Multi-objective optimal allocation of water resources in Shule River Basin of Northwest China based on climate change scenarios

The optimal allocation of water resources is crucial for addressing regional water scarcity, adapting to climate change, and promoting sustainable development. This study focused on the Shule River Basin and considered three climate scenarios (SSP1–2.6, SSP2–4.5, SSP5–8.5), which is combinations of Shared Socioeconomic Pathways (SSPs) and Representative Concentration Pathways (RCPs). A water resources optimal allocation model including water supply and demand prediction, multi-objective optimization, decision-making and analysis on optimal water allocation schemes was constructed. This model aims to analyze the optimal allocation of water resources in the Shule River Basin over three planning years (2025, 2030, 2035), considering guarantee rates of 50 % and 75 % under various climate scenarios. The obtained results indicate that: (1) An increasing trend in water demand in the planning year. For instance, under the SSP1–2.6 scenario, the basin's water demand is projected to reach 1.920×10^9 m3, 2.037×10^9 m3, and 2.103×10^9 m3 in 2025, 2030, and 2035, respectively. (2) The total water supply with a guarantee rate of 50 % (75 %) in the planning years is projected to be 1.939 (1.483)×10^9, 1.957(1.502) ×10^9, and 1.974 (1.519) ×10^9 m3, respectively. (3) In the three scenarios of SSP1–2.6, SSP2–4.5, and SSP5–8.5, the water demand for domestic and ecology is met in each planning year. There is a slight water shortage in the industrial sector, with a shortage rate ranging from 0 % to 13.41 %. The agricultural sector experiences the highest water shortage, with a rate of 1.93–44.77 %. (4) The water supply structure of each optimal allocation scheme of water resources was optimized. The economic benefits mainly depend on the industrial and ecological sectors. These findings offer valuable insights for optimizing the distribution of regional water resources in response to changing climatic conditions.