Validation of the SWAT Model on a Large River Basin With Point and Nonpoint Sources
01 Oct 2001-Journal of The American Water Resources Association (Blackwell Publishing Ltd)-Vol. 37, Iss: 5, pp 1169-1188
TL;DR: In this paper, the 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.
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.
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TL;DR: In this paper, the authors present guidelines for watershed model evaluation based on the review results and project-specific considerations, including single-event simulation, quality and quantity of measured data, model calibration procedure, evaluation time step, and project scope and magnitude.
Abstract: Watershed models are powerful tools for simulating the effect of watershed processes and management on soil and water resources. However, no comprehensive guidance is available to facilitate model evaluation in terms of the accuracy of simulated data compared to measured flow and constituent values. Thus, the objectives of this research were to: (1) determine recommended model evaluation techniques (statistical and graphical), (2) review reported ranges of values and corresponding performance ratings for the recommended statistics, and (3) establish guidelines for model evaluation based on the review results and project-specific considerations; all of these objectives focus on simulation of streamflow and transport of sediment and nutrients. These objectives were achieved with a thorough review of relevant literature on model application and recommended model evaluation methods. Based on this analysis, we recommend that three quantitative statistics, Nash-Sutcliffe efficiency (NSE), percent bias (PBIAS), and ratio of the root mean square error to the standard deviation of measured data (RSR), in addition to the graphical techniques, be used in model evaluation. The following model evaluation performance ratings were established for each recommended statistic. In general, model simulation can be judged as satisfactory if NSE > 0.50 and RSR < 0.70, and if PBIAS + 25% for streamflow, PBIAS + 55% for sediment, and PBIAS + 70% for N and P. For PBIAS, constituent-specific performance ratings were determined based on uncertainty of measured data. Additional considerations related to model evaluation guidelines are also discussed. These considerations include: single-event simulation, quality and quantity of measured data, model calibration procedure, evaluation time step, and project scope and magnitude. A case study illustrating the application of the model evaluation guidelines is also provided.
9,386 citations
Cites background or methods from "Validation of the SWAT Model on a L..."
...As a component of the CEAP-WAS, the Soil and Water Assessment Tool (SWAT2005; Arnold et al., 1998) was applied to the Leon River watershed in Texas....
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...Watershed - Model (Reference) Calibration Value Ranges Validation Value Ranges Statistic Daily Monthly Daily Monthly Iroquois River, Illinois and Indiana - SWAT (Singh et al., 2005) NSE 0.79 0.88 0.70 to 0.83 0.80 to 0.93 PBIAS Black Creek, Indiana - SWAT (Bracmort et al., 2006) NSE -- 0.73 to 0.84 -- 0.63 to 0.73 PBIAS Five USDA-ARS experimental watersheds - SWAT (Van Liew et al., 2007) NSE 0.30 to 0.76 0.48 to 0.90 -1.81 to 0.68 -2.50 to 0.89 PBIAS 2.9 to -91.7 -- 2.7 to -155.6 -- [a] Weekly values....
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...Most of the literature reviewed used daily and/or monthly time steps (Saleh et al., 2000; Santhi et al., 2001; Yuan et al., 2001; Sands et al., 2003; Van Liew et al., 2003; Chu and Shirmohammadi, 2004; Saleh and Du, 2004; Singh et al., 2004; Bracmort et al., 2006; Singh et al., 2005; Van Liew et…...
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...R2 ranges from 0 to 1, with higher values indicating less error variance, and typically values greater than 0.5 are considered acceptable (Santhi et al., 2001, Van Liew et al., 2003)....
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...Additional research work that supports the described findings includes that of Santhi et al. (2001), Van Liew et al. (2003), and Van Liew et al. (2007) using SWAT....
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TL;DR: The Soil and Water Assessment Tool (SWAT) model is a continuation of nearly 30 years of modeling efforts conducted by the USDA Agricultural Research Service (ARS) and has gained international acceptance as a robust interdisciplinary watershed modeling tool.
