Figure. Relation between direct damage costs by “Source” (left column), “Hazard identification” (middle column) and “Affected element” (right column) triggered by Gloria Storm 2020 (Pantaleoni et al., 2025).
Núria Pantaleoni, Marcel Hürlimann and Nieves Lantada
UPC – Universitat Politècnica de Catalunya
One key lesson from recent events, such as Storm Gloria, which severely affected Catalonia and other parts of Spain in 2020, is that public-sector compensation data is often missing from disaster loss databases. While insured losses are relatively easy to quantify, many assets, particularly public infrastructure, community resources, and environmental systems, are typically uninsured and underreported. Documenting how governments allocate funds to repair and rebuild these assets provides a more complete picture of a disaster’s financial burden.
Beyond simple accounting, these loss databases also help us understand how the recovery process works. By tracking public and private disaster aftermath funding, databases can reveal patterns in financial responsibility, sectoral focus, and procedural efficiency. This information is invaluable for evaluating in how resources are prioritized and distributed ensuring that future compensation mechanisms are both fair and effective.
Another important insight is that disasters are rarely single-hazard events. Multi-hazard events, like Storm Gloria, where flooding, landslides, storms, and other hazards occur simultaneously or sequentially, create complex, cascading impacts across sectors. Most traditional loss databases focus on single hazards, which can obscure these interactions. For effective disaster risk management, databases must evolve to capture not just the type of hazard but also its timing, location, intensity, and interactions with other hazards.
Despite the clear necessity of these databases, the process of compiling them remains a formidable challenge. Reporting on multi-hazard is not a straightforward task, and consequently, compiling reliable loss databases is even more complex. Information on damages and compensation is often highly dispersed across multiple institutions, administrative levels, and documentation formats. In addition, there is significant diversity in how compensation is calculated, with different agencies using their own evaluation criteria, methodologies, and accounting systems. As a result, building comprehensive and standardized disaster loss databases requires considerable effort in data collection and harmonization.
Finally, we have to recognize that we are still far from achieving a fully comprehensive capture of disaster damages. Most loss databases focus primarily on direct, tangible costs that can be verified through repair and reconstruction investments. However, disasters also generate a wide range of indirect impacts that are far more difficult to quantify in economic terms. These include business interruptions, long-term environmental degradation, social disruption, and cascading effects across interconnected sectors. Because these impacts are harder to measure and often emerge over longer timeframes, they are rarely fully reflected in loss datasets.
In short, loss databases are a foundational element of modern disaster risk management. Their value extends far beyond simple accounting, they provide evidence for planning, highlight vulnerabilities, and support the design of more resilient societies. Investing in comprehensive, standardized, and multi-hazard databases is crucial if we want to understand the full consequences of natural disasters and develop strategies that minimize their human and economic costs.
References
Pantaleoni Reluy, N., Hürlimann, M., and Lantada, N.: How are public compensation efforts implemented in multi-hazard events? Insights from the 2020 Gloria storm in Catalonia, Nat. Hazards Earth Syst. Sci., 25, 3483–3504, https://doi.org/10.5194/nhess-25-3483-2025, 2025.
