Agent-Based Modeling of Groundwater Irrigation
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This research couples agent-based models of farmer behavior with groundwater and crop systems to understand how individual irrigation and crop-choice decisions aggregate into system-scale outcomes — and how those behaviors shift over time.
It combines human and machine intelligence to derive agents' behavioral rules, and examines non-stationary irrigation behavior under changing conditions.