Journal Article10.13031/TRANS.13576
Multi-Variable Sensitivity Analysis, Calibration, and Validation of a Field-Scale SWAT Model: Building Stakeholder Trust in Hydrologic and Water Quality Modeling
Ritesh Karki,Puneet Srivastava,David D. Bosch,Latif Kalin,Jasmeet Lamba,Timothy C. Strickland +5 more
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TL;DR: In this paper, the authors evaluated the ability of SWAT to simulate runoff, soil moisture, cotton and peanut yields, and nitrate in conventionally tilled and strip-tilled plots while also evaluating the differences in hydrological and nutrient simulation parameters for two tillage practices.
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Abstract: Highlights SWAT can adequately simulate runoff, soil moisture, cotton and peanut yields, and nitrate at field scale. Muskingum routing and adjusting DIS_STREAM are important to simulate fields as watersheds rather than HRUs. Crop yield calibration is critical for improving SWAT model robustness in nutrient transport simulations and for building stakeholder trust. SWAT can quantify the impacts of different management scenarios at the field scale. Abstract. Multi-variable calibration of a field-scale Soil and Water Assessment (SWAT) model is critical for understanding the true impacts of irrigation and nutrient best management practices (BMPs) on hydrology, water quality, and agricultural productivity and for building stakeholder trust for eventual BMP implementation at the watershed scale. This study evaluated the ability of SWAT to simulate runoff, soil moisture, cotton and peanut yields, and nitrate in conventionally tilled and strip-tilled plots while also evaluating the differences in hydrological and nutrient simulation parameters for the two tillage practices. Modeling results showed that SWAT adequately simulated runoff, soil moisture, cotton and peanut yields, and nitrate at the field scale and that calibrated values for the curve number of operation (CNOP) were different for the conventionally tilled and strip-tilled plots and critical to runoff calibration. It was also important to change the routing method from variable storage to Muskingum and to adjust DIS_STREAM for runoff simulation if the field was to be simulated as a watershed rather than as an HRU. Sequential calibration of surface runoff, soil moisture, crop yield, and nitrate showed that crop yield can be an important consideration for improving SWAT model robustness in nutrient transport simulations. Soil moisture calibration did not have a significant effect on runoff simulations. Evaluation of the impacts of different management scenarios showed that soil moisture sensor-based irrigation, cover crop, and strip tillage had the highest potential for reducing nutrient loss and conserving water while maintaining agricultural productivity in southern Georgia. This study also demonstrated to stakeholders that the SWAT model can successfully quantify the impacts of different management scenarios on their farm fields.
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Citations
Predicting of Runoff Using an Optimized SWAT-ANN: A Case Study
TL;DR: In this paper, the authors used the SWAT and ANN models and an improved model of a metaheuristic employed for resolving the explained shortcoming, which is based on a Mutated model of the Whale Optimization Algorithm (MWOA) that enhances the expected results by reducing the error in the ANN.
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Application of artificial neural network and Soil and Water Assessment Tools in evaluating power generation of small hydropower stations
TL;DR: In this paper, an Artificial Neural Network (ANN) alongside the SWAT model has been used to increase the model's ability to estimate streams flow, and an optimized algorithm called Improved the Pathfinder Optimizer (IPFO) have been utilized to reduce error during the learning process.
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Ecological Compensation Mechanism in a Trans-Provincial River Basin: A Hydrological/Water-Quality Modeling-Based Analysis
TL;DR: In this paper , the authors simulated hydrologic and nutrient cycling in the Tangbai River Basin (TRB) using Soil and Water Assessment Tool (SWAT) with limited data available.
Assessing environmental sustainability of a vital crop in a critical region: Investigating climate change impacts on agriculture using the SWAT model and HWA method
TL;DR: This study assesses environmental sustainability in the Ardabil Plain, Iran, using the SWAT model and HWA method, projecting a 25% decline in wheat production and $139 million net income loss by 2050 due to climate change impacts.
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References
Large Area Hydrologic Modeling and Assessment Part i: Model Development
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.
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SWAT: Model Use, Calibration, and Validation
Jeffrey G. Arnold,Daniel N. Moriasi,Philip W. Gassman,Karim C. Abbaspour,Michael J. White,Raghavan Srinivasan,C. Santhi,R. D. Harmel,A. van Griensven,M. W. Van Liew,Narayanan Kannan,Manoj Jha +11 more
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.
The Soil and Water Assessment Tool: Historical Development, Applications, and Future Research Directions
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.
Hydrologic and Water Quality Models: Performance Measures and Evaluation Criteria
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.
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