@misc{SultanaSiegKellermannetal.2018,
  author    = {Sultana, Zakia and Sieg, Tobias and Kellermann, Patric and M{\"u}ller, Meike and Kreibich, Heidi},
  title     = {Assessment of business interruption of flood-affected companies using random forests},
  series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  journal   = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  number    = {939},
  issn      = {1866-8372},
  doi       = {10.25932/publishup-45977},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-459778},
  pages     = {18},
  year      = {2018},
  abstract  = {Losses due to floods have dramatically increased over the past decades, and losses of companies, comprising direct and indirect losses, have a large share of the total economic losses. Thus, there is an urgent need to gain more quantitative knowledge about flood losses, particularly losses caused by business interruption, in order to mitigate the economic loss of companies. However, business interruption caused by floods is rarely assessed because of a lack of sufficiently detailed data. A survey was undertaken to explore processes influencing business interruption, which collected information on 557 companies affected by the severe flood in June 2013 in Germany. Based on this data set, the study aims to assess the business interruption of directly affected companies by means of a Random Forests model. Variables that influence the duration and costs of business interruption were identified by the variable importance measures of Random Forests. Additionally, Random Forest-based models were developed and tested for their capacity to estimate business interruption duration and associated costs. The water level was found to be the most important variable influencing the duration of business interruption. Other important variables, relating to the estimation of business interruption duration, are the warning time, perceived danger of flood recurrence and inundation duration. In contrast, the amount of business interruption costs is strongly influenced by the size of the company, as assessed by the number of employees, emergency measures undertaken by the company and the fraction of customers within a 50 km radius. These results provide useful information and methods for companies to mitigate their losses from business interruption. However, the heterogeneity of companies is relatively high, and sector-specific analyses were not possible due to the small sample size. Therefore, further sector-specific analyses on the basis of more flood loss data of companies are recommended.},
  language  = {en}
}
@article{SultanaSiegKellermannetal.2018,
  author    = {Sultana, Zakia and Sieg, Tobias and Kellermann, Patric and M{\"u}ller, Meike and Kreibich, Heidi},
  title     = {Assessment of business interruption of flood-affected companies using random forests},
  series = {Water},
  volume    = {10},
  journal   = {Water},
  number    = {8},
  publisher = {MDPI},
  address   = {Basel},
  issn      = {2073-4441},
  doi       = {10.3390/w10081049},
  pages     = {16},
  year      = {2018},
  abstract  = {Losses due to floods have dramatically increased over the past decades, and losses of companies, comprising direct and indirect losses, have a large share of the total economic losses. Thus, there is an urgent need to gain more quantitative knowledge about flood losses, particularly losses caused by business interruption, in order to mitigate the economic loss of companies. However, business interruption caused by floods is rarely assessed because of a lack of sufficiently detailed data. A survey was undertaken to explore processes influencing business interruption, which collected information on 557 companies affected by the severe flood in June 2013 in Germany. Based on this data set, the study aims to assess the business interruption of directly affected companies by means of a Random Forests model. Variables that influence the duration and costs of business interruption were identified by the variable importance measures of Random Forests. Additionally, Random Forest-based models were developed and tested for their capacity to estimate business interruption duration and associated costs. The water level was found to be the most important variable influencing the duration of business interruption. Other important variables, relating to the estimation of business interruption duration, are the warning time, perceived danger of flood recurrence and inundation duration. In contrast, the amount of business interruption costs is strongly influenced by the size of the company, as assessed by the number of employees, emergency measures undertaken by the company and the fraction of customers within a 50 km radius. These results provide useful information and methods for companies to mitigate their losses from business interruption. However, the heterogeneity of companies is relatively high, and sector-specific analyses were not possible due to the small sample size. Therefore, further sector-specific analyses on the basis of more flood loss data of companies are recommended.},
