Spatially dependent flood probabilities to support  the design of civil infrastructure systems

Le, Phuong Dong; Leonard, Michael; Westra, Seth

doi:https://doi.org/10.5194/hess-23-4851-2019

Articles | Volume 23, issue 11

https://doi.org/10.5194/hess-23-4851-2019

© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/hess-23-4851-2019

© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 23, issue 11

Research article

|

27 Nov 2019

Research article |

| 27 Nov 2019

Spatially dependent flood probabilities to support the design of civil infrastructure systems

Phuong Dong Le, Michael Leonard, and Seth Westra

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Cited articles

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.

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.

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.

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.

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.