Modeling sediment and nitrogen export from a rural watershed in eastern Canada using the soil and water assessment tool

Watershed simulation models can be used to assess agricultural nonpoint-source pollution and for environmental planning and improvement projects. However, before application of any process-based watershed model, the model performance and reliability must be tested with measured data. The Soil and Water Assessment Tool version 2005 (SWAT2005) was used to model sediment and nitrogen loads from the Thomas Brook Watershed, which drains a 7.84 km rural landscape in the Annapolis Valley of Nova Scotia, Canada. The Thomas Brook SWAT model was comprised of 28 subbasins and 265 hydrologic response units, most of them containing agricultural land use, which is the main nonpoint nitrogen source in the watershed. Crop rotation schedules were incorporated into the model using field data collected within Agriculture and Agri-Food Canada's Watershed Evaluation of Beneficial Management Practices program. Model calibration (2004-2006) and validation (2007-2008) were performed on a monthly basis using continuous stream flow, sediment, and nitrogen export measurements. Model performance was evaluated using the coefficient of determination, Nash-Sutcliff efficiency (NSE), and percent bias (PBIAS) statistics. Study results show that the model performance was satisfactory (NSE > 0.4; > 0.5) for stream flow, sediment, nitrate-nitrogen, and total nitrogen simulations. Annual corn, barley, and wheat yields were also simulated well, with PBIAS values ranging from 0.3 to 7.2%. This evaluation of SWAT demonstrated that the model has the potential to be used as a decision support tool for agricultural watershed management in Nova Scotia.     

SENSITIVITY ANALYSIS,CALIBRATION, AND VALIDATIONS FOR A MULTISITE AND MULTIVARIABLE SWAT MODEL1

The ability of a watershed model to mimic specified watershed processes is assessed through the calibration and validation process. The Soil and Water Assessment Tool (SWAT) watershed model was implemented in the Beaver Reservoir Watershed of Northwest Arkansas. The objectives were to: (1) provide detailed information on calibrating and applying a multisite and multivariable SWAT model; (2) conduct sensitivity analysis; and (3) perform calibration and validation at three different sites for flow, sediment, total phosphorus (TP), and nitrate‐nitrogen (NO₃‐N) plus nitrite‐nitrogen (NO₂‐N). Relative sensitivity analysis was conducted to identify parameters that most influenced predicted flow, sediment, and nutrient model outputs. A multi objective function was defined that consisted of optimizing three statistics: percent relative error (RE), Nash‐Sutcliffe Coefficient (R_NS²), and coefficient of determination (R²). This function was used to successfully calibrate and validate a SWAT model of Beaver Reservoir Watershed at multi‐sites while considering multivariables. Calibration and validation of the model is a key factor in reducing uncertainty and increasing user confidence in its predictive abilities, which makes the application of the model effective. Information on calibration and validation of multisite, multivariable SWAT models has been provided to assist watershed modelers in developing their models to achieve watershed management goals.     

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).     

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.     

VALIDATION OF THE SWAT MODEL ON A LARGE RWER BASIN WITH POINT AND NONPOINT SOURCES1

ABSTRACT: The State of Texas has initiated the development of a Total Maximum Daily Load program in the Bosque River Watershed, where point and nonpoint sources of pollution are a concern. Soil Water Assessment Tool (SWAT) was validated for flow, sediment, and nutrients in the watershed to evaluate alternative management scenarios and estimate their effects in controlling pollution. This paper discusses the calibration and validation at two locations, Hico and Valley Mills, along the North Bosque River. Calibration for flow was performed from 1960 through 1998. Sediment and nutrient calibration was done from 1993 through 1997 at Hico and from 1996 through 1997 at Valley Mills. Model validation was performed for 1998. Time series plots and statistical measures were used to verify model predictions. Predicted values generally matched well with the observed values during calibration and validation (R²≥ 0.6 and Nash‐Suttcliffe Efficiency ≥ 0.5, in most instances) except for some underprediction of nitrogen during calibration at both locations and sediment and organic nutrients during validation at Valley Mills. This study showed that SWAT was able to predict flow, sediment, and nutrients successfully and can be used to study the effects of alternative management scenarios.     

