TY - GEN A1 - Sultana, Zakia A1 - Sieg, Tobias A1 - Kellermann, Patric A1 - Müller, Meike A1 - Kreibich, Heidi T1 - Assessment of business interruption of flood-affected companies using random forests T2 - Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe N2 - 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. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 939 KW - business interruption KW - floods KW - Random Forests KW - companies KW - variable importance Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-459778 SN - 1866-8372 IS - 939 ER - TY - JOUR A1 - Sultana, Zakia A1 - Sieg, Tobias A1 - Kellermann, Patric A1 - Müller, Meike A1 - Kreibich, Heidi T1 - Assessment of business interruption of flood-affected companies using random forests JF - Water N2 - 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. KW - business interruption KW - floods KW - Random Forests KW - companies KW - variable importance Y1 - 2018 U6 - https://doi.org/10.3390/w10081049 SN - 2073-4441 VL - 10 IS - 8 PB - MDPI CY - Basel ER - TY - JOUR A1 - Schoppa, Lukas A1 - Sieg, Tobias A1 - Vogel, Kristin A1 - Zöller, Gert A1 - Kreibich, Heidi T1 - Probabilistic flood loss models for companies JF - Water resources research N2 - 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. KW - flood loss estimation KW - probabilistic modeling KW - companies KW - multivariable KW - models Y1 - 2020 U6 - https://doi.org/10.1029/2020WR027649 SN - 0043-1397 SN - 1944-7973 VL - 56 IS - 9 PB - American Geophysical Union CY - Washington ER - TY - JOUR A1 - Sieg, Tobias A1 - Thieken, Annegret T1 - Improving flood impact estimations JF - Environmental research letters N2 - 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. KW - rapid impact assessment KW - floods KW - OpenStreetMap KW - flood risk management KW - natural hazards Y1 - 2022 U6 - https://doi.org/10.1088/1748-9326/ac6d6c SN - 1748-9326 VL - 17 IS - 6 PB - IOP Publ. Ltd. CY - Bristol ER - TY - JOUR A1 - Laudan, Jonas A1 - Roezer, Viktor A1 - Sieg, Tobias A1 - Vogel, Kristin A1 - Thieken, Annegret T1 - Damage assessment in Braunsbach 2016: data collection and analysis for an improved understanding of damaging processes during flash floods JF - Natural hazards and earth system sciences Y1 - 2017 U6 - https://doi.org/10.5194/nhess-17-2163-2017 SN - 1561-8633 VL - 17 SP - 2163 EP - 2179 PB - Copernicus CY - Göttingen ER - TY - JOUR A1 - Vogel, Kristin A1 - Ozturk, Ugur A1 - Riemer, Adrian A1 - Laudan, Jonas A1 - Sieg, Tobias A1 - Wendi, Dadiyorto A1 - Agarwal, Ankit A1 - Roezer, Viktor A1 - Korup, Oliver A1 - Thieken, Annegret T1 - Die Sturzflut von Braunsbach am 29. Mai 2016 – Entstehung, Ablauf und Schäden eines „Jahrhundertereignisses“ T1 - The Braunsbach Flashflood of Mai 29th, 2016-Origin, Pathways and Impacts of an Extreme Hydro-Meteorological Event BT - Teil 2: Geomorphologische Prozesse und Schadensanalyse BT - Part 2: Geomorphological Processes and Damage Analysis JF - Hydrologie und Wasserbewirtschaftung N2 - Am Abend des 29. Mai 2016 wurde der Ort Braunsbach im Landkreis Schwäbisch-Hall (Baden-Württemberg) von einer Sturzflut getroffen, bei der mehrere Häuser stark beschädigt oder zerstört wurden. Die Sturzflut war eine der Unwetterfolgen, die im Frühsommer 2016 vom Tiefdruckgebiet Elvira ausgelöst wurden. Der vorliegende Bericht ist der zweite Teil einer Doppelveröffentlichung, welche die Ergebnisse zur Untersuchung des Sturzflutereignisses im Rahmen des DFG-Graduiertenkollegs “Naturgefahren und Risiken in einer sich verändernden Welt” (NatRiskChange, GRK 2043/1) der Universität Potsdam präsentiert. Während Teil 1 die meteorologischen und hydrologischen Ereignisse analysiert, fokussiert Teil 2 auf die geomorphologischen Prozesse und die verursachten Gebäudeschäden. Dazu wurden Ursprung und Ausmaß des während des Sturzflutereignisses mobilisierten und in