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Approximation of Metro Water District Basin Using Parallel Computing of Emulator Based Spatial Optimization (PCESO)

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Abstract

Metro Water District (MWD) is an agency that administers water distribution in a large geographic region. It targets for existing conditions with future projections of water resources for conservation, supply, and usage. Hence, it is required to show proper water resources management for MWD. Where the river basin profiles are projected to provide the water resources management with potential issues for MWD. Here, Upper Chattahoochee River (UCR) basin of the Metropolitan North Georgia Water Planning District (MNGWPD) selected for the study area. UCR is one of the largest river basins in the MNGWPD and it provides drinking and primary receiving water for nearly 3.5 million people of Atlanta Metro Region. In this study, Parallel Computing of Emulator based Spatial Optimization (PCESO) framework developed for spatial optimization of large complex watersheds. The proposed framework optimizes the hydrological model by parallel computing, emulator fit, sampling design, and spatial optimization. The results showed that 1) the computational time required for spatial optimization was significantly reduced by 50%, 2) goodness-of-fit reached its threshold limit in all stations inclusive in reservoir containing stations, 3) the water balance components and the optimized parameter values with sensitivity index provided the physical phenomena of the study area and showed the approximate hydrological processes in MWD. Further, this proposed work incorporates into future climate data can provide an accurate hydrological analysis with water allocation issues like water use, demand, conservation, and supply for MWD and it helps to identify the water-related disasters floods and droughts.

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Correspondence to Amit Baburao Mahindrakar.

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Budamala, V., Mahindrakar, A.B. Approximation of Metro Water District Basin Using Parallel Computing of Emulator Based Spatial Optimization (PCESO). Water Resour Manage 34, 121–137 (2020). https://doi.org/10.1007/s11269-019-02424-3

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  • DOI: https://doi.org/10.1007/s11269-019-02424-3

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