HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS		QUICK SEARCH:   [advanced] Author: Keyword(s): Year:  Vol:  Page:

This Article Figures Only Full Text Free Full Text (PDF) Free Alert me when this article is cited Alert me if a correction is posted Services Similar articles in this journal Similar articles in ISI Web of Science Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Si, B. C. Articles by Bodhinayake, W. Search for Related Content PubMed Articles by Si, B. C. Articles by Bodhinayake, W. GeoRef GeoRef Citation Agricola Articles by Si, B. C. Articles by Bodhinayake, W. Related Collections Uncertainty Analysis Inverse Procedures/Parameter Estimation Hydraulic Conductivity

Soil Physics

Determining Soil Hydraulic Properties from Tension Infiltrometer Measurements

Fuzzy Regression

Dep. of Soil Science, University of Saskatchewan, Saskatoon, SK, Canada

^* Corresponding author (Bing.Si{at}usask.ca)

Tension infiltrometer measurements have been used to measure steady-state infiltration rates at applied tensions. The measurements can be used to determined soil hydraulic properties through linear or nonlinear regression. Such regression methods are often based on a few imprecise field measurements, and the traditional regression analysis may not yield valid estimates and reliable predictions. The objective of this study is to introduce fuzzy linear regression as an alternative to statistical regression analysis in determining hydraulic properties from tension infiltrometer measurements. Using a tension infiltrometer, in situ steady-state infiltration rates [q(h)] were measured at six different tensions (h) between 3 and 22 cm of water on silty loam and clay loam soils. Hydraulic properties (i.e., field saturated hydraulic conductivity, K_fs, and inverse macroscopic capillary length scale, _G) and their confidence intervals were estimated following the fuzzy least-square linear regression procedure with the minimum fuzziness criterion and linear least-squares method (traditional statistical method). Both calculation procedures yielded the same mean hydraulic properties. A comparison between fuzzy and statistical ln q(h) relationship indicated that the confidence bands resulting from both procedures enveloped all the measurement points, but fuzzy regression estimates offered a tighter fit around the midpoint values (least-square estimates). Fuzzy linear regression is more reliable and may be used as a complement or an alternative to statistical linear regression analysis for determining hydraulic properties from tension infiltrometer measurements.

This article has been cited by other articles:

				J. A. Vrugt, P. H. Stauffer, Th. Wohling, B. A. Robinson, and V. V. Vesselinov Inverse Modeling of Subsurface Flow and Transport Properties: A Review with New Developments Vadose Zone J., May 27, 2008; 7(2): 843 - 864. [Abstract] [Full Text] [PDF]