A three-dimensional numerical model of groundwater flow was developed and calibrated for the unconsolidated New Jersey Coastal Plain aquifers underlying Joint Base McGuire-Dix-Lakehurst (JBMDL) and vicinity, New Jersey, to evaluate groundwater flow pathways of per- and polyfluoroalkyl substances (PFAS) contamination associated with use of aqueous film forming foam (AFFF) at the base. The regional subsurface flow model spans an area of approximately 518 square miles around JBMDL and is based on a previously developed hydrogeologic framework of the area. Steady-state flow in the unconsolidated aquifers was simulated using the MODFLOW 6 groundwater flow model, which is able to account for hydrostratigraphic pinchouts and discontinuities in the Coastal Plain aquifers underlying JBMDL. To account for local patterns of fluid flow driving advective subsurface migration of PFAS, the grid was refined using quadtree meshes spanning 21 areas where historical AFFF use was identified, five off-site reconnaissance areas identified by AFCEC as areas in which the occurrence of PFAS is most likely to pose a potential danger to local drinking water supplies, and along streams that behave as drains in the base-flow-dominated Coastal Plain.
Following grid refinement, four physical processes known to govern subsurface flow were introduced to the model. These included effective precipitation recharge, discharge to streams and stream-connected wetlands, regional inflows and outflows along the model bottom, and withdrawals from wells, each of which were incorporated into the model as either external or internal boundary conditions. To account for effective precipitation recharge, a specified-flow boundary was assigned along the top of the model. Similarly, regional flows predicted using the modified U.S Geological Survey’s New Jersey Coastal Plain Regional Aquifer System Analysis model were treated as specified-flow boundary conditions along the bottom of the model. Base-flow losses were treated as drains along streams delineated using a 10-foot LiDAR dataset. Drains were also assigned to cells falling within stream-connected National Hydrologic Database wetlands. Finally, well-pumpage data mined from the New Jersey Water Transfer database were added to the model to account for extraction of groundwater through pumping from industrial-supply and drinking-water-supply wells. Along model edges established at groundwater divides, where the net flux of water across the boundary is equal to zero, natural no-flow boundary conditions were imposed.
The refined flow model was calibrated using the parameter-estimation (PEST) program, which adjusts model parameters by performing a gradient search over the sum-of-squared-error objective function until the parameter set that produces simulated water levels and base flows most closely matches 544 water levels and 20 estimated base flows and closely adheres to initial parameter estimates. Based on the analysis of calibration residuals, the model did not appear to be affected by significant model structural error.
The MODPATH particle-tracking algorithm was used to estimate advective transport paths of PFAS in the vicinity of JBMDL. Forward tracking was used to determine paths of PFAS away from AFFF source areas to streams, wetlands, pumping wells, and geographic areas that PFAS may contaminate. Additionally, reverse tracking was used to determine particle pathlines away from off-site PFAS reconnaissance areas, or areas within which all sources of PFAS might be advectively transported into subsurface drinking-water supplies, to locations at land surface that may indicate a source of PFAS.
The coupled and calibrated groundwater flow and particle-tracking transport model provide valuable tools for predicting the relative extent of PFAS contamination from onsite legacy source areas. The calibrated model also provides measures of water-level and base-flow observation influence that can help guide future data-collection efforts related to groundwater and surface water sampling for PFAS.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221112","collaboration":"Prepared in cooperation with the U.S. Air Force","usgsCitation":"Fiore, A.R., and Colarullo, S.J., 2023, Simulation of regional groundwater flow and advective transport of per- and polyfluoroalkyl substances, Joint Base McGuire-Dix-Lakehurst and vicinity, New Jersey, 2018: U.S. Geological Survey Open-File Report 2022–1112, 41 p., 2 pls., https://doi.org/10.3133/ofr20221112.","productDescription":"Report: ix, 41 p.; 2 Plates: 35.00 x 45.00 inches and 45.00 x 30.00 inches; Data Release","numberOfPages":"41","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-129806","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":412124,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9EK4CZS","text":"USGS data release","linkHelpText":"MODFLOW6 and MODPATH7 used to simulate regional groundwater flow and advective transport of per- and polyfluoroalkyl substances, Joint Base McGuire-Dix-Lakehurst and vicinity, New Jersey, 2018"},{"id":412125,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1112/ofr20221112.XML"},{"id":412123,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/ofr20221112/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1112"},{"id":412121,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1112/coverthb.jpg"},{"id":412126,"rank":6,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1112/images/"},{"id":412129,"rank":7,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2022/1112/ofr20221112_plate1.pdf","text":"Plate 1","size":"212 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Forward particle tracks from aqueous film-forming foam source areas 1 to 15 and reverse particle tracks from per- and polyfluoroalkyl substances reconnaissance areas 4 and 14, Joint Base McGuire-Dix-Lakehurst and vicinity, New Jersey, 2018"},{"id":412122,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1112/ofr20221112.pdf","text":"Report","size":"7.96 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1112"},{"id":412130,"rank":8,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2022/1112/ofr20221112_plate2.pdf","text":"Plate 2","size":"200 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Forward particle tracks from aqueous film-forming foam source areas 16 to 21 and reverse particle tracks from per- and polyfluoroalkyl substances reconnaissance areas 16 to 19, Joint Base McGuire-Dix-Lakehurst and vicinity, New Jersey, 2018"},{"id":499723,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114286.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"New Jersey","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -74.77016941849112,\n 40.156458843115274\n ],\n [\n -74.77016941849112,\n 39.93505011875061\n ],\n [\n -74.17559168378837,\n 39.93505011875061\n ],\n [\n -74.17559168378837,\n 40.156458843115274\n ],\n [\n -74.77016941849112,\n 40.156458843115274\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
In the United States and globally, contaminant exposure in unregulated private-well point-of-use tapwater (TW) is a recognized public-health data gap and an obstacle to both risk-management and homeowner decision making. To help address the lack of data on broad contaminant exposures in private-well TW from hydrologically-vulnerable (alluvial, karst) aquifers in agriculturally-intensive landscapes, samples were collected in 2018–2019 from 47 northeast Iowa farms and analyzed for 35 inorganics, 437 unique organics, 5 in vitro bioassays, and 11 microbial assays. Twenty-six inorganics and 51 organics, dominated by pesticides and related transformation products (35 herbicide-, 5 insecticide-, and 2 fungicide-related), were observed in TW. Heterotrophic bacteria detections were near ubiquitous (94 % of the samples), with detection of total coliform bacteria in 28 % of the samples and growth on at least one putative-pathogen selective media across all TW samples. Health-based hazard index screening levels were exceeded frequently in private-well TW and attributed primarily to inorganics (nitrate, uranium). Results support incorporation of residential treatment systems to protect against contaminant exposure and the need for increased monitoring of rural private-well homes. Continued assessment of unmonitored and unregulated private-supply TW is needed to model contaminant exposures and human-health risks.