  language  = {en}
}
@article{SchoppaSiegVogeletal.2020,
  author    = {Schoppa, Lukas and Sieg, Tobias and Vogel, Kristin and Z{\"o}ller, Gert and Kreibich, Heidi},
  title     = {Probabilistic flood loss models for companies},
  series = {Water resources research},
  volume    = {56},
  journal   = {Water resources research},
  number    = {9},
  publisher = {American Geophysical Union},
  address   = {Washington},
  issn      = {0043-1397},
  doi       = {10.1029/2020WR027649},
  pages     = {19},
  year      = {2020},
  abstract  = {Flood loss modeling is a central component of flood risk analysis. Conventionally, this involves univariable and deterministic stage-damage functions. Recent advancements in the field promote the use of multivariable and probabilistic loss models, which consider variables beyond inundation depth and account for prediction uncertainty. Although companies contribute significantly to total loss figures, novel modeling approaches for companies are lacking. Scarce data and the heterogeneity among companies impede the development of company flood loss models. We present three multivariable flood loss models for companies from the manufacturing, commercial, financial, and service sector that intrinsically quantify prediction uncertainty. Based on object-level loss data (n = 1,306), we comparatively evaluate the predictive capacity of Bayesian networks, Bayesian regression, and random forest in relation to deterministic and probabilistic stage-damage functions, serving as benchmarks. The company loss data stem from four postevent surveys in Germany between 2002 and 2013 and include information on flood intensity, company characteristics, emergency response, private precaution, and resulting loss to building, equipment, and goods and stock. We find that the multivariable probabilistic models successfully identify and reproduce essential relationships of flood damage processes in the data. The assessment of model skill focuses on the precision of the probabilistic predictions and reveals that the candidate models outperform the stage-damage functions, while differences among the proposed models are negligible. Although the combination of multivariable and probabilistic loss estimation improves predictive accuracy over the entire data set, wide predictive distributions stress the necessity for the quantification of uncertainty.},
  language  = {en}
}
@article{SairamBrillSiegetal.2021,
  author    = {Sairam, Nivedita and Brill, Fabio Alexander and Sieg, Tobias and Farrag, Mostafa and Kellermann, Patric and Viet Dung Nguyen, and L{\"u}dtke, Stefan and Merz, Bruno and Schr{\"o}ter, Kai and Vorogushyn, Sergiy and Kreibich, Heidi},
  title     = {Process-based flood risk assessment for Germany},
  series = {Earth's future / American Geophysical Union},
  volume    = {9},
  journal   = {Earth's future / American Geophysical Union},
  number    = {10},
  publisher = {Wiley-Blackwell},
  address   = {Hoboken, NJ},
  issn      = {2328-4277},
  doi       = {10.1029/2021EF002259},
  pages     = {12},
  year      = {2021},
  abstract  = {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.},
  language  = {en}
}
@article{SiegVogelMerzetal.2017,
  author    = {Sieg, Tobias and Vogel, Kristin and Merz, Bruno and Kreibich, Heidi},
  title     = {Tree-based flood damage modeling of companies: Damage processes and model performance},
  series = {Water resources research},
  volume    = {53},
  journal   = {Water resources research},
  publisher = {American Geophysical Union},
  address   = {Washington},
  issn      = {0043-1397},
  doi       = {10.1002/2017WR020784},
  pages     = {6050 -- 6068},
  year      = {2017},
  abstract  = {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.},
  language  = {en}
}
@article{SiegThieken2022,
  author    = {Sieg, Tobias and Thieken, Annegret},
  title     = {Improving flood impact estimations},
  series = {Environmental research letters},
  volume    = {17},
  journal   = {Environmental research letters},
  number    = {6},
  publisher = {IOP Publ. Ltd.},
  address   = {Bristol},
  issn      = {1748-9326},
  doi       = {10.1088/1748-9326/ac6d6c},
  pages     = {16},
  year      = {2022},
