TY  - JOUR
A1  - Vorogushyn, Sergiy
A1  - Apel, Heiko
A1  - Kemter, Matthias
A1  - Thieken, Annegret
T1  - Analyse der Hochwassergefährdung im Ahrtal unter Berücksichtigung historischer Hochwasser
T1  - Analysis of flood hazard in the Ahr Valley considering historical floods
JF  - Hydrologie und Wasserbewirtschaftung
N2  - The flood disaster in July 2021 in western Germany calls for a critical discussion on flood hazard assessment, revision of flood hazard maps and communication of extreme flood scenarios. In the presented work, extreme value analysis was carried out for annual maximum peak flow series at the Altenahr gauge on the river Ahr. We compared flood statistics with and without considering historical flood events. An estimate for the return period of the recent flood based on the Generalized Extreme Value (GEV) distribution considering historical floods ranges between about 2600 and above 58700 years (90% confidence interval) with a median of approximately 8600 years, whereas an estimate based on the 74-year long systematically recorded flow series would theoretically exceed 100 million years. Consideration of historical floods dramatically changes the flood quantiles that are used for the generation of official flood hazard maps. The fitting of the GEV to the time series with historical floods reveals, however, that the model potentially inadequately reflects the flood population. In this case, we might face a mixed sample, in which extreme floods result from very different processes compared to smaller floods. Hence, the probabilities of extreme floods could be much larger than those resulting from a single GEV model. The application of a process-based mixed flood distribution should be explored in future work. <br /> The comparison of the official HQextrem flood maps for the AhrValley with the inundation areas from July 2021 shows a striking discrepancy in the affected areas and calls for revision of design values used to define extreme flood scenarios. The hydrodynamic simulations of a 1000-year return period flood considering historical events and of the 1804 flood scenario compare much better to the flooded areas from July 2021, though both scenarios still underestimated the flood extent. <br /> Particular effects such as clogging of bridges and geomorphological changes of the river channel led to considerably larger flooded areas in July 2021 compared to the simulation results. Based on this analysis, we call for a consistent definition of HQextrem for flood hazard mapping in Germany, and suggest using high flood quantiles in the range of a 1,000-year flood. Flood maps should additionally include model-based reconstructions of the largest, reliably documented historical floods and/or synthetic worst-case scenarios. This would be an important step towards protecting potentially affected population and disaster management from surprises due to very rare and extreme flood events in future.
N2  - Die Hochwasserkatastrophe im Juli 2021 in Westdeutschland erfordert eine kritische Diskussion über die Abschätzung der Hochwassergefährdung, Aktualisierung von Hochwassergefahrenkarten und Kommunikation von extremen Hochwasserszenarien. In der vorliegenden Arbeit wurde die Extremwertstatistik für die jährlichen maximalen Spitzenabflüsse am Pegel Altenahr im Ahrtal mit und ohne Berücksichtigung historischer Hochwasser berechnet und verglichen. Die Schätzung der Wiederkehrperiode für das aktuelle Hochwasser mittels Generalisierter Extremwertverteilung (GEV) unter Berücksichtigung historischer Hochwasser schwankt zwischen etwa 2.600 und über 58.700 Jahren (90%-Konfidenzintervall) mit einem Median bei etwa 8.600 Jahren, wogegen die Schätzung, die nur auf der systematisch gemessenen Abflusszeitreihe von 74 Jahren basiert, theoretisch eine Wiederkehrperiode von über 100 Millionen Jahren ergeben würde. Die Berücksichtigung der historischen Hochwasser führt zu einer dramatischen Änderung der Hochwasserquan-
tile, die für eine Gefahrenkartierung zugrunde gelegt werden. Die Anpassung der GEV an die Zeitreihe mit historischen Hochwassern zeigt dennoch, dass das GEV-Modell möglicherweise die Grundgesamtheit der Hochwasser im Ahrtal nicht adäquat abbilden kann. Es könnte sich im vorliegenden Fall um eine gemischte Stichprobe handeln, in der die extremen Hochwasser im Vergleich zu kleineren Ereignissen durch besondere Prozesse hervorgerufen werden. Somit könnten die Wahrscheinlichkeiten von extremen Hochwassern deutlich größer sein, als aus dem GEV-Modell hervorgeht. Hier sollte in Zukunft die Anwendung einer prozessbasierten Mischverteilung