210Po, which is of human-health concern based on lifetime ingestion cancer risk, is indirectly regulated in drinking water through the U.S. Environmental Protection Agency’s gross alpha-particle activity (GAPA) maximum contaminant level of 15 pCi/L (picocuries per liter). This regulation requires independent measurement of 226Ra for samples exceeding the GAPA screening level of 5 pCi/L. There is no such requirement for 210Po. Co-occurrence of 226Ra and 210Po, alpha-emitting 238U-decay-series progeny, might be helpful in locating high-210Po waters but is unverified. Relations among 210Po, 226Ra, and GAPA evaluated for samples from 257 public-supply wells from Coastal Plain aquifers showed that concentrations of 226Ra correlated with GAPA but neither correlated with 210Po concentrations. The highest concentrations of 226Ra and 210Po were found under differing geochemical conditions. The highest 226Ra occurred in low-pH oxidizing waters and in neutral-pH reducing waters, where geochemical conditions render Fe–Mn-hydroxide sorbents inefficient. 210Po was highest (10.1 pCi/L) in reducing waters with high pH (>7.5, which results from progressive cation exchange), where 226Ra was lowest─exchanged to clay minerals. Because 226Ra and 210Po did not co-occur, the GAPA screening might not be protective for 210Po. Independent 210Po analysis is prudent, especially where groundwater is reducing with high pH and low 226Ra concentrations.
Conservation efforts have been implemented in agroecosystems to enhance pollinator diversity by creating grassland habitat, but little is known about the exposure of bees to pesticides while foraging in these grassland fields. Pesticide exposure was assessed in 24 conservation grassland fields along an agricultural gradient at two time points (July and August) using silicone band passive samplers (nonlethal) and bee tissues (lethal). Overall, 46 pesticides were detected including 9 herbicides, 19 insecticides, 17 fungicides, and a plant growth regulator. For the bands, there were more frequent/higher concentrations of herbicides in July (maximum: 1600 ng/band in July; 570 ng/band in August), while insecticides and fungicides had more frequent/higher concentrations in August (maximum: 110 and 65 ng/band in July; 1500 and 1700 ng/band in August). Pesticide concentrations in bands increased 16% with every 10% increase in cultivated crops. The bee tissues showed no difference in detection frequency, and concentrations were similar among months; maximum concentrations of herbicides, insecticides, and fungicides in July and August were 17, 27, and 180 and 19, 120, and 170 ng/g, respectively. Pesticide residues in bands and bee tissues did not always show the same patterns; of the 20 compounds observed in both media, six (primarily fungicides) showed a detection-concentration relationship between the two media. Together, the band and bee residue data can provide a more complete understanding of pesticide exposure and accumulation in conserved grasslands.
","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.2c07195","usgsCitation":"Hladik, M.L., Kraus, J.M., Smith, C., Vandever, M.W., Kolpin, D., Givens, C.E., and Smalling, K., 2023, Wild bee exposure to pesticides in conservation grasslands increases along an agricultural gradient: A tale of two sample types: Environmental Science and Technology, v. 57, no. 1, p. 321-330, https://doi.org/10.1021/acs.est.2c07195.","productDescription":"10 p.","startPage":"321","endPage":"330","ipdsId":"IP-145884","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":435530,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9M3QCVW","text":"USGS data release","linkHelpText":"Pesticide residues in passive samplers and bee tissue from Conservation Reserve Program fields across an agricultural gradient in eastern Iowa, USA, 2019 (ver 2.0, October 2023)"},{"id":411113,"rank":1,"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 -93.84229194623344,\n 43.40823254194967\n ],\n [\n -93.84229194623344,\n 40.49028000708452\n ],\n [\n -90.2987761617945,\n 40.49028000708452\n ],\n [\n -90.2987761617945,\n 43.40823254194967\n ],\n [\n 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0000-0002-3529-6505","orcid":"https://orcid.org/0000-0002-3529-6505","contributorId":205652,"corporation":false,"usgs":true,"family":"Kolpin","given":"Dana W.","affiliations":[{"id":351,"text":"Iowa 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},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true}],"preferred":true,"id":860117,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"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":860118,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"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":860119,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70238984,"text":"70238984 - 2023 - Bottled water contaminant exposures and potential human effects","interactions":[],"lastModifiedDate":"2022-12-20T12:58:13.822249","indexId":"70238984","displayToPublicDate":"2022-12-19T06:55:17","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1523,"text":"Environment International","active":true,"publicationSubtype":{"id":10}},"title":"Bottled water contaminant exposures and potential human effects","docAbstract":"Bottled water (BW) consumption in the United States and globally has increased amidst heightened concern about environmental contaminant exposures and health risks in drinking water supplies, despite a paucity of directly comparable, environmentally-relevant contaminant exposure data for BW. This study provides insight into exposures and cumulative risks to human health from inorganic/organic/microbial contaminants in BW.
BW from 30 total domestic US (23) and imported (7) sources, including purified tapwater (7) and spring water (23), were analyzed for 3 field parameters, 53 inorganics, 465 organics, 14 microbial metrics, and in vitro estrogen receptor (ER) bioactivity. Health-benchmark-weighted cumulative hazard indices and ratios of organic-contaminant in vitro exposure-activity cutoffs were assessed for detected regulated and unregulated inorganic and organic contaminants.
48 inorganics and 45 organics were detected in sampled BW. No enforceable chemical quality standards were exceeded, but several inorganic and organic contaminants with maximum contaminant level goal(s) (MCLG) of zero (no known safe level of exposure to vulnerable sub-populations) were detected. Among these, arsenic, lead, and uranium were detected in 67 %, 17 %, and 57 % of BW, respectively, almost exclusively in spring-sourced samples not treated by advanced filtration. Organic MCLG exceedances included frequent detections of disinfection byproducts (DBP) in tapwater-sourced BW and sporadic detections of DBP and volatile organic chemicals in BW sourced from tapwater and springs. Precautionary health-based screening levels were exceeded frequently and attributed primarily to DBP in tapwater-sourced BW and co-occurring inorganic and organic contaminants in spring-sourced BW.
