Risk-based damage potential and loss estimation of extreme flooding scenarios in the Austrian Federal Province of Tyrol

Within the last decades serious flooding events occurred in many parts of Europe and especially in 2005 the Austrian Federal Province of Tyrol was serious affected. These events in general and particularly the 2005 event have sensitised decision makers and the public. Beside discussions pertaining to protection goals and lessons learnt, the issue concerning potential consequences of extreme and severe flooding events has been raised. Additionally to the general interest of the public, decision makers of the insurance industry, public authorities, and responsible politicians are especially confronted with the question of possible consequences of extreme events. Answers thereof are necessary for the implementation of preventive appropriate risk management strategies. Thereby, property and liability losses reflect a large proportion of the direct tangible losses. These are of great interest for the insurance sector and can be understood as main indicators to interpret the severity of potential events. The natural scientific-technical risk analysis concept provides a predefined and structured framework to analyse the quantities of affected elements at risk, their corresponding damage potentials, and the potential losses. Generally, this risk concept framework follows the process steps hazard analysis, exposition analysis, and consequence analysis. Additionally to the conventional hazard analysis, the potential amount of endangered elements and their corresponding damage potentials were analysed and, thereupon, concrete losses were estimated. These took the specific vulnerability of the various individual elements at risk into consideration. The present flood risk analysis estimates firstly the general exposures of the risk indicators in the study area and secondly analyses the specific exposures and consequences of five extreme event scenarios. In order to precisely identify, localize, and characterize the relevant risk indicators of buildings, dwellings and inventory, vehicles, and individuals, a detailed geodatabase of the existing stock of elements and values was established on a single object level. Therefore, the localized and functional differentiated stock of elements was assessed monetarily on the basis of derived representative mean insurance values. Thus, well known difference factors between the analysis of the stock of elements and values on local and on regional scale could be reduced considerably. The spatial join of the results of the hazard analysis with the stock of elements and values enables the identification and quantification of the elements at risk and their corresponding damage potential. Thereupon, Extreme Scenario Losses (ESL) were analysed under consideration of different vulnerability approaches which describe the individual element's specific susceptibility. This results in scenario-specific ranges of ESL rather than in single values. The exposure analysis of the general endangerment in Tyrol identifies (i) 105 330 individuals, (ii) 20 272 buildings and 50 157 dwellings with a corresponding damage potential of approx. EUR 20 bn. and (iii) 62 494 vehicles with a corresponding damage potential of EUR 1 bn. Depending on the individual extreme event scenarios, the ESL solely to buildings and inventory vary between EUR 0.9–1.3 bn. for the scenario with the least ESL and EUR 2.2–2.5 bn. for the most serious scenarios. The correlation of the private property losses to buildings and inventory with further direct tangible loss categories on the basis of investigation after the event in 2005, results in potential direct tangible ESL of up to EUR 7.6 bn. Apart from the specific study results a general finding shows that beside the further development of modelling capabilities and scenario concepts, the key to considerably decrease uncertainties of integral flood risk analyses is the development and implementation of more precise methods. These are to determine the stock of elements and values and to evaluate the vulnerability or susceptibility of affected structures to certain flood characteristics more differentiated

Ermittlung des monetären Werteinventars als Basis von Analysen naturgefahreninduzierter Risiken in Tirol (Österreich)

Im Rahmen von Risikoanalysen besitzt die Quantifizierung und Monetarisierung der potenziellen Risikoelemente zur Ermittlung des Werteinventars eine wesentliche Rolle, speziell bei regionalen Maßstabsebenen bestehen jedoch große Unsicherheiten. Durch eine differenzierte Bearbeitung und die Anwendung von repräsentativen, aus einzelnen Versicherungspolicen analysierten Werten können diese Unsicherheiten wesentlich minimiert werden. Eingebunden in eine moderne (Geo-)Datenbankstruktur entsteht ein effizientes Instrument für Expositions- und Folgenanalysen naturgefahreninduzierter Risiken

