How are public compensation efforts implemented in multi-hazard events? Insights from the 2020 Gloria storm in Catalonia
Abstract. Natural disasters result in increasing economic losses worldwide. Existing loss databases primarily capture insured damages and therefore often overlook uninsured assets and public compensation efforts. This study examines the role of public-sector compensation in disaster recovery, using the multi-hazard 2020 Storm Gloria in Catalonia as a case study. By systematically collecting, classifying and analyzing public compensation data related to rebuilding and restoring the direct tangible damages, we provide new insights into financial aid distribution for disaster recovery. In addition, an analysis of single major hazards is performed to understand the event's frequency, as well as its temporal and spatial distribution. Finally, the damages caused by the storm are used to estimate losses based on the probability of the triggering hazard's occurrence. The findings reveal that fluvial and coastal hazards caused over 80 % of recorded damages, while meteorological and slope hazards contributed the remainder. Concerning the affected elements, infrastructure sustained the highest losses, followed by economic and social sectors. Rebuilding and reconstruction costs for Storm Gloria were split evenly between fully public and public-private partnerships efforts. Public funding prioritized community assets and critical infrastructure, using hazard-dependent cost assessments and standardized government procedures. Additionally, the study identifies potential multi-hazard municipalities where overlapping hazards intensified damages, highlighting the need for comprehensive disaster documentation. Results also indicate that fully public compensations lack a direct correlation with hazard probability, reflecting prioritization based on recovery needs rather than hazard frequency. The research underscores the critical role of public intervention in disaster risk management and calls for enhanced data standardization to improve loss estimation methodologies in multi-hazard scenarios. Finally, this study contributes to the improve our understanding on disaster loss assessment and provides a framework for future evaluations of government interventions in post-disaster recovery.