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Extreme hydro-meteorological events are among the primary drivers of hydrologic and geomorphic hazards, posing an increasing threat to societies worldwide. The combined effects of climate change, and increased exposure and vulnerability in hazard-prone areas have led to a continuous rise in disaster risk.This contribution addresses some key challenges in forecasting and managing hydro-meteorological processes across two main interrelated contexts—data-rich or data-scarce regions—which, despite their known differences, share common issues of scale, complexity, and uncertainty in hazard–society interactions.In both environments, local-scale factors such as small-scale processes, and human disturbances interact with regional climate variability and large-scale atmospheric drivers to shape evolving hydro-geomorphic processes. At the same time, decisions happen at national, basin, or urban scales, often creating cross-scale mismatches between where hydro-meteorological processes materialize and where decisions are taken.The presentation discusses how Earthcasting-oriented approaches, such as the integration of remote sensing, reanalysis products, crowd-sourced information, and qualitative socio-economic data, can partially address these gaps. While these data sources introduce new uncertainties, they also provide opportunities to improve awareness and support process-based forecasts and decision-making in regions where conventional data are unavailable, or they might not be enough.Building on recent advances in technology but also risk science, this talk advocates for integrated assessment frameworks that explicitly account for cross-scale interactions, feedbacks, and data limitations, also highlighting implications for communication strategies. Ultimately, advancing such integrated approaches is essential for translating scientific knowledge into an added social value of the predictability of Earth surface processes.