Getirana A. auteur aut IRD Boone A. auteur aut IRD Peugeot Christophe auteur aut IRD ALMIP Working Group auteur aut IRD Cappelaere Bernard auteur aut IRD Demarty Jérome auteur aut IRD Séguis Luc auteur aut IRD Velluet Cecile auteur aut IRD Chaffard Véronique auteur aut IRD Galle Sylvie auteur aut IRD Lebel Thierry auteur aut IRD Quantin Guillaume auteur aut IRD Mougin Eric auteur aut IRD et al. auteur aut IRD text journalArticle eng text/pdf born digital access Comparing streamflow simulations against observations has become a straightforward way to evaluate a land surface model's (LSM) ability in simulating water budget within a catchment. Using a mesoscale river routing scheme (RRS), this study evaluates simulated streamflows over the upper Oueme River basin resulting from 14 LSMs within the framework of phase 2 of the African Monsoon Multidisciplinary Analysis (AMMA) Land Surface Model Intercomparison Project (ALMIP2). The ALMIP2 RRS (ARTS) has been used to route LSM outputs. ARTS is based on the nonlinear Muskingum-Cunge method and a simple deep water infiltration formulation representing water-table recharge as previously observed in that region. Simulations are performed for the 2005-08 period during which ground observations are largely available. Experiments are designed using different ground-based rainfall datasets derived from two interpolation methods: the Thiessen technique and a combined kriging-Lagrangian methodology. LSM-based total runoff (TR) averages vary from 0.07 to 1.97mmday(-1), while optimal TR was estimated as; 0.65mmday(-1). This highly affected the RRS parameterization and streamflow simulations. Optimal Nash-Sutcliffe coefficients for LSM-averaged streamflows varied from 0.66 to 0.92, depending on the gauge station. However, individual LSM performances show a wider range. A more detailed rainfall distribution provided by the kriging-Lagrangian methodology resulted in overall better streamflow simulations. The early runoff generation related to reduced infiltration rates during early rainfall events features as one of the main reasons for poor LSM performances. specialized MALI NIGER BENIN 062 020 18 7 1831-1845 2017 1525-755X https://www.documentation.ird.fr/hor/fdi:010070366 10.1175/jhm-d-16-0233.1 1525-755X [F B010070366] https://www.documentation.ird.fr/hor/fdi:010070366 https://www.documentation.ird.fr/intranet/publi/2017/08/010070366.pdf Accès réservé (Intranet de l'IRD) IRD - Base Horizon / Pleins textes 2017-09-05 2023-07-11 fdi:010070366 fre