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    Cascading Model-Based Framework for the Sustainability Assessment of a Multipurpose Reservoir in a Changing Climate

    Source: Journal of Water Resources Planning and Management:;2021:;Volume ( 148 ):;issue: 002::page 05021029
    Author:
    Wenxin Xu
    ,
    Jie Chen
    ,
    Tianhua Su
    ,
    Jong-Suk Kim
    ,
    Lei Gu
    ,
    Joo-Heon Lee
    DOI: 10.1061/(ASCE)WR.1943-5452.0001501
    Publisher: ASCE
    Abstract: Climate change impacts on hydrological processes can affect reservoir operational performance. Hence, the reservoir operation model, based on historical climate conditions, may not guarantee sustainable water resources management in the future. To enable stakeholders to design reliable adaptation strategies, this study aims to propose a cascading framework to quantify the impacts of climate change on the operational performance and sustainability of a multipurpose reservoir. The Danjiangkou Reservoir (DJKR), which serves as the water source for the middle route of the South-to-North Water Diversion Project in China, was selected as a case study. To achieve the aforementioned aims, bias-corrected simulations from 13 global climate models (GCMs) were first input into five hydrological models [i.e., one data-driven [deep belief network (DBN)], three conceptual [SIMHYD, HBV, and Xin’anjiang (XAJ)], and one physically-based [variable infiltration capacity (VIC)]. The simulated reservoir inflows were then fed into a 10-day reservoir simulation model where DJKR operation followed the designed operating rules to evaluate reservoir operational performance. Finally, a data envelopment analysis (DEA) model was proposed to assess reservoir sustainability under both historical (1976–2005) and future (2021–2050) climate conditions. The results show that the combination of the GCM ensembles and the SIMHYD, HBV, XAJ, and VIC models exhibit similar growth patterns in the reservoir inflow and operational benefits for the future period. However, the DBN model produces consistent decreases in most cases, which may be attributed to its inability to generate accurate estimates of extreme events. The results indicate that hydrological models may be extensively utilized in decision making with greater confidence, and the data-driven model should be interpreted with caution when used in hydrological climate change impact studies. The efficiency metrics suggest that decision makers should focus more on increasing operational benefits, which can subsequently enhance reservoir sustainability. Overall, the framework proposed in this study provides a foundation for evaluating the reservoir sustainability and adaptability to climate change from water managers’ perspective.
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      Cascading Model-Based Framework for the Sustainability Assessment of a Multipurpose Reservoir in a Changing Climate

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4282614
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    contributor authorWenxin Xu
    contributor authorJie Chen
    contributor authorTianhua Su
    contributor authorJong-Suk Kim
    contributor authorLei Gu
    contributor authorJoo-Heon Lee
    date accessioned2022-05-07T20:33:57Z
    date available2022-05-07T20:33:57Z
    date issued2021-12-07
    identifier other(ASCE)WR.1943-5452.0001501.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4282614
    description abstractClimate change impacts on hydrological processes can affect reservoir operational performance. Hence, the reservoir operation model, based on historical climate conditions, may not guarantee sustainable water resources management in the future. To enable stakeholders to design reliable adaptation strategies, this study aims to propose a cascading framework to quantify the impacts of climate change on the operational performance and sustainability of a multipurpose reservoir. The Danjiangkou Reservoir (DJKR), which serves as the water source for the middle route of the South-to-North Water Diversion Project in China, was selected as a case study. To achieve the aforementioned aims, bias-corrected simulations from 13 global climate models (GCMs) were first input into five hydrological models [i.e., one data-driven [deep belief network (DBN)], three conceptual [SIMHYD, HBV, and Xin’anjiang (XAJ)], and one physically-based [variable infiltration capacity (VIC)]. The simulated reservoir inflows were then fed into a 10-day reservoir simulation model where DJKR operation followed the designed operating rules to evaluate reservoir operational performance. Finally, a data envelopment analysis (DEA) model was proposed to assess reservoir sustainability under both historical (1976–2005) and future (2021–2050) climate conditions. The results show that the combination of the GCM ensembles and the SIMHYD, HBV, XAJ, and VIC models exhibit similar growth patterns in the reservoir inflow and operational benefits for the future period. However, the DBN model produces consistent decreases in most cases, which may be attributed to its inability to generate accurate estimates of extreme events. The results indicate that hydrological models may be extensively utilized in decision making with greater confidence, and the data-driven model should be interpreted with caution when used in hydrological climate change impact studies. The efficiency metrics suggest that decision makers should focus more on increasing operational benefits, which can subsequently enhance reservoir sustainability. Overall, the framework proposed in this study provides a foundation for evaluating the reservoir sustainability and adaptability to climate change from water managers’ perspective.
    publisherASCE
    titleCascading Model-Based Framework for the Sustainability Assessment of a Multipurpose Reservoir in a Changing Climate
    typeJournal Paper
    journal volume148
    journal issue2
    journal titleJournal of Water Resources Planning and Management
    identifier doi10.1061/(ASCE)WR.1943-5452.0001501
    journal fristpage05021029
    journal lastpage05021029-19
    page19
    treeJournal of Water Resources Planning and Management:;2021:;Volume ( 148 ):;issue: 002
    contenttypeFulltext
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