Hydrological extremes, such as droughts and floods, can trigger a complex web of compound and cascading impacts due to interdependencies between coupled natural and social systems. However, current decision-making processes typically only consider one impact and disaster event at a time, ignoring causal chains, feedback loops, and conditional dependencies between impacts. Analyses capturing these complex patterns across space and time are thus needed to better inform effective adaptation planning. This perspective paper aims to bridge this critical gap by presenting methods for assessing the dynamics of the multi-sector compound and cascading impacts (CCI) of hydrological extremes. We discuss existing challenges, good practices, and potential ways forward. Rather than pursuing a single methodological approach, we advocate for methodological pluralism. We see complementary roles for analyses building on quantitative (e.g. data-mining, systems modeling) and qualitative methods (e.g. mental models, qualitative storylines). We believe the data-driven and knowledge-driven methods provided here can serve as a useful starting point for understanding the dynamics of both high-frequency CCI and low-likelihood but high-impact CCI. With this perspective, we hope to foster research on CCI to improve the development of adaptation strategies for reducing the risk of hydrological extremes.

Disaster risks are the results of complex spatiotemporal interactions between risk components, impacts and societal response. The complexities of these interactions increase when multi-risk events occur in fragile contexts characterized by ethnic conflicts, unstable governments, and high levels of poverty, resulting in impacts that are larger than anticipated. Yet, only few multi-risk studies explore human-environment interactions, as most studies are hazard-focused, consider only a single type of multi-risk interaction, and rarely account for spatiotemporal variations of risk components. Here, we developed a step-wise, bottom-up approach, in which a range of qualitative and semi-quantitative methods was used iteratively to reconstruct interactions and feedback loops between risk components and impacts of consecutive drought-to-flood events, and explore their spatiotemporal variations. Within this approach, we conceptualize disaster risk as a set of multiple (societal and physical) events interacting and evolving across space and time. The approach was applied to the 2017-2018 humanitarian crises in Kenya and Ethiopia, where extensive flooding followed a severe drought lasting 18-24 months. The events were also accompanied by government elections, crop pest outbreaks and ethnic conflicts. Results show that (1) the fragile Kenyan and Ethiopian contexts further aggravated drought and flood impacts; (2) heavy rainfall after drought led to both an increase and decrease of the drought impacts dependent on topographic and socio-economic conditions; (3) societal response to one hazard may influence risk components of opposite hazards. A better understanding of the human-water interactions that characterize multi-risk events can support the development of effective monitoring systems and response strategies.