Towards a global assessment of rooftop rainwater harvesting for hydro-meteorological hazard mitigation

Urban areas worldwide are increasingly exposed to hydro-meteorological extremes, including intense rainfall events and prolonged dry periods, which exacerbate flood hazards and water scarcity. Rooftop rainwater harvesting is widely discussed as a decentralised adaptation option that may contribute both to urban water supply and to the mitigation of hydrological extremes. However, existing assessments are largely limited to local case studies, and a consistent global-scale framework that links rooftop harvesting potential to hydro-meteorological hazard characteristics is still missing.In this contribution, we present a global assessment framework to quantify the potential of rooftop rainwater harvesting using high-resolution building footprint data in combination with reanalysis-based precipitation datasets. The approach integrates detailed global building roof areas (LoD1) with ERA5-Land precipitation data for the period 2014–2024. Mean monthly precipitation climatologies are used to estimate long-term average harvestable water volumes, while daily precipitation data are considered to characterise precipitation intensity, seasonality, and temporal continuity relevant for flood and drought mitigation. Capture efficiency is applied to account for system-level losses.By explicitly combining multiple precipitation timescales, the proposed framework enables a differentiated interpretation of rooftop rainwater harvesting potential under varying hydro-climatic regimes. While monthly precipitation provides a basis for estimating average water supply contributions, daily-scale metrics enable the assessment of conditions under which rooftop harvesting may be relevant for mitigating flood peaks or buffering dry spells. The study aims to provide a globally consistent, spatially explicit basis for evaluating rooftop rainwater harvesting as a complementary measure for increasing urban resilience to hydro-meteorological hazards.