A generic physical vulnerability model for floods: review and concept for data-scarce regions

被引:34
|
作者
Malgwi, Mark Bawa [1 ,2 ]
Fuchs, Sven [3 ]
Keiler, Margreth [1 ,2 ,4 ]
机构
[1] Univ Bern, Inst Geog, Hallerstr 12, CH-3012 Bern, Switzerland
[2] Univ Bern, Oeschger Ctr Climate Change Res, Hochschulstr 6, CH-3012 Bern, Switzerland
[3] Univ Nat Resources & Life Sci, Inst Mt Risk Engn, Peter Jordan Str 82, A-1190 Vienna, Austria
[4] Univ Bern, Mobiliar Lab Nat Risks, Hallerstr 12, CH-3012 Bern, Switzerland
关键词
INDICATOR-BASED APPROACH; DISASTER RISK; URBAN VULNERABILITY; DAMAGE ASSESSMENT; COASTAL CITIES; CLIMATE-CHANGE; FLASH FLOODS; LARGE-SCALE; PTVA MODEL; HAZARDS;
D O I
10.5194/nhess-20-2067-2020
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
The use of different methods for physical flood vulnerability assessment has evolved over time, from traditional single-parameter stage-damage curves to multi-parameter approaches such as multivariate or indicator-based models. However, despite the extensive implementation of these models in flood risk assessment globally, a considerable gap remains in their applicability to data-scarce regions. Considering that these regions are mostly areas with a limited capacity to cope with disasters, there is an essential need for assessing the physical vulnerability of the built environment and contributing to an improvement of flood risk reduction. To close this gap, we propose linking approaches with reduced data requirements, such as vulnerability indicators (integrating major damage drivers) and damage grades (integrating frequently observed damage patterns). First, we present a review of current studies of physical vulnerability indicators and flood damage models comprised of stage-damage curves and the multivariate methods that have been applied to predict damage grades. Second, we propose a new conceptual framework for assessing the physical vulnerability of buildings exposed to flood hazards that has been specifically tailored for use in data-scarce regions. This framework is operationalized in three steps: (i) developing a vulnerability index, (ii) identifying regional damage grades, and (iii) linking resulting index classes with damage patterns, utilizing a synthetic "what-if" analysis. The new framework is a first step for enhancing flood damage prediction to support risk reduction in data-scarce regions. It addresses selected gaps in the literature by extending the application of the vulnerability index for damage grade prediction through the use of a synthetic multi-parameter approach. The framework can be adapted to different data-scarce regions and allows for integrating possible modifications to damage drivers and damage grades.
引用
收藏
页码:2067 / 2090
页数:24
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