@phdthesis{Roezer2018,
  author    = {R{\"o}zer, Viktor},
  title     = {Pluvial flood loss to private households},
  doi       = {10.25932/publishup-42991},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-429910},
  school      = {Universit{\"a}t Potsdam},
  pages     = {XXII, 109},
  year      = {2018},
  abstract  = {Today, more than half of the world's population lives in urban areas. With a high density of population and assets, urban areas are not only the economic, cultural and social hubs of every society, they are also highly susceptible to natural disasters. As a consequence of rising sea levels and an expected increase in extreme weather events caused by a changing climate in combination with growing cities, flooding is an increasing threat to many urban agglomerations around the globe. To mitigate the destructive consequences of flooding, appropriate risk management and adaptation strategies are required. So far, flood risk management in urban areas is almost exclusively focused on managing river and coastal flooding. Often overlooked is the risk from small-scale rainfall-triggered flooding, where the rainfall intensity of rainstorms exceeds the capacity of urban drainage systems, leading to immediate flooding. Referred to as pluvial flooding, this flood type exclusive to urban areas has caused severe losses in cities around the world. Without further intervention, losses from pluvial flooding are expected to increase in many urban areas due to an increase of impervious surfaces compounded with an aging drainage infrastructure and a projected increase in heavy precipitation events. While this requires the integration of pluvial flood risk into risk management plans, so far little is known about the adverse consequences of pluvial flooding due to a lack of both detailed data sets and studies on pluvial flood impacts. As a consequence, methods for reliably estimating pluvial flood losses, needed for pluvial flood risk assessment, are still missing. Therefore, this thesis investigates how pluvial flood losses to private households can be reliably estimated, based on an improved understanding of the drivers of pluvial flood loss. For this purpose, detailed data from pluvial flood-affected households was collected through structured telephone- and web-surveys following pluvial flood events in Germany and the Netherlands. Pluvial flood losses to households are the result of complex interactions between impact characteristics such as the water depth and a household's resistance as determined by its risk awareness, preparedness, emergency response, building properties and other influencing factors. Both exploratory analysis and machine-learning approaches were used to analyze differences in resistance and impacts between households and their effects on the resulting losses. The comparison of case studies showed that the awareness around pluvial flooding among private households is quite low. Low awareness not only challenges the effective dissemination of early warnings, but was also found to influence the implementation of private precautionary measures. The latter were predominately implemented by households with previous experience of pluvial flooding. Even cases where previous flood events affected a different part of the same city did not lead to an increase in preparedness of the surveyed households, highlighting the need to account for small-scale variability in both impact and resistance parameters when assessing pluvial flood risk. While it was concluded that the combination of low awareness, ineffective early warning and the fact that only a minority of buildings were adapted to pluvial flooding impaired the coping capacities of private households, the often low water levels still enabled households to mitigate or even prevent losses through a timely and effective emergency response. These findings were confirmed by the detection of loss-influencing variables, showing that cases in which households were able to prevent any loss to the building structure are predominately explained by resistance variables such as the household's risk awareness, while the degree of loss is mainly explained by impact variables. Based on the important loss-influencing variables detected, different flood loss models were developed. Similar to flood loss models for river floods, the empirical data from the preceding data collection was used to train flood loss models describing the relationship between impact and resistance parameters and the resulting loss to building structures. Different approaches were adapted from river flood loss models using both models with the water depth as only predictor for building structure loss and models incorporating additional variables from the preceding variable detection routine. The high predictive errors of all compared models showed that point predictions are not suitable for estimating losses on the building level, as they severely impair the reliability of the estimates. For that reason, a new probabilistic framework based on Bayesian inference was introduced that is able to provide predictive distributions instead of single loss estimates. These distributions not only give a range of probable losses, they also provide information on how likely a specific loss value is, representing the uncertainty in the loss estimate. Using probabilistic loss models, it was found that the certainty and reliability of a loss estimate on the building level is not only determined by the use of additional predictors as shown in previous studies, but also by the choice of response distribution defining the shape of the predictive distribution. Here, a mix between a beta and a Bernoulli distribution to account for households that are able to prevent losses to their building's structure was found to provide significantly more certain and reliable estimates than previous approaches using Gaussian or non-parametric response distributions. The successful model transfer and post-event