Spatial variability of surface properties and estimation of surface fluxes of a savannah

Abstract

During the HAPEX-Sahel experiment in 1992, a data set including atmospheric forcing, soil temperature at several depths, surface fluxes and surface soil moisture from 0 to 15 cm was collected on a degraded fallow savannah over a period of 18 days. The SiSPAT SVAT model was calibrated using this data set to provide a realistic reference set of parameters. The sensitivity of surface fluxes to the specification of surface properties based on this reference set of parameters was quantified focusing on runoff, evapotranspiration and soil moisture at the field scale. Runoff and latent heat flux, predominantly bare soil evaporation, were found to be the most sensitive processes in relation to soil parameters. For transpiration, even with such a sparse vegetation, leaf area index was the most sensitive factor. A stochastic approach was used to analyze the sensitivity of surface fluxes to the spatial variability of surface parameters. For a variation of ±50% of the parameters, no significant bias was obtained between the mean of the stochastic simulations and the 1-D simulation performed with the median values of the parameters. The analysis indicates that the variations of the components of the water budget are linearly related. For larger variations of the parameters, the bias is significant; therefore, simple aggregation rules fail to capture the nonlinearities induced by water transfer into the soil. When diurnal cycles are considered, the standard deviation of bare soil evaporation and surface soil moisture was found to be maximum for the intermediate wetting range. For this period, it would be valuable to parameterize the spatial variability of surface properties into larger scale models. Finally, the SiSPAT model, which solves equations derived from the Richards equation [Richards, L.A., 1931. Capillary conduction of liquids through porous mediums. J. Phys. 1, pp. 318–333.]. for soil water distribution is shown to be very sensitive to the specification of soil parameters. This result would hold for similar models, showing that the Richards equation should be used with caution within large-scale models if a robust estimation of the long- term water budget is to be obtained.