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Multiobjective management of ecosystem services by integrative watershed modeling and evolutionary algorithms
Author(s) -
Bekele Elias G.,
Nicklow John W.
Publication year - 2005
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1029/2005wr004090
Subject(s) - ecosystem services , watershed , gross margin , nonpoint source pollution , ecosystem , watershed management , margin (machine learning) , environmental science , environmental resource management , computer science , agriculture , ecology , machine learning , biology
This paper explores the role of landscapes in generating ecosystem services while maximizing gross margin associated with agricultural commodity production. Ecosystem services considered include the reduction of nonpoint source pollutants such as sediment, phosphorous, and nitrogen yields from a watershed. The analysis relies on an integrative modeling framework that combines a comprehensive watershed model (SWAT) with a multiobjective evolutionary algorithm (SPEA2). Application of the resulting model to a watershed in southern Illinois demonstrates the effectiveness of the approach in providing tradeoff solutions between gross margin and the generation of ecosystem services. These solutions are important to policy makers and planners in that they provide information about the cost‐effectiveness of alternative agricultural landscapes.