Preliminary investigation of groundwater quality near a Michigan cemetery, 2016–17

Angela K. Brennan; Carrie E. Givens; Julia G. Prokopec; Christopher J. Hoard

doi:10.3133/sir20185120

Home/Archive/USGS

USGS · sir20185120

Preliminary investigation of groundwater quality near a Michigan cemetery, 2016–17

Angela K. Brennan·Carrie E. Givens·Julia G. Prokopec·Christopher J. Hoard

View original source ↗Read source document ↗Export metadata ↓

Abstract

The potential effect of cemetery leachate on groundwater quality in the United States has rarely been studied. Nutrients and other constituents associated with decomposition and burial processes (such as embalming) have the potential to reach shallow groundwater and could affect nearby drinking-water sources. The objective of this preliminary investigation was to evaluate the potential effect of cemetery leachate on shallow groundwater quality near Mt. Hope Cemetery in Ingham County, Lansing, Michigan, which is within the Well-head Protection Area for the City of Lansing. The constituents measured in this study include nutrients, trace metals, formaldehyde, fecal indicator bacteria, bacterial pathogen genes, contaminants of emerging concern (including pharmaceuticals, personal care products, and wastewater indicator compounds), and age-dating compounds. Three monitoring wells were installed 7 to 12 feet below land surface downgradient from the cemetery and sampled quarterly for 1 year. A fourth well (Fenner) was sampled to determine groundwater conditions outside the potential effects of cemetery leachate; samples from this well were collected near the water table. Nitrogen and phosphorus compounds were present at higher concentrations in two of the three monitoring wells (wells C1 and C3) than in the Fenner well. Formaldehyde and pharmaceuticals were not detected in any of the wells; however, several trace metals, including arsenic, manganese, and aluminum, were present in high concentrations, with arsenic concentrations typically exceeding the U.S. Environmental Protection Agency (EPA) drinking-water standard. Several wastewater indicator compounds, including atrazine, phenol, p-cresol, camphor, and skatole, were detected in the monitoring wells. Microbial data indicate the presence of staphylococci, enterococci, and Escherichia coli (E. coli) , with the highest concentrations being measured in the same two monitoring wells that exhibited elevated concentrations of nutrients in the groundwater (wells C1 and C3). Several bacterial pathogen genes were detected, including several Enterococcus species (spp.)— vanB (vancomycin-resistant enterococci), shiga-toxin-producing E. coli genes (including eaeA [attachment virulence trait] and stx1 [moderate toxin]), and the E. coli 16s ribosomal RNA (rDNA) gene ( E. coli species marker). These results were similar to results of studies conducted in Canada, Australia, and the United Kingdom, in which concentrations of bacteria, metals, and nutrients were elevated in groundwater near cemeteries.

Explore related subjects

Scientific Investigations Report Report

Source-reported bounding extent: 42.70460970722399° to 42.711862740860546° latitude; -84.52966690063477° to -84.51863765716553° longitude. This indicates report coverage, not an exact sampling location. View area on OpenStreetMap.

Keep this discovery

Explore connections, maps & timelines

BibTeX RIS

Angela K. Brennan, Carrie E. Givens, Julia G. Prokopec, Christopher J. Hoard. 2018-10-24. Preliminary investigation of groundwater quality near a Michigan cemetery, 2016–17. https://doi.org/10.3133/sir20185120

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

KEEP EXPLORING

Related USGS reports

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.

Scientific Investigations Report↗

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↗

USGS2026

World minerals outlook—Antimony, copper, graphite, niobium, potash, silicon, silver, and tungsten through 2030

Demand for mineral commodities continues to increase owing to rapid technological advancements and global economic growth. To support this increase in demand, information about current and near-term supplies of these mineral commodities is essential. Such data help evaluate the health and stability of global supply chains and protect against potential supply risks. Current production and production capacity data coupled with information regarding near-term expected changes (such as facility closures, planned expansions, or the completion of new mineral production projects) can provide insight into expected future market developments and expected available supply of mineral commodities. This report within the “World Minerals Outlook” series analyzes data for antimony, copper, natural graphite, niobium, potash, silicon metal, silver, and tungsten—eight mineral commodities listed in the 2025 List of Critical Minerals. World production data from 2019 through 2025, as well as estimated world capacity data from 2023 through 2025 were analyzed. Using these data, near-term (2026–2030) expected world capacities were estimated. For antimony, copper, niobium, silicon metal, silver, and tungsten, modest increases in production capacity of 4 to 10 percent were expected between 2025 and 2030, whereas capacities for natural graphite and potash were expected to increase by about 18 to 20 percent.

Scientific Investigations Report↗