Modeling the Spatially Varying Water Balance Processes in a Semiarid Mountainous Watershed of Idaho1

Stratton, Benjamin T., Venakataramana Sridhar, Molly M. Gribb, James P. McNamara, and Balaji Narasimhan, 2009. Modeling the Spatially Varying Water Balance Processes in a Semiarid Mountainous Watershed of Idaho. Journal of the American Water Resources Association (JAWRA) 45(6):1390‐1408. Abstract: The distributed Soil Water Assessment Tool (SWAT) hydrologic model was applied to a research watershed, the Dry Creek Experimental Watershed, near Boise Idaho to investigate its water balance components both temporally and spatially. Calibrating and validating SWAT is necessary to enable our understanding of the water balance components in this semiarid watershed. Daily streamflow data from four streamflow gages were used for calibration and validation of the model. Monthly estimates of streamflow during the calibration phase by SWAT produced satisfactory results with a Nash Sutcliffe coefficient of model efficiency 0.79. Since it is a continuous simulation model, as opposed to an event‐based model, it demonstrated the limited ability in capturing both streamflow and soil moisture for selected rain‐on‐snow (ROS) events during the validation period between 2005 and 2007. Especially, soil moisture was generally underestimated compared with observations from two monitoring pits. However, our implementation of SWAT showed that seasonal and annual water balance partitioning of precipitation into evapotranspiration, streamflow, soil moisture, and drainage was not only possible but closely followed the trends of a typical semiarid watershed in the intermountain west. This study highlights the necessity for better techniques to precisely identify and drive the model with commonly observed climatic inversion‐related snowmelt or ROS weather events. Estimation of key parameters pertaining to soil (e.g., available water content and saturated hydraulic conductivity), snow (e.g., lapse rates, melting), and vegetation (e.g., leaf area index and maximum canopy index) using additional field observations in the watershed is critical for better prediction.     

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.     

Modeling riverine nitrate export from an East-Central Illinois watershed using SWAT

Reliable water quality models are needed to forecast the water quality consequences of different agricultural nutrient management scenarios. In this study, the Soil and Water Assessment Tool (SWAT), version 2000, was applied to simulate streamflow, riverine nitrate (NO(3)) export, crop yield, and watershed nitrogen (N) budgets in the upper Embarras River (UER) watershed in east-central Illinois, which has extensive maize-soybean cultivation, large N fertilizer input, and extensive tile drainage. During the calibration (1994-2002) and validation (1985-1993) periods, SWAT simulated monthly and annual stream flows with Nash-Sutcliffe coefficients (E) ranging from 0.67 to 0.94 and R(2) from 0.75 to 0.95. For monthly and annual NO(3) loads, E ranged from -0.16 to 0.45 and R(2) from 0.36 to 0.74. Annual maize and soybean yields were simulated with relative errors ranging from -10 to 6%. The model was then used to predict the changes in NO(3) output with N fertilizer application rates 10 to 50% lower than original application rates in UER. The calibrated SWAT predicted a 10 to 43% decrease in NO(3) export from UER and a 6 to 38% reduction in maize yield in response to the reduction in N fertilizer. The SWAT model markedly overestimated NO(3) export during major wet periods. Moreover, SWAT estimated soybean N fixation rates considerably greater than literature values, and some simulated changes in the N cycle in response to fertilizer reduction seemed to be unrealistic. Improving these aspects of SWAT could lead to more reliable predictions in the water quality outcomes of nutrient management practices in tile-drained watersheds.     

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.     

EFFECTS OF STATSGO AND SSURGO AS INPUTS ON SWAT MODEL'S SNOWMELT SIMULATION1

ABSTRACT: Soil data comprise a basic input of SWAT (Soil and Water Assessment Tool) for a watershed application. For watersheds where site specific soil data are unavailable, the two U.S. Department of Agriculture (USDA) soil databases, the State Soil Geographic (STATSGO) and Soil Survey Geographic (SSURGO) databases, may be the best alternatives. Although it has been noted that SWAT models using the STATSGO and SSURGO data may give different simulation results for water, sediment, and agricultural chemical yields, information is scarce on the effects of using these two databases in predicting streamflows that are predominantly generated from melting snow in spring. The objective of this study was to assess the effects of using STATSGO versus SSURGO as an input for the SWAT model's simulation of the streamflows in the upper 45 percent of the Elm River watershed in eastern North Dakota. Designating the model as SWAT‐STATSGO when the STATSGO data were used and SWAT‐SSURGO when the SSURGO data were used, SWAT‐STATSGO and SWAT‐SSURGO were separately calibrated and validated using the observed daily streamflows. The results indicated that SWAT‐SSURGO provided an overall better prediction of the discharges than SWAT‐STATSGO, although both did a good and comparable job of predicting the high streamflows. However, SWAT‐STATSGO predicted the low streamflows more accurately and had a slightly better performance during the validation period. In addition, the discrepancies between the discharges predicted by these two SWAT models tended to be larger at upstream locations than at those farther downstream within the study area.     