The results indicate that simultaneous exposures to multiple drinking-water contaminants of potential human-health concern are common in BW. Improved understandings of human exposures based on more environmentally realistic and directly comparable point-of-use exposure characterizations, like this BW study, are essential to public health because drinking water is a biological necessity and, consequently, a high-vulnerability vector for human contaminant exposures.
Best management practices (BMPs) have been predominantly used throughout the Chesapeake Bay watershed (CBW) to reduce nutrients and sediments entering streams, rivers, and the bay. These practices have been successful in reducing loads entering the estuary and have shown the potential to reduce other contaminants (pesticides, hormonally active compounds, pathogens) in localized studies and modeled load estimates. However, further understanding of relationships between BMPs and non-nutrient contaminant reductions at regional scales using sampled data would be beneficial. Total estrogenic activity was measured in surface water samples collected over a decade (2008–2018) in 211 undeveloped NHDPlus V2.1 watersheds within the CBW. Bayesian hierarchical modeling between total estrogenic activity and landscape predictors including landcover, runoff, BMP intensity, and a BMP*agriculture intensity interaction term indicates a 96% posterior probability that BMP intensity on agricultural land is reducing total estrogenic activity. Additionally, watersheds with high agriculture and low BMPs had a 49% posterior probability of exceeding an effects-based threshold in aquatic organisms of 1 ng/L but only a 1% posterior probability of exceeding this threshold in high-agriculture, high-BMP watersheds.
Stream morphology is affected by changes on the surrounding landscape. Understanding the effects of urbanization on stream morphology is a critical factor for land managers to maintain and improve vulnerable stream corridors in urbanizing landscapes. Stormwater practices are used in urban landscapes to manage runoff volumes and peak flows, potentially mitigating alterations to the flow regime that drive changes in channel morphology. However, there remains a paucity of long-term studies assessing watershed-scale relationships between urbanization and effects on stream morphology where green stormwater infrastructure exists in high densities. This paper evaluates the geomorphic changes across four headwater catchments in the Chesapeake Bay Watershed over the course of >10 yr and relates these changes to urban development. Annual cross-sectional surveys conducted from 2002 to 2019 in one forested catchment, one agricultural catchment, and two treatment catchments were used to understand the relationship between urbanization and changes in stream morphology. Six cross-sectional geomorphic metrics were calculated and compared with development timelines and high flow events. A channel evolution model was then used to understand the status of morphologic stability at sites within the study. Results suggest downstream environments in developing areas are more impacted during early phases of suburban construction. Channel change during construction could be a result of sediment and erosion control efforts' limitations on preventing and controlling overland sediment mobilization or of increased discharge causing widening and thus bank-derived sediment to move to the streambed. Results demonstrate that geomorphic metrics are highly variable within a small area and are not always accurate representations of broader landscape changes but rather of the more localized environment at a specific stream segment. Despite a high density of stormwater management facilities in urban catchments, substantial alterations to cross sections were found at multiple locations in each catchment including the controls.
Bioaugmentation is a promising strategy for enhancing trichloroethylene (TCE) degradation in fractured rock. However, slow or incomplete biodegradation can lead to stalling at degradation byproducts such as 1,2-dichloroethene (cis-DCE) and vinyl chloride (VC). Over the course of 7 years, we examined the response of groundwater microbial populations in a bioaugmentation test where an emulsified vegetable oil solution (EOS®) and a dechlorinating consortium (KB-1®), containing the established dechlorinator Dehalococcoides (DHC), were injected into a TCE-contaminated fractured rock aquifer. Indigenous microbial communities responded within 2 days to added substrate and outcompeted KB-1®, and over the years of monitoring, several other notable turnover events were observed. Concentrations of ethene, the end product in reductive dechlorination, had the strongest correlations (P< .05) with members of Candidatus Colwellbacteria but their involvement in reductive dechlorination is unknown and warrants further investigation.DHC never exceeded 0.6% relative abundance of groundwater microbial communities, despite its previously presumed importance at the site. Increased concentrations of carbon dioxide, acetic acid, and methane were positively correlated with increasing ethene concentrations; however, concentrations of cis-DCE and VC remained high by the end of the monitoring period suggesting preferential enrichment of indigenous partial dechlorinators over bioaugmented complete dechlorinators. This study highlights the importance of characterizing in situ microbial populations to understand how they can potentially enhance or inhibit augmented TCE degradation.
","language":"English","publisher":"Oxford University Press","doi":"10.1093/femsec/fiac077","usgsCitation":"Underwood, J.C., Akob, D., Lorah, M.M., Imbrigiotta, T.E., Harvey, R.W., and Tiedeman, C.R., 2022, Microbial community response to a bioaugmentation test to degrade trichloroethylene in a fractured rock aquifer, Trenton, N.J: Microbial Ecology, v. 98, no. 7, fiac077, 16 p., https://doi.org/10.1093/femsec/fiac077.","productDescription":"fiac077, 16 p.","ipdsId":"IP-136036","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true},{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":446899,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/femsec/fiac077","text":"Publisher Index Page"},{"id":435740,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9RCWZPH","text":"USGS data release","linkHelpText":"Microbial community analyses of groundwater collected during an enhanced bioremediation experiment of trichlorethylene in a fractured rock aquifer, West Trenton, NJ (2008-2015)"},{"id":404875,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Jersey","city":"Trenton","otherGeospatial":"Naval Air Warfare Center","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.81015682220459,\n 40.26737800407964\n ],\n [\n -74.80513572692871,\n 40.27612061363972\n ],\n [\n -74.80620861053467,\n 40.27726656481315\n ],\n [\n -74.80620861053467,\n 40.277855903568465\n ],\n [\n -74.80582237243652,\n 40.27903456566876\n ],\n [\n -74.80449199676514,\n 40.28001676838985\n ],\n [\n -74.80384826660156,\n 40.28093347805573\n ],\n [\n -74.80393409729004,\n 40.28227578049736\n ],\n [\n -74.80462074279785,\n 40.28315972120923\n ],\n [\n -74.80582237243652,\n 40.283847222661024\n ],\n [\n -74.80753898620605,\n 40.28407638825784\n ],\n [\n -74.80955600738525,\n 40.28437102859794\n ],\n [\n -74.81015682220459,\n 40.28391269862511\n ],\n [\n -74.8119592666626,\n 40.28355258003785\n ],\n [\n -74.81316089630127,\n 40.28342162734864\n ],\n [\n -74.81380462646484,\n 40.283749008596\n ],\n [\n -74.81393337249756,\n 40.28443650405466\n ],\n [\n -74.81462001800536,\n 40.28515672989297\n ],\n [\n -74.81569290161133,\n 40.285385891050446\n ],\n [\n -74.81676578521729,\n 40.2853531537898\n ],\n [\n -74.81959819793701,\n 40.283847222661024\n ],\n [\n -74.8218297958374,\n 