Regression models for estimating concentrations of atrazine plus deethylatrazine in shallow groundwater in agricultural areas of the United States.

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 conterminous United States. The from DEA concentrations samples 1298 wells explanatory variables that represent source various aspects transport fate subsurface. One advantage these newly over previous national is they (rather than detection frequency), which can be compared with water quality benchmarks. Model results indicate variability residues (atrazine plus DEA) areas more strongly controlled by history use relation timing recharge (groundwater age) processes control dispersion, adsorption, or degradation compounds saturated zone. Current (1990s) was found a weak variable, perhaps because it does not at time sampled likelihood will reach table affected other factors operating within unsaturated zone, such as soil characteristics, artificial drainage, movement. Results show only about 5% have greater 10% probability exceeding USEPA maximum contaminant level 3.0 μg L. These are for regulatory purposes but rather used (i) identify potential concern, (ii) provide conservative estimates deeper drinking supplies, (iii) set priorities among future monitoring.