Unravelling compound risks of hydrological extremes in a changing climate: Typology, methods and futures

TL;DR

This paper reviews the increasing occurrence of compound hydrological extremes in a changing climate, proposing a framework for risk assessment and emphasizing the importance of socioeconomic factors and interdisciplinary approaches for effective climate action.

Contribution

It introduces a typology of compound hydrological events, a probabilistic risk framework, and discusses the potential of AI for trend identification, integrating socioeconomic considerations.

Findings

Identified four types of compound hydrological events.

Proposed a probabilistic framework for risk quantification.

Highlighted the role of AI and socioeconomic factors in climate risk management.

Abstract

We have witnessed and experienced increasing compound extreme events resulting from simultaneous or sequential occurrence of multiple events in a changing climate. In addition to a growing demand for a clearer explanation of compound risks from a hydrological perspective, there has been a lack of attention paid to socioeconomic factors driving and impacted by these risks. Through a critical review and co-production approaches, we identified four types of compound hydrological events based on autocorrelated, multivariate, and spatiotemporal patterns. A framework to quantify compound risks based on conditional probability is offered, including an argument on the potential use of generative Artificial Intelligence (AI) algorithms for identifying emerging trends and patterns for climate change. Insights for practices are discussed, highlighting the implications for disaster risk reduction and knowledge co-production. Our argument centres on the importance of meaningfully considering the socioeconomic contexts in which compound risks may have impacts, and the need for interdisciplinary collaboration to effectively translate climate science to climate actions.