40.28122813209425\n ],\n [\n -74.82221603393555,\n 40.28057334359796\n ],\n [\n -74.82208728790283,\n 40.27978758903121\n ],\n [\n -74.82079982757568,\n 40.278641680585025\n ],\n [\n -74.82058525085449,\n 40.277757680799304\n ],\n [\n -74.82191562652588,\n 40.273304765410735\n ],\n [\n -74.82174396514893,\n 40.272813617082406\n ],\n [\n -74.82213020324707,\n 40.271765822059926\n ],\n [\n -74.82414722442626,\n 40.27058703325471\n ],\n [\n -74.82354640960693,\n 40.269735673006274\n ],\n [\n -74.8218297958374,\n 40.26858959420978\n ],\n [\n -74.8192548751831,\n 40.26580617913769\n ],\n [\n -74.81462001800536,\n 40.268098411637695\n ],\n [\n -74.81015682220459,\n 40.26737800407964\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"98","issue":"7","noUsgsAuthors":false,"publicationDate":"2022-06-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Underwood, Jennifer C. 0000-0002-2702-0410 jcunder@usgs.gov","orcid":"https://orcid.org/0000-0002-2702-0410","contributorId":294555,"corporation":false,"usgs":true,"family":"Underwood","given":"Jennifer","email":"jcunder@usgs.gov","middleInitial":"C.","affiliations":[{"id":37464,"text":"WMA - 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To achieve this goal the TMDL requires the implementation of Best Management Practices (BMPs), which are accepted land management practices for reducing pollutant runoff to nearby bodies of water. While the TMDL requires that the necessary management actions be in place by 2025 to eventually reach targeted nutrient loads, the ability to detect an effect of BMPs while assuming that one has occurred (i.e. statistical power) is still not well understood. The goal of this study was to investigate the power and required timelines to detect nutrient reductions in streams and rivers as the result of BMP implementation at the Chesapeake Watershed scale. Power estimates were produced using SPAtially Referenced Regression On Watershed attributes (SPARROW) models, which offer a flexible statistical framework and were recently extended to allow for modeling multiple time steps. Nitrogen and phosphorus focused models were calibrated to estimate the power to detect reductions in flux from numerous constituent sources. To confidently detect a decrease in constituent flux reaching the Chesapeake Bay’s tidal waters from a specific constituent source, reductions ranging from 30–60% were required for the nitrogen model. In contrast, reductions of up to 80% were not detectable under the phosphorus model. The timelines necessary to detect reductions in nitrogen flux ranged from 11 to several hundred years under different rates-of-change and management scenarios. The approach proposed here can help better understand the ability to detect the effects of BMPs on a regional scale and help guide future management actions and monitoring programs.
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twagner@usgs.gov","orcid":"https://orcid.org/0000-0003-1726-016X","contributorId":1050,"corporation":false,"usgs":true,"family":"Wagner","given":"Tyler","email":"twagner@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":837248,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"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":837247,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70229101,"text":"70229101 - 2022 - Lessons learned from 20 y of monitoring suburban development with distributed stormwater management in Clarksburg, Maryland, USA","interactions":[],"lastModifiedDate":"2022-09-15T14:05:49.817277","indexId":"70229101","displayToPublicDate":"2022-02-25T06:18:11","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1699,"text":"Freshwater Science","active":true,"publicationSubtype":{"id":10}},"title":"Lessons learned from 20 y of monitoring suburban development with distributed stormwater management in Clarksburg, Maryland, USA","docAbstract":"Urban development is a well-known stressor for stream ecosystems, presenting a challenge to managers tasked with mitigating its effects. For the past 20 y, streamflow, water quality, geomorphology, and benthic communities were monitored in 5 watersheds in Montgomery County, Maryland, USA. This study presents a synthesis of multiple studies of monitoring efforts in the study area and new analysis of more recent monitoring data to document the primary lessons learned from monitoring. The monitored watersheds include a forested control, an urban control with centralized stormwater management, and 3 suburban treatment watersheds featuring low-impact development and a high density of infiltration-focused stormwater facilities distributed across the watershed. Treatment watersheds were monitored before development, during construction, and after development. Monitoring was initiated to inform adaptive management of stormwater and impervious cover limits within the study area, with a focus on the impacts of distributed stormwater management. Results from our synthesis indicate that distributed stormwater management is advantageous compared with centralized stormwater management in numerous ways. Hydrologic benefits were greater with distributed stormwater infrastructure, demonstrating the ability to mitigate runoff volumes and peak flows and, for small storms, replicate predevelopment conditions. Baseflow temporarily increased during the construction phase in the treatment watersheds. Water-quality benefits were mixed, with declines in baseflow nitrate concentrations but limited changes to nitrate export and increases in specific conductance after development. Substantial topographic changes occurred during construction in the treatment watersheds, including changes within the riparian zone, despite riparian buffer protections. Ecological monitoring indicated that even though index of biotic integrity scores rebounded in some cases, sensitive benthic macroinvertebrate families did not fully recover in the treatment watersheds. Lessons learned from this synthesis highlight the importance of tracking multiple indicators of stream health and considering past land use and that more stormwater facilities distributed across the watershed is beneficial but cannot mitigate the effects of all urban stressors on aquatic ecosystems.
We present a new field measurement and numerical interpretation method (combined termed ‘test’) to parameterize the diffusion of trichloroethene (TCE) and its biodegradation products (DPs) from the matrix of sedimentary rock. The method uses a dual-packer system to interrogate a low-permeability section of the rock matrix adjacent to a previously contaminated borehole and uses the borehole monitoring history to establish the pre-test condition. TCE and its DPs are removed from the groundwater between the packers at the onset of the testing. The parameters estimated by fitting a radial diffusion model to the concentration history and borehole concentration data, also termed back-diffusion, are the tortuosity factor and sorption coefficients of TCE and DPs in the rock matrix and the TCE and DP biodegradation rate coefficients in the borehole. We demonstrate the equipment design and the interpretive method using a borehole accessing the grey mudstone at a TCE contaminated site in the Newark Basin. In this test, both nonreactive (bromide) and reactive (trichlorofluoroethene) tracers are used to constrain the estimated parameters; however, the bromide tracer was not needed to estimate the parameters in this test. The parameters estimated from the field test are consistent with values measured independently in laboratory experiments using field samples of similar lithology. From the interpretation, we compute the TCE and DP concentration distributions in the rock matrix prior to the test to illustrate how the results can be used to enhance understanding of contaminant distribution in the rock matrix.
