@phdthesis{Banerjee2022,
  author    = {Banerjee, Abhirup},
  title     = {Characterizing the spatio-temporal patterns of extreme events},
  doi       = {10.25932/publishup-55983},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-559839},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xiv, 91},
  year      = {2022},
  abstract  = {Over the past decades, there has been a growing interest in 'extreme events' owing to the increasing threats that climate-related extremes such as floods, heatwaves, droughts, etc., pose to society. While extreme events have diverse definitions across various disciplines, ranging from earth science to neuroscience, they are characterized mainly as dynamic occurrences within a limited time frame that impedes the normal functioning of a system. Although extreme events are rare in occurrence, it has been found in various hydro-meteorological and physiological time series (e.g., river flows, temperatures, heartbeat intervals) that they may exhibit recurrent behavior, i.e., do not end the lifetime of the system. The aim of this thesis to develop some sophisticated methods to study various properties of extreme events. One of the main challenges in analyzing such extreme event-like time series is that they have large temporal gaps due to the paucity of the number of observations of extreme events. As a result, existing time series analysis tools are usually not helpful to decode the underlying information. I use the edit distance (ED) method to analyze extreme event-like time series in their unaltered form. ED is a specific distance metric, mainly designed to measure the similarity/dissimilarity between point process-like data. I combine ED with recurrence plot techniques to identify the recurrence property of flood events in the Mississippi River in the United States. I also use recurrence quantification analysis to show the deterministic properties and serial dependency in flood events. After that, I use this non-linear similarity measure (ED) to compute the pairwise dependency in extreme precipitation event series. I incorporate the similarity measure within the framework of complex network theory to study the collective behavior of climate extremes. Under this architecture, the nodes are defined by the spatial grid points of the given spatio-temporal climate dataset. Each node is associated with a time series corresponding to the temporal evolution of the climate observation at that grid point. Finally, the network links are functions of the pairwise statistical interdependence between the nodes. Various network measures, such as degree, betweenness centrality, clustering coefficient, etc., can be used to quantify the network's topology. We apply the methodology mentioned above to study the spatio-temporal coherence pattern of extreme rainfall events in the United States and the Ganga River basin, which reveals its relation to various climate processes and the orography of the region. The identification of precursors associated with the occurrence of extreme events in the near future is extremely important to prepare the masses for an upcoming disaster and mitigate the potential risks associated with such events. Under this motivation, I propose an in-data prediction recipe for predicting the data structures that typically occur prior to extreme events using the Echo state network, a type of Recurrent Neural Network which is a part of the reservoir computing framework. However, unlike previous works that identify precursory structures in the same variable in which extreme events are manifested (active variable), I try to predict these structures by using data from another dynamic variable (passive variable) which does not show large excursions from the nominal condition but carries imprints of these extreme events. Furthermore, my results demonstrate that the quality of prediction depends on the magnitude of events, i.e., the higher the magnitude of the extreme, the better is its predictability skill. I show quantitatively that this is because the input signals collectively form a more coherent pattern for an extreme event of higher magnitude, which enhances the efficiency of the machine to predict the forthcoming extreme events.},
  language  = {en}
}
@phdthesis{Laudan2019,
  author    = {Laudan, Jonas},
  title     = {Changing susceptibility of flood-prone residents in Germany},
  doi       = {10.25932/publishup-43442},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-434421},
  school      = {Universit{\"a}t Potsdam},
  pages     = {113},
  year      = {2019},
  abstract  = {Floods are among the most costly natural hazards that affect Europe and Germany, demanding a continuous adaptation of flood risk management. While social and economic development in recent years altered the flood risk patterns mainly with regard to an increase in flood exposure, different flood events are further expected to increase in frequency and severity in certain European regions due to climate change. As a result of recent major flood events in Germany, the German flood risk management shifted to more integrated approaches that include private precaution and preparation to reduce the damage on exposed assets. Yet, detailed insights into the preparedness decisions of flood-prone households remain scarce, especially in connection to mental impacts and individual coping strategies after being affected by different flood types. This thesis aims to gain insights into flash floods as a costly hazard in certain German regions and compares the damage driving factors to the damage driving factors of