Ground‐Water Sampling and Time‐Series Evaluation Techniques to Determine Vertical Concentration Distributions

Abstract

AbstractData analysis methodologies are developed for using time‐series measurements of effluent concentrations during continuous sampling to determine the vertical shape and location of a horizontally uniform contaminant plume and to estimate physical/ chemical aquifer parameters such as vertical anisotropy, effective porosity, and retardation factor. Temporal water‐quality variations during constant‐flow sampling are calculated in the form of concentration type curves for a wide variety of plume shapes and positions and are shown to be directly related to the geometry and growth rate of the three‐dimensional capture volume of the well. An analytical type‐curve solution is derived for discrete‐interval sampling in homogeneous and isotropic/anisotropic aquifers containing plumes with complex vertical shapes that are described by the superposition of multiple Gaussian distributions. Results from two‐dimensional, axisymmetric simulations of ground‐water flow and particle transport demonstrate the sensitivity of concentration type curves to sandpack hydraulic conductivity, screen length, well diameter, flow through the well screen during discrete‐interval sampling, aquifer anisotropy and heterogeneities, pumping rate, effective porosity, and chemical retardation. Two applications of the concentration type‐curve method for determining plume and aquifer characteristics are presented. The first illustrates the use of discrete‐interval sampling to evaluate the vertical shape and location of a hypothetical plume in a homogeneous, isotropic aquifer. In the second, extraction‐well effluent data collected during a field experiment were used to evaluate the vertical concentration distribution in a sulfate plume and estimate the vertical anisotropy ratio of the aquifer. The results demonstrate the importance of developing consistency in purge and sample volumes to minimize artificial measurement variability in monitoring programs.