ALBERT

Description: Polish coastal zone is thought to be of the most exposed to sea level rise in Europe. With climate change expected to raise mean sea levels between 26 and 200 cm by the end of the century, and storms increasing in severity, accurate estimates of those phenomena are needed. Recent advances in quality and availability of spatial data in Poland made in possible to revisit previous estimates. Up-to-date detailed information on land use, population and buildings were used to calculate inundation risk at a broad range of scenarios. Inclusion, though imperfect, of flood defences from a high-resolution digital elevation model contributes to a further improvement of estimates. The results revealed that even by using a static "bathtub fill" approach the amount of land, population or assets at risk has been significantly revised down. Sea level rise or storm surges are unlikely to reach intensity required to cause significant damage to the economy or endanger the population. The exposure of different kinds of assets and sectors of the economy varies to a large extent, though the structural breakdown of potential losses is remarkably stable between scenarios.

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: In this paper we discuss PyBanshee, which is a Python-based open-source implementation of the MATLAB toolbox BANSHEE. PyBanshee constitutes the first fully open-source package to quantify, visualize and validate Non-Parametric Bayesian Networks (NPBNs). The architecture of PyBanshee is heavily based on its MATLAB predecessor. It presents the full implementation of existing tools and introduces new modules. Specifically, PyBanshee allows for: (i) choosing fully parametric one-dimensional margins, (ii) choosing different sample sizes for the model-validation tests based on the Hellinger distance, (iii) drawing user-defined sample sizes of the NPBN, (iv) sample-based conditioning sampling (similarly to the closed-source proprietary package UNINET by LightTwist Software) and (v) visualizing the comparison between the histograms of the unconditional and conditional marginal distributions. New detailed examples demonstrating new features are provided.

Description: V2.0.1: a correction was made to disaggregation of GDP, as the code incorrectly used 50:50 ratio of labour to capital instead of 60:40 ratio as in the methodology. The output GDP and uncertainty files were recomputed.

Description: This dataset provides all output data generated in the standard settings of HANZE v2.0 model. The 100-m pan-European maps (GeoTIFF) provide gridded totals of five variables for years 1870-2020 for 42 countries.

Description: This dataset provides all input data needed to run HANZE v2.0 model. The two ZIP files need to be downloaded and unpacked in the same directory, which has to be defined in "get_file.py" (variable "main_path" at the beginning of the file). For detailed description of the files, see the documentation provided with the code.

Description: This dataset provides average national-level current gross replacement costs of the stock of residential assets (buildings and household contents) per m2 of useful floor space. The dataset includes annual time series (2000–2020) for 33 European countries, in nominal and real prices. It is intended for application in microscale disaster models by enabling approximation of the monetary value of individual buildings exposed to hazards, especially floods, for which damage functions often distinguish between vulnerability of the building structure and contents inside.

Description: This contribution presents an assessment at a regional (island) scale of the beach erosion due to storm events under Climate Change. The approach adopted to assess beach erosion at the island scale consisted of three modules. First, the location, dimensions and other attributes of the Cypriot beaches were recorded on the basis of widely-available satellite imagery. Secondly, sea levels and waves were modeled along the coast under different climatic scenarios and dates in the 21st century. Finally, using these projections beach retreat due to the relative mean sea level rise (RSLR) and extreme sea levels (ESLs) was estimated using ensembles of analytical and numerical cross-shore morphodynamic models, respectively. Extreme sea levels (ESLs) were projected to (a) increase by up to 60% in 2100 from their baseline (2000) levels, and (b) vary along the coast, with the highest ESLs (and corresponding waves) projected for the southern and western coasts. The mostly narrow Cypriot beaches (91% recorded maximum widths of 〈 50 m) showed increased exposure to erosion. In 2100, about 47% and 72% (based on the median model estimates) of the 241 unprotected Cypriot beaches will be permanently eroded, due to mean sea level rise (SLR), to 50% of their present maximum width, depending on the scenario. In addition to the long-term erosion due to SLR, severe storm erosion is projected by 2050 even under the RCP4.5 scenario; the 100-year extreme sea level event (ESL100) may overwhelm (at least temporarily) 49% of the currently unprotected Cypriot beaches without effective adaptation responses, with the most exposed beaches located along the northern coast. As the beach carrying capacity and hedonic value will be severely compromised, effective adaptation policies and technical measures will be urgently required.