Geology Reports⌕ Search

USGS · sir20165073

Baseline assessment of groundwater quality in Wayne County, Pennsylvania, 2014

Abstract

The Devonian-age Marcellus Shale and the Ordovician-age Utica Shale, geologic formations which have potential for natural gas development, underlie Wayne County and neighboring counties in northeastern Pennsylvania. In 2014, the U.S. Geological Survey, in cooperation with the Wayne Conservation District, conducted a study to assess baseline shallow groundwater quality in bedrock aquifers in Wayne County prior to potential extensive shale-gas development. The 2014 study expanded on previous, more limited studies that included sampling of groundwater from 2 wells in 2011 and 32 wells in 2013 in Wayne County. Eighty-nine water wells were sampled in summer 2014 to provide data on the presence of methane and other aspects of existing groundwater quality throughout the county, including concentrations of inorganic constituents commonly present at low levels in shallow, fresh groundwater but elevated in brines associated with fluids extracted from geologic formations during shale-gas development. Depths of sampled wells ranged from 85 to 1,300 feet (ft) with a median of 291 ft. All of the groundwater samples collected in 2014 were analyzed for bacteria, major ions, nutrients, selected inorganic trace constituents (including metals and other elements), radon-222, gross alpha- and gross beta-particle activity, selected man-made organic compounds (including volatile organic compounds and glycols), dissolved gases (methane, ethane, and propane), and, if sufficient methane was present, the isotopic composition of methane. Results of the 2014 study show that groundwater quality generally met most drinking-water standards, but some well-water samples had one or more constituents or properties, including arsenic, iron, pH, bacteria, and radon-222, that exceeded primary or secondary maximum contaminant levels (MCLs). Arsenic concentrations were higher than the MCL of 10 micrograms per liter (µg/L) in 4 of 89 samples (4.5 percent) with concentrations as high as 20 µg/L; arsenic concentrations were higher than the Health Advisory level of 2 µg/L in 27 of 89 samples (30 percent). Total iron concentrations exceeded the secondary maximum contaminant level (SMCL) of 300 µg/L in 9 of 89 samples (10 percent). The pH ranged from 5.4 to 9.3 and did not meet the SMCL range of greater than 6.5 to less than 8.5 in 27 samples (30 percent); 22 samples had pH values less than 6.5, and 5 samples had pH values greater than 8.5. Total coliform bacteria were detected in 22 of 89 samples (25 percent); Escherichia coli were detected in only 2 of those 22 samples. Radon-222 activities ranged from 25 to 7,400 picocuries per liter (pCi/L), with a median of 2,120 pCi/L, and exceeded the proposed drinking-water standard of 300 pCi/L in 86 of 89 samples (97 percent); radon-222 activities were higher than the alternative proposed standard of 4,000 pCi/L in 12 of 89 samples (13.5 percent). Water from 8 of the 89 wells (9 percent) had concentrations of methane greater than the reporting level of 0.24 milligrams per liter (mg/L) with the detectable methane concentrations ranging from 0.74 to 9.6 mg/L. Of 16 replicate samples submitted to another laboratory with a lower reporting level of 0.0002 mg/L, 15 samples had detectable methane concentrations that ranged from 0.0011 to 9.7 mg/L. Of these 15 samples, low levels of ethane (0.00032 to 0.0017 mg/L) were detected in 6 of 7 samples with methane concentrations greater than 0.75 mg/L. The isotopic composition of methane in 6 of 8 samples with sufficient dissolved methane (about 1 mg/L) for isotopic analysis is consistent with a predominantly thermogenic methane source (sample carbon isotopic ratio δ13C CH4 values ranging from -56.36 to -45.97 parts per thousand (‰) and hydrogen isotopic ratio δD CH4 values ranging from -233.1 to -141.1 ‰). However, the low levels of ethane relative to methane indicate that the methane may be of microbial origin and subsequently underwent oxidation. Isotopic compositions indicated a possibly mixed thermogenic and microbial source (carbon dioxide reduction process) for the methane in 1 of the 8 samples (δ 13 C CH4 of -63.72 and δD CH4 of -192.3 ‰) and potential oxidation of microbial and (or) thermogenic methane in the remaining sample (δ 13 C CH4 of -46.56 and δD CH4 of -79.7 ‰). Groundwater samples with relatively elevated methane concentrations (near or greater than 1 mg/L) had a chemical composition that differed in some respects (pH, selected major ions, and inorganic trace constituents) from groundwater with relatively low methane concentrations (less than 0.75 mg/L). The seven well-water samples with the highest methane concentrations (from about 1 to 9.6 mg/L) also had among the highest pH values (8.1 to 9.3, respectively) and the highest concentrations of sodium, lithium, boron, fluoride, arsenic, and bromide. Relatively elevated concentrations of some other constituents, such as barium, strontium, and chloride, commonly were present in, but not limited to, those well-water samples with elevated methane. Groundwater samples with the highest methane concentrations had chloride/bromide ratios that indicate mixing with a small amount of brine (0.02 percent or less, by volume) similar in composition to that reported for gas and oil well brines in Pennsylvania. Most other samples with low methane concentrations (less than about 1 mg/L) had chloride/bromide ratios that indicate predominantly man-made sources of chloride, such as road salt, septic systems, and (or) animal waste. Although naturally occurring brines may originate from deeper parts of the aquifer system, the man-made sources are likely to affect shallow groundwater. Geochemical modeling showed that the water chemistry of samples with elevated pH, sodium, lithium, bromide, and alkalinity could result from dissolution of calcite (calcium carbonate) combined with cation exchange and mixing with a small amount of brine. Through cation exchange reactions (which are equivalent to processes in a water softener) calcium ions released by calcite dissolution are exchanged for sodium ions on clay minerals. The spatial distribution of groundwater compositions generally shows that (1) relatively dilute, slightly acidic, oxygenated, calcium-carbonate type waters tend to occur in the uplands along the western border of Wayne County; (2) waters of near neutral pH with the highest amounts of hardness (calcium and magnesium) generally occur in areas of intermediate altitudes; and (3) waters with pH values greater than 8, low oxygen concentrations, and the highest arsenic, sodium, lithium, bromide, and methane concentrations can occur in deep wells in uplands but most frequently occur in stream valleys, especially at low elevations (less than about 1,200 ft above North American Vertical Datum of 1988) where groundwater may be discharging regionally, such as to the Delaware River. Thus, the baseline assessment of groundwater quality in Wayne County prior to gas-well development shows that shallow (less than about 1,000 ft deep) groundwater is generally of good quality, but methane and some constituents present in high concentrations in brine (and produced waters from gas and oil wells) may be present at low to moderate concentrations in some parts of Wayne County.

Explore related subjects

90° N90° S · 180° W ← longitude → 180° E
Source-reported bounding extent: 41.2324° to 41.9992° latitude; -75.5059° to -75.0446° longitude. This indicates report coverage, not an exact sampling location. View area on OpenStreetMap.

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Lisa A. Senior, III Cravotta, Ronald A. Sloto. 2016-06-30. Baseline assessment of groundwater quality in Wayne County, Pennsylvania, 2014. https://doi.org/10.3133/sir20165073

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

KEEP EXPLORING

Related USGS reports

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↗

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↗

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↗