Abstract

In this paper, a new systematic approach is designed to maximize the demand coverage and receiving waste load by river-reservoir systems while enhancing water quality criteria. The approach intends to control the reservoir eutrophication while developing a trade-off between the maximum receiving load and shortage on demand coverage. To simulate the system, a hybrid process-based and data-driven model is tailored. Initially, the two-dimensional hydrodynamics and water quality simulation model (CE-QUAL-W2) is linked with an effective single and/or multiple optimization algorithms (PSO) to evaluate the proposed scenarios. To increase the computational efficiencies, the simulation model is substituted with a surrogate model (ANN) in an adaptive-dynamically refined routine. The proposed method is illustrated by a case study in Iran, namely, Karkheh River Reservoir, for 180-monthly periods. The results showed the applicability of the methodology especially to solve high-dimensional multi-period complex water resource optimization problems. Also, the results demonstrated that eutrophication could be reduced under the optimal inflow phosphate control and reservoir operation, regulating the total phosphorous concentration in the reservoir.

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