@phdthesis{Vorogushyn2008, author = {Vorogushyn, Sergiy}, title = {Analysis of flood hazard under consideration of dike breaches}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-27646}, school = {Universit{\"a}t Potsdam}, year = {2008}, abstract = {River reaches protected by dikes exhibit high damage potential due to strong value accumulation in the hinterland areas. While providing an efficient protection against low magnitude flood events, dikes may fail under the load of extreme water levels and long flood durations. Hazard and risk assessments for river reaches protected by dikes have not adequately considered the fluvial inundation processes up to now. Particularly, the processes of dike failures and their influence on the hinterland inundation and flood wave propagation lack comprehensive consideration. This study focuses on the development and application of a new modelling system which allows a comprehensive flood hazard assessment along diked river reaches under consideration of dike failures. The proposed Inundation Hazard Assessment Model (IHAM) represents a hybrid probabilistic-deterministic model. It comprises three models interactively coupled at runtime. These are: (1) 1D unsteady hydrodynamic model of river channel and floodplain flow between dikes, (2) probabilistic dike breach model which determines possible dike breach locations, breach widths and breach outflow discharges, and (3) 2D raster-based diffusion wave storage cell model of the hinterland areas behind the dikes. Due to the unsteady nature of the 1D and 2D coupled models, the dependence between hydraulic load at various locations along the reach is explicitly considered. The probabilistic dike breach model describes dike failures due to three failure mechanisms: overtopping, piping and slope instability caused by the seepage flow through the dike core (micro-instability). The 2D storage cell model driven by the breach outflow boundary conditions computes an extended spectrum of flood intensity indicators such as water depth, flow velocity, impulse, inundation duration and rate of water rise. IHAM is embedded in a Monte Carlo simulation in order to account for the natural variability of the flood generation processes reflected in the form of input hydrographs and for the randomness of dike failures given by breach locations, times and widths. The model was developed and tested on a ca. 91 km heavily diked river reach on the German part of the Elbe River between gauges Torgau and Vockerode. The reach is characterised by low slope and fairly flat extended hinterland areas. The scenario calculations for the developed synthetic input hydrographs for the main river and tributary were carried out for floods with return periods of T = 100, 200, 500, 1000 a. Based on the modelling results, probabilistic dike hazard maps could be generated that indicate the failure probability of each discretised dike section for every scenario magnitude. In the disaggregated display mode, the dike hazard maps indicate the failure probabilities for each considered breach mechanism. Besides the binary inundation patterns that indicate the probability of raster cells being inundated, IHAM generates probabilistic flood hazard maps. These maps display spatial patterns of the considered flood intensity indicators and their associated return periods. Finally, scenarios of polder deployment for the extreme floods with T = 200, 500, 1000 were simulated with IHAM. The developed IHAM simulation system represents a new scientific tool for studying fluvial inundation dynamics under extreme conditions incorporating effects of technical flood protection measures. With its major outputs in form of novel probabilistic inundation and dike hazard maps, the IHAM system has a high practical value for decision support in flood management.}, language = {en} } @article{MerzVorogushynLalletal.2015, author = {Merz, Bruno and Vorogushyn, Sergiy and Lall, Upmanu and Viglione, Alberto and Bl{\"o}schl, G{\"u}nter}, title = {Charting unknown waters-On the role of surprise in flood risk assessment and management}, series = {Water resources research}, volume = {51}, journal = {Water resources research}, number = {8}, publisher = {American Geophysical Union}, address = {Washington}, issn = {0043-1397}, doi = {10.1002/2015WR017464}, pages = {6399 -- 6416}, year = {2015}, abstract = {Unexpected incidents, failures, and disasters are abundant in the history of flooding events. In this paper, we introduce the metaphors of terra incognita and terra maligna to illustrate unknown and wicked flood situations, respectively. We argue that surprise is a neglected element in flood risk assessment and management. Two sources of surprise are identified: (1) the complexity of flood risk systems, represented by nonlinearities, interdependencies, and nonstationarities and (2) cognitive biases in human perception and decision making. Flood risk assessment and management are particularly prone to cognitive biases due to the rarity and uniqueness of extremes, and the nature of human risk perception. We reflect on possible approaches to better understanding and reducing the potential for surprise and its adverse consequences which may be supported by conceptually charting maps that separate terra incognita from terra cognita, and terra maligna from terra benigna. We conclude that flood risk assessment and management should account for the potential for surprise and devastating consequences which will require a shift in thinking.