  abstract  = {A reliable estimation of flood impacts enables meaningful flood risk management and rapid assessments of flood impacts shortly after a flood. The flood in 2021 in Central Europe and the analysis of its impacts revealed that these estimations are still inadequate. Therefore, we investigate the influence of different data sets and methods aiming to improve flood impact estimates. We estimated economic flood impacts to private households and companies for a flood event in 2013 in Germany using (a) two different flood maps, (b) two approaches to map exposed objects based on OpenStreetMap and the Basic European Asset Map, (c) two different approaches to estimate asset values, and (d) tree-based models and Stage-Damage-Functions to describe the vulnerability. At the macro scale, water masks lead to reasonable impact estimations. At the micro and meso-scale, the identification of affected objects by means of water masks is insufficient leading to unreliable estimations. The choice of exposure data sets is most influential on the estimations. We find that reliable impact estimations are feasible with reported numbers of flood-affected objects from the municipalities. We conclude that more effort should be put in the investigation of different exposure data sets and the estimation of asset values. Furthermore, we recommend the establishment of a reporting system in the municipalities for a fast identification of flood-affected objects shortly after an event.},
  language  = {en}
}
@phdthesis{Sieg2018,
  author    = {Sieg, Tobias},
  title     = {Reliability of flood damage estimations across spatial scales},
  doi       = {10.25932/publishup-42616},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-426161},
  school      = {Universit{\"a}t Potsdam},
  pages     = {XIII, 115},
  year      = {2018},
  abstract  = {Extreme Naturereignisse sind ein integraler Bestandteil der Natur der Erde. Sie werden erst dann zu Gefahren f{\"u}r die Gesellschaft, wenn sie diesen Ereignissen ausgesetzt ist. Dann allerdings k{\"o}nnen Naturgefahren verheerende Folgen f{\"u}r die Gesellschaft haben. Besonders hydro-meteorologische Gefahren wie zum Beispiel Flusshochwasser, Starkregenereignisse, Winterst{\"u}rme, Orkane oder Tornados haben ein hohes Schadenspotential und treten rund um den Globus auf. Einhergehend mit einer immer w{\"a}rmer werdenden Welt, werden auch Extremwetterereignisse, welche potentiell Naturgefahren ausl{\"o}sen k{\"o}nnen, immer wahrscheinlicher. Allerdings tr{\"a}gt nicht nur eine sich ver{\"a}ndernde Umwelt zur Erh{\"o}hung des Risikos von Naturgefahren bei, sondern auch eine sich ver{\"a}ndernde Gesellschaft. Daher ist ein angemessenes Risikomanagement erforderlich um die Gesellschaft auf jeder r{\"a}umlichen Ebene an diese Ver{\"a}nderungen anzupassen. Ein essentieller Bestandteil dieses Managements ist die Absch{\"a}tzung der {\"o}konomischen Auswirkungen der Naturgefahren. Bisher allerdings fehlen verl{\"a}ssliche Methoden um die Auswirkungen von hydro-meteorologischen Gefahren abzusch{\"a}tzen. Ein Hauptbestandteil dieser Arbeit ist daher die Entwicklung und Anwendung einer neuen Methode, welche die Verl{\"a}sslichkeit der Schadenssch{\"a}tzung verbessert. Die Methode wurde beispielhaft zur Sch{\"a}tzung der {\"o}konomischen Auswirkungen eines Flusshochwassers auf einzelne Unternehmen bis hin zu den Auswirkungen auf das gesamte Wirtschaftssystem Deutschlands erfolgreich angewendet. Bestehende Methoden geben meist wenig Information {\"u}ber die Verl{\"a}sslichkeit ihrer Sch{\"a}tzungen. Da diese Informationen Entscheidungen zur Anpassung an das Risiko erleichtern, wird die Verl{\"a}sslichkeit der Schadenssch{\"a}tzungen mit der neuen Methode dargestellt. Die Verl{\"a}sslichkeit bezieht sich dabei nicht nur auf die Schadenssch{\"a}tzung selber, sondern auch auf die Annahmen, die {\"u}ber betroffene Geb{\"a}ude gemacht werden. Nach diesem Prinzip kann auch die Verl{\"a}sslichkeit von Annahmen {\"u}ber die Zukunft dargestellt werden, dies ist ein wesentlicher Aspekt f{\"u}r Prognosen. Die Darstellung der Verl{\"a}sslichkeit und die erfolgreiche Anwendung zeigt das Potential der Methode zur Verwendung von Analysen f{\"u}r gegenw{\"a}rtige und zuk{\"u}nftige hydro-meteorologische Gefahren.},
  language  = {en}
}
@article{SiegSchinkoVogeletal.2019,
  author    = {Sieg, Tobias and Schinko, Thomas and Vogel, Kristin and Mechler, Reinhard and Merz, Bruno and Kreibich, Heidi},
  title     = {Integrated assessment of short-term direct and indirect economic flood impacts including uncertainty quantification},
  series = {PLoS ONE},
  volume    = {14},
  journal   = {PLoS ONE},
  number    = {4},
  publisher = {Public Library of Science},
  address   = {San Francisco},
  issn      = {1932-6203},
  doi       = {10.1371/journal.pone.0212932},
  pages     = {21},
  year      = {2019},
