Mathematical modeling for planning water-food-ecology-energy nexus system under uncertainty: A case study of the Aral Sea Basin

Abstract A bi-level decentralized chance-constrained programming (BDCP) method is developed to plan the water-food-ecology-energy (WFEE) nexus system. The developed method has advantages in balancing the tradeoffs between two-level stakeholders in hierarchical structure and reflecting the synergies among multiple divisions under random uncertainty. Then, a BDCP-WFEE model is formulated for the Aral Sea Basin, where the upper-level model aims to maximize system benefit, and the multiple divisions at lower-level model aim to maximize food production, ecological water allocation and electricity generation, respectively. The obtained results reveal that compared with conventional single-level model, (i) the food production from BDCP-WFEE model would increase by 2.0% to 3.6% (the average annual increase is about 243.1 × 106 kg), which means that the food demand of additional 0.7 million people can be met; (ii) the ecological water allocation would increase by 0.9% to 3.0%, especially the amount of water flowing to the Aral Sea would be nearly 23.4 km3 at the end of planning periods; (iii) the electricity generation would increase by 5.4% to 8.5% (i.e., 5.3 × 1012 kWh to 8.4 × 1012 kWh), which shows the superiority of BDCP-WFEE model. Besides, under the premise of ensuring food security, the proportion of agricultural water allocation in Aral Sea Basin would reduce by nearly 17.0%, which indicates that BDCP-WFEE model can effectively optimize the water allocation structure and alleviate the competition for water resources among different users. These findings can provide policy support for managers to solve the problems of water shortage, food crisis, ecological degradation and electricity insecurity.