With the decline of bee populations worldwide, studies determining current wild bee distributions and diversity are increasingly important. Wild bee identification is often completed by experienced taxonomists or by genetic analysis. The current study was designed to compare two methods of identification including: (1) morphological identification by experienced taxonomists using images of field-collected wild bees and (2) genetic analysis of composite bee legs (multiple taxa) using metabarcoding. Bees were collected from conservation grasslands in eastern Iowa in summer 2019 and identified to the lowest taxonomic unit using both methods. Sanger sequencing of individual wild bee legs was used as a positive control for metabarcoding. Morphological identification of bees using images resulted in 36 unique taxa among 22 genera, and >80% of Bombus specimens were identified to species. Metabarcoding was limited to genus-level assignments among 18 genera but resolved some morphologically similar genera. Metabarcoding did not consistently detect all genera in the composite samples, including kleptoparasitic bees. Sanger sequencing showed similar presence or absence detection results as metabarcoding but provided species-level identifications for cryptic species (i.e., Lasioglossum). Genus-specific detections were more frequent with morphological identification than metabarcoding, but certain genera such as Ceratina and Halictus were identified equally well with metabarcoding and morphology. Genera with proportionately less tissue in a composite sample were less likely to be detected using metabarcoding. Image-based methods were limited by image quality and visible morphological features, while genetic methods were limited by databases, primers, and amplification at target loci. This study shows how an image-based identification method compares with genetic techniques, and how in combination, the methods provide valuable genus- and species-level information for wild bees while preserving tissue for other analyses. These methods could be improved and transferred to a field setting to advance our understanding of wild bee distributions and to expedite conservation research.
Municipal and industrial wastewater effluent is an important source of water for lotic systems, especially during periods of low flow. The accumulated wastewater effluent flows—expressed as a percentage of total streamflow (ACCWW%)—contain chemical mixtures that pose a risk to aquatic life; fish may be particularly vulnerable when chronically exposed. Although there has been considerable focus on individual-level effects of exposure to chemical mixtures found in wastewater effluent, scaling up to population-level effects remains a challenging component needed to better understand the potential consequences of exposure in wild populations. This may be particularly important under a changing climate in which wastewater reuse could be essential to maintain river flows. We evaluated the effects of chronic exposure to wastewater effluent, as measured by ACCWW%, on the relative abundance of young-of-year (YOY), juvenile, and adult smallmouth bass (Micropterus dolomieu) populations in the Shenandoah River Watershed (USA). We found that increases in ACCWW% in the previous year and during the prespawn period were negatively correlated with the relative abundance of YOY, resulting in an average 41% predicted decrease in abundance (range = 0.5%–94% predicted decrease in abundance). This lagged effect suggests that adult fish reproductive performance may be compromised by chemical exposure during periods of high ACCWW%. No relationships between ACCWW% and juvenile or adult relative abundance were found, suggesting that negative effects of ACCWW% on YOY abundance may be offset due to compensatory mechanisms following higher ACCWW% exposure. Understanding the effects of wastewater effluent exposure at multiple levels of biological organization will help in the development of management strategies aimed at protecting aquatic life. Environ Toxicol Chem 2024;43:1138–1148. © 2024 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.
The U.S. Geological Survey (USGS) collected data on the vertical distribution of hydraulic head, specific capacity, and water quality using aquifer-interval-isolation tests and other vertical profiling methods in 15 boreholes completed in fractured sedimentary bedrock in Northampton, Warminster, and Warwick Townships, Bucks County, Pennsylvania during 2018–19. This work was done, in cooperation with the U.S. Navy, to support detailed investigations at and near the former Naval Air Warfare Center (NAWC) Warminster, where groundwater contamination with per- and polyfluoroalkyl substances (PFAS) had become a concern since 2014. Two PFAS compounds, perfluorooctanesulfonic acid (PFOS) and perfluorooctanoic acid (PFOA), have been measured in groundwater samples from supply and monitoring wells at or near NAWC Warminster in concentrations above U.S. Environmental Protection Agency health advisory levels for drinking water. The area is underlain by the Triassic Stockton Formation, which predominantly consists of sandstone interbedded with shale and siltstone beds and forms a layered fractured-rock aquifer used for private, industrial, and public drinking water supply.
The vertical distribution of aquifer properties and water quality was assessed through hydraulic tests and sampling of aquifer intervals using a straddle-packer system (13 boreholes) or depth-discrete point sampling under known borehole-flow conditions (2 boreholes). Geophysical and video logs collected by USGS during 2017–19 were used to identify potential water-bearing fractures in 15 boreholes, which ranged in depth from 210 to 604 feet (ft) and included 6 boreholes drilled in 2018 and 9 existing wells on or near the former NAWC Warminster. Measured borehole flow was predominantly downward in most of the deepest boreholes (greater than 400 ft), which were commonly located at the highest land-surface elevations, with inflow from fractures at relatively shallow depths and outflow through fractures near or below depths of 500 ft below land surface. Hydraulic head differences measured during packer tests were up to about 60 ft between shallow and deep intervals. Borehole flow was predominantly upward in most boreholes less than 400 ft in depth and farther from, and at lower land-surface elevations than, the former NAWC Warminster. Total borehole specific capacity ranged from about 0.07 to 41 gallons per minute per foot [(gal/min)/ft]. Specific-capacity values for individual intervals ranged from 0.02 to 40.0 (gal/min)/ft, with a median of 1.14 (gal/min)/ft and a large range in values at most depths.
Differences in water quality of samples as indicated by field properties (pH, dissolved oxygen, and specific conductance) and concentrations of dissolved major ions, PFOA, and PFOS were apparent among isolated intervals in the boreholes. Summed concentrations of PFOA and PFOS ranged from about 11 to 10,780 nanograms per liter (ng/L) and were greater than the 2016 U.S. Environmental Protection Agency health advisory of 70 ng/L for summed PFOA and PFOS concentrations in 62 of 104 intervals and discrete depths tested. The mass ratio of PFOS to PFOA was generally higher than 1.0 in samples with summed PFOA and PFOS concentrations greater than 70 ng/L, with ratio values as high as 8.7. In many boreholes, summed concentrations of PFOA and PFOS were positively related to chloride concentrations, which were elevated above natural-background values [less than 10 milligrams per liter] in most samples and as high as 717 milligrams per liter. Sources of the elevated chloride other than, or in addition to, common rock salt (sodium chloride) were indicated by chloride to sodium molar ratios greater than 1.0. Water-quality data indicated that sampled water from some intervals with lower hydraulic heads may be affected by water from intervals with higher hydraulic heads because of vertical flow in open boreholes; samples from these intervals with lower hydraulic heads may not be fully representative due to some component of cross contamination and should be interpreted with caution.
Through a preliminary correlation of natural gamma and resistivity logs of boreholes drilled at and near the former NAWC Warminster, 11 lithologic units were identified and interpreted to strike northeast and dip to the northwest. Hydraulic heads were generally highest in isolated intervals that intercepted beds which, when projected up dip, crop out at the highest land-surface elevation on the former NAWC Warminster, indicating that the dipping-bed structure and topography are factors affecting the distribution of hydraulic head in the aquifer. The hydrogeologic framework in conjunction with the vertical distribution of hydraulic heads and water quality may assist in evaluating the locations of various PFAS sources and potential migration pathways of PFAS in groundwater at and near NAWC Warminster.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20241007","collaboration":"Prepared in cooperation with the U.S. Navy","usgsCitation":"Senior, L.A., and Fiore, A.R., 2024, Results of 2018–19 water-quality and hydraulic characterization of aquifer intervals using packer tests and preliminary geophysical-log correlations for selected boreholes at and near the former Naval Air Warfare Center Warminster, Bucks County, Pennsylvania (ver. 1.1, January 2025): U.S. Geological Survey Open-File Report 2024–1007, 136 p., https://doi.org/10.3133/ofr20241007.","productDescription":"Report: xv, 136 p.; 5 Plates; Data Release","numberOfPages":"136","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-138405","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":426405,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20241007/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2024-1007 HTML"},{"id":426406,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2024/1007/ofr20241007.XML","description":"OFR 2024-1007 XML"},{"id":426407,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2024/1007/images/"},{"id":426403,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2024/1007/coverthb2.jpg"},{"id":426404,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2024/1007/ofr20241007.pdf","text":"Report","size":"9.26 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2024-1007 PDF"},{"id":426408,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9TC92B5","text":"USGS data release","linkHelpText":"Water-level data and selected field notes for aquifer-interval-isolation tests at and near the former Naval Air Warfare Center Warminster, Bucks County, Pennsylvania, 2018–19 (ver. 2.0, January 2024)"},{"id":426409,"rank":7,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2024/1007/ofr20241007_plates.pdf","text":"Plates 1–5","size":"921 KB"},{"id":481558,"rank":8,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2024/1007/ofr20241007_versionHist.txt","size":"949 B","linkFileType":{"id":2,"text":"txt"}}],"country":"United States","state":"Pennsylvania","otherGeospatial":"Naval Air Warfare Center Warminster","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -75.21874919403015,\n 40.292862181975266\n ],\n [\n -75.21874919403015,\n 40.12697956762551\n ],\n [\n -74.97075997042653,\n 40.12697956762551\n ],\n [\n -74.97075997042653,\n 40.292862181975266\n ],\n [\n -75.21874919403015,\n 40.292862181975266\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Version 1.0: March 2024; Version 1.1 January 2025","contact":"Director, Pennsylvania Water Science Center
U.S. Geological Survey
215 Limekiln Road
New Cumberland, PA 17070
In support of a preliminary analysis performed by New York State Department of Environmental Conservation that found elevated nutrient levels along selected reaches of the Mohawk River, a one-dimensional, unsteady hydraulic and water-quality model (Hydrologic Engineering Center River Analysis System Nutrient Simulation Module 1 [HEC–RAS NSM I]) was developed by the U.S. Geological Survey for the 127-mile reach of the Mohawk River between Rome and Cohoes, New York. The model was designed to accurately simulate within-channel flow conditions for this highly regulated, control-structure dense river reach. The model was calibrated for the period of May through September 2016 using available streamflow, temperature, and water-quality data. Nitrogen, phosphorus, dissolved oxygen, and water column algae were balanced within the model; however, the nutrient model calibration was focused on phosphorus.
The HEC–RAS hydraulic model simulated streamflow adequately at the calibration locations with observed and simulated daily flows demonstrating coefficient of determination (r2) values ranging from 0.91 to 0.97, mean absolute error ranging from 15–20 percent, and bias ranging from −7 to 16 percent. The water temperature model within HEC–RAS NSM I demonstrated remarkable ability to simulate water temperature: typical water temperature errors were less than 1.0 degree Celsius (°C). Simulated water temperature results closely tracked observed continuous water temperature data at three locations on the Mohawk River, with mean absolute error for the 2016 study period ranging from 0.87 to 0.90 °C, and a root mean square error of 1.00 to 1.07 °C.
