Rabotyagov, Sergey SRLang, Zhengxin2021-03-192021-03-192020Lang_washington_0250E_22457.pdfhttp://hdl.handle.net/1773/46808Thesis (Ph.D.)--University of Washington, 2020In the United States, there are more than 330 million acres of row crop agricultural land that produce an abundant supply of food and other products to support food security and economic development. Meanwhile, agricultural nonpoint source (NPS) pollution, most generally occurring in the absence of a landscape conservation plan, is the leading cause of water quality impairments in the rivers and streams in the United States. Voluntary incentive programs are the primary policy mechanism to improve the water quality of agricultural landscapes, employed to increase the supply of non-market ecosystem services alongside food and energy provision. This project seeks to improve the cost-effectiveness of the incentive designs by paying careful attention to both biophysical and farmers’ socio-economic factors. Specifically, I 1).developed a hybrid optimization paradigm that combined the evolutionary algorithms with weighted benefit-to-cost ratio ranking to tackle the problem of spatial interdependence in multi-objective optimization; 2).identified the underlying socio-psychological drivers of farmers’ intentions for conservation practices adoption, based on first-hand agricultural landowner survey data, factor analysis, and cluster analysis; and 3).estimated landowners’ Willingness-to-Accept to the incentive payments and characterized their preference heterogeneity by discrete choice experiments and mixed logit modeling. The project’s results enable us to identify the spatially explicit cost-efficient conservation portfolios and analyze trade-offs/synergies among water conservation objectives under various management scenarios. Meanwhile, it advances the designs of targeted incentive mechanisms corresponding to landowners’ preferences. My research integrated interdisciplinary knowledge and techniques to explore the complex natural-human system within the Minnesota River Basin for cost-efficient conservation incentive designs. The modeling framework is also transferable to other agricultural landscapes across the nation.application/pdfen-USnoneBehavioral intentionBenefit-to-Cost AnalysisEvolutionary AlgorithmsMulti-objective OptimizationPreference heterogeneityWillingness-to-AcceptNatural resource managementEnvironmental economicsEnvironmental managementForestryThesis