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Title: Effect of Soil Water on Apparent Soil Electrical Conductivity and Texture Relationships in a Dryland Field.

Author
item MCCUTSHEON, M.C. - NORTHERN COLORADO WATER C
item FAHAHANI, J.J - INTERNATIONAL CENTER FOR
item STEDNICK, J.D. - FORESTY, RANGE AND WATERS
item Buchleiter, Gerald
item Green, Timothy

Submitted to: Biosystems Engineering
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 1/6/2006
Publication Date: 3/24/2006
Citation: Mccutsheon, M., Fahahani, J., Stednick, J., Buchleiter, G.W., Green, T.R. 2006. Effect of Soil Water on Apparent Soil Electrical Conductivity and Texture Relationships in a Dryland Field. Biosystems Engineering (2006) 94,19-3

Interpretive Summary: Precision farming is a relatively new management approach that seeks to apply the right input (e.g. fertilizer, pesticide) at the right time and place in a field to minimize production costs and/or maximize yield. Since soil in a field is naturally variable, maps of management zones are useful in determining where and how much fertilizer, etc to apply across a field. Several approaches have been developed to determine management zones easily and inexpensively. One popular approach is to use the soil’s apparent electrical conductivity (ECa), which is the ease that electricity passes through soil. Previous research has shown ECa is primarily affected by salinity levels, texture (% sand, % silt, % clay), and water content of the soil. Equipment is available to quickly map ECa of two different soil layers over large fields. Concurrent with mapping, soil samples are taken at specific locations in the field for subsequent analysis in the lab. Various statistical procedures are used to determine how well ECa is correlated with the various soil parameters. If the salinity level of the soil is low, ECa is usually correlated most strongly with soil texture and water content. This study of a dryland field with a wheat-fallow cropping system, focused on evaluating the statistical correlations between ECa and various soil parameters, to determine whether ECa data were useful in developing maps of management zones useful in precision farming. Results indicated that soil water content was the dominant factor affecting ECa . Thus the temporal variation in water content over the cropping and fallow periods, severely limited the use of the weaker correlation of soil texture and ECa , to make useful management zone maps.

Technical Abstract: Precision farming (PF) research has shown that when high salinity levels are not present, apparent soil electrical conductivity (ECa) is usually strongly correlated with soil texture. Mapping ECa has been promoted as a means for identifying management zones that are needed for variable application of various production inputs. Research results have shown the practical utility of this mapping is sometimes elusive because of changing relationships between ECa and transient soil properties such as soil moisture. This study explored relationships between ECa and soil properties and evaluated the usefulness of ECa mapping to infer soil texture when soil moisture content changed between mapping dates. ECa mapping of a 110 ha dryland field with 12 alternating wheat and fallow strips, was done 4 times over a 2 year period. Soil samples from 198 locations within the field were also analyzed for texture, volumetric water content, pH, and fertility levels. Based on several statistical tests and procedures, correlations of ECa and various soil parameters indicated that soil moisture was the dominant factor affecting spatial and temporal ECa variability. Thus because of the relatively low soil water contents in this dryland field, ECa maps have limited utility in representing the spatial variability of soil properties, particularly soil texture.