Performance criteria for the water-quality (nutrient) model were applied differently than the water temperature model because of the temporally coarse discrete samples collected for the project. The average difference between final simulated concentrations and observed concentrations of organic phosphorus for all sample locations was within 0.01 milligrams per liter (mg/L) and within 0.09 mg/L for orthophosphate using all locations except Rome, which was within 0.25 mg/L.
The calibrated model was used to implement nine phosphorus reduction scenarios by applying reductions to wastewater treatment plant effluent concentrations within the model. Monthly mean differences were computed for five comparison locations. Scenario results were generally linear and predictable; scenarios implementing the highest reductions showed correspondingly larger differences in Mohawk River concentrations downstream from the wastewater treatment plants associated with those reductions. The largest monthly mean differences were realized from reduction scenario nine and ranged from −0.018 to −0.076 mg/L for organic phosphorus and from 0.001 to −0.138 mg/L for orthophosphate.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245005","collaboration":"Prepared in cooperation with New York State Department of Environmental Conservation","usgsCitation":"Suro, T.P., Niemoczynski, M.J., and Boetsma, A., 2024, Development and calibration of HEC–RAS hydraulic, temperature, and nutrient models for the Mohawk River, New York: U.S. Geological Survey Scientific Investigations Report 2024–5005, 90 p., https://doi.org/10.3133/sir20245005","productDescription":"Report: xii, 90 p.; Data Release","numberOfPages":"90","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-127136","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":425874,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FRAYLT","text":"USGS data release","linkHelpText":"HEC–RAS hydraulic, temperature, and nutrient models for the Mohawk River between Rome and Cohoes, New York"},{"id":425872,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2024/5005/images/"},{"id":425873,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2024/5005/sir20245005.XML"},{"id":425869,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5005/coverthb.jpg"},{"id":425870,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5005/sir20245005.pdf","text":"Report","size":"20.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2024-5005"},{"id":425871,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20245005/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2024-5005"},{"id":499420,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_116141.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"New York","otherGeospatial":"Mohawk River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -75.4,\n 42.0\n ],\n [\n -73.2,\n 42.0\n ],\n [\n -73.2,\n 43.4\n ],\n [\n -75.4,\n 43.4\n ],\n [\n -75.4,\n 42.0\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, New Jersey Water Science Center
U.S. Geological Survey
3450 Princeton Pike
Lawrenceville, NJ 08648
Living shorelines with salt marsh species, rock breakwaters, and sand nourishment were built along the coastal areas in the Glenn Martin National Wildlife Refuge, Maryland, in 2016 in response to Hurricane Sandy (2012). The Fog Point living shoreline at Glenn Martin National Wildlife Refuge was designed with the “headland - breakwater - embayment” pattern. Scientists from the U.S. Geological Survey, Northeastern University, U.S. Fish and Wildlife Service, and Louisiana State University studied wave, current, and sediment dynamics to assess the effectiveness of the Fog Point living shoreline structures in terms of wave attenuation and erosion reduction. Wave gages, current meters, sediment traps, sediment tiles, and lateral erosion pins were deployed along the Fog Point shoreline during February 10–14, 2020. Because of COVID-19 pandemic travel restrictions, sensors were not retrieved until August 25, 2021, which was 18 months after field deployment, resulting in tremendous loss or damage of sensors and sediment measurements.
Monitoring data indicated that wave heights were substantially reduced at locations behind the breakwater (headland) compared to the wave heights in the offshore location, but not at the location in the control area (the embayment). Current patterns and current velocities at the location behind the breakwater were complex and changed dramatically compared to the current patterns and current velocities offshore. Sediments were blocked by the breakwater most of the time except during periods of storms with wave heights larger than 0.9 meter, when waves overtopped the breakwater and brought sediments to the tidal flat and salt marshes behind the breakwater. Behind the breakwater, both sediment deposition and erosion were observed during the 18 months of monitoring. Continued low elevation marsh edge erosion from wave undercutting along the embayment was observed, especially at the existing wave-cut gullies.
Monitoring results indicate that the “breakwater + marsh planting” structure along the Fog Point shoreline has limited shoreline protection capacity. Marsh edge erosion behind the breakwater was likely caused by the limited sediment supply from marine sources for transport and delivery, as well as the effects of circulation and current velocity on the settling and deposition of suspended sediments from eroded marshes. Marsh edge erosion continued in the embayment or control area where no shoreline restoration structures were implemented. Long-term (decadal scale) monitoring and adaptive management of living shoreline structures could help to assess the effectiveness of wave attenuation for reducing shoreline erosion and enhancing vegetation growth for trapping sediments and the effectiveness of marsh surface elevation growth for keeping pace with sea level rise.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20241004","issn":"2331-1258","collaboration":"Prepared in collaboration with Northeastern University, U.S. Fish and Wildlife Service, and Louisiana State University","usgsCitation":"Wang, H., Chen, Q., Capurso, W.D., Niemoczynski, L.M., Wang, N., Zhu, L., Snedden, G.A., Whitbeck, M., Wilson, C.A., and Brownley, M., 2024, Monitoring of wave, current, and sediment dynamics along the Fog Point Living Shoreline, Glenn Martin National Wildlife Refuge, Maryland: U.S. Geological Survey Open-File Report 2024–1004, 32 p., https://doi.org/10.3133/ofr20241004.","productDescription":"Report: x, 32 p.; Data Release","numberOfPages":"46","onlineOnly":"Y","ipdsId":"IP-153204","costCenters":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true},{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":499204,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_116048.htm","linkFileType":{"id":5,"text":"html"}},{"id":425618,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9TXZX5W","text":"USGS data release","linkHelpText":"Field observation of wind waves and current velocity (2020) along the Fog Point Living Shoreline, Maryland"},{"id":425617,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2024/1004/ofr20241004.XML","linkFileType":{"id":8,"text":"xml"},"description":"OFR 2024-1004 XML"},{"id":425616,"rank":4,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20241004/full","linkFileType":{"id":5,"text":"html"},"description":"OFR 2024-1004 HTML"},{"id":425615,"rank":2,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2024/1004/images"},{"id":425614,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2024/1004/ofr20241004.pdf","size":"5.01 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2024-1004"},{"id":425613,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2024/1004/coverthb.jpg"}],"country":"United States","state":"Maryland","otherGeospatial":"Glenn Martin National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -76.16645677294429,\n 38.13763711090462\n ],\n [\n -76.16645677294429,\n 37.8778983810208\n ],\n [\n -75.85669162075443,\n 37.8778983810208\n ],\n [\n -75.85669162075443,\n 38.13763711090462\n ],\n [\n -76.16645677294429,\n 38.13763711090462\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Wetland and Aquatic Research Center
U.S. Geological Survey
700 Cajundome Blvd.
Lafayette, LA 70506–3152
Large variations in redox-related water parameters, like pH and dissolved oxygen (DO), have been documented in New Hampshire (United States) drinking-water wells over the course of a few hours under pumping conditions. These findings suggest that comparable sub-daily variability in dissolved concentrations of redox-reactive and toxic arsenic (As) also may occur, representing a potentially critical public-health data gap and a fundamental challenge for long-term As-trends monitoring. To test this hypothesis, discrete groundwater As samples were collected approximately hourly during one day in May and again in August 2019 from three New Hampshire drinking-water wells (2 public-supply, 1 private) under active pumping conditions. Collected samples were assessed by laboratory analysis (total As [AsTot], As(III), As(V)) and by field analysis (AsTot) using a novel integrated biosensor system. Laboratory analysis revealed sub-daily variability (range) in AsTot concentrations equivalent to 16 % – 36 % of that observed in the antecedent 3-year bimonthly trend monitoring. Thus, the results indicated that, along with previously demonstrated seasonality effects, the timing and duration of pumping are important considerations when assessing trends in drinking-water As exposures and concomitant risks. Results also illustrated the utility of the field sensor for monitoring and management of AsTot exposures in near-real-time.
In response to previous reports of per- and polyfluoroalkyl substances (PFAS) contamination in French Island’s (located in the Mississippi River within the town of Campbell, Wisconsin) primary source of drinking water, 11 locations were sampled by the U.S. Geological Survey (USGS) in October 2021 to assess the potential presence of contaminant mixtures, including PFAS, in tapwater. Three locations were assessed seven times each over the course of three days. These samples were chosen to evaluate the water quality of the deeper Mount Simon bedrock aquifer and the water quality of the shallower sand and gravel (alluvial) aquifer at two locations. The other eight sample locations were spatially distributed within Campbell and were sampled once each. For each of these 11 sites, tapwater samples were analyzed for disinfection byproducts (DBP), pesticides, PFAS, pharmaceuticals, semi-volatile organic compounds (SVOC), volatile organic compounds (VOC), cations, anions, trace elements, alkalinity, microbial indicators, as well as measurements of water temperature, specific conductance, and pH. Of the 506 organic compounds analyzed in each water-quality sample, 74 (14 percent) were detected at least one time in any of the samples collected. Of the 14 percent, detected analytes included 27 pesticides (5 percent), 14 PFAS (3 percent), 6 pharmaceuticals (1 percent), 7 SVOC (1 percent), and 20 VOC (4 percent). No DBP were detected. The total number of organic compounds detected per sample ranged from 0–20 (median of 10), with the sum of concentrations ranging from not detected (nd)–2.53 micrograms per liter (μg/L; median of 0.333 μg/L). Of the inorganic constituents measured, eight were not detected above their reporting limit in any of the samples. The inorganic constituents that were not detected were antimony, arsenic, beryllium, cadmium, cobalt, molybdenum, selenium, and vanadium.
