Toward a New Flood Assessment Paradigm: From Exceedance Probabilities to the Expected Maximum Floods and Damages

Author:

Todini E.1,Reggiani P.2ORCID

Affiliation:

1. Italian Hydrological Society Bologna Italy

2. Research Institute for Water and Environment, Department of Civil Engineering University of Siegen Siegen Germany

Abstract

AbstractTo assess flood risks, we seek to estimate the probability distribution of the worst possible single‐event over a contiguous period of N years rather than the cumulative losses expected over a planning horizon. For this we use the probability distribution FN of extreme flood events over a multi‐year period, which is different from using the conventional single‐valued exceedance probability of 1/N years. FN can be used to estimate the hazard and then proceed to the estimation of risk, which we define as the “largest expected damage” over the set period. It also allows for a more coherent determination of design values, which descend from fully acknowledging the aleatoric uncertainty of the underlying natural river flow process. The epistemic uncertainty is removed by marginalizing the aleatoric‐epistemic uncertainty joint distribution over the parameter space. The advantage of the proposed Bayesian approach, which can be summarized in 12 steps, is demonstrated for the 2021 River Ahr flood in Germany, which caused casualties and huge material damage. Adopting the multi‐year maxima extreme value distribution can potentially lead to the reclassification of vulnerability levels for flood‐prone areas and reconsideration of current policy‐making and flood risk communication.

Funder

Deutsche Forschungsgemeinschaft

Publisher

American Geophysical Union (AGU)

Subject

Water Science and Technology

Reference67 articles.

1. Assessment of flood frequency models using empirical distribution function statistics

2. Statistical Analysis in Hydrology

3. Benson M. A.(1952).Characteristics of frequency curves based on a theoretical 1000 year record(Tech. Rep.).University of Melbourne.

4. Bayesian Theory

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3