Decision Support for Watershed Management Using Evolutionary Algorithms
Publication: Journal of Water Resources Planning and Management
Volume 131, Issue 1
Abstract
An integrative computational methodology is developed for the management of nonpoint source pollution from watersheds. The associated decision support system is based on an interface between evolutionary algorithms (EAs) and a comprehensive watershed simulation model, and is capable of identifying optimal or near-optimal land use patterns to satisfy objectives. Specifically, a genetic algorithm (GA) is linked with the U.S. Department of Agriculture’s Soil and Water Assessment Tool (SWAT) for single objective evaluations, and a Strength Pareto Evolutionary Algorithm has been integrated with SWAT for multiobjective optimization. The model can be operated at a small spatial scale, such as a farm field, or on a larger watershed scale. A secondary model that also uses a GA is developed for calibration of the simulation model. Sensitivity analysis and parameterization are carried out in a preliminary step to identify model parameters that need to be calibrated. Application to a demonstration watershed located in Southern Illinois reveals the capability of the model in achieving its intended goals. However, the model is found to be computationally demanding as a direct consequence of repeated SWAT simulations during the search for favorable solutions. An artificial neural network (ANN) has been developed to mimic SWAT outputs and ultimately replace it during the search process. Replacement of SWAT by the ANN results in an 84% reduction in computational time required to identify final land use patterns. The ANN model is trained using a hybrid of evolutionary programming (EP) and the back propagation (BP) algorithms. The hybrid algorithm was found to be more effective and efficient than either EP or BP alone. Overall, this study demonstrates the powerful and multifaceted role that EAs and artificial intelligence techniques could play in solving the complex and realistic problems of environmental and water resources systems.
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Acknowledgment
The writers wish to thank the Illinois Council for Food and Agricultural Research (CFAR) for their support of this ongoing research effort, and the anonymous reviewers for their valuable input.
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Information & Authors
Information
Published In
Journal of Water Resources Planning and Management
Volume 131 • Issue 1 • January 2005
Pages: 35 - 44
Copyright
© 2005 ASCE.
History
Received: Nov 6, 2002
Accepted: May 5, 2004
Published online: Jan 1, 2005
Published in print: Jan 2005
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