Along with the 11 sites sampled throughout Campbell, Wisconsin, beginning in October 2021, four more wells were sampled on the Upper Midwest Environmental Sciences Center (UMESC) campus for PFAS. Three of these sites withdraw water from the shallow alluvial aquifer (the same source water for tapwater site 002) and one from the Mount Simon aquifer (the same source of water for tapwater site 001). This sampling is ongoing with results from samples through December 2022 summarized in this report. Of the 33 PFAS analyzed in samples from the four UMESC locations, 15 individual PFAS were detected at least one time in any of the samples analyzed with the sum of PFAS concentrations ranging from nd–1.49 μg/L (median of 0.309 μg/L).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231088","collaboration":"Prepared in cooperation with the Town of Campbell, Wisconsin","programNote":"Environmental Health Program","usgsCitation":"Romanok, K.M., Meppelink, S.M., Bradley, P.M., Breitmeyer, S.E., Donahue, L., Gaikowski, M.P., Hines, R.K., and Smalling, K.L., 2023, Occurrence of mixed organic and inorganic chemicals in groundwater and tapwater, town of Campbell, Wisconsin, 2021–22: U.S. Geological Survey Open-File Report 2023–1088, 29 p., https://doi.org/10.3133/ofr20231088.","productDescription":"Report: viii, 29 p.; 2 Data Releases","numberOfPages":"29","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-150739","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":499196,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115939.htm","linkFileType":{"id":5,"text":"html"}},{"id":423893,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9J6XKVS","text":"USGS data release","linkHelpText":"Quarterly sample results for perand polyfluoroalkyl substances (PFAS) for locations in Campbell, Wisconsin, 2021–22"},{"id":423892,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9EUBGUF","text":"USGS data release","linkHelpText":"Target-chemical concentrations for assessment of mixed-organic/inorganic chemical and biological exposures in private-well tapwater at Campbell, Wisconsin, 2021"},{"id":423887,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1088/coverthb.jpg"},{"id":423888,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1088/ofr20231088.pdf","text":"Report","size":"1.62 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1088"},{"id":423889,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231088/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2023-1088"},{"id":423890,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1088/ofr20231088.XML"},{"id":423891,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1088/images/"}],"country":"United States","state":"Wisconsin","county":"La Crosse County","city":"Campbell","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -91.29371444024203,\n 43.904997377408506\n ],\n [\n -91.29371444024203,\n 43.84807720086516\n ],\n [\n -91.23878279961701,\n 43.84807720086516\n ],\n [\n -91.23878279961701,\n 43.904997377408506\n ],\n [\n -91.29371444024203,\n 43.904997377408506\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, New Jersey Water Science Center
3450 Princeton Pike, Suite 110
Lawrenceville, New Jersey 08648
Infectious diseases are a major driver of the global amphibian decline. In addition, many factors, including genetics, stress, pollution, and climate change can influence the response to pathogens. Therefore, it is important to be able to evaluate amphibian immunity in the laboratory and in the field. The phytohemagglutinin (PHA) assay is an inexpensive and relatively non-invasive tool that has been used extensively to assess immunocompetence, especially in birds, and more recently in amphibians. However, there is substantial variation in experimental methodology among amphibian PHA studies in terms of species and life stages, PHA doses and injection sites, and use of experimental controls. Here, we compile and compare all known PHA studies in amphibians to identify knowledge gaps and develop best practices for future work. We found that research has only been conducted on a limited number of species, which may not reflect the diversity of amphibians. There is also a lack of validation studies in most species, so that doses and timing of PHA injection and subsequent swelling measurements may not effectively evaluate immunocompetence. Based on these and other findings, we put forward a set of recommendations to make future PHA studies more consistent and improve the ability to utilize this assay in wild populations, where immune surveillance is greatly needed.
","language":"English","publisher":"Oxford Academic Press","doi":"10.1093/conphys/coad090","usgsCitation":"Hawley, L., Smalling, K., and Glaberman, S., 2023, Critical review of the phytohemagglutinin assay for assessing amphibian immunity: Conservation Physiology, v. 11, no. 1, coad090, 23 p., https://doi.org/10.1093/conphys/coad090.","productDescription":"coad090, 23 p.","ipdsId":"IP-150838","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":441422,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/conphys/coad090","text":"Publisher Index Page"},{"id":423506,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","issue":"1","noUsgsAuthors":false,"publicationDate":"2023-12-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Hawley, Lauren","contributorId":332337,"corporation":false,"usgs":false,"family":"Hawley","given":"Lauren","email":"","affiliations":[{"id":12909,"text":"George Mason University","active":true,"usgs":false}],"preferred":false,"id":890070,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smalling, Kelly L. 0000-0002-1214-4920","orcid":"https://orcid.org/0000-0002-1214-4920","contributorId":214623,"corporation":false,"usgs":true,"family":"Smalling","given":"Kelly L.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":890071,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Glaberman, Scott 0000-0003-0594-4732","orcid":"https://orcid.org/0000-0003-0594-4732","contributorId":266060,"corporation":false,"usgs":false,"family":"Glaberman","given":"Scott","email":"","affiliations":[{"id":12909,"text":"George Mason University","active":true,"usgs":false}],"preferred":false,"id":890072,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70250853,"text":"70250853 - 2023 - Conserved grasslands support similar pollinator diversity as pollinator-specific practice regardless of proximal cropland and pesticide exposure","interactions":[],"lastModifiedDate":"2024-01-10T15:20:56.832051","indexId":"70250853","displayToPublicDate":"2023-11-22T09:12:27","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3908,"text":"Royal Society Open Science","active":true,"publicationSubtype":{"id":10}},"title":"Conserved grasslands support similar pollinator diversity as pollinator-specific practice regardless of proximal cropland and pesticide exposure","docAbstract":"Pollinator diversity and abundance are declining globally. Cropland agriculture and the corresponding use of agricultural pesticides may contribute to these declines, while increased pollinator habitat (flowering plants) can help mitigate them. Here we tested whether the relative effect of wildflower plantings on pollinator diversity and counts were modified by proportion of nearby agricultural land cover and pesticide exposure in 24 conserved grasslands in Iowa, USA. Compared with general grassland conservation practices, wildflower plantings led to only a 5% increase in pollinator diversity and no change in counts regardless of the proportion of cropland agriculture within a 1 km radius. Pollinator diversity increased earlier in the growing season and with per cent flower cover. Unexpectedly, neither insecticide nor total pesticide concentrations on above-ground passive samplers were related to pollinator diversity. However, pollinator community composition was most strongly related to date of sampling, total pesticide concentration, and forb or flower cover. Our results indicate very little difference in pollinator diversity between grassland conservation practices with and without wildflower plantings. Given the relatively high economic costs of wildflower plantings, our research provides initial evidence that investment in general grassland conservation may efficiently conserve pollinator diversity in temperate regions of intensive cropland agriculture.
","language":"English","publisher":"The Royal Society Publishing","doi":"10.1098/rsos.231093","usgsCitation":"Kraus, J.M., Smalling, K., Vandever, M.W., Givens, C.E., Smith, C., Kolpin, D., and Hladik, M.L., 2023, Conserved grasslands support similar pollinator diversity as pollinator-specific practice regardless of proximal cropland and pesticide exposure: Royal Society Open Science, v. 10, no. 11, https://doi.org/10.1098/rsos.231093.","productDescription":"231093, 12 p.","startPage":"231093","ipdsId":"IP-157224","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":441567,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1098/rsos.231093","text":"Publisher Index Page"},{"id":435116,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9Q0NAF8","text":"USGS data release","linkHelpText":"Plant and insect pollinator diversity data from Conservation Reserve Program fields across an agricultural gradient in eastern Iowa"},{"id":424274,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Iowa","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -94.06613018879129,\n 43.47459165083325\n ],\n [\n -94.06613018879129,\n 40.39777384484779\n ],\n [\n -90.07425648496523,\n 40.39777384484779\n ],\n [\n -90.07425648496523,\n 43.47459165083325\n ],\n [\n -94.06613018879129,\n 43.47459165083325\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"10","issue":"11","noUsgsAuthors":false,"publicationDate":"2023-11-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Kraus, Johanna M. 0000-0002-9513-4129 jkraus@usgs.gov","orcid":"https://orcid.org/0000-0002-9513-4129","contributorId":4834,"corporation":false,"usgs":true,"family":"Kraus","given":"Johanna","email":"jkraus@usgs.gov","middleInitial":"M.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":891794,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smalling, Kelly L. 0000-0002-1214-4920","orcid":"https://orcid.org/0000-0002-1214-4920","contributorId":221234,"corporation":false,"usgs":true,"family":"Smalling","given":"Kelly","middleInitial":"L.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":891795,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vandever, Mark W. 0000-0003-0247-2629 vandeverm@usgs.gov","orcid":"https://orcid.org/0000-0003-0247-2629","contributorId":197674,"corporation":false,"usgs":true,"family":"Vandever","given":"Mark","email":"vandeverm@usgs.gov","middleInitial":"W.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":891796,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Givens, Carrie E. 0000-0003-2543-9610","orcid":"https://orcid.org/0000-0003-2543-9610","contributorId":247691,"corporation":false,"usgs":true,"family":"Givens","given":"Carrie","middleInitial":"E.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":891797,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Smith, Cassandra 0000-0003-1088-1772 cassandrasmith@usgs.gov","orcid":"https://orcid.org/0000-0003-1088-1772","contributorId":193491,"corporation":false,"usgs":true,"family":"Smith","given":"Cassandra","email":"cassandrasmith@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":891798,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kolpin, Dana W. 0000-0002-3529-6505","orcid":"https://orcid.org/0000-0002-3529-6505","contributorId":204154,"corporation":false,"usgs":true,"family":"Kolpin","given":"Dana W.","affiliations":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true}],"preferred":true,"id":891799,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hladik, Michelle L. 0000-0002-0891-2712","orcid":"https://orcid.org/0000-0002-0891-2712","contributorId":221087,"corporation":false,"usgs":true,"family":"Hladik","given":"Michelle","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":891800,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70250099,"text":"sir20235066 - 2023 - Updates to the regional groundwater-flow model of the New Jersey Coastal Plain, 1980–2013","interactions":[],"lastModifiedDate":"2026-03-09T16:53:50.063749","indexId":"sir20235066","displayToPublicDate":"2023-11-17T13:55:00","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-5066","displayTitle":"Updates to the Regional Groundwater-Flow Model of the New Jersey Coastal Plain, 1980–2013","title":"Updates to the regional groundwater-flow model of the New Jersey Coastal Plain, 1980–2013","docAbstract":"A 21-layer three-dimensional transient groundwater-flow model of the New Jersey Coastal Plain was developed and calibrated by the U.S. Geological Survey (USGS) in cooperation with the New Jersey Department of Environmental Protection to simulate groundwater-flow conditions during 1980–2013, incorporating average annual groundwater withdrawals and average annual groundwater recharge. This model is the third version of the New Jersey Coastal Plain regional groundwater-flow model that was initially developed as part of the USGS Regional Aquifer System Analysis (RASA) program. The model simulates groundwater flow in 11 aquifers and 10 intervening confining units of the New Jersey Coastal Plain to provide a regional overview of groundwater conditions. Averaged groundwater withdrawal data for 1980 to 2013 were used in the model. The 11 aquifers in New Jersey are, from shallowest to deepest, the Holly Beach water-bearing zone and the confined Cohansey aquifer in Cape May County; the Rio Grande water-bearing zone; the Atlantic City 800-foot sand; the Piney Point, Vincentown, and Wenonah-Mount Laurel aquifers; the Englishtown aquifer system; and the upper, middle, and lower aquifers of the Potomac-Raritan-Magothy (PRM) aquifer system.