","language":"English","publisher":"National Ground Water Association","doi":"10.1111/gwmr.12495","usgsCitation":"Allen-King, R.M., Kiekhaefer, R.L., Goode, D.J., Hsieh, P.A., Lorah, M.M., and Imbrigiotta, T.E., 2022, A borehole test for chlorinated solvent diffusion and degradation rates in sedimentary rock: Groundwater Monitoring and Remediation, v. 42, no. 2, p. 23-34, https://doi.org/10.1111/gwmr.12495.","productDescription":"12 p.","startPage":"23","endPage":"34","ipdsId":"IP-122580","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":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":394652,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":394804,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P99I50JE","text":"USGS data release","linkHelpText":"A finite-difference algorithm used to simulate radial diffusion, adsorption, and reactions of chlorinated ethenes in porous media"}],"volume":"42","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-01-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Allen-King, Richelle M. 0000-0001-5559-1213","orcid":"https://orcid.org/0000-0001-5559-1213","contributorId":272047,"corporation":false,"usgs":false,"family":"Allen-King","given":"Richelle","email":"","middleInitial":"M.","affiliations":[{"id":56340,"text":"University at Buffalo, SUNY","active":true,"usgs":false}],"preferred":false,"id":831399,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kiekhaefer, Rebecca L.","contributorId":272048,"corporation":false,"usgs":false,"family":"Kiekhaefer","given":"Rebecca","email":"","middleInitial":"L.","affiliations":[{"id":56340,"text":"University at Buffalo, SUNY","active":true,"usgs":false}],"preferred":false,"id":831400,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Goode, Daniel J. 0000-0002-8527-2456","orcid":"https://orcid.org/0000-0002-8527-2456","contributorId":216750,"corporation":false,"usgs":true,"family":"Goode","given":"Daniel","email":"","middleInitial":"J.","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":831401,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hsieh, Paul A. 0000-0003-4873-4874 pahsieh@usgs.gov","orcid":"https://orcid.org/0000-0003-4873-4874","contributorId":1634,"corporation":false,"usgs":true,"family":"Hsieh","given":"Paul","email":"pahsieh@usgs.gov","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":39113,"text":"WMA - Office of Quality Assurance","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":831402,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lorah, Michelle M. 0000-0002-9236-587X","orcid":"https://orcid.org/0000-0002-9236-587X","contributorId":224040,"corporation":false,"usgs":true,"family":"Lorah","given":"Michelle","middleInitial":"M.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":831403,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Imbrigiotta, Thomas E. 0000-0003-1716-4768 timbrig@usgs.gov","orcid":"https://orcid.org/0000-0003-1716-4768","contributorId":152114,"corporation":false,"usgs":true,"family":"Imbrigiotta","given":"Thomas","email":"timbrig@usgs.gov","middleInitial":"E.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":831404,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70227176,"text":"70227176 - 2022 - Food, beverage, and feedstock processing facility wastewater: A unique and underappreciated source of contaminants to U.S. streams","interactions":[],"lastModifiedDate":"2022-02-15T16:19:12.225859","indexId":"70227176","displayToPublicDate":"2021-12-30T08:50:43","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Food, beverage, and feedstock processing facility wastewater: A unique and underappreciated source of contaminants to U.S. streams","docAbstract":"Process wastewaters from food, beverage, and feedstock facilities, although regulated, are an under-investigated environmental contaminant source. Food process wastewaters (FPWWs) from 23 facilities in 17 U.S. states were sampled and documented for a plethora of chemical and microbial contaminants. Of the 576 analyzed organics, 184 (32%) were detected at least once, with concentrations as large as 143 μg L–1 (6:2 fluorotelomer sulfonic acid), and as many as 47 were detected in a single FPWW sample. Cumulative per/polyfluoroalkyl substance concentrations up to 185 μg L–1 and large pesticide transformation product concentrations (e.g., methomyl oxime, 40 μg L–1; clothianidin TMG, 2.02 μg L–1) were observed. Despite 48% of FPWW undergoing disinfection treatment prior to discharge, bacteria resistant to third-generation antibiotics were found in each facility type, and multiple bacterial groups were detected in all samples, including total coliforms. The exposure–activity ratios and toxicity quotients exceeded 1.0 in 13 and 22% of samples, respectively, indicating potential biological effects and toxicity to vertebrates and invertebrates associated with the discharge of FPWW. Organic contaminant profiles of FPWW differed from previously reported contaminant profiles of municipal effluents and urban storm water, indicating that FPWW is another important source of chemical and microbial contaminant mixtures discharged into receiving surface waters.
