@phdthesis{SamprognaMohor2022,
  author    = {Samprogna Mohor, Guilherme},
  title     = {Exploring the transferability of flood loss models across flood types},
  doi       = {10.25932/publishup-55714},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-557141},
  school      = {Universit{\"a}t Potsdam},
  pages     = {XXIV, 182},
  year      = {2022},
  abstract  = {The estimation of financial losses is an integral part of flood risk assessment. The application of existing flood loss models on locations or events different from the ones used to train the models has led to low performance, showing that characteristics of the flood damaging process have not been sufficiently well represented yet. To improve flood loss model transferability, I explore various model structures aiming at incorporating different (inland water) flood types and pathways. That is based on a large survey dataset of approximately 6000 flood-affected households which addresses several aspects of the flood event, not only the hazard characteristics but also information on the affected building, socioeconomic factors, the household's preparedness level, early warning, and impacts. Moreover, the dataset reports the coincidence of different flood pathways. Whilst flood types are a classification of flood events reflecting their generating process (e.g. fluvial, pluvial), flood pathways represent the route the water takes to reach the receptors (e.g. buildings). In this work, the following flood pathways are considered: levee breaches, river floods, surface water floods, and groundwater floods. The coincidence of several hazard processes at the same time and place characterises a compound event. In fact, many flood events develop through several pathways, such as the ones addressed in the survey dataset used. Earlier loss models, although developed with one or multiple predictor variables, commonly use loss data from a single flood event which is attributed to a single flood type, disregarding specific flood pathways or the coincidence of multiple pathways. This gap is addressed by this thesis through the following research questions: 1. In which aspects do flood pathways of the same (compound inland) flood event differ? 2. How much do factors which contribute to the overall flood loss in a building differ in various settings, specifically across different flood pathways? 3. How well can Bayesian loss models learn from different settings? 4. Do compound, that is, coinciding flood pathways result in higher losses than a single pathway, and what does the outcome imply for future loss modelling? Statistical analysis has found that households affected by different flood pathways also show, in general, differing characteristics of the affected building, preparedness, and early warning, besides the hazard characteristics. Forecasting and early warning capabilities and the preparedness of the population are dominated by the general flood type, but characteristics of the hazard at the object-level, the impacts, and the recovery are more related to specific flood pathways, indicating that risk communication and loss models could benefit from the inclusion of flood-pathway-specific information. For the development of the loss model, several potentially relevant predictors are analysed: water depth, duration, velocity, contamination, early warning lead time, perceived knowledge about self-protection, warning information, warning source, gap between warning and action, emergency measures, implementation of property-level precautionary measures (PLPMs), perceived efficacy of PLPMs, previous flood experience, awareness of flood risk, ownership, building type, number of flats, building quality, building value, house/flat area, building area, cellar, age, household size, number of children, number of elderly residents, income class, socioeconomic status, and insurance against floods. After a variable selection, descriptors of the hazard, building, and preparedness were deemed significant, namely: water depth, contamination, duration, velocity, building area, building quality, cellar, PLPMs, perceived efficacy of PLPMs, emergency measures, insurance, and previous flood experience. The inclusion of the indicators of preparedness is relevant, as they are rarely involved in loss datasets and in loss modelling, although previous studies have shown their potential in reducing losses. In addition, the linear model fit indicates that the explanatory factors are, in several cases, differently relevant across flood pathways. Next, Bayesian multilevel models were trained, which intrinsically incorporate uncertainties and allow for partial pooling (i.e. different groups of data, such as households affected by different flood pathways, can learn from each other), increasing the statistical power of the model. A new variable selection was performed for this new model approach, reducing the number of predictors from twelve to seven variables but keeping factors of the hazard, building, and preparedness, namely: water depth, contamination, duration, building area, PLPMs, insurance, and previous flood experience. The new model was trained not only across flood pathways but also across regions of Germany, divided according to general socioeconomic factors and insurance policies, and across flood events. The distinction across regions and flood events did not improve loss modelling and led