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.     

Effect of Watershed Subdivision and Filter Width on SWAT Simulation of a Coastal Plain Watershed1

Cho, Jaepil, Richard R. Lowrance, David D. Bosch, Timothy C. Strickland, Younggu Her, and George Vellidis, 2010. Effect of Watershed Subdivision and Filter Width on SWAT Simulation of a Coastal Plain Watershed. Journal of the American Water Resources Association (JAWRA) 46(3):586-602. DOI: 10.1111/j.1752-1688.2010.00436.x Abstract: The Soil and Water Assessment Tool (SWAT) does not fully simulate riparian buffers, but has a simple filter function that is responsive to filter strip width (FILTERW). The objectives of this study were to (1) evaluate SWAT hydrology and water quality response to changes in watershed subdivision levels and different FILTERW configurations and (2) provide guidance for selecting appropriate watershed subdivision for model runs that include the riparian buffer feature through the FILTERW parameter. Watershed subdivision level is controlled by the critical source area (CSA) which defines the minimum drainage area required to form the origin of a stream. SWAT was calibrated on a 15.7 km² subdrainage within the Little River Experimental Watershed, Georgia. The calibrated parameter set was applied to 32 watershed configurations consisting of four FILTERW representations for each of eight CSA levels. Streamflow predictions were stable regardless of watershed subdivision and FILTERW configuration. Predicted sediment and nutrient loads from upland areas decreased as CSA increased when spatial variations of riparian buffers are considered. Sediment and nutrient yield at the watershed outlet was responsive to different combinations of CSA and FILTERW depending on selected in-stream processes. CSA ranges which provide stable sediment and nutrient yields at the watershed outlet was suggested for avoiding significant modifications in selected parameter set.     

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.     

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.     

Importance of Crop Yield in Calibrating Watershed Water Quality Simulation Tools1

Surendran Nair, Sujithkumar, Kevin W. King, Jonathan D. Witter, Brent L. Sohngen, and Norman R. Fausey, 2011. Importance of Crop Yield in Calibrating Watershed Water Quality Simulation Tools. Journal of the American Water Resources Association (JAWRA) 47(6):1285–1297. DOI: 10.1111/j.1752‐1688.2011.00570.x Abstract: Watershed‐scale water‐quality simulation tools provide a convenient and economical means to evaluate the environmental impacts of conservation practices. However, confidence in the simulation tool’s ability to accurately represent and capture the inherent variability of a watershed is dependent upon high quality input data and subsequent calibration. A four‐stage iterative and rigorous calibration procedure is outlined and demonstrated for Soil Water Analysis Tool (SWAT) using data from Upper Big Walnut Creek (UBWC) watershed in central Ohio, USA. The four stages and the sequence of their application were: (1) parameter selection, (2) hydrology calibration, (3) crop yield calibration, and (4) nutrient loading calibration. Following the calibration, validation was completed on a 10 year period. Nash‐Sutcliffe efficiencies for streamflow over the validation period were 0.5 for daily, 0.86 for monthly, and 0.87 for annual. Prediction efficiencies for crop yields during the validation period were 0.69 for corn, 0.54 for soybeans, and 0.61 for wheat. Nitrogen loading prediction efficiency was 0.66. Compared to traditional calibration approaches (no crop yield calibration), the four‐stage approach (with crop yield calibration) produced improved prediction efficiencies, especially for nutrient balances.     

The Influence of Forest Regrowth on the Stream Discharge in the North Carolina Piedmont Watersheds

This study focuses on the relationships of watershed runoff with historical land use/land cover (LULC) and climate trends. Over the 20th Century, LULC in the Southeast United States, particularly the North Carolina Piedmont, has evolved from an agriculture dominated to an extensively forested landscape with more recent localized urbanization. The regrowth of forest has an important influence on the hydrology of the region as it enhances ecosystem interaction with recent climate change. During 1920‐2009, the amount of precipitation in some parts of the North Carolina Piedmont forest regrowth area showed increasing trends without corresponding increments in runoff. We employed the Soil and Water Assessment Tool (SWAT) to backcast long‐term hydrologic behavior of watersheds in North Carolina with different LULC conditions: (1) LULC conversion from agricultural to forested area and (2) long‐term stable forested area. Comparing U.S. Geological Survey‐measured stream discharge with SWAT‐simulated stream discharge under the assumption of constant 2006 LULC, we found significant stream discharge underprediction by SWAT in two LULC conversion watersheds during the early simulation period (1920s) with differences gradually decreasing by the mid‐1970s. This model bias suggests that forest regrowth on abandoned agricultural land was a key factor contributing to mitigate the impact of increased precipitation on runoff due to increasing water consumption driven by changes in vegetation.     

