Summary
This review synthesises challenges common to flood and drought prediction across multiple timescales (daily forecasts, seasonal predictions, and long-term projections). Although droughts and floods are typically modelled independently, the authors argue they share related approaches and common obstacles. The paper proposes that addressing challenges in data availability, process understanding, modelling frameworks, and human–water interactions—including non-stationary conditions and compounding drivers—will improve predictions and reduce societal impacts of extreme hydrological events.
UK applicability
The identified challenges in modelling non-stationary flood and drought behaviour are directly relevant to UK water management, where climate change is altering extremes frequency and intensity. The review's emphasis on joint assessment of droughts and floods, improved data integration, and stakeholder communication aligns with UK policy priorities for water security and resilience planning.
Key measures
Qualitative assessment of prediction challenges; categorisation of methodological and data barriers; discussion of modelling approaches
Outcomes reported
The review identifies four interrelated categories of challenges in flood and drought prediction: data availability and event definition; process understanding including multivariate characteristics and non-stationarities; modelling across frequency, stochastic, hydrological and hydraulic frameworks; and human–water interactions. The paper proposes tractable approaches to address these challenges, including new data sources, joint frameworks for studying droughts and floods, and improved stakeholder engagement.
Topic tags
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