Ground-Water Pesticide Monitoring in Areas with Different Vulnerability Ratings

WRD PROJECT #: MD168
PROJECT CHIEF: Bolton, David
BEGIN DATE: 01-June-2001
END DATE: 31-March-2002

Customers currently supporting the project:

Maryland Geological Survey
U.S. Geological Survey

Problem

Ground water in the surficial aquifer of Maryland's Eastern Shore is particularly susceptible to contamination due to the shallow depth of the water, the lack of a protective confining layer, and the extensive agricultural activity there (Bachman, 1984; Hamilton and others, 1993; Koterba and others, 1993; Shedlock and others, 1999). Maps showing the relative vulnerability of surficial aquifers to pesticide contamination were developed by the Maryland Geological Survey (MGS) in 1999. However, the relation between pesticide vulnerability and ground-water pesticide concentrations has not been investigated. This proposal presents a plan to collect data that will help evaluate this relation.

Objectives

1. Collect and analyze water samples from approximately 30 wells in the surficial aquifer of Maryland's Eastern Shore.
2. Evaluate pesticide and other water-quality data with respect to pesticide vulnerability and other factors.

Approach

1. Purchase necessary equipment and supplies.
2. Identify areas with different degrees of relative vulnerability to pesticide contamination.
3. Obtain permission to sample approximately 30 wells in three areas having different pesticide vulnerabilities.
4. Compile a list of all ground-water analyses for atrazine, alachlor, metolachlor, and simazine in the study area. Data will come from U.S. Geological Survey (USGS) and MGS databases.
5. Collect water samples from wells. Samples will be analyzed for a suite of pesticides, major ions, and nutrients.
6. Analyze pesticide detection data (particularly atrazine, alachlor, metolachlor, and simazine) and other water-quality measures in relation to pesticide vulnerability, land use, hydrogeology, and other relevant factors. Pre-existing pesticide data from MGS and USGS databases will be included, to the extent possible.
7. Write a document that summarizes the data analysis and contains all data used in the study.