}, language = {en} } @article{DuethmannBolchFarinottietal.2015, author = {Duethmann, Doris and Bolch, Tobias and Farinotti, Daniel and Kriegel, David and Vorogushyn, Sergiy and Merz, Bruno and Pieczonka, Tino and Jiang, Tong and Su, Buda and G{\"u}ntner, Andreas}, title = {Attribution of streamflow trends in snow and glacier melt-dominated catchments of the Tarim River, Central Asia}, series = {Water resources research}, volume = {51}, journal = {Water resources research}, number = {6}, publisher = {American Geophysical Union}, address = {Washington}, issn = {0043-1397}, doi = {10.1002/2014WR016716}, pages = {4727 -- 4750}, year = {2015}, abstract = {Observed streamflow of headwater catchments of the Tarim River (Central Asia) increased by about 30\% over the period 1957-2004. This study aims at assessing to which extent these streamflow trends can be attributed to changes in air temperature or precipitation. The analysis includes a data-based approach using multiple linear regression and a simulation-based approach using a hydrological model. The hydrological model considers changes in both glacier area and surface elevation. It was calibrated using a multiobjective optimization algorithm with calibration criteria based on glacier mass balance and daily and interannual variations of discharge. The individual contributions to the overall streamflow trends from changes in glacier geometry, temperature, and precipitation were assessed using simulation experiments with a constant glacier geometry and with detrended temperature and precipitation time series. The results showed that the observed changes in streamflow were consistent with the changes in temperature and precipitation. In the Sari-Djaz catchment, increasing temperatures and related increase of glacier melt were identified as the dominant driver, while in the Kakshaal catchment, both increasing temperatures and increasing precipitation played a major role. Comparing the two approaches, an advantage of the simulation-based approach is the fact that it is based on process-based relationships implemented in the hydrological model instead of statistical links in the regression model. However, data-based approaches are less affected by model parameter and structural uncertainties and typically fast to apply. A complementary application of both approaches is recommended.}, language = {en} } @article{MerzVietDungNguyenVorogushyn2016, author = {Merz, Bruno and Viet Dung Nguyen, and Vorogushyn, Sergiy}, title = {Temporal clustering of floods in Germany: Do flood-rich and flood-poor periods exist?}, series = {Journal of hydrology}, volume = {541}, journal = {Journal of hydrology}, publisher = {Elsevier}, address = {Amsterdam}, issn = {0022-1694}, doi = {10.1016/j.jhydrol.2016.07.041}, pages = {824 -- 838}, year = {2016}, abstract = {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.}, language = {en} } @article{MurawskiBuergerVorogushynetal.2016, author = {Murawski, Aline and B{\"u}rger, Gerd and Vorogushyn, Sergiy and Merz, Bruno}, title = {Can local climate variability be explained by weather patterns? A multi-station evaluation for the Rhine basin}, series = {Hydrology and earth system sciences : HESS}, volume = {20}, journal = {Hydrology and earth system sciences : HESS}, publisher = {Copernicus}, address = {G{\"o}ttingen}, issn = {1027-5606}, doi = {10.5194/hess-20-4283-2016}, pages = {4283 -- 4306}, year = {2016}, abstract = {To understand past flood changes in the Rhine catchment and in particular the role of anthropogenic climate change in extreme flows, an attribution study relying on a proper GCM (general circulation model) downscaling is needed. A downscaling based on conditioning a stochastic weather generator on weather patterns is a promising approach. This approach assumes a strong link between weather patterns and local climate, and sufficient GCM skill in reproducing weather pattern climatology. These presuppositions are unprecedentedly evaluated here using 111 years of daily climate data from 490 stations in the Rhine basin and comprehensively testing the number of classification parameters and GCM weather pattern characteristics. A classification based on a combination of mean sea level pressure, temperature, and humidity from the ERA20C reanalysis of atmospheric fields over central Europe with 40 weather types was found to be the most appropriate for stratifying six local climate variables. The corresponding skill is quite diverse though, ranging from good for radiation to poor for precipitation. Especially for the latter it was apparent that pressure fields alone cannot sufficiently stratify local variability. To test the skill of the latest generation of GCMs from the CMIP5 ensemble in reproducing the frequency, seasonality, and persistence of the derived weather patterns, output from 15 GCMs is evaluated. Most GCMs are able to capture these characteristics well, but some models showed consistent deviations in all three evaluation criteria and should be excluded from further attribution analysis.}, language = {en} } @misc{MurawskiBuergerVorogushynetal.2016, author = {Murawski, Aline and B{\"u}rger, Gerd and Vorogushyn, Sergiy and Merz, Bruno}, title = {Can local climate variability be explained by weather patterns?}, series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, journal = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, number = {525}, issn = {1866-8372}, doi = {10.25932/publishup-41015}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-410155}, pages = {24}, year = {2016}, abstract = {To understand past flood changes in the Rhine catchment and in particular the role of anthropogenic climate change in extreme flows, an attribution study relying on a proper GCM (general circulation model) downscaling is needed. A downscaling based on conditioning a stochastic weather generator on weather patterns is a promising approach. This approach assumes a strong link between weather patterns and local climate, and sufficient GCM skill in reproducing weather pattern climatology. These presuppositions are unprecedentedly evaluated here using 111 years of daily climate data from 490 stations in the Rhine basin and comprehensively testing the number of classification parameters and GCM weather pattern characteristics. A classification based on a combination of mean sea level pressure, temperature, and humidity from the ERA20C reanalysis of atmospheric fields over central Europe with 40 weather types was found to be the most appropriate for stratifying six local climate variables. The corresponding skill is quite diverse though, ranging from good for radiation to poor for precipitation. Especially for the latter it was apparent that pressure fields alone cannot sufficiently stratify local variability. To test the skill of the latest generation of GCMs from the CMIP5 ensemble in reproducing the frequency, seasonality, and persistence of the derived weather patterns, output from 15 GCMs is evaluated. Most GCMs are able to capture these characteristics well, but some models showed consistent deviations in all three evaluation criteria and should be excluded from further attribution analysis.