Fitting performance of particle-size distribution models on data derived by conventional and laser diffraction techniques

Bah, A.R., Kravchuk, O. and Kirchhof, G. (2009) Fitting performance of particle-size distribution models on data derived by conventional and laser diffraction techniques. Soil Science Society of America Journal, 73 4: 1101-1107. doi:10.2136/sssaj2007.0433


Author Bah, A.R.
Kravchuk, O.
Kirchhof, G.
Title Fitting performance of particle-size distribution models on data derived by conventional and laser diffraction techniques
Journal name Soil Science Society of America Journal   Check publisher's open access policy
ISSN 0361-5995
Publication date 2009-07-01
Year available 2009
Sub-type Article (original research)
DOI 10.2136/sssaj2007.0433
Open Access Status
Volume 73
Issue 4
Start page 1101
End page 1107
Total pages 7
Editor D.D. Myroid
Sally D. Logsdon
Place of publication United States
Publisher Soil Science Society of America
Language eng
Subject C1
961499 Soils not elsewhere classified
050305 Soil Physics
Abstract Mathematical description of most classical particle size distribution (PSD) data is often used for estimating soil hydraulic properties. Fast laser diffraction (LD) techniques now provide more detailed PSDs, but deriving a function to characterize the entire range of sizes is a major challenge. The aim of this study was to compare the fitting performance of seven PSD functions with one to four parameters on sieve-pipette and LD data sets of fine-textured soils. The fits were evaluated by the adjusted R2, MSE, and Akaike's information criterion. The fractal and exponential functions performed poorly while the performance of the Gompertz model increased with clay content for the LD data sets. The Fredlund function provided very good fits with sieve-pipette PSDs but not the corresponding LD data sets, probably due to underestimation of the clay fraction in the latter. The two-parameter lognormal function showed better overall performance and provided very good fits with both sieve-pipette and LD data sets.
Keyword WATER-RETENTION CURVE
Q-Index Code C1
Q-Index Status Confirmed Code

Document type: Journal Article
Sub-type: Article (original research)
Collections: 2010 Higher Education Research Data Collection
School of Agriculture and Food Sciences
 
Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 21 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 20 times in Scopus Article | Citations
Google Scholar Search Google Scholar
Created: Thu, 03 Sep 2009, 17:49:25 EST by Mr Andrew Martlew on behalf of School of Land, Crop and Food Sciences