","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.1c06821","usgsCitation":"Hubbard, L.E., Kolpin, D., Givens, C.E., Blackwell, B.D., Bradley, P., Gray, J., Lane, R.F., Masoner, J.R., McCleskey, R., Romanok, K., Sandstrom, M.W., Smalling, K., and Villeneuve, D., 2022, Food, beverage, and feedstock processing facility wastewater: A unique and underappreciated source of contaminants to U.S. streams: Environmental Science & Technology, v. 56, no. 2, p. 1028-1040, https://doi.org/10.1021/acs.est.1c06821.","productDescription":"13 p.","startPage":"1028","endPage":"1040","ipdsId":"IP-130265","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":452,"text":"National Water Quality Laboratory","active":true,"usgs":true},{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":449332,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9219000","text":"External Repository"},{"id":436021,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WJYI2H","text":"USGS data release","linkHelpText":"Concentrations of inorganic, organic, and microbial analytes from a national reconnaissance of wastewater from food, beverage, and feedstock facilities across the United States"},{"id":393860,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alabama, Arkansas, California, Idaho, Illinois, Iowa, Michigan, Minnesota, Nebraska, New York, Pennsylvania, Tennessee, Texas, 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Land management activities (e.g., Best Management Practices) are an important tool used to reduce point and non-point sources of pollution. However, the ability to confidently make inferences about the efficacy of land management activities on reducing in-stream chemical concentrations is poorly understood. We estimated regional temporal trends and components of variation for commonly used herbicides (atrazine and metolachlor), total estrogenicity, and riverine sediment concentrations of total PCBs for rivers in the Chesapeake Bay Watershed, USA. We then used the estimated variance components to perform a power analysis and evaluated the statistical power to detect regional temporal trends under different monitoring scenarios. Scenarios included varying the magnitude of the annual contaminant decline, the number of sites sampled each year, the number of years sampled, and sampling frequency. Monitoring for short time periods (e.g., 5 years) was inadequate for detecting regional temporal trends, regardless of the number of sites sampled or the magnitude of the annual declines. Even when monitoring over a 20-year period, sampling a relatively large number of sites each year was required (e.g., > 50 sites) to achieve adequate statistical power for smaller trend magnitudes (declines of 5 – 7%/year). Annual sampling frequency had little impact on power for any monitoring scenario. All sampling scenarios were underpowered for sediment total PCBs. Power was greatest for total estrogenicity, suggesting that this aggregate measure of estrogenic activity may be a useful indicator. This study provides information that can be used to help (1) guide the development of monitoring programs aimed at detecting regional declines in riverine chemical contaminant concentrations in response to land management actions, and (2) set expectations for the ability to detect changes over time.","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2021.152435","usgsCitation":"Wagner, T., McLaughlin, P., Smalling, K., Breitmeyer, S.E., Gordon, S.E., and Noe, G.E., 2022, The statistical power to detect regional temporal trends in riverine contaminants in the Chesapeake Bay Watershed, USA: Science of the Total Environment, v. 812, 152435, 10 p., https://doi.org/10.1016/j.scitotenv.2021.152435.","productDescription":"152435, 10 p.","ipdsId":"IP-133554","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience 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units","interactions":[],"lastModifiedDate":"2021-11-16T13:07:12.267368","indexId":"70226171","displayToPublicDate":"2021-09-28T07:04:59","publicationYear":"2022","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":"Populations using public-supply groundwater in the conterminous U.S. 2010; Identifying the wells, hydrogeologic regions, and hydrogeologic mapping units","docAbstract":"Most Americans receive their drinking water from publicly supplied sources, a large portion of it from groundwater. Mapping these populations consistently and at a high resolution is important for understanding where the resource is used and needs to be protected. The results show that 269 million people are supplied by public supply, 107 million are supplied by groundwater and 162 million are supplied by surface water. The population using public supply drinking water was mapped in two ways: the census enhanced method (CEM) evenly distributes the population across populated census blocks, and the urban land-use enhanced method (ULUEM) distributes the population only to certain urban land use designations. In addition, a two-dimensional polygon dataset was created for the conterminous U.S. that identifies 177 unique Hydrogeologic Mapping Units (HMUs) with similar hydrogeologic characteristics. The HMUs do not overlap, but they can delineate areas where stacked hydrogeologic regions (HRs) contribute drinking water from below the surface. HRs are waterbearing geologic regions identified as either a principal aquifers (PA) or secondary hydrogeologic regions (SHR). Within each HMU, the wells were used to determine the proportion of each HR that is providing groundwater to the HMU. In 63% of the HMUs, a single HR is providing water to the public supply wells located within it, while the rest of the HMUs show that the wells are tapping up to a maximum of four stacked HRs. In total, groundwater from 108 HRs provide drinking water for public supply, six of which provide more than 50% of the groundwater used for public supply drinking water. The aquifer serving the largest number of equivalent people (>17 million) is the glacial aquifer. The HR providing the greatest number of people per km2 is the Biscayne aquifer in Florida at nearly 453 people per km2.
The Valmont TCE Superfund Site, Luzerne County, Pennsylvania is underlain by fractured and folded sandstones and shales of the Pottsville and Mauch Chunk Formations, which form a fractured-rock aquifer recharged locally by precipitation. Industrial activities at the former Chromatex Plant resulted in trichloroethene (TCE) contamination of groundwater at and near the facility, which was identified in 1987 and led to listing as a Superfund site by the U.S. Environmental Protection Agency (EPA) in 1989. To address the problem of TCE concentrations in nearby residential wells that exceed the maximum contaminant level (MCL) of 5 micrograms per liter (μg/L), alternate water supplies were provided. A 2015 review of initial characterization and subsequent remediation by the EPA identified the need for an updated understanding of the complex hydrogeology and the conceptual site model. Additional contaminants present in groundwater at the site include some other volatile organic compounds (VOCs) and per- and polyfluoroalkyl substances (PFAS), predominantly consisting of perfluorooctanoic acid (PFOA) and perfluorooctanesulfonic acid (PFOS) present in concentrations that exceeded the EPA Health Advisory (HA) level of 5 nanograms per liter (ng/L) for combined PFOA and PFOS.
In response to a request from the EPA in 2019, the U.S. Geological Survey (USGS) prepared cross sections and maps to provide more information about the hydrogeologic framework at and near the site and assist in improving the conceptual site model using water level and contaminant data collected by the EPA in 2020. The cross sections present lithologic correlations from available geophysical logs collected in wells from 2002 to 2014; they show alternating intervals of relatively elevated and reduced natural gamma activity that correspond to changes in lithology, with water-bearing zones and well screens commonly located at lithologic contacts, sometimes near thin coal seams. Water-bearing zones commonly are associated with fractures at or near lithologic contacts but also may be associated with fractures at or near apparent faulting. Recent (March 2020) water-level data shown on cross sections and maps indicate large downward vertical gradients and apparent radial gradients laterally to the northeast, northwest, and southwest that generally following topography. Recent (February to March 2020) data for TCE groundwater concentration shown on cross sections and maps indicate the highest TCE concentrations (greater than 3,000 μg/L and as much as 75,000 μg/L) and combined PFOA and PFOS concentrations (greater than 1,000 ng/L and up to at least 2,350 ng/L) are from shallow (less than 60 feet [ft] below land surface [bls]) and intermediate depth (60 to 100 ft bls) wells near the center of the former Chromatex Plant. TCE and PFAS (as combined PFOA and PFOS) contamination is present at greater depths, as much as 304 ft bls, as evidenced by samples collected from one well (a reconstructed former production well) near the plant, that contained concentrations of about 240 μg/L and 508 ng/L, respectively. The 2020 data also indicate that TCE and PFAS concentrations which exceed drinking-water MCL or HA levels are present in groundwater depths of less than 200 ft in an area that extends predominantly in a northeast direction from the former Chromatex Plant, and is apparently influenced by hydraulic gradients, lithology, and geologic structure.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211093","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Senior, L.A., Fiore, A.R., and Bird, P.H., 2021, Hydrogeologic framework, water levels, and selected contaminant concentrations at Valmont TCE Superfund Site, Luzerne County, Pennsylvania, 2020 (ver. 1.1, August 2022): U.S. Geological Survey Open-File Report 2021–1093, 80 p., https://doi.org/10.3133/ofr20211093.","productDescription":"Report: xii, 80 p.; 17 Plates: 17.00 x 11.00 inches or smaller","numberOfPages":"80","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-128502","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":501527,"rank":21,"type":{"id":36,"text":"NGMDB Index 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1.0: September 30, 2021; Version 1.1: August 9, 2022","contact":"Director, Pennsylvania Water Science Center
