Keywords
bmps, decision support, optimization algorithm, swat, trade-off
Start Date
1-7-2012 12:00 AM
Abstract
Irrigation and fertilization of crops are common practices necessary forthe viability of agricultural communities, but also responsible for water scarcity andwater quality deterioration. The effort to cost-effectively manage fresh wateravailability and diffuse nutrient pollution at the same time needs to take intoaccount trade-offs between economic and multiple environmental objectives.Agricultural Best Management Practices (BMPs) are adaptation options formitigating both environmental problems; however, their optimal allocation acrossthe landscape becomes a multi-objective problem, with the need to identify themost suitable combinations. An efficient Decision Support Tool developed inMATLAB, able to assess the cost-effectiveness of irrigation and nutrient applicationmanagement BMPs in reducing agricultural water use or nutrient losses to surfacewaters is used in this study. The tool integrates the process-based Soil and WaterAssessment Tool (SWAT) model, which evaluates the effectiveness of the BMPs atdifferent catchment locations, into a multi-objective genetic algorithm, whichoptimizes their selection and placement across the agricultural land. The novelsoftware aspect of the tool is the automatic development of a BMP database (alook-up table), which stores environmental data and costs for the different locationsand BMPs implemented on them and is used in the optimization scheme instead ofthe computationally intensive model. The application of the tool with the purpose tominimize cost, irrigation water consumption and nitrate-nitrogen loads to rivers fromthe cotton fields of the Pinios River Basin, the largest and most intensivelycultivated area of Greece, demonstrated specific BMPs allocation schemes thatcould be affordable-cost solutions of efficient water quantity and qualitymanagement. In this paper, one such solution is presented and discussed,demonstrating the potential usefulness of the methodology in identifying costeffectivemanagement interventions, even in large, complex river basins and undera climatically and socio-economically changing environment.
A Multi-Objective Decision Support Tool for Rural Basin Management
Irrigation and fertilization of crops are common practices necessary forthe viability of agricultural communities, but also responsible for water scarcity andwater quality deterioration. The effort to cost-effectively manage fresh wateravailability and diffuse nutrient pollution at the same time needs to take intoaccount trade-offs between economic and multiple environmental objectives.Agricultural Best Management Practices (BMPs) are adaptation options formitigating both environmental problems; however, their optimal allocation acrossthe landscape becomes a multi-objective problem, with the need to identify themost suitable combinations. An efficient Decision Support Tool developed inMATLAB, able to assess the cost-effectiveness of irrigation and nutrient applicationmanagement BMPs in reducing agricultural water use or nutrient losses to surfacewaters is used in this study. The tool integrates the process-based Soil and WaterAssessment Tool (SWAT) model, which evaluates the effectiveness of the BMPs atdifferent catchment locations, into a multi-objective genetic algorithm, whichoptimizes their selection and placement across the agricultural land. The novelsoftware aspect of the tool is the automatic development of a BMP database (alook-up table), which stores environmental data and costs for the different locationsand BMPs implemented on them and is used in the optimization scheme instead ofthe computationally intensive model. The application of the tool with the purpose tominimize cost, irrigation water consumption and nitrate-nitrogen loads to rivers fromthe cotton fields of the Pinios River Basin, the largest and most intensivelycultivated area of Greece, demonstrated specific BMPs allocation schemes thatcould be affordable-cost solutions of efficient water quantity and qualitymanagement. In this paper, one such solution is presented and discussed,demonstrating the potential usefulness of the methodology in identifying costeffectivemanagement interventions, even in large, complex river basins and undera climatically and socio-economically changing environment.
