Journal article
Ensemble-based flood vulnerability assessment for probable maximum flood in a changing environment
Journal of Hydrology, Vol.576, pp.342-355
2019
Abstract
The magnitude and frequency of hydro-meteorological extremes are expected to increase in a changing environment in ways that threaten the security of US energy-water assets. These include probable maximum precipitation (PMP) and probable maximum flood (PMF), which are used as hydraulic design standards for highly sensitive infrastructures such as nuclear power plants and main dams. To assess the flood vulnerability due to PMP/PMF, an integrated high-resolution process-based hydro-meteorologic modeling framework was used to develop ensemble-based probabilistic flood maps based on best-available historic observations and future climate projections. A graphics processing unit-accelerated 2-dimensional hydrodynamic model was used to simulate the surface inundation areas corresponding to a total of 120 PMF hydrographs. These ensemble-based PMF maps were compared with flood maps obtained from the conventional deterministic PMP/PMF approach, revealing added information about conditional probability of flooding. Further, a relative sensitivity test was conducted to explore the effects of various factors in the framework, such as meteorological forcings, antecedent hydrologic conditions, reservoir storage, and flood model input resolution and parameters. The proposed framework better illustrates the uncertainties associated with model inputs, parameterization, and hydro-meteorological factors, allowing more informed decision-making for future emergency preparation.
Details
- Title
- Ensemble-based flood vulnerability assessment for probable maximum flood in a changing environment
- Authors
- S Gangrade (Author)S-C Kao (Author)T T Dullo (Author)A J Kalyanapu (Author)Benjamin Preston (Author) - RAND Corporation, United States
- Publication details
- Journal of Hydrology, Vol.576, pp.342-355
- Publisher
- Elsevier BV
- Date published
- 2019
- DOI
- 10.1016/j.jhydrol.2019.06.027
- ISSN
- 0022-1694
- Organisation Unit
- University of the Sunshine Coast, Queensland; Sustainability Research Cluster
- Language
- English
- Record Identifier
- 99451212002621
- Output Type
- Journal article
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- Collaboration types
- Domestic collaboration
- Web Of Science research areas
- Engineering, Civil
- Geosciences, Multidisciplinary
- Water Resources
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