den Ort getragenen Materials untersucht. Des Weiteren wurden zu 96 betroffenen Gebäuden Daten zum Schadensgrad sowie Prozess- und Gebäudecharakteristika aufgenommen und ausgewertet. Die Untersuchungen zeigen, dass bei der Betrachtung von Hochwassergefährdung die Berücksichtigung von Sturzfluten und ihrer speziellen Charakteristika, wie hoher Feststofftransport und sprunghaftes Verhalten insbesondere in bebautem Gelände, wesentlich ist, um effektive Schutzmaßnahmen ergreifen zu können. N2 - A severe flash flood event hit the town of Braunsbach (Baden-Wurttemberg, Germany) on the evening of May 29, 2016, heavily damaging and destroying several dozens of buildings. It was only one of several disastrous events in Central Europe caused by the low-pressure system "Elvira". The DFG Graduate School "Natural hazards and risks in a changing world" (NatRiskChange, GRK 2043/1) at the University of Potsdam investigated the Braunsbach flash flood as a recent showcase for catastrophic events triggered by severe weather. This contribution is part two of a back-to-back publication on the results of this storm event. While part 1 analyses the meteorological and hydrological situation, part 2 concentrates on the geomorphological aspects and damage to buildings. The study outlines the origin and amount of material that was mobilized and transported into the town by the flood, and analyses damage data collected for 96 affected buildings, describing the degree of impact, underlying processes, and building characteristics. Due to the potentially high sediment load of flash floods and their non-steady and non-uniform flow especially in built-up areas, the damaging processes differ from those of clear water floods. The results underline the need to consider flash floods and their specific behaviour in flood hazard assessments. KW - flash flood KW - flood risk KW - damaging processes KW - debris flow KW - erosion KW - landslides KW - Braunsbach KW - Sturzflut KW - Hochwassergefährdung KW - Schadensprozesse KW - Erosion KW - Hangrutschungen Y1 - 2017 U6 - https://doi.org/10.5675/HyWa_2017,3_2 SN - 1439-1783 VL - 61 IS - 3 SP - 163 EP - 175 PB - Bundesanst. für Gewässerkunde CY - Koblenz ER - TY - GEN A1 - Laudan, Jonas A1 - Rözer, Viktor A1 - Sieg, Tobias A1 - Vogel, Kristin A1 - Thieken, Annegret T1 - Damage assessment in Braunsbach 2016 BT - data collection and analysis for an improved understanding of damaging processes during flash floods T2 - Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe N2 - 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. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 653 KW - building damage KW - mai 29th KW - flow KW - vulnerability KW - 2016-origin KW - pathways KW - Germany KW - impacts KW - model Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-418392 SN - 1866-8372 IS - 653 ER - TY - GEN A1 - Kuhlicke, Christian A1 - Masson, Torsten A1 - Kienzler, Sarah A1 - Sieg, Tobias A1 - Thieken, Annegret A1 - Kreibich, Heidi T1 - Multiple flood experiences and social resilience BT - Findings from three surveys on households and companies exposed to the 2013 flood in Germany T2 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe N2 - 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. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 1398 KW - social science KW - Europe Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-516500 SN - 1866-8372 IS - 1 ER - TY - JOUR A1 - Sairam, Nivedita A1 - Brill, Fabio Alexander A1 - Sieg, Tobias A1 - Farrag, Mostafa A1 - Kellermann, Patric A1 - Viet Dung Nguyen, A1 - Lüdtke, Stefan A1 - Merz, Bruno A1 - Schröter, Kai A1 - Vorogushyn, Sergiy A1 - Kreibich, Heidi T1 - Process-based flood risk assessment for Germany JF - Earth's future / American Geophysical Union N2 - 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. KW - risk model chain