Abstract: The Soil and Water Assessment Tool (SWAT) model is a continuation of nearly 30 years of modeling efforts conducted by the USDA Agricultural Research Service (ARS). SWAT has gained international acceptance as a robust interdisciplinary watershed modeling tool as evidenced by international SWAT conferences, hundreds of SWAT-related papers presented at numerous other scientific meetings, and dozens of articles published in peer-reviewed journals. The model has also been adopted as part of the U.S. Environmental Protection Agency (USEPA) Better Assessment Science Integrating Point and Nonpoint Sources (BASINS) software package and is being used by many U.S. federal and state agencies, including the USDA within the Conservation Effects Assessment Project (CEAP). At present, over 250 peer-reviewed published articles have been identified that report SWAT applications, reviews of SWAT components, or other research that includes SWAT. Many of these peer-reviewed articles are summarized here according to relevant application categories such as streamflow calibration and related hydrologic analyses, climate change impacts on hydrology, pollutant load assessments, comparisons with other models, and sensitivity analyses and calibration techniques. Strengths and weaknesses of the model are presented, and recommended research needs for SWAT are also provided.
2,357 citations
Posted Content•
TL;DR: The Soil and Water Assessment Tool (SWAT) model is a continuation of nearly 30 years of modeling efforts conducted by the U.S. Department of Agriculture (USDA), Agricultural Research Service.
Abstract: The Soil and Water Assessment Tool (SWAT) model is a continuation of nearly 30 years of modeling efforts conducted by the U.S. Department of Agriculture (USDA), Agricultural Research Service. SWAT has gained international acceptance as a robust interdisciplinary watershed modeling tool, as evidenced by international SWAT conferences, hundreds of SWAT-related papers presented at numerous scientific meetings, and dozens of articles published in peer-reviewed journals. The model has also been adopted as part of the U.S. Environmental Protection Agency's BASINS (Better Assessment Science Integrating Point & Nonpoint Sources) software package and is being used by many U.S. federal and state agencies, including the USDA within the Conservation Effects Assessment Project. At present, over 250 peer-reviewed, published articles have been identified that report SWAT applications, reviews of SWAT components, or other research that includes SWAT. Many of these peer-reviewed articles are summarized here according to relevant application categories such as streamflow calibration and related hydrologic analyses, climate change impacts on hydrology, pollutant load assessments, comparisons with other models, and sensitivity analyses and calibration techniques. Strengths and weaknesses of the model are presented, and recommended research needs for SWAT are provided.
2,274 citations
TL;DR: The SWAT-CUP tool as discussed by the authors is a semi-distributed river basin model that requires a large number of input parameters, which complicates model parameterization and calibration, and is used to provide statistics for goodness-of-fit.
Abstract: SWAT (Soil and Water Assessment Tool) is a comprehensive, semi-distributed river basin model that requires a large number of input parameters, which complicates model parameterization and calibration. Several calibration techniques have been developed for SWAT, including manual calibration procedures and automated procedures using the shuffled complex evolution method and other common methods. In addition, SWAT-CUP was recently developed and provides a decision-making framework that incorporates a semi-automated approach (SUFI2) using both manual and automated calibration and incorporating sensitivity and uncertainty analysis. In SWAT-CUP, users can manually adjust parameters and ranges iteratively between autocalibration runs. Parameter sensitivity analysis helps focus the calibration and uncertainty analysis and is used to provide statistics for goodness-of-fit. The user interaction or manual component of the SWAT-CUP calibration forces the user to obtain a better understanding of the overall hydrologic processes (e.g., baseflow ratios, ET, sediment sources and sinks, crop yields, and nutrient balances) and of parameter sensitivity. It is important for future calibration developments to spatially account for hydrologic processes; improve model run time efficiency; include the impact of uncertainty in the conceptual model, model parameters, and measured variables used in calibration; and assist users in checking for model errors. When calibrating a physically based model like SWAT, it is important to remember that all model input parameters must be kept within a realistic uncertainty range and that no automatic procedure can substitute for actual physical knowledge of the watershed.
2,200 citations
TL;DR: In this paper, a meta-analysis of performance data reported in recent peer-reviewed literature for three widely published watershed-scale models (SWAT, HSPF, WARMF), and one field-scale model (ADAPT) is performed.
