TY - JOUR A1 - Merz, Bruno A1 - Viet Dung Nguyen, A1 - Vorogushyn, Sergiy T1 - Temporal clustering of floods in Germany: Do flood-rich and flood-poor periods exist? JF - Journal of hydrology N2 - The repeated occurrence of exceptional floods within a few years, such as the Rhine floods in 1993 and 1995 and the Elbe and Danube floods in 2002 and 2013, suggests that floods in Central Europe may be organized in flood-rich and flood-poor periods. This hypothesis is studied by testing the significance of temporal clustering in flood occurrence (peak-over-threshold) time series for 68 catchments across Germany for the period 1932-2005. To assess the robustness of the results, different methods are used: Firstly, the index of dispersion, which quantifies the departure from a homogeneous Poisson process, is investigated. Further, the time-variation of the flood occurrence rate is derived by non-parametric kernel implementation and the significance of clustering is evaluated via parametric and non-parametric tests. Although the methods give consistent overall results, the specific results differ considerably. Hence, we recommend applying different methods when investigating flood clustering. For flood estimation and risk management, it is of relevance to understand whether clustering changes with flood severity and time scale. To this end, clustering is assessed for different thresholds and time scales. It is found that the majority of catchments show temporal clustering at the 5% significance level for low thresholds and time scales of one to a few years. However, clustering decreases substantially with increasing threshold and time scale. We hypothesize that flood clustering in Germany is mainly caused by catchment memory effects along with intra- to inter-annual climate variability, and that decadal climate variability plays a minor role. (C) 2016 Elsevier B.V. All rights reserved. KW - Climate variability KW - Flooding KW - Temporal clustering KW - Index of dispersion KW - Kernel occurrence rate Y1 - 2016 U6 - https://doi.org/10.1016/j.jhydrol.2016.07.041 SN - 0022-1694 SN - 1879-2707 VL - 541 SP - 824 EP - 838 PB - Elsevier CY - Amsterdam ER - 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 - Metin, Ayse Duha A1 - Dung, Nguyen Viet A1 - Schröter, Kai A1 - Vorogushyn, Sergiy A1 - Guse, Björn A1 - Kreibich, Heidi A1 - Merz, Bruno T1 - The role of spatial dependence for large-scale flood risk estimation JF - Natural hazards and earth system sciences N2 - Flood risk assessments are typically based on scenarios which assume homogeneous return periods of flood peaks throughout the catchment. This assumption is unrealistic for real flood events and may bias risk estimates for specific return periods. We investigate how three assumptions about the spatial dependence affect risk estimates: (i) spatially homogeneous scenarios (complete dependence), (ii) spatially heterogeneous scenarios (modelled dependence) and (iii) spatially heterogeneous but uncorrelated scenarios (complete independence). To this end, the model chain RFM (regional flood model) is applied to the Elbe catchment in Germany, accounting for the spatio-temporal dynamics of all flood generation processes, from the rainfall through catchment and river system processes to damage mechanisms. Different assumptions about the spatial dependence do not influence the expected annual damage (EAD); however, they bias the risk curve, i.e. the cumulative distribution function of damage. The widespread assumption of complete dependence strongly overestimates flood damage of the order of 100% for return periods larger than approximately 200 years. On the other hand, for small and medium floods with return periods smaller than approximately 50 years, damage is underestimated. The overestimation aggravates when risk is estimated for larger areas. This study demonstrates the importance of representing the spatial dependence of flood peaks and damage for risk assessments. Y1 - 2020 U6 - https://doi.org/10.5194/nhess-20-967-2020 SN - 1561-8633 SN - 1684-9981 VL - 20 IS - 4 SP - 967 EP - 979 PB - European Geosciences Union (EGU) ; Copernicus CY - Göttingen ER - TY - GEN A1 - Metin, Ayse Duha A1 - Dung, Nguyen Viet 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? T2 - Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe 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. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 1067 KW - global sensitivity analysis KW - climate change KW - river floods KW - frequency KW - Europe KW - model KW - vulnerability KW - adaptation KW - strategies KW - catchment Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-468790 SN - 1866-8372 IS - 1067 ER - TY - JOUR A1 - Sun, Xun A1 - Lall, Upmanu A1 - Merz, Bruno A1 - Nguyen Viet Dung, T1 - Hierarchical Bayesian clustering for nonstationary flood frequency analysis: Application to trends of annual maximum flow in Germany JF - Water resources research N2 - Especially for extreme precipitation or floods, there is considerable spatial and temporal variability in long term trends or in the response of station time series to large-scale climate indices. Consequently, identifying trends or sensitivity of these extremes to climate parameters can be marked by high uncertainty. When one develops a nonstationary frequency analysis model, a key step is the identification of potential trends or effects of climate indices on the station series. An automatic clustering procedure that effectively pools stations where there are similar responses is desirable to reduce the estimation variance, thus improving the identification of trends or responses, and accounting for spatial dependence. This paper presents a new hierarchical Bayesian approach for exploring homogeneity of response in large area data sets, through a multicomponent mixture model. The approach allows the reduction of uncertainties through both full pooling and partial pooling of stations across automatically chosen subsets of the data. We apply the model to study the trends in annual maximum daily stream flow at 68 gauges over Germany. The effects of changing the number of clusters and the parameters used for clustering are demonstrated. The results show that there are large, mainly upward trends in the gauges of the River Rhine Basin in Western Germany and along the main stream of the Danube River in the south, while there are also some small upward trends at gauges in Central and Northern Germany. Y1 - 2015 U6 - https://doi.org/10.1002/2015WR017117 SN - 0043-1397 SN - 1944-7973 VL - 51 IS - 8 SP - 6586 EP - 6601 PB - American Geophysical Union CY - Washington ER -