Unraveling the Phenomenon of Supply‐Demand Feedback in Agricultural Water Interventions

Abstract The Agricultural water interventions can trigger human‐water feedback, including unintended supply demand feedback—where increased water availability drives greater water use. In the Kamadhiya catchment, India, the introduction of check dams (CDs) led to a shift toward more water‐intensive crops like cotton and wheat. This study formulates and tests hypotheses to understand these dynamics using an agent‐based model (ABM) that integrates a spatially explicit hydrological model with a farmer behavior module. The ABM simulates 38,447 farmers using the RANAS behavioral framework, based on household surveys and observed data. Model results confirm the hypothesized feedback: increased water from CDs led to an 11.9% rise in cotton and 36.1% in wheat areas, boosting incomes and increasing adoption of drip and borewell irrigation, particularly near CDs. While drip irrigation systems improve water efficiency and post‐monsoon groundwater levels, the saved water enables further wheat expansion—triggering a second supply demand feedback loop. These changes are spatially concentrated near CDs, exacerbating within‐catchment disparities. Overall, about 54% of the additional recharge is used for irrigation expansion, lowering groundwater levels by 1.0 m and reducing the net benefit of recharge interventions. These findings underscore the need to critically understand human‐water feedback and value of ABM as a tool to support more informed planning by offering strategies that mitigate negative externalities.