A Novel Compromise Approach for Risk-Based Selective Water Withdrawal from Reservoirs Considering Qualitative-Quantitative Aspects

A novel risk-based multi-objective compromise methodology was proposed for selective withdrawal from a dam reservoir. Developed for devising a five-year optimal reservoir policy in dry, wet, and normal periods, it allowed for selective water withdrawal from multiple outlets at different depths to account for the reservoir's water quality and thermal stratification. A calibrated version of the CE-QUAL-W2 numerical model was utilized for simulating temperature and other water quality parameters at different reservoir outlets under possible scenarios of reservoir inflow and outflow. To address the computational burden problem, two multilayer perceptron meta-models were trained and validated using the CE-QUAL-W2 simulation results for temperature and the IRan Water Quality Index (IRWQI) at each reservoir outlet. Then, the validated meta-models were coupled with the non-dominated sorting genetic algorithm-II (NSGA-II) optimization technique, allowing one to incorporate different stakeholders' utility functions. Three objective functions were considered: (i) minimization of the storage deficit risk, (ii) minimization of the low water quality risk (due to reservoir thermal stratification), and (iii) minimization of the deficit between total releases and demands. Finally, the GMCR-plus model resolved stakeholder conflicts and achieved a compromise solution. Alleviating the shortcomings of previous models in achieving coupled water quality-quantity allocation by drawing on the capabilities of conditional value-at-risk (CVaR) and graph models, along with NSGA-II, constituted the present study's principal contribution. The research findings revealed that applying the proposed methodology could provide adequate water quality corresponding to different demands during thermal stratification to prepare effective guidelines for optimal reservoir operation.