Augmenting a socio-hydrological flood risk model for companies with process-oriented loss estimation

Socio-hydrological flood risk models describe the temporal co-evolution of coupled human-flood systems. However, most models oversimplify the flood loss processes and do not consider companies' substantial contribution to total losses. This work presents a socio-hydrological flood risk model for companies that focuses on changes in vulnerability. In addition, we augment the socio-hydrological model with a process-oriented, sector-specific loss model in order to capture damage processes more realistically. In a case study, we simulate the historical flood risk dynamics of companies in the floodplain of Dresden, Germany, over the course of 120 years. Our analysis suggests that the companies in Dresden increase their exposure more cautiously than private households and decrease their vulnerability more actively through private precaution. The augmentation, consisting of informative predictors, a refined probabilistic model, and the incorporation of additional data, improves the accuracy and reliability of the flood loss estimates and reduces their uncertainty.