The model was developed with the MODFLOW–2005 numerical code and the UCODE parameter estimation technique and calibrated using water-level and base-flow observations. A total of 3,453 water-level observations from 392 wells in New Jersey and 48 wells in Delaware from 1983 to 2013 were used in model calibration, which includes historical water-level trends for 29 wells in New Jersey during 1980–2013 presented in time-series hydrographs. In addition, derived observations also were included by calculating the vertical gradient at 33 pairs of nested observation wells in New Jersey, for a total of 210 observations. Changes in water levels over time were calculated for 134 wells in New Jersey and four wells in Delaware where water levels had varied substantially (approximately 10 ft) over the 30-year span of synoptic water-level measurements, for a total of 767 observations. A total of 1,485 base-flow observations in 47 surface-water basins in New Jersey from 1980 to 2013 were used in model calibration.
Updates to the groundwater-flow model include the conversion to a fully three-dimensional model from the previous quasi-three-dimensional model. The new model will allow for potential future uses such as particle tracking or simulation of variable-density groundwater flow that could not be accomplished with earlier versions of the model. Spatially and temporally variable recharge estimated by using a soil-water balance model resulted in a spatially and temporally finer discretization. The Rio Grande water-bearing zone was added to the model as an aquifer layer to refine estimates of simulated flow in Atlantic and Cape May Counties, New Jersey. Hydrogeologic parameters were updated to include the confining units in New Jersey and corresponding hydrogeologic units in Delaware and eastern Maryland.
The simulated water levels for the New Jersey Coastal Plain aquifers were compared to water-level measurements made during 1980–2013. The average residual for 4,243 water-level observations for New Jersey (simulated water levels minus measured water levels) is 1.5 feet. The simulated water-level contours for the confined aquifers for 2013 were compared to potentiometric surfaces produced from water levels measured during 2013. Simulated water levels generally matched the 2013 potentiometric surfaces of the confined aquifers in the areas of large withdrawals. Hydrographs of wells in the confined Coastal Plain aquifers of New Jersey show that simulated water levels generally match the magnitude and seasonal variation of the observed water levels. Hydrographs of base flow for the 47 streamgaging stations in New Jersey indicate that most of the simulated and estimated data match reasonably well.
Groundwater withdrawals are an important resource for water supply, agricultural, industrial, and commercial needs in the New Jersey Coastal Plain. Groundwater withdrawals from the New Jersey Coastal Plain aquifers have resulted in persistent, regionally extensive cones of depression in the Englishtown aquifer system and Wenonah-Mount Laurel aquifer in Ocean and Monmouth Counties; Wenonah-Mount Laurel and upper, middle, and lower PRM aquifers in Camden County; and Atlantic City 800-foot sand in Atlantic County. Because hydrologic stresses and water-management needs change with time, periodic updates to the groundwater-flow model are required to provide current information about hydrologic conditions in the New Jersey Coastal Plain and to maintain its usefulness as a tool to manage water resources and develop water-resource strategies. The current updates will support the continued application of this model as a tool for evaluating the regional effects of changes in groundwater withdrawals and of current and potential future water-management strategies on groundwater levels in the New Jersey Coastal Plain.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235066","collaboration":"Prepared in cooperation with the New Jersey Department of Environmental Protection","usgsCitation":"Gordon, A.D., and Carleton, G.B., 2023, Updates to the regional groundwater-flow model of the New Jersey Coastal Plain, 1980–2013: U.S. Geological Survey Scientific Investigations Report 2023–5066, 116 p., https://doi.org/10.3133/sir20235066","productDescription":"Report: xii, 116 p.; Data Release","numberOfPages":"116","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-127396","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":500947,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115639.htm","linkFileType":{"id":5,"text":"html"}},{"id":422695,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5066/images/"},{"id":422693,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235066/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2023-5066"},{"id":422696,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9W6RXFC","text":"USGS data release","linkHelpText":"MODFLOW-2005 model used to simulate the regional groundwater flow system in the updated New Jersey Coastal Plain model, 1980-2013"},{"id":422694,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5066/sir20235066.XML"},{"id":422692,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5066/sir20235066.pdf","text":"Report","size":"25.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5066"},{"id":422691,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5066/coverthb.jpg"}],"country":"United States","otherGeospatial":"New Jersey Coastal Plain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -74.49018324613056,\n 41.03712838002892\n ],\n [\n -75.25922621488034,\n 41.417217443631785\n ],\n [\n -77.41254652738019,\n 39.17183412365296\n ],\n [\n -75.22626723050551,\n 37.8132834585617\n ],\n [\n -72.98505629300531,\n 40.4043207917766\n ],\n [\n -74.49018324613056,\n 41.03712838002892\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, New Jersey Water Science Center
3450 Princeton Pike, Suite 110
Lawrenceville, New Jersey 08648
Mercury (Hg) is a toxic contaminant that has been mobilized and distributed worldwide and is a threat to many wildlife species. Amphibians are facing unprecedented global declines due to many threats including contaminants. While the biphasic life history of many amphibians creates a potential nexus for methylmercury (MeHg) exposure in aquatic habitats and subsequent health effects, the broad-scale distribution of MeHg exposure in amphibians remains unknown. We used nonlethal sampling to assess MeHg bioaccumulation in 3,241 juvenile and adult amphibians during 2017–2021. We sampled 26 populations (14 species) across 11 states in the United States, including several imperiled species that could not have been sampled by traditional lethal methods. We examined whether life history traits of species and whether the concentration of total mercury in sediment or dragonflies could be used as indicators of MeHg bioaccumulation in amphibians. Methylmercury contamination was widespread, with a 33-fold difference in concentrations across sites. Variation among years and clustered subsites was less than variation across sites. Life history characteristics such as size, sex, and whether the amphibian was a frog, toad, newt, or other salamander were the factors most strongly associated with bioaccumulation. Total Hg in dragonflies was a reliable indicator of bioaccumulation of MeHg in amphibians (R2 ≥ 0.67), whereas total Hg in sediment was not (R2 ≤ 0.04). Our study, the largest broad-scale assessment of MeHg bioaccumulation in amphibians, highlights methodological advances that allow for nonlethal sampling of rare species and reveals immense variation among species, life histories, and sites. Our findings can help identify sensitive populations and provide environmentally relevant concentrations for future studies to better quantify the potential threats of MeHg to amphibians.
","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.3c05549","usgsCitation":"Tornabene, B.J., Hossack, B., Halstead, B., Eagles-Smith, C., Adams, M.J., Backlin, A.R., Brand, A., Emery, C., Fisher, R., Fleming, J.E., Glorioso, B., Grear, D.A., Campbell Grant, E.H., Kleeman, P.M., Miller, D., Muths, E., Pearl, C., Rowe, J., Rumrill, C.T., Waddle, J.H., Winzeler, M., and Smalling, K., 2023, Broad-scale assessment of methylmercury in adult amphibians: Environmental Science and Technology, v. 57, no. 45, p. 17511-17521, https://doi.org/10.1021/acs.est.3c05549.","productDescription":"11 p.","startPage":"17511","endPage":"17521","ipdsId":"IP-151126","costCenters":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true},{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":441743,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1021/acs.est.3c05549","text":"Publisher Index Page"},{"id":422428,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"57","issue":"45","noUsgsAuthors":false,"publicationDate":"2023-10-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Tornabene, Brian J. 0000-0002-2348-3119","orcid":"https://orcid.org/0000-0002-2348-3119","contributorId":303977,"corporation":false,"usgs":true,"family":"Tornabene","given":"Brian","email":"","middleInitial":"J.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":887130,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hossack, Blake R. 0000-0001-7456-9564","orcid":"https://orcid.org/0000-0001-7456-9564","contributorId":229347,"corporation":false,"usgs":true,"family":"Hossack","given":"Blake R.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":887131,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Halstead, Brian J. 0000-0002-5535-6528 bhalstead@usgs.gov","orcid":"https://orcid.org/0000-0002-5535-6528","contributorId":3051,"corporation":false,"usgs":true,"family":"Halstead","given":"Brian J.","email":"bhalstead@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":887132,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Eagles-Smith, Collin A. 0000-0003-1329-5285","orcid":"https://orcid.org/0000-0003-1329-5285","contributorId":221745,"corporation":false,"usgs":true,"family":"Eagles-Smith","given":"Collin A.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":887133,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Adams, Michael J. 0000-0001-8844-042X","orcid":"https://orcid.org/0000-0001-8844-042X","contributorId":211916,"corporation":false,"usgs":true,"family":"Adams","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":887134,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Backlin, Adam R. 0000-0001-5618-8426 abacklin@usgs.gov","orcid":"https://orcid.org/0000-0001-5618-8426","contributorId":3802,"corporation":false,"usgs":true,"family":"Backlin","given":"Adam","email":"abacklin@usgs.gov","middleInitial":"R.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":887135,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Brand, Adrianne 0000-0003-2664-0041","orcid":"https://orcid.org/0000-0003-2664-0041","contributorId":304281,"corporation":false,"usgs":true,"family":"Brand","given":"Adrianne","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":887136,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Emery, Colleen 0000-0002-1208-3224","orcid":"https://orcid.org/0000-0002-1208-3224","contributorId":215534,"corporation":false,"usgs":true,"family":"Emery","given":"Colleen","email":"","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":887137,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Fisher, Robert N. 0000-0002-2956-3240","orcid":"https://orcid.org/0000-0002-2956-3240","contributorId":51675,"corporation":false,"usgs":true,"family":"Fisher","given":"Robert N.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":887138,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Fleming, Jillian Elizabeth 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Hardin 0000-0003-1940-2133 waddleh@usgs.gov","orcid":"https://orcid.org/0000-0003-1940-2133","contributorId":138953,"corporation":false,"usgs":true,"family":"Waddle","given":"J.","email":"waddleh@usgs.gov","middleInitial":"Hardin","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":887149,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Winzeler, Megan 0000-0002-0361-1582 mwinzeler@usgs.gov","orcid":"https://orcid.org/0000-0002-0361-1582","contributorId":196714,"corporation":false,"usgs":true,"family":"Winzeler","given":"Megan","email":"mwinzeler@usgs.gov","affiliations":[],"preferred":true,"id":887150,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Smalling, Kelly L. 0000-0002-1214-4920","orcid":"https://orcid.org/0000-0002-1214-4920","contributorId":214623,"corporation":false,"usgs":true,"family":"Smalling","given":"Kelly L.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":887151,"contributorType":{"id":1,"text":"Authors"},"rank":22}]}} ,{"id":70261282,"text":"70261282 - 2023 - Quantifying salinity in the layered coastal aquifers underlying and adjacent to Delaware Bay USA using AEM-derived resistivity","interactions":[],"lastModifiedDate":"2026-04-23T15:46:29.198886","indexId":"70261282","displayToPublicDate":"2023-10-30T10:39:27","publicationYear":"2023","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Quantifying salinity in the layered coastal aquifers underlying and adjacent to Delaware Bay USA using AEM-derived resistivity","docAbstract":"Airborne electromagnetic (AEM) methods are particularly well suited to coastal aquifer salinity studies, yet the quantitative translation from bulk resistivity to fluid salinity carries uncertainty that can impact mapped salinity distributions and interpretations of the freshwater-saline interface and hydrostratigraphic layers. A recent AEM survey of the region near the Delaware Bay, USA highlights several challenges common to coastal hydrogeologic settings that may influence both qualitative and quantitative interpretation. We use a Bayesian inversion to estimate geophysical parameter uncertainty, and results are integrated with hydrogeologic measurements to develop quantitative interpretations of salinity across the freshwater-saline interface in stacked aquifers.
