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Model Report

SCREENING CONCENTRATION IN GROUND WATER

Last Revision Date: 08/25/2009 View as PDF
General Information Back to Top
Model Abbreviated Name:

SCI-GROW
Model Extended Name:

SCREENING CONCENTRATION IN GROUND WATER
Model Overview/Abstract:
SCI-GROW is a simple, empirically based point estimate model. SCI-GROW estimates are based on the results of pesticide ground-water monitoring studies conducted in areas where the ground water is less than 30 feet deep and the soil, weather, and overall hydrogeologic environment is such that the ground water is considered to be highly vulnerable to contamination by certain pesticides applied to the surface. SCI-GROW is used by EPA's Office of Pesticides as a tier 1 screening model for ground water / drinking water exposure. SCI-GROW is designed to minimize the amount of analysis required to evaluate pesticides that are unlikely to reach ground water that could be used as drinking water. When the Agency determines that the pesticide does not pose a significant risk to human health at the screening concentration returned by SCI-GROW, then there is no need for further analysis of existing monitoring data, requirements for forward monitoring to further assess the risk, or higher tier modeling. Conversely, when the SCI-GROW screening concentration is of concern, additional data analysis and/or new monitoring programs or modeling may be required to assess the potential risk in detail. The Office of Pesticide Programs (OPP) does not take significant regulatory action based upon the results of tier 1 screening models.
Keywords:
Model Technical Contact Information:
Michael R. Barrett
Environmental Fate and Effects Division
Office of Pesticide Programs
Barrett.Michael@epa.gov
(703) 305-6391
Model Homepage: http://www.epa.gov/oppefed1/models/water/index.htm

User Information Back to Top
Technical Requirements
Computer Hardware
Any PC
Compatible Operating Systems
DOS, Windows95/98/2000/XT/XP
Download Information
The SCI-GROW model is available to be downloaded.
Using the Model
Basic Model Inputs
Pesticide label application information, physico-chemical properties of the pesticide.
Basic Model Outputs
Pesticide concentration representing the most probable concentration in ground water less than 30-feet deep in a highly vulnerable hydrogeologic setting.
User Support
User's Guide Available?
Currently, the SCI-GROW Use's Guide must be requested from EPA. In the future, it will in the future be available here.

Model Science Back to Top
Problem Identification
SCI-GROW is a regression model that relates observed concentrations in ground water considered to be highly vulnerable to contamination to pesticides.
Summary of Model Structure and Methods
SCI-GROW utilizes as a primary source of data for the regression results of prospective ground-water monitoring studies that were previously required to support the registration of pesticides. In the past, this was the only way to obtain information on the kinds of concentrations of pesticides that might occur in highly vulnerable ground water. SCI-GROW regresses this prior experience of observed concentrations of pesticides previously subjected to these intensive site investigations to the use rate and the soil adsorption coefficients and degradation rates of the pesticides, SCI-GROW has been secondarily compared to upper bound concentrations of pesticides observed in large-scale monitoring surveys. The model is based on a body of experience that has demonstrated that the amount of pesticides that leaches in soils is most strongly correlated with three parameters: the application rate of the pesticide, the soil adsorption coefficient, and its degradation rate. Comparisons with monitoring surveys provide support for its utility as a screening model that provides realistic estimates of concentrations of pesticides that will only be observed in a very small percentage of drinking water sources that tap ground water that is highly susceptible to contamination.

The regression for SCI-GROW is not directly based on concentrations observed for pesticides with very high adsorption coefficients or very rapid degradation rates because these compounds do not leach significantly and there are no field-scale studies to confirm their occurrence in vulnerable ground water (which, if true, would probably be at concentrations too low to detect). However, comparisons with large scale monitoring survey results confirm that SCI-GROW provides an effective screening tool for such compounds as well.

Model Evaluation
Model QA/QC assessment has been performed and rests with the OPP/EFED quality control officer.

Performance of SCI-GROW as a screening model has been evaluated by comparisons with large-scale modeling surveys. The core of the analysis is two large-scale surveys (chosen because of their scope, high level of characterization of monitoring sites, and quality of residue analysis; other available datasets are inferior in one or more of these characteristics):

1. USGS' National Water Quality Assessment (NAWQA) program is the most comprehensive monitoring dataset available for evaluating the ability of SCI-GROW to bound (i.e., provide a screening value that is modestly higher than observed upper-bound concentrations) the vast majority of concentrations observed in ground water. The NAWQA dataset is expected to represent ground-water that is in general more vulnerable to pesticide contamination than most ground water sourced drinking water; many NAWQA wells that were not drinking water wells were observation wells installed in areas where susceptibility of the ground water to contamination from nearby pesticide use was expected to be high. Special characteristics of NAWQA include:

  • Largest scale study covering a large number of pesticide analytes with realistic detection limits.
  • Significant attempts to associate the detections with local pesticide use, land use, and hydrogeologic information.
  • Multi-year study.
2. The National Alachlor Well Water Survey was a large-scale statistically designed study that focused on the population of domestic drinking water wells in the United States located adjacent to corn fields highly likely to be treated with alachlor. Other corn herbicides were also analyzed for in the collected samples. Special characteristics of NAWWS include:
  • Largest scale study with specific association of well locations to local use of specific pesticides.
  • Statistically representative of all domestic drinking water wells in the study area.
To further test the performance of SCI-GROW as a Tier 1 screen, we compared this screening tool to the results of the National Alachlor Well Water Survey (NAWWS) of approximately 1430 domestic drinking water wells in the United States all located in corn and soybean production areas where an alachlor use history had been demonstrated (Holden et al., 1992; Environ. Sci. Technol. 26:935-943). This study was submitted to EPA as data on the impact of alachlor use on ground water used for drinking water. Four other herbicides were also analyzed for which also had significant use in the study area: atrazine, metolachlor, cyanazine, and simazine. The only pesticide for which there was an exceedance of the screening concentration at the 99.8 percentile level was alachlor; there were no exceedances at the 99.5 percentile level.

Possible reasons for the few exceedances at the 99.8 percentile level in either the NAWQA or NAWWS data sets include:

  • The environmental fate data for these pesticides may not be appropriately representative.
  • Other factors influence the occurrence of these pesticides in ground water, such as point source contamination, preferential flow, etc.


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