Cascading Model-Based Framework for the Sustainability Assessment of a Multipurpose Reservoir in a Changing Climate
Publication: Journal of Water Resources Planning and Management
Volume 148, Issue 2
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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Data Availability Statement
The following data and code that support the findings of this study are available from the corresponding author upon reasonable request:
1.
All data used in this study.
2.
The code of the daily bias-correction method.
3.
The code of all models used in this study.
Acknowledgments
This work was partially supported by the Hubei Provincial Natural Science Foundation of China (No. 2020CFA100), the Natural Science Foundation of China (Grant Nos. 51779176 and 52079093), and the Overseas Expertise Introduction Project for Discipline Innovation (111 Project) funded by the Ministry of Education and State Administration of Foreign Experts Affairs, P.R. China (Grant No. B18037). The authors would like to acknowledge contributions from the World Climate Research Program Working Group on Coupled Modelling, and to thank climate modeling groups for providing their respective climate model outputs. The authors wish to thank the National Climatic Center of China Meteorological Administration and Bureau of Hydrology of the Changjiang Water Resources Commission for providing the data set for the Hanjiang River Basin.
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Journal of Water Resources Planning and Management
Volume 148 • Issue 2 • February 2022
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© 2021 American Society of Civil Engineers.
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Received: Mar 15, 2021
Accepted: Sep 26, 2021
Published online: Dec 7, 2021
Published in print: Feb 1, 2022
Discussion open until: May 7, 2022
ASCE Technical Topics:
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