TY - JOUR A1 - Nied, Manuela A1 - Schröter, Kai A1 - Lüdtke, Stefan A1 - Nguyen, Viet Dung A1 - Merz, Bruno T1 - What are the hydro-meteorological controls on flood characteristics? JF - Journal of hydrology N2 - Flood events can be expressed by a variety of characteristics such as flood magnitude and extent, event duration or incurred loss. Flood estimation and management may benefit from understanding how the different flood characteristics relate to the hydrological catchment conditions preceding the event and to the meteorological conditions throughout the event. In this study, we therefore propose a methodology to investigate the hydro-meteorological controls on different flood characteristics, based on the simulation of the complete flood risk chain from the flood triggering precipitation event, through runoff generation in the catchment, flood routing and possible inundation in the river system and floodplains to flood loss. Conditional cumulative distribution functions and regression tree analysis delineate the seasonal varying flood processes and indicate that the effect of the hydrological pre-conditions, i.e. soil moisture patterns, and of the meteorological conditions, i.e. weather patterns, depends on the considered flood characteristic. The methodology is exemplified for the Elbe catchment. In this catchment, the length of the build-up period, the event duration and the number of gauges undergoing at least a 10-year flood are governed by weather patterns. The affected length and the number of gauges undergoing at least a 2-year flood are however governed by soil moisture patterns. In case of flood severity and loss, the controlling factor is less pronounced. Severity is slightly governed by soil moisture patterns whereas loss is slightly governed by weather patterns. The study highlights that flood magnitude and extent arise from different flood generation processes and concludes that soil moisture patterns as well as weather patterns are not only beneficial to inform on possible flood occurrence but also on the involved flood processes and resulting flood characteristics. KW - Flood KW - Flood duration KW - Flood magnitude KW - Flood loss KW - Soil moisture patterns KW - Antecedent conditions KW - Weather patterns KW - Large basins Y1 - 2017 U6 - https://doi.org/10.1016/j.jhydrol.2016.12.003 SN - 0022-1694 SN - 1879-2707 VL - 545 SP - 310 EP - 326 PB - Elsevier CY - Amsterdam 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 - 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 - Sieg, Tobias A1 - Vogel, Kristin A1 - Merz, Bruno A1 - Kreibich, Heidi T1 - Tree-based flood damage modeling of companies: Damage processes and model performance JF - Water resources research N2 - Reliable flood risk analyses, including the estimation of damage, are an important prerequisite for efficient risk management. However, not much is known about flood damage processes affecting companies. Thus, we conduct a flood damage assessment of companies in Germany with regard to two aspects. First, we identify relevant damage-influencing variables. Second, we assess the prediction performance of the developed damage models with respect to the gain by using an increasing amount of training data and a sector-specific evaluation of the data. Random forests are trained with data from two postevent surveys after flood events occurring in the years 2002 and 2013. For a sector-specific consideration, the data set is split into four subsets corresponding to the manufacturing, commercial, financial, and service sectors. Further, separate models are derived for three different company assets: buildings, equipment, and goods and stock. Calculated variable importance values reveal different variable sets relevant for the damage estimation, indicating significant differences in the damage process for various company sectors and assets. With an increasing number of data used to build the models, prediction errors decrease. Yet the effect is rather small and seems to saturate for a data set size of several hundred observations. In contrast, the prediction improvement achieved by a sector-specific consideration is more distinct, especially for damage to equipment and goods and stock. Consequently, sector-specific data acquisition and a consideration of sector-specific company characteristics in future flood damage assessments is expected to improve the model performance more than a mere increase in data. Y1 - 2017 U6 - https://doi.org/10.1002/2017WR020784 SN - 0043-1397 SN - 1944-7973 VL - 53 SP - 6050 EP - 6068 PB - American Geophysical Union CY - Washington ER - TY - JOUR A1 - Agarwal, Ankit A1 - Marwan, Norbert A1 - Maheswaran, Rathinasamy A1 - Merz, Bruno A1 - Kurths, Jürgen T1 - Multi-scale event synchronization analysis for unravelling climate processes: a wavelet-based approach JF - Nonlinear processes in geophysics N2 - The temporal dynamics of climate processes are spread across different timescales and, as such, the study of these processes at only one selected timescale might not reveal the complete mechanisms and interactions within and between the (sub-) processes. To capture the non-linear interactions between climatic events, the method of event synchronization has found increasing attention recently. The main drawback with the present estimation of event synchronization is its restriction to analysing the time series at one reference timescale only. The study of event synchronization at multiple scales would be of great interest to comprehend the dynamics of the investigated climate processes. In this paper, the wavelet-based multi-scale event synchronization (MSES) method is proposed by combining the wavelet transform and event synchronization. Wavelets are used extensively to comprehend multi-scale processes and the dynamics of processes across various timescales. The proposed method allows the study of spatio-temporal patterns across different timescales. The method is tested on synthetic and real-world time series in order to check its replicability and applicability. The results indicate that MSES is able to capture relationships that exist between processes at different timescales. Y1 - 2017 U6 - https://doi.org/10.5194/npg-24-599-2017 SN - 1023-5809 VL - 24 SP - 599 EP - 611 PB - Copernicus CY - Göttingen ER -