}, language = {en} } @article{KreibichDiBaldassarreVorogushynetal.2017, author = {Kreibich, Heidi and Di Baldassarre, Giuliano and Vorogushyn, Sergiy and Aerts, Jeroen C. J. H. and Apel, Heiko and Aronica, Giuseppe T. and Arnbjerg-Nielsen, Karsten and Bouwer, Laurens M. and Bubeck, Philip and Caloiero, Tommaso and Chinh, Do T. and Cortes, Maria and Gain, Animesh K. and Giampa, Vincenzo and Kuhlicke, Christian and Kundzewicz, Zbigniew W. and Llasat, Maria Carmen and Mard, Johanna and Matczak, Piotr and Mazzoleni, Maurizio and Molinari, Daniela and Dung, Nguyen V. and Petrucci, Olga and Schr{\"o}ter, Kai and Slager, Kymo and Thieken, Annegret and Ward, Philip J. and Merz, Bruno}, title = {Adaptation to flood risk}, series = {Earth's Future}, volume = {5}, journal = {Earth's Future}, publisher = {Wiley}, address = {Hoboken}, issn = {2328-4277}, doi = {10.1002/2017EF000606}, pages = {953 -- 965}, year = {2017}, abstract = {As flood impacts are increasing in large parts of the world, understanding the primary drivers of changes in risk is essential for effective adaptation. To gain more knowledge on the basis of empirical case studies, we analyze eight paired floods, that is, consecutive flood events that occurred in the same region, with the second flood causing significantly lower damage. These success stories of risk reduction were selected across different socioeconomic and hydro-climatic contexts. The potential of societies to adapt is uncovered by describing triggered societal changes, as well as formal measures and spontaneous processes that reduced flood risk. This novel approach has the potential to build the basis for an international data collection and analysis effort to better understand and attribute changes in risk due to hydrological extremes in the framework of the IAHSs Panta Rhei initiative. Across all case studies, we find that lower damage caused by the second event was mainly due to significant reductions in vulnerability, for example, via raised risk awareness, preparedness, and improvements of organizational emergency management. Thus, vulnerability reduction plays an essential role for successful adaptation. Our work shows that there is a high potential to adapt, but there remains the challenge to stimulate measures that reduce vulnerability and risk in periods in which extreme events do not occur.}, language = {en} } @article{DiBaldassarreKreibichVorogushynetal.2018, author = {Di Baldassarre, Giuliano and Kreibich, Heidi and Vorogushyn, Sergiy and Aerts, Jeroen and Arnbjerg-Nielsen, Karsten and Barendrecht, Marlies and Bates, Paul and Borga, Marco and Botzen, Wouter and Bubeck, Philip and De Marchi, Bruna and Llasat, Carmen Maria and Mazzoleni, Maurizio and Molinari, Daniela and Mondino, Elena and Mard, Johanna and Petrucci, Olga and Scolobig, Anna and Viglione, Alberto and Ward, Philip J.}, title = {Hess Opinions: An interdisciplinary research agenda to explore the unintended consequences of structural flood protection}, series = {Hydrology and earth system sciences : HESS}, volume = {22}, journal = {Hydrology and earth system sciences : HESS}, number = {11}, publisher = {Copernicus}, address = {G{\"o}ttingen}, issn = {1027-5606}, doi = {10.5194/hess-22-5629-2018}, pages = {5629 -- 5637}, year = {2018}, abstract = {One common approach to cope with floods is the implementation of structural flood protection measures, such as levees or flood-control reservoirs, which substantially reduce the probability of flooding at the time of implementation. Numerous scholars have problematized this approach. They have shown that increasing the levels of flood protection can attract more settlements and high-value assets in the areas protected by the new measures. Other studies have explored how structural measures can generate a sense of complacency, which can act to reduce preparedness. These paradoxical risk changes have been described as "levee effect", "safe development paradox" or "safety dilemma". In this commentary, we briefly review this phenomenon by critically analysing the intended benefits and unintended effects of structural flood protection, and then we propose an interdisciplinary research agenda to uncover these paradoxical dynamics of risk.}, language = {en} } @article{MetinNguyenVietDungSchroeteretal.2018, author = {Metin, Ayse Duha and Nguyen Viet Dung, and Schr{\"o}ter, Kai and Guse, Bj{\"o}rn and Apel, Heiko and Kreibich, Heidi and Vorogushyn, Sergiy and Merz, Bruno}, title = {How do changes along the risk chain affect flood risk?}, series = {Natural hazards and earth system sciences}, volume = {18}, journal = {Natural hazards and earth system sciences}, number = {11}, publisher = {Copernicus}, address = {G{\"o}ttingen}, issn = {1561-8633}, doi = {10.5194/nhess-18-3089-2018}, pages = {3089 -- 3108}, year = {2018}, abstract = {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.}, language = {en} } @article{MerzApelDungNguyenetal.2018, author = {Merz, Bruno and Apel, Heiko and Dung Nguyen, Viet-Dung and Falter, Daniela and Guse, Bj{\"o}rn and Hundecha, Yeshewatesfa and Kreibich, Heidi and Schr{\"o}ter, Kai and Vorogushyn, Sergiy}, title = {From precipitation to damage}, series = {Global flood hazard : applications in modeling, mapping and forecasting}, volume = {233}, journal = {Global flood hazard : applications in modeling, mapping and forecasting}, publisher = {American Geophysical Union}, address = {Washington}, isbn = {978-1-119-21788-6}, issn = {0065-8448}, doi = {10.1002/9781119217886.ch10}, pages = {169 -- 183}, year = {2018}, abstract = {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.