Extreme Value Theory for Climate-Related Environmental Disaster Risk Analysis: A Review of Urban Impacts and Vulnerabilities

Abstract

Climate change is a major contributing factor to environmental disasters, frequently increase the risk and vulnerability of urban areas to various hazards. Appropriate methods for analysing climate change indicators are essential for developing risk management strategies in urban areas. Extreme Value Theory (EVT) provides a robust statistical framework for modelling and predicting rare, high impact events, making it essential for assessing climate-related risks. This review examines the application of EVT in analysing environmental disasters triggered by climate change, focusing on the Block Maxima (BM) method and Peak Over Threshold (POT) approaches, with an emphasis on assessing urban impacts and vulnerabilities. Through a comprehensive literature review, this paper highlights EVT’s growing importance in predicting extreme climate events in cities, underscoring its value for researchers, policymakers, and disaster risk managers that are important for urban adaptation strategies. The findings confirm the effectiveness of EVT in reliably modelling and predicting extreme environmental events, indicating its competence to obtain accurate risk estimates that reflect observed extreme events through its return period calculations. The BM is beneficial for determining absolute extremes, while POT provides more detail about threshold-exceeding extreme events. EVT describes an essential framework for modelling extreme environmental disasters exacerbated by climate change, enabling the development of adaptive strategies to reduce urban impacts and vulnerabilities.