A STOCHASTIC APPROACH TO STUDYING THE INFLUENCE OF THE SPATIAL VARIABILITY OF SOIL HYDRAULIC-PROPERTIES ON SURFACE FLUXES, TEMPERATURE AND HUMIDITY

Citation
I. Braud et al., A STOCHASTIC APPROACH TO STUDYING THE INFLUENCE OF THE SPATIAL VARIABILITY OF SOIL HYDRAULIC-PROPERTIES ON SURFACE FLUXES, TEMPERATURE AND HUMIDITY, Journal of hydrology, 165(1-4), 1995, pp. 283-310
Citations number
60
Categorie Soggetti
Engineering, Civil","Water Resources","Geosciences, Interdisciplinary
Journal title
ISSN journal
00221694
Volume
165
Issue
1-4
Year of publication
1995
Pages
283 - 310
Database
ISI
SICI code
0022-1694(1995)165:1-4<283:ASATST>2.0.ZU;2-L
Abstract
The assessment of mass and energy fluxes at the soil-biosphere-atmosph ere interface is a key point for the improvement and reliability of cl imate model predictions. At the local scale, numerous models have been developed to predict surface fluxes, These models are generally deter ministic and the extension of their results to larger scales, such as the catchment scale or the scale of an atmospheric or climatic model m esh, is greatly complicated by the large variability of surface proper ties. To address this issue, stochastic approaches have been proposed to enable prediction of fluxes in terms of probability density functio ns. This paper is concerned with the influence of the spatial variabil ity of soil hydraulic properties. This variability is expressed throug h one parameter, the scale factor for which a log-normal distribution is assumed. Values of the scale factor, drawn from this distribution, are introduced into a unidimensional model, called SiSPAT, which descr ibes the soil-plant-atmosphere coupled heat and water transfers. Two l and uses are considered: a bare soil and a rather densely vegetated on e for which the same forcing is applied over 7 days. Comparison of the two cases shows that the vegetation tends to smooth the influence of the spatial variability of soil properties limiting the number of obse rvations required to estimate a spatial mean with a prescribed degree of accuracy. Comparison of the deterministic and stochastic solutions also shows that the former approach leads to a bias for the bare soil case, the differences between the two being almost negligible in the p resence of vegetation.