SSSAJ Journal of Natural Resources and Life Sciences Education
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Published online 28 June 2005
Published in Soil Sci Soc Am J 69:1338-1350 (2005)
DOI: 10.2136/sssaj2004.0154
© 2005 Soil Science Society of America
677 S. Segoe Rd., Madison, WI 53711 USA
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Soil & Water Management & Conservation

Spatial Variability Analysis of Soil Physical Properties of Alluvial Soils

Javed Iqbala,*, John A. Thomassond, Johnie N. Jenkinsc, Phillip R. Owense and Frank D. Whislerb

a Dep. of Agricultural and Biological Engineering, Mississippi State Univ., Mississippi State, MS 39762
b Dep. of Plant and Soil Sci., Mississippi State Univ., Mississippi State, MS 39762
c USDA-ARS, Crop Science Research Lab., P.O. Box 5367, Mississippi State, MS 39762
d Dep. of Agricultural and Biological Engineering, Texas A&M University, College Station, TX 77843
e Dep. of Agronomy, Lilly Hall of Life Sci., 915 W. State Street, Purdue Univ., West Lafayette, IN 47907

* Corresponding author (ji1{at}ra.msstate.edu)

Analysis and interpretation of spatial variability of soils is a keystone in site-specific farming. Soil survey maps may have up to 0.41-ha inclusions of dissimilar soils within a mapping unit. The objectives of this study were to determine the degree of spatial variability of soil physical properties and variance structure, and to model the sampling interval of alluvial floodplain soils. Soil profiles (n = 209) from 18 parallel transects were sampled with a mean separation distance of 79.4 m. Each profile was classified into surface, subsurface, and deep horizons. Structural analysis of soil bulk density ({rho}b), sand, clay, saturated hydraulic conductivity (Ks), volumetric water content ({theta}v) at seven pressure potentials ({Psi}a) (–1, –10, –33, –67, –100, –500, and –1500 kPa) were modeled for the three horizons. Variance of soil physical properties varied from as low as 0.01% ({rho}b) to as high as 1542% (Ks). The LSD test indicated significant (P < 0.05) differences in sand, clay, {rho}b, Ks, and {theta}v at various {Psi}a. Geostatistical analyses illustrated that the spatially dependent stochastic component was predominant over the nugget effect. Structured semivariogram functions of each variable were used in generating fine-scale kriged contour maps. Overall autocorrelation, Moran's I, indicated a 400-m sampling range would be adequate for detection of spatial structure of sand, silt, clay, and a 100-m sampling range for soil hydraulic properties and {rho}b. The magnitude and spatial patterns soil physical property variability have implications for variable rate applications and design of soil sampling strategies in alluvial floodplain soils.

Abbreviations: {theta}v, volumetric water content • {rho}b, soil bulk density • {Psi}a, pressure potential • AWC, available water content • FC, field capacity • Ks, saturated hydraulic conductivity • OM, organic matter • VRI, variable rate irrigation • WP, wilting point







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