","conferenceTitle":"8th International Airborne Electromagnetics Workshop (AEM2023)","conferenceDate":"September 4-7, 2023","conferenceLocation":"Fitzroy Island, Australia","language":"English","publisher":"Australian Society of Exploration Geophysicists","doi":"10.5281/zenodo.10052454","usgsCitation":"Ball, L.B., Minsley, B.J., Wilson, G., Michael, H.A., Burns, D.A., Nardi, M.R., and Charles, E.G., 2023, Quantifying salinity in the layered coastal aquifers underlying and adjacent to Delaware Bay USA using AEM-derived resistivity, 8th International Airborne Electromagnetics Workshop (AEM2023), v. 2, Fitzroy Island, Australia, September 4-7, 2023, 4 p., https://doi.org/10.5281/zenodo.10052454.","productDescription":"4 p.","ipdsId":"IP-151783","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true},{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":503356,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Delaware, New Jersey","otherGeospatial":"Delaware Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.67992866783241,\n 39.73205086283977\n ],\n [\n -74.74344283080298,\n 39.73205086283977\n ],\n [\n -74.74344283080298,\n 38.77272026027043\n ],\n [\n -75.67992866783241,\n 38.77272026027043\n ],\n [\n -75.67992866783241,\n 39.73205086283977\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"2","noUsgsAuthors":false,"publicationDate":"2023-10-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Ball, Lyndsay B. 0000-0002-6356-4693 lbball@usgs.gov","orcid":"https://orcid.org/0000-0002-6356-4693","contributorId":1138,"corporation":false,"usgs":true,"family":"Ball","given":"Lyndsay","email":"lbball@usgs.gov","middleInitial":"B.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":920208,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Minsley, Burke J. 0000-0003-1689-1306 bminsley@usgs.gov","orcid":"https://orcid.org/0000-0003-1689-1306","contributorId":697,"corporation":false,"usgs":true,"family":"Minsley","given":"Burke","email":"bminsley@usgs.gov","middleInitial":"J.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":920209,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wilson, Gavin Scott 0000-0002-4312-0374","orcid":"https://orcid.org/0000-0002-4312-0374","contributorId":333700,"corporation":false,"usgs":true,"family":"Wilson","given":"Gavin Scott","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":920210,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Michael, Holly A.","contributorId":190224,"corporation":false,"usgs":false,"family":"Michael","given":"Holly","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":920211,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Burns, Douglas A. 0000-0001-6516-2869 daburns@usgs.gov","orcid":"https://orcid.org/0000-0001-6516-2869","contributorId":1237,"corporation":false,"usgs":true,"family":"Burns","given":"Douglas","email":"daburns@usgs.gov","middleInitial":"A.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":920212,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nardi, Mark R. 0000-0002-7310-8050 mrnardi@usgs.gov","orcid":"https://orcid.org/0000-0002-7310-8050","contributorId":1859,"corporation":false,"usgs":true,"family":"Nardi","given":"Mark","email":"mrnardi@usgs.gov","middleInitial":"R.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":920213,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Charles, Emmanuel G. 0000-0002-3338-4958 echarles@usgs.gov","orcid":"https://orcid.org/0000-0002-3338-4958","contributorId":4280,"corporation":false,"usgs":true,"family":"Charles","given":"Emmanuel","email":"echarles@usgs.gov","middleInitial":"G.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":960204,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70246786,"text":"70246786 - 2023 - Modeling surface wave dynamics in upper Delaware Bay with living shorelines","interactions":[],"lastModifiedDate":"2023-07-19T13:25:40.835054","indexId":"70246786","displayToPublicDate":"2023-06-27T08:13:36","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2924,"text":"Ocean Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Modeling surface wave dynamics in upper Delaware Bay with living shorelines","docAbstract":"Living shorelines gain increasing attention because they stabilize shorelines and reduce erosion. This study leverages physics-based models and bagged regression tree (BRT) machine learning algorithm to simulate wave dynamics at a living shoreline composed of constructed oyster reefs (CORs) in upper Delaware Bay. The physics-based models consist of coupled Delft3D-FLOW and SWAN in four-level nested domains. The model accuracy converges with increasing mesh resolution. The simulated wave-induced current circulation substantiates the effectiveness of CORs in trapping sediments. The simulated yearly-averaged wave power correlates qualitatively with historical shoreline retreat rates. BRT is adopted to improve the model accuracy, identify key processes responsible for simulation errors in wave height (H8) and wave period (Tp), and quantify their importance. In the CORs sheltered area, BRT reveals that simulation errors of wind seas mainly arise from wind forcing, wave breaking and wave triad interactions. Wave breaking is seven times more important than wind forcing for simulating H8, while wind forcing and triad interactions are of equal importance for simulating Tp. Simulation errors of swells mostly stem from bottom friction and offshore wave boundary conditions. Results from this study can help the assessment and adaptive management of CORs-based living shoreline restoration projects under climate change.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.oceaneng.2023.115207","usgsCitation":"Zhu, L., Chen, Q., Wang, H., Wang, N., Hu, K., Capurso, W.D., Niemoczynski, L., and Snedden, G., 2023, Modeling surface wave dynamics in upper Delaware Bay with living shorelines: Ocean Engineering, v. 284, 115207, 17 p., https://doi.org/10.1016/j.oceaneng.2023.115207.","productDescription":"115207, 17 p.","ipdsId":"IP-146841","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":419147,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Jersey","otherGeospatial":"upper Delaware Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -75.244,\n 39.2775\n ],\n [\n -75.244,\n 39.2755\n ],\n [\n -75.241,\n 39.2755\n ],\n [\n -75.241,\n 39.2775\n ],\n [\n -75.244,\n 39.2775\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"284","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Zhu, Ling 0000-0003-0261-6848","orcid":"https://orcid.org/0000-0003-0261-6848","contributorId":222169,"corporation":false,"usgs":false,"family":"Zhu","given":"Ling","affiliations":[{"id":38331,"text":"Northeastern University","active":true,"usgs":false}],"preferred":false,"id":878283,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chen, Q. 0000-0002-6540-8758","orcid":"https://orcid.org/0000-0002-6540-8758","contributorId":56532,"corporation":false,"usgs":false,"family":"Chen","given":"Q.","affiliations":[{"id":38331,"text":"Northeastern University","active":true,"usgs":false}],"preferred":true,"id":878284,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wang, Hongqing 0000-0002-2977-7732","orcid":"https://orcid.org/0000-0002-2977-7732","contributorId":221902,"corporation":false,"usgs":true,"family":"Wang","given":"Hongqing","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":878285,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wang, Nan 0000-0001-7569-9598","orcid":"https://orcid.org/0000-0001-7569-9598","contributorId":291600,"corporation":false,"usgs":false,"family":"Wang","given":"Nan","email":"","affiliations":[{"id":38331,"text":"Northeastern University","active":true,"usgs":false}],"preferred":false,"id":878286,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hu, Kelin","contributorId":177218,"corporation":false,"usgs":false,"family":"Hu","given":"Kelin","email":"","affiliations":[],"preferred":false,"id":878287,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Capurso, William D. 0000-0003-1182-2846","orcid":"https://orcid.org/0000-0003-1182-2846","contributorId":218672,"corporation":false,"usgs":true,"family":"Capurso","given":"William","email":"","middleInitial":"D.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":878288,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Niemoczynski, Lukasz M. 0000-0003-2008-9148","orcid":"https://orcid.org/0000-0003-2008-9148","contributorId":222171,"corporation":false,"usgs":true,"family":"Niemoczynski","given":"Lukasz","middleInitial":"M.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":878289,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Snedden, Gregg 0000-0001-7821-3709","orcid":"https://orcid.org/0000-0001-7821-3709","contributorId":213411,"corporation":false,"usgs":true,"family":"Snedden","given":"Gregg","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":878290,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70245600,"text":"70245600 - 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Drinking-water exposures to per- and poly-fluoroalkyl substances (PFAS) are a national concern, however, there is limited information on PFAS in residential tapwater at the point-of-use, especially from private-wells. We conducted a national reconnaissance to compare human PFAS exposures in unregulated private-well and regulated public-supply tapwater. Tapwater from 716 locations (269 private-wells; 447 public supply) across the US was collected during 2016–2021 including three locations where temporal sampling was conducted. Concentrations of PFAS were assessed by three laboratories and compared with land-use and potential-source metrics to explore drivers of contamination. The number of individual PFAS observed ranged from 1 to 9 (median: 2) with corresponding cumulative concentrations (sum of detected PFAS) ranging from 0.348 to 346 ng/L. Seventeen PFAS were observed at least once with PFBS, PFHxS and PFOA observed most frequently in approximately 15% of the samples. Across the US, PFAS profiles and estimated median cumulative concentrations were similar among private wells and public-supply tapwater. We estimate that at least one PFAS could be detected in about 45% of US drinking-water samples. These detection probabilities varied spatially with limited temporal variation in concentrations/numbers of PFAS detected. Benchmark screening approaches indicated potential human exposure risk was dominated by PFOA and PFOS, when detected. Potential source and land-use information was related to cumulative PFAS concentrations, and the number of PFAS detected; however, corresponding relations with specific PFAS were limited likely due to low detection frequencies and higher detection limits. Information generated supports the need for further assessments of cumulative health risks of PFAS as a class and in combination with other co-occurring contaminants, particularly in unmonitored private-wells where information is limited or not available.
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Warfare Center, West Trenton, New Jersey, 2018","title":"Distribution of chlorinated volatile organic compounds and per- and polyfluoroalkyl substances in groundwater and surface water at the former Naval Air Warfare Center, West Trenton, New Jersey, 2018","docAbstract":"Groundwater wells and surface-water storm sewers contaminated with volatile organic compounds (VOCs) and per- and polyfluoroalkyl substances (PFASs) at the former Naval Air Warfare Center (NAWC) site in West Trenton, New Jersey were sampled in 2018 as part of the Navy’s long-term monitoring program. Trichloroethene (TCE), cis-1,2-dichloroethene (cisDCE), and vinyl chloride concentrations were plotted in map view and selected cross sections to elucidate the vertical and horizontal extent and distribution of contamination, along with a tabular comparison between 2018 and previous analytical results. The 2018 data showed that the areas of VOC contamination (>1 microgram per liter) decreased slightly on the north and east sides of the NAWC site from previous sampling dates; these decreases are attributed to the influence of the pump-and-treat system, natural attenuation processes, and various engineered bioaugmentation experiments that have occurred onsite. Off-site groundwater samples indicate the VOC contaminated groundwater is likely hydraulically constrained by the pump-and-treat system and appears to not be moving offsite to the south and west of NAWC. Only one offsite well, 50BR, located along the eastern margin of the site, was found to have detectable TCE and cisDCE concentrations, indicating that VOC contamination continues to migrate a short distance offsite to the east. Detectable VOC contamination was found in wells as deep as 200 and 221 feet on both the east and west sides of the NAWC site. Comparisons of present-day data to data from past sampling efforts indicate that TCE concentrations in most wells have decreased slowly over time.
