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.
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-floodprone 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.
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.
Abstract. River floods are among the most damaging natural disasters that occur frequently in Germany, causing high economic losses and affecting many residents. In 2016, several Southern German municipalities were hit by flash floods after heavy rainfalls which have been unexpectedly severe and led to total economic losses of EUR 2.6 bn. This study investigates the psychological impacts of river floods and compares them to the impacts of flash floods, using computer-aided telephone interviews that were conducted among flood affected households 8 to 9 months in the aftermath of the events. By applying Bayesian statistics and negative binomial regressions, the suitability of psychological indicators to predict the precaution motivation of individuals is analysed. The results show that not the particular flood type, but rather the severity and local impact of the event is crucial for different and potentially negative impacts on mental health. Moreover, it is revealed that the derived psychological indicators coping appraisal, threat appraisal, burden and evasion only show a limited usefulness for predictions of the individual precaution motivation, which is displayed by a generally low explanation power and non-significant results. Further research is needed to better address established psychological assessment procedures and to focus on alternative data sources regarding floods and the connected precaution motivation of affected residents.
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