Methods for Minimization and Management of Variability in Long Term Groundwater Monitoring Results

Abstract

The purpose of this project was to: 1) validate sample collection methods and procedures that minimize variability in groundwater monitoring results; and 2) validate improved methods to optimize monitoring frequency and assess long-term concentration trends that better account for short-term variability in groundwater monitoring results. All three objectives of the project were met. The demonstration results indicated that the sample method (except active no purge) has only a modest impact on monitoring variability and concentration, suggesting sampling methods should be selected based on factors such as cost, ease of implementation, and sample volume requirements rather than concerns regarding data quality. At both sites, low flow standard (purging to parameter stability) and low flow alternative (small volume) showed the lowest variability. The results were consistent between the two sites except for the active no purge (HydraSleeve) method, which was more variable at the California site than the Texas site. Low flow small volume purge and passive no-purge (SNAP sampler) were the two best sampling methods based on the combined goals of minimizing monitoring cost and minimizing variability in monitoring results.

Method for Assessing Source Zone Natural Depletion at Chlorinated Aliphatic Spill Sites

“…Finally, it should be noted that uncertainties inherent in the SZNA rate estimation are difficult to quantify. This reflects uncertainties in all of the measured quantities used in the discharge calculations, especially errors in concentration data (up to 30%; McHugh et al ), errors in hydraulic conductivity measurement (2× to 10×), errors in measurement of hydraulic gradient (2×), differences in results for different data interpolation methods (log, linear, nearest neighbor; 2× to 5×), and uncertainty related to the spatial resolution (sampling density) of transect data. Some have suggested that uncertainty caused by the latter increases with decreasing spatial resolution of transect data and sampling densities of 1–7% of the discharge surface area may be required to achieve accurate discharge estimates (e.g., Kubert et al 2006; Li et al ; Mackay et al ).…”

Passive Sampling with Active Carbon Fibres in the Determination of Organic Pollutants in Groundwater

“…A passive sampler can cover a long sampling period and integrate pollutant concentrations over time. Although compared to conventional monitoring, the use of passive samplers can significantly reduce analytical costs, a validation procedure that includes an assessment of the degree of sampling uncertainty remains a challenge [15,17,[40][41][42][43][44][45][46][47][48][49].…”