untersucht werden. Der Vergleich von amtlichen Gefahrenkarten zu Extremhochwassern (HQextrem) im Ahrtal mit den Überflutungsflächen vom Juli 2021
zeigt eine deutliche Diskrepanz in den betroffenen Gebieten und die Notwendigkeit, die Grundlagen zur Erstellung der Extremszenarien zu überdenken. Die hydrodynamisch-numerischen Simulationen von 1.000-jährlichen Hochwassern (HQ1000) unter Berücksichtigung historischer Ereignisse und des größten historischen Hochwassers 1804 können die Gefährdung des Juli-Hochwassers 2021 deutlich besser widerspiegeln, wenngleich auch diese beiden Szenarien die Überflutungsflächen unterschätzen. Besondere Effekte wie die Verklausung von Brücken und die geomorphologischen Änderungen im Flussschlauch führten zu noch größeren Überflutungs- flächen im Juli 2021, als die Simulationsergebnisse zeigten. Basierend auf dieser Analyse wird eine einheitliche Festlegung von HQextrem bei Hochwassergefahrenkartierungen in Deutschland vorgeschlagen, die sich an höheren Hochwasserquantilen im Bereich von HQ1000 orientiert. Zusätzlich sollen simulationsbasierte Rekonstruktionen von den größten verlässlich dokumentierten historischen Hochwassern und/oder synthetische Worst-Case-Szenarien in den Hochwassergefahrenkarten gesondert dargestellt werden. Damit wird ein wichtiger Beitrag geleistet, um die potenziell betroffene Bevölkerung und das Katastrophenmanagement vor Überraschungen durch sehr seltene und extreme Hochwasser in Zukunft besser zu schützen.
KW  - Extreme value statistics
KW  - historical floods
KW  - flood hazard mapping;
KW  - inundation simulation
KW  - Ahr River
KW  - Extremwertstatistik
KW  - historische Hochwasser
KW  - Gefahrenkarten
KW  - Überflutungssimulation
KW  - Ahr
Y1  - 2022
U6  - https://doi.org/10.5675/HyWa_2022.5_2
SN  - 1439-1783
VL  - 66
IS  - 5
SP  - 244
EP  - 254
PB  - Bundesanst. für Gewässerkunde
CY  - Koblenz
ER  - 
TY  - JOUR
A1  - Seibert, Mathias
A1  - Merz, Bruno
A1  - Apel, Heiko
T1  - Seasonal forecasting of hydrological drought in the Limpopo Basin
BT  - a comparison of statistical methods
JF  - Hydrology and earth system sciences : HESS
N2  - The Limpopo Basin in southern Africa is prone to droughts which affect the livelihood of millions of people in South Africa, Botswana, Zimbabwe and Mozambique. Seasonal drought early warning is thus vital for the whole region. In this study, the predictability of hydrological droughts during the main runoff period from December to May is assessed using statistical approaches. Three methods (multiple linear models, artificial neural networks, random forest regression trees) are compared in terms of their ability to forecast streamflow with up to 12 months of lead time. The following four main findings result from the study. 1. There are stations in the basin at which standardised streamflow is predictable with lead times up to 12 months. The results show high inter-station differences of forecast skill but reach a coefficient of determination as high as 0.73 (cross validated). 2. A large range of potential predictors is considered in this study, comprising well-established climate indices, customised teleconnection indices derived from sea surface temperatures and antecedent streamflow as a proxy of catchment conditions. El Nino and customised indices, representing sea surface temperature in the Atlantic and Indian oceans, prove to be important teleconnection predictors for the region. Antecedent streamflow is a strong predictor in small catchments (with median 42% explained variance), whereas teleconnections exert a stronger influence in large catchments. 3. Multiple linear models show the best forecast skill in this study and the greatest robustness compared to artificial neural networks and random forest regression trees, despite their capabilities to represent nonlinear relationships. 4. Employed in early warning, the models can be used to forecast a specific drought level. Even if the coefficient of determination is low, the forecast models have a skill better than a climatological forecast, which is shown by analysis of receiver operating characteristics (ROCs). Seasonal statistical forecasts in the Limpopo show promising results, and thus it is recommended to employ them as complementary to existing forecasts in order to strengthen preparedness for droughts.
Y1  - 2017
U6  - https://doi.org/10.5194/hess-21-1611-2017
SN  - 1027-5606
SN  - 1607-7938
VL  - 21
SP  - 1611
EP  - 1629
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  - 
TY  - JOUR
A1  - Duy, Nguyen Le
A1  - Heidbüchel, Ingo
A1  - Meyer, Hanno
A1  - Merz, Bruno
A1  - Apel, Heiko
T1  - What controls the stable isotope composition of precipitation in the Mekong Delta?
