@article{OttoKellermannThiekenetal.2018, author = {Otto, Antje and Kellermann, Patric and Thieken, Annegret and Costa, Maria Manez and Carmona, Maria and Bubeck, Philip}, title = {Risk reduction partnerships in railway transport infrastructure in an alpine environment}, series = {International journal of disaster risk reduction}, volume = {33}, journal = {International journal of disaster risk reduction}, publisher = {Elsevier}, address = {Amsterdam}, issn = {2212-4209}, doi = {10.1016/j.ijdrr.2018.10.025}, pages = {385 -- 397}, year = {2018}, abstract = {The transport sector is crucial for the functioning of modern societies and their economic welfares. However, it is vulnerable to natural hazards since damage and disturbances appear recurrently. Risk management of transport infrastructure is a complex task that usually involves various stakeholders from the public and private sector. Related scientific knowledge, however, is limited so far. Therefore, this paper presents detailed information on the risk management of the Austrian railway operator gathered through literature studies, in interviews, meetings and workshops. The findings reveal three decision making levels of risk reduction: 1) a superordinate level for the negotiation of frameworks and guidelines, 2) a regional to local level for the planning and implementation of structural measures and 3) a regional to local level for non-structural risk reduction measures and emergency management. On each of these levels, multi-sectoral partnerships exist that aim at reducing the risk to railway infrastructure. Chosen partnerships are evaluated applying the Capital Approach Framework and some collaborations are analyzed considering the flood and landslide events in June 2013. The evaluation reveals that the risk management of the railway operator and its partners has been successful, but there is still potential for enhancement. Difficulties are seen for instance in obtaining continuity of employees and organizational structures which can affect personal contacts and mutual trust and might hamper sharing data and experiences. Altogether, the case reveals the importance of multi-sectoral partnerships that are seen as a crucial element of risk management in the Sendai Framework for Disaster Risk Reduction 2015-2030.}, language = {en} } @article{OttoHornbergThieken2018, author = {Otto, Antje and Hornberg, Anja and Thieken, Annegret}, title = {Local controversies of flood risk reduction measures in Germany}, series = {Journal of flood risk management}, volume = {11}, journal = {Journal of flood risk management}, publisher = {Wiley}, address = {Hoboken}, issn = {1753-318X}, doi = {10.1111/jfr3.12227}, pages = {S382 -- S394}, year = {2018}, abstract = {In light of the flood event in June 2013, local disputes of flood risk reduction measures became a public concern in Germany, as it was argued that these controversies delayed the implementation of flood defence schemes and thus aggravated the flood impacts. However, actual knowledge about such disputes is generally quite limited. Therefore, this paper uses different empirical approaches to present first an explorative overview of such ongoing controversies with a focus on the measures under dispute and their geographical distribution. Second, current insights in the disputes are delineated, and the following four central conflict lines are expounded: (1) the desire for safety, (2) arguments of nature and landscape protection, (3) questions regarding economic development, and (4) participation issues. The results are discussed comprehensively, and conclusions are drawn regarding further research as well as planning practice in the field of risk reduction measures.}, language = {en} } @article{BubeckBotzenLaudanetal.2018, author = {Bubeck, Philip and Botzen, W. J. Wouter and Laudan, Jonas and Aerts, Jeroen C. J. H. and Thieken, Annegret}, title = {Insights into flood-coping appraisals of protection motivation theory}, series = {Risk analysis}, volume = {38}, journal = {Risk analysis}, number = {6}, publisher = {Wiley}, address = {Hoboken}, issn = {0272-4332}, doi = {10.1111/risa.12938}, pages = {1239 -- 1257}, year = {2018}, abstract = {Protection motivation theory (PMT) has become a popular theory to explain the risk-reducing behavior of residents against natural hazards. PMT captures the two main cognitive processes that individuals undergo when faced with a threat, namely, threat appraisal and coping appraisal. The latter describes the evaluation of possible response measures that may reduce or avert the perceived threat. Although the coping appraisal component of PMT was found to be a better predictor of protective intentions and behavior, little is known about the factors that influence individuals' coping appraisals of natural hazards. More insight into flood-coping appraisals of PMT, therefore, are needed to better understand the decision-making process of individuals and to develop effective risk communication strategies. This study presents the results of two surveys among more than 1,600 flood-prone households in Germany and France. Five hypotheses were tested using