Sustainable Irrigation Planning Through Optimization-Based Cropping Pattern Analysis Under Water Scarcity: A Case Study of the Nam Mang 3 Irrigation Project, Lao PDR

Sustainable irrigation planning under increasing water scarcity requires efficient allocation of limited water resources while simultaneously considering land suitability and agricultural productivity. In this study, we aim to identify optimal cropping patterns for sustainable irrigation management using an optimization-based decision-support framework applied to the Nam Mang 3 Irrigation Project in Lao PDR, based on data from 2022. Focusing on the dry season (November–April), we evaluated six major crops—rice, beans, maize, tomato, cucumber, and watermelon—under six irrigation scenarios to assess the impacts of land suitability and water availability. The analysis incorporated a water availability range from 17. 70 to 18. 10 mm3 to evaluate system robustness. Linear Programming (LP), the Genetic Algorithm (GA), and the African Vultures Optimization Algorithm (AVOA) were employed to determine optimal crop allocation. The proposed framework explicitly incorporates varied soil types and land-use constraints, providing a more realistic representation than conventional homogeneous assumptions. The results indicate that AVOA outperformed other models in terms of stability. Under the evaluated scenarios, the optimal cultivated area ranged from 3192 to 3200 ha, with total profits fluctuating between 34, 125, 930 and 34, 314, 900 US. These findings demonstrate that integrating soil variability and sensitivity-based optimization significantly enhances irrigation planning, providing a practical, robust decision-support tool for planners to design adaptive and sustainable cropping strategies in water-scarce regions.