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Natural Hazards and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/nhess-2019-366
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-2019-366
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 22 Nov 2019

Submitted as: research article | 22 Nov 2019

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Natural Hazards and Earth System Sciences (NHESS).

An adaptive regional vulnerability assessment model: Review and concepts for data-scarce regions

Mark Bawa Malgwi1,2, Sven Fuchs3, and Margreth Keiler1,2,4 Mark Bawa Malgwi et al.
  • 1University of Bern, Institute of Geography, Hallerstrasse 12, 3012 Bern, Switzerland
  • 2University of Bern, Oeschger Centre for Climate Change Research, Hochschulstrasse 6, 3012 Bern, Switzerland
  • 3University of Natural Resources and Life Sciences, Institute of Mountain Risk Engineering, Peter-Jordan-Str. 82, 1190 Vienna, Austria
  • 4University of Bern, Mobiliar Lab for Natural Risks, Hallerstrasse 12, 3012 Bern, Switzerland

Abstract. Although the vulnerability indicator method has been applied to several data-scarce regions, a missing linkage with damage grades had hindered its application for loss evaluation to complement disaster risk reduction efforts. To address this gap, we present a review of physical vulnerability indicators and flood damage models to gain insights on best practice. Thereafter, we present a conceptual framework for linking the vulnerability indicators and damage grades using three phases (i) developing a vulnerability index, (ii) identifying regional damage grades, and (iii) linking vulnerability index classes with damage grades. The vulnerability index comprehensively integrates elements of the hazard using a Building Impact Index (BII) on one hand, and exposure, susceptibility and local protection elements using a Building Resistance Index (BRI) on the other hand. For the damage grades, local expert assessments are used for identifying and categorizing frequently observed regional damage patterns. Finally, by means of synthetic what-if analysis, experts are asked to estimate damage grades for each interval of the BII and class of BRI to develop a vulnerability curve. The proposed conceptual framework can be used for damage prediction in data-scarce regions to support loss assessment and to provide guidance for disaster risk reduction.

Mark Bawa Malgwi et al.
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Mark Bawa Malgwi et al.
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Short summary
Damage prediction is important for economic assessment of future flood scenarios so that stake-holders and emergency planners can strategize against disasters. This paper utilizes a combination of methods (vulnerability indicators and synthetic what-if analysis) to develop a conceptual framework for predicting building damage grade in data-scarce regions. The framework promotes transferability of damage prediction methods in data-scarce areas and can be fully implemented using expert knowledge.
Damage prediction is important for economic assessment of future flood scenarios so that...
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