Inefficient irrigation water distribution remains a critical barrier to achieving optimal crop productivity and ensuring food security in rural Indonesia. This study focuses on the Gembolo Irrigation Area, Mojokerto Regency, by applying Deterministic Dynamic Programming (DDP) to optimize water allocation under a Rice–Rice–Secondary Crop (RTTG) rotation. The comprehensive integration of hydrological, climatological, and cropping data was employed to construct a DDP model that synchronizes irrigation supply with crop water demand across nine irrigation structures (G1–G9). The optimization results reveal significant improvements: irrigated area expanded by 254 ha, cropping intensity increased from 277 to 300%, and farmers’ net income rose by IDR 5.3 billion compared to the existing allocation scheme. These findings demonstrate the capacity of DDP to enhance water-use efficiency while strengthening the resilience and sustainability of rural agricultural systems. The study highlights the importance of data-driven optimization as a decision-support framework for advancing integrated irrigation management and rural development.
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