A novel two-stage fuzzy stochastic model for water supply management from a water-energy nexus perspective

Abstract

Integrated water resources management from a water-energy nexus perspective is necessary to realize sustainable development. However, the inherent uncertainties and complexities in the nexus system have posed great challenges for decision makers. In this study, a novel two-stage fuzzy stochastic programming approach capable of addressing uncertainties with both possibility and probability distribution is developed for water resources management problems under water-energy nexus. Under this framework, the future uncertain events can be effectively defined as a scenario tree with fuzzy random information and fuzzy probability distribution. Then, the proposed method is examined through a real case of Tianjin, a coastal water-stressed city in northeast China. A series of decision alternatives are obtained under various water resource availability scenarios with the consideration of decision makers’ risk preferences. Results showed that the surface water and the imported water accounting for 70% of the total water supply would still be the main contributors to support local socioeconomic development and that the estimated electricity consumption embodied in per-unit water supply ranges from 0.56 kWh/m3 to 0.61 kWh/m3 through the system nexus relationship modeling. The results also disclosed that due to climate change, water scarcity would require more exploitation of groundwater and utilization of desalination water and recycle water, which would exacerbate environmental pressure and increase energy demand for water supply. These findings can provide managerial insights and suggestions for decision makers to achieve flexible water management with the consideration of system uncertainties, water-energy nexus, water shortage, and decision maker’s risk attitude.