Compound hot-dry and the dry-wet seesaw transition are extreme meteorological events driven by the interaction between rainfall, temperature and soil moisture. Using data covering New Zealand for the 1950-2021 period we model these interactions using both copulas and single variables. The copula approach detects more frequent and intense events, particularly across eastern regions of the country, while also better representing the event drivers and improving our understanding of their risk.

Heavy rainfall over short periods can cause floods and damage in cities, yet rainfall is often only measured daily. We developed a new method to generate realistic hourly rainfall data from daily values, using information from many weather stations in Spain and the United States. Our approach reproduces extreme rainfall more accurately than existing methods, helping to improve flood risk studies, infrastructure design, and climate impact assessments.

River flow (streamflow) behaviour varies across Europe and is shaped by climate and landscape. Using data from more than 7000 European catchments, we identified 10 hydrological response types based on flow magnitude, timing, and seasonality. At the continental scale, streamflow behaviour is mainly driven by climate, but landscape features are equally or more influential in several regions. These results show that streamflow behaviour emerges from the combined effects of climate and landscape.

Improving how rainfall-runoff models estimate evapotranspiration is key to better reproducing water partitioning under current conditions, and will increase model realism under future changing conditions. We tested how well different conceptual rainfall-runoff model equations simulate evapotranspiration using Australian catchment and flux tower data. We found one equation consistently worked better than the others. However, even this equation had flaws, pointing to missing vegetation processes.