Results from surface-water samples indicate that VOCs enter surface water predominantly through the West Ditch drainage system. Concentrations and fluxes of VOCs are higher when groundwater levels are higher, indicating contaminated groundwater discharges into the surface water system. Higher VOC concentrations at the Interceptor site relative to other sites in the West Ditch indicate the contamination in the West Ditch system is likely caused by contaminated groundwater discharging to the West Ditch storm sewer near manhole MH-140 when water table levels are high.
The pump-and-treat extraction wells at the former NAWC site were sampled for per- and polyfluoroalkyl substances (PFAS) in 2018. The suite of reported PFAS include perfluorooctane sulfonate (PFOS), perfluorooctanoic acid (PFOA), perfluorononanoic acid, and perfluorobutane sulfonate. Concentrations were plotted in map view to determine the areal extent of the PFAS contamination at the site. Extraction well 48BR sampled on the eastern half of the site was found to have PFOS and PFOA concentrations greater than the New Jersey Department of Environmental Protection Drinking Water maximum contaminant levels (MCLs), which is consistent with the distribution of highest PFAS concentrations in surface water in the OF-4 storm sewer system that drains that area, as well as previously collected PFAS concentrations in monitoring wells. On the western half of the site, the extraction well 08BR sample exceeded MCLs for PFOA and PFOS and the extraction well 22BR sample exceeded the MCL for PFOA, but samples from all other extraction wells were below the MCLs or other criteria for all PFAS analyzed. Concentrations of PFOA exceeded concentrations of PFOS on the west side of NAWC in both groundwater and surface water, which contrasts with the conditions on the east side of NAWC where PFOS concentrations exceeded PFOA concentrations. However, this observation was based on a limited number of samples on the west side of NAWC from 2018 and previous years, so more PFAS sampling is needed on the west side to assess this further.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231022","collaboration":"Prepared in cooperation with the U.S. Navy","usgsCitation":"Fiore, A.R., Imbrigiotta, T.E., and Wilson, T.P., 2023, Distribution of chlorinated volatile organic compounds and per- and polyfluoroalkyl substances in groundwater and surface water at the former Naval Air Warfare Center, West Trenton, New Jersey, 2018: U.S. Geological Survey Open-File Report 2023–1022, 81 p., https://doi.org/10.3133/ofr20231022.","productDescription":"Report: ix, 81 p.; Data Release","numberOfPages":"81","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-114249","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":417658,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9RCAQ5N","text":"USGS data release","linkHelpText":"Concentrations of chlorinated volatile organic compounds and per- and polyfluoroalkyl substances in groundwater and surface water, former Naval Air Warfare Center, West Trenton, New Jersey"},{"id":417657,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1022/images/"},{"id":417656,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1022/ofr20231022.XML"},{"id":417655,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/ofr20231022/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2023-1022"},{"id":417654,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1022/ofr20231022.pdf","text":"Report","size":"11.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1022"},{"id":417653,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1022/coverthb.jpg"},{"id":499772,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114760.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"New Jersey","city":"West Trenton","otherGeospatial":"former Naval Air Warfare Center","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -74.816667,\n 40.275\n ],\n [\n -74.816667,\n 40.2667\n ],\n [\n -74.808333,\n 40.2667\n ],\n [\n -74.808333,\n 40.275\n ],\n [\n -74.816667,\n 40.275\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, New Jersey Water Science Center
U.S. Geological Survey
3450 Princeton Pike, Suite 110
Lawrenceville, NJ, 08648
Groundwater is important as a drinking-water source and for maintaining base flow in rivers, streams, and lakes. Groundwater quality can be predicted, in part, by its residence time in the subsurface, but the residence-time distribution cannot be measured directly and must be inferred from models. This report compares residence-time distributions from four areas where groundwater flow and travel time were simulated with conventional simulation-inset models (IMs) and with a new automated model-construction method called general simulation models (GSMs). The comparison provides an opportunity to explore controls on travel time and improve the methods used in the creation of GSMs. These models can be useful for three main-use cases: (1) rapid testing of relationships that govern groundwater flow and age, (2) generation of consistent examples for training a machine-learning metamodel, and (3) serving as a starting point for more detailed models.
Comparison of the GSMs to IMs indicated a qualified pattern of agreement for residence-time distributions as indicated by the Nash-Sutcliffe efficiency and Spearman’s correlation coefficient. The agreement was best for the median values of the simulated residence times in young fractions of groundwater (defined as the fractions of groundwater in samples less than 65 years old) at the scale of the eight-digit hydrologic-unit code. Generally, the median values of the young fractions in the IMs were correlated with the median values from the GSMs. The relative trends across the four areas also were similar for the other residence-time metrics. The medians of residence-time metrics at finer scales show a fair degree of scatter. The GSM results compared most poorly for median travel times in the older fraction of groundwater (older than 65 years).
The GSM approach is intended as a flexible framework for developing models that can be useful individually as screening tools or collectively to support projects in statistical learning. Although one set of GSM algorithms was presented here, the approach can accommodate many types of data and also different categories of prior information. Comparison of GSMs and IMs suggests ways in which the GSMs, while remaining easy to construct and calibrate, can be improved for estimating groundwater travel times. IMs do not yield exact travel times, and matching GSMs to IMs does not guarantee an improvement; however, IMs provide a convenient benchmark against which to explore relations between physical characteristics of watersheds and the distribution of travel times within them.
This effort was undertaken as part of the National Water Quality Program of the U.S. Geological Survey to assist in determining the susceptibility of groundwater in glacial aquifers to a variety of natural and anthropogenic contaminants.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215142","programNote":"National Water Quality Program","usgsCitation":"Starn, J.J., Kauffman, L.J., and Feinstein, D.T., 2023, Groundwater residence times in glacial aquifers—A new general simulation-model approach compared to conventional inset models: U.S. Geological Survey Scientific Investigations Report 2021–5142, 37 p., https://doi.org/10.3133/sir20215142.","productDescription":"Report: v, 37 p.; Data Release","numberOfPages":"37","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-112499","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":500447,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114759.htm","linkFileType":{"id":5,"text":"html"}},{"id":413862,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2021/5142/images/"},{"id":413858,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5142/coverthb.jpg"},{"id":413859,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5142/sir20215142.pdf","text":"Report","size":"6.69 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5142"},{"id":413861,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2021/5142/sir20215142.XML"},{"id":413863,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HS83JL","text":"USGS data release","linkHelpText":"MODPATH-NWT and MODPATH6 models used to compare a new general simulation model approach with a conventional inset model approach for groundwater residence time in glacial aquifers"},{"id":413860,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20215142/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2021-5142"}],"country":"United States","state":"Illinois, Indiana, Michigan, Wisconsin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -84.5,\n 46\n ],\n [\n -89,\n 46\n ],\n [\n -89,\n 41.5\n ],\n [\n -84.5,\n 41.5\n ],\n [\n -84.5,\n 46\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
The U.S. Geological Survey (USGS), in cooperation with the New Jersey Department of Environmental Protection (NJDEP) and the New Jersey Office of Emergency Management (NJOEM), created digital flood-inundation maps for approximately 1,430 square miles of the New Jersey coast and tidewaters through 10 coastal counties stretching from Cumberland County through Bergen County, New Jersey. The maps depict extent and depth estimates of coastal flooding corresponding to selected tidal elevations recorded by 25 real-time USGS tide gages located within the study area. The flood-inundation maps can be accessed through the USGS Interagency Flood Risk Management (InFRM) Flood Decision Support Toolbox (FDST).
Previously published modeled data were utilized from the coupled ADvanced CIRCulation Model (ADCIRC) and Simulating Waves Nearshore (SWAN) model. Simulated tropical storm events were selected based on parameters including landfall location or closest approach location, maximum wind speed, central pressure, and radii of winds. Two storm events were selected per tide gage providing two “scenarios” and accompanying inundation-map libraries for each gage. Flood-inundation maps reflect between 9 to 30 stages (elevations) at each tide gage that correspond to areal extents and depths for ADCIRC-SWAN storm time steps extracted from modeled hydrographs at the gage locations. Water-surface elevations from ADCIRC-SWAN node points extending through each tide gage station extent were used to interpolate a water surface. Combining these surfaces with a geographic information system (GIS) topobathymetric digital elevation model (TBDEM) delineated the area flooded by coastal waters at each tide gage elevation.
The availability of these maps to visualize potential inundation for selected water levels along with real-time water level data available online from USGS tide gages, coastal impact statements, and forecasted tide elevations from the National Weather Service (NWS) will provide emergency management personnel and residents with a link between numeric and text warning information and images of estimated inundation extents in their community. User selected display of inundation allows early response activities to NWS forecasted water level elevations or mitigation planning by selecting targeted water levels and planning critical pre-flood activities such as building elevations, early traffic pattern changes because of neighborhood building inundation levels, improved understanding about when major road access is affected, as well as for post-flood recovery efforts.
