Browsing by Author "Zacharias, Sebastian"
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- Fate and transport of pesticides in a Virginia Coastal Plain soilHeatwole, Conrad D.; Zacharias, Sebastian; Mostaghimi, Saied; Dillaha, Theo A. III; Young, Roderick W. (Virginia Water Resources Research Center, Virginia Polytechnic Institute and State University, 1992)The fate and transport of atrazine, metolachlor, and bromide as a tracer, were characterized through surface runoff monitoring and soil core sampling on no-till and conventionally tilled field plots planted with corn. A rainfall simulator was used to generate a surface runoff event within 48 hours of pesticide application. In comparison with the conventional-tillage plot, the no-till plot yielded 32% of the runoff volume, 8% of the sediment, and 50% of the pesticide mass. Total losses of atrazine and metolachlor in surface runoff were 0.5-1 .5% of the amount applied, with the greatest losses associated with conventional tillage. Significant precipitation in the early stages of the study resulted in rapid leaching of the chemicals in both plots. Statistical tests show that chemicals moved deeper in the no-till plot, as compared to the conventional-tillage plot, in the first two weeks after application. However, statistical analysis of the remaining period shows no consistent differences in pesticide concentrations in the soil profile based on tillage practice. Atrazine dissipation was higher in the no-till plot, and there was a significant carryover of the pesticide in both plots at the end of the 157-day period.
- Modeling Spatial Variability of Field-Scale Solute Transport in the Vadose ZoneZacharias, Sebastian (Virginia Tech, 1998-06-25)Spatial heterogeneity in the soil system has a profound influence on the flow of water and chemicals in the unsaturated zone. Incorporating intrinsic soil variability and extrinsic variability into root zone leaching models will provide a better representation of pollutant distribution in natural field conditions. In this study, a stochastic framework (SF) was developed to represent spatial variability of soil properties in one-dimensional solute transport models, and implemented with two existing root zone leaching models, Opus and GLEAMS. The accuracy of soil water, bromide and pesticide transport predictions from Opus-SF and GLEAMS-SF was evaluated using field-measured soil water content, bromide and pesticide mass data from a 3.9-ha agricultural field in the Dougherty Plain of Georgia and a 0.05-ha field plot in Nomini Creek watershed in Virginia. Results from the rate-based Opus-SF and capacity-based GLEAMS-SF were compared to determine if there were significant differences in their predictions. In the stochastic approach, the heterogeneous field is conceptualized as a collection of vertical, non-interacting soil columns differing in soil properties. The horizontal variations of soil hydraulic and retention properties in each horizon are treated as random functions of zero transverse spatial correlation length, after accounting for any spatial trends. The spatially variable parameters were generated using the Latin hypercube sampling method, and the stochastic simulation of the model was performed using Monte-Carlo simulation techniques. Statistical tests indicated that Opus-SF and GLEAMS-SF did not predict the central tendency and distribution of depth-averaged soil water content and total pesticide mass observed in the field on most sampling dates. But their predictions were sufficiently accurate for most management-type applications. Soil hydraulic and retention properties derived from texture data at the Nomini Creek site substantially reduced the variability in soil water content predictions from both models, but had less impact on bromide and pesticide mass predictions from both models. The mean values predicted by Opus-SF and GLEAMS-SF were similar, but not equal to those predicted by the deterministic version of the models. Soil water and solute transport predictions from Opus-SF and GLEAMS-SF were not substantially different from corresponding results from the traditional Monte-Carlo approach, although soil water predictions from the two modeling approaches were significantly different for the first 150 days of simulation. Comparison between results from Opus-SF and GLEAMS-SF showed that the distributions and medians of soil water content predicted by the two models were significantly different on most sampling dates. The distributions and medians of pesticide mass predicted by the two models were closer than soil water content, but were significantly different on more than half of the field sampling dates. The more functional GLEAMS-SF model was able to simulate depth-averaged soil water content in the root zone better than the more physically based Opus-SF, although GLEAMS-SF was not able to simulate the depth distribution of soil water as accurately as Opus-SF. GLEAMS-SF was also able to predict solute movement at least as well as Opus-SF. GLEAMS-SF was able to simulate spatial variations of depth-averaged soil water content and pesticide mass in the field with reasonable accuracy employing fewer parameters that exhibit relatively lesser spatial variability.
