Spatially dependent flood probabilities to support the design of civil infrastructure systems
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Published:2019-11-27
Issue:11
Volume:23
Page:4851-4867
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ISSN:1607-7938
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Container-title:Hydrology and Earth System Sciences
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language:en
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Short-container-title:Hydrol. Earth Syst. Sci.
Author:
Le Phuong Dong,Leonard Michael,Westra Seth
Abstract
Abstract. Conventional flood risk methods typically focus on estimation at a single
location, which can be inadequate for civil infrastructure systems such as
road or railway infrastructure. This is because rainfall extremes are
spatially dependent; to understand overall system risk, it is
necessary to assess the interconnected elements of the system jointly. For
example, when designing evacuation routes it is necessary to understand the
risk of one part of the system failing given that another region is flooded
or exceeds the level at which evacuation becomes necessary. Similarly,
failure of any single part of a road section (e.g., a flooded river
crossing) may lead to the wider system's failure (i.e., the entire road
becomes inoperable). This study demonstrates a spatially dependent
intensity–duration–frequency (IDF) framework that can be used to estimate flood
risk across multiple catchments, accounting for dependence both in space and
across different critical storm durations. The framework is demonstrated via
a case study of a highway upgrade comprising five river crossings. The
results show substantial differences in conditional and unconditional design
flow estimates, highlighting the importance of taking an integrated
approach. There is also a reduction in the estimated failure probability of
the overall system compared with the case where each river crossing is
treated independently. The results demonstrate the potential uses of
spatially dependent intensity–duration–frequency methods and suggest the
need for more conservative design estimates to take into account conditional
risks.
Publisher
Copernicus GmbH
Subject
General Earth and Planetary Sciences,General Engineering,General Environmental Science
Reference62 articles.
1. Ball, J., Babister, M., Nathan, R., Weeks, W., Weinmann, E., Retallick, M.,
and Testoni, I.: Australian Rainfall and Runoff: A Guide to Flood
Estimation, ©Commonwealth of Australia (Geoscience Australia),
available at: http://book.arr.org.au.s3-website-ap-southeast-2.amazonaws.com/ (last access: 25 October 2019), 2016. 2. Bárdossy, A. and Pegram, G. G. S.: Copula based multisite model for daily precipitation simulation, Hydrol. Earth Syst. Sci., 13, 2299–2314,
https://doi.org/10.5194/hess-13-2299-2009, 2009. 3. Baxevani, A. and Lennartsson, J.: A spatiotemporal precipitation generator
based on a censored latent Gaussian field, Water Resour. Res., 51,
4338–4358, https://doi.org/10.1002/2014WR016455, 2015. 4. Bennett, B., Lambert, M., Thyer, M., Bates, B. C., and Leonard, M.: Estimating Extreme Spatial Rainfall Intensities, J. Hydrol. Eng., 21, 04015074, https://doi.org/10.1061/(ASCE)HE.1943-5584.0001316, 2016a. 5. Bennett, B., Thyer, M., Leonard, M., Lambert, M., and Bates, B.: A
comprehensive and systematic evaluation framework for a parsimonious daily
rainfall field model, J. Hydrol., 556, 1123–1138, https://doi.org/10.1016/j.jhydrol.2016.12.043, 2016b.
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