TY - JOUR A1 - Steirou, Eva A1 - Gerlitz, Lars A1 - Sun, Xun A1 - Apel, Heiko A1 - Agarwal, Ankit A1 - Totz, Sonja Juliana A1 - Merz, Bruno T1 - Towards seasonal forecasting of flood probabilities in Europe using climate and catchment information JF - Scientific reports N2 - We investigate whether the distribution of maximum seasonal streamflow is significantly affected by catchment or climate state of the season/month ahead. We fit the Generalized Extreme Value (GEV) distribution to extreme seasonal streamflow for around 600 stations across Europe by conditioning the GEV location and scale parameters on 14 indices, which represent the season-ahead climate or catchment state. The comparison of these climate-informed models with the classical GEV distribution, with time-constant parameters, suggests that there is a substantial potential for seasonal forecasting of flood probabilities. The potential varies between seasons and regions. Overall, the season-ahead catchment wetness shows the highest potential, although climate indices based on large-scale atmospheric circulation, sea surface temperature or sea ice concentration also show some skill for certain regions and seasons. Spatially coherent patterns and a substantial fraction of climate-informed models are promising signs towards early alerts to increase flood preparedness already a season ahead. Y1 - 2022 U6 - https://doi.org/10.1038/s41598-022-16633-1 SN - 2045-2322 VL - 12 IS - 1 PB - Nature portfolio CY - Berlin ER - TY - JOUR A1 - Merz, Bruno A1 - Basso, Stefano A1 - Fischer, Svenja A1 - Lun, David A1 - Bloeschl, Guenter A1 - Merz, Ralf A1 - Guse, Bjorn A1 - Viglione, Alberto A1 - Vorogushyn, Sergiy A1 - Macdonald, Elena A1 - Wietzke, Luzie A1 - Schumann, Andreas T1 - Understanding heavy tails of flood peak distributions JF - Water resources research N2 - 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. KW - extreme events KW - flood frequency KW - flood risk KW - upper tail Y1 - 2022 U6 - https://doi.org/10.1029/2021WR030506 SN - 0043-1397 SN - 1944-7973 VL - 58 IS - 6 PB - American Geophysical Union CY - Washington ER - TY - JOUR A1 - Macdonald, Elena A1 - Merz, Bruno A1 - Guse, Björn A1 - Wietzke, Luzie A1 - Ullrich, Sophie A1 - Kemter, Matthias A1 - Ahrens, Bodo A1 - Vorogushyn, Sergiy T1 - Event and catchment controls of heavy tail behavior of floods JF - Water resources research N2 - 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. KW - heavy tail behavior KW - floods KW - event characteristics KW - catchment KW - characteristics KW - catchment response Y1 - 2022 U6 - https://doi.org/10.1029/2021WR031260 SN - 0043-1397 SN - 1944-7973 VL - 58 IS - 6 PB - American Geophysical Union CY - Washington ER - TY - JOUR A1 - Ullrich, Sophie Louise A1 - Hegnauer, Mark A1 - Nguyen, Dung Viet A1 - Merz, Bruno A1 - Kwadijk, Jaap A1 - Vorogushyn, Sergiy T1 - Comparative evaluation of two types of stochastic weather generators for synthetic precipitation in the Rhine basin JF - Journal of hydrology N2 - 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. KW - Rainfall generation KW - Rainfall occurrence KW - Multi-site stochastic weather KW - generator KW - Resampling weather generator KW - Time series analysis Y1 - 2021 U6 - https://doi.org/10.1016/j.jhydrol.2021.126544 SN - 0022-1694 SN - 1879-2707 VL - 601 PB - Elsevier CY - Amsterdam [u.a.] ER - TY - JOUR A1 - Farrag, Mostafa A1 - Brill, Fabio Alexander A1 - Nguyen, Viet Dung A1 - Sairam, Nivedita A1 - Schröter, Kai A1 - Kreibich, Heidi A1 - Merz, Bruno A1 - de Bruijn, Karin M. A1 - Vorogushyn, Sergiy T1 - On the role of floodplain storage and hydrodynamic interactions in flood risk estimation JF - Hydrological sciences journal = Journal des sciences hydrologiques N2 - 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. KW - hydrodynamic interactions KW - derived flood risk analysis KW - flood modelling; KW - Rhine basin Y1 - 2022 U6 - https://doi.org/10.1080/02626667.2022.2030058 SN - 0262-6667 SN - 2150-3435 VL - 67 IS - 4 SP - 508 EP - 534 PB - Routledge, Taylor & Francis Group CY - Abingdon ER - TY - JOUR A1 - Kreibich, Heidi A1 - Hudson, Paul A1 - Merz, Bruno T1 - Knowing what to do substantially improves the effectiveness of flood early warning JF - Bulletin of the American Meteorological Society N2 - Flood warning systems are longstanding success stories with respect to protecting human life, but monetary losses continue to grow. Knowledge on the effectiveness of flood early warning in reducing monetary losses is scarce, especially at the individual level. To gain more knowledge in this area, we analyze a dataset that is unique with respect to detailed information on warning reception and monetary losses at the property level and with respect to amount of data available. The dataset contains 4,468 loss cases from six flood events in Germany. These floods occurred between 2002 and 2013. The data from each event were collected by computer-aided telephone interviews in four surveys following a repeated cross-sectional design. We quantitatively reveal that flood early warning is only effective in reducing monetary losses when people know what to do when they receive the warning. We also show that particularly long-term preparedness is associated with people knowing what to do when they receive a warning. Thus, risk communication, training, and (financial) support for private preparedness are effective in mitigating flood losses in two ways: precautionary measures and