TY - JOUR A1 - Merz, Bruno A1 - Nguyen, Viet Dung A1 - Apel, Heiko A1 - Gerlitz, Lars A1 - Schröter, Kai A1 - Steirou, Eva Styliani A1 - Vorogushyn, Sergiy T1 - Spatial coherence of flood-rich and flood-poor periods across Germany JF - Journal of hydrology N2 - Despite its societal relevance, the question whether fluctuations in flood occurrence or magnitude are coherent in space has hardly been addressed in quantitative terms. We investigate this question for Germany by analysing fluctuations in annual maximum series (AMS) values at 68 discharge gauges for the common time period 1932-2005. We find remarkable spatial coherence across Germany given its different flood regimes. For example, there is a tendency that flood-rich/-poor years in sub-catchments of the Rhine basin, which are dominated by winter floods, coincide with flood-rich/-poor years in the southern sub-catchments of the Danube basin, which have their dominant flood season in summer. Our findings indicate that coherence is caused rather by persistence in catchment wetness than by persistent periods of higher/lower event precipitation. Further, we propose to differentiate between event-type and non-event-type coherence. There are quite a number of hydrological years with considerable nonevent-type coherence, i.e. AMS values of the 68 gauges are spread out through the year but in the same magnitude range. Years with extreme flooding tend to be of event-type and non-coherent, i.e. there is at least one precipitation event that affects many catchments to various degree. Although spatial coherence is a remarkable phenomenon, and large-scale flooding across Germany can lead to severe situations, extreme magnitudes across the whole country within one event or within one year were not observed in the investigated period. (C) 2018 Elsevier B.V. All rights reserved. KW - Flood timing KW - Spatial coherence KW - Flood regimes KW - Climate variability KW - Catchment wetness Y1 - 2018 U6 - https://doi.org/10.1016/j.jhydrol.2018.02.082 SN - 0022-1694 SN - 1879-2707 VL - 559 SP - 813 EP - 826 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Vogel, Kristin A1 - Weise, Laura A1 - Schröter, Kai A1 - Thieken, Annegret T1 - Identifying Driving Factors in Flood-Damaging Processes Using Graphical Models JF - Water resources research N2 - Flood damage estimation is a core task in flood risk assessments and requires reliable flood loss models. Identifying the driving factors of flood loss at residential buildings and gaining insight into their relations is important to improve our understanding of flood damage processes. For that purpose, we learn probabilistic graphical models, which capture and illustrate (in-)dependencies between the considered variables. The models are learned based on postevent surveys with flood-affected residents after six flood events, which occurred in Germany between 2002 and 2013. Besides the sustained building damage, the survey data contain information about flooding parameters, early warning and emergency measures, property-level mitigation measures and preparedness, socioeconomic characteristics of the household, and building characteristics. The analysis considers the entire data set with a total of 4,468 cases as well as subsets of the data set partitioned into single flood events and flood types: river floods, levee breaches, surface water flooding, and groundwater floods, to reveal differences in the damaging processes. The learned networks suggest that the flood loss ratio of residential buildings is directly influenced by hydrological and hydraulic aspects as well as by building characteristics and property-level mitigation measures. The study demonstrates also that for different flood events and process types the building damage is influenced by varying factors. This suggests that flood damage models need to be capable of reproducing these differences for spatial and temporal model transfers. KW - flood loss KW - Bayesian Network KW - Markov Blanket KW - vulnerability KW - Germany Y1 - 2018 U6 - https://doi.org/10.1029/2018WR022858 SN - 0043-1397 SN - 1944-7973 VL - 54 IS - 11 SP - 8864 EP - 8889 PB - American Geophysical Union CY - Washington ER - TY - JOUR A1 - Metin, Ayse Duha A1 - Nguyen Viet Dung, A1 - Schröter, Kai A1 - Guse, Björn A1 - Apel, Heiko A1 - Kreibich, Heidi A1 - Vorogushyn, Sergiy A1 - Merz, Bruno T1 - How do changes along the risk chain affect flood risk? JF - Natural hazards and earth system sciences N2 - Flood risk is impacted by a range of physical and socio-economic processes. Hence, the quantification of flood risk ideally considers the complete flood risk chain, from atmospheric processes through catchment and river system processes to damage mechanisms in the affected areas. Although it is generally accepted that a multitude of changes along the risk chain can occur and impact flood risk, there is a lack of knowledge of how and to what extent changes in influencing factors propagate through the chain and finally affect flood risk. To fill this gap, we present a comprehensive sensitivity analysis which considers changes in all risk components, i.e. changes in climate, catchment, river system, land use, assets, and vulnerability. The application of this framework to the mesoscale Mulde catchment in Germany shows that flood risk can vary dramatically as a consequence of plausible change scenarios. It further reveals that components that have not received much attention, such as changes in dike systems or in vulnerability, may outweigh changes in often investigated components, such as climate. Although the specific results are conditional on the case study area and the selected assumptions, they emphasize the need for a broader consideration of potential drivers of change in a comprehensive way. Hence, our approach contributes to a better understanding of how the different risk components influence the overall flood risk. Y1 - 2018 U6 - https://doi.org/10.5194/nhess-18-3089-2018 SN - 1561-8633 SN - 1684-9981 VL - 18 IS - 11 SP - 3089 EP - 3108 PB - Copernicus CY - Göttingen ER - TY - JOUR A1 - Merz, Bruno A1 - Apel, Heiko A1 - Dung Nguyen, Viet-Dung A1 - Falter, Daniela A1 - Guse, Björn A1 - Hundecha, Yeshewatesfa A1 - Kreibich, Heidi A1 - Schröter, Kai A1 - Vorogushyn, Sergiy T1 - From precipitation to damage BT - a coupled model chain for spatially coherent, large-scale flood risk assessment JF - Global flood hazard : applications in modeling, mapping and forecasting N2 - Flood risk assessments for large river basins often involve piecing together smaller-scale assessments leading to erroneous risk statements. We describe a coupled model chain for quantifying flood risk at the scale of 100,000 km(2). It consists of a catchment model, a 1D-2D river network model, and a loss model. We introduce the model chain and present two applications. The first application for the Elbe River basin with an area of 66,000 km(2) demonstrates that it is feasible to simulate the complete risk chain for large river basins in a continuous simulation mode with high temporal and spatial resolution. In the second application, RFM is coupled to a multisite weather generator and applied to the Mulde catchment with an area of 6,000 km(2). This approach is able to provide a very long time series of spatially heterogeneous patterns of precipitation, discharge, inundation, and damage. These patterns respect the spatial correlation of the different processes and are suitable to derive large-scale risk estimates. We discuss how the RFM approach can be transferred to the continental scale. Y1 - 2018 SN - 978-1-119-21788-6 SN - 978-1-119-21786-2 U6 - https://doi.org/10.1002/9781119217886.ch10 SN - 0065-8448 VL - 233 SP - 169 EP - 183 PB - American Geophysical Union CY - Washington ER -