A comparison of building value models for flood risk analysis

Quantitative flood risk analyses support decisions in flood management policies that aim for cost efficiency. Risk is commonly calculated by a combination of the three quantified factors: hazard, exposure and vulnerability. Our paper focuses on the quantification of exposure, in particular on the relevance of building value estimation schemes within flood exposure analyses on regional to national scales. We compare five different models that estimate the values of flood-exposed buildings. Four of them refer to individual buildings, whereas one is based on values per surface area, differentiated by land use category. That one follows an approach commonly used in flood risk analyses on regional or larger scales. Apart from the underlying concepts, the five models differ in complexity, data and computational expenses required for parameter estimations and in the data they require for model application.The model parameters are estimated by using a database of more than half a million building insurance contracts in Switzerland, which are provided by 11 (out of 19) cantonal insurance companies for buildings that operate under a monopoly within the respective Swiss cantons. Comparing the five model results with the directly applied spatially referenced insurance data suggests that models based on individual buildings produce better results than the model based on surface area, but only if they include an individual building's volume.Applying the five models to all of Switzerland produces results that are very similar with regard to the spatial distribution of exposed-building values. Therefore, for spatial prioritizations, simpler models are preferable. In absolute values, however, the five model results differ remarkably. The two simplest models underestimate the overall exposure, and even more so the extreme high values, upon which risk management strategies generally focus. In decision-making processes based on cost-efficiency, this underestimation would result in suboptimal resource allocation for protection measures. Consequently, we propose that estimating exposed-building values should be based on individual buildings rather than on areas of land use types. In addition, a building's individual volume has to be taken into account in order to provide a reliable basis for cost–benefit analyses. The consideration of other building features further improves the value estimation. However, within the context of flood risk management, the optimal value estimation model depends on the specific questions to be answered. The concepts of the presented building value models are generic. Thus, these models are transferable, with minimal adjustments according to the application's purpose and the data available. Within risk analyses, the paper's focus is on exposure. However, the findings also have direct implications for flood risk analyses as most risk analyses take the value of exposed assets into account in a linear way.</p

Effects of variability in probable maximum precipitation patterns on flood losses

The assessment of the impacts of extreme floods is important for dealing with residual risk, particularly for critical infrastructure management and for insurance purposes. Thus, modelling of the probable maximum flood (PMF) from probable maximum precipitation (PMP) by coupling hydrological and hydraulic models has gained interest in recent years. Herein, we examine whether variability in precipitation patterns exceeds or is below selected uncertainty factors in flood loss estimation and if the flood losses within a river basin are related to the probable maximum discharge at the basin outlet. We developed a model experiment with an ensemble of probable maximum precipitation scenarios created by Monte Carlo simulations. For each rainfall pattern, we computed the flood losses with a model chain and benchmarked the effects of variability in rainfall distribution with other model uncertainties. The results show that flood losses vary considerably within the river basin and depend on the timing and superimposition of the flood peaks from the basin's sub-catchments. In addition to the flood hazard component, the other components of flood risk, exposure, and vulnerability contribute remarkably to the overall variability. This leads to the conclusion that the estimation of the probable maximum expectable flood losses in a river basin should not be based exclusively on the PMF. Consequently, the basin-specific sensitivities to different precipitation patterns and the spatial organization of the settlements within the river basin need to be considered in the analyses of probable maximum flood losses

Blended Learning in ESP Methodology: WebQuest

The paper focuses on key issues of blended learning and introduces the idea of WebQuest and the adaptation of this approach in teaching ESP.Статья посвящена основным вопросам смешанного обучения (blended learning) и рассматривает возможности использования образовательной технологии WebQuest при обучении английскому языку профессионального общения

Brief communication: "An inventory of permafrost evidence for the European Alps"

The investigation and modelling of permafrost distribution, particularly in areas of discontinuous permafrost, is challenging due to spatial heterogeneity, remoteness of measurement sites and data scarcity. We have designed a strategy for standardizing different local data sets containing evidence of the presence or absence of permafrost into an inventory for the entire European Alps. With this brief communication, we present the structure and contents of this inventory. This collection of permafrost evidence not only highlights existing data and allows new analyses based on larger data sets, but also provides complementary information for an improved interpretation of monitoring results

ROckfall risk MAnagement assessment: the RO.MA. approach

The analysis of risk for vehicles and drivers as a result of rockfall on a road is relevant to design management in geotechnical engineering. This process is very complex due to the large number of parameters involved. In this paper, we discuss risk analysis and management procedures for roads subject to rockfall phenomena. To this aims, we are proposing a quantitative method (the RO.MA. approach). We developed an abacus to define the threshold values of acceptable rockfall risk for a given road. Rockfall risk is calculated using an Event Tree approach and compared with the abacus thresholds to evaluate road safety and the need for additional protective measures to reduce the risk to an acceptable level. The approach was successfully applied at a test site located in Bard, Aosta Valley, north-western Italy