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United States Department of Agriculture

Agricultural Research Service


item Gimenez, Daniel
item Rawls, Walter
item Lauren, Julie

Submitted to: Geoderma
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 8/12/1999
Publication Date: N/A
Citation: N/A

Interpretive Summary: None.

Technical Abstract: Variability of saturated hydraulic conductivity, ksat, increases when sample size decreases implying that saturated water flow might be a scaling process. Statistical properties of scaling distributions observed at different resolutions can be related by a power-law function, with the exponent being single- (single scaling) or multi-valued (multiscaling). Our objective was to investigate scaling characteristics of ksat using the method of the moments applied to measurements obtained with different sample sizes. We analyzed three data sets of ksat measured in: (1) cores with small diameters and increasing length spanning a single soil horizon, (2) columns with increasing cross sectional area constant length, and (3) columns with increasing cross sectional area and length, the longest column spanning three soil horizons. Visible porosity (macroporosity) was traced on acetate transparency sheets prior to measurement of ksat in situations (2). Six moments of the distributions of ksat were estimated assuming normal and log-normal distribution of observations. Scaling of ksat was observed in all three data sets. Simple scaling was only found when flux occurred in small cross sectional areas of a simple soil horizon (data set (1)). Moments of a normal distribution were multiscaling whereas the ones from a log-normal distributions were simple scaling when larger soil volumes were involved in the flux process (data sets (2) and (3)). Moments of macroporosity distributions showed multiscaling characteristics, with exponents slightly different than those from ksat distributions. Saturated flow in soil is most likely multiscaling because of several sources of flux control. The methods of the moments is promising for investigating spatial variability and scaling.

Last Modified: 10/18/2017
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