}, language = {en} } @article{MerzNguyenApeletal.2018, author = {Merz, Bruno and Nguyen, Viet Dung and Apel, Heiko and Gerlitz, Lars and Schr{\"o}ter, Kai and Steirou, Eva Styliani and Vorogushyn, Sergiy}, title = {Spatial coherence of flood-rich and flood-poor periods across Germany}, series = {Journal of hydrology}, volume = {559}, journal = {Journal of hydrology}, publisher = {Elsevier}, address = {Amsterdam}, issn = {0022-1694}, doi = {10.1016/j.jhydrol.2018.02.082}, pages = {813 -- 826}, year = {2018}, abstract = {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.}, language = {en} } @article{HeVorogushynUngerShayestehetal.2018, author = {He, Zhihua and Vorogushyn, Sergiy and Unger-Shayesteh, Katy and Gafurov, Abror and Kalashnikova, Olga and Omorova, Elvira and Merz, Bruno}, title = {The Value of Hydrograph Partitioning Curves for Calibrating Hydrological Models in Glacierized Basins}, series = {Water resources research}, volume = {54}, journal = {Water resources research}, number = {3}, publisher = {American Geophysical Union}, address = {Washington}, issn = {0043-1397}, doi = {10.1002/2017WR021966}, pages = {2336 -- 2361}, year = {2018}, abstract = {This study refines the method for calibrating a glacio-hydrological model based on Hydrograph Partitioning Curves (HPCs), and evaluates its value in comparison to multidata set optimization approaches which use glacier mass balance, satellite snow cover images, and discharge. The HPCs are extracted from the observed flow hydrograph using catchment precipitation and temperature gradients. They indicate the periods when the various runoff processes, such as glacier melt or snow melt, dominate the basin hydrograph. The annual cumulative curve of the difference between average daily temperature and melt threshold temperature over the basin, as well as the annual cumulative curve of average daily snowfall on the glacierized areas are used to identify the starting and end dates of snow and glacier ablation periods. Model parameters characterizing different runoff processes are calibrated on different HPCs in a stepwise and iterative way. Results show that the HPC-based method (1) delivers model-internal consistency comparably to the tri-data set calibration method; (2) improves the stability of calibrated parameter values across various calibration periods; and (3) estimates the contributions of runoff components similarly to the tri-data set calibration method. Our findings indicate the potential of the HPC-based approach as an alternative for hydrological model calibration in glacierized basins where other calibration data sets than discharge are often not available or very costly to obtain.}, language = {en} } @misc{MetinDungSchroeteretal.2018, author = {Metin, Ayse Duha and Dung, Nguyen Viet and Schr{\"o}ter, Kai and Guse, Bj{\"o}rn and Apel, Heiko and Kreibich, Heidi and Vorogushyn, Sergiy and Merz, Bruno}, title = {How do changes along the risk chain affect flood risk?}, series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, journal = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, number = {1067}, issn = {1866-8372}, doi = {10.25932/publishup-46879}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-468790}, pages = {22}, year = {2018}, abstract = {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.}, language = {en} } @article{MurawskiVorogushynBuergeretal.2018, author = {Murawski, Aline and Vorogushyn, Sergiy and B{\"u}rger, Gerd and Gerlitz, Lars and Merz, Bruno}, title = {Do changing weather types explain observed climatic trends in the rhine basin?}, series = {Journal of geophysical of geophysical research-atmosheres}, volume = {123}, journal = {Journal of geophysical of geophysical research-atmosheres}, number = {3}, publisher = {American Geophysical Union}, address = {Washington}, issn = {2169-897X}, doi = {10.1002/2017JD026654}, pages = {1562 -- 1584}, year = {2018}, abstract = {For attributing hydrological changes to anthropogenic climate change, catchment models are driven by climate model output. A widespread approach to bridge the spatial gap between global climate and hydrological catchment models is to use a weather generator conditioned on weather patterns (WPs). This approach assumes that changes in local climate are characterized by between-type changes of patterns. In this study we test this assumption by analyzing a previously developed WP classification for the Rhine basin, which is based on dynamic and thermodynamic variables. We quantify changes in pattern characteristics and associated climatic properties. The amount of between- and within-type changes is investigated by comparing observed trends to trends resulting solely from WP occurrence. To overcome uncertainties in trend detection resulting from the selected time period, all possible periods in 1901-2010 with a minimum length of 31 years are analyzed. Increasing frequency is found for some patterns associated with high precipitation, although the trend sign highly depends on the considered period. Trends and interannual variations of WP frequencies are related to the long-term variability of large-scale circulation modes. Long-term WP internal warming is evident for summer patterns and enhanced warming for spring/autumn patterns since the 1970s. Observed trends in temperature and partly in precipitation are mainly associated with frequency changes of specific WPs, but some amount of within-type changes remains. The classification can be used for downscaling of past changes considering this limitation, but the inclusion of thermodynamic variables into the classification impedes the downscaling of future climate projections.