river floods. Furthermore, psychological impacts as well as the effects on coping and mitigation behaviour of flood-affected households are assessed. In this context, psychological models such as the Protection Motivation Theory (PMT) and methods such as regressions and Bayesian statistics are used to evaluate influencing factors on the mental coping after an event and to identify psychological variables that are connected to intended private flood mitigation. The database consists of surveys that were conducted among affected households after major river floods in 2013 and flash floods in 2016. The main conclusions that can be drawn from this thesis reveal that the damage patterns and damage driving factors of strong flash floods differ significantly from those of river floods due to a rapid flow origination process, higher flow velocities and flow forces. However, the effects on mental coping of people that have been affected by flood events appear to be weakly influenced by different flood types, but yet show a coherence to the event severity, where often thinking of the respective event is pronounced and also connected to a higher mitigation motivation. The mental coping and preparation after floods is further influenced by a good information provision and a social environment, which encourages a positive attitude towards private mitigation. As an overall recommendation, approaches for an integrated flood risk management in Germany should be followed that also take flash floods into account and consider psychological characteristics of affected households to support and promote private flood mitigation. Targeted information campaigns that concern coping options and discuss current flood risks are important to better prepare for future flood hazards in Germany.},
  language  = {en}
}
@phdthesis{Nied2016,
  author    = {Nied, Manuela},
  title     = {The role of soil moisture and weather patterns for flood occurrence and characteristics at the river basin scale},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-94612},
  school      = {Universit{\"a}t Potsdam},
  pages     = {XVI, 86},
  year      = {2016},
  abstract  = {Flood generation at the scale of large river basins is triggered by the interaction of the hydrological pre-conditions and the meteorological event conditions at different spatial and temporal scales. This interaction controls diverse flood generating processes and results in floods varying in magnitude and extent, duration as well as socio-economic consequences. For a process-based understanding of the underlying cause-effect relationships, systematic approaches are required. These approaches have to cover the complete causal flood chain, including the flood triggering meteorological event in combination with the hydrological (pre-)conditions in the catchment, runoff generation, flood routing, possible floodplain inundation and finally flood losses. In this thesis, a comprehensive probabilistic process-based understanding of the causes and effects of floods is advanced. The spatial and temporal dynamics of flood events as well as the geophysical processes involved in the causal flood chain are revealed and the systematic interconnections within the flood chain are deciphered by means of the classification of their associated causes and effects. This is achieved by investigating the role of the hydrological pre-conditions and the meteorological event conditions with respect to flood occurrence, flood processes and flood characteristics as well as their interconnections at the river basin scale. Broadening the knowledge about flood triggers, which up to now has been limited to linking large-scale meteorological conditions to flood occurrence, the influence of large-scale pre-event hydrological conditions on flood initiation is investigated. Using the Elbe River basin as an example, a classification of soil moisture, a key variable of pre-event conditions, is developed and a probabilistic link between patterns of soil moisture and flood occurrence is established. The soil moisture classification is applied to continuously simulated soil moisture data which is generated using the semi-distributed conceptual rainfall-runoff model SWIM. Applying successively a principal component analysis and a cluster analysis, days of similar soil moisture patterns are identified in the period November 1951 to October 2003. The investigation of flood triggers is complemented by including meteorological conditions described by a common weather pattern classification that represents the main modes of atmospheric state variability. The newly developed soil moisture classification thereby provides the basis to study the combined impact of hydrological pre-conditions and large-scale meteorological event conditions on flood occurrence at the river basin scale. A process-based understanding of flood generation and its associated probabilities is attained by classifying observed flood events into process-based flood types such as snowmelt floods or long-rain floods. Subsequently, the flood types are linked to the soil moisture and weather patterns. Further understanding of the processes is gained by modeling of the complete causal flood chain, incorporating a rainfall-runoff model, a 1D/2D hydrodynamic model and a flood loss model. A reshuffling approach based on weather patterns and the month of their occurrence is developed to generate synthetic data fields of meteorological conditions, which drive the model chain, in order to increase the flood sample size. From the large number of simulated flood events, the impact