A modeling framework for evaluating the drought resilience of a surface water supply system under non-stationarity

被引:25
|
作者
Zhao, Gang [1 ]
Gao, Huilin [1 ]
Kao, Shih-Chieh [2 ,3 ]
Voisin, Nathalie [4 ]
Naz, Bibi S. [5 ]
机构
[1] Texas A&M Univ, Zachry Dept Civil Engn, College Stn, TX 77843 USA
[2] Oak Ridge Natl Lab, Div Environm Sci, POB 2008, Oak Ridge, TN 37831 USA
[3] Oak Ridge Natl Lab, Climate Change Sci Inst, Oak Ridge, TN 37831 USA
[4] Pacific Northwest Natl Lab, Hydrol Grp, Richland, WA 99352 USA
[5] Forschungszentrum Julich, Inst Bio & Geosci Agrosphere IBG 3, D-52428 Julich, Germany
基金
美国国家科学基金会;
关键词
Water supply resilience; Non-stationarity; Droughts; Climate change; Demand growth; CLIMATE-CHANGE; FLOOD FREQUENCY; GLOBAL DROUGHT; RIVER-BASIN; IMPACTS; UNCERTAINTY; SUSTAINABILITY; URBANIZATION; 21ST-CENTURY; RESOURCES;
D O I
10.1016/j.jhydrol.2018.05.037
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
The future resilience of water supply systems is unprecedentedly challenged by non-stationary processes, such as fast population growth and a changing climate. A thorough understanding of how these non-stationarities impact water supply resilience is vital to support sustainable decision making, particularly for large cities in arid and/or semi-arid regions. In this study, a novel modeling framework, which integrates hydrological processes and water management, was established over a representative water limited metropolitan area to evaluate the impacts of water availability and water demand on reservoir storage and water supply reliability. In this framework, climate change induced drought events were selected from statistically downscaled Coupled Model Intercomparison Project Phase 5 outputs under the Representative Concentration Pathway 83 scenario, while future water demand was estimated by the product of projected future population and per capita water use. Compared with the first half of the 21st century (2000-2049), reservoir storage and water supply reliability during the second half century (2050-2099) are projected to reduce by 16.1% and 14.2%, respectively. While both future multi-year droughts and population growth will lower water supply resilience, the uncertainty associated with future climate projection is larger than that associated with urbanization. To reduce the drought risks, a combination of mitigation strategies (e.g., additional conservation, integrating new water sources, and water use redistribution) was found to be the most efficient approach and can significantly improve water supply reliability by as much as 15.9%.
引用
收藏
页码:22 / 32
页数:11
相关论文
共 38 条
  • [1] Modeling hydrological non-stationarity to analyze environmental impacts on drought propagation
    Jehanzaib, Muhammad
    Ali, Shoaib
    Kim, Min Ji
    Kim, Tae-Woong
    [J]. ATMOSPHERIC RESEARCH, 2023, 286
  • [2] A Regional-Scale Non-Stationarity Based Framework in Unsaturated Zone Flow Modeling
    Karamouz, Mohammad
    Meidani, Hadi
    Mahmoodzadeh, Davood
    [J]. WORLD ENVIRONMENTAL AND WATER RESOURCES CONGRESS 2021: PLANNING A RESILIENT FUTURE ALONG AMERICA'S FRESHWATERS, 2021, : 52 - 63
  • [3] Evaluating the Non-Stationarity, Seasonality and Temporal Risk to Water Resources in the Wei River Basin
    Yuan, Xin
    O'Loughlin, Fiachra
    [J]. WATER, 2024, 16 (17)
  • [4] A simple framework for estimating the annual runoff frequency distribution under a non-stationarity condition
    Liu, Ziwei
    Yang, Hanbo
    Wang, Taihua
    [J]. JOURNAL OF HYDROLOGY, 2021, 592
  • [5] Evaluation and promotion strategy of resilience of urban water supply system under flood and drought disasters
    Li, Zhijie
    Zhao, Hui
    Liu, Jinning
    Zhang, Jingqi
    Shao, Zhiguo
    [J]. SCIENTIFIC REPORTS, 2022, 12 (01)
  • [6] Evaluation and promotion strategy of resilience of urban water supply system under flood and drought disasters
    Zhijie Li
    Hui Zhao
    Jinning Liu
    Jingqi Zhang
    Zhiguo Shao
    [J]. Scientific Reports, 12
  • [7] Modeling longitudinal INMA(1) with COM–Poisson innovation under non-stationarity: application to medical data
    Naushad Mamode Khan
    Vandna Jowaheer
    Yuvraj Sunecher
    Marcelo Bourguignon
    [J]. Computational and Applied Mathematics, 2018, 37 : 5217 - 5238
  • [8] Modeling longitudinal INMA(1) with COM-Poisson innovation under non-stationarity: application to medical data
    Khan, Naushad Mamode
    Jowaheer, Vandna
    Sunecher, Yuvraj
    Bourguignon, Marcelo
    [J]. COMPUTATIONAL & APPLIED MATHEMATICS, 2018, 37 (04): : 5217 - 5238
  • [9] Assessing the effects of non-stationarity on reservoir yield estimations: A case study of the Southern Okavango Integrated Water Development system in Botswana
    Mazvimavi, Dominic
    Kapangaziwiri, Evison
    Gumbo, Anesu Dion
    [J]. RIVER RESEARCH AND APPLICATIONS, 2024, 40 (01) : 3 - 13
  • [10] RESILIENCE EMERGENCY STRATEGIES FOR URBAN WATER SUPPLY SYSTEM UNDER EMERGENT WATER POLLUTION EVENTS
    Yan Yan
    Zhu Aimin
    Tsydypova, Ayagma
    [J]. ENVIRONMENTAL ENGINEERING AND MANAGEMENT JOURNAL, 2021, 20 (02): : 185 - 194