KW - continuous simulation KW - expected annual damage KW - risk KW - curves KW - multi-sector risk Y1 - 2021 U6 - https://doi.org/10.1029/2021EF002259 SN - 2328-4277 VL - 9 IS - 10 PB - Wiley-Blackwell CY - Hoboken, NJ ER - TY - RPRT A1 - Agarwal, Ankit A1 - Boessenkool, Berry A1 - Fischer, Madlen A1 - Hahn, Irene A1 - Köhn, Lisei A1 - Laudan, Jonas A1 - Moran, Thomas A1 - Öztürk, Ugur A1 - Riemer, Adrian A1 - Rözer, Viktor A1 - Sieg, Tobias A1 - Vogel, Kristin A1 - Wendi, Dadiyorto A1 - Bronstert, Axel A1 - Thieken, Annegret T1 - Die Sturzflut in Braunsbach, Mai 2016 T1 - The flash flood of Braunsbach, May 2006 BT - eine Bestandsaufnahme und Ereignisbeschreibung BT - a hydrological survey and event analysis N2 - Im Graduiertenkolleg NatRiskChange der Universität Potsdam und anderen Forschungseinrichtungen werden beobachtete sowie zukünftig mögliche Veränderungen von Naturgefahren untersucht. Teil des strukturierten Doktorandenprogramms sind sogenannte Task-Force-Einsätze, bei denen die Promovierende zeitlich begrenzt ein aktuelles Ereignis auswerten. Im Zuge dieser Aktivität wurde die Sturzflut vom 29.05.2016 in Braunsbach (Baden-Württemberg) untersucht. In diesem Bericht werden erste Auswertungen zur Einordnung der Niederschläge, zu den hydrologischen und geomorphologischen Prozessen im Einzugsgebiet des Orlacher Bachs sowie zu den verursachten Schäden beleuchtet. Die Region war Zentrum extremer Regenfälle in der Größenordnung von 100 mm innerhalb von 2 Stunden. Das 6 km² kleine Einzugsgebiet hat eine sehr schnelle Reaktionszeit, zumal bei vorgesättigtem Boden. Im steilen Bachtal haben mehrere kleinere und größere Hangrutschungen über 8000 m³ Geröll, Schutt und Schwemmholz in das Gewässer eingetragen und möglicherweise kurzzeitige Aufstauungen und Durchbrüche verursacht. Neben den großen Wassermengen mit einer Abflussspitze in einer Größenordnung von 100 m³/s hat gerade die Geschiebefracht zu großen Schäden an den Gebäuden entlang des Bachlaufs in Braunsbach geführt. N2 - The DFG graduate school “Natural Hazards and Risks in a Changing World” (NatRiskChange), which is located at the University of Potsdam and its partner institutions, studies previous as well as ongoing and potential future changes in the risk posed by natural hazards. The education program includes so-called task force activities, where the PhD students conduct a rapid event assessment directly after the occurrence of a hazardous natural event. Within this context the flash flood that hit the village Braunsbach (Baden-Württemberg, Germany) at May 29th, 2016 was investigated. This report summarizes first results describing the rainfall amount and intensities as well as hydrological and geomorphological processes in the corresponding catchment area of the Orlacher Bach. Further, the damages caused in Braunsbach are investigated. Rainfall intensity measures documented extreme precipitation in the area of Braunsbach with a cumulative amount of about 100 mm within 2 hours. The small catchment area, with a size of 6 km², has a small response time, especially under pre-saturated soil conditions. Several landslides, that occurred at the steep slopes of the river valley, transported more than 8000 m³ of gravel, debris and organic material into the water runoff. They may have caused temporal blockades, that collapsed after a certain amount of water accumulated. In addition to the high discharge, with peak values in the order of 100 m³/s, the high sediment content of the flash flood is mainly responsible for the large damages caused to the buildings in Braunsbach. KW - Sturzflut KW - Naturgefahren KW - Extremniederschlag KW - Schadensabschätzung KW - Hangrutschungen KW - flash flood KW - natural hazards KW - extreme precipitation KW - damage assessment KW - landslides Y1 - 2016 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-394881 ER -