  abstract  = {Understanding and quantifying total economic impacts of flood events is essential for flood risk management and adaptation planning. Yet, detailed estimations of joint direct and indirect flood-induced economic impacts are rare. In this study an innovative modeling procedure for the joint assessment of short-term direct and indirect economic flood impacts is introduced. The procedure is applied to 19 economic sectors in eight federal states of Germany after the flood events in 2013. The assessment of the direct economic impacts is object-based and considers uncertainties associated with the hazard, the exposed objects and their vulnerability. The direct economic impacts are then coupled to a supply-side Input-Output-Model to estimate the indirect economic impacts. The procedure provides distributions of direct and indirect economic impacts which capture the associated uncertainties. The distributions of the direct economic impacts in the federal states are plausible when compared to reported values. The ratio between indirect and direct economic impacts shows that the sectors Manufacturing, Financial and Insurance activities suffered the most from indirect economic impacts. These ratios also indicate that indirect economic impacts can be almost as high as direct economic impacts. They differ strongly between the economic sectors indicating that the application of a single factor as a proxy for the indirect impacts of all economic sectors is not appropriate.},
  language  = {en}
}
@article{SiegVogelMerzetal.2019,
  author    = {Sieg, Tobias and Vogel, Kristin and Merz, Bruno and Kreibich, Heidi},
  title     = {Seamless Estimation of Hydrometeorological Risk Across Spatial Scales},
  series = {Earth's Future},
  volume    = {7},
  journal   = {Earth's Future},
  number    = {5},
  publisher = {Wiley-Blackwell},
  address   = {Hoboken, NJ},
  issn      = {2328-4277},
  doi       = {10.1029/2018EF001122},
  pages     = {574 -- 581},
  year      = {2019},
  abstract  = {Hydrometeorological hazards caused losses of approximately 110 billion U.S. Dollars in 2016 worldwide. Current damage estimations do not consider the uncertainties in a comprehensive way, and they are not consistent between spatial scales. Aggregated land use data are used at larger spatial scales, although detailed exposure data at the object level, such as openstreetmap.org, is becoming increasingly available across the globe.We present a probabilistic approach for object-based damage estimation which represents uncertainties and is fully scalable in space. The approach is applied and validated to company damage from the flood of 2013 in Germany. Damage estimates are more accurate compared to damage models using land use data, and the estimation works reliably at all spatial scales. Therefore, it can as well be used for pre-event analysis and risk assessments. This method takes hydrometeorological damage estimation and risk assessments to the next level, making damage estimates and their uncertainties fully scalable in space, from object to country level, and enabling the exploitation of new exposure data.},
  language  = {en}
}
@misc{SiegVogelMerzetal.2019,
  author    = {Sieg, Tobias and Vogel, Kristin and Merz, Bruno and Kreibich, Heidi},
  title     = {Seamless Estimation of Hydrometeorological Risk Across Spatial Scales},
  series = {Postprints der Universit{\"a}t Potsdam Mathematisch-Naturwissenschaftliche Reihe},
  journal   = {Postprints der Universit{\"a}t Potsdam Mathematisch-Naturwissenschaftliche Reihe},
  number    = {743},
  issn      = {1866-8372},
  doi       = {10.25932/publishup-43534},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-435341},
  pages     = {574 -- 581},
  year      = {2019},
  abstract  = {Hydrometeorological hazards caused losses of approximately 110 billion U.S. Dollars in 2016 worldwide. Current damage estimations do not consider the uncertainties in a comprehensive way, and they are not consistent between spatial scales. Aggregated land use data are used at larger spatial scales, although detailed exposure data at the object level, such as openstreetmap.org, is becoming increasingly available across the globe.We present a probabilistic approach for object-based damage estimation which represents uncertainties and is fully scalable in space. The approach is applied and validated to company damage from the flood of 2013 in Germany. Damage estimates are more accurate compared to damage models using land use data, and the estimation works reliably at all spatial scales. Therefore, it can as well be used for pre-event analysis and risk assessments. This method takes hydrometeorological damage estimation and risk assessments to the next level, making damage estimates and their uncertainties fully scalable in space, from object to country level, and enabling the exploitation of new exposure data.},
