Dynamic programming for sustainable water management: improving water allocation in a large irrigation network

Sustainable agricultural production depends on effective water management. This study presents a novel use of dynamic programming to integrate the Relative Secondary Crops Factor-Relative Secondary Crops Area (RSCF-RSCA) method and the Net Field Requirements (NFR) method to optimize irrigation water allocation especially in areas with limited water supplies like East Java, Indonesia. This method outperforms conventional heuristic approaches in tackling the intricacies of temporal and spatial variability in water demands. In terms of increasing cultivation intensity, water distribution equity, and economic benefits, the results show that RSCF-RSCA continuously performs better than NFR in a 2% increase in the economy, a 2.27% increase in irrigated area, and a 2.79% increase in cultivation intensity. The innovation of this research resides in the application of dynamic programming to formulate irrigation strategies that are both scalable and adaptable, effectively aligning water distribution with the essential growth requirements of crops. The results underscore its capacity to promote long-term sustainability within the agricultural sector by enhancing the efficiency and equity of resource utilization. The study recommends that water treatment specialists, agriculturalists, and governments use smart irrigation to tackle world water shortage and climate change. Models of climate change should be included in the following investigations, along with results from ecological and agricultural initiatives in different regions.