U.S. Geological Survey
215 Limekiln Road
New Cumberland, PA 17070-2424
Concerns related to perfluoroalkyl and polyfluoroalkyl substances (PFAS) in sources of drinking water and in natural and engineered environments have captured national attention over the last few decades. This report provides an overview of the science gaps that exist in the fields of study related to PFAS that are relevant to the U.S. Geological Survey mission and identifies opportunities where the U.S. Geological Survey can help address these gaps on the basis of the agency’s capabilities and expertise. The integrated science activities envisioned in this document can be designed to address science needs at local, regional, and national scales and varying timeframes as stakeholders are engaged and their needs evolve. This document is intended as an information resource for U.S. Geological Survey scientists who are prioritizing and planning research related to PFAS and may be useful for developing partnerships and collaborations with other scientists, agencies, and stakeholders.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1490","usgsCitation":"Tokranov, A.K., Bradley, P.M., Focazio, M.J., Kent, D.B., LeBlanc, D.R., McCoy, J.W., Smalling, K.L., Steevens, J.A., and Toccalino, P.L., 2021, Integrated science for the study of perfluoroalkyl and polyfluoroalkyl substances (PFAS) in the environment—A strategic science vision for the U.S. Geological Survey: U.S. Geological Survey Circular 1490, 50 p., https://doi.org/10.3133/cir1490.","productDescription":"v, 50 p.","numberOfPages":"50","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-120645","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":392952,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/circ/1490/coverthb.jpg"},{"id":392953,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1490/cir1490.pdf","text":"Report","size":"5.76 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Circular 1490"}],"contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
Saltwater intrusion and declining water levels have been a water-supply problem in Cape May County, New Jersey, for decades. Cape May County is surrounded by saltwater on three sides. Several communities in the county have only one aquifer from which freshwater withdrawals can be made, and that sole source is threatened by saltwater intrusion and (or) substantial declines in water levels caused by groundwater withdrawals. Growth of the year-round and summer tourism populations have caused water demand for some purveyors to approach the full-allocation withdrawal rates set by the New Jersey Department of Environmental Protection, leading these purveyors to request increases in allocations. Simulated water levels resulting from withdrawals including proposed increases in allocations by four purveyors and a shift of some withdrawals from one aquifer to another by a fifth purveyor were compared to simulated baseline water levels with withdrawals at 2012 full-allocation rates.
The Lower Township Scenario simulates proposed full-allocation withdrawals of 1,079 million gallons per year (Mgal/yr) from the Cohansey aquifer, 211 Mgal/yr (24 percent) higher than the 2012 full allocation withdrawals. Lower Township Scenario simulated water levels are between 2 and 4 feet (ft) lower than those of the shallow-aquifer-system Baseline Scenario simulation in much of Lower Township. The simulated 250-milligrams per liter (mg/L) isochlor is a maximum of 750 ft farther eastward than the simulated position in the shallow-aquifer-system Baseline Scenario, and the isochlor is simulated to be 700 ft from the northwestern-most Lower Township Municipal Utility Authority well at the airport in 2050.
The Wildwood Scenario simulates proposed full-allocation withdrawals of 388 Mgal/yr at the Wildwood Water Utility Rio Grande well field in Middle Township from the Rio Grande water-bearing zone (upper Kirkwood Formation) and 776 Mgal/yr from the Atlantic City 800-foot sand (lower Kirkwood Formation). Simulated water levels in the Atlantic City 800-foot sand near the well field are 30–55 ft lower than in the deep-aquifer-system Baseline Scenario, more than 15 ft lower south and west of Cape May Court House, and 5–10 ft lower between Cape May Court House and Woodbine and Upper Township.
The Avalon Scenario simulates proposed full-allocation withdrawals from the Atlantic City 800-foot sand in Avalon Borough of 495 Mgal/yr, which is 141 Mgal/yr (40 percent) higher than the 2012 full-allocation withdrawals. The Cape May Court House Scenario simulates proposed full-allocation withdrawals near Cape May Court House from the Atlantic City 800-foot sand of 495 Mgal/yr, which is 150 Mgal/yr (64 percent) higher than 2012 full-allocation withdrawals. The Strathmere Scenario simulates proposed full-allocation withdrawals in Strathmere from the Atlantic City 800-foot sand of 30 Mgal/yr, which is 11 Mgal/yr (58 percent) higher than 2012 full-allocation withdrawals. All three of these scenarios generally show simulated water levels to be less than 10 ft lower compared to the deep-aquifer-system Baseline Scenario.
The Combined Scenario simulates proposed full-allocation withdrawals, including increased withdrawals from the Atlantic City 800-foot sand in all four locations—the Rio Grande well field, Avalon, Cape May Court House, and Strathmere. Water levels from the Combined Scenario are 40–65 ft lower than those from the deep-aquifer-system Baseline Scenario near the Wildwood Water Utility Rio Grande well field, 15–40 ft lower south of Dennis Township, and 5–15 ft lower in much of the rest of Cape May County.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205052","collaboration":"Prepared in cooperation with the New Jersey Department of Environmental Protection","usgsCitation":"Carleton, G.B., 2021, Simulation of potential water allocation changes, Cape May County, New Jersey: U.S. Geological Survey Scientific Investigations Report 2020–5052, 39 p., https://doi.org/10.3133/sir20205052.","productDescription":"Report: vi, 39 p.; Data Release","numberOfPages":"39","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-044323","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":392461,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20205052/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":392262,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2020/5052/sir20205052.XML"},{"id":392260,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9KC1PGV","text":"USGS data release","linkHelpText":"SEAWAT, MODFLOW-2000, and SHARP models used to simulate potential water-allocation changes, Cape May County, New Jersey"},{"id":392261,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2020/5052/images/"},{"id":392259,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5052/sir20205052.pdf","text":"Report","size":"4.35 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5052"},{"id":392258,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5052/coverthb.jpg"}],"country":"United States","state":"New Jersey","county":"Cape May County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.99404907226562,\n 38.92843409820933\n ],\n [\n -74.91439819335938,\n 38.91133881927712\n ],\n [\n -74.82376098632812,\n 38.92629741358616\n ],\n [\n -74.77844238281249,\n 38.9807627650163\n ],\n [\n -74.74925994873047,\n 39.041319605445445\n ],\n [\n -74.95010375976561,\n 39.0882354732187\n ],\n [\n -74.99404907226562,\n 38.92843409820933\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New Jersey Water Science Center
U.S. Geological Survey
3450 Princeton Pike, Suite 110
Lawrenceville, NJ 08648
The U.S. Geological Survey (USGS) Water-Use Program is responsible for compiling and disseminating the Nation's water-use data. Working in cooperation with local, State, and Federal agencies, the USGS has collected and published national water-use estimates every 5 years, beginning in 1950. These water-use data may vary because of actual changes in water use, because of changes in estimation methods, or because of errors. Comparison and interpretation of these data is difficult without first determining the factors that contribute to data variability. This report describes factors that may affect data quality and documents ways to investigate the variability of public supply, self-supplied domestic, irrigation, and thermoelectric water-use data for the 1985–2015 compilations.