}, language = {en} } @article{BarendrechtViglioneKreibichetal.2019, author = {Barendrecht, Marlies H. and Viglione, Alberto and Kreibich, Heidi and Merz, Bruno and Vorogushyn, Sergiy and Bl{\"o}schl, G.}, title = {The Value of Empirical Data for Estimating the Parameters of a Sociohydrological Flood Risk Model}, series = {Water resources research}, volume = {55}, journal = {Water resources research}, number = {2}, publisher = {American Geophysical Union}, address = {Washington}, issn = {0043-1397}, doi = {10.1029/2018WR024128}, pages = {1312 -- 1336}, year = {2019}, abstract = {In this paper, empirical data are used to estimate the parameters of a sociohydrological flood risk model. The proposed model, which describes the interactions between floods, settlement density, awareness, preparedness, and flood loss, is based on the literature. Data for the case study of Dresden, Germany, over a period of 200years, are used to estimate the model parameters through Bayesian inference. The credibility bounds of their estimates are small, even though the data are rather uncertain. A sensitivity analysis is performed to examine the value of the different data sources in estimating the model parameters. In general, the estimated parameters are less biased when using data at the end of the modeled period. Data about flood awareness are the most important to correctly estimate the parameters of this model and to correctly model the system dynamics. Using more data for other variables cannot compensate for the absence of awareness data. More generally, the absence of data mostly affects the estimation of the parameters that are directly related to the variable for which data are missing. This paper demonstrates that combining sociohydrological modeling and empirical data gives additional insights into the sociohydrological system, such as quantifying the forgetfulness of the society, which would otherwise not be easily achieved by sociohydrological models without data or by standard statistical analysis of empirical data.}, language = {en} } @article{WinterSchneebergerDungetal.2019, author = {Winter, Benjamin and Schneeberger, Klaus and Dung, N. V. and Huttenlau, M. and Achleitner, S. and St{\"o}tter, J. and Merz, Bruno and Vorogushyn, Sergiy}, title = {A continuous modelling approach for design flood estimation on sub-daily time scale}, series = {Hydrological sciences journal = Journal des sciences hydrologiques}, volume = {64}, journal = {Hydrological sciences journal = Journal des sciences hydrologiques}, number = {5}, publisher = {Routledge, Taylor \& Francis Group}, address = {Abingdon}, issn = {0262-6667}, doi = {10.1080/02626667.2019.1593419}, pages = {539 -- 554}, year = {2019}, abstract = {Design flood estimation is an essential part of flood risk assessment. Commonly applied are flood frequency analyses and design storm approaches, while the derived flood frequency using continuous simulation has been getting more attention recently. In this study, a continuous hydrological modelling approach on an hourly time scale, driven by a multi-site weather generator in combination with a -nearest neighbour resampling procedure, based on the method of fragments, is applied. The derived 100-year flood estimates in 16 catchments in Vorarlberg (Austria) are compared to (a) the flood frequency analysis based on observed discharges, and (b) a design storm approach. Besides the peak flows, the corresponding runoff volumes are analysed. The spatial dependence structure of the synthetically generated flood peaks is validated against observations. It can be demonstrated that the continuous modelling approach can achieve plausible results and shows a large variability in runoff volume across the flood events.}, language = {en} } @misc{TarasovaMerzKissetal.2019, author = {Tarasova, Larisa and Merz, Ralf and Kiss, Andrea and Basso, Stefano and Bl{\"o}chl, G{\"u}nter and Merz, Bruno and Viglione, Alberto and Pl{\"o}tner, Stefan and Guse, Bj{\"o}rn and Schumann, Andreas and Fischer, Svenja and Ahrens, Bodo and Anwar, Faizan and B{\´a}rdossy, Andr{\´a}s and B{\"u}hler, Philipp and Haberlandt, Uwe and Kreibich, Heidi and Krug, Amelie and Lun, David and M{\"u}ller-Thomy, Hannes and Pidoto, Ross and Primo, Cristina and Seidel, Jochen and Vorogushyn, Sergiy and Wietzke, Luzie}, title = {Causative classification of river flood events}, series = {Wiley Interdisciplinary Reviews : Water}, volume = {6}, journal = {Wiley Interdisciplinary Reviews : Water}, number = {4}, publisher = {Wiley}, address = {Hoboken}, issn = {2049-1948}, doi = {10.1002/wat2.1353}, pages = {23}, year = {2019}, abstract = {A wide variety of processes controls the time of occurrence, duration, extent, and severity of river floods. Classifying flood events by their causative processes may assist in enhancing the accuracy of local and regional flood frequency estimates and support the detection and interpretation of any changes in flood occurrence and magnitudes. This paper provides a critical review of existing causative classifications of instrumental and preinstrumental series of flood events, discusses their validity and applications, and identifies opportunities for moving toward more comprehensive approaches. So far no unified definition of causative mechanisms of flood events exists. Existing frameworks for classification of instrumental and preinstrumental series of flood events adopt different perspectives: hydroclimatic (large-scale circulation patterns and atmospheric state at the time of the event), hydrological (catchment scale precipitation patterns and antecedent catchment state), and hydrograph-based (indirectly considering generating mechanisms through their effects on hydrograph characteristics). All of these approaches intend to capture the flood generating mechanisms and are useful for characterizing the flood processes at various spatial and temporal scales. However, uncertainty analyses with respect to indicators, classification methods, and data to assess the robustness of the classification are rarely performed which limits the transferability across