BT  - a model-based statistical approach
JF  - Hydrology and earth system sciences : HESS
N2  - This study analyzes the influence of local and regional climatic factors on the stable isotopic composition of rainfall in the Vietnamese Mekong Delta (VMD) as part of the Asian monsoon region. It is based on 1.5 years of weekly rainfall samples. In the first step, the isotopic composition of the samples is analyzed by local meteoric water lines (LMWLs) and single-factor linear correlations. Additionally, the contribution of several regional and local factors is quantified by multiple linear regression (MLR) of all possible factor combinations and by relative importance analysis. This approach is novel for the interpretation of isotopic records and enables an objective quantification of the explained variance in isotopic records for individual factors. In this study, the local factors are extracted from local climate records, while the regional factors are derived from atmospheric backward trajectories of water particles. The regional factors, i.e., precipitation, temperature, relative humidity and the length of backward trajectories, are combined with equivalent local climatic parameters to explain the response variables delta O-18, delta H-2, and d-excess of precipitation at the station of measurement. The results indicate that (i) MLR can better explain the isotopic variation in precipitation (R-2 = 0.8) compared to single-factor linear regression (R-2 = 0.3); (ii) the isotopic variation in precipitation is controlled dominantly by regional moisture regimes (similar to 70 %) compared to local climatic conditions (similar to 30 %); (iii) the most important climatic parameter during the rainy season is the precipitation amount along the trajectories of air mass movement; (iv) the influence of local precipitation amount and temperature is not sig-nificant during the rainy season, unlike the regional precipitation amount effect; (v) secondary fractionation processes (e.g., sub-cloud evaporation) can be identified through the d-excess and take place mainly in the dry season, either locally for delta O-18 and delta H-2, or along the air mass trajectories for d-excess. The analysis shows that regional and local factors vary in importance over the seasons and that the source regions and transport pathways, and particularly the climatic conditions along the pathways, have a large influence on the isotopic composition of rainfall. Although the general results have been reported qualitatively in previous studies (proving the validity of the approach), the proposed method provides quantitative estimates of the controlling factors, both for the whole data set and for distinct seasons. Therefore, it is argued that the approach constitutes an advancement in the statistical analysis of isotopic records in rainfall that can supplement or precede more complex studies utilizing atmospheric models. Due to its relative simplicity, the method can be easily transferred to other regions, or extended with other factors. The results illustrate that the interpretation of the isotopic composition of precipitation as a recorder of local climatic conditions, as for example performed for paleorecords of water isotopes, may not be adequate in the southern part of the Indochinese Peninsula, and likely neither in other regions affected by monsoon processes. However, the presented approach could open a pathway towards better and seasonally differentiated reconstruction of paleoclimates based on isotopic records.
Y1  - 2018
U6  - https://doi.org/10.5194/hess-22-1239-2018
SN  - 1027-5606
SN  - 1607-7938
VL  - 22
IS  - 2
SP  - 1239
EP  - 1262
PB  - Copernicus
CY  - Göttingen
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  - Kreibich, Heidi
A1  - Di Baldassarre, Giuliano
A1  - Vorogushyn, Sergiy
A1  - Aerts, Jeroen C. J. H.
A1  - Apel, Heiko
A1  - Aronica, Giuseppe T.
A1  - Arnbjerg-Nielsen, Karsten
A1  - Bouwer, Laurens M.
A1  - Bubeck, Philip
A1  - Caloiero, Tommaso
A1  - Chinh, Do T.
A1  - Cortes, Maria
A1  - Gain, Animesh K.
A1  - Giampa, Vincenzo
A1  - Kuhlicke, Christian
A1  - Kundzewicz, Zbigniew W.
A1  - Llasat, Maria Carmen
A1  - Mard, Johanna
A1  - Matczak, Piotr
A1  - Mazzoleni, Maurizio
A1  - Molinari, Daniela
A1  - Dung, Nguyen V.
A1  - Petrucci, Olga
A1  - Schröter, Kai
A1  - Slager, Kymo
A1  - Thieken, Annegret
A1  - Ward, Philip J.
A1  - Merz, Bruno
T1  - Adaptation to flood risk
BT  - Results of international paired flood event studies
JF  - Earth's Future
N2  - 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.
