Hydrological modeling of the Ilave river basin based on observed and satellite precipitation data, period 2011-2015, Puno, Peru

Precipitation datasets obtained from satellites can be useful in regions where rainfall is very heterogeneous, such as Peruvian Andes, which is usually poorly monitored. The objective of this study is to characterize the main hydrological variables and to understand the potential of precipitation estimates based on satellite datasets for hydrological modeling. This article evaluates the usefulness of estimated precipitation from observed (rain gauges) and satellites datasets (TMPA V7 and TMPA RT products of the TRMM satellite) as input in GR2M hydrological model to simulate monthly streamflows between 2011-2015 for the Ilave River basin located in the Peruvian Altiplano. The results from observational datasets indicate a deficit of streamflows due to decreased rainfall during wet season (~ 50%), whereas evapotranspiration is greater during dry season (~ 24%). Our results show that TMPA V7 has a higher similarity with respect to precipitation observed during wet season. Results also indicate that GR2M perform better with observed inputs and when TMPA-V7 precipitation datasets are used, while the opposite occurs with TMPA RT dataset. This poor performance of the hydrological model may be due to inadequate rainfall estimation in the water balance. © 2018 Instituto Mexicano de Tecnologia del Agua. All rights reserved.