Flood modeling through remote sensing datasets such as LPRM soil moisture and GPM-IMERG precipitation: A case study of ungauged basins across Morocco

North Africa is characterized by several ungauged basins, especially in Morrocco, where satellite products could be an alternative of the lack ground-based measurements. In this study, the Land Parameter Retrieval Model (LPRM) soil moisture and the Integrated Multi-Satellite Retrievals for Global Precipitation Measurement (GPM-IMERG) were used in flood modeling in Moroccan ungauged basins (Bourrous, Al Wiza, El Hallouf and Jamala). We started with comparing GPM-IMERG Early with ground measurements from five rain gauges. Next, the Soil Conservation Service - Curve Number (SCS-CN) was applied with ground precipitation measurements, LPRM and GPM-IMERG Early datasets to simulated flood events in a gauged basin, the Ghdat. Finally, this SCS-CN model was transposed with these satellite data sets validated to those ungauged basins in order to reproduce flood events. The results show that the GPM-IMERG Early is best with in situ measurements (correlation coefficient = 0.50; relative bias = 27.51%; probability of detection = 0.77; false alarm rate = 0.23), on a daily scale. The observed precipitation, LPRM and GPM-IMERG Early were performed well in validation to simulate floods in the Ghdat, where Nash-Sutcliffe criterion range from 0.43 and 0.98 using the SCS-CN model. For Bourrous, Al Wiza, El Hallouf and Jamala all flood events and hydrographs were reproduced by GPM-IMERG Early and LPRM products. Furthermore, LPRM products were validated against soil moisture measurements with a coefficient of determine R-2 between 0.72 and 0.84. The results of this work provided interesting insights for flood modeling using GPM-IMERG and LPRM satellite products in ungauged basins.