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    About the influence of elevation model quality and small-scale damage functions on flood damage estimation
    (Göttingen : Copernicus GmbH, 2011) Boettle, M.; Kropp, J.P.; Reiber, L.; Roithmeier, O.; Rybski, D.; Walther, C.
    The assessment of coastal flood risks in a particular region requires the estimation of typical damages caused by storm surges of certain characteristics and annualities. Although the damage depends on a multitude of factors, including flow velocity, duration of flood, precaution, etc., the relationship between flood events and the corresponding average damages is usually described by a stage-damage function, which considers the maximum water level as the only damage influencing factor. Starting with different (microscale) building damage functions we elaborate a macroscopic damage function for the entire case study area Kalundborg (Denmark) on the basis of multiple coarse-graining methods and assumptions of the hydrological connectivity. We find that for small events, the macroscopic damage function mostly depends on the properties of the elevation model, while for large events it strongly depends on the assumed building damage function. In general, the damage in the case study increases exponentially up to a certain level and then less steep.
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    Human displacements from Tropical Cyclone Idai attributable to climate change
    (Katlenburg-Lindau : European Geophysical Society, 2023) Mester, Benedikt; Vogt, Thomas; Bryant, Seth; Otto, Christian; Frieler, Katja; Schewe, Jacob
    Extreme weather events, such as tropical cyclones, often trigger population displacement. The frequency and intensity of tropical cyclones are affected by anthropogenic climate change. However, the effect of historical climate change on displacement risk has so far not been quantified. Here, we show how displacement can be partially attributed to climate change using the example of the 2019 Tropical Cyclone Idai in Mozambique. We estimate the population exposed to high water levels following Idai's landfall using a combination of a 2D hydrodynamical storm surge model and a flood depth estimation algorithm to determine inland flood depths from remote sensing images, factual (climate change) and counterfactual (no climate change) mean sea level, and maximum wind speed conditions. Our main estimates indicate that climate change has increased displacement risk from this event by approximately 12 600-14 900 additional displaced persons, corresponding to about 2.7 % to 3.2 % of the observed displacements. The isolated effect of wind speed intensification is double that of sea level rise. These results are subject to important uncertainties related to both data and modeling assumptions, and we perform multiple sensitivity experiments to assess the range of uncertainty where possible. Besides highlighting the significant effects on humanitarian conditions already imparted by climate change, our study provides a blueprint for event-based displacement attribution.