ALBERT

Description: Episodic failures of ice-dammed lakes have produced some of the largest floods in history, with disastrous consequences for communities in high mountains1,2,3,4,5,6,7. Yet, estimating changes in the activity of ice-dam failures through time remains controversial because of inconsistent regional flood databases. Here, by collating 1,569 ice-dam failures in six major mountain regions, we systematically assess trends in peak discharge, volume, annual timing and source elevation between 1900 and 2021. We show that extreme peak flows and volumes (10 per cent highest) have declined by about an order of magnitude over this period in five of the six regions, whereas median flood discharges have fallen less or have remained unchanged. Ice-dam floods worldwide today originate at higher elevations and happen about six weeks earlier in the year than in 1900. Individual ice-dammed lakes with repeated outbursts show similar negative trends in magnitude and earlier occurrence, although with only moderate correlation to glacier thinning8. We anticipate that ice dams will continue to fail in the near future, even as glaciers thin and recede. Yet widespread deglaciation, projected for nearly all regions by the end of the twenty-first century9, may bring most outburst activity to a halt.

Description: Understanding and quantifying total economic impacts of flood events is essential for flood risk management and adaptation planning. Yet, detailed estimations of joint direct and indirect flood-induced economic impacts are rare. In this study an innovative modeling procedure for the joint assessment of short-term direct and indirect economic flood impacts is introduced. The procedure is applied to 19 economic sectors in eight federal states of Germany after the flood events in 2013. The assessment of the direct economic impacts is object-based and considers uncertainties associated with the hazard, the exposed objects and their vulnerability. The direct economic impacts are then coupled to a supply-side Input-Output-Model to estimate the indirect economic impacts. The procedure provides distributions of direct and indirect economic impacts which capture the associated uncertainties. The distributions of the direct economic impacts in the federal states are plausible when compared to reported values. The ratio between indirect and direct economic impacts shows that the sectors Manufacturing, Financial and Insurance activities suffered the most from indirect economic impacts. These ratios also indicate that indirect economic impacts can be almost as high as direct economic impacts. They differ strongly between the economic sectors indicating that the application of a single factor as a proxy for the indirect impacts of all economic sectors is not appropriate.

Description: A severe flash flood event hit the town of Braunsbach (Baden-Württemberg, Germany) on the evening of May 29, 2016, heavily damaging and destroying several dozens of buildings. It was only one of several disastrous events in Central Europe caused by the low-pressure system “Elvira”. The DFG Research Training Group “Natural hazards and risks in a changing world” (NatRiskChange, GRK 2043/1) at the University of Potsdam investigated the Braunsbach flash flood. In this context damage data for 94 affected buildings, describing building characteristics, the degree of impact and the caused damage, were collected ten days after the flood event and provide the basis for damage assessment studies (Agarwal et al., 2017; Laudan et al., 2017, Vogel et al., 2017). The multi-polygon maps provide flood loss in EUR for residential land use areas according to the ATKIS (Authoritative Topographic Cartographic Information System) codes residential areas (2111) and areas of mixed use (2113), (BKG GEODATENZENTRUM: ATKIS-Basis-DLM, 2005). Loss values are calculated using the FloodLossEstimationMOdel for the residential sector (FLEMOps+r) developed by Elmer et al. (2010) in combination with exposure data based on total replacement costs for residential buildings (Kleist et al., 2006). Asset values with a spatial resolution corresponding to the underlying inundation depth maps of the stochastic event set (100x100 m) have been derived by applying a binary disaggregation method and using the digital basic landscape model ATKIS as ancillary information (Wünsch et al. 2009). The flood event sets are derived for the historical period (1970-1990) and two RCPs (4.5 and 8.5) for the near future (2020-2049) and far future (2070-2099) for four CORDEX models. These flood event sets are created within continuous long-term simulations of a coupled model chain including the IMAGE stochastic multi-variable, multi-site weather generator, the eco-hydrological model SWIM and 1D river network coupled with 2D hydro-numeric hinterland inundation model, see Schröter et al. (2017) for further details The data have been produced within the OASIS+ demonstrator project 'Future Danube Multi Hazard and Risk Model' funded by Climate-KIC in the period from January 2016 to December 2017. Key features: • Flood loss maps for residential areas in the German part of the Danube catchment from stochastic flood event sets for current and future climate. • High spatial resolution for ATKIS residential land use areas intersected with 100x100 m inundation depth maps. • Flood loss scenarios for historical period (1970-1990) and two RCPs (4.5 and 8.5) for the near future (2020-2049) and far future (2070-2099) from four CORDEX models Key usage: • Large-scale flood risk assessment • Future flood risk assessment • Flood risk management with long-term perspective A full description of the data provenance and specification is given in the README_Schroeter-et-al-2017-004.txt file available in the data download section at this DOI Landing Page.

