World’s deepest convective storms develop in southeastern South America (SESA), often resulting in flash floods over complex terrain. We implemented convection-permitting WRF model and its process-based hydrologic modeling component WRF-Hydro to design a flash flood forecasting framework leveraging observations from the RELAMPAGO field campaign. Our results highlight that ensemble hydrologic forecasts with atmospheric data assimilation can provide realistic flash flood prediction. SESA is also a ‘hot spot’ for land-atmosphere interactions, which play an important role in modulating the hydroclimate of this region. We use flux tower observations from RELAMPAGO and land-surface modeling to investigate how the land cover affects the sub-surface, surface and atmospheric fluxes of moisture and energy. Results indicate that the observed increases in streamflow and decreases in water table depth in this region are linked to the pronounced shifts in land cover from alfalfa to soy. Furthermore, a 250% increase in Bowen ratio might have a significant impact on the organized convections over SESA.
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