TY - JOUR A1 - Sieg, Tobias A1 - Thieken, Annegret T1 - Improving flood impact estimations JF - Environmental research letters N2 - A reliable estimation of flood impacts enables meaningful flood risk management and rapid assessments of flood impacts shortly after a flood. The flood in 2021 in Central Europe and the analysis of its impacts revealed that these estimations are still inadequate. Therefore, we investigate the influence of different data sets and methods aiming to improve flood impact estimates. We estimated economic flood impacts to private households and companies for a flood event in 2013 in Germany using (a) two different flood maps, (b) two approaches to map exposed objects based on OpenStreetMap and the Basic European Asset Map, (c) two different approaches to estimate asset values, and (d) tree-based models and Stage-Damage-Functions to describe the vulnerability. At the macro scale, water masks lead to reasonable impact estimations. At the micro and meso-scale, the identification of affected objects by means of water masks is insufficient leading to unreliable estimations. The choice of exposure data sets is most influential on the estimations. We find that reliable impact estimations are feasible with reported numbers of flood-affected objects from the municipalities. We conclude that more effort should be put in the investigation of different exposure data sets and the estimation of asset values. Furthermore, we recommend the establishment of a reporting system in the municipalities for a fast identification of flood-affected objects shortly after an event. KW - rapid impact assessment KW - floods KW - OpenStreetMap KW - flood risk management KW - natural hazards Y1 - 2022 U6 - https://doi.org/10.1088/1748-9326/ac6d6c SN - 1748-9326 VL - 17 IS - 6 PB - IOP Publ. Ltd. CY - Bristol ER - TY - JOUR A1 - Gomez Zapata, Juan Camilo A1 - Zafrir, Raquel A1 - Pittore, Massimiliano A1 - Merino, Yvonne T1 - Towards a sensitivity analysis in seismic risk with probabilistic building exposure models BT - an application in Valparaiso, Chile using ancillary open-source data and parametric ground motions JF - ISPRS International Journal of Geo-Information N2 - Efforts have been made in the past to enhance building exposure models on a regional scale with increasing spatial resolutions by integrating different data sources. This work follows a similar path and focuses on the downscaling of the existing SARA exposure model that was proposed for the residential building stock of the communes of Valparaiso and Vina del Mar (Chile). Although this model allowed great progress in harmonising building classes and characterising their differential physical vulnerabilities, it is now outdated, and in any case, it is spatially aggregated over large administrative units. Hence, to more accurately consider the impact of future earthquakes on these cities, it is necessary to employ more reliable exposure models. For such a purpose, we propose updating this existing model through a Bayesian approach by integrating ancillary data that has been made increasingly available from Volunteering Geo-Information (VGI) activities. Its spatial representation is also optimised in higher resolution aggregation units that avoid the inconvenience of having incomplete building-by-building footprints. A worst-case earthquake scenario is presented to calculate direct economic losses and highlight the degree of uncertainty imposed by exposure models in comparison with other parameters used to generate the seismic ground motions within a sensitivity analysis. This example study shows the great potential of using increasingly available VGI to update worldwide building exposure models as well as its importance in scenario-based seismic risk assessment. KW - exposure KW - buildings KW - Bayesian model KW - downscaling KW - OpenStreetMap KW - ground motion fields KW - sensitivity KW - earthquake KW - vulnerability KW - risk Y1 - 2022 U6 - https://doi.org/10.3390/ijgi11020113 SN - 2220-9964 VL - 11 IS - 2 PB - MDPI CY - Basel ER -