Description: Flash floods and debris flows are iconic hazards in mountainous regions with steep relief, high rainfall intensities, rapid snowmelt events, and abundant sediments. The cuesta landscapes of southern Germany hardly come to mind when dealing with such hazards. A series of heavy rainstorms dumping up to 140 mm in 2 h caused destructive flash floods and debris flows in May 2016. The most severe damage occurred in the Braunsbach municipality, which was partly buried by 42,000 m3 of boulders, gravel, mud, and anthropogenic debris from the small catchment of Orlacher Bach (~6 km2). We analysed this event by combining rainfall patterns, geological conditions, and geomorphic impacts to estimate an average sediment yield of 14,000 t/km2 that mostly (~95%) came from some 50 riparian landslides and channel-bed incision of ~2 m. This specific sediment yield ranks among the top 20% globally, while the intensity-duration curve of the rainstorm is similarly in the upper percentile range of storms that had triggered landslides. Compared to similar-sized catchments in the greater region hit by the rainstorms, we find that the Orlacher Bach is above the 95th percentile in terms of steepness, storm-rainfall intensity, and topographic curvatures. The flash flood transported a sediment volume equal to as much as 20–40% of the Pleistocene sediment volume stored in the Orlacher Bach fan, and may have had several predecessors in the Holocene. River control structures from 1903 and records of a debris flow in the 1920s in a nearby catchment indicate that the local inhabitants may have been aware of the debris-flow hazards earlier. Such recurring and destructive events elude flood-hazard appraisals in humid landscapes of gentle relief, and broaden mechanistic views of how landslides and debris flows contribute to shaping small and deeply cut tributaries in the southern Germany cuesta landscape.

Description: Hydrometeorological hazards caused losses of approximately 110 billion U.S. Dollars in 2016 worldwide. Current damage estimations do not consider the uncertainties in a comprehensive way, and they are not consistent between spatial scales. Aggregated land use data are used at larger spatial scales, although detailed exposure data at the object level, such as openstreetmap.org, is becoming increasingly available across the globe. We present a probabilistic approach for object‐based damage estimation which represents uncertainties and is fully scalable in space. The approach is applied and validated to company damage from the flood of 2013 in Germany. Damage estimates are more accurate compared to damage models using land use data, and the estimation works reliably at all spatial scales. Therefore, it can as well be used for pre‐event analysis and risk assessments. This method takes hydrometeorological damage estimation and risk assessments to the next level, making damage estimates and their uncertainties fully scalable in space, from object to country level, and enabling the exploitation of new exposure data.

Description: In recent years, urban and rural flash floods in Europe and abroad have gained considerable attention because of their sudden occurrence, severe material damages and even danger to life of inhabitants. This contribution addresses questions about possibly changing environmental conditions which might have altered the occurrence frequencies of such events and their consequences. We analyze the following major fields of environmental changes. Altered high intensity rain storm conditions, as a consequence of regional warming; Possibly altered runoff generation conditions in response to high intensity rainfall events; Possibly altered runoff concentration conditions in response to the usage and management of the landscape, such as agricultural, forest practices or rural roads; Effects of engineering measures in the catchment, such as retention basins, check dams, culverts, or river and geomorphological engineering measures. We take the flash-flood in Braunsbach, SW-Germany, as an example, where a particularly concise flash flood event occurred at the end of May 2016. This extreme cascading natural event led to immense damage in this particular village. The event is retrospectively analyzed with regard to meteorology, hydrology, geomorphology and damage to obtain a quantitative assessment of the processes and their development. The results show that it was a very rare rainfall event with extreme intensities, which in combination with catchment properties and altered environmental conditions led to extreme runoff, extreme debris flow and immense damages. Due to the complex and interacting processes, no single flood cause can be identified, since only the interplay of those led to such an event. We have shown that environmental changes are important, but—at least for this case study—even natural weather and hydrologic conditions would still have resulted in an extreme flash flood event.

Description: In this article, we address the question of how observed ground-motion data can most effectively be modeled for engineering seismological purposes. Toward this goal, we use a data-driven method, based on a deep-learning autoencoder with a variable number of nodes in the bottleneck layer, to determine how many parameters are needed to reconstruct synthetic and observed ground-motion data in terms of their median values and scatter. The reconstruction error as a function of the number of nodes in the bottleneck is used as an indicator of the underlying dimensionality of ground-motion data, that is, the minimum number of predictor variables needed in a ground-motion model. Two synthetic and one observed datasets are studied to prove the performance of the proposed method. We find that mapping ground-motion data to a 2D manifold primarily captures magnitude and distance information and is suited for an approximate data reconstruction. The data reconstruction improves with an increasing number of bottleneck nodes of up to three and four, but it saturates if more nodes are added to the bottleneck.