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

Abstract

In this study, a novel optimization-simulation dynamic approach is developed for optimal water operation of reservoir-river systems to improve the water quality and supply the water demands along the river. To this purpose, the WEAP-QUAL2 K linked model is developed to simulate water quality and quantity, which is coupled to a fuzzy multi-objective imperialist competition algorithm (FMOICA) dynamically. The approach's applicability is demonstrated through the case study of the Dez reservoir river in Iran. The simulation and optimization period is six years (October 2019-September 2025). The stochastic models (SARIMA(1,0,1)(1,1,1)) are 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 models, it can be concluded that the model has high accuracy in simulating the parameters of water quality and quantity. Two scenarios are considered, the first scenario is used for dynamical coupling of the quantity-quality model (reference scenario), and the second is the fuzzy optimization of a linked model (optimal scenario). The results showed 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. As well as, it is found that environmental flow rate demands of the river are fully supplied in different months.