application to estimate building structure loss in Houston, TX, caused by pluvial flooding during Hurricane Harvey confirmed previous findings, and demonstrated the potential of the newly developed multi-variable beta model for future risk assessments. The highly detailed input data set constructed from openly available data sources containing over 304,000 affected buildings in Harris County further showed the potential of data-driven, building-level loss models for pluvial flood risk assessment. In conclusion, pluvial flood losses to private households are the result of complex interactions between impact and resistance variables, which should be represented in loss models. The local occurrence of pluvial floods requires loss estimates on high spatial resolutions, i.e. on the building level, where losses are variable and uncertainties are high. Therefore, probabilistic loss estimates describing the uncertainty of the estimate should be used instead of point predictions. While the performance of probabilistic models on the building level are mainly driven by the choice of response distribution, multi-variable models are recommended for two reasons: First, additional resistance variables improve the detection of cases in which households were able to prevent structural losses. Second, the added variability of additional predictors provides a better representation of the uncertainties when loss estimates from multiple buildings are aggregated. This leads to the conclusion that data-driven probabilistic loss models on the building level allow for a reliable loss estimation at an unprecedented level of detail, with a consistent quantification of uncertainties on all aggregation levels. This makes the presented approach suitable for a wide range of applications, from decision support in spatial planning to impact- based early warning systems.},
  language  = {en}
}
@article{LaudanZoellerThieken2020,
  author    = {Laudan, Jonas and Z{\"o}ller, Gert and Thieken, Annegret},
  title     = {Flash floods versus river floods},
  series = {Natural Hazards and Earth System Sciences},
  volume    = {20},
  journal   = {Natural Hazards and Earth System Sciences},
  publisher = {European Geophysical Society},
  address   = {Katlenburg-Lindau},
  issn      = {1684-9981},
  doi       = {10.5194/nhess-20-999-2020},
  pages     = {999 -- 1023},
  year      = {2020},
  abstract  = {River floods are among the most damaging natural hazards that frequently occur in Germany. Flooding causes high economic losses and impacts many residents. In 2016, several southern German municipalities were hit by flash floods after unexpectedly severe heavy rainfall, while in 2013 widespread river flooding had occurred. This study investigates and compares the psychological impacts of river floods and flash floods and potential consequences for precautionary behaviour. Data were collected using computer-aided telephone interviews that were conducted among flood-affected households around 9 months after each damaging event. This study applies Bayesian statistics and negative binomial regressions to test the suitability of psychological indicators to predict the precaution motivation of individuals. The results show that it is not the particular flood type but rather the severity and local impacts of the event that are crucial for the different, and potentially negative, impacts on mental health. According to the used data, however, predictions of the individual precaution motivation should not be based on the derived psychological indicators - i.e. coping appraisal, threat appraisal, burden and evasion - since their explanatory power was generally low and results are, for the most part, non-significant. Only burden reveals a significant positive relation to planned precaution regarding weak flash floods. In contrast to weak flash floods and river floods, the perceived threat of strong flash floods is significantly lower although feelings of burden and lower coping appraisals are more pronounced. Further research is needed to better include psychological assessment procedures and to focus on alternative data sources regarding floods and the connected precaution motivation of affected residents.},
  language  = {en}
}
@misc{LaudanZoellerThieken2020,
  author    = {Laudan, Jonas and Z{\"o}ller, Gert and Thieken, Annegret},
  title     = {Flash floods versus river floods},
  series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  journal   = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  number    = {968},
  issn      = {1866-8372},
  doi       = {10.25932/publishup-47397},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-473974},
  pages     = {999 -- 1023},
  year      = {2020},
  abstract  = {River floods are among the most damaging natural hazards that frequently occur in Germany. Flooding causes high economic losses and impacts many residents. In 2016, several southern German municipalities were hit by flash floods after unexpectedly severe heavy rainfall, while in 2013 widespread river flooding had occurred. This study investigates and compares the psychological impacts of river floods and flash floods and potential consequences for precautionary behaviour. Data were collected using computer-aided telephone interviews that were conducted among flood-affected households around 9 months after each damaging event. This study applies Bayesian statistics and negative binomial regressions to test the suitability of psychological indicators to predict the precaution motivation of individuals. The results show that it is not the particular flood type but rather the severity and local impacts of the event that are crucial for the different, and potentially negative, impacts on mental health. According to the used data, however, predictions of the individual precaution motivation should not be based on the derived psychological indicators - i.e. coping appraisal, threat appraisal, burden and evasion - since their explanatory power was generally low and results are, for the most part, non-significant. Only burden reveals a significant positive relation to planned precaution regarding weak flash floods. In contrast to weak flash floods and river floods, the perceived threat of strong flash floods is significantly lower although feelings of burden and lower coping appraisals are more pronounced. Further research is needed to better include psychological assessment procedures and to focus on alternative data sources regarding floods and the connected precaution motivation of affected residents.},
