Integrated Assessment of Cost-Effective Water Quality Improvements in the Minnesota River Basin: Combining Stated Preferences and Simulation-Optimization Approaches.

Clicks: 18
ID: 283173
2025
Article Quality & Performance Metrics
Overall Quality Improving Quality
0.0 /100
Combines engagement data with AI-assessed academic quality
AI Quality Assessment
Not analyzed
Abstract
Voluntary incentive programs are central to U.S. agricultural policy, aimed at enhancing sustainability by improving environmental outcomes and increasing the supply of non-market ecosystem services. This study integrates econometric insights with biophysical modeling to identify cost-effective strategies for nitrate and sediment reductions at the watershed scale. Survey data from Minnesota River Basin farmers characterizes willingness to accept (WTA) distributions for wetland restoration, cover crops, and nutrient management. A mixed logit model reveals significant heterogeneity in WTA, influenced by income, farm size, political leanings, taxes, water impairments, and non-pecuniary factors like ecosystem service appreciation, conservation experience, and stewardship. Integrated modeling highlights fluvial wetland restoration as a cost-effective and impactful strategy. Up to a 43% nitrogen reduction and 82% sediment reduction may be attained at an annual cost of under $10 million through targeted conservation investments. Scenarios with lower costs ($5 million annually) achieve substantial sediment reductions (82%) but limited nitrogen reductions (22%), demonstrating the utility of multi-objective optimization frameworks to elucidate optimal trade-offs in watershed planning.
Reference Key
lang2025integrated Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Lang, Zhengxin; Rabotyagov, Sergey; Hansen, Amy T; Dalzell, Brent; Campbell, Todd; Tao, Jingjing
Journal environmental management
Year 2025
DOI
10.1007/s00267-025-02179-1
URL
Keywords

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

No comments yet. Be the first to comment on this article.