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Large-scale flood risk assessments are crucial for decision making, especially with respect to new flood defense schemes, adaptation planning and estimating insurance premiums. We apply the process-based Regional Flood Model (RFM) to simulate a 5000-year flood event catalog for all major catchments in Germany and derive risk curves based on the losses per economic sector. The RFM uses a continuous process simulation including a multisite, multivariate weather generator, a hydrological model considering heterogeneous catchment processes, a coupled 1D-2D hydrodynamic model considering dike overtopping and hinterland storage, spatially explicit sector-wise exposure data and empirical multi-variable loss models calibrated for Germany. For all components, uncertainties in the data and models are estimated. We estimate the median Expected Annual Damage (EAD) and Value at Risk at 99.5% confidence for Germany to be euro0.529 bn and euro8.865 bn, respectively. The commercial sector dominates by making about 60% of the total risk, followed by the residential sector. The agriculture sector gets affected by small return period floods and only contributes to less than 3% to the total risk. The overall EAD is comparable to other large-scale estimates. However, the estimation of losses for specific return periods is substantially improved. The spatial consistency of the risk estimates avoids the large overestimation of losses for rare events that is common in other large-scale assessments with homogeneous return periods. Thus, the process-based, spatially consistent flood risk assessment by RFM is an important step forward and will serve as a benchmark for future German-wide flood risk assessments.
The Flood Damage Database HOWAS 21 contains object-specific flood damage data resulting from fluvial, pluvial and groundwater flooding. The datasets incorporate various variables of flood hazard, exposure, vulnerability and direct tangible damage at properties from several economic sectors. The main purpose of development of HOWAS 21 was to support forensic flood analysis and the derivation of flood damage models. HOWAS 21 was first developed for Germany and currently almost exclusively contains datasets from Germany. However, its scope has recently been enlarged with the aim to serve as an international flood damage database; e.g. its web application is now available in German and English. This paper presents the recent advancements of HOWAS 21 and highlights exemplary analyses to demonstrate the use of HOWAS 21 flood damage data. The data applications indicate a large potential of the database for fostering a better understanding and estimation of the consequences of flooding.
The transport sector is crucial for the functioning of modern societies and their economic welfares. However, it is vulnerable to natural hazards since damage and disturbances appear recurrently. Risk management of transport infrastructure is a complex task that usually involves various stakeholders from the public and private sector. Related scientific knowledge, however, is limited so far. Therefore, this paper presents detailed information on the risk management of the Austrian railway operator gathered through literature studies, in interviews, meetings and workshops. The findings reveal three decision making levels of risk reduction: 1) a superordinate level for the negotiation of frameworks and guidelines, 2) a regional to local level for the planning and implementation of structural measures and 3) a regional to local level for non-structural risk reduction measures and emergency management. On each of these levels, multi-sectoral partnerships exist that aim at reducing the risk to railway infrastructure. Chosen partnerships are evaluated applying the Capital Approach Framework and some collaborations are analyzed considering the flood and landslide events in June 2013. The evaluation reveals that the risk management of the railway operator and its partners has been successful, but there is still potential for enhancement. Difficulties are seen for instance in obtaining continuity of employees and organizational structures which can affect personal contacts and mutual trust and might hamper sharing data and experiences. Altogether, the case reveals the importance of multi-sectoral partnerships that are seen as a crucial element of risk management in the Sendai Framework for Disaster Risk Reduction 2015-2030.
For effective disaster risk management and adaptation planning, a good understanding of current and projected flood risk is required. Recent advances in quantifying flood risk at the regional and global scale have largely neglected critical infrastructure, or addressed this important sector with insufficient detail. Here, we present the first European-wide assessment of current and future flood risk to railway tracks for different global warming scenarios using an infrastructure-specific damage model. We find that the present risk, measured as expected annual damage, to railway networks in Europe is approx. (sic)581 million per year, with the highest risk relative to the length of the network in North Macedonia, Croatia, Norway, Portugal, and Germany. Based on an ensemble of climate projections for RCP8.5, we show that current risk to railway networks is projected to increase by 255% under a 1.5 degrees C, by 281% under a 2 degrees C, and by 310% under a 3 degrees C warming scenario. The largest increases in risk under a 3 degrees C scenario are projected for Slovakia, Austria, Slovenia, and Belgium. Our advances in the projection of flood risk to railway infrastructure are important given their criticality, and because losses to public infrastructure are usually not insured or even uninsurable in the private market. To cover the risk increase due to climate change, European member states would need to increase expenditure in transport by (sic)1.22 billion annually under a 3 degrees C warming scenario without further adaptation. Limiting global warming to the 1.5 degrees C goal of the Paris Agreement would result in avoided losses of (sic)317 million annually.