Bed-load transport modelling by coupling an empirical routing scheme and a hydrological-1-D-hydrodynamic model – case study application for a large alpine valley

Sediment transport in mountain rivers and torrents is a substantial process within the assessment of flood related hazard potential and vulnerability in alpine catchments. Focusing on fluvial transport processes, river bed erosion and deposition considerably affects the extent of inundation. The present work deals with scenario-specific bed-load transport modelling in a large alpine valley in the Austrian Alps. A routing scheme founding on empirical equations for the calculation of transport capacities, incipient motion conditions and drag forces is set up and applied to the case study area for two historic flood events. The required hydraulic data result from a distributed hydrological-1-D-hydraulic model. Hydraulics and bed-load transport are simulated sequentially providing a technically well-founded and feasible methodology for the estimation of bed-load transport rates during flood events

L'adaptation dynamique de l'infrastructure de l'eau en milieu urbain, en réponse à un environnement changeant

Colloque avec actes et comité de lecture. Internationale.International audienc

Continuous monitoring of snowpack dynamics in alpine terrain by aboveground neutron sensing

The characteristics of an aboveground cosmic-ray neutron sensor (CRNS) are evaluated for monitoring a mountain snowpack in the Austrian Alps from March 2014 to June 2016. Neutron counts were compared to continuous point-scale snow depth (SD) and snow-water-equivalent (SWE) measurements from an automatic weather station with a maximum SWE of 600 mm (April 2014). Several spatially distributed Terrestrial Laser Scanning (TLS)-based SD and SWE maps were additionally used. A strong nonlinear correlation is found for both SD and SWE. The representative footprint of the CRNS is in the range of 230\u2013270 m. In contrast to previous studies suggesting signal saturation at around 100 mm of SWE, no complete signal saturation was observed. These results imply that CRNS could be transferred into an unprecedented method for continuous detection of spatially averaged SD and SWE for alpine snowpacks, though with sensitivity decreasing with increasing SWE. While initially different functions were found for accumulation and melting season conditions, this could be resolved by accounting for a limited measurement depth. This depth limit is in the range of 200 mm of SWE for dense snowpacks with high liquid water contents and associated snow density values around 450 kg m 123 and above. In contrast to prior studies with shallow snowpacks, interannual transferability of the results is very high regardless of presnowfall soil moisture conditions. This underlines the unexpectedly high potential of CRNS to close the gap between point-scale measurements, hydrological models, and remote sensing of the cryosphere in alpine terrain

Retrospective forecasts of the upcoming winter season snow accumulation in the Inn headwaters (European Alps)

This article presents analyses of retrospective seasonal forecasts of snow accumulation. Re-forecasts with 4 months' lead time from two coupled atmosphere–ocean general circulation models (NCEP CFSv2 and MetOffice GloSea5) drive the Alpine Water balance and Runoff Estimation model (AWARE) in order to predict mid-winter snow accumulation in the Inn headwaters. As snowpack is hydrological storage that evolves during the winter season, it is strongly dependent on precipitation totals of the previous months. Climate model (CM) predictions of precipitation totals integrated from November to February (NDJF) compare reasonably well with observations. Even though predictions for precipitation may not be significantly more skilful than for temperature, the predictive skill achieved for precipitation is retained in subsequent water balance simulations when snow water equivalent (SWE) in February is considered. Given the AWARE simulations driven by observed meteorological fields as a benchmark for SWE analyses, the correlation achieved using GloSea5-AWARE SWE predictions is r  =  0.57. The tendency of SWE anomalies (i.e. the sign of anomalies) is correctly predicted in 11 of 13 years. For CFSv2-AWARE, the corresponding values are r  =  0.28 and 7 of 13 years. The results suggest that some seasonal prediction of hydrological model storage tendencies in parts of Europe is possible