A subsequent analysis of several community metrics including total structures, structure density, percent of buildings inundated, and roads and bridges affected by flooding was used to evaluate moderate flooding impacts among the mapped station extents. Initial comparisons are presented to show the variability of these characteristics within each mapped station extent then extended to evaluate impacts from moderate flooding on these same areas. The analysis used simulated inundation layers at the moderate flood stage to investigate the magnitude of inundation on building structures and major roads among the mapped station extents. Experimental equations were developed to begin testing if a mathematical equation could help identify communities that were disproportionately impacted at moderate flood stage. The community analysis of impacts to moderate flooding based on these inundation scenario maps should provide community leaders and local and state planning officials with tools to better visualize and understand how flooding begins to disrupt and damage building structures and major roads as a surrogate for direct increased risk to human life and property.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235005","collaboration":"Prepared in cooperation with New Jersey Department of Environmental Protection","usgsCitation":"Suro, T.P., Niemoczynski, M.J., Boetsma, A., and Niemoczynski, L.M., 2023, Moderate flood level scenarios—Synthetic storm-driven flood-inundation maps for coastal communities in 10 New Jersey counties: U.S. Geological Survey Scientific Investigations Report 2023–5005, 49 p., https://doi.org/10.3133/sir20235005.","productDescription":"Report: viii, 49 p.; Data Release","numberOfPages":"49","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-136043","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":417140,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5005/images/"},{"id":500685,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114740.htm","linkFileType":{"id":5,"text":"html"}},{"id":417141,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9RVF9P8","text":"USGS data release","linkHelpText":"Synthetic storm-driven flood-inundation grids for coastal communities in 10 New Jersey counties"},{"id":417139,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5005/sir20235005.XML"},{"id":417138,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235005/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2023-5005"},{"id":417137,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5005/sir20235005.pdf","text":"Report","size":"21.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5005"},{"id":417136,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5005/coverthb.jpg"}],"country":"United States","state":"New Jersey","county":"Atlantic County, Bergen County, Cape May County, Cumberland County, Essex County, Middlesex County, Monmouth County, Ocean County, Salem County, Union County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -74.1277080228522,\n 40.638935692142724\n ],\n [\n -74.41159623268268,\n 40.50386433220055\n ],\n [\n -74.13706697482502,\n 40.31620957676867\n ],\n [\n -74.07155431101805,\n 40.27813984647429\n ],\n [\n -74.2088189399465,\n 39.95129023758125\n ],\n [\n -74.58317622656678,\n 39.43518753081048\n ],\n [\n -74.78283386864535,\n 39.20591467723193\n ],\n [\n -75.42236225342704,\n 39.6781159291034\n ],\n [\n -75.58146443695806,\n 39.64689563243181\n ],\n [\n -75.51907142380868,\n 39.57479497276381\n ],\n [\n -75.55650723169862,\n 39.449642684385594\n ],\n [\n -75.2258242620061,\n 39.23250052123328\n ],\n [\n -75.13535439293969,\n 39.15996996348281\n ],\n [\n -75.03864522255803,\n 39.19382687463093\n ],\n [\n -74.92009849757379,\n 39.14303539458916\n ],\n [\n -75.00120941466811,\n 38.92494240360199\n ],\n [\n -74.90138059362884,\n 38.89338447021902\n ],\n [\n -74.52078321341743,\n 39.249413543217884\n ],\n [\n -74.25873255818952,\n 39.44482463320827\n ],\n [\n -74.05907491611174,\n 39.72851891657447\n ],\n [\n -73.93740900673615,\n 40.3827789234833\n ],\n [\n -73.99044306791338,\n 40.49911897812299\n ],\n [\n -74.17762210736144,\n 40.48488407551238\n ],\n [\n -74.0372378277754,\n 40.579726378448925\n ],\n [\n -74.06219503303558,\n 40.65787019904499\n ],\n [\n -74.1277080228522,\n 40.638935692142724\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, New Jersey Water Science Center
U.S. Geological Survey
3450 Princeton Pike, Suite 110
Lawrenceville, NJ 08648
The central Salem River in New Jersey is subject to periods of water-quality impairment, marked by elevated concentrations of phosphorus and chlorophyll-a, and low concentrations of and large diurnal swings in concentrations of dissolved oxygen. These seasonal eutrophic conditions are controlling factors for water quality in lower reaches, where the river is more lacustrine than in upper reaches, as a result of downstream damming. This biological productivity is supported by nutrient wash-off from agricultural areas in the surrounding watershed. To investigate this impairment, flow measurement and water-quality sampling were conducted during 2007–08 in support of development of a one-dimensional surface-water-quality model that simulates nutrient cycling and transformation processes.
The U.S. Geological Survey, in cooperation with the New Jersey Department of Environmental Protection, used the U.S. Environmental Protection Agency Water Quality Analysis Simulation Program (WASP) to develop a receiving-water-quality model of the central Salem River between Woodstown and Deepwater, New Jersey, from April 2007 to October 2008. The main-stem river and largest tributary were simulated. In the flow model, kinematic wave flow is used to simulate flow in upper reaches and ponded weir flow is used to simulate flow in lower reaches. The water-quality model makes use of a mass-balance equation to simulate the fate and transport of nutrients, phytoplankton chlorophyll-a, dissolved oxygen, and oxygen demands (an indicator rather than a substance) in the river. Model input included channel characteristics, boundary conditions for flow and water quality, environmental parameters, vertical dispersion coefficients, settling rates, and kinetic constants. Inputs were estimated where field data were lacking, notably for tributary flows and nutrient loads.
The model was calibrated to observed flow variables and concentrations of dissolved oxygen, chlorophyll-a, and nutrients at sampling locations, with emphasis on growing-season conditions. Calibration was achieved through graphical and statistical comparison of simulated results to observed data. Sensitivity analyses were performed, and model limitations and applicability were evaluated. Simulated results closely matched observed data in most cases, although some were overpredicted slightly. The most important causes of overprediction were estimated tributary flows for the flow model and estimated tributary watershed loads for the water-quality model. Calibration of dissolved-oxygen concentrations was closer, and predicted diurnal variations were consistent with high algal photosynthesis/respiration, although lack of continuous dissolved-oxygen data precluded verifying these predictions. A similar caveat applies to predicted diurnal variations in chlorophyll-a. Simulated limitations on algal growth were consistent with those based on observed data and indicated phosphorus was the main limiting nutrient, except during certain periods when nitrogen was limiting.
Two water-quality management scenarios were simulated with the model to assess the effect of point- and nonpoint-source nutrient reductions on water-quality conditions in the river. Scenarios involved (1) a return of watershed land use to predevelopment natural conditions and (2) an extreme reduction in nutrient input. Although the extreme-nutrient-reduction scenario yielded improvements in water quality, the natural-conditions scenario yielded the largest improvements as indicated by minimal violations of surface-water-quality standards or thresholds. However, years may be needed to attain the full benefit of these management scenarios as a result of accumulation of phosphorus and organic carbon in riverbed sediments in lacustrine reaches. The results of this study indicate that the quality of water in the central Salem River will improve if management policies that mitigate the effects of nutrient-loading practices in the watershed, particularly those related to agriculture, are implemented.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225047","collaboration":"Prepared in cooperation with the New Jersey Department of Environmental Protection","usgsCitation":"Spitz, F.J., and DePaul, V.T., 2023, Simulation of flow and eutrophication in the central Salem River, New Jersey: U.S. Geological Survey Scientific Investigations Report 2022–5047, 72 p., https://doi.org/10.3133/sir20225047.","productDescription":"Report: x, 72 p.; Data Release","numberOfPages":"72","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-109225","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":500449,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114735.htm","linkFileType":{"id":5,"text":"html"}},{"id":417027,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F78G8JPJ","text":"USGS data release","linkHelpText":"WASP model used to simulate flow and eutrophication in the central Salem River, New Jersey"},{"id":417026,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5047/images/"},{"id":417025,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5047/sir20225047.XML"},{"id":417024,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/sir20225047/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2022-5047"},{"id":417023,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5047/sir20225047.pdf","text":"Report","size":"12.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5047"},{"id":417022,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5047/coverthb.jpg"}],"country":"United States","state":"New Jersey","otherGeospatial":"Central Salem River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -75.51261142665348,\n 39.66506027345514\n ],\n [\n -75.13011677160785,\n 39.493754929673486\n ],\n [\n -75.01123329774249,\n 39.637202213256444\n ],\n [\n -75.41569555121957,\n 39.76545497451639\n ],\n [\n -75.51261142665348,\n 39.66506027345514\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, New Jersey Water Science Center
U.S. Geological Survey
3450 Princeton Pike, Suite 110
Lawrenceville, NJ 08648
Continued improvements in drinking-water quality characterization and treatment/distribution infrastructure are required to address the expanding number of documented environmental contaminants. To better understand the variability in contaminant exposures from the drinking water resource (surface and groundwater), through the distribution process, to the point-of-use (tapwater), in 2019 a synoptic assessment of broad chemical exposures was conducted in system-specific source waters, finished drinking water and service-area tapwater from 10 drinking water treatment facilities in the greater Minneapolis/St. Paul area of Minnesota, United States. Source water, finished water (collected pre-distribution in the treatment facility), and tapwater samples were analyzed for 465 unique organic compounds, 34 inorganic constituents, and 3 field parameters as well as in vitro estrogen, androgen, and glucocorticoid bioactivities. Mixtures of organic and inorganic contaminants were prevalent in source water, finished water, and tapwater samples, indicating the continued need for broad assessments of mixed contaminant exposures to characterize potential drinking-water human health outcomes. Contaminant concentrations were similar among drinking water sources and no exceedances of Environmental Protection Agency maximum contaminant level(s) (MCL) were observed in any treated sample (finished water or tapwater) in this study. No treated sample contained estrogenic, androgenic, or glucocorticoid activity at concentrations that may cause adverse human health effects. However, there were multiple exceedances of non-enforceable MCL goal(s) (MCLG), and other health advisories combined with frequent exceedances of benchmark-based hazard indices in both finished water and tapwater samples. These results indicate that exposure to contaminant mixtures is a potential public health concern underscoring our continued efforts to assess contaminant mixture exposures at the drinking-water point of consumption using a broad analytical scope.