  language  = {en}
}
@misc{SiegShinkoVogeletal.2019,
  author    = {Sieg, Tobias and Shinko, Thomas and Vogel, Kristin and Mechler, Reinhard and Merz, Bruno and Kreibich, Heidi},
  title     = {Integrated assessment of short-term direct and indirect economic flood impacts including uncertainty quantification},
  series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  journal   = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  number    = {708},
  doi       = {10.25932/publishup-42911},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-429119},
  pages     = {21},
  year      = {2019},
  abstract  = {Understanding and quantifying total economic impacts of flood events is essential for flood risk management and adaptation planning. Yet, detailed estimations of joint direct and indirect flood-induced economic impacts are rare. In this study an innovative modeling procedure for the joint assessment of short-term direct and indirect economic flood impacts is introduced. The procedure is applied to 19 economic sectors in eight federal states of Germany after the flood events in 2013. The assessment of the direct economic impacts is object-based and considers uncertainties associated with the hazard, the exposed objects and their vulnerability. The direct economic impacts are then coupled to a supply-side Input-Output-Model to estimate the indirect economic impacts. The procedure provides distributions of direct and indirect economic impacts which capture the associated uncertainties. The distributions of the direct economic impacts in the federal states are plausible when compared to reported values. The ratio between indirect and direct economic impacts shows that the sectors Manufacturing, Financial and Insurance activities suffered the most from indirect economic impacts. These ratios also indicate that indirect economic impacts can be almost as high as direct economic impacts. They differ strongly between the economic sectors indicating that the application of a single factor as a proxy for the indirect impacts of all economic sectors is not appropriate.},
  language  = {en}
}
@article{LaudanRoezerSiegetal.2017,
  author    = {Laudan, Jonas and Roezer, Viktor and Sieg, Tobias and Vogel, Kristin and Thieken, Annegret},
  title     = {Damage assessment in Braunsbach 2016: data collection and analysis for an improved understanding of damaging processes during flash floods},
  series = {Natural hazards and earth system sciences},
  volume    = {17},
  journal   = {Natural hazards and earth system sciences},
  publisher = {Copernicus},
  address   = {G{\"o}ttingen},
  issn      = {1561-8633},
  doi       = {10.5194/nhess-17-2163-2017},
  pages     = {2163 -- 2179},
  year      = {2017},
  language  = {en}
}
@article{VogelOzturkRiemeretal.2017,
  author    = {Vogel, Kristin and Ozturk, Ugur and Riemer, Adrian and Laudan, Jonas and Sieg, Tobias and Wendi, Dadiyorto and Agarwal, Ankit and Roezer, Viktor and Korup, Oliver and Thieken, Annegret},
  title     = {Die Sturzflut von Braunsbach am 29. Mai 2016 - Entstehung, Ablauf und Sch{\"a}den eines „Jahrhundertereignisses"},
  series = {Hydrologie und Wasserbewirtschaftung},
  volume    = {61},
  journal   = {Hydrologie und Wasserbewirtschaftung},
  number    = {3},
  publisher = {Bundesanst. f{\"u}r Gew{\"a}sserkunde},
  address   = {Koblenz},
  issn      = {1439-1783},
  doi       = {10.5675/HyWa_2017,3_2},
  pages     = {163 -- 175},
  year      = {2017},
  abstract  = {Am Abend des 29. Mai 2016 wurde der Ort Braunsbach im Landkreis Schw{\"a}bisch-Hall (Baden-W{\"u}rttemberg) von einer Sturzflut getroffen, bei der mehrere H{\"a}user stark besch{\"a}digt oder zerst{\"o}rt wurden. Die Sturzflut war eine der Unwetterfolgen, die im Fr{\"u}hsommer 2016 vom Tiefdruckgebiet Elvira ausgel{\"o}st wurden. Der vorliegende Bericht ist der zweite Teil einer Doppelver{\"o}ffentlichung, welche die Ergebnisse zur Untersuchung des Sturzflutereignisses im Rahmen des DFG-Graduiertenkollegs "Naturgefahren und Risiken in einer sich ver{\"a}ndernden Welt" (NatRiskChange, GRK 2043/1) der Universit{\"a}t Potsdam pr{\"a}sentiert. W{\"a}hrend Teil 1 die meteorologischen und hydrologischen Ereignisse analysiert, fokussiert Teil 2 auf die geomorphologischen Prozesse und die verursachten Geb{\"a}udesch{\"a}den. Dazu wurden Ursprung und Ausmaß des w{\"a}hrend des Sturzflutereignisses mobilisierten und in den Ort getragenen Materials untersucht. Des Weiteren wurden zu 96 betroffenen Geb{\"a}uden Daten zum Schadensgrad sowie Prozess- und Geb{\"a}udecharakteristika aufgenommen und ausgewertet. Die Untersuchungen zeigen, dass bei der Betrachtung von Hochwassergef{\"a}hrdung die Ber{\"u}cksichtigung von Sturzfluten und ihrer speziellen Charakteristika, wie hoher Feststofftransport und sprunghaftes Verhalten insbesondere in bebautem Gel{\"a}nde, wesentlich ist, um effektive Schutzmaßnahmen ergreifen zu k{\"o}nnen.},
