Environmental fate models are increasingly used to evaluate potential impacts of agrochemicals on water quality to aid in decision making. However, errors in predicting processes like evapotranspiration (ET), which is rarely measured during model validation studies, can significantly affect predictions of chemical fate and transport. This study compared approaches and predictions for ET by GLEAMS, Opus, PRZM-2, and RZWQM and determined effects of the predicted ET on simulations of other hydrology components. The ET was investigated for 2 years of various fallow–corn growing seasons under sprinkler irrigation. The comparison included annual cumulative daily potential ET (ETp), actual ET, and partitioning of total ET between soil evaporation (Es) and crop transpiration (Et). When measured pan evaporation was used for calculating ETp (the pan evaporation method), Opus, PRZM-2, and RZWQM predicted 74, 65, and 59%, respectively, of the 10-year average ET reported for a nearby site. When the energy-balance equations were used for calculating ETp (the combination methods), GLEAMS, Opus, PRZM-2, and RZWQM predicted 84, 105, 60, and 72% of the reported ET, respectively. The pan evaporation method predicted a similar amount of ET to the combination methods for bare soil, but predicted less ET when both Es and Et occurred. RZWQM reasonably predicted partitioning of ET to Es, while GLEAMS and Opus over-predicted this partitioning. A close correlation between soil water storage in the root zone and ET suggests that accurate soil water content predictions were fundamental to ET predictions. ©

The Brooks‐Corey functions are commonly used in hydrologic models, with parameters obtained by fitting the functions directly to measured soil water retention data or by conversion methods from the van Genuchten functions which are continuous across the domain of matric suctions. Problems in fitting the BC functions directly to the retention data motivated use of the conversion methods. However, differences in converted parameters could significantly influence model predictions. We compared the direct fitting method and the conversion methods of Lenhard et al., Morel‐Seytoux et al., and van Genuchten using measured water retention data during drainage and determined the influence of these methods on hydrological predictions when the converted parameters were used in the root zone water quality model. The conversion methods had significant influence on predictions of water retention, hydraulic conductivity, runoff, and evapotranspiration, with the observed level of significance (p ≤ 0.006) much lower than the test level of significance (α = 0.05). The method of Morel‐Seytoux et al. inadequately described measured water retention data (p=0.027), whereas the other two methods adequately described the data at relatively high suctions (p ≥ 0.687), deviations occurred around the air‐entry suction. The method of Lenhard et al. best reproduced the characteristics of the Brooks‐Corey functions (p ≥ 0.31) and could be used to obtain the Brooks‐Corey parameters simply and reproducibly.

Frequent pesticide applications to gulf courses causes concern that surface water may become contaminated, We hypothesized that runoff potential of these pesticides could be predicted by the recently developed Opus model. We conducted a 3-yr field study measuring surface runoff of water and dimethylamine salts of 2,4-D [(2,4-dichlorophenoxy) acetic acid], dicamba (3,6-dichloro-2-methylphenoxy-benzoic acid), and mecoprop [(+/-)-2-(4-chloro-2-methylphenoxy)-propanoic acid]. Twelve 7.4 m by 3.7 m plots of 'Tifway 419' bermudagrass (Cynodon dactylon (L.) Pers. x C. transvaalensis Burtt Davy) were managed as a golf course fairway. Simulated rainfall was applied at an average intensity of 29 mm h(-1) 1 d before and 1, 2, 4, and 8 d after pesticide application for 0.92, 1.75, 1.75, 0.92, and 0.92 h, respectively. Average annual runoff loss was 9.13, 15.41, and 10.82% of applied 2,4-D, dicamba, and mecoprop, respectively. Both mass and concentration of pesticide runoff decreased rapidly, with the first posttreatment event runoff averaging 74.5, 71.7, and 73.0% of the total runoff of 2,4-D, dicamba, and mecoprop, respectively. The Opus model adequately simulated runoff [R(2) = 0.897 and normalized root mean square error (NRMSE) = 24.6%], The 2,4-D in runoff was better simulated by complete-kinetic sorption (R(2) = 0.876, NRMSE = 60.2%) than by equilibrium sorption (R(2) = 0.848, NRMSE = 68.2%). Opus did not accurately simulate 2,4-D over all runoff events, but simulated 2,4-D in the first posttreatment runoff within a factor of 2 of those measured.

A three-year field study was conducted using twelve 7.4 x 3.7 m plots and simulated rainfall to investigate pesticide run-off following application to a golf course fairway. The plots were sprigged with 'Tifway 419' bermudagrass (Cynodon dactylon x C transvaalensis). The dimethylamine salt of 2,4-D [(2,4-dichlorophenoxy)acetic acid] was applied as foliar sprays at a rate of 2.24 kg AI ha(-1). Simulated rainfall was applied at an intensity of 29 mm h(-1) one day before and 1, 2, 4, and 8 days after the pesticide applications for 0.92, 1.75. 1.75, 0.92, and 0.92 h, respectively. Water run-off was measured using a tipping-bucket apparatus and sub-samples were analyzed for pesticide residues. Data collected from the study were also compared with the GLEAMS and PRZM-2 model simulations for surface water and 2,4-D run-off. Mass and concentration of 2,4-D in run-off decreased rapidly, with 74.5% of the total run-off of 2,4-D occurring in the first run-off event after treatment. When calibrated to the site-specific characteristics, the GLEAMS and the PRZM-2 models adequately simulated the average of surface water run-off over all plots, with normalized root mean square error (NRMSE) and coefficient of determination for linear regression (R(2)) being 22.8% and 0.917 for GLEAMS, and 23.7% and 0.879 for PRZM-2, respectively. However, both GLEAMS (NRMSE = 82.1%, R(2) = 0.776) and PRZM-2 (NRMSE = 125.8%, R(2) = 0.513) less accurately simulated 2,4-D concentrations in run-off. (C) 1999 Society of Chemical Industry.

