This study develops an integrated methodological framework coupling CMIP6 climate projections with a socio-economic-hydrological System Dynamics (SD) model to evaluate adaptation strategies for agricultural resilience. Applied to the Qazvin Plain aquifer in Iran, the model demonstrates high fidelity in capturing hydrological–human interactions, evidenced by a 97% correlation between simulated and observed groundwater levels. The system was developed using long-term meteorological drivers (1993–2024) and calibrated against observed socio-hydrological data for the period 2006–2024 and projected to 2062 under multiple CMIP6 scenarios, identifying SSP245 and SSP126 as the most accurate predictors for regional precipitation and temperature, respectively. Modeling outcomes indicate that aridity will intensify across all scenarios; specifically, under current water-use patterns, groundwater storage is projected to decline by 24.5%, 25.4%, and 27.6% by 2041 under SSP126, SSP245, and SSP585, respectively. However, the simulation reveals that integrating demand-side management with crop pattern optimization can stabilize the aquifer and boost agricultural value added by 7.4%. The findings further highlight that a 48% reduction in current groundwater withdrawals is essential to reach a sustainable threshold of 781 million m3. These quantitative insights suggest that while climatic pressures are increasing, human-driven management remains the decisive factor, provided that economic tools and smart monitoring are prioritized for long-term sustainability.
Nazari et al. (Tue,) studied this question.