KW  - flooding
KW  - vulnerability
KW  - global environmental change
KW  - adaptation
Y1  - 2017
U6  - https://doi.org/10.1002/2017EF000606
SN  - 2328-4277
VL  - 5
SP  - 953
EP  - 965
PB  - Wiley
CY  - Hoboken
ER  - 
TY  - JOUR
A1  - Triet, Nguyen Van Khanh
A1  - Dung, Nguyen Viet
A1  - Merz, Bruno
A1  - Apel, Heiko
T1  - Towards risk-based flood management in highly productive paddy rice cultivation
BT  - concept development and application to the Mekong Delta
JF  - Natural hazards and earth system sciences
N2  - Flooding is an imminent natural hazard threatening most river deltas, e.g. the Mekong Delta. An appropriate flood management is thus required for a sustainable development of the often densely populated regions. Recently, the traditional event-based hazard control shifted towards a risk management approach in many regions, driven by intensive research leading to new legal regulation on flood management. However, a large-scale flood risk assessment does not exist for the Mekong Delta. Particularly, flood risk to paddy rice cultivation, the most important economic activity in the delta, has not been performed yet. Therefore, the present study was developed to provide the very first insight into delta-scale flood damages and risks to rice cultivation. The flood hazard was quantified by probabilistic flood hazard maps of the whole delta using a bivariate extreme value statistics, synthetic flood hydrographs, and a large-scale hydraulic model. The flood risk to paddy rice was then quantified considering cropping calendars, rice phenology, and harvest times based on a time series of enhanced vegetation index (EVI) derived from MODIS satellite data, and a published rice flood damage function. The proposed concept provided flood risk maps to paddy rice for the Mekong Delta in terms of expected annual damage. The presented concept can be used as a blueprint for regions facing similar problems due to its generic approach. Furthermore, the changes in flood risk to paddy rice caused by changes in land use currently under discussion in the Mekong Delta were estimated. Two land-use scenarios either intensifying or reducing rice cropping were considered, and the changes in risk were presented in spatially explicit flood risk maps. The basic risk maps could serve as guidance for the authorities to develop spatially explicit flood management and mitigation plans for the delta. The land-use change risk maps could further be used for adaptive risk management plans and as a basis for a cost-benefit of the discussed land-use change scenarios. Additionally, the damage and risks maps may support the recently initiated agricultural insurance programme in Vietnam.
Y1  - 2018
U6  - https://doi.org/10.5194/nhess-18-2859-2018
SN  - 1561-8633
VL  - 18
IS  - 11
SP  - 2859
EP  - 2876
PB  - Copernicus
CY  - Göttingen
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  - Steirou, Eva
A1  - Gerlitz, Lars
A1  - Apel, Heiko
A1  - Sun, Xun
A1  - Merz, Bruno
T1  - Climate influences on flood probabilities across Europe
JF  - Hydrology and earth system sciences : HESS
N2  - The link between streamflow extremes and climatology has been widely studied in recent decades. However, a study investigating the effect of large-scale circulation variations on the distribution of seasonal discharge extremes at the European level is missing. Here we fit a climate-informed generalized extreme value (GEV) distribution to about 600 streamflow records in Europe for each of the standard seasons, i.e., to winter, spring, summer and autumn maxima, and compare it with the classical GEV distribution with parameters invariant in time. The study adopts a Bayesian framework and covers the period 1950 to 2016. Five indices with proven influence on the European climate are examined independently as covariates, namely the North Atlantic Oscillation (NAO), the east Atlantic pattern (EA), the east Atlantic-western Russian pattern (EA/WR), the Scandinavia pattern (SCA) and the polar-Eurasian pattern (POL). It is found that for a high percentage of stations the climate-informed model is preferred to the classical model. Particularly for NAO during winter, a strong influence on streamflow extremes is detected for large parts of Europe (preferred to the classical GEV distribution for 46% of the stations). Climate-informed fits are characterized by spatial coherence and form patterns that resemble relations between the climate indices and seasonal precipitation, suggesting a prominent role of the considered circulation modes for flood generation. For certain regions, such as northwestern Scandinavia and the British Isles, yearly variations of the mean seasonal climate indices result in considerably different extreme value distributions and thus in highly different flood estimates for individual years that can also persist for longer time periods.
Y1  - 2019
U6  - https://doi.org/10.5194/hess-23-1305-2019
SN  - 1027-5606
SN  - 1607-7938
VL  - 23
IS  - 3
SP  - 1305
EP  - 1322
PB  - 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  -