ALBERT

Description: Flooding is the most costly natural hazard in Europe. Climatic and socioeconomic change are expected to further increase the amount of loss in the future. To counteract this development, policymaking, and adaptation planning need reliable large-scale risk assessments and an improved understanding of potential risk drivers. In this study, recent datasets for hazard and flood protection standards are combined with high resolution exposure projections and attributes of vulnerability derived from open data sources. The independent and combined influence of exposure change and climate scenarios rcp45 and rcp85 on fluvial flood risk are evaluated for three future periods centered around 2025, 2055 and 2085. Scenarios with improved and neglected private precaution are examined for their influence on flood risk using a probabilistic, multivariable flood loss model — BN-FLEMOps — to estimate fluvial flood losses for residential buildings in Europe. The results on NUTS-3 level reveal that urban centers and their surrounding regions are the hotspots of flood risk in Europe. Flood risk is projected to increase in the British Isles and Central Europe throughout the 21st century, while risk in many regions of Scandinavia and the Mediterranean will stagnate or decline. Under the combined effects of exposure change and climate scenarios rcp45, rcp85, fluvial flood risk in Europe is estimated to increase seven-fold and ten-fold respectively until the end of the century. Our results confirm the dominance of socioeconomic change over climate change on increasing risk. Improved private precautionary measures would reduce flood risk in Europe on an average by 15%. The quantification of future flood risk in Europe by integrating climate, socioeconomic and private precaution scenarios provides an overview of risk drivers, trends, and hotspots. This large-scale comprehensive assessment at a regional level resolution is valuable for multi-scale risk-based adaptation planning.

Description: Increasing flood losses over the last decades emphasize the need towards significantly improved and more efficient flood risk management. One key requirement is reliable risk assessment in conjunction with consistent flood loss modeling. Current risk assessments and flood loss estimations for Europe are until now based on regional approaches using deterministic depth-damage function and do rarely report associated uncertainties. To reduce these shortcomings, we present the results of a novel, consistent approach based on the Bayesian Network Flood Loss Estimation MOdel for the private sector (BN-FLEMOps). The dataset is consistent in terms of the input data used to drive the model and because we use the same vulnerability model to derive the flood loss estimation. Essential inputs for any flood loss estimation are hazard (usually water depth), asset (value of objects at risk) and flood experience parameters. The hazard input was given by a European inundation scenario for a continent-wide flood with 100 years return period (Alfieri et al., 2014). Asset values were computed following the the approach by Huizinga et al. (2017) and the flood experience was derived using the database of the Dartmouth Flood Observatory (DFO) (Brakenridge, 2018).

Description: The Flood Similarity Workflow is part of the Flood Event Explorer (FEE, Eggert et al., 2022), developed at the GFZ German Research Centre for Geosciences . It is funded by the Initiative and Networking Fund of the Helmholtz Association through the Digital Earth project (https://www.digitalearth-hgf.de/). River floods and associated adverse consequences are caused by complex interactions of hydro-meteorological and socio-economic pre-conditions and event characteristics. The Flood Similarity Workflow supports the identification, assessment and comparison of hydro-meteorological controls of flood events. The analysis of flood events requires the exploration of discharge time series data for hundreds of gauging stations and their auxiliary data. Data availability and accessibility and standard processing techniques are common challenges in that application and addressed by this workflow. The Flood Similarity Workflow allows the assessment and comparison of arbitrary flood events. The workflow includes around 500 gauging stations in Germany comprising discharge data and the associated extreme value statistics as well as precipitation and soil moisture data. This provides the basis to identify and compare flood events based on antecedent catchment conditions, catchment precipitation, discharge hydrographs, and inundation maps. The workflow also enables the analysis of multidimensional flood characteristics including aggregated indicators (in space and time), spatial patterns and time series signatures. The added value of the Flood Event Explorer comprises two major points. First, scientist work on a common, homogenized database of flood events and their hydro-meteorological controls for a large spatial and temporal domain , with fast and standardized interfaces to access the data. Second, the standardized computation of common flood indicators allows a consistent comparison and exploration of flood events.

Description: The dataset comprises a range of variables describing characteristics of flood events and river catchments for 480 gauging stations in Germany and Austria. The event characteristics are asscoiated with annual maximum flood events in the period from 1951 to 2010. They include variables on event precipitation, antecedent catchment state, event catchment response, event timing, and event types. The catchment characteristics include variables on catchment area, catchment wetness, tail heaviness of rainfall, nonlinearity of catchment response, and synchronicity of precipitation and catchment state. The variables were compiled as potential predictors of heavy tail behaviour of flood peak distributions. They are based on gauge observations of discharge, E-OBS meteorological data (Haylock et al. 2008), mHM hydrological model simulations (Samaniego et al., 2010), 4DAS climate reanalysis data (Primo et al., 2019), and the 25x25 m resolution EU-DEM v1.1. A short description of the data processing is included in the file inventory and more details can be found in Macdonald et al. (2022).

Description: floodsimilarity provides classes and methods to conduct a similarity analysis between multiple flood events. The library mainly consists of two parts: (1) algorithms to compute indices and other statistics based on pandas and xarray (2) well-defined data structures for data exchange (e.g. through the Similarity Backend Module) floodsimilarity is used by the Digital Earth Similarity Backend Module (Eggert, 2021) as part of the Digital Earth Flood Event Explorer. It is developed at the GFZ German Research Centre for Geosciences and funded by the Initiative and Networking Fund of the Helmholtz Association through the Digital Earth project.

