|Clevenger, W -|
|Saraswat, D -|
Submitted to: National Association of County Agricultural Agents Proceedings
Publication Type: Abstract Only
Publication Acceptance Date: July 11, 2010
Publication Date: September 1, 2010
Repository URL: http://www.nacaa.com/ampic/2010/proceedings.pdf
Citation: Clevenger, W.B., Allred, B.J., Saraswat, D. 2010. Application of GPS and Near-Surface Geophysical Methods to Evaluate Agricultural Test Plot Difference. National Association of County Agricultural Agents Proceedings. p. 42. Technical Abstract: Real-time kinematic (RTK) GPS, ground penetrating radar, resistivity surveying, cone penetrometer probing, and soil sampling were used to measure soil properties that may influence future soil and water management research inherent to a selected set of research fields. A topographic map generated from RTK GPS show that there was a 1 m elevation difference across the four test plots. Ground penetrating radar determined that for one pair of replicated test plots, there was a 0.25 m difference in drainage pipe depth when comparing one test plot to the other. The resistivity survey found substantial spatial variations for ECa both within individual test plots and across the four test plots as a whole. The mean and median values of ECa and the other soil properties were calculated for each of the four test plots and indicated significant differences exist from one test plot to the next in regard to soil properties. Furthermore, the test plot soil property mean and median values, along with spatial correlation coefficients, all provide strong evidence, that for this particular site does produce a spatial pattern of soil productivity reflected by the crop yield maps. Overall, the RTK GPS and near-surface geophysical information obtained at this site provided valuable insight on test plot dissimilarities potentially causing differences in the hydrologic response between replicated test plots. This investigation serves as a very good example of how RTK GPS and near-surface geophysical methods can be successfully employed to better characterize a farm field.