Publications des scientifiques de l'IRD

Getirana A., Boone A., Peugeot Christophe, ALMIP Working Group, Cappelaere Bernard, Demarty Jérome, Séguis Luc, Velluet Cecile, Chaffard Véronique, Galle Sylvie, Lebel Thierry, Quantin Guillaume, Mougin Eric, et al. (2017). Streamflows over a West African Basin from the ALMIP2 model ensemble. Journal of Hydrometeorology, 18 (7), p. 1831-1845. ISSN 1525-755X.

Titre du document
Streamflows over a West African Basin from the ALMIP2 model ensemble
Année de publication
2017
Type de document
Article référencé dans le Web of Science WOS:000405926700002
Auteurs
Getirana A., Boone A., Peugeot Christophe, ALMIP Working Group, Cappelaere Bernard, Demarty Jérome, Séguis Luc, Velluet Cecile, Chaffard Véronique, Galle Sylvie, Lebel Thierry, Quantin Guillaume, Mougin Eric, et al.
Source
Journal of Hydrometeorology, 2017, 18 (7), p. 1831-1845 ISSN 1525-755X
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.
Plan de classement
Sciences fondamentales / Techniques d'analyse et de recherche [020] ; Hydrologie [062]
Description Géographique
MALI ; NIGER ; BENIN
Localisation
Fonds IRD [F B010070366]
Identifiant IRD
fdi:010070366
Contact