A simulation-based interval two-stage stochastic model for agricultural non-point source pollution control through...

Area of Science:

• Environmental Science
• Agricultural Engineering
• Operations Research

Background:

• Agricultural non-point source (NPS) pollution poses significant environmental challenges.
• Land retirement is a strategy to mitigate NPS pollution but faces uncertainties.
• Balancing agricultural revenue with water quality protection is crucial.

Purpose of the Study:

• To develop a simulation-based interval two-stage stochastic programming (SITSP) model for agricultural NPS pollution control.
• To optimize land retirement schemes by minimizing total economic and environmental costs under uncertainty.
• To identify sensitive croplands for targeted pollution mitigation.

Main Methods:

• Developed an interval two-stage stochastic program using simulation outcomes from a distributed water quality model.
• Quantified uncertainties in the agriculture-water system using interval programming.
• Applied the model to the Swift Current Creek watershed, using HSPF for sediment simulation.

Main Results:

• The SITSP model effectively managed the trade-off between agricultural revenue and water quality.
• Optimal land retirement schemes were identified, limiting total economic and environmental costs within an interval.
• Best and worst-case land retirement scenarios were determined under various uncertainties.

Conclusions:

• The developed SITSP model provides an effective framework for agricultural NPS pollution control through land retirement.
• The approach successfully quantifies uncertainties and identifies optimal strategies for environmental management.
• The study demonstrates the applicability of the model in real-world watershed management scenarios.