of hydro-meteorological conditions on various flood characteristics is detected through the analysis of conditional cumulative distribution functions and regression trees. The results show the existence of catchment-scale soil moisture patterns, which comprise of large-scale seasonal wetting and drying components as well as of smaller-scale variations related to spatially heterogeneous catchment processes. Soil moisture patterns frequently occurring before the onset of floods are identified. In winter, floods are initiated by catchment-wide high soil moisture, whereas in summer the flood-initiating soil moisture patterns are diverse and the soil moisture conditions are less stable in time. The combined study of both soil moisture and weather patterns shows that the flood favoring hydro-meteorological patterns as well as their interactions vary seasonally. In the analysis period, 18 \% of the weather patterns only result in a flood in the case of preceding soil saturation. The classification of 82 past events into flood types reveals seasonally varying flood processes that can be linked to hydro-meteorological patterns. For instance, the highest flood potential for long-rain floods is associated with a weather pattern that is often detected in the presence of so-called 'Vb' cyclones. Rain-on-snow and snowmelt floods are associated with westerly and north-westerly wind directions. The flood characteristics vary among the flood types and can be reproduced by the applied model chain. In total, 5970 events are simulated. They reproduce the observed event characteristics between September 1957 and August 2002 and provide information on flood losses. A regression tree analysis relates the flood processes of the simulated events to the hydro-meteorological (pre-)event conditions and highlights the fact that flood magnitude is primarily controlled by the meteorological event, whereas flood extent is primarily controlled by the soil moisture conditions. Describing flood occurrence, processes and characteristics as a function of hydro-meteorological patterns, this thesis is part of a paradigm shift towards a process-based understanding of floods. The results highlight that soil moisture patterns as well as weather patterns are not only beneficial to a probabilistic conception of flood initiation but also provide information on the involved flood processes and the resulting flood characteristics.},
  language  = {en}
}
@phdthesis{Schlolaut2013,
  author    = {Schlolaut, Gordon},
  title     = {Varve and event layer chronology of Lake Suigetsu (Japan) back to 40 kyr BP and contribution to the international consensus atmospheric radiocarbon calibration curve},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-69096},
  school      = {Universit{\"a}t Potsdam},
  year      = {2013},
  abstract  = {The main intention of the PhD project was to create a varve chronology for the Suigetsu Varves 2006' (SG06) composite profile from Lake Suigetsu (Japan) by thin section microscopy. The chronology was not only to provide an age-scale for the various palaeo-environmental proxies analysed within the SG06 project, but also and foremost to contribute, in combination with the SG06 14C chronology, to the international atmospheric radiocarbon calibration curve (IntCal). The SG06 14C data are based on terrestrial leaf fossils and therefore record atmospheric 14C values directly, avoiding the corrections necessary for the reservoir ages of the marine datasets, which are currently used beyond the tree-ring limit in the IntCal09 dataset (Reimer et al., 2009). The SG06 project is a follow up of the SG93 project (Kitagawa \& van der Plicht, 2000), which aimed to produce an atmospheric calibration dataset, too, but suffered from incomplete core recovery and varve count uncertainties. For the SG06 project the complete Lake Suigetsu sediment sequence was recovered continuously, leaving the task to produce an improved varve count. Varve counting was carried out using a dual method approach utilizing thin section microscopy and micro X-Ray Fluorescence (µXRF). The latter was carried out by Dr. Michael Marshall in cooperation with the PhD candidate. The varve count covers 19 m of composite core, which corresponds to the time frame from ≈10 to ≈40 kyr BP. The count result showed that seasonal layers did not form in every year. Hence, the varve counts from either method were incomplete. This rather common problem in varve counting is usually solved by manual varve interpolation. But manual interpolation often suffers from subjectivity. Furthermore, sedimentation rate estimates (which are the basis for interpolation) are generally derived from neighbouring, well varved intervals. This assumes that the sedimentation rates in neighbouring intervals are identical to those in the incompletely varved section, which is not necessarily true. To overcome these problems a novel interpolation method was devised. It is computer based and automated (i.e. avoids subjectivity and ensures reproducibility) and derives the sedimentation rate estimate directly from the incompletely varved interval by statistically analysing distances between successive seasonal layers. Therefore, the interpolation approach is also suitable for sediments which do not contain well varved intervals. Another benefit of the novel method is that it provides objective interpolation error estimates. Interpolation results from the two counting methods were combined and the resulting chronology compared to the 14C chronology from Lake Suigetsu, calibrated with the tree-ring derived section of