Comprehensive models for agrichemical transport necessarily include runoff predictions to partition rainfall between infiltration and runoff as this ability is fundamental to predictions of chemical runoff and leaching. We compared GLEAMS, Opus, and PRZM-2 model runoff predictions with runoff measured in a precisely controlled field site used for chemical runoff studies. In 1992 and 1993, two 14.5 m x 42.9 m corn (Zea mays, L.) field plots with 3% slope on Tifton loamy sand (fine-loamy, siliceous, thermic Plinthic Kandiudult) received six severe, artificial rainfall events over the growing season with each event consisting of a 25 mm h(-1) rainfall for 2 h. Runoff was monitored continuously using a collector and flume. Model performance criteria included sensitivity analysis, graphical comparison and statistical analysis including mean, ratio of means, root mean square error (RMSE), and a paired difference t-test. Observed runoff averaged 20% of added rainfall. Lowest values occurred with freshly plowed soil or full canopy covet; while 24 to 34% runoff occurred when nearly bare soils had crusted over. Using an initial moisture condition-II curve number (CN) of 85, GLEAMS and Opus predicted runoff within 10%, overall, and produced a pattern of high and low runoff that closely followed observed. PRZM-2 overpredicted runoff by 90%, overall, and predicted its highest runoff when observed runoff was lowest. Paired difference t-tests indicated a significant difference between measured and predicted runoff for PRZM-2 (p<0.001 at alpha = 0.05), but none for GLEAMS (p = 0.761) or Opus (p = 0.194). Mean, ratio of means, and RMSE showed that GLEAMS and Opus performed better than PRZM-2. All three models were very sensitive to CN values which were empirical and subjective, but less sensitive to measurable soil physical properties. With careful parameterization, GLEAMS and Opus could be used to simulate runoff from similar row-crop and soil conditions.

In simulations on the fate of agricultural chemicals applied to crops, accurate partitioning of rainfall between infiltration and runoff is fundamental to chemical runoff predictions. We evaluated the Root Zone Water Quality Model (RZWQM version 3.1) against measured runoff from two field plots (15×45 m with 3% slope) on a Tifton loamy sand (fine-loamy, siliceous, thermic Plinthic Kandiudult). Six simulated rainfall events, each 25 mm h−1 for 2 h, were applied to maize (Zea mays, L.) each year. In the uncalibrated mode, RZWQM under-predicted runoff by 40% on average, with the closest fit for events that occurred after full canopy. Saturated hydraulic conductivity (Ks) accounted for the majority of the uncertainty in predicted runoff. When Ks of the surface crust was back calibrated from the measured runoff, RZWQM predicted runoff closely for the remaining plots and events. Alternatively, using different Ks values for wheel track and crop beds, running the model for each and, then, proportionally assigning runoff also led to predictions that agreed with measured runoff. When spatial and temporal changes in Ks were calibrated to specific conditions at the site, RZWQM effectively predicted runoff.

Two chemical sorption models, a two-site equilibrium-kinetic sorption model (E-K) and an instantaneous equilibrium sorption model (I-E), were used to describe pesticide leaching and runoff, Concentrations of bromide, atrazine, and fenamiphos in leachate and runoff water from 1.0 m x 0.5 m x 0.1-m boxes of packed air-dry Tifton loamy sand (fine-loamy, siliceous, thermic Plinthic Kandiudults) were compared with simulated concentrations predicted by the Root Zone Water Quality Model (RZWQM), Atrazine and bromide (as KBr) were applied to the soil surface and fenamiphos was incorporated into the top 7 cm. Water (100 mm in 2 h) was applied using sprinkler rainfall simulator 24 h later. The E-K model and the I-E model, which are the two submodels for chemical sorption in RZWQM, were used for pesticide sorption simulations, and a nonuniform mixing model was used for pesticide runoff simulations, Model parameter values were obtained by measurements, from the literature, and by calibration with measured atrazine and fenamiphos breakthrough curves (BTCs) and a runoff chemograph from an independent experiment, Results showed that the E-K model simulated atrazine and fenamiphos leaching and atrazine runoff better than the I-E model, The I-E sorption model underestimated pesticide leaching and overestimated atrazine runoff, Compared with previous studies showing that the E-K model simulated pesticide sorption and leaching better than the I-E sorption model with initially saturated soils and under steady state water flow conditions, this study showed that the E-K model also worked better than the I-E sorption model for initially air-dry soil and under fast and transient water flow conditions for leaching as well as runoff of a pesticide.

A randomized triple-blind and placebo-controlled clinical trial on the effect of lidocaine and Anodyne-lubricant jelly (ALJ) containing dicaine on cervical dilatation is reported. Three-hundred-seventy-two consecutive cases were randomly allocated to 4 groups. The four groups were given: ALJ and placebo (placebo 1); and lidocaine and placebo (placebo 2). ALJ and placebo 1 treatment was by topical application, and lidocaine and placebo 2 by injection. In parous women, a significant difference was found for satisfactory dilatation (SD) rate (p less than 0.01) among four groups. It was unexpected that there were no significant differences between drug and placebo groups, neither between ALJ treatment group and placebo 1 group (p greater than 0.5), nor between lidocaine and placebo 2 (p greater than 0.75). However, the combined SD rate was 60.9% for the topical groups compared with 39.0% for the injection groups (p less than 0.005). The findings suggested that the effect of ALJ on cervical dilatation was not mainly due to dicaine, but associated with the lubricant and the topical treatment.