Water quality–quantity management in river–reservoir system using sustainability‐based simulation‐optimization meta‐model approach

Abstract

AbstractThe present research, for the first time, introduces a sustainability‐based water quality–quantity management model in the river–reservoir system. Vulnerability, resiliency, reliability and maximum deficit are the factors that have been considered in the Sustainability Index (S.I.). The two‐dimensional hydrodynamics and water quality simulation model (CE‐QUAL‐W2) is linked to the multi‐objective particle swarm optimization (MOPSO) to develop a simulation‐optimization approach. Also, artificial neural network (ANN) model, substituted for the Ce‐QUAL‐W2 model, reduces the computational time in adaptive dynamically refined routine. The proposed methodology is applied to the Karkheh river–reservoir in Iran. The results showed that using ANN in an adaptive form, replacing CE‐QUAL‐W2, significantly impacts the computational time, considering accuracy in the developed simulation‐optimization model. Moreover, using the S.I. greatly reduces both the severity of failure periods in the water quantity–quality and the sequence of failure periods.