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

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

A method to reconstruct flood scenarios using field interviews and hydrodynamic modelling: application to the 2017 Suleja and Tafa, Nigeria flood

Abstract The scarcity of model input and calibration data has limited efforts in reconstructing scenarios of past floods in many regions globally. Recently, the number of studies that use distributed post-flood observation data collected throughout flood-affected communities (e.g. face-to-face interviews) are increasing. However, a systematic method that applies such data for hydrodynamic modelling of past floods in locations without hydrological is lacking. In this study, we developed a method for reconstructing plausible scenarios of past flood events in data-scarce regions by applying flood observation data collected through field interviews to a hydrodynamic model (CAESAR-Lisflood). We tested the method using 300 spatially distributed flood depths and duration data collected using questionnaires on five river reaches after the 2017 flood event in Suleja and Tafa region, Nigeria. A stepwise process that aims to minimize the error between modelled and observed flood depth and duration at the locations of interviewed households was implemented. Results from the reconstructed flood depth scenario produced an error of ± 0.61 m for all observed and modelled locations and lie in the range of error produced by studies using comparable hydrodynamic models. The study demonstrates the potential of utilizing interview data for hydrodynamic modelling applications in data-scarce regions to support regional flood risk assessment. Furthermore, the method can provide flow depths and durations at houses without observations, which is useful input data for physical vulnerability assessment to complement disaster risk reduction efforts

Scenario building and runout modelling for debris flow hazards in pro-/periglacial catchments with scarce past event data: application of a multi-methods approach for the Dar catchment (western Swiss Alps)

In high mountain areas, the disposition (susceptibility of occurrence) for debris flows is increasing in steep terrain, as – due to climate change – rapid glacier retreat and permafrost degradation is favouring higher availability of loose sediments. The probability of occurrence and magnitude of pro- and periglacial debris flows is increasing, too, as triggering events such as heavy thunderstorms, long-lasting rainfalls, intense snow melt or rain-on-snow events are likely to occur more often and more intensely in future decades. Hazard assessment for debris flows originating from pro- and periglacial areas is thus crucial but remains challenging, as records of past events on which local magnitude-frequency relationships and debris flow scenarios can be based on are often scarce or inexistent. In this study, we present a multi-methods approach for debris flow hazard scenario building and runout modelling in pro- and periglacial catchments with scarce past event data. Scenario building for the debris flow initiation zone reposes on (i) the definition of meteorological and hydrological triggering scenarios using data on extreme point rainfall and precipitation-runoff modelling, and (ii) the definition of bed load scenarios from empirical approaches and field surveys. Numerical runout modelling and hazard assessment for the resulting debris flow scenarios is carried out using RAMMS-DF, which was calibrated to the studied catchment (Le Dar, western Swiss Alps) based on the area of debris flow deposits from the single major event recorded there in summer 2005. The developed approach is among the first to propose systematic scenario building for pro- and periglacial debris flows triggered by precipitation dependent events

A physical approach on flood risk vulnerability of buildings

The design of efficient hydrological risk mitigation strategies and their subsequent implementation relies on a careful vulnerability analysis of the elements exposed. Recently, extensive research efforts were undertaken to develop and refine empirical relationships linking the structural vulnerability of buildings to the impact forces of the hazard processes. These empirical vulnerability functions allow estimating the expected direct losses as a result of the hazard scenario based on spatially explicit representation of the process patterns and the elements at risk classified into defined typological categories. However, due to the underlying empiricism of such vulnerability functions, the physics of the damage-generating mechanisms for a well-defined element at risk with its peculiar geometry and structural characteristics remain unveiled, and, as such, the applicability of the empirical approach for planning hazard-proof residential buildings is limited. Therefore, we propose a conceptual assessment scheme to close this gap. This assessment scheme encompasses distinct analytical steps: modelling (a) the process intensity, (b) the impact on the element at risk exposed and (c) the physical response of the building envelope. Furthermore, these results provide the input data for the subsequent damage evaluation and economic damage valuation. This dynamic assessment supports all relevant planning activities with respect to a minimisation of losses, and can be implemented in the operational risk assessment procedure

Short communication: A model to predict flood loss in mountain areas

Because effects of climate change and an increase in elements at risk, mountain hazard loss increased throughout Europe. Yet, factors influencing loss, i.e. vulnerability, have gained less attention to date. Vulnerability is defined as the degree of loss resulting from the hazard impact on buildings. Recent studies have focused on evaluating vulnerability to dynamic flooding using proxies from case studies and based on empirical ex-post approaches. However, the transferability to other case studies and, therefore, the ability of such models to actually predict future losses is limited. To overcome this gap, we present a beta model based on loss data from the European Alps, which clearly shows that a single vulnerability function is sufficient to predict losses resulting from different types of torrential hazards and to provide probabilities of destruction under specific scenarios. As a result, the curves are transferable and may significantly increase the predictive power of risk analyses

Vulnerability patterns of road network to extreme floods based on accessibility measures

Accessibility is a key measure of the vulnerability of road networks to disruptions such as floods. However, studies comparing the contribution of parameters to the accuracy of accessibility-based vulnerability assessment are lacking. We propose modifying two accessibility measures to include flood-affected populations, opportunities, and average shortest travel time. We also applied three methods including the divergent ranking method to identify the direct impact of extreme floods on road networks. The shortest travel time pathway calculation was enhanced with the inclusion of spatially distributed settlements as an input. The results indicate a strong relationship between parameter weights and the accessibility measures, irrespective of the evaluated approaches. The results of the study highlight that measures of overall vulnerability, with respect to inter-comparisons of flood scenarios alone, do not fully capture the local vulnerability of some traffic zones. This is particularly evident with the flooding of highly connected roads that serve these zones

Development of the damage potential resulting from avalanche risk in the period 1950-2000, case study Galtur

International audienceThe risk resulting from natural hazards can be derived from the combination of parameters of physical processes and the damage potential. Even though the damage potential has been taken into account more frequently, quantifying statements are still missing. This study presents a detailed recording of the damage potential in the study area and describes the development of the damage potential since 1950 in decades. In the community, the increase of the number of buildings and their values is above average of the region. 37% of the existing buildings are located in legally declared avalanche hazard zones. In these areas, the probability of presence of persons increased considerably due to tourism activities and shows substantial seasonal fluctuations. If the analysis of the damage potential and the hazard estimation are performed with the same degree of precision, risk analysis and risk management will be improved significantly