  language  = {de}
}
@article{KuhlickeMassonKienzleretal.2020,
  author    = {Kuhlicke, Christian and Masson, Torsten and Kienzler, Sarah and Sieg, Tobias and Thieken, Annegret and Kreibich, Heidi},
  title     = {Multiple flood experiences and social resilience},
  series = {Weather, Climate, and Society},
  volume    = {12},
  journal   = {Weather, Climate, and Society},
  number    = {1},
  publisher = {American Meteorological Society},
  address   = {Boston},
  issn      = {1948-8327},
  doi       = {10.1175/WCAS-D-18-0069.1},
  pages     = {63 -- 88},
  year      = {2020},
  abstract  = {Previous studies have explored the consequences of flood events for exposed households and companies by focusing on single flood events. Less is known about the consequences of experiencing repeated flood events for the resilience of households and companies. In this paper, we therefore explore how multiple floods experience affects the resilience of exposed households and companies. Resilience was made operational through individual appraisals of households and companies' ability to withstand and recover from material as well as health and psychological impacts of the 2013 flood in Germany. The paper is based on three different datasets including more than 2000 households and 300 companies that were affected by the 2013 flood. The surveys revealed that the resilience of households seems to increase, but only with regard to their subjectively appraised ability to withstand impacts on mobile goods and equipment (e.g., cars, TV, and radios). In regard to the ability of households to withstand overall financial consequences of repetitive floods, evidence for nonlinear (quadratic) trends can be found. With regard to psychological and health-related consequences, the findings are mixed but provide tentative evidence for eroding resilience among households. Companies' resilience increased with respect to material assets but appears to decrease with respect to ability to recover. We conclude by arguing that clear and operational definitions of resilience are required so that evidence-based resilience baselines can be established to assess whether resilience is eroding or improving over time.},
  language  = {en}
}
@misc{LaudanRoezerSiegetal.2017,
  author    = {Laudan, Jonas and R{\"o}zer, Viktor and Sieg, Tobias and Vogel, Kristin and Thieken, Annegret},
  title     = {Damage assessment in Braunsbach 2016},
  series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  journal   = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  number    = {653},
  issn      = {1866-8372},
  doi       = {10.25932/publishup-41839},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-418392},
  pages     = {17},
  year      = {2017},
  abstract  = {Flash floods are caused by intense rainfall events and represent an insufficiently understood phenomenon in Germany. As a result of higher precipitation intensities, flash floods might occur more frequently in future. In combination with changing land use patterns and urbanisation, damage mitigation, insurance and risk management in flash-flood-prone regions are becoming increasingly important. However, a better understanding of damage caused by flash floods requires ex post collection of relevant but yet sparsely available information for research. At the end of May 2016, very high and concentrated rainfall intensities led to severe flash floods in several southern German municipalities. The small town of Braunsbach stood as a prime example of the devastating potential of such events. Eight to ten days after the flash flood event, damage assessment and data collection were conducted in Braunsbach by investigating all affected buildings and their surroundings. To record and store the data on site, the open-source software bundle KoBoCollect was used as an efficient and easy way to gather information. Since the damage driving factors of flash floods are expected to differ from those of riverine flooding, a post-hoc data analysis was performed, aiming to identify the influence of flood processes and building attributes on damage grades, which reflect the extent of structural damage. Data analyses include the application of random forest, a random general linear model and multinomial logistic regression as well as the construction of a local impact map to reveal influences on the damage grades. Further, a Spearman's Rho correlation matrix was calculated. The results reveal that the damage driving factors of flash floods differ from those of riverine floods to a certain extent. The exposition of a building in flow direction shows an especially strong correlation with the damage grade and has a high predictive power within the constructed damage models. Additionally, the results suggest that building materials as well as various building aspects, such as the existence of a shop window and the surroundings, might have an effect on the resulting damage. To verify and confirm the outcomes as well as to support future mitigation strategies, risk management and planning, more comprehensive and systematic data collection is necessary.},
