Contaminants in groundwater linked to agricultural land use

Contaminants in groundwater linked to agricultural land use

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US, November 13, 2014: Groundwater contamination that was first detected in Chesterfield County in the early 2000s has been linked to historical agricultural land use, according to a recent U.S. Geological Survey study.

Scientists used water-quality data, numerical simulations and historical aerial photographs to link three major contaminants found in local aquifers to the agricultural land use. The three contaminants exceed the Environmental Protection Agency’s maximum allowed levels in groundwater pumped from public-supply wells in the Crouch Branch and McQueen Branch aquifers.

For the study, the location of each well, spring, and soil-gas sampler was determined by the USGS using a global positioning system reporting latitude and longitude using the North American Datum of 1983 (NAD 83). The groundwater levels were measured at the monitoring wells in near-real time, and data collected is available at the USGS National Water Information System (NWIS).

Groundwater pumped by the wells most likely became contaminated due to the fact that the recharge areas for the contaminated wells — the land-surface area where rainfall enters the earth and fills the aquifer– are located in historically agricultural areas. Groundwater pumped from some public-supply wells was also found to contain elevated levels of total radium isotopes–derived from the breakdown of naturally occurring uranium- and thorium-bearing sediments in the aquifers. Groundwater pumped from these contaminated wells also passed through recharge areas located in the areas used for agriculture since the early 1900s.

To complete the study, scientists from the USGS South Atlantic Water Science Center collected water-quality data from 2010 and 2012. Groundwater samples were collected from multiple public-supply, domestic-supply, agricultural-supply and monitoring wells throughout the study area. Wells with contaminated groundwater were found to be clustered in specific areas.

Source: USGS