An integrated fuzzy optimization and simulation method for optimal quality-quantity operation of a reservoir-river system

Abstract

Abstract In this study, a novel optimization-simulation dynamic approach was developed for optimal water operation of reservoir-river systems to improve the water quality and supply the water demands along a river. To this purpose, the WEAP-QUAL2 K linked model was developed to simulate water quality and quantity, which is dynamically coupled to a fuzzy multi-objective imperialist competition algorithm (FMOICA). The approach's applicability is demonstrated through the case study of the Dez reservoir river in Iran. The simulation and optimization period used was six years (October 2019-September 2025). Stochastic models (SARIMA(1,0,1)(1,1,1)) were used to forecast inflow into the Dez dam reservoir for the simulation period. Given that in the verification stage of the QUAL2 K and WEAP model it was concluded that the model has high accuracy in simulating the parameters of water quality and quantity, two scenarios were considered: the first scenario was used for dynamic coupling of the quantity-quality model (reference scenario), and the second was the fuzzy optimization of a linked model (optimal scenario). The results show that average water supply reliability increased from 86.13% in the reference scenario to 95.76% in the optimal scenario. Also, under the optimal scenario, the river water quality improves. It was also found that environmental flow rate demands of the river are fully supplied in different months.