Abstract
Abstract. Soil physical properties play an important role in estimating soil water and energy fluxes. Many hydrological and land surface models (LSMs) use soil texture maps to infer these properties. Here, we investigate the impact of soil texture on soil water fluxes and storage at different scales using the ORCHIDEE (ORganizing Carbon and Hydrology in Dynamic EcosystEms) LSM, forced by several complex or globally uniform soil texture maps. At the point scale, the model shows a realistic sensitivity of runoff processes and soil moisture to soil texture and reveals that loamy textures give the highest evapotranspiration and lowest total runoff rates. The three tested complex soil texture maps result in similar water budgets at all scales, compared to the uncertainties of observation-based products and meteorological forcing datasets, although important differences can be found at the regional scale, particularly in areas where the different maps disagree on the prevalence of clay soils. The three tested soil texture maps are also found to be similar by construction, with a shared prevalence of loamy textures, and have a spatial overlap over 40 % between each pair of maps, which explains the overall weak impact of soil texture map change. A useful outcome is that the choice of the input soil texture map is not crucial for large-scale modelling, but the added value of more detailed soil information (horizontal and vertical resolution, soil composition) deserves further studies.
Highlights
Land surface models (LSMs) simulate water and energy fluxes at the interface between the land surface and the atmosphere
The Silt texture class is absent from the Reynolds and Zobler maps, while it is found in the SP-MIP map, but only to fill the no-data land points (3.3 %)
Using the ORCHIDEE LSM and different soil texture maps, we found that the model shows a realistic sensitivity of surface runoff, drainage and soil moisture to soil texture compared to experimental and field studies (Rawls et al, 1993; Osman, 2013)
Summary
Land surface models (LSMs) simulate water and energy fluxes at the interface between the land surface and the atmosphere. Look-up tables relate these broad texture classes to multiple soil properties, usually with one single central value for each class and property, as found in Cosby et al (1984) and Carsel and Parrish (1988) for the Clapp and Hornberger (1978) and Van Genuchten (1980) soil water models respectively In this framework, several global soil texture maps are used by LSMs, with different resolutions and soil texture distributions: based on the 1 : 5 000 000 FAO/UNESCO Soil Map of the World (FAO/UNESCO, 1971–1981), itself based on soil surveys defining 106 soil units, Zobler (1986) and Reynolds et al (2000) provided soil texture maps at a res-
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