Numercial Weather Prediction performance assessment using a distributed hydrological model

SEBASTIAN LOPEZ; MARIA EUGENIA DILLON; PAULA SOLEDAD MALDONADO; ARATA AMEMIYA; JUAN RUIZ; YANINA GARCÍA SKABAR; SHIGENORI OTSUKA; DAIKI KAKINUMA; KENTARO AIDA; TOMOKI USHIYAMA; MATIE CANCELADA; DAICHI KITAHARA; MARTIN RUGNA; MARIANO RE; CARLOS MARCELO GARCÍA; CELESTE SAULO; TAKEMASA MIYOSHI

Workshop; 6th Workshop on Mesoscale Modeling; 2023

Urban floods and intense precipitation are highly destructive natural disasters. In the context ofclimate change, it is imperative to undertake novel measures for mitigating their impact onvulnerable communities. The PREVENIR initiative started in 2022, with the objective of developingan early warning system centered on the impacts caused by heavy rainfall and urban floods, focusingon two vulnerable urban basins in Argentina. In this study, the performance of two numerical weatherprediction (NWP) models using different initial and boundary conditions strategies was assessed byemploying forecasted precipitation as input for a distributed hydrological model in a heavy rainfallevent occurred on the Suquía River (SR) basin in a mountainous region of the Córdoba Province.