Leroux D. J. auteur aut IRD Pellarin T. auteur aut IRD Vischel T. auteur aut IRD Cohard J. M. auteur aut IRD Gascon T. auteur aut IRD Gibon F. auteur aut IRD Mialon A. auteur aut IRD Galle Sylvie auteur aut IRD Peugeot Christophe auteur aut IRD Séguis Luc auteur aut IRD text journalArticle eng text/pdf reformatted digital access Precipitation forcing is usually the main source of uncertainty in hydrology. It is of crucial importance to use accurate forcing in order to obtain a good distribution of the water throughout the basin. For real-time applications, satellite observations allow quasi-real-time precipitation monitoring like the products PERSIANN (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks, TRMM (Tropical Rainfall Measuring Mission) or CMORPH (CPC (Climate Prediction Center) MORPHing). However, especially in West Africa, these precipitation satellite products are highly inaccurate and the water amount can vary by a factor of 2. A post-adjusted version of these products exists but is available with a 2 to 3 month delay, which is not suitable for real-time hydrologic applications. The purpose of this work is to show the possible synergy between quasi-real-time satellite precipitation and soil moisture by assimilating the latter into a hydrological model. Soil Moisture Ocean Salinity (SMOS) soil moisture is assimilated into the Distributed Hydrology Soil Vegetation Model (DHSVM) model. By adjusting the soil water content, water table depth and streamflow simulations are much improved compared to real-time precipitation without assimilation: soil moisture bias is decreased even at deeper soil layers, correlation of the water table depth is improved from 0.09-0.70 to 0.82-0.87, and the Nash coefficients of the streamflow go from negative to positive. Overall, the statistics tend to get closer to those from the reanalyzed precipitation. Soil moisture assimilation represents a fair alternative to reanalyzed rainfall products, which can take several months before being available, which could lead to a better management of available water resources and extreme events. specialized BENIN 062 072 126 20 7 2827-2840 2016 1027-5606 https://www.documentation.ird.fr/hor/fdi:010067766 10.5194/hess-20-2827-2016 1027-5606 [F B010067766] https://www.documentation.ird.fr/hor/fdi:010067766 https://horizon.documentation.ird.fr/exl-doc/pleins_textes/divers16-09/010067766.pdf IRD - Base Horizon / Pleins textes 2016-09-30 2017-08-23 fdi:010067766 fre