  language  = {en}
}
@techreport{AgarwalBoessenkoolFischeretal.2016,
  author    = {Agarwal, Ankit and Boessenkool, Berry and Fischer, Madlen and Hahn, Irene and K{\"o}hn, Lisei and Laudan, Jonas and Moran, Thomas and {\"O}zt{\"u}rk, Ugur and Riemer, Adrian and R{\"o}zer, Viktor and Sieg, Tobias and Vogel, Kristin and Wendi, Dadiyorto and Bronstert, Axel and Thieken, Annegret},
  title     = {Die Sturzflut in Braunsbach, Mai 2016},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-394881},
  pages     = {20},
  year      = {2016},
  abstract  = {Im Graduiertenkolleg NatRiskChange der Universit{\"a}t Potsdam und anderen Forschungseinrichtungen werden beobachtete sowie zuk{\"u}nftig m{\"o}gliche Ver{\"a}nderungen von Naturgefahren untersucht. Teil des strukturierten Doktorandenprogramms sind sogenannte Task-Force-Eins{\"a}tze, bei denen die Promovierende zeitlich begrenzt ein aktuelles Ereignis auswerten. Im Zuge dieser Aktivit{\"a}t wurde die Sturzflut vom 29.05.2016 in Braunsbach (Baden-W{\"u}rttemberg) untersucht. In diesem Bericht werden erste Auswertungen zur Einordnung der Niederschl{\"a}ge, zu den hydrologischen und geomorphologischen Prozessen im Einzugsgebiet des Orlacher Bachs sowie zu den verursachten Sch{\"a}den beleuchtet. Die Region war Zentrum extremer Regenf{\"a}lle in der Gr{\"o}ßenordnung von 100 mm innerhalb von 2 Stunden. Das 6 km² kleine Einzugsgebiet hat eine sehr schnelle Reaktionszeit, zumal bei vorges{\"a}ttigtem Boden. Im steilen Bachtal haben mehrere kleinere und gr{\"o}ßere Hangrutschungen {\"u}ber 8000 m³ Ger{\"o}ll, Schutt und Schwemmholz in das Gew{\"a}sser eingetragen und m{\"o}glicherweise kurzzeitige Aufstauungen und Durchbr{\"u}che verursacht. Neben den großen Wassermengen mit einer Abflussspitze in einer Gr{\"o}ßenordnung von 100 m³/s hat gerade die Geschiebefracht zu großen Sch{\"a}den an den Geb{\"a}uden entlang des Bachlaufs in Braunsbach gef{\"u}hrt.},
  language  = {de}
}
@misc{KuhlickeMassonKienzleretal.2020,
  author    = {Kuhlicke, Christian and Masson, Torsten and Kienzler, Sarah and Sieg, Tobias and Thieken, Annegret and Kreibich, Heidi},
  title     = {Multiple flood experiences and social resilience},
  series = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  journal   = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  number    = {1},
  issn      = {1866-8372},
  doi       = {10.25932/publishup-51650},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-516500},
  pages     = {28},
  year      = {2020},
  abstract  = {Previous studies have explored the consequences of flood events for exposed households and companies by focusing on single flood events. Less is known about the consequences of experiencing repeated flood events for the resilience of households and companies. In this paper, we therefore explore how multiple floods experience affects the resilience of exposed households and companies. Resilience was made operational through individual appraisals of households and companies' ability to withstand and recover from material as well as health and psychological impacts of the 2013 flood in Germany. The paper is based on three different datasets including more than 2000 households and 300 companies that were affected by the 2013 flood. The surveys revealed that the resilience of households seems to increase, but only with regard to their subjectively appraised ability to withstand impacts on mobile goods and equipment (e.g., cars, TV, and radios). In regard to the ability of households to withstand overall financial consequences of repetitive floods, evidence for nonlinear (quadratic) trends can be found. With regard to psychological and health-related consequences, the findings are mixed but provide tentative evidence for eroding resilience among households. Companies' resilience increased with respect to material assets but appears to decrease with respect to ability to recover. We conclude by arguing that clear and operational definitions of resilience are required so that evidence-based resilience baselines can be established to assess whether resilience is eroding or improving over time.},
  language  = {en}
}