Abstract

Negligence of environmental flow (e-flow) has severe adverse impacts on wetlands. Additionally, hydrological droughts, compounded by mismanagement of available water resources and anthropogenic activities, lead to water shortage and degrade wetland ecosystem. However, in dealing with reservoir operation/re-operation, a few studies have addressed inflow uncertainty and hydrological drought state to improve the monthly operation performance of an upstream reservoir in coordination with downstream wetland needs. Hence, the study objective is to adopt a linear/nonlinear reservoir operation rule to hydrological drought states and e-flow requirements. So, first, the soil and water assessment (SWAT) model is applied to simulate the natural daily flow regime by eliminating human impacts. Then, using the Tennant e-flow scheme, the intra/inter-annual variability of e-flow and the degree of alteration of the flow are measured. Afterward, using the Standardized Hydrological Drought Index (SHDI), the drought/wet severity and duration are determined. A linear/nonlinear simulation model adopted for the presentation of reservoir policies and the non-dominated sorting genetic algorithm-II (NSGA-II) was employed to determine the optimal monthly operation of the upstream reservoir. The simulated operation policies correspond to each hydrological drought state were evaluated with reliability, resilience, vulnerability, and water-deficit indices. Results indicated that incorporation of hydrological drought state could improve the overall system reliability by 23% over simply enforcing the monthly variable-parameter nonlinear decision rules. Also, the proposed methodology simultaneously maximized the downstream allocated water and e-flow of the terminal wetland. It also implicitly minimized the change in extreme flow metrics that are known to benefit ecosystem diversity. The proposed framework supports reservoir re-operation in regions subject to challenges in supplying water to different sectors while maintaining e-flow during drought periods.

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