to a large overlap of regression coefficients, with no clear trend or pattern. The distinction of flood pathways showed credibly distinct regression coefficients, leading to a better understanding of flood loss modelling and indicating one potential reason why model transferability has been challenging. Finally, new model structures were trained to include the possibility of compound inland floods (i.e. when multiple flood pathways coincide on the same affected asset). The dataset does not allow for verifying in which sequence the flood pathway waves occurred and predictor variables reflect only their mixed or combined outcome. Thus, two Bayesian models were trained: 1. a multi-membership model, a structure which learns the regression coefficients for multiple flood pathways at the same time, and 2. a multilevel model wherein the combination of coinciding flood pathways makes individual categories. The multi-membership model resulted in credibly different coefficients across flood pathways but did not improve model performance in comparison to the model assuming only a single dominant flood pathway. The model with combined categories signals an increase in impacts after compound floods, but due to the uncertainty in model coefficients and estimates, it is not possible to ascertain such an increase as credible. That is, with the current level of uncertainty in differentiating the flood pathways, the loss estimates are not credibly distinct from individual flood pathways. To overcome the challenges faced, non-linear or mixed models could be explored in the future. Interactions, moderation, and mediation effects, as well as non-linear effects, should also be further studied. Loss data collection should regularly include preparedness indicators, and either data collection or hydraulic modelling should focus on the distinction of coinciding flood pathways, which could inform loss models and further improve estimates. Flood pathways show distinct (financial) impacts, and their inclusion in loss modelling proves relevant, for it helps in clarifying the different contribution of influencing factors to the final loss, improving understanding of the damaging process, and indicating future lines of research.},
  language  = {en}
}
@misc{BuschingKrahe2015,
  author    = {Busching, Robert and Krah{\´e}, Barbara},
  title     = {The girls set the tone},
  series = {Postprints der Universit{\"a}t Potsdam : Humanwissenschaftliche Reihe},
  journal   = {Postprints der Universit{\"a}t Potsdam : Humanwissenschaftliche Reihe},
  number    = {401},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-404831},
  pages     = {18},
  year      = {2015},
  abstract  = {In a four-wave longitudinal study with N = 1,321 adolescents in Germany, we examined the impact of class-level normative beliefs about aggression on aggressive norms and behavior at the individual level over the course of 3 years. At each data wave, participants indicated their normative acceptance of aggressive behavior and provided self-reports of physical and relational aggression. Multilevel analyses revealed significant cross-level interactions between class-level and individual-level normative beliefs at T1 on individual differences in physical aggression at T2, and the indirect interactive effects were significant up to T4. Normative approval of aggression at the class level, especially girls' normative beliefs, defined the boundary conditions for the expression of individual differences in aggressive norms and their impact on physically and relationally aggressive behavior for both girls and boys. The findings demonstrate the moderating effect of social norms on the pathways from individual normative beliefs to aggressive behavior in adolescence.},
  language  = {en}
}
@article{BuschingKrahe2015,
  author    = {Busching, Robert and Krah{\´e}, Barbara},
  title     = {The Girls Set the Tone: Gendered Classroom Norms and the Development of Aggression in Adolescence},
  series = {Personality and social psychology bulletin},
  volume    = {41},
  journal   = {Personality and social psychology bulletin},
  number    = {5},
  publisher = {Sage Publ.},
  address   = {Thousand Oaks},
  issn      = {0146-1672},
  doi       = {10.1177/0146167215573212},
  pages     = {659 -- 676},
  year      = {2015},
  abstract  = {In a four-wave longitudinal study with N = 1,321 adolescents in Germany, we examined the impact of class-level normative beliefs about aggression on aggressive norms and behavior at the individual level over the course of 3 years. At each data wave, participants indicated their normative acceptance of aggressive behavior and provided self-reports of physical and relational aggression. Multilevel analyses revealed significant cross-level interactions between class-level and individual-level normative beliefs at T1 on individual differences in physical aggression at T2, and the indirect interactive effects were significant up to T4. Normative approval of aggression at the class level, especially girls' normative beliefs, defined the boundary conditions for the expression of individual differences in aggressive norms and their impact on physically and relationally aggressive behavior for both girls and boys. The findings demonstrate the moderating effect of social norms on the pathways from individual normative beliefs to aggressive behavior in adolescence.},
  language  = {en}
}