IntCal09 (which is considered accurate). The varve and 14C chronology showed a high degree of similarity, demonstrating that the novel interpolation method produces reliable results. In order to constrain the uncertainties of the varve chronology, especially the cumulative error estimates, U-Th dated speleothem data were used by linking the low frequency 14C signal of Lake Suigetsu and the speleothems, increasing the accuracy and precision of the Suigetsu calibration dataset. The resulting chronology also represents the age-scale for the various palaeo-environmental proxies analysed in the SG06 project. One proxy analysed within the PhD project was the distribution of event layers, which are often representatives of past floods or earthquakes. A detailed microfacies analysis revealed three different types of event layers, two of which are described here for the first time for the Suigetsu sediment. The types are: matrix supported layers produced as result of subaqueous slope failures, turbidites produced as result of landslides and turbidites produced as result of flood events. The former two are likely to have been triggered by earthquakes. The vast majority of event layers was related to floods (362 out of 369), which allowed the construction of a respective chronology for the last 40 kyr. Flood frequencies were highly variable, reaching their greatest values during the global sea level low-stand of the Glacial, their lowest values during Heinrich Event 1. Typhoons affecting the region represent the most likely control on the flood frequency, especially during the Glacial. However, also local, non-climatic controls are suggested by the data. In summary, the work presented here expands and revises knowledge on the Lake Suigetsu sediment and enabls the construction of a far more precise varve chronology. The 14C calibration dataset is the first such derived from lacustrine sediments to be included into the (next) IntCal dataset. References: Kitagawa \& van der Plicht, 2000, Radiocarbon, Vol 42(3), 370-381 Reimer et al., 2009, Radiocarbon, Vol 51(4), 1111-1150},
  language  = {en}
}
@phdthesis{Uhlemann2013,
  author    = {Uhlemann, Steffi},
  title     = {Understanding trans-basin floods in Germany : data, information and knowledge},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-68868},
  school      = {Universit{\"a}t Potsdam},
  year      = {2013},
  abstract  = {Large Central European flood events of the past have demonstrated that flooding can affect several river basins at the same time leading to catastrophic economic and humanitarian losses that can stretch emergency resources beyond planned levels of service. For Germany, the spatial coherence of flooding, the contributing processes and the role of trans-basin floods for a national risk assessment is largely unknown and analysis is limited by a lack of systematic data, information and knowledge on past events. This study investigates the frequency and intensity of trans-basin flood events in Germany. It evaluates the data and information basis on which knowledge about trans-basin floods can be generated in order to improve any future flood risk assessment. In particu-lar, the study assesses whether flood documentations and related reports can provide a valuable data source for understanding trans-basin floods. An adaptive algorithm was developed that systematically captures trans-basin floods using series of mean daily discharge at a large number of sites of even time series length (1952-2002). It identifies the simultaneous occurrence of flood peaks based on the exceedance of an initial threshold of a 10 year flood at one location and consecutively pools all causally related, spatially and temporally lagged peak recordings at the other locations. A weighted cumulative index was developed that accounts for the spatial extent and the individual flood magnitudes within an event and allows quantifying the overall event severity. The parameters of the method were tested in a sensitivity analysis. An intensive study on sources and ways of information dissemination of flood-relevant publications in Germany was conducted. Based on the method of systematic reviews a strategic search approach was developed to identify relevant documentations for each of the 40 strongest trans-basin flood events. A novel framework for assessing the quality of event specific flood reports from a user's perspective was developed and validated by independent peers. The framework was designed to be generally applicable for any natural hazard type and assesses the quality of a document addressing accessibility as well as representational, contextual, and intrinsic dimensions of quality. The analysis of time-series of mean daily discharge resulted in the identification of 80 trans-basin flood events within the period 1952-2002 in Germany. The set is dominated by events that were recorded in the hydrological winter (64\%); 36\% occurred during the summer months. The occurrence of floods is characterised by a distinct clustering in time. Dividing the study period into two sub-periods, we find an increase in the percentage of winter events from 58\% in the first to 70.5\% in the second sub-period. Accordingly, we find a significant increase in the number of extreme trans-basin floods in the second sub-period. A large body of 186 flood relevant documentations was identified. For 87.5\% of the 40 strongest trans-basin floods in Germany at least one report has been found and for the most severe floods a substantial amount of documentation could be obtained. 