more effective emergency responses. KW - adaptation KW - damage assessment KW - emergency preparedness KW - emergency KW - response KW - flood events Y1 - 2021 U6 - https://doi.org/10.1175/BAMS-D-20-0262.1 SN - 0003-0007 SN - 1520-0477 VL - 102 IS - 7 SP - E1450 EP - E1463 PB - American Meteorological Soc. CY - Boston ER - TY - JOUR A1 - Wietzke, Luzie M. A1 - Merz, Bruno A1 - Gerlitz, Lars A1 - Kreibich, Heidi A1 - Guse, Björn A1 - Castellarin, Attilio A1 - Vorogushyn, Sergiy T1 - Comparative analysis of scalar upper tail indicators JF - Hydrological sciences journal = Journal des sciences hydrologiques N2 - 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. KW - upper tail behaviour KW - heavy-tailed distributions KW - extremes KW - diagnostics KW - surprise Y1 - 2020 U6 - https://doi.org/10.1080/02626667.2020.1769104 SN - 0262-6667 SN - 2150-3435 VL - 65 IS - 10 SP - 1625 EP - 1639 PB - Routledge, Taylor & Francis Group CY - Abingdon ER - TY - JOUR A1 - Speckhann, Gustavo Andrei A1 - Kreibich, Heidi A1 - Merz, Bruno T1 - Inventory of dams in Germany JF - Earth system science data : the data publishing journal N2 - Dams are an important element of water resources management. Data about dams are crucial for practitioners, scientists, and policymakers for various purposes, such as seasonal forecasting of water availability or flood mitigation. However, detailed information on dams on the national level for Germany is so far not freely available. We present the most comprehensive open-access dam inventory for Germany (DIG) to date. We have collected and combined information on dams using books, state agency reports, engineering reports, and internet pages. We have applied a priority rule that ensures the highest level of reliability for the dam information. Our dam inventory comprises 530 dams in Germany with information on name, location, river, start year of construction and operation, crest length, dam height, lake area, lake volume, purpose, dam structure, and building characteristics. We have used a global, satellite-based water surface raster to evaluate the location of the dams. A significant proportion (63 %) of dams were built between 1950-2013. Our inventory shows that dams in Germany are mostly single-purpose (52 %), 53% can be used for flood control, and 25% are involved in energy production. The inventory is freely available through GFZ (GeoForschungsZentrum) Data Services (https://doi.org/10.5880/GFZ.4.4.2020.005) Y1 - 2021 U6 - https://doi.org/10.5194/essd-13-731-2021 SN - 1866-3508 SN - 1866-3516 VL - 13 IS - 2 SP - 731 EP - 740 PB - Copernicus CY - Göttingen ER - TY - JOUR A1 - Sairam, Nivedita A1 - Brill, Fabio Alexander A1 - Sieg, Tobias A1 - Farrag, Mostafa A1 - Kellermann, Patric A1 - Viet Dung Nguyen, A1 - Lüdtke, Stefan A1 - Merz, Bruno A1 - Schröter, Kai A1 - Vorogushyn, Sergiy A1 - Kreibich, Heidi T1 - Process-based flood risk assessment for Germany JF - Earth's future / American Geophysical Union N2 - 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. KW - risk model chain KW - continuous simulation KW - expected annual damage KW - risk KW - curves KW - multi-sector risk Y1 - 2021 U6 - https://doi.org/10.1029/2021EF002259 SN - 2328-4277 VL - 9 IS - 10 PB - Wiley-Blackwell CY - Hoboken, NJ ER - TY - JOUR A1 - Ganguli, Poulomi A1 - Paprotny, Dominik A1 - Hasan, Mehedi A1 - Güntner, Andreas A1 - Merz, Bruno T1 - Projected changes in compound flood hazard from riverine and coastal floods in northwestern Europe JF - Earth's future N2 - Compound flooding in coastal regions, that is, the simultaneous or successive occurrence of high sea levels and high river flows, is expected to increase in a warmer world. To date, however, there is no robust evidence on projected changes in compound flooding for northwestern Europe. We combine projected storm surges and river floods with probabilistic, localized relative sea-level rise (SLR) scenarios to assess the future compound flood hazard over northwestern coastal Europe in the high (RCP8.5) emission scenario. We use high-resolution, dynamically downscaled regional climate models (RCM) to drive a storm surge model and a hydrological model, and analyze the joint occurrence of high coastal water levels and associated river peaks in a multivariate copula-based approach. The RCM-forced multimodel mean reasonably represents the observed spatial pattern of the dependence strength between annual maxima surge and peak river discharge, although substantial discrepancies exist between observed and simulated dependence strength. All models overestimate the dependence strength, possibly due to limitations in model parameterizations. This bias affects compound flood hazard estimates and requires further investigation. While our results suggest decreasing compound flood hazard over the majority of sites by 2050s (2040-2069) compared to the reference period (1985-2005), an increase in projected compound flood hazard is limited to around 34% of the sites. Further, we show the substantial role of SLR, a driver of compound floods, which has frequently been neglected. Our findings highlight the need to be aware of the limitations of the current generation of Earth system models in simulating coastal compound floods. KW - compound flood KW - storm surge KW - river floods KW - sea level rise KW - climate KW - change KW - Europe Y1 - 2020 U6 - https://doi.org/10.1029/2020EF001752 SN - 2328-4277 VL - 8 IS - 11 PB - Wiley-Blackwell CY - Hoboken, NJ ER -