- Spatial Trends in the Texture, Moisture Content, and pH of a Virginia Coastal Plain SoilZacharias, Sebastian; Cheryl B. Heatwole; Campbell, James B. Jr. (American Society of Agricultural and Biological Engineers, 1997)Soil texture, moisture content, and pH data from an agricultural field area of 48 _ 32 m in a Suffolk sandy loam soil in the Virginia Coastal Plain was examined for spatial trends. Trend surface analysis of sand, silt, and clay content data (n = 35) found that 68%, 74%, and 31% of the total variability in sand, silt, and clay content, respectively, was explained by second-order trend surfaces. Soil moisture content and pH also exhibited spatial trends, which resulted in statistically significant differences between subsurface moisture content and pH in two 18 _ 27 m subplots within the study area. Both moisture content and pH trends had some similarity to the trend for clay content. The spatial trends in these soil properties, however, did not translate directly into spatial trends in depth to center of bromide mass, indicating the influence of other factors in the variability of chemical distribution in the soil.
- Tillage effects on leaching and persistence of pesticides in coastal plain soilZacharias, Sebastian (Virginia Tech, 1992)The effect of tillage practices on leaching and persistence of atrazine and metolachlor was evaluated in a field study in the Coastal Plain region of Virginia. Field data were also used to validate pesticide transport models, GLEAMS and PRZM. The study was conducted on two 18x27 m plots located in a field that was in the second year of a two-year no-till wheat-beaDs-com rotation. One plot was conventionally tilled using a moldboard plow and a disk harrow before planting of com and application of chemicals. Soil samples were collected on six sampling dates during the crop growing season at 20 randomly selected locations in each plot with the 0-150 cm sampling depth divided into eight increments. Bromide concentrations were analyzed to provide an estimate of solute movement. High rainfall following chemical application led to rapid leaching of bromide, with the chemical moving faster in the no-till profile. Pesticide concentrations also showed a greater potential for leaching in the no-till plot in the early stages of the study. Chemical concentrations were higher in the no-till profile initially, and were higher in the tilled profile toward the end of the season. Atrazine dissipation was higher in the no-till plot, but there was no marked difference in metolachlor dissipation between the two tillage treatments. Over 35% of atrazine mass remained in the soil profile in both plots at the end of the crop growing season. Pesticide concentrations were found to vary largely over the two plots. The field data were used to evaluate the ability of the pesticide transport models, GLEAMS and PRZM, to represent chemical concentration distribution, depth of solute center of mass, and pesticide mass in the no-till and the conventionally-tilled root zone. The models were evaluated in three sequential steps. The fast simulation was completely uncalibrated, using best available estimates for the input parameters. For the second simulation hydrology parameters were calibrated to minimize errors in the hydrology component so as to better evaluate the prediction of pesticide behavior in soil. The third stage of the evaluation used pesticide dissipation half-life calculated from the field data. Model performance was evaluated using both objective and subjective criteria. GLEAMS and PRZM predicted pesticide concentration in soils reasonably well when run without any calibration. Bromide concentrations were predicted closer to the observed values than pesticides. Overall predictions by both models were better in the conventional tillage plot than in the no-till plot. The comparative effect of tillage on observed chemical concentrations was represented better by GLEAMS than by PRZM. The models under-predicted leaching of pesticides in the early sampling dates. Predicted pesticide mass in the root zone were reasonably close to the field measured values. Calibration of the hydrology component of the models did not improve the prediction of pesticide behavior in soils. The use of field pesticide half-life resulted in better prediction of pesticide persistence but did not improve the overall prediction of pesticide behavior in the two plots. The study identifies selection of input parameters and correct interpretation of results as important factors in the effective use of GLEAMS and PRZM as management tools.