Abstract: Performance measures (PMs) and corresponding performance evaluation criteria (PEC) are important aspects of calibrating and validating hydrologic and water quality models and should be updated with advances in modeling science. We synthesized PMs and PEC from a previous special collection, performed a meta-analysis of performance data reported in recent peer-reviewed literature for three widely published watershed-scale models (SWAT, HSPF, WARMF), and one field-scale model (ADAPT), and provided guidelines for model performance evaluation. Based on the synthesis, meta-analysis, and personal modeling experiences, we recommend coefficient of determination (R2; in conjunction with gradient and intercept of the corresponding regression line), Nash Sutcliffe efficiency (NSE), index of agreement (d), root mean square error (RMSE; alongside the ratio of RMSE and standard deviation of measured data, RSR), percent bias (PBIAS), and several graphical PMs to evaluate model performance. We recommend that model performance can be judged satisfactory for flow simulations if monthly R2 0.70 and d 0.75 for field-scale models, and daily, monthly, or annual R2 0.60, NSE 0.50, and PBIAS ≤ ±15% for watershed-scale models. Model performance at the watershed scale can be evaluated as satisfactory if monthly R2 0.40 and NSE 0.45 and daily, monthly, or annual PBIAS ≤ ±20% for sediment; monthly R20.40 and NSE 0.35 and daily, monthly, or annual PBIAS ≤ ±30% for phosphorus (P); and monthly R2 0.30 and NSE 0.35 and daily, monthly, or annual PBIAS ≤ ±30% for nitrogen (N). For RSR, we recommend that previously published PEC be used as detailed in this article. We also recommend that these PEC be used primarily for the four models for which there were adequate data, and used only with caution for other models. These PEC can be adjusted within acceptable bounds based on additional considerations, such as quality and quantity of available measured data, spatial and temporal scales, and project scope and magnitude, and updated based on the framework presented herein. This initial meta-analysis sets the stage for more comprehensive meta-analysis to revise PEC as new PMs and more data become available.
1,213 citations
Cites methods from "Validation of the SWAT Model on a L..."
...Past literature on model PMs includes Willmott (1984), Loague and Green (1991), ASCE (1993), Refsgaard (1997), Gupta et al. (1998), Legates and McCabe (1999), Santhi et al. (2001), Krause (2005), McCuen et al. (2006), Engel et al. (2007), and Moriasi et al. (2007)....
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...Many studies (e.g., Santhi et al., 2001; VazquezAmabile and Engel, 2005; Reungsang et al., 2010; Pai et al., 2011; Douglas-Mankin et al., 2013) have used NSE to evaluate model performances for various output responses (e.g., flow, sediment, N, P, crop yields, etc.) using different models (MIKE-SHE,…...
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...Selection and use of PEC also varies by study and by model (Santhi et al., 2001; Van Liew et al., 2007; Parajuli et al., 2009; Benett et al., 2013, Daggupati et al., 2014; Harmel et al., 2014)....
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References
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TL;DR: In this article, the principles governing the application of the conceptual model technique to river flow forecasting are discussed and the necessity for a systematic approach to the development and testing of the model is explained and some preliminary ideas suggested.
19,601 citations
TL;DR: A conceptual, continuous time model called SWAT (Soil and Water Assessment Tool) was developed to assist water resource managers in assessing the impact of management on water supplies and nonpoint source pollution in watersheds and large river basins as discussed by the authors.
Abstract: A conceptual, continuous time model called SWAT (Soil and Water Assessment Tool) was developed to assist water resource managers in assessing the impact of management on water supplies and nonpoint source pollution in watersheds and large river basins. The model is currently being utilized in several large area projects by EPA, NOAA, NRCS and others to estimate the off-site impacts of climate and management on water use, nonpoint source loadings, and pesticide contamination. Model development, operation, limitations, and assumptions are discussed and components of the model are described. In Part II, a GIS input/output interface is presented along with model validation on three basins within the Upper Trinity basin in Texas.
6,674 citations
01 Jan 1980
1,558 citations
Journal Article•
981 citations
01 Jan 1984
TL;DR: A mathematical model developed to determine the relationship between soil erosion and soil productivity throughout the U.S. and Hawaii indicates that EPIC is capable of simulating erosion and crop growth realistically.
Abstract: ABSTRACT A mathematical model called EPIC (Erosion-Productivity Impact Calculator) was developed to determine the relationship between soil erosion and soil productivity throughout the U.S. EPIC continuously simulates the processes involved simultaneously and realistically, using a daily time step and readily available inputs. Since erosion can be relatively slow process, EPIC is capable of simulating hundreds of years if necessary. EPIC is generally applicable, computationally efficient, and capable of computing the effects of management changes on outputs. The model must be comprehensive to define the erosion-productivity relationship adequately. EPIC is composed of physically-based components for simulating erosion, plant growth, and related processes and economic components for assessing the cost of erosion, determining optimal management strategies, etc. The EPIC components include weather simulation, hydrology, erosion-sedimentation, nutrient cycling, plant growth, tillage, soil temperature, economics, and plant environment control. Typical results are presented for 15 of the 163 tests performed in the continental U.S. and Hawaii. These results generally indicate that EPIC is capable of simulating erosion and crop growth realistically.
958 citations