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首页> 外文期刊>Journal of Environmental Quality >Regression models for estimating concentrations of atrazine plus deethylatrazine in shallow groundwater in agricultural areas of the United States.
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Regression models for estimating concentrations of atrazine plus deethylatrazine in shallow groundwater in agricultural areas of the United States.

机译：估算美国农业地区浅层地下水中阿特拉津加脱乙基阿特拉津浓度的回归模型。

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摘要

Tobit regression models were developed to predict the summed concentration of atrazine [6-chloro--ethyl--(1-methylethyl)-1,3,5-triazine-2,4-diamine] and its degradate deethylatrazine [6-chloro--(1-methylethyl)-1,3,5,-triazine-2,4-diamine] (DEA) in shallow groundwater underlying agricultural settings across the conterminous United States. The models were developed from atrazine and DEA concentrations in samples from 1298 wells and explanatory variables that represent the source of atrazine and various aspects of the transport and fate of atrazine and DEA in the subsurface. One advantage of these newly developed models over previous national regression models is that they predict concentrations (rather than detection frequency), which can be compared with water quality benchmarks. Model results indicate that variability in the concentration of atrazine residues (atrazine plus DEA) in groundwater underlying agricultural areas is more strongly controlled by the history of atrazine use in relation to the timing of recharge (groundwater age) than by processes that control the dispersion, adsorption, or degradation of these compounds in the saturated zone. Current (1990s) atrazine use was found to be a weak explanatory variable, perhaps because it does not represent the use of atrazine at the time of recharge of the sampled groundwater and because the likelihood that these compounds will reach the water table is affected by other factors operating within the unsaturated zone, such as soil characteristics, artificial drainage, and water movement. Results show that only about 5% of agricultural areas have greater than a 10% probability of exceeding the USEPA maximum contaminant level of 3.0 mug L. These models are not developed for regulatory purposes but rather can be used to (i) identify areas of potential concern, (ii) provide conservative estimates of the concentrations of atrazine residues in deeper potential drinking water supplies, and (iii) set priorities among areas for future groundwater monitoring. Copyright Copyright by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.
机译：开发了Tobit回归模型来预测阿特拉津[6-氯-乙基-（1-甲基乙基）-1,3,5-三嗪-2,4-二胺]及其降解的去乙基阿特拉津[6-氯- -（1-甲基乙基）-1,3,5，-三嗪-2,4-二胺]（DEA）在整个美国本土附近农业环境中的浅层地下水中。该模型是根据1298口井中样品中at去津和DEA的浓度以及解释变量来开发的，这些变量代表at去津的来源以及地下r去津和DEA的运输和结局的各个方面。这些新开发的模型相对于以前的国家回归模型的一个优势是，它们可以预测浓度（而不是检测频率），可以将其与水质基准进行比较。模型结果表明，农业区域地下水中阿特拉津残留物浓度的变化（阿特拉津加DEA）受阿特拉津使用历史与补给时间（地下水年龄）的影响要强于控制分散的过程，这些化合物在饱和区的吸附或降解。发现当前（1990年代）使用）去津是一个较弱的解释变量，这可能是因为它不代表在补充采样的地下水时使用azine去津，并且由于这些化合物到达地下水位的可能性受到其他因素的影响。在非饱和区中起作用的因素，例如土壤特性，人工排水和水分运动。结果表明，只有约5％的农业地区有超过10％的可能性超过USEPA最大污染水平3.0马克杯。这些模型并非出于监管目的而开发，而是可用于（i）识别潜在区域（ii）提供较深的潜在饮用水供应中of去津残留浓度的保守估计，并且（iii）在未来的地下水监测领域中确定优先级。版权美国农艺学会，美国作物科学学会和美国土壤科学学会版权所有。

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