Spatial Variability of Soil Surface Properties and Consequences for the Annual and Monthly Water Balance of a Semiarid Environment (EFEDA Experiment)

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During the second phase of the European International Project on Climatic and Hydrological Interactions between Vegetation, Atmosphere, and Land Surface (ECHIDA) Field Experiment in a Desertification Threatened Area (EFEDA) the spatial variability of the soil water retention and hydraulic conductivity characteristics of layers at 2–12- and 17–27-cm depth was characterized. A simplified method, based on particle size distribution and simple infiltration tests, was used. It provided these characteristics at the nodes of a 1-km grid over 10 × 10 km2 around the town of Tomelloso (Castilla–La Mancha, Spain). A total number of 78 sample points were used to address the problem of soil surface properties variability and its consequences on the monthly and annual water balance. The Simple Soil Plant Atmosphere Transfer model (SiSPAT) 1D Soil–Vegetation–Atmosphere Transfer (SVAT) model was run with a 1-yr climatic forcing for the 78 soil profiles until equilibrium was reached. As no runoff was generated, the spatial variability of the water budget components only concerned soil evaporation, transpiration, and deep drainage. It was found that (i) the choice of the type of boundary condition at the bottom of the soil profile was greatly influencing the final variability, (ii) the variability of transpiration was the largest in situations of water stress for the vegetation, and (iii) soil evaporation was the most sensitive component when plants were well supplied with water. Various aggregation methods of soil surface parameters (use of the arithmetic mean, median of the parameters, or parameters associated to the average soil texture of the Clapp and Hornberger classification) were assessed. The use of median parameters in a single 1D simulation was found to provide the best agreement with the average of the 78 simulations performed for each grid cell using locally measured soil properties. The use of average soil texture parameters led to a significant bias, especially in the case of water stress.