An integrated PMP-ABM model of adaptive enforcement and behavioral spillover

Coupling economic optimization and behavioral models is critical to understanding how agents (farmers) respond to water scarcity, policy enforcement, and social dynamics and nonlinear changes. This study presents a novel hybrid framework that couples Positive Mathematical Programming (PMP) with Agent-Based Modeling (ABM) to simulate illegal water use decisions under uncertainty, peer influence, and evolving enforcement pressure. While the PMP model ensures economic realism by calibrating profitmaximizing land and water allocation based on observed data, the ABM layer introduces bounded rationality, non-compliance behaviors, dynamic risk perception, peer imitation, and learning mechanisms.