Atrazine and Alachlor Dissipation Rates from Field Experiments

Chemical transport is being monitored in the root zone of three agricultural management systems at the Ohio Management Systems Evaluation Area (OMSEA). Atrazine and alachlor concentration data from soil cores taken to a depth of 0.9 m and partitioned into the increments of 0.0 to 0.15, 0.15 to 0.3, 0.45 to 0.6, and 0.75 to 0.9 m show the herbicides remained in the top 0.15 m of the profile during the 1991 and 1992 growing seasons. The slow movement of herbicides was partly due to below normal rainfall during the period. Since the herbicides have not been transported out of the soil profile, dissipation rates could be determined from the field observations. The data collected follow first-order kinetics in the dissipation of atrazine during the 1991 and 1992 growing season and of alachlor during the 1991 growing season for the two- to three-month period following chemical application. The computed rate constant, k, was 0.02 d–1 and half-life, t1/2, was 35 days for atrazine for both years. A rate constant of 0.04 d–1 and half-life of 17 days were computed for alachlor. The degradation rates became slower with residence time in the soil as a result of decreased availability from sorption/binding in the soil

Comparison of Daily Water Table Depth Prediction by Four Simulation Models

The Agricultural Drainage And Pesticide Transport (ADAPT) model was compared to the water management simulation models DRAINMOD, SWATREN, and PREFLO. SWATREN and PREFLO are one-dimensional finite-difference models while ADAPT and DRAINMOD are one-dimensional mass balance models. ADAPT, an extension of the computer model GLEAMS, also provides chemical transport information. All four models were tested against field data from Aurora, North Carolina. Observed water table depth data were collected during 1973 through 1977 from a water table management field experiment with three subsurface drain spacing treatments of 7.5, 15, and 30 m. Both the standard error of estimate and the average absolute deviation were computed between measured and predicted midpoint water table depths. For the five-year period ADAPT, DRAINMOD, SWATREN, and PREFLO had standard errors of estimated water table depth of 0.18, 0.19, 0.19, and 0.18 m and absolute deviations of 0.14, 0.14, 0.14, and 0.14 m, respectively. The results show good agreement between the models for this experimental site and encourage the further adoption of ADAPT to predict chemical transport

Most Asked Agronomic Questions

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Properties of the Fractured Glacial Till at the Madison County, Ohio, Field Workshop Pit Site

Author Institution: USDA/ARS, Soil Drainage Research Unit ; School of Natural Resources, The Ohio State University ; Department of Food, Agricultural and Biological Engineering, The Ohio State UniversityWater and contaminants obviously do move through the so-called impermeable glacial tills in Ohio. This study was conducted to illustrate the extensive presence of fractures in the till and to quantify the differences in hydraulic conductivity and physical and chemical properties between the fractureaffected zones and the till matrix. In situ measurements of the saturated hydraulic conductivity were made in small boreholes positioned either in the matrix or intersecting the fractures. Soil samples from both the fracture faces and the matrix were analyzed for particle size distribution, clay mineralogy, calcite, dolomite, and iron content. Hydraulic conductivity measured in boreholes intersecting fractures was 1.25 x 105 cm/sec (0.018 in/hr), one order of magnitude greater than in boreholes in the matrix. Particle size distribution was the same for the fracture faces and the matrix. The fracture faces showed no significant change in total clay content and a slight increase in expandable clay. Calcite content was 62% greater, dolomite content was 6% lower, and iron content was 73% lower on the fracture faces as compared to the matrix. The fractures affected approximately 7% of the soil volume

Manipulation of High Spatial Resolution Aircraft Remote Sensing Data for Use in Site-Specific Farming

Three spatial data sets consisting of high spatial resolution (1 m) remote sensing images acquired in 12 spectral bands, an on-the-go yield map, and a Digital Elevation Model were co-registered and evaluated for spatial variability studies in a Geographic Information Systems environment. Separate on-the-go yield maps were developed for 3, 5, and 12 statistically significant mean yield classes. For each yield class, the corresponding mean spectral and elevation data were extracted. The relationship between mean spectral and yield data was strongly linear (r = 0.99). Also, a strong linear relationship between mean yield and elevation data (r = 0.92) was found. The relationship between the spectral and on-the-go yield data indicated the potential of remote sensing for spatial variability studies