TY - JOUR A1 - Paprotny, Dominik A1 - Kreibich, Heidi A1 - Morales-Napoles, Oswaldo A1 - Wagenaar, Dennis A1 - Castellarin, Attilio A1 - Carisi, Francesca A1 - Bertin, Xavier A1 - Merz, Bruno A1 - Schröter, Kai T1 - A probabilistic approach to estimating residential losses from different flood types JF - Natural hazards : journal of the International Society for the Prevention and Mitigation of Natural Hazards N2 - Residential assets, comprising buildings and household contents, are a major source of direct flood losses. Existing damage models are mostly deterministic and limited to particular countries or flood types. Here, we compile building-level losses from Germany, Italy and the Netherlands covering a wide range of fluvial and pluvial flood events. Utilizing a Bayesian network (BN) for continuous variables, we find that relative losses (i.e. loss relative to exposure) to building structure and its contents could be estimated with five variables: water depth, flow velocity, event return period, building usable floor space area and regional disposable income per capita. The model's ability to predict flood losses is validated for the 11 flood events contained in the sample. Predictions for the German and Italian fluvial floods were better than for pluvial floods or the 1993 Meuse river flood. Further, a case study of a 2010 coastal flood in France is used to test the BN model's performance for a type of flood not included in the survey dataset. Overall, the BN model achieved better results than any of 10 alternative damage models for reproducing average losses for the 2010 flood. An additional case study of a 2013 fluvial flood has also shown good performance of the model. The study shows that data from many flood events can be combined to derive most important factors driving flood losses across regions and time, and that resulting damage models could be applied in an open data framework. KW - fluvial floods KW - coastal floods KW - pluvial floods KW - Bayesian networks KW - flood KW - damage surveys Y1 - 2020 U6 - https://doi.org/10.1007/s11069-020-04413-x SN - 0921-030X SN - 1573-0840 VL - 105 IS - 3 SP - 2569 EP - 2601 PB - Springer CY - New York ER - TY - JOUR A1 - Bricker, Jeremy D. A1 - Schwanghart, Wolfgang A1 - Adhikari, Basanta Raj A1 - Moriguchi, Shuji A1 - Roeber, Volker A1 - Giri, Sanjay T1 - Performance of Models for Flash Flood Warning and Hazard Assessment BT - the 2015 Kali Gandaki Landslide Dam Breach in Nepal JF - Mountain research and development N2 - The 2015 magnitude 7.8 Gorkha earthquake and its aftershocks weakened mountain slopes in Nepal. Co- and postseismic landsliding and the formation of landslide-dammed lakes along steeply dissected valleys were widespread, among them a landslide that dammed the Kali Gandaki River. Overtopping of the landslide dam resulted in a flash flood downstream, though casualties were prevented because of timely evacuation of low-lying areas. We hindcast the flood using the BREACH physically based dam-break model for upstream hydrograph generation, and compared the resulting maximum flow rate with those resulting from various empirical formulas and a simplified hydrograph based on published observations. Subsequent modeling of downstream flood propagation was compromised by a coarse-resolution digital elevation model with several artifacts. Thus, we used a digital-elevation-model preprocessing technique that combined carving and smoothing to derive topographic data. We then applied the 1-dimensional HEC-RAS model for downstream flood routing, and compared it to the 2-dimensional Delft-FLOW model. Simulations were validated using rectified frames of a video recorded by a resident during the flood in the village of Beni, allowing estimation of maximum flow depth and speed. Results show that hydrological smoothing is necessary when using coarse topographic data (such as SRTM or ASTER), as using raw topography underestimates flow depth and speed and overestimates flood wave arrival lag time. Results also show that the 2-dimensional model produces more accurate results than the 1-dimensional model but the 1-dimensional model generates a more conservative result and can be run in a much shorter time. Therefore, a 2-dimensional model is recommended for hazard assessment and planning, whereas a 1-dimensional model would facilitate real-time warning declaration. KW - Nepal KW - earthquake KW - landslide dam breach KW - flood KW - HEC-RAS KW - Delft-FLOW KW - steep mountain stream Y1 - 2017 U6 - https://doi.org/10.1659/MRD-JOURNAL-D-16-00043.1 SN - 0276-4741 SN - 1994-7151 VL - 37 IS - 1 SP - 5 EP - 15 PB - International Mountain Society CY - Lawrence ER -