different geographic regions. It is argued that more rigorous testing is needed. There are opportunities for extending classification methods to include indicators of space-time dynamics of rainfall, antecedent wetness, and routing effects, which will make the classification schemes even more useful for understanding and estimating floods. This article is categorized under: Science of Water > Water Extremes Science of Water > Hydrological Processes Science of Water > Methods}, language = {en} } @article{HeUngerShayestehVorogushynetal.2019, author = {He, Zhihua and Unger-Shayesteh, Katy and Vorogushyn, Sergiy and Weise, Stephan M. and Kalashnikova, Olga and Gafurov, Abror and Duethmann, Doris and Barandun, Martina and Merz, Bruno}, title = {Constraining hydrological model parameters using water isotopic compositions in a glacierized basin, Central Asia}, series = {Journal of hydrology}, volume = {571}, journal = {Journal of hydrology}, publisher = {Elsevier}, address = {Amsterdam}, issn = {0022-1694}, doi = {10.1016/j.jhydrol.2019.01.048}, pages = {332 -- 348}, year = {2019}, abstract = {Water stable isotope signatures can provide valuable insights into the catchment internal runoff processes. However, the ability of the water isotope data to constrain the internal apportionments of runoff components in hydrological models for glacierized basins is not well understood. This study developed an approach to simultaneously model the water stable isotopic compositions and runoff processes in a glacierized basin in Central Asia. The fractionation and mixing processes of water stable isotopes in and from the various water sources were integrated into a glacio-hydrological model. The model parameters were calibrated on discharge, snow cover and glacier mass balance data, and additionally isotopic composition of streamflow. We investigated the value of water isotopic compositions for the calibration of model parameters, in comparison to calibration methods without using such measurements. Results indicate that: (1) The proposed isotope-hydrological integrated modeling approach was able to reproduce the isotopic composition of streamflow, and improved the model performance in the evaluation period; (2) Involving water isotopic composition for model calibration reduced the model parameter uncertainty, and helped to reduce the uncertainty in the quantification of runoff components; (3) The isotope-hydrological integrated modeling approach quantified the contributions of runoff components comparably to a three-component tracer-based end-member mixing analysis method for summer peak flows, and required less water tracer data. Our findings demonstrate the value of water isotopic compositions to improve the quantification of runoff components using hydrological models in glacierized basins.}, language = {en} } @article{GerlitzSteirouSchneideretal.2019, author = {Gerlitz, Lars and Steirou, Eva and Schneider, Christoph and Moron, Vincent and Vorogushyn, Sergiy and Merz, Bruno}, title = {Variability of the Cold Season Climate in Central Asia. Part II: Hydroclimatic Predictability}, series = {Journal of climate}, volume = {32}, journal = {Journal of climate}, number = {18}, publisher = {American Meteorological Soc.}, address = {Boston}, issn = {0894-8755}, doi = {10.1175/JCLI-D-18-0892.1}, pages = {6015 -- 6033}, year = {2019}, abstract = {Central Asia (CA) is subjected to a large variability of precipitation. This study presents a statistical model, relating precipitation anomalies in three subregions of CA in the cold season (November-March) with various predictors in the preceding October. Promising forecast skill is achieved for two subregions covering 1) Uzbekistan, Turkmenistan, Kyrgyzstan, Tajikistan, and southern Kazakhstan and 2) Iran, Afghanistan, and Pakistan. ENSO in October is identified as the major predictor. Eurasian snow cover and the quasi-biennial oscillation further improve the forecast performance. To understand the physical mechanisms, an analysis of teleconnections between these predictors and the wintertime circulation over CA is conducted. The correlation analysis of predictors and large-scale circulation indices suggests a seasonal persistence of tropical circulation modes and a dynamical forcing of the westerly circulation by snow cover variations over Eurasia. An EOF analysis of pressure and humidity patterns allows separating the circulation variability over CA into westerly and tropical modes and confirms that the identified predictors affect the respective circulation characteristics. Based on the previously established weather type classification for CA, the predictors are investigated with regard to their effect on the regional circulation. The results suggest a modification of the Hadley cell due to ENSO variations, with enhanced moisture supply from the Arabian Gulf during El Nino. They further indicate an influence of Eurasian snow cover on the wintertime Arctic Oscillation (AO) and Northern Hemispheric Rossby wave tracks. Positive anomalies favor weather types associated with dry conditions, while negative anomalies promote the formation of a quasi-stationary trough over CA, which typically occurs during positive AO conditions.