","language":"English","publisher":"Royal Society of Chemistry","doi":"10.1039/d3ew00066d","usgsCitation":"Smalling, K., Bradley, P., Romanok, K., Elliott, S.M., de Lambert, J., Focazio, M.J., Gordon, S.E., Gray, J., Kanagy, L.K., Hladik, M.L., Loftin, K.A., McCleskey, R., Medlock-Kakaley, E., Cardon, M.C., Evans, N., and Weis, C., 2023, Exposures and potential health implications of contaminant mixtures in linked source water, finished drinking water, and tapwater from public-supply drinking water systems in Minneapolis/St. Paul area, USA: Environmental Science: Water Research and Technology, v. 9, p. 1813-1828, https://doi.org/10.1039/d3ew00066d.","productDescription":"16 p.","startPage":"1813","endPage":"1828","ipdsId":"IP-128928","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":443579,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1039/d3ew00066d","text":"Publisher Index Page"},{"id":417337,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota","city":"Minneapolis, St. Paul","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -94.00943612221862,\n 45.502541617459315\n ],\n [\n -94.00943612221862,\n 44.35362851581243\n ],\n [\n -92.69794345075478,\n 44.35362851581243\n ],\n [\n -92.69794345075478,\n 45.502541617459315\n ],\n [\n -94.00943612221862,\n 45.502541617459315\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"9","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Smalling, Kelly L. 0000-0002-1214-4920","orcid":"https://orcid.org/0000-0002-1214-4920","contributorId":214623,"corporation":false,"usgs":true,"family":"Smalling","given":"Kelly L.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":873432,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bradley, Paul M. 0000-0001-7522-8606","orcid":"https://orcid.org/0000-0001-7522-8606","contributorId":221226,"corporation":false,"usgs":true,"family":"Bradley","given":"Paul M.","affiliations":[{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":873433,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Romanok, Kristin M. 0000-0002-8472-8765","orcid":"https://orcid.org/0000-0002-8472-8765","contributorId":221227,"corporation":false,"usgs":true,"family":"Romanok","given":"Kristin M.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":873434,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Elliott, Sarah M. 0000-0002-1414-3024 selliott@usgs.gov","orcid":"https://orcid.org/0000-0002-1414-3024","contributorId":1472,"corporation":false,"usgs":true,"family":"Elliott","given":"Sarah","email":"selliott@usgs.gov","middleInitial":"M.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":873435,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"de Lambert, Jane","contributorId":303692,"corporation":false,"usgs":false,"family":"de Lambert","given":"Jane","affiliations":[{"id":65878,"text":"MN Department of Health","active":true,"usgs":false}],"preferred":false,"id":873436,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Focazio, Michael J. 0000-0003-0967-5576 mfocazio@usgs.gov","orcid":"https://orcid.org/0000-0003-0967-5576","contributorId":1276,"corporation":false,"usgs":true,"family":"Focazio","given":"Michael","email":"mfocazio@usgs.gov","middleInitial":"J.","affiliations":[{"id":38175,"text":"Toxics Substances Hydrology Program","active":true,"usgs":true},{"id":5056,"text":"Office of the AD Energy and Minerals, and Environmental Health","active":true,"usgs":true}],"preferred":true,"id":873437,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gordon, Stephanie E. 0000-0002-6292-2612 sgordon@usgs.gov","orcid":"https://orcid.org/0000-0002-6292-2612","contributorId":200931,"corporation":false,"usgs":true,"family":"Gordon","given":"Stephanie","email":"sgordon@usgs.gov","middleInitial":"E.","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":873438,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Gray, James L. 0000-0002-0807-5635","orcid":"https://orcid.org/0000-0002-0807-5635","contributorId":202726,"corporation":false,"usgs":true,"family":"Gray","given":"James L.","affiliations":[{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true},{"id":37464,"text":"WMA - 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The aggregated risks to multiple aquatic trophic levels (fish, invertebrates, plants) of the stormwater mixture exposures, which were documented in the national study, were explored herein by calculating cumulative ratios of organic-contaminant in vitro exposure–activity cutoffs (∑EAR) and health-benchmark-weighted cumulative toxicity quotients (∑TQ). Both risk assessment approaches indicated substantial (moderate to high) risk for acute adverse effects to aquatic organisms across multiple trophic levels (fish, macroinvertebrates, non-vascular/vascular plants) at or near stormwater discharge points across the United States. The results are interpreted as potential orders of magnitude underestimates of actual aquatic risk in stormwater control wetlands or in the immediate vicinity of such discharges to surface-water receptors, because the 438 organic-compound analytical space assessed in this study is orders of magnitude less than the 350 000 parent compounds estimated to be in current commercial use globally and the incalculable chemical-space of potential metabolites and degradates.
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0000-0002-1214-4920","orcid":"https://orcid.org/0000-0002-1214-4920","contributorId":214623,"corporation":false,"usgs":true,"family":"Smalling","given":"Kelly L.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":868976,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Masoner, Jason R. 0000-0002-4829-6379 jmasoner@usgs.gov","orcid":"https://orcid.org/0000-0002-4829-6379","contributorId":3193,"corporation":false,"usgs":true,"family":"Masoner","given":"Jason","email":"jmasoner@usgs.gov","middleInitial":"R.","affiliations":[{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":868977,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kolpin, Dana W. 0000-0002-3529-6505","orcid":"https://orcid.org/0000-0002-3529-6505","contributorId":204154,"corporation":false,"usgs":true,"family":"Kolpin","given":"Dana W.","affiliations":[{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true},{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"preferred":true,"id":868978,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gordon, Stephanie E. 0000-0002-6292-2612 sgordon@usgs.gov","orcid":"https://orcid.org/0000-0002-6292-2612","contributorId":200931,"corporation":false,"usgs":true,"family":"Gordon","given":"Stephanie","email":"sgordon@usgs.gov","middleInitial":"E.","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":868979,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70242071,"text":"70242071 - 2023 - Energy-related wastewater contamination alters microbial communities of sediment, water, and amphibian skin","interactions":[],"lastModifiedDate":"2023-04-06T11:59:01.360524","indexId":"70242071","displayToPublicDate":"2023-04-05T06:53:46","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Energy-related wastewater contamination alters microbial communities of sediment, water, and amphibian skin","docAbstract":"To inform responsible energy development, it is important to understand the ecological effects of contamination events. Wastewaters, a common byproduct of oil and gas extraction, often contain high concentrations of sodium chloride (NaCl) and heavy metals (e.g., strontium and vanadium). These constituents can negatively affect aquatic organisms, but there is scarce information for how wastewaters influence potentially distinct microbiomes in wetland ecosystems. Additionally, few studies have concomitantly investigated effects of wastewaters on the habitat (water and sediment) and skin microbiomes of amphibians or relationships among these microbial communities. We sampled microbiomes of water, sediment, and skin of four larval amphibian species across a gradient of chloride contamination (0.04–17,500 mg/L Cl) in the Prairie Pothole Region of North America. We detected 3129 genetic phylotypes and 68 % of those phylotypes were shared among the three sample types. The most common shared phylotypes were Proteobacteria, Firmicutes, and Bacteroidetes. Salinity of wastewaters increased dissimilarity within all three microbial communities, but not the diversity or richness of water and skin microbial communities. Strontium was associated with lower diversity and richness of sediment microbial communities, but not those of water or amphibian skin, likely because metal deposition occurs in sediment when wetlands dry. Based on Bray Curtis distance matrices, sediment microbiomes were similar to those of water, but neither had substantial overlap with amphibian microbiomes. Species identity was the strongest predictor of amphibian microbiomes; frog microbiomes were similar but differed from that of the salamander, whose microbiome had the lowest richness and diversity. Understanding how effects of wastewaters on the dissimilarity, richness, and diversity of microbial communities also influence the ecosystem function of communities will be an important next step. However, our study provides novel insight into the characteristics of, and associations among, different wetland microbial communities and effects of wastewaters from energy production.
Winslow Township and the Camden County Municipal Utility Authority (CCMUA) developed a plan to shut down the Winslow sewage-treatment facility and associated effluent infiltration facility and transfer the effluent to the CCMUA sewage-treatment facility on the Delaware River in Camden, New Jersey. Winslow Township reduced groundwater withdrawals from the Kirkwood-Cohansey aquifer system to offset groundwater recharge lost with the cessation of effluent infiltration. The U.S. Geological Survey, in cooperation with Winslow Township and the CCMUA, collected data to evaluate conditions prior to cessation of effluent infiltration and installed two continuous-record streamflow-gaging stations. Streamflow measurements also were made at two low-flow partial-record sites, and groundwater levels were measured in 17 wells at high and low water-level periods (May and September 2010). A groundwater-flow model provides estimated changes in base flow of the Great Egg Harbor River under several groundwater-withdrawal and effluent infiltration scenarios.
Water levels were measured in an observation well 480 feet (ft) from the infiltration lagoons during 1971–2010. A downward trend in water levels in the well prior to 1985 is attributed in part to increased impervious surfaces and groundwater withdrawals associated with development in the area that began in the early 1970s. From late 1985 to 2010, there was an upward trend in water levels in the well that is attributed to the construction of nearby effluent infiltration lagoons in 1985 and the increasing rate of effluent infiltration during the period. Recent and historical measurements made at the four surface-water sites were correlated with same-day discharges measured at three nearby index stations to estimate continuous low-flow record at the sites. Effects on base flow caused by reductions in groundwater withdrawals or the cessation of effluent infiltration in Winslow Township could not be ascertained from the available data with the statistical and analysis methods used.
Groundwater discharge to streams (base flow) was simulated with a groundwater-flow model of the Great Egg Harbor and Mullica River Basins. Simulated monthly base flows using 2008–10 withdrawal rates and effluent recharge (Scenario 1) are generally about 1.5 million gallons per day (Mgal/d) greater than simulated base flows using 2003–07 withdrawal rates (Baseline Scenario) because of the 1.57 Mgal/d reduction in average withdrawals by Winslow Township from the Kirkwood-Cohansey aquifer system from 2003–07 to 2008–10. Simulated monthly base flows using 2008–10 withdrawals but without effluent infiltration (Scenario 2) are very similar to, but typically slightly lower than, Baseline Scenario base flows.
Three hypothetical future distributions of groundwater withdrawals from existing Winslow Township wells are simulated, each without effluent infiltration and using the same groundwater withdrawal rate as Scenario 2, but with different hypothetical distributions of withdrawals among existing Winslow Township wells. The Scenario 3 and 4 base flows are greater than the Baseline Scenario base flows in all months, and the Scenario 5 base flows are less than the Baseline Scenario base flows in all months. The simulation results indicate that a reduction in average withdrawals from the Kirkwood-Cohansey aquifer system by 1.57 Mgal/d offsets the reduction of effluent infiltration by about the same rate, resulting in nearly unchanged base flows in the Great Egg Harbor River near Blue Anchor (01410820).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235002","collaboration":"Prepared in cooperation with the Township of Winslow and the Camden County Municipal Utilities Authority","usgsCitation":"Carleton, G.B., and Pope, D.A., 2023, Hydrologic effects of possible changes in water-supply withdrawals from, and effluent recharge to, the Kirkwood-Cohansey aquifer system, Winslow Township, Camden County, New Jersey: U.S. Geological Survey Scientific Investigations Report 2023–5002, 16 p., https://doi.org/10.3133/sir20235002.","productDescription":"Report: vii, 16 p.; Data Release","numberOfPages":"16","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-057410","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":413542,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7154G0Z","text":"USGS data release","linkHelpText":"MODFLOW-2000 model used to evaluate the effects of possible changes in water-supply withdrawals from, and effluent recharge to, the Kirkwood-Cohansey aquifer system, Winslow Township, Camden County, New Jersey"},{"id":500487,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114441.htm","linkFileType":{"id":5,"text":"html"}},{"id":413541,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5002/images/"},{"id":413538,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5002/sir20235002.pdf","text":"Report","size":"1.58 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5002"},{"id":413537,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5002/coverthb.jpg"},{"id":413539,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235002/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2023-5002"},{"id":413540,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5002/sir20235002.XML"}],"country":"United States","state":"New Jersey","county":"Camden County","otherGeospatial":"Winslow Township","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -75,\n 39.833\n ],\n [\n -75,\n 39.5833\n ],\n [\n -74.833,\n 39.5833\n ],\n [\n -74.833,\n 39.833\n ],\n [\n -75,\n 39.833\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, New Jersey Water Science Center
U.S. Geological Survey
3450 Princeton Pike, Suite 110
Lawrenceville, NJ, 08648
No abstract available.
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