Ronald L. Bingner

Bio: Ronald L. Bingner is an academic researcher from Agricultural Research Service. The author has contributed to research in topics: Watershed & Surface runoff. The author has an hindex of 28, co-authored 106 publications receiving 9978 citations. Previous affiliations of Ronald L. Bingner include United States Department of Agriculture.

Model Evaluation Guidelines for Systematic Quantification of Accuracy in Watershed Simulations

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.

Comparison of green-ampt and curve number methods on goodwin creek watershed using swat

Abstract: Two methods of simulating excess rainfall were compared on a large basin with multiple rain gages. The SCS daily curve number method (CN) was compared with the Green-Ampt Mein-Larson (GAML) method on the Goodwin Creek Watershed (GCW). GCW is 21.3 km2 in area and has 32 rain gages located within and surrounding the watershed. The model used was the Soil and Water Assessment Tool (SWAT). SWAT is a comprehensive watershed scale model developed to simulate management impacts on water, sediment, and chemical yields for ungaged basins. SWAT was modified to accept breakpoint rainfall data and route streamflow on a sub-daily time-step. Eight years of measured climatic data were used in the study. Simulated and measured streamflow at the watershed outlet were evaluated. Results were not calibrated. Monthly model efficiencies were 0.84 for CN and 0.69 for GAML. The use of a sub-daily routing technique allowed for very good correlation between measured and simulated hydrographs. Generally, CN undersimulated surface runoff while GAML had no pattern associated with events. Results suggest that no significant advantage was gained by using breakpoint rainfall and sub-daily time-steps when simulating the large basin used in this study.

Effect of watershed subdivision on simulation runoff and fine sediment yield

Abstract: The objective of this study was to establish the subwatershed size dependency of the Soil and Water Analysis Tool (SWAT) erosion model to adequately simulate annual runoff and fine sediment (< 0.063 mm) from the 21.3 km2 Goodwin Creek Watershed (GCW). Results of the GCW application show that runoff volume is not appreciably affected by the number and size of subwatersheds. However, an upper limit to subwatershed size is required to adequately simulate fine sediment yield produced from upland sources. Decreasing the size of subwatersheds beyond this threshold does not substantially affect the computed fine sediment yield. The proper identification of this threshold size can optimize input data preparation requirements and computational resources needed for effective utilization of the SWAT model, and simplify the interpretation of results.

A Review of effectiveness of vegetative buffers on sediment trapping in agricultural areas

Abstract: In recent years, there has been growing recognition of the importance of riparian buffers between agricultural fields and waterbodies. Riparian buffers play an important role in mitigating the impacts of land use activities on water quality and aquatic ecosystems. However, evaluating the effectiveness of riparian buffer systems on a watershed scale is complex, and watershed models have limited capabilities for simulating riparian buffer processes. Thus, the overall objective of this paper is to develop an understanding of riparian buffer processes towards water quality modelling/monitoring and nonpoint source pollution assessment. The paper provides a thorough review of relevant literature on the performance of vegetative buffers on sediment reduction. It was found that although sediment trapping capacities are site- and vegetation-specific, and many factors influence the sediment trapping efficiency, the width of a buffer is important in filtering agricultural runoff and wider buffers tended to trap more sediment. Sediment trapping efficiency is also affected by slope, but the overall relationship is not consistent among studies. Overall, sediment trapping efficiency did not vary by vegetation type and grass buffers and forest buffers have roughly the same sediment trapping efficiency. This analysis can be used as the basis for planning future studies on watershed scale simulation of riparian buffer systems, design of effective riparian buffers for nonpoint source pollution control or water quality restoration and design of riparian buffer monitoring programs in watersheds. Published in 2009 by John Wiley & Sons, Ltd.

Evaluation of annagnps on mississippi delta msea watersheds

Abstract: Sediment and its associated pollutants entering a water body can be very destructive to the health of that system. Best Management Practices (BMPs) can be used to reduce these pollutants, but understanding the most effective practices is very difficult. Watershed models are the most cost–effective tools to aid in the decision–making process of selecting the BMP that is most effective in reducing the pollutant loadings. The Annualized Agricultural Non–Point Source Pollutant Loading model (AnnAGNPS) is one such tool. The objectives of this study were to assemble all necessary data from the Mississippi Delta Management System Evaluation Area (MDMSEA) Deep Hollow watershed to validate AnnAGNPS, and to use the validated AnnAGNPS to evaluate the effectiveness of BMPs for sediment reduction. In this study, AnnAGNPS predictions were compared with three years of field observations from the MDMSEA Deep Hollow watershed. Using no calibrated parameters, AnnAGNPS underestimated observed runoff for extreme events, but the relationship between simulated and observed runoff on an event basis was significant (R2 = 0.9). In contrast, the lower R2 of 0.5 for event comparison of predicted and observed sediment yields demonstrated that the model was not best suited for short–term individual event sediment prediction. This may be due to the use of Revised Universal Soil Loss Equation (RUSLE) within AnnAGNPS, and parameters associated with determining soil loss were derived from long–term average annual soil loss estimates. The agreement between monthly average predicted sediment yield and monthly average observed sediment yield had an R2 of 0.7. Three–year predicted total runoff was 89% of observed total runoff, and three–year predicted total sediment yield was 104% of observed total sediment yield. Alternative scenario simulations showed that winter cover crops and impoundments are promising BMPs for sediment reduction.

Model Evaluation Guidelines for Systematic Quantification of Accuracy in Watershed Simulations

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.

The Soil and Water Assessment Tool: Historical Development, Applications, and Future Research Directions

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.

Soil and Water Assessment Tool: Historical Development, Applications, and Future Research Directions, The

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.

SWAT: Model Use, Calibration, and Validation

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.