A coupled agent-based risk-based optimization model for integrated urban water management

Abstract

Integrated urban water management (IUWM) is a comprehensive mitigation strategy to control water deficit due to simultaneous effects of reduction in water resources capacity and increase in water demand. Here we develop a coupled agent-based risk-based optimization model, which is able to account for water resources capacity and water demand uncertainties to determine the optimum annual water allocation. An optimization model based on conditional value at risk (CVaR) is employed to minimize the water supply risk in a long-term horizon and obtain the annual probabilities of complete supply of water demand. According to the generated synthetic weather data by LARS-WG for different climate scenarios, surface water and groundwater resources are modeled using HMETS and MODFLOW, respectively. Then, the developed agent-based model considers agents’ attributes, action roles and interactions by applying Borda scoring approach, and determines the most compatible IUWM strategies to increase water supply or modify water demand. The proposed framework is implemented for the Shiraz city in Iran, revealing a strong need to IUWM strategies to alleviate the water deficit over the period of 2018 to 2050. The proposed approach provides an efficient framework to achieve sustainable management strategies for cities with stressed water resources and rapid urban development.