multivariate statistics regarding factors related to flood-coping appraisals, which were derived from the PMT framework, related literature, and the literature on social vulnerability. We found that socioeconomic characteristics alone are not sufficient to explain flood-coping appraisals. Particularly, observational learning from the social environment, such as friends and neighbors, is positively related to flood-coping appraisals. This suggests that social norms and networks play an important role in flood-preparedness decisions. Providing risk and coping information can also have a positive effect. Given the strong positive influence of the social environment on flood-coping appraisals, future research should investigate how risk communication can be enhanced by making use of the observed social norms and network effects.}, language = {en} } @article{NathoThieken2018, author = {Natho, Stephanie and Thieken, Annegret}, title = {Implementation and adaptation of a macro-scale method to assess and monitor direct economic losses caused by natural hazards}, series = {International Journal of Disaster Risk Reduction}, volume = {28}, journal = {International Journal of Disaster Risk Reduction}, publisher = {Elsevier}, address = {Amsterdam}, issn = {2212-4209}, doi = {10.1016/j.ijdrr.2018.03.008}, pages = {191 -- 205}, year = {2018}, abstract = {As one of the 195 member countries of the United Nations, Germany signed the Sendai Framework for Disaster Risk Reduction 2015-2030 (SFDRR). Among other targets, the SFDRR aims at reducing direct economic losses caused by natural hazards by 2030. The United Nations Office for Disaster Risk Reduction (UNISDR) has hence proposed a methodology for estimating direct economic losses per event and country, based on experiences from developing countries. Since its usability in industrialized countries is unknown, this study presents the first implementation and validation of this approach in Germany. The methodology was tested for the three costliest natural hazard types in Germany, i.e. floods, wind and hail storms, considering 12 case studies between 1984 and 2016. Although the event-specific input data requirements are restricted to the number of damaged or destroyed units per sector, incomplete event documentations did not allow a full validation of all sectors necessary to describe the total direct economic loss. New modules (cars, forestry, paved roads, housing contents and overall costs of urban infrastructure) were developed to better adapt this methodology to German conditions. Whereas the original UNISDR methodology both over-and underestimates the losses of the tested events by a wide margin, the adapted methodology is able to calculate losses accounting well for all event types except for flash floods. Hence, this approach serves as a good starting point for macro-scale loss estimations. By implementing this approach into damage and event documentation and reporting standards, a consistent monitoring of the SFDRR could be achieved.}, language = {en} } @article{VogelWeiseSchroeteretal.2018, author = {Vogel, Kristin and Weise, Laura and Schr{\"o}ter, Kai and Thieken, Annegret}, title = {Identifying Driving Factors in Flood-Damaging Processes Using Graphical Models}, series = {Water resources research}, volume = {54}, journal = {Water resources research}, number = {11}, publisher = {American Geophysical Union}, address = {Washington}, issn = {0043-1397}, doi = {10.1029/2018WR022858}, pages = {8864 -- 8889}, year = {2018}, abstract = {Flood damage estimation is a core task in flood risk assessments and requires reliable flood loss models. Identifying the driving factors of flood loss at residential buildings and gaining insight into their relations is important to improve our understanding of flood damage processes. For that purpose, we learn probabilistic graphical models, which capture and illustrate (in-)dependencies between the considered variables. The models are learned based on postevent surveys with flood-affected residents after six flood events, which occurred in Germany between 2002 and 2013. Besides the sustained building damage, the survey data contain information about flooding parameters, early warning and emergency measures, property-level mitigation measures and preparedness, socioeconomic characteristics of the household, and building characteristics. The analysis considers the entire data set with a total of 4,468 cases as well as subsets of the data set partitioned into single flood events and flood types: river floods, levee breaches, surface water flooding, and groundwater floods, to reveal differences in the damaging processes. The learned networks suggest that the flood loss ratio of residential buildings is directly influenced by hydrological and hydraulic aspects as well as by building characteristics and property-level mitigation measures. The study demonstrates also that for different flood events and process types the building damage is influenced by varying factors. This suggests that flood damage models need to be capable of reproducing these differences for spatial and temporal model transfers.}, language = {en} }