Stochastic Analysis of Pesticide Transport in the Shallow Groundwater of Oatland Island, Georgia, USA

Analytical models, when used in stochastic analysis mode, may provide an effective tool for making informed management decisions for simplified environmental systems. This approach was used to evaluate migration of an organochlorine pesticide plume in a shallow, unconfined aquifer underlying a barrier island in coastal Georgia, USA. The contaminant plume at the site consists of four isomers of benzene hexachloride (BHC), also known as hexachlorocyclohexane (HCH). The deterministic analysis conducted at the site, which used calibrated, single-value input parameters, indicates that the contaminant plume will not reach wetlands that are downgradient of the source. Given the uncertainties involved in the deterministic analysis, this outcome was not considered to be sufficient to make effective management decisions at the site. Subsequently, probabilistic analysis using a range of input parameter values was conducted to estimate the risk that the pesticide plume would reach the downgradient wetlands. The two-stage Monte Carlo analysis that was conducted indicates the probability that contaminant levels will exceed the detection limit of BHC (0.044 micrograms per liter) at the wetlands increases from 1 percent to a maximum of 13 percent during the period 2005–2065. This represents an 87% or greater confidence level that the pesticide plume will not reach the wetlands. This outcome was used to inform environmental management decisions at the site. The modeling analysis was conducted using the publicly available analytical contaminant transport analysis system (ACTS) software.