DOI: 10.1007/s11069-020-04413-x
论文题名: A probabilistic approach to estimating residential losses from different flood types
作者: Paprotny D. ; Kreibich H. ; Morales-Nápoles O. ; Wagenaar D. ; Castellarin A. ; Carisi F. ; Bertin X. ; Merz B. ; Schröter K.
刊名: Natural Hazards
ISSN: 0921030X
出版年: 2021
卷: 105, 期: 3 起始页码: 2569
结束页码: 2601
语种: 英语
中文关键词: Bayesian networks
; Coastal floods
; Flood damage surveys
; Fluvial floods
; Pluvial floods
英文摘要: Residential assets, comprising buildings and household contents, are a major source of direct flood losses. Existing damage models are mostly deterministic and limited to particular countries or flood types. Here, we compile building-level losses from Germany, Italy and the Netherlands covering a wide range of fluvial and pluvial flood events. Utilizing a Bayesian network (BN) for continuous variables, we find that relative losses (i.e. loss relative to exposure) to building structure and its contents could be estimated with five variables: water depth, flow velocity, event return period, building usable floor space area and regional disposable income per capita. The model’s ability to predict flood losses is validated for the 11 flood events contained in the sample. Predictions for the German and Italian fluvial floods were better than for pluvial floods or the 1993 Meuse river flood. Further, a case study of a 2010 coastal flood in France is used to test the BN model’s performance for a type of flood not included in the survey dataset. Overall, the BN model achieved better results than any of 10 alternative damage models for reproducing average losses for the 2010 flood. An additional case study of a 2013 fluvial flood has also shown good performance of the model. The study shows that data from many flood events can be combined to derive most important factors driving flood losses across regions and time, and that resulting damage models could be applied in an open data framework. © 2020, The Author(s). Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/169281
Appears in Collections: 气候变化与战略
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作者单位: Helmholtz Centre Potsdam, GFZ German Research Centre for Geosciences, Section Hydrology, Potsdam, Germany; Department of Hydraulic Engineering, Delft University of Technology, Delft, Netherlands; Deltares, Delft, Netherlands; DICAM, Water Resources, University of Bologna, Bologna, Italy; UMR 7266 LIENSs CNRS-La Rochelle Université, La Rochelle, France; Institute for Environmental Sciences and Geography, University of Potsdam, Potsdam, Germany
Recommended Citation:
Paprotny D.,Kreibich H.,Morales-Nápoles O.,et al. A probabilistic approach to estimating residential losses from different flood types[J]. Natural Hazards,2021-01-01,105(3)