Comparison of diffusion- and pumped-sampling methods to monitor volatile organic compounds in ground water, Massachusetts Military Reservation, Cape Cod, Massachusetts, July 1999–December 2002

Stacey A. Archfield; Denis R. LeBlanc

doi:10.3133/sir20055010

Home/Archive/USGS

USGS · sir20055010

Comparison of diffusion- and pumped-sampling methods to monitor volatile organic compounds in ground water, Massachusetts Military Reservation, Cape Cod, Massachusetts, July 1999–December 2002

Stacey A. Archfield·Denis R. LeBlanc

View original source ↗Export metadata ↓

Abstract

To evaluate diffusion sampling as an alternative method to monitor volatile organic compound (VOC) concentrations in ground water, concentrations in samples collected by traditional pumped-sampling methods were compared to concentrations in samples collected by diffusion-sampling methods for 89 monitoring wells at or near the Massachusetts Military Reservation, Cape Cod. Samples were analyzed for 36 VOCs. There was no substantial difference between the utility of diffusion and pumped samples to detect the presence or absence of a VOC. In wells where VOCs were detected, diffusion-sample concentrations of tetrachloroethene (PCE) and trichloroethene (TCE) were significantly lower than pumped-sample concentrations. Because PCE and TCE concentrations detected in the wells dominated the calculation of many of the total VOC concentrations, when VOC concentrations were summed and compared by sampling method, visual inspection also showed a downward concentration bias in the diffusion-sample concentration. The degree to which pumped- and diffusion-sample concentrations agreed was not a result of variability inherent within the sampling methods or the diffusion process itself. A comparison of the degree of agreement in the results from the two methods to 13 quantifiable characteristics external to the sampling methods offered only well-screen length as being related to the degree of agreement between the methods; however, there is also evidence to indicate that the flushing rate of water through the well screen affected the agreement between the sampling methods. Despite poor agreement between the concentrations obtained by the two methods at some wells, the degree to which the concentrations agree at a given well is repeatable. A one-time, well-bywell comparison between diffusion- and pumped-sampling methods could determine which wells are good candidates for the use of diffusion samplers. For wells with good method agreement, the diffusion-sampling method is a time-saving and cost-effective alternative to pumped-sampling methods in a long-term monitoring program, such as at the Massachusetts Military Reservation.

Explore related subjects

Scientific Investigations Report Report

Source-reported bounding extent: 41.5958° to 41.7083° latitude; -70.625° to -70.5° longitude. This indicates report coverage, not an exact sampling location. View area on OpenStreetMap.

Keep this discovery

Explore connections, maps & timelines

BibTeX RIS

Stacey A. Archfield, Denis R. LeBlanc. 2005. Comparison of diffusion- and pumped-sampling methods to monitor volatile organic compounds in ground water, Massachusetts Military Reservation, Cape Cod, Massachusetts, July 1999–December 2002. https://doi.org/10.3133/sir20055010

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related USGS reports

USGS2026

Analysis of groundwater geochemistry in the Lansing, Michigan, area

Groundwater resources in the Lansing, Michigan, area are protected by a wellhead protection plan, but previous studies have indicated that groundwater in this area may be susceptible to surface contamination. The U.S. Geological Survey, in cooperation with the Lansing Board of Water & Light, analyzed geochemical and aquifer characteristics to assess the potential for contamination of groundwater resources. Recharge age categories were determined from tritium concentrations for some wells, and by using ternary diagrams and principal component analysis for other wells. These age classifications, combined with hydrogeologic and geochemical data, were analyzed by using statistical methods to identify trends that may indicate areas of increased groundwater susceptibility. Wells with modern recharge tended to have higher sodium, chloride, and chloride:bromide ratios than did wells with mixed recharge, suggesting greater surface connectivity and potential influence from anthropogenic sources such as road salt. In contrast, wells in the mixed age category exhibited more stable geochemistry and lower constituent concentrations. Classification and regression tree models identified aquifer geometry—particularly the thickness of the uppermost bedrock unit and presence of confining layers—as key predictors of recharge age and geochemical indicators. The trends identified from these analyses could help to reveal locations in the Lansing area that are among the most susceptible to contamination.