Description: The Digital Earth Flood Event Explorer supports geoscientists and experts to analyse flood events along the process cascade event generation, evolution and impact across atmospheric, terrestrial, and marine disciplines. It applies the concept of scientific workflows and the component-based Data Analytics Software Framework (DASF, Eggert and Dransch, 2021) to an exemplary showcase. It aims at answering the following geoscientific questions: - How does precipitation change over the course of the 21st century under different climate scenarios over a certain region? - What are the main hydro-meteorological controls of a specific flood event? - What are useful indicators to assess socio-economic flood impacts? - How do flood events impact the marine environment? - What are the best monitoring sites for upcoming flood events? The Flood Event Explorer developed scientific workflows for each geoscientific question providing enhanced analysis methods from statistics, machine learning, and visual data exploration that are implemented in different languages and software environments, and that access data form a variety of distributed databases. The collaborating scientists are from different Helmholtz research centers and belong to different scientific fields such as hydrology, climate-, marine-, and environmental science, and computer- and data science. It is funded by the Initiative and Networking Fund of the Helmholtz Association through the Digital Earth project (https://www.digitalearth-hgf.de/).

Description: Climate change manifests in terms of changing frequency and magnitude of extreme hydro-meteorological events and thus drives changes in urban flood hazard. Flood risk oriented urban planning is key to derive smart adaptation strategies, strengthen resilience and achieve sustainable development. 3D city models offer detailed spatial information which is useful to describe the exposure and to characterize the susceptibility of buildings at risk.This web-based application presents the 3d-city flood damage module (3DCFD) prototype which has been developed and implemented within a pathfinder projected funded by Climate-KIC during 2015-2016. The presentation illustrates the results of the 3DCFD-module exemplarily for the demonstration case in the City of Dresden. Relative damage to residential buildings which results from various flooding scenarios is shown for the focus area Pieschen in Dresden.The application allows the user to browse through the virtual city model and to colour the residential buildings regarding their relative damage values caused by different flooding scenarios. To do so click on 'Content', then on the brush-icon next to 'Buildings' and select a certain style from the drop-down menu. A style represents a specific combination of loss model and flooding scenario. Flooding scenarios provide spatially detailed inundation depth information according to different water stages at the gauge Dresden. Currently two flood loss models are implemented: a simple stage-damage-function (sdf) which related inundation depth to relative loss and the 3DCFD-module which uses additional information about building characteristics available from the virtual city model. A click on a coloured building will display additional information. The loss estimation module has been developed by the German Research Centre for Geosciences (GFZ), Section Hydrology. The web-application has been developed by virtualcitySYSTEMS GmbH. The data consisting of flood scenarios, a virtual 3D city model, and a terrain model were provided by the City of Dresden.

Description: The European exposure data for BN-FLEMO models contains three datasets that can be used with BN-FLEMO models for the estimation of flood loss. The dataset contains: (1) European asset map with unit area values of residential and commercial buildings in EURO per square meter based on reconstruction cost and NUTS-3 regions or national GDP per capita. The values are mapped on CORINE land cover classes for urban areas (111 and 112). (2) Residential building areas in Europe with building area sizes in square meter for each NUTS-3 region. The building area sizes were calculated based on the building geometries extracted from the OSM database. (3) Flood experience in Europe with geometries of historic flood events (1985- 2015) with start date of the events. This dataset can be used to calculate the number of past flood events in an area.

Description: Flooding is the most costly natural hazard in Europe. Climatic and socioeconomic change are expected to further increase the amount of loss in the future. To counteract this development, policymaking, and adaptation planning need reliable large-scale risk assessments and an improved understanding of potential risk drivers. In this study, recent datasets for hazard and flood protection standards are combined with high resolution exposure projections and attributes of vulnerability derived from open data sources. The independent and combined influence of exposure change and climate scenarios rcp45 and rcp85 on fluvial flood risk are evaluated for three future periods centered around 2025, 2055 and 2085. Scenarios with improved and neglected private precaution are examined for their influence on flood risk using a probabilistic, multivariable flood loss model — BN-FLEMOps — to estimate fluvial flood losses for residential buildings in Europe. The results on NUTS-3 level reveal that urban centers and their surrounding regions are the hotspots of flood risk in Europe. Flood risk is projected to increase in the British Isles and Central Europe throughout the 21st century, while risk in many regions of Scandinavia and the Mediterranean will stagnate or decline. Under the combined effects of exposure change and climate scenarios rcp45, rcp85, fluvial flood risk in Europe is estimated to increase seven-fold and ten-fold respectively until the end of the century. Our results confirm the dominance of socioeconomic change over climate change on increasing risk. Improved private precautionary measures would reduce flood risk in Europe on an average by 15%. The quantification of future flood risk in Europe by integrating climate, socioeconomic and private precaution scenarios provides an overview of risk drivers, trends, and hotspots. This large-scale comprehensive assessment at a regional level resolution is valuable for multi-scale risk-based adaptation planning.