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

This Article Full Text (PDF) Alert me when this article is cited Alert me if a correction is posted Services Similar articles in this journal 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 Vaughan, P. J. Articles by Cone, D. G. Search for Related Content PubMed Articles by Vaughan, P. J. Articles by Cone, D. G. Agricola Articles by Vaughan, P. J. Articles by Cone, D. G.

Water Content Effect on Soil Salinity Prediction: A Geostatistical Study Using Cokriging

USDA-ARS, U.S. Salinity Lab., 4500 Glenwood Dr., Riverside, CA 92501

David G. Cone

Broadview Water District, P.O. Box 95, Firebaugh, CA 93622

*Corresponding author (vpeter{at}ucrac1.ucr.edu).

ABSTRACT

A geostatistical analysis of soil salinity in an agricultural area in the San Joaquin Valley included measurements of electrical conductivity of soil paste extract (EC_e) and water content of soil samples supplemented by surface measurements of apparent electrical conductivity (EM_H). Prediction of soil salinity at unsampled points by cokriging log_e(EC_e) and EM_H is worthwhile because EM_H measurements are quicker than soil sampling. This work studies how patterns of log_e(EC_e) predicted by cokriging with EM_H are influenced by variation in gravimetric water content (W). The data are mean EM_H = 1.00 ± 0.13 dS m^–1 for 2378 locations, mean log_e(EC_e) = 1.40 ± 0.29 dS m^–1, and mean gravimetric W = 0.260 ± 0.003, both averaged for four samples from 0.3-m intervals to 1.2-m depth for 315 locations. The coefficient of determination (R²) for EM_H vs. log_e(EC_e) increased with depth from 0.05 to 0.54 whereas the R² for EM_H vs. W decreased from 0.48 to 0.28. A gray-scale EM_H map contained nine out of 56 quarter-section boundaries coinciding with step variations in EM_H. The t-statistics for differences in mean W were six of nine significant at 0.001 and nine of nine at 0.05, but mean log_e(EC_e) had only two of nine at 0.05, implying that W caused EM_H steps. Water-affected EM_H impaired prediction of EC_e at depth by cokriging, because near-surface variations in W masked EC_e. Two subareas were defined, one where management factors, such as irrigation, controlled EM_H, causing steps, and one where near-surface W varied less, making cokriging predictions more reliable.

Contribution from the USDA-ARS, U.S. Salinity Lab.

Received for publication May 23, 1994.

This article has been cited by other articles:

				H. Zhang, J. L. Schroder, J. J. Pittman, J. J. Wang, and M. E. Payton Soil Salinity Using Saturated Paste and 1:1 Soil to Water Extracts Soil Sci. Soc. Am. J., June 2, 2005; 69(4): 1146 - 1151. [Abstract] [Full Text] [PDF]

				J. Wu, W. A. Norvell, D. G. Hopkins, D. B. Smith, M. G. Ulmer, and R. M. Welch Improved Prediction and Mapping of Soil Copper by Kriging with Auxiliary Data for Cation-Exchange Capacity Soil Sci. Soc. Am. J., May 1, 2003; 67(3): 919 - 927. [Abstract] [Full Text] [PDF]

				T. G. Mueller and F. J. Pierce Soil Carbon Maps: Enhancing Spatial Estimates with Simple Terrain Attributes at Multiple Scales Soil Sci. Soc. Am. J., January 1, 2003; 67(1): 258 - 267. [Abstract] [Full Text] [PDF]

				J. Triantafilis, I.O.A. Odeh, and A.B. McBratney Five Geostatistical Models to Predict Soil Salinity from Electromagnetic Induction Data Across Irrigated Cotton Soil Sci. Soc. Am. J., May 1, 2001; 65(3): 869 - 878. [Abstract] [Full Text] [PDF]