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

Zhao, Gang; Gao, Huilin; Kao, Shih -Chieh; Voisin, Nathalie; Naz, Bibi S.

doi:10.1016/j.jhydrol.2018.05.037

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

Journal Article · Wed May 23 00:00:00 EDT 2018 · Journal of Hydrology

DOI:https://doi.org/10.1016/j.jhydrol.2018.05.037· OSTI ID:1440826

^[1]; ^[1]; ^[2]; ^[3]; Naz, Bibi S. ^[4]

Texas A & M Univ., College Station, TX (United States)
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Forschungszentrum Julich, Julich (Germany)

Here, 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 8.5 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%.

View Accepted Manuscript (DOE)

Research Organization:: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States); Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)

Sponsoring Organization:: USDOE; USDOE Office of Energy Efficiency and Renewable Energy (EERE)

Grant/Contract Number:: AC05-00OR22725; AC05-76RL01830

OSTI ID:: 1440826

Alternate ID(s):: OSTI ID: 1548252
OSTI ID: 1454775
OSTI ID: 1489983

Report Number(s):: PNNL--SA-135071

Journal Information:: Journal of Hydrology, Journal Name: Journal of Hydrology Journal Issue: C Vol. 563; ISSN 0022-1694

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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