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

被引:9
|
作者
Xu, Wenxin [1 ,2 ]
Chen, Jie [1 ,2 ]
Su, Tianhua [1 ,2 ]
Kim, Jong-Suk [1 ,2 ]
Gu, Lei [1 ,2 ]
Lee, Joo-Heon [3 ,4 ]
机构
[1] Wuhan Univ, State Key Lab Water Resources & Hydropower Engn S, Wuhan 430072, Peoples R China
[2] Wuhan Univ, Hubei Key Lab Water Syst Sci Sponge City Construc, Wuhan 430072, Peoples R China
[3] Joongbu Univ, Dept Civil Engn, Goyang Si 10279, Gyeunggi Do, South Korea
[4] Joongbu Univ, Drought Res Ctr, Goyang Si 10279, Gyeunggi Do, South Korea
关键词
Climate change; Multipurpose reservoir; Global climate models (GCMs); Hydrological models; Data envelopment analysis (DEA); Sustainability; DATA ENVELOPMENT ANALYSIS; CHANGE IMPACTS; WATER-RESOURCES; PERFORMANCE; HYDROLOGY; ENSEMBLE; UNCERTAINTY; EFFICIENCY; SENSITIVITY; GENERATION;
D O I
10.1061/(ASCE)WR.1943-5452.0001501
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
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.
引用
收藏
页数:19
相关论文
共 50 条
  • [1] A Hybrid Model-Based Adaptive Framework for the Analysis of Climate Change Impact on Reservoir Performance
    P. Biglarbeigi
    W. A. Strong
    D. Finlay
    R. McDermott
    P. Griffiths
    Water Resources Management, 2020, 34 : 4053 - 4066
  • [2] A Hybrid Model-Based Adaptive Framework for the Analysis of Climate Change Impact on Reservoir Performance
    Biglarbeigi, P.
    Strong, W. A.
    Finlay, D.
    McDermott, R.
    Griffiths, P.
    WATER RESOURCES MANAGEMENT, 2020, 34 (13) : 4053 - 4066
  • [3] A Model-Based Framework for the Estimation of the Self-Purifying Capacity of Intermittent Streams Under a Changing Climate
    Tritthart, Michael
    Wildt, Daniel
    Weigelhofer, Gabriele
    PROCEEDINGS OF THE 39TH IAHR WORLD CONGRESS, 2022, : 6028 - 6032
  • [4] Model-based Sustainability Assessment - an enabler for Transition to Sustainable Manufacturing
    Moldavska, Anastasiia
    23RD CIRP CONFERENCE ON LIFE CYCLE ENGINEERING, 2016, 48 : 413 - 418
  • [5] MODEL-BASED RESILIENCE ASSESSMENT FRAMEWORK FOR AUTONOMOUS SYSTEMS
    Diaconeasa, Mihai A.
    Mosleh, Ali
    Morozov, Andrey
    Tai, Ann T.
    PROCEEDINGS OF THE ASME INTERNATIONAL MECHANICAL ENGINEERING CONGRESS AND EXPOSITION, 2019, VOL 13, 2020,
  • [6] A model-based approach for sustainability and value assessment in the aerospace value chain
    Bertoni, Marco
    Hallstedt, Sophie
    Isaksson, Ola
    ADVANCES IN MECHANICAL ENGINEERING, 2015, 7 (06)
  • [7] A Reference Framework to Combine Model-Based Design and AR to Improve Social Sustainability
    Grandi, Fabio
    Khamaisi, Riccardo Karim
    Peruzzini, Margherita
    Raffaeli, Roberto
    Pellicciari, Marcello
    SUSTAINABILITY, 2021, 13 (04) : 1 - 16
  • [8] Stochastic model-based framework for assessment of sustainable manufacturing technology
    Yooeui Jin
    Sang Do Noh
    International Journal of Precision Engineering and Manufacturing, 2014, 15 : 519 - 525
  • [9] Stochastic Model-based Framework for Assessment of Sustainable Manufacturing Technology
    Jin, Yooeui
    Noh, Sang Do
    INTERNATIONAL JOURNAL OF PRECISION ENGINEERING AND MANUFACTURING, 2014, 15 (03) : 519 - 525
  • [10] Model-Based Relaying Supervision for Mitigation of Cascading Outages
    Lwin, Min
    Padullaparti, Harsha V.
    Santoso, Surya
    2016 IEEE POWER AND ENERGY SOCIETY GENERAL MEETING (PESGM), 2016,