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Chlorsulfuron [2‐chloro‐N‐[[(4‐methoxy‐6‐methyl‐1,3,5‐triazin‐2‐yl)amino]carbonyl]‐benzenesulfonamide] is an anionic sulfonylurea herbicide with high soil persistence; consequently, there is interest in predicting its mobility hi agricultural soils. The objectives of this study were to determine the transport characteristics of chlorsulfuron in disturbed and undisturbed soil columns and evaluate the capabilities of LEACHM (Leaching Estimation and Chemistry Model) for predicting chlorsulfuron transport. Soil column experiments were conducted with two Montana soils (Amsterdam silt loam, file‐silty, mixed Typic Haploboroll, and Haverson silty clay loam, fine‐loamy, mixed (calcareous), mesic Ustic Torrifluvent) under unsaturated flow conditions. Unit gradient was established in all columns by balancing surface water input to outflow at the bottom of each column through a stainless steel porous plate connected to a vacuum chamber containing a fraction collector. A nonlinear least squares approach (CXTFIT) was used to fit breakthrough curves (BTCs) for Br−and 14C‐labeled chlorsulfuron using the linear equilibrium adsorption model (i.e., local equilibrium assumption or LEA model) and the bicontinuum model (i.e., nonequilibrium assumption). Observed Br−BTCs were best described by the bicontinuum model indicating physical nonequilibrium due to immobile water regions. Observed chlorsulfuron BTCs demonstrated both chemical and physical nonequilibrium during transport. The best fit to observed chlorsulfuron BTCs was obtained with the bicontinuum model using the dispersion coefficient optimized (i.e., fixed) from the Br−BTCs. LEACHM was used to generate predicted BTCs for chlorsulfuron utilizing independently measured or estimated soil physical parameters as input data. Predicted BTCs utilizing the Br−‐derived dispersion coefficient (D) and the bicontinuum model‐derived partition coefficient (Koc) did not adequately reflect observed BTCs primarily because the current version of LEACHM has no capability for accepting input parameters relating to nonequilibrium conditions. The Dand Kocvalues for chlorsulfuron BTCs derived from the LEA model improved predictions; however, it is important to note that LEA‐derived Dand Kocvalues for chlorsulfuron BTCs essentially compensate for nonequilibrium behavior. Finally, the experimentally determined chlorsulfuron BTCs confirmed the high mobility of this chemical at neutral soil pH values.

Numerous soil factors and climatic conditions affect the degradation rate of pesticides in soils. A major soil factor influencing herbicide degradation is the composition and abundance of the microbiota, which has been shown to vary considerably with soil depth. Another important variable affecting microbial growth and degradation kinetics is temperature. Soil samples from 0‐ to 30‐, 30‐ to 60‐, and 60‐ to 120‐cm depths of two Montana soils were placed in reaction flasks and treated with 14C‐labeled 2,4‐D at representative field use rates at temperatures of 10, 17, and 24°C. A carrier gas was used to continuously evacuate evolved 14CO2into NaOH traps as a measure of 2,4‐D degradation. Comparisons of the effects of soil depth and temperature were made by fitting experimental data to both first‐order and logistic kinetic models. Degradation rates of 2,4‐D decreased significantly with increasing soil depth and were positively correlated with bacterial plate counts. Effects of temperature on degradation rate constants were adequately described using the Arrhenius equation. Degradation rates of 2,4‐D and bacterial enumerations were positively correlated with changes in soil organic C as a function of soil depth. These results support the idea that changes in organic C with soil depth could be used as a parameter for estimating changes in degradation rate as a function of soil depth. Efforts to model the transport of 2,4‐D in soils should account for variation in degradation rate as a function of soil depth and temperature.

The major objective of this study was to determine what environmental characteristics best related to increased small grain yield when fertilizer K was included in a balanced soil fertility management program. These results would help explain why contemporary soil test approaches for predicting crop response to applied K fertilizers do not work in this region, and help lead to alternative approaches to resolve this problem. Two hundred twenty‐two small grain experiments established over a 13 yr period on 127 site locations throughout the Great Plains of Montana were selected for this study. Two to five rates of K, ranging from 0 to 135 kg K/ha, had been applied in the field experiments. Both KCl and K2SO4were included as fertilizer sources in most experiments. Adequate rates of N and P were constant within an experiment, but varied from one experiment to another. Originally a total of 47 independent variables in various combinations were used in 45 multiple linear regression analyses. The dependent variables were (i) maximum, and (ii) average percent grain yield response to applied K. The statistical analysis was confounded considerably because of missing data for certain independent variables at some sites and because of intercorrelations between variables; however, significant relationships (simple r) existed in many of the regression analyses between independent variables and the dependent variables. In the final analyses, 32 sites were examined using 27 independent variables with a universal data base. Variables with the highest correlation to percent yield response (in decreasing order) were: (i) dry consistence of the Bkhorizon; (ii) textural family; (iii) average soil temperature in May; (iv) growing season rainfall; and (v) stored spring soil moisture from 0 to 90 cm. Together these five variables produced a significant R2of 0.34 (P=0.05).