  language  = {en}
}
@misc{KienzlerPechKreibichetal.2014,
  author    = {Kienzler, Sarah and Pech, I. and Kreibich, Heidi and M{\"u}ller, M. and Thieken, Annegret},
  title     = {After the extreme flood in 2002},
  series = {Postprints der Universit{\"a}t Potsdam : Mathematisch Naturwissenschaftliche Reihe},
  journal   = {Postprints der Universit{\"a}t Potsdam : Mathematisch Naturwissenschaftliche Reihe},
  number    = {488},
  issn      = {1866-8372},
  doi       = {10.25932/publishup-40805},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-408056},
  pages     = {505 -- 526},
  year      = {2014},
  abstract  = {In the aftermath of the severe flooding in Central Europe in August 2002, a number of changes in flood policies were launched in Germany and other European countries, aiming at improved risk management. The question arises as to whether these changes have already had an impact on the residents' ability to cope with floods, and whether flood-affected private households are now better prepared than they were in 2002. Therefore, computer-aided telephone interviews with private households in Germany that suffered from property damage due to flooding in 2005, 2006, 2010 or 2011 were performed and analysed with respect to flood awareness, precaution, preparedness and recovery. The data were compared to a similar investigation conducted after the flood in 2002. After the flood in 2002, the level of private precautions taken increased considerably. One contributing factor is the fact that, in general, a larger proportion of people knew that they were at risk of flooding. The best level of precaution was found before the flood events in 2006 and 2011. The main reason for this might be that residents had more experience with flooding than residents affected in 2005 or 2010. Yet, overall, flood experience and knowledge did not necessarily result in building retrofitting or flood-proofing measures, which are considered as mitigating damages most effectively. Hence, investments still need to be stimulated in order to reduce future damage more efficiently. Early warning and emergency responses were substantially influenced by flood characteristics. In contrast to flood-affected people in 2006 or 2011, people affected by flooding in 2005 or 2010 had to deal with shorter lead times and therefore had less time to take emergency measures. Yet, the lower level of emergency measures taken also resulted from the people's lack of flood experience and insufficient knowledge of how to protect themselves. Overall, it was noticeable that these residents suffered from higher losses. Therefore, it is important to further improve early warning systems and communication channels, particularly in hilly areas with rapid-onset flooding.},
  language  = {en}
}
@misc{SpekkersRoezerThiekenetal.2017,
  author    = {Spekkers, Matthieu and R{\"o}zer, Viktor and Thieken, Annegret and ten Veldhuis, Marie-Claire and Kreibich, Heidi},
  title     = {A comparative survey of the impacts of extreme rainfall in two international case studies},
  series = {Postprints der Universit{\"a}t Potsdam : Mathematisch Naturwissenschaftliche Reihe},
  journal   = {Postprints der Universit{\"a}t Potsdam : Mathematisch Naturwissenschaftliche Reihe},
  number    = {640},
  issn      = {1866-8372},
  doi       = {10.25932/publishup-41843},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-418432},
  pages     = {1337 -- 1355},
  year      = {2017},
  abstract  = {Flooding is assessed as the most important natural hazard in Europe, causing thousands of deaths, affecting millions of people and accounting for large economic losses in the past decade. Little is known about the damage processes associated with extreme rainfall in cities, due to a lack of accurate, comparable and consistent damage data. The objective of this study is to investigate the impacts of extreme rainfall on residential buildings and how affected households coped with these impacts in terms of precautionary and emergency actions. Analyses are based on a unique dataset of damage characteristics and a wide range of potential damage explaining variables at the household level, collected through computer-aided telephone interviews (CATI) and an online survey. Exploratory data analyses based on a total of 859 completed questionnaires in the cities of Munster (Germany) and Amsterdam (the Netherlands) revealed that the uptake of emergency measures is related to characteristics of the hazardous event. In case of high water levels, more efforts are made to reduce damage, while emergency response that aims to prevent damage is less likely to be effective. The difference in magnitude of the events in Munster and Amsterdam, in terms of rainfall intensity and water depth, is probably also the most important cause for the differences between the cities in terms of the suffered financial losses. Factors that significantly contributed to damage in at least one of the case studies are water contamination, the presence of a basement in the building and people's awareness of the upcoming event. Moreover, this study confirms conclusions by previous studies that people's experience with damaging events positively correlates with precautionary behaviour. For improving future damage data acquisition, we recommend the inclusion of cell phones in a CATI survey to avoid biased sampling towards certain age groups.},
  language  = {en}
}