PARATUS Forensic Analysis Approach of Past Disasters to Develop Quantifiable Multi-Hazard Impact Scenarios

Understanding complex interactions between hazardous events and dynamic risk conditions in today’s geographies requires carefully analyzing the historical data. Learning from the past will contribute to developing models and multi-hazard risk scenarios. Current disaster databases often concentrate on individual hazards and their direct consequences, lacking the ability to attribute impacts resulting from hazard interactions or adequately depict risk pathways from root causes to ensuing losses. Although the Post Disaster Needs Assessment (PDNA) approach is widely used to assess physical damages, economic losses, and recovery costs following major disasters, it proves less straightforward in estimating impacts and losses for future events.

In forensic analysis, when examining post-event conditions, the investigator formulates hypotheses regarding the pre-event conditions and gathers relevant evidence and facts. Forensic investigations of disasters, i.e. FORIN, highlight the necessity to characterize systemic, structural root causes and risk drivers at global, national, and local levels. While historical disaster data is indispensable, acknowledging the dynamic nature of economic, social, and environmental conditions, at the same time it challenges the prevailing notion that "the past is the key to the future."

Within the realm of disaster risk literature, several forensic analysis approaches are present. In the context of the PARATUS project's development of a forensic approach, three specific methodologies are incorporated: Investigation of Disasters (FORIN), Post Event Review Capability (PERC), and Detecting Disaster Root Causes (DKKV). PARATUS approach applies a combination of these three forensic approaches to a set of learning case studies drawn from selected past disaster events to analyze and navigate the complexity of disaster impacts across diverse contexts.

In PARATUS, we employ forensic analysis alongside historical datasets and earth observation across 18 learning case studies. Three primary criteria guide the selection of these case studies: 1) featuring hazard interactions representative of the European context; 2) having an impact on diverse sectors; and 3) global scenarios that could potentially occur in Europe.