Abstract
As a first step of the international Global Soil Wetness Project (GSWP), several state-of-the-art land surface models were recently forced by 1° × 1° atmospheric analyses and observations to obtain global soil moisture climatologies over the 1987–1988 period. Besides the 6-hourly atmospheric forcing, the models also used common boundary conditions (soil and vegetation parameters), also drawn from the ISLSCP Initiative I dataset. While very few in situ observations are available to validate the soil moisture fields, the simulated runoff can be compared with river discharge measurements. This strategy is employed here to assess the quality of GSWP simulations based on the ISBA land surface model. The ISBA runoff is transformed into 1° × 1° gridded stream flows by using the TRIP river routing model. The focus is on the Amazon basin where all models participating in GSWP showed a strong underestimation in the annual runoff and a significant lag in the annual cycle of the runoff. A sample of 31 gauging stations is selected to validate the gridded runoff simulated by ISBA. Sensitivity tests have been performed, that suggest that deficiencies in both the precipitation forcing and the boundary conditions provided by ISLSCP contribute to the poor simulation of the Amazon water balance. The use of alternative precipitation, soil and vegetation datasets allows ISBA to produce a more realistic annual runoff, although the amplitude of the annual cycle remains exaggerated at the downstream gauging station of Obidos. Among these experiments, the simulation leading to the best annual runoff has been used as a reference to test simple modifications in the TRIP river routing model. Tuning the parameters of TRIP or increasing the resolution of the river channel network is not sufficient to improve the annual cycle of the simulated discharge. New developments are necessary to deal more explicitly with the floodplain inundation that occurs during the rainy season over the Amazon basin, and to derive a geographically variable and time-evolving stream flow velocity. In future, considerable efforts are needed to provide more reliable global land surface and forcing datasets in the continuation of GSWP, in order to validate more efficiently the land surface models and thereby to produce more realistic soil moisture climatologies.
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