Soil spatial variability: Areal interpolations of physical and chemical parameters.

Persistent Link:
http://hdl.handle.net/10150/184290
Title:
Soil spatial variability: Areal interpolations of physical and chemical parameters.
Author:
El-Haris, Mamdouh Khamis.
Issue Date:
1987
Publisher:
The University of Arizona.
Rights:
Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
Abstract:
Four fields of 117 ha area located at the University of Arizona's Maricopa Agricultural Center were selected for this study. Two soil series, the Casa Grande sandy clay loam and Trix clay loam occur. Surface samples (0-25 cm) were collected on a 98 m interval and 3 rows providing 47 sites per field. Sites were classified either as surveying (32) or testing (15) in each of the four fields. Additional samples at 25-50, 50-75, 75-100, and 100-125 cm were obtained with duplicate surface undisturbed cores at 5 sites per field. Soil parameters include bulk density, saturated hydraulic conductivity, moisture retention, particle size analysis, pH, EC, soluble cations, SAR, and ESP. A quantification of the spatial interdependence of samples was developed based on the variogram of soil parameters. A linear model was best fitted to the clay, EC, Ca²⁺, Mg²⁺, Na⁺, SAR and ESP, and a spherical model to the sand, silt, pH, and K⁺ observed variograms. A comparison of variograms obtained conventionally and with the robust estimation of Cressie and Hawkins (1980) for sand and Ca²⁺ were performed with a fixed couples number per class and with a fixed class size. Additionally, a negative log-likelihood function along with cross-validation criteria were used with the jackknifing method to validate and determine variogram parameters. Three interpolation techniques have been compared for estimating 11 soil properties at the test sites. The techniques include Arithmetic Mean, Inversely Weighted Average, and Kriging with various numbers of neighbor estimates. Using 4 point estimates resulted in nearly identical results, but the 8 point estimates gave more contrast for results among the alternative techniques. Jackknifing was used with 4, 8, 15, 25 neighbors for estimating 188 points of sand and Ca²⁺ with the three techniques. Sand showed a definite advantage of Kriging by lowering the Mean Square Error with increasing neighbor number. The simple interpolator Arithmetic Mean was comparable and sometimes even better than the other techniques. Kriging, the most complex technique, was not the absolute best interpolator over all situations as perhaps expected. The spatial dependence for the 11 soil variables was studied by preparing contour maps by punctual Kriging. Sand and Ca²⁺ were also mapped by block Kriging estimates.
Type:
text; Dissertation-Reproduction (electronic)
Keywords:
Soils -- Arizona -- Maricopa County -- Analysis.; Soil mapping -- Arizona -- Maricopa County.; Soil structure -- Arizona -- Maricopa County.
Degree Name:
Ph.D.
Degree Level:
doctoral
Degree Program:
Soil and Water Science; Graduate College
Degree Grantor:
University of Arizona
Advisor:
Arthur, Warrick W.

Full metadata record

DC FieldValue Language
dc.language.isoenen_US
dc.titleSoil spatial variability: Areal interpolations of physical and chemical parameters.en_US
dc.creatorEl-Haris, Mamdouh Khamis.en_US
dc.contributor.authorEl-Haris, Mamdouh Khamis.en_US
dc.date.issued1987en_US
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.description.abstractFour fields of 117 ha area located at the University of Arizona's Maricopa Agricultural Center were selected for this study. Two soil series, the Casa Grande sandy clay loam and Trix clay loam occur. Surface samples (0-25 cm) were collected on a 98 m interval and 3 rows providing 47 sites per field. Sites were classified either as surveying (32) or testing (15) in each of the four fields. Additional samples at 25-50, 50-75, 75-100, and 100-125 cm were obtained with duplicate surface undisturbed cores at 5 sites per field. Soil parameters include bulk density, saturated hydraulic conductivity, moisture retention, particle size analysis, pH, EC, soluble cations, SAR, and ESP. A quantification of the spatial interdependence of samples was developed based on the variogram of soil parameters. A linear model was best fitted to the clay, EC, Ca²⁺, Mg²⁺, Na⁺, SAR and ESP, and a spherical model to the sand, silt, pH, and K⁺ observed variograms. A comparison of variograms obtained conventionally and with the robust estimation of Cressie and Hawkins (1980) for sand and Ca²⁺ were performed with a fixed couples number per class and with a fixed class size. Additionally, a negative log-likelihood function along with cross-validation criteria were used with the jackknifing method to validate and determine variogram parameters. Three interpolation techniques have been compared for estimating 11 soil properties at the test sites. The techniques include Arithmetic Mean, Inversely Weighted Average, and Kriging with various numbers of neighbor estimates. Using 4 point estimates resulted in nearly identical results, but the 8 point estimates gave more contrast for results among the alternative techniques. Jackknifing was used with 4, 8, 15, 25 neighbors for estimating 188 points of sand and Ca²⁺ with the three techniques. Sand showed a definite advantage of Kriging by lowering the Mean Square Error with increasing neighbor number. The simple interpolator Arithmetic Mean was comparable and sometimes even better than the other techniques. Kriging, the most complex technique, was not the absolute best interpolator over all situations as perhaps expected. The spatial dependence for the 11 soil variables was studied by preparing contour maps by punctual Kriging. Sand and Ca²⁺ were also mapped by block Kriging estimates.en_US
dc.typetexten_US
dc.typeDissertation-Reproduction (electronic)en_US
dc.subjectSoils -- Arizona -- Maricopa County -- Analysis.en_US
dc.subjectSoil mapping -- Arizona -- Maricopa County.en_US
dc.subjectSoil structure -- Arizona -- Maricopa County.en_US
thesis.degree.namePh.D.en_US
thesis.degree.leveldoctoralen_US
thesis.degree.disciplineSoil and Water Scienceen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.grantorUniversity of Arizonaen_US
dc.contributor.advisorArthur, Warrick W.en_US
dc.contributor.committeememberMatthias, Allan D.en_US
dc.contributor.committeememberFfolliott, Peter F.en_US
dc.contributor.committeememberTucker, Thomas C.en_US
dc.contributor.committeememberWarrick, Arthur W.en_US
dc.identifier.proquest8805510en_US
dc.identifier.oclc700069702en_US
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