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Estimating Herbicide Partition Coefficients from Electromagnetic Induction Measurements

USDA-ARS National Soil Tilth Lab., 2150 Pammel Dr., Ames, IA 50011;
USDA-ARS Coastal Plains Soil and Water Res. Ctr., P.O. Box 3039, Florence, SC 29502.

^* Corresponding author (jaynes{at}nstl.gov).

ABSTRACT

A potential method for reducing pesticide leaching is to base application rates on the leaching potential of a specific chemical and soil combination. However, leaching is determined in part by the partitioning of the chemical between the soil and soil solution, which varies across a field. Standard methods of measuring the pesticide-soil partitioning coefficient (K_d) are too expensive and slow for routine field mapping. Therefore, alternative methods for mapping K_d must be found if variable application methods are to be successful. We investigated the use of noncontacting electromagnetic induction measurements as surrogate measures of K_d. We measured the partition coefficient for atrazine (2-chloro-4-ethylamino-6-isopropylamino-s-triazine), apparent electrical conductivity by electromagnetic induction (E_m), and mass fraction of soil organic carbon (f_oc) on a 250 by 250 m grid with a 25 m spacing. Both K_d and f_oc were lognormally distributed, while E_m was poorly described by either a normal or lognormal distribution. Maps of the measured parameters showed similar spatial patterns, having low values on well-drained soils and high values on poorly drained soils. Correlation coefficients between K_d and E_m and K_d and f_oc were 0.575 and 0.686, and showed distinct spatial patterns. Spatial structure as indicated by correlograms indicated that each parameter was spatially dependent to distances of about 80 m. Simple relationships of K_d = 176 f_oc and K_d = exp(0.0336 E_m) were found between the data. Maps of K_d estimated from f_oc or E_m were similar to measured K_d, but more diffuse. Electromagnetic induction measurements failed to predict the observed high K6_d values. The advantage of using E_m measurements to map K_d is that it is a rapid, easy, and inexpensive method once it has been calibrated.

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