Bayesian characterization of uncertainties surrounding fluvial flood hazard estimates

Sharma, Sanjib; Ghimire, Ganesh Raj; Talchabhadel, Rocky; Panthi, Jeeban; Lee, Benjamin Seiyon; Sun, Fengyun; Baniya, Rupesh; Adhikari, Tirtha Raj

doi:10.1080/02626667.2021.1999959

Title: Bayesian characterization of uncertainties surrounding fluvial flood hazard estimates

Journal Article · 21 January 2022 · Hydrological Sciences Journal

DOI: https://doi.org/10.1080/02626667.2021.1999959 · OSTI ID:1842597

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^[5]; Sun, Fengyun ^[6]; Baniya, Rupesh ^[7]; Adhikari, Tirtha Raj ^[8]

Pennsylvania State Univ., University Park, PA (United States)
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Texas A & M Univ., El Paso, TX (United States)
Univ. of Rhode Island, Kingston, RI (United States)
George Mason Univ., Fairfax, VA (United States)
East China Normal Univ. (ECNU), Shanghai (China)
Tribhuvan Univ., Lalitpur (Nepal)
Tribhuvan Univ., Kirtipur (Nepal)

Fluvial floods drive severe risk to riverine communities. There is strong evidence of increasing flood hazards in many regions around the world. The choice of methods and assumptions used in flood hazard estimates can impact the design of risk management strategies. In this study, we characterize the expected flood hazards conditioned on the uncertain model structures, model parameters, and prior distributions of the parameters. We construct a Bayesian framework for river stage return level estimation using a nonstationary statistical model that relies exclusively on the Indian Ocean Dipole Index. We show that ignoring uncertainties can lead to biased estimation of expected flood hazards. We find that the considered model parametric uncertainty is more influential than model structures and model priors. Our results highlight the importance of incorporating uncertainty in extreme flood stage estimates, and are of practical use for informing water infrastructure designs in a changing climate.

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Research Organization:: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Sponsoring Organization:: USDOE

Grant/Contract Number:: AC05-00OR22725

OSTI ID:: 1842597

Journal Information:: Hydrological Sciences Journal, Journal Name: Hydrological Sciences Journal Journal Issue: 2 Vol. 67; ISSN 0262-6667

Publisher:: Taylor & FrancisCopyright Statement

Country of Publication:: United States

Language:: English

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Bayesian characterization of uncertainties surrounding fluvial flood hazard estimates Sharma, Sanjib; Ghimire, Ganesh Raj; Talchabhadel, Rocky https://doi.org/10.6084/m9.figshare.16924263 The current record is supplemented by this text	text	January 2021
Bayesian characterization of uncertainties surrounding fluvial flood hazard estimates Sharma, Sanjib; Ghimire, Ganesh Raj; Talchabhadel, Rocky https://doi.org/10.6084/m9.figshare.16924263.v1 The current record is supplemented by this text	text	January 2021

Title: Bayesian characterization of uncertainties surrounding fluvial flood hazard estimates

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