Disaster impact forecasting framework for multi hazard disaster risk assessment

Yeganegi, R. ORCID: https://orcid.org/0000-0003-4109-0690 & Komendantova, N. ORCID: https://orcid.org/0000-0003-2568-6179 (2025). Disaster impact forecasting framework for multi hazard disaster risk assessment. In: 19th International Joint Conference on Computational and Financial Econometrics (CFE) and Computational and Methodological Statistics (CMStatistics), 13-15 December 2025, London, UK.

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Abstract

Disaster risk management relies largely on the estimated disaster impact under different scenarios, as well as the estimation of the disaster probability itself. The results of such disaster risk estimation models are inputs to disaster risk management strategy building and decision-making. Decision-makers need an estimation of the risk metrics under each scenario to determine the best combination of strategies for managing disaster risk. Various studies provided models for estimating the probabilistic behavior of the disastrous event. However, the vast diversity of risk metrics and risk drivers poses a challenge in forecasting the disaster impact and consequently, the disaster risk. Furthermore, disaster risk drivers (e.g., public trust, social vulnerability, socio-economic variables, climate change) have a dynamic nature, and it is crucial to consider their dynamic structure when estimating the disaster impact. In other words, the impact should be estimated considering the interactions among the risk metrics as well as adapting to the changes in risk drivers. Furthermore, the comprehensive risk assessment relies on the distribution estimation of the disaster impacts. The purpose is to formulate the problem of the disaster impact estimation in relation to the disaster risk assessment and decision-making, and propose a framework for forecasting the disaster impact. The proposed solution extends the commonly used value at risk (VaR) concept for disaster impact forecasting.

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