80\% of the material can be considered grey literature (i.e. literature not controlled by commercial publishers). The results of the quality assessment show that the majority of flood event specific reports are of a good quality, i.e. they are well enough drafted, largely accurate and objective, and contain a substantial amount of information on the sources, pathways and receptors/consequences of the floods. The inclusion of this information in the process of knowledge building for flood risk assessment is recommended. Both the results as well as the data produced in this study are openly accessible and can be used for further research. The results of this study contribute to an improved spatial risk assessment in Germany. The identified set of trans-basin floods provides the basis for an assessment of the chance that flooding occurs simultaneously at a number of sites. The information obtained from flood event documentation can usefully supplement the analysis of the processes that govern flood risk.},
  language  = {en}
}
@phdthesis{Petrow2009,
  author    = {Petrow, Theresia},
  title     = {Floods in Germany : analyses of trends, seasonality and circulation patterns},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-37392},
  school      = {Universit{\"a}t Potsdam},
  year      = {2009},
  abstract  = {Flood hazard estimations are conducted with a variety of methods. These include flood frequency analysis (FFA), hydrologic and hydraulic modelling, probable maximum discharges as well as climate scenarios. However, most of these methods assume stationarity of the used time series, i.e., the series must not exhibit trends. Against the background of climate change and proven significant trends in atmospheric circulation patterns, it is questionable whether these changes are also reflected in the discharge data. The aim of this PhD thesis is therefore to clarify, in a spatially-explicit manner, whether the available discharge data derived from selected German catchments exhibit trends. Concerning the flood hazard, the suitability of the currently used stationary FFA approaches is evaluated for the discharge data. Moreover, dynamics in atmospheric circulation patterns are studied and the link between trends in these patterns and discharges is investigated. To tackle this research topic, a number of different analyses are conducted. The first part of the PhD thesis comprises the study and trend test of 145 discharge series from catchments, which cover most of Germany for the period 1951-2002. The seasonality and trend pattern of eight flood indicators, such as maximum series and peak-over-threshold series, are analyzed in a spatially-explicit manner. Analyses are performed on different spatial scales: at the local scale, through gauge-specific analyses, and on the catchment-wide and basin scales. Besides the analysis of discharge series, data on atmospheric circulation patterns (CP) are an important source of information, upon which conclusions about the flood hazard can be drawn. The analyses of these circulation patterns (after Hess und Brezowsky) and the study of the link to peak discharges form the second part of the thesis. For this, daily data on the dominant CP across Europe are studied; these are represented by different indicators, which are tested for trend. Moreover, analyses are performed to extract flood triggering circulation patterns and to estimate the flood potential of CPs. Correlations between discharge series and CP indicators are calculated to assess a possible link between them. For this research topic, data from 122 meso-scale catchments in the period 1951-2002 are used. In a third part, the Mulde catchment, a mesoscale sub-catchment of the Elbe basin, is studied in more detail. Fifteen discharge series of different lengths in the period 1910-2002 are available for the seasonally differentiated analysis of the flood potential of CPs and flood influencing landscape parameters. For trend tests of discharge and CP data, different methods are used. The Mann-Kendall test is applied with a significance level of 10\%, ensuring statistically sound results. Besides the test of the entire series for trend, multiple time-varying trend tests are performed with the help of a resampling approach in order to better differentiate short-term fluctuations from long-lasting trends. Calculations of the field significance complement the flood hazard assessment for the studied regions. The present thesis shows that the flood hazard is indeed significantly increasing for selected regions in Germany during the winter season. Especially affected are the middle mountain ranges in Central Germany. This increase of the flood hazard is attributed to a longer persistence of selected CPs during winter. Increasing trends in summer floods are found in the Rhine and Danube catchments, decreasing trends in the Elbe and Weser catchments. Finally, a significant trend towards a reduced diversity of CPs is found causing fewer patterns with longer persistence to dominate the weather over Europe. The detailed study of the Mulde catchment reveals a flood regime with frequent low winter floods and fewer summer floods, which bear, however, the potential of becoming extreme. Based on the results, the use of instationary approaches for flood hazard estimation is recommended in order to account for the detected trends in many of the series. Through this methodology it is possible to directly consider temporal changes in flood series, which in turn reduces the possibility of large under- or overestimations of the extreme discharges, respectively.},
  language  = {en}
}