Modeling long-term and interannual crop area changes: Integrating socioeconomic and hydrometeorological factors in the Indus Basin

Abstract

Water management is critical for policymakers in agriculture-dominated regions, where water demand and withdrawals change in response to variations in crop area, such as in the Indus River Basin (IRB). However, the mechanisms driving long-term and interannual crop area changes, particularly farmers’ responses to socio-economic and hydro-meteorological factors, such as economic incentives and water availability, remain insufficiently explored. In this study, rice crop area (hereafter CA) dynamics in the IRB, with a focus on Punjab, Pakistan, are analyzed to identify drivers of both long-term trends and interannual variability and to incorporate these mechanisms into a modeling framework. Using observational socio-economic and hydro-meteorological data for 1950–2020, the analysis reveals that CA changes are strongly influenced by lagged relationships with crop price, yield, and river water availability. These insights guided the development of two modeling approaches, Multiple Linear Regression (MLR) and System Dynamics (SD). While MLR captured some CA variations, it failed to reproduce observed CA dynamics. In contrast, the SD model, integrating feedback of farmer income on CA expansion and the balancing feedback of water stress limiting CA growth, effectively captured historical CA changes (R 2 =0.95, NRMSE=9.8%) and significantly outperformed other models in capturing both long-term trends and interannual variability. Future projections indicate a 35–50% increase in CA and a 45–60% rise in groundwater withdrawals by 2060, highlighting an increasingly unsustainable reliance on groundwater. By incorporating interannual crop area variability into assessments of water withdrawals, the framework provides transferable insights for agricultural water management and groundwater sustainability in irrigation-dominated basins.