}, language = {en} } @article{WietzkeMerzGerlitzetal.2020, author = {Wietzke, Luzie M. and Merz, Bruno and Gerlitz, Lars and Kreibich, Heidi and Guse, Bj{\"o}rn and Castellarin, Attilio and Vorogushyn, Sergiy}, title = {Comparative analysis of scalar upper tail indicators}, series = {Hydrological sciences journal = Journal des sciences hydrologiques}, volume = {65}, journal = {Hydrological sciences journal = Journal des sciences hydrologiques}, number = {10}, publisher = {Routledge, Taylor \& Francis Group}, address = {Abingdon}, issn = {0262-6667}, doi = {10.1080/02626667.2020.1769104}, pages = {1625 -- 1639}, year = {2020}, abstract = {Different upper tail indicators exist to characterize heavy tail phenomena, but no comparative study has been carried out so far. We evaluate the shape parameter (GEV), obesity index, Gini index and upper tail ratio (UTR) against a novel benchmark of tail heaviness - the surprise factor. Sensitivity analyses to sample size and changes in scale-to-location ratio are carried out in bootstrap experiments. The UTR replicates the surprise factor best but is most uncertain and only comparable between records of similar length. For samples with symmetric Lorenz curves, shape parameter, obesity and Gini indices provide consistent indications. For asymmetric Lorenz curves, however, the first two tend to overestimate, whereas Gini index tends to underestimate tail heaviness. We suggest the use of a combination of shape parameter, obesity and Gini index to characterize tail heaviness. These indicators should be supported with calculation of the Lorenz asymmetry coefficients and interpreted with caution.}, language = {en} } @article{MetinDungSchroeteretal.2020, author = {Metin, Ayse Duha and Dung, Nguyen Viet and Schr{\"o}ter, Kai and Vorogushyn, Sergiy and Guse, Bj{\"o}rn and Kreibich, Heidi and Merz, Bruno}, title = {The role of spatial dependence for large-scale flood risk estimation}, series = {Natural hazards and earth system sciences}, volume = {20}, journal = {Natural hazards and earth system sciences}, number = {4}, publisher = {European Geosciences Union (EGU) ; Copernicus}, address = {G{\"o}ttingen}, issn = {1561-8633}, doi = {10.5194/nhess-20-967-2020}, pages = {967 -- 979}, year = {2020}, abstract = {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.}, language = {en} } @article{SairamBrillSiegetal.2021, author = {Sairam, Nivedita and Brill, Fabio Alexander and Sieg, Tobias and Farrag, Mostafa and Kellermann, Patric and Viet Dung Nguyen, and L{\"u}dtke, Stefan and Merz, Bruno and Schr{\"o}ter, Kai and Vorogushyn, Sergiy and Kreibich, Heidi}, title = {Process-based flood risk assessment for Germany}, series = {Earth's future / American Geophysical Union}, volume = {9}, journal = {Earth's future / American Geophysical Union}, number = {10}, publisher = {Wiley-Blackwell}, address = {Hoboken, NJ}, issn = {2328-4277}, doi = {10.1029/2021EF002259}, pages = {12}, year = {2021}, abstract = {Large-scale flood risk assessments are crucial for decision making, especially with respect to new flood defense schemes, adaptation planning and estimating insurance premiums. We apply the process-based Regional Flood Model (RFM) to simulate a 5000-year flood event catalog for all major catchments in Germany and derive risk curves based on the losses per economic sector. The RFM uses a continuous process simulation including a multisite, multivariate weather generator, a hydrological model considering heterogeneous catchment processes, a coupled 1D-2D hydrodynamic model considering dike overtopping and hinterland storage, spatially explicit sector-wise exposure data and empirical multi-variable loss models calibrated for Germany. For all components, uncertainties in the data and models are estimated. We estimate the median Expected Annual Damage (EAD) and Value at Risk at 99.5\% confidence for Germany to be euro0.529 bn and euro8.865 bn, respectively. The commercial sector dominates by making about 60\% of the total risk, followed by the residential sector. The agriculture sector gets affected by small return period floods and only contributes to less than 3\% to the total risk. The overall EAD is comparable to other large-scale estimates. However, the estimation of losses for specific return periods is substantially improved. The spatial consistency of the risk estimates avoids the large overestimation of losses for rare events that is common in other large-scale assessments with homogeneous return periods. Thus, the process-based, spatially consistent flood risk assessment by RFM is an important step forward and will serve as a benchmark for future German-wide flood risk assessments.}, language = {en} } @article{UllrichHegnauerNguyenetal.2021, author = {Ullrich, Sophie Louise and Hegnauer, Mark and Nguyen, Dung Viet and Merz, Bruno and Kwadijk, Jaap and Vorogushyn, Sergiy}, title = {Comparative evaluation of two types of stochastic weather generators for synthetic precipitation in the Rhine basin}, series = {Journal of hydrology}, volume = {601}, journal = {Journal of hydrology}, publisher = {Elsevier}, address = {Amsterdam [u.a.]}, issn = {0022-1694}, doi = {10.1016/j.jhydrol.2021.126544}, pages = {16}, year = {2021}, abstract = {Stochastic modeling of precipitation for estimation of hydrological extremes is an important element of flood risk assessment and management. The spatially consistent estimation of rainfall fields and their temporal variability remains challenging and is addressed by various stochastic weather generators. In this study, two types of weather generators are evaluated against observed data and benchmarked regarding their ability to simulate spatio-temporal precipitation fields in the Rhine catchment. A multi-site station-based weather generator uses an auto-regressive model and estimates the spatial correlation structure between stations. Another weather generator is raster-based and uses the nearest-neighbor resampling technique for reshuffling daily patterns while preserving the correlation structure between the observations. Both weather generators perform well and are comparable at the point (station) scale with regards to daily mean and 99.9th percentile precipitation as well as concerning wet/dry frequencies and transition probabilities. The areal extreme precipitation at the sub-basin scale is however overestimated in the station-based weather generator due to an overestimation of the correlation structure between individual stations. The auto-regressive model tends to generate larger rainfall fields in space for extreme precipitation than observed, particularly in summer. The weather generator based on nearest-neighbor resampling reproduces the observed daily and multiday (5, 10 and 20) extreme events in a similar magnitude. Improvements in performance regarding wet frequencies and transition probabilities are recommended for both models.