the GIS method may prove advantageous over manual methods when study areas are large or numerous, runoff is modeled repetitively, alternative landcover scenarios are explored, or a digital database already exists for the study area.     

Augmenting Watershed Model Calibration with Incorporation of Ancillary Data Sources and Qualitative Soft Data Sources

Watershed simulation models such as the Soil & Water Assessment Tool (SWAT) can be calibrated using “hard data” such as temporal streamflow observations; however, users may find upon examination of model outputs, that the calibrated models may not reflect actual watershed behavior. Thus, it is often advantageous to use “soft data” (i.e., qualitative knowledge such as expected denitrification rates that observed time series do not typically exist) to ensure that the calibrated model is representative of the real world. The primary objective of this study is to evaluate the efficacy of coupling SWAT‐Check (a post‐evaluation framework for SWAT outputs) and IPEAT‐SD (Integrated Parameter Estimation and Uncertainty Analysis Tool‐Soft & hard Data evaluation) to constrain the bounds of soft data during SWAT auto‐calibration. IPEAT‐SD integrates 59 soft data variables to ensure SWAT does not violate physical processes known to occur in watersheds. IPEAT‐SD was evaluated for two case studies where soft data such as denitrification rate, nitrate attributed from subsurface flow to total discharge ratio, and total sediment loading were used to conduct model calibration. Results indicated that SWAT model outputs may not satisfy reasonable soft data responses without providing pre‐defined bounds. IPEAT‐SD provides an efficient and rigorous framework for users to conduct future studies while considering both soft data and traditional hard information measures in watershed modeling.     

Evaluation of SWAT Impoundment Modeling Methods in Water and Sediment Simulations

Worldwide studies show 80%–90% of all sediments eroded from watersheds is trapped within river networks such as reservoirs, ponds, and wetlands. To represent the impact of impoundments on sediment routing in watershed modeling, Soil and Water Assessment Tool (SWAT) developers recommend to model reservoirs, ponds, and wetlands using impoundment tools (ITs). This study evaluates performance of SWAT ITs in the modeling of a small, agricultural watershed dominated by lakes and wetlands. The study demonstrates how to incorporate impoundments into the SWAT model, and discusses and evaluates involved parameters. The study then recommends an appropriate calibration sequence, i.e., landscape parameters calibration, followed by pond/wetlands calibration, then channel parameter calibrations, and lastly, reservoir parameter calibration. Results of this study demonstrate not following SWAT recommendation regarding modeling water land use as an impoundment depreciates SWAT performance, and may lead to misplaced calibration efforts and model over‐calibration. Further, the chosen method to model impoundments’ outflow significantly impacts sediment loads in the watershed, while streamflow simulation is not very sensitive. This study also allowed calculation of mass accumulation rates in modeled impoundments where the annual mass accumulation rate in wetlands (2.3 T/ha/yr) was 39% higher than mass accumulation rate in reservoirs (1.4 T/ha/yr).     

WATER QUALITY MODELING OF ALTERNATIVE AGRICULTURAL SCENARIOS IN THE U.S. CORN BELT1

ABSTRACT: Simulated water quality resulting from three alternative future land‐use scenarios for two agricultural watersheds in central Iowa was compared to water quality under current and historic land use/land cover to explore both the potential water quality impact of perpetuating current trends and potential benefits of major changes in agricultural practices in the U.S. Corn Belt. The Soil Water Assessment Tool (SWAT) was applied to evaluate the effect of management practices on surface water discharge and annual loads of sediment and nitrate in these watersheds. The agricultural practices comprising Scenario 1, which assumes perpetuation of current trends (conversion to conservation tillage, increase in farm size and land in production, use of currently‐employed Best Management Practices (BMPs)) result in simulated increased export of nitrate and decreased export of sediment relative to the present. However, simulations indicate that the substantial changes in agricultural practices envisioned in Scenarios 2 and 3 (conversion to conservation tillage, strip intercropping, rotational grazing, conservation set‐asides and greatly extended use of best management practices (BMPs) such as riparian buffers, engineered wetlands, grassed waterways, filter strips and field borders) could potentially reduce current loadings of sediment by 37 to 67 percent and nutrients by 54 to 75 percent. Results from the study indicate that major improvements in water quality in these agricultural watersheds could be achieved if such environmentally‐targeted agricultural practices were employed. Traditional approaches to water quality improvement through application of traditional BMPs will result in little or no change in nutrient export and minor decreases in sediment export from Corn Belt watersheds.     

INFLUENCES OF SOIL DATASET RESOLUTION ON HYDROLOGIC MODELING1

ABSTRACT: Soils represent a fundamental abiotic parameter in defining the characteristics of an ecosystem. The U.S. Department of Agriculture (USDA) Natural Resources Conservation Service (NRCS) produces the most detailed digital spatial soil datasets that are publicly available. The Soil Survey Geographic (SSURGO) database contains basic attributes for the continuous coverage of soils across the United States. In its standard format, the SSURGO database is incompatible for use within the ArcView Soil and Water Assessment Tool (SWAT). A modified version of the State Soil and Geographic (STATSGO) database is the template soils dataset used by ArcView SWAT. This paper presents the methodology and development of a SSURGO database preprocessor extension for the ArcView SWAT model. A case study for the Upper Sabinal River Watershed near Uvalde, Texas, is given. Results indicate that hydro‐logic output parameter differences occur when comparing the STATSGO and SSURGO database information in the ArcView SWAT model under identical modeling conditions. Specifically, the SSURGO model produced a greater daily mean water yield with evapotranspiration and surface runoff being found consistently lower across the watershed. The most likely causes assigned to this phenomenon were higher percolation and resulting ground water return flow values due to significantly larger saturated hydraulic conductivity values associated with the SSURGO 2.x database.