Scientific Investigations Report↗

USGS2026

Evaluating the number of realizations (train-test splits) necessary to ensure robust estimates of conventional hydrothermal resource favorability using Monte Carlo cross-validation, the Great Basin, Western USA

Supervised machine learning approaches used to produce favorability maps in resource assessments commonly partition an input dataset into training and testing subsets (that is, through train-test splits). However, if a single split is not representative of underlying resource conditions, the resulting favorability map may be biased, particularly with sparse or heterogeneous datasets. To mitigate the potential for unrepresentative favorability maps, recent works by U.S. Geological Survey researchers have used Monte Carlo cross-validation to implement a large number ( n) of randomized train-test splits to produce n realizations. The realizations are then aggregated using cell-wise median predictions to produce the resulting final favorability map, recognizing that the median will remove extreme values that might have been estimated from a comparatively few unrepresentative realizations. Theoretically, the median prediction at every cell converges to a single estimate as n approaches infinity, and the question addressed herein is: How many realizations are necessary to get a robust estimate (that is, an estimate unaffected by additional realizations)? Therefore, convergence metrics are described to identify the number of train-test splits and realizations needed to make a reliable map using the data and supervised machine learning workflow for conventional hydrothermal resource assessment of the Great Basin of the Western United States. For this study, robust prediction occurs with n approximately equal to 600 realizations, and smaller ensembles (for example, n is approximately equal to 200 or even 100) may be suitable during preliminary or exploratory analyses. Although the resulting threshold numbers will vary depending on the data and modeling approach used, the convergence metrics proposed and applied herein are applicable to other supervised machine learning studies that use Monte Carlo cross-validation.

California, Idaho, Nevada, Oregon, Utah↗

USGS2026

Groundwater budget for the Portneuf River Basin, southeastern Idaho

The U.S. Geological Survey, in cooperation with the Idaho Department of Water Resources, developed the first groundwater budget for the upper Portneuf River Basin in southeastern Idaho, a tributary of the Snake River. A groundwater budget for the Portneuf River Basin supports water resource and administrative management decisions within the basin and for downstream users of the eastern Snake River Plain aquifer. The analysis quantifies inflows, outflows, and residuals for an aquifer system defined by the Idaho Department of Water Resources under three recent precipitation conditions: an average year (2016), a dry year (2021), and a wet year (2023). The budget was calculated for the basin and for two subbasins delineated by the U.S. Geological Survey streamgage Portneuf River at Topaz, Idaho (13073000): the above Topaz subbasin, which includes the Portneuf-Gem valley, and the below Topaz subbasin, which includes Marsh Valley. Aquifer inflows include mountain-front recharge; areal recharge; recharge from applied water, including recharge from irrigation, canal seepage, and effluent returns; groundwater flow into the basin; and reservoir seepage. Outflows include groundwater pumping for agricultural, municipal, and domestic uses; subsurface outflow through the Portneuf gap; and discharge to streams as base flow. Estimated annual inflows for the full basin ranged from 116,880 acre-feet in 2021 to 154,880 acre-feet in 2023, and outflows ranged from 132,190 acre-feet in 2016 to 158,490 acre-feet in 2023. Basinwide residuals, the change in storage plus uncertainty, were −2,410 acre-feet in 2016, −18,410 acre-feet in 2021, and −3,610 acre-feet in 2023, and each subbasin had a mixture of negative and positive residuals. These basinwide results, interpreted as change in storage plus water-budget uncertainty, indicate minor net losses that increase with dry conditions, consistent with well depth-to-water measurements indicating gradual multi-decadal declines. Patterns in subbasin residuals are driven by irrigation practices and surface-water management; for example, the above Topaz subbasin relies more on groundwater for irrigation, resulting in more negative residuals during dry years. In contrast, the below Topaz subbasin depends more on surface water, producing positive residuals during dry years because of irrigation losses and canal seepage. The analyses for both subbasins indicate decades-long groundwater declines, which agree with the overall negative residuals calculated. The largest sources of uncertainty include climate inputs (precipitation and evapotranspiration) and poorly constrained components such as groundwater inflow and tributary stream infiltration. These findings provide insight into how climatic variables and irrigation practices affect groundwater inflows and outflows within the Portneuf River Basin.

Idaho↗