}, language = {en} } @article{MacdonaldMerzGuseetal.2022, author = {Macdonald, Elena and Merz, Bruno and Guse, Bj{\"o}rn and Wietzke, Luzie and Ullrich, Sophie and Kemter, Matthias and Ahrens, Bodo and Vorogushyn, Sergiy}, title = {Event and catchment controls of heavy tail behavior of floods}, series = {Water resources research}, volume = {58}, journal = {Water resources research}, number = {6}, publisher = {American Geophysical Union}, address = {Washington}, issn = {0043-1397}, doi = {10.1029/2021WR031260}, pages = {25}, year = {2022}, abstract = {In some catchments, the distribution of annual maximum streamflow shows heavy tail behavior, meaning the occurrence probability of extreme events is higher than if the upper tail decayed exponentially. Neglecting heavy tail behavior can lead to an underestimation of the likelihood of extreme floods and the associated risk. Partly contradictory results regarding the controls of heavy tail behavior exist in the literature and the knowledge is still very dispersed and limited. To better understand the drivers, we analyze the upper tail behavior and its controls for 480 catchments in Germany and Austria over a period of more than 50 years. The catchments span from quickly reacting mountain catchments to large lowland catchments, allowing for general conclusions. We compile a wide range of event and catchment characteristics and investigate their association with an indicator of the tail heaviness of flood distributions, namely the shape parameter of the GEV distribution. Following univariate analyses of these characteristics, along with an evaluation of different aggregations of event characteristics, multiple linear regression models, as well as random forests, are constructed. A novel slope indicator, which represents the relation between the return period of flood peaks and event characteristics, captures the controls of heavy tails best. Variables describing the catchment response are found to dominate the heavy tail behavior, followed by event precipitation, flood seasonality, and catchment size. The pre-event moisture state in a catchment has no relevant impact on the tail heaviness even though it does influence flood magnitudes.}, language = {en} } @article{MerzBassoFischeretal.2022, author = {Merz, Bruno and Basso, Stefano and Fischer, Svenja and Lun, David and Bloeschl, Guenter and Merz, Ralf and Guse, Bjorn and Viglione, Alberto and Vorogushyn, Sergiy and Macdonald, Elena and Wietzke, Luzie and Schumann, Andreas}, title = {Understanding heavy tails of flood peak distributions}, series = {Water resources research}, volume = {58}, journal = {Water resources research}, number = {6}, publisher = {American Geophysical Union}, address = {Washington}, issn = {0043-1397}, doi = {10.1029/2021WR030506}, pages = {37}, year = {2022}, abstract = {Statistical distributions of flood peak discharge often show heavy tail behavior, that is, extreme floods are more likely to occur than would be predicted by commonly used distributions that have exponential asymptotic behavior. This heavy tail behavior may surprise flood managers and citizens, as human intuition tends to expect light tail behavior, and the heaviness of the tails is very difficult to predict, which may lead to unnecessarily high flood damage. Despite its high importance, the literature on the heavy tail behavior of flood distributions is rather fragmented. In this review, we provide a coherent overview of the processes causing heavy flood tails and the implications for science and practice. Specifically, we propose nine hypotheses on the mechanisms causing heavy tails in flood peak distributions related to processes in the atmosphere, the catchment, and the river system. We then discuss to which extent the current knowledge supports or contradicts these hypotheses. We also discuss the statistical conditions for the emergence of heavy tail behavior based on derived distribution theory and relate them to the hypotheses and flood generation mechanisms. We review the degree to which the heaviness of the tails can be predicted from process knowledge and data. Finally, we recommend further research toward testing the hypotheses and improving the prediction of heavy tails.}, language = {en} } @article{FarragBrillNguyenetal.2022, author = {Farrag, Mostafa and Brill, Fabio Alexander and Nguyen, Viet Dung and Sairam, Nivedita and Schr{\"o}ter, Kai and Kreibich, Heidi and Merz, Bruno and de Bruijn, Karin M. and Vorogushyn, Sergiy}, title = {On the role of floodplain storage and hydrodynamic interactions in flood risk estimation}, series = {Hydrological sciences journal = Journal des sciences hydrologiques}, volume = {67}, journal = {Hydrological sciences journal = Journal des sciences hydrologiques}, number = {4}, publisher = {Routledge, Taylor \& Francis Group}, address = {Abingdon}, issn = {0262-6667}, doi = {10.1080/02626667.2022.2030058}, pages = {508 -- 534}, year = {2022}, abstract = {Hydrodynamic interactions, i.e. the floodplain storage effects caused by inundations upstream on flood wave propagation, inundation areas, and flood damage downstream, are important but often ignored in large-scale flood risk assessments. Although new methods considering these effects sometimes emerge, they are often limited to a small or meso scale. In this study, we investigate the role of hydrodynamic interactions and floodplain storage on flood hazard and risk in the German part of the Rhine basin. To do so, we compare a new continuous 1D routing scheme within a flood risk model chain to the piece-wise routing scheme, which largely neglects floodplain storage. The results show that floodplain storage is significant, lowers water levels and discharges, and reduces risks by over 50\%. Therefore, for accurate risk assessments, a system approach must be adopted, and floodplain storage and hydrodynamic interactions must carefully be considered.}, language = {en} }