Recent advances in vulnerability assessment for the built environment exposed to torrential hazards: Challenges and the way forward

Fuchs, Sven; Keiler, Margreth; Ortlepp, Regine; Schinke, Reinhard; Papathoma-Köhle, Maria

doi:10.1016/j.jhydrol.2019.05.067

Cited by 79 publications

(45 citation statements)

References 58 publications

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“…Stage-damage functions are a quantitative method for assessing the vulnerability of buildings, and they are widely used for 510 assessing flood hazard risk where the number of affected buildings is large enough to deduce a reliable curve (Fuchs et al, 2019a). These functions are continuous curves relating the magnitude of a hazard process (X-axis) to the damage state of a building (Y-axis), usually expressed as degree of loss.…”

Section: Stage-damage Curvesmentioning

confidence: 99%

“…However, these studies differ with respect to vulnerability definitions, vulnerability dimensions, the spatial scale of application, the applicability in the risk cycle, and according to the function of the developed index. Detailed reviews on vulnerability assessment methods are given by Papathoma-Köhle et al 80 (2017) and Fuchs et al (2019a).. Vulnerability assessment methods are mainly used to estimate damage or loss.…”

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confidence: 99%

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

Malgwi¹,

Fuchs²,

Keiler³

2019

Preprint

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10Although 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 15 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 20 for damage prediction in data-scarce regions to support loss assessment and to provide guidance for disaster risk reduction.

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Section: Stage-damage Curvesmentioning

confidence: 99%

mentioning

confidence: 99%

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

Malgwi¹,

Fuchs²,

Keiler³

2019

Preprint

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“…Following this approach, hazard-specific vulnerability can be assessed either in terms of loss estimates (e.g., Papathoma-Köhle et al, 2011;Fuchs et al, 2019) or in terms of other socioeconomic variables, such as limited access in case of road blockage or interruption (Schlögl et al, 2019). Focusing on the first and neglecting any type of hazard chains, our study demonstrates the application of risk to a specific road section in the Eastern European Alps and shows the sensitivity of the results using deterministic and probabilistic risk approaches.…”

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confidence: 93%

Multi-hazard risk assessment for roads: Probabilistic versus deterministic approaches

Oberndorfer

Sander

Fuchs

2020

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Abstract. Mountain hazard risk analysis for transport infrastructure is regularly based on deterministic approaches. Due to a variety of variables and data needed for risk computation, a considerable degree of epistemic uncertainty results. Consequently, input data needed for risk assessment is normally processed as mean values with or without scatter, or as an individual deterministic value from expert judgement if no statistical data is available. To overcome this gap, we used a probabilistic approach to express the potential bandwidth of input data with two different distribution functions, taking a mountain road in the Eastern European Alps as case study. The risk assessment included the damage potential of road infrastructure and traffic exposed to a multi-hazard environment (torrent processes, snow avalanches, rock fall). Reliable quantiles of the calculated probability density distributions attributed to the aggregated road risk due to the impact of multiple-mountain hazards were compared to the deterministic results from the standard guidelines on road safety. The results clearly show that with common deterministic approaches risk is significantly underestimated in comparison to a probabilistic risk modelling setup, mainly due to epistemic uncertainties of the input data. The study provides added value to further develop standardized road safety guidelines and may therefore be of particular importance for road authorities and political decision-makers.

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“…Merz et al, 2013;Amadio et al, 2019). A distinction can also be made between absolute and relative damage models: the first directly return a value in a specific currency (Dottori et al, 2016;Rouchon et al, 2018), while relative damage models estimate the physical vulnerability or the degree of loss of an exposed asset (Fuchs et al, 2019a), to be multiplied by its monetary value to assess the damage. Linked to this point is the question of what is defined as exposure in the models: besides the distinction whether a model relies on the value of the whole building or just of the affected floors, it is also important to know if, for instance, the basement is considered as well.…”

Section: Introductionmentioning

confidence: 99%

Are flood damage models converging to reality? Lessons learnt from a blind test

Molinari¹,

Scorzini²,

Arrighi³

et al. 2020

Preprint

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Abstract. Effective flood risk management requires a realistic estimation of flood losses. However, available flood damage estimates are still characterised by significant levels of uncertainty, questioning the capacity of flood damage models to depict real damages. With a joint effort of eight international research groups, the objective of this study was to compare the performances of different damage models for the estimation of the direct flood damage to the residential sector at the building level (i.e. micro scale) in a blind validation test. The test consisted in a common flood case study characterised by high availability of hazard and building data, but with undisclosed information on observed losses in the implementation stage of the models. The selected nine models were chosen in order to guarantee a good mastery of the models by the research teams, variety of the modelling approaches and heterogeneity of the original calibration context, in relation to both hazard and vulnerability features. By avoiding possible biases in model implementation, this blind comparison provided more objective insights on the transferability of the models and on the reliability of their estimations, especially regarding the potentials of local and multi-variable models. From another perspective, the exercise allowed to increase authors’ awareness on strengths and limits of flood damage modelling, which are summarised in the paper in the form of take-home messages from a modeller's perspective.

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Recent advances in vulnerability assessment for the built environment exposed to torrential hazards: Challenges and the way forward

Cited by 79 publications

References 58 publications

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

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

Multi-hazard risk assessment for roads: Probabilistic versus deterministic approaches

Are flood damage models converging to reality? Lessons learnt from a blind test

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