Modeling farmer responses to reservoir operation policies using agent based analysis of risk behavior and irrigation adoption.

Understanding farmers' responses to reservoir operation policies is crucial for water resources management. This study employs an Agent-Based model with established socio-hydrological rules to simulate farmers' decision-making. Operator agents utilize either the Standard Operation Policy (SOP), a hedging rule (strategies to balance water shortages over time), or a dynamic informed hedging rule for reservoir operation. Farmer agents annually decide on land cultivation and the potential adoption of modern irrigation systems based on socioeconomic characteristics and water availability. The study focuses on Iran's Borkhar Plain, modeling operator and farmer agents within MODSIM, a decision-support system used for water allocation and reservoir operations. Results indicate that high-risk-taking farmers tend to cultivate more land, particularly under SOP averaging 69.6%, while under the hedging rule, farmers' decisions became more predictable, with reduced land use averaging 63.6% and retaining profitability. The dynamic informed hedging rule scheme, however, resulted in the most synchronized farmer behavior, with land use decreasing further to 54% without a significant decrease in profitability. Adoption of modern irrigation systems was significantly influenced by education levels and risk-taking behavior. Adoption rates increased across policies, from 37.5% under SOP to 45.83% under the hedging rule, and peaked at 62.5% under the informed hedging rule scheme.