Evaluation of a Watershed Model for Estimating Daily Flow Using Limited Flow Measurements1

Abstract: The Soil and Water Assessment Tool (SWAT) model was evaluated for estimation of continuous daily flow based on limited flow measurements in the Upper Oyster Creek (UOC) watershed. SWAT was calibrated against limited measured flow data and then validated. The Nash‐Sutcliffe model Efficiency (NSE) and mean relative error values of daily flow estimations were 0.66 and 15% for calibration, and 0.56 and 4% for validation, respectively. Also, further evaluation of the model’s estimation of flow at multiple locations was conducted with parametric paired t‐test and nonparametric sign test at a 95% confidence level. Among the five main stem stations, four stations were statistically shown to have good agreement between predicted and measured flows. SWAT underestimated the flow of the fifth main stem station possibly because of the existence of complex flood control measures near to the station. SWAT estimated the daily flow at one tributary station well, but with relatively large errors for the other two tributaries. The spatial pattern of predicted flows matched the measured ones well. Overall, it was concluded from the graphical comparisons and statistical analyses of the model results that SWAT was capable of reproducing continuous daily flows based on limited flow data as is the case in the UOC watershed.     

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).     

SWATmodel: A Multi‐Operating System,Multi‐Platform SWAT Model Package in R

The Soil and Water Assessment Tool (SWAT) model (Arnold et al., 1998) is a popular watershed management tool. Currently, the SWAT model, actively supported by the U.S. Department of Agriculture and Texas A&M, operates only on Microsoft^® Windows, which hinders modelers that use other operating systems (OS). This technical note introduces the Comprehensive R Archive Network (CRAN) distributed “SWATmodel” package which allows SWAT 2005 and 2012 to be widely distributed and run as a linear model‐like function on multiple OS and processor platforms. This allows researchers anywhere in the world using virtually any OS to run SWAT. In addition to simplifying the use of SWAT across computational platforms, the SWATmodel package allows SWAT modelers to utilize the analytical capabilities, statistical libraries, modeling tools, and programming flexibility inherent to R. The software allows watershed modelers to develop a simple hydrological watershed model conceptualization of the SWAT model and to obtain a first approximation of the minimum expected results a more complicated model should deliver. As a proof of concept, we test the SWAT model by initializing and calibrating 314 U.S. Geological Survey stream gages in the Chesapeake Bay watershed and present the results.     

HYDROLOGIC SIMULATION OF THE LITTLE WASHITA RIVER EXPERIMENTAL WATERSHED USING SWAT1

ABSTRACT: Precipitation and streamflow data from three nested subwatersheds within the Little Washita River Experimental Watershed (LWREW) in southwestern Oklahoma were used to evaluate the capabilities of the Soil and Water Assessment Tool (SWAT) to predict streamflow under varying climatic conditions. Eight years of precipitation and streamflow data were used to calibrate parameters in the model, and 15 years of data were used for model validation. SWAT was calibrated on the smallest and largest sub‐watersheds for a wetter than average period of record. The model was then validated on a third subwatershed for a range in climatic conditions that included dry, average, and wet periods. Calibration of the model involved a multistep approach. A preliminary calibration was conducted to estimate model parameters so that measured versus simulated yearly and monthly runoff were in agreement for the respective calibration periods. Model parameters were then fine tuned based on a visual inspection of daily hydrographs and flow frequency curves. Calibration on a daily basis resulted in higher baseflows and lower peak runoff rates than were obtained in the preliminary calibration. Test results show that once the model was calibrated for wet climatic conditions, it did a good job in predicting streamflow responses over wet, average, and dry climatic conditions selected for model validation. Monthly coefficients of efficiencies were 0.65, 0.86, and 0.45 for the dry, average, and wet validation periods, respectively. Results of this investigation indicate that once calibrated, SWAT is capable of providing adequate simulations for hydrologic investigations related to the impact of climate variations on water resources of the LWREW.