Inland arid basins face the challenge of ecological deterioration due to insufficient water availability. The irrigation water consumption depletes the water flowing into the downstream tailrace ecological wetland, leading to increasing ecological deterioration. It is urgent to optimize the management of irrigation water resources in the middle reaches and improve the ecological sustainability of the lower reaches. To ensure sustainable development, improving water use efficiency and preserving the health of basin ecosystems should be simultaneously considered in the agricultural water management of these regions. Therefore, a 0–1 integer multi-objective programming approach was proposed to optimize midstream crop planting. This method has advantages in (1) effectively balancing ecological sustainability, agricultural production, and water-saving goals; (2) linking irrigation district management with grid geographic information to develop land use strategies; and (3) obtaining optimal solutions for multi-objective synergies. The proposed approach is applied to a typical inland river basin in China, the Heihe River Basin in Gansu Province. Results indicate that the optimization schemes can increase agricultural benefits, crop suitability, water use efficiency, and ecological quality by 12.37%, 6.82%, 13.00%, and 8.04% (compared to 2022), respectively, while irrigation water can be saved about 7.53%. The optimization results and proposed approach can help decision-makers manage water resources in the Heihe River Basin and similar regions.

Optimizing irrigation strategies to simultaneously enhance crop yield and fruit quality under water scarcity is a critical challenge for sustainable agriculture. This study addresses this challenge by developing a novel fuzzy credibility-constrained fuzzy multi-objective programming (FCC-FMOP) model for irrigation planning under uncertainty. The model incorporates stochastic hydrologic factors, decision-maker preferences, and complex interrelationships among fruit quality attributes and market dynamics. Applied to a citrus-producing region in Southwest China prone to seasonal drought, the approach demonstrates its capability to reconcile multiple objectives under fuzzy constraints. The key findings include the following: (1) The IVIF-TOPSIS analysis quantitatively revealed that yield was the paramount objective for decision-makers in the study region, followed by single fruit weight, highlighting the economic drivers that must be balanced with qualitative metrics. (2) The FCC-FMOP model effectively balances yield and quality objectives while adapting to real-world fuzzy constraints, proving to be both robust and practical. (3) Compared with conventional practices, the proposed irrigation strategy—calibrated under varying credibility levels (β = 0.55, 0.75, and 0.95)—significantly improves yield, fruit weight, hue angle, water content, and soluble sugar content. Performance evaluation using synthetic degree (SD), the sustainability index (SI), and approximation degree (AD) confirmed the model’s superiority over single-objective models and conventional practices. The FCC-FMOP model provides a scalable and decision-maker-oriented tool for sustainable irrigation management in water-limited environments.