The present research focuses on evaluating the prediction capacity of the hydrological flood model called Rainfall-Runoff-Inundation (RRI), using observed data and satellite remote sensing in order to produce flood maps of the Alto Huallaga basin in Peru. The RRI model required as input data the topographic map of the region (we use FABDEM product), information on vegetation cover and land use obtained from FAO-UNESCO, and precipitation and evapotranspiration data from the Peruvian Interpolation data of the SENAMHI's Climatological and Hydrological observations (PISCO).

The RRI model was evaluated for the 2014-2019 period, previously carrying out a sensitivity analysis process of the parameters and estimating the geometric parameters of the RRI model using information from satellite altimetry and remote sensing. The hydrological part of the model is calibrated at 2 hydrological stations on the Huallaga River (Tingo María and Tocache), obtaining acceptable results with Kling-Gupta (KGE) coefficients above 0.7 for both stations during the calibration and validation period. In addition, satellite images of the MODIS product were used for the part of flood maps, compared with the results of the RRI (flood areas), obtaining acceptable statistics when comparing the resulting images.

This work is part of the results of the Enandes project (Enhancing Adaptive Capacity of Andean Communities through Climate Services) implemented in Peru that seeks to improve climate services in Peru with an emphasis on disaster risk management in Andean basins regarding floods.