Journal article
Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
Journal of Visualized Experiments, Vol.70, e4009
12/09/2012
DOI: 10.3791/4009
PMCID: PMC3598409
PMID: 23242132
Abstract
Finding the cost-efficient (i.e., lowest-cost) ways of targeting conservation practice investments for the achievement of specific water quality goals across the landscape is of primary importance in watershed management. Traditional economics methods of finding the lowest-cost solution in the watershed context (e.g.,5,12,20) assume that off-site impacts can be accurately described as a proportion of on-site pollution generated. Such approaches are unlikely to be representative of the actual pollution process in a watershed, where the impacts of polluting sources are often determined by complex biophysical processes. The use of modern physically-based, spatially distributed hydrologic simulation models allows for a greater degree of realism in terms of process representation but requires a development of a simulation-optimization framework where the model becomes an integral part of optimization.
Evolutionary algorithms appear to be a particularly useful optimization tool, able to deal with the combinatorial nature of a watershed simulation-optimization problem and allowing the use of the full water quality model. Evolutionary algorithms treat a particular spatial allocation of conservation practices in a watershed as a candidate solution and utilize sets (populations) of candidate solutions iteratively applying stochastic operators of selection, recombination, and mutation to find improvements with respect to the optimization objectives. The optimization objectives in this case are to minimize nonpoint-source pollution in the watershed, simultaneously minimizing the cost of conservation practices. A recent and expanding set of research is attempting to use similar methods and integrates water quality models with broadly defined evolutionary optimization methods3,4,9,10,13-15,17-19,22,23,25. In this application, we demonstrate a program which follows Rabotyagov et al.'s approach and integrates a modern and commonly used SWAT water quality model7 with a multiobjective evolutionary algorithm SPEA226, and user-specified set of conservation practices and their costs to search for the complete tradeoff frontiers between costs of conservation practices and user-specified water quality objectives. The frontiers quantify the tradeoffs faced by the watershed managers by presenting the full range of costs associated with various water quality improvement goals. The program allows for a selection of watershed configurations achieving specified water quality improvement goals and a production of maps of optimized placement of conservation practices.
Details
- Title: Subtitle
- Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
- Creators
- Sergey Rabotyagov - University of WashingtonTodd Campbell - Iowa State UniversityAdriana Valcu - Iowa State UniversityPhilip Gassman - Iowa State UniversityManoj Jha - North Carolina Agricultural and Technical State UniversityKeith Schilling - Indiana Geological and Water SurveyCalvin Wolter - Indiana Geological and Water SurveyCatherine Kling - Iowa State University
- Resource Type
- Journal article
- Publication Details
- Journal of Visualized Experiments, Vol.70, e4009
- DOI
- 10.3791/4009
- PMID
- 23242132
- PMCID
- PMC3598409
- NLM abbreviation
- J Vis Exp
- ISSN
- 1940-087X
- eISSN
- 1940-087X
- Publisher
- MyJove Corporation
- Language
- English
- Date published
- 12/09/2012
- Academic Unit
- Earth and Environmental Sciences; IIHR--Hydroscience and Engineering
- Record Identifier
- 9984383279302771
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