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000038889 084__ $$2WoS$$aEnvironmental Sciences
000038889 084__ $$2WoS$$aSoil Science
000038889 084__ $$2WoS$$aWater Resources
000038889 1001_ $$0P:(DE-HGF)0$$ade Rooij, G. H.$$b0
000038889 245__ $$aJoint Distributions of the Unsaturated Soil Hydraulic Parameters and their Effect on Other Variates
000038889 260__ $$aMadison, Wis.$$bSSSA$$c2004
000038889 300__ $$a947 - 955
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000038889 440_0 $$010301$$aVadose Zone Journal$$v3$$x1539-1663
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000038889 520__ $$aVariability in the unsaturated soil hydraulic properties affects the behavior of water and solutes in the subsurface. When these properties are described by parametric functions, subsurface heterogeneity can be quantified by variations in the parameters of these functions. We propose a procedure to characterize systematically the statistical properties of each soil hydraulic parameter and the parameter correlations First, the parameter with the best-defined probability distribution function (pdf) is identified. Curvilinear regression analysis identifies transformations that linearize the relationships between this reference parameter and the remaining parameters. From this we determine the joint pdf of the transformed parameters, which is then used to calculate the distributions of derived variates ( functions of the hydraulic parameters). The procedure is applied to the hydraulic parameters of 140 samples in total taken from two layers of an agricultural soil profile. We developed analytical expressions for the pdfs of derived variates ( hydraulic conductivities and water contents at heads between 0 and - 5000 cm) from the multivariate parameter pdf. The numerical integration required to evaluate these expressions proved extremely cumbersome, thus reducing the robustness of the analytical expressions. We therefore performed a Monte Carlo simulation from which we determined the first two moments, as well as the skewness and excess of the derived variates. The estimated mean and standard deviation of the derived variates generally agreed well with values determined directly from the soil samples. Skewness and excess were estimated less accurately. Both the derived analytical pdfs and the Monte Carlo simulation showed markedly nonsymmetrical pdfs, suggesting that it is generally insufficient to limit statistical to the first two moments only.
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000038889 7001_ $$0P:(DE-Juel1)VDB38957$$aKasteel, R. T. A.$$b1$$uFZJ
000038889 7001_ $$0P:(DE-HGF)0$$aPapritz, A.$$b2
000038889 7001_ $$0P:(DE-HGF)0$$aFlühler, M. O.$$b3
000038889 773__ $$0PERI:(DE-600)2088189-7$$gVol. 3, p. 947 - 955$$p947 - 955$$q3<947 - 955$$tVadose zone journal$$v3$$x1539-1663$$y2004
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000038889 9141_ $$y2004
000038889 915__ $$0StatID:(DE-HGF)0010$$aJCR/ISI refereed
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