The USGS produces national water-use estimates for various categories of water use for every county in the United States. Knowledge about the sources of data for county estimates is important because factors such as estimation methodology and reporting affect data uncertainty Determination of meaningful patterns and trends in the data are contingent on the use of consistent methodology throughout the period of interest. With the many ways that water-use data have been collected, assembled, and estimated, multiple factors likely contribute to data uncertainty, Data used to produce these estimates may be furnished from agencies that collect information from entities who report water use; gaps in reported data are typically estimated to achieve a comprehensive county estimate. For example, public supply and thermoelectric category data are based primarily on furnished site-specific data; whereas crop irrigation is often furnished or estimated at the county scale. Public supply deliveries for domestic use and self-supplied domestic withdrawals are most often estimated by USGS personnel using per capita use rate coefficients. Irrigation may be estimated using crop water requirements, application rates, or other soil water balance methods when furnished reported data are not available.
Rates, percentages, medians, and interquartile ranges were used to investigate variability in the water-use data among States, regions, and years. The purposes of these evaluations were to (1) identify extreme values that may reflect changes in information sources, estimation methods, or errors; (2) indicate areas of variable or consistent values that are unexpected; and (3) indicate areas where values change because of local climate or other factors. Where factors are identified that contribute to data variability, such as a change in methodology, additional work could determine uncertainty because of these factors.
These evaluations identified the availability of information that is needed to address data limitations. Factors such as estimation methodology affect data quality. Some updates to method codes assigned in 2015 and assignment of method codes to earlier compilation datasets for all categories would provide much needed metadata for users of the data. Improvements in data documentation describing sources of information and estimation methods and additional metadata information from agencies and entities that furnish water-use data, would enable a more complete understanding and depiction of water-use patterns and trends. Additional metadata are needed for users of the data to better understand the water-use data and interpret changes in water use across the United States and with time.
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U.S. Geological Survey
5840 Enterprise Drive
Lansing, MI 48911
Per- and polyfluoroalkyl substances (PFAS) have been identified in two lakes near Joint Base McGuire-Dix-Lakehurst (JBMDL) in New Jersey—Little Pine Lake in Pemberton Township and Pine Lake in Manchester Township. The streams that enter these lakes begin in or near JBMDL where sources of PFAS contamination are located. The U.S. Geological Survey, in cooperation with the U.S. Air Force Civil Engineer Center, performed a study of the hydrogeology and the gaining or losing conditions associated with these lakes.
Hydrogeologic characteristics in the vicinity of both lakes were assessed using qualitative vertical hydraulic profiling of the subsurface. Groundwater was pumped from test intervals at various depths below land surface, then groundwater levels were measured until they recovered to static conditions. Low permeability aquifer intervals were identified within the aquifer underlying both lakes, consistent with silty and (or) clayey subunits of the Kirkwood-Cohansey aquifer system indicated on geophysical and lithologic logs.
Gaining or losing conditions between groundwater and lake surface water were assessed with continuous monitoring of water levels and temperature in the lakes and in three piezometers per lake screened at different depths in the underlying aquifer from August 2020 through May 2021. At Little Pine Lake, surface water levels were consistently lower than groundwater levels, which is indicative of a gaining condition with groundwater flowing into the lake. Gaining conditions also support the lack of diurnal temperature fluctuations observed in groundwater, but poor response of surface-water temperature prevents complete analysis. The potential for losing conditions at other locations around Little Pine Lake necessitates further assessment in regard to possible PFAS contamination of groundwater in the underlying aquifer. Temperature results were inconclusive at Pine Lake, but surface water levels were consistently higher than groundwater levels throughout the monitoring period, which indicates a losing condition with lake water flowing into the underlying aquifer. Because of the downward vertical hydraulic gradient identified at Pine Lake, there is a strong possibility that PFAS in the lake water has also contaminated groundwater in its vicinity.
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Lawrenceville, NJ 08648
A continuous-variable Bayesian network (cBN) model is used to link watershed development and climate change to stream ecosystem indicators. A graphical model, reflecting our understanding of the connections between climate change, weather condition, loss of natural land cover, stream flow characteristics, and stream ecosystem indicators is used as the basis for selecting flow metrics for predicting macroinvertebrate-based indicators. Selected flow metrics were then linked to variables representing watershed development and climate change. We fit the model to data from two river basins in southeast US and the resulting model was used to simulate future stream ecological conditions using projected future climate and development scenarios. The three climate models predicted varying ecological condition trajectories, but similar worst-case ecological conditions. The established modeling approach couples mechanistic understanding with field data to develop predictions of management-relevant variables across a heterogeneous landscape. We discussed the transferability of the modeling approach.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.watres.2021.117685","usgsCitation":"Qian, S.S., Kennen, J., May, J., Freeman, M., and Cuffney, T.F., 2021, Evaluating the impact of watershed development and climate change on stream ecosystems: A Bayesian network modeling approach: Water Research, v. 205, 117685, 11 p., https://doi.org/10.1016/j.watres.2021.117685.","productDescription":"117685, 11 p.","ipdsId":"IP-125255","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":450679,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.watres.2021.117685","text":"Publisher Index Page"},{"id":417645,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina, South Carolina, Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -79.52179800853753,\n 32.86310990611119\n ],\n [\n -78.95424437482033,\n 33.20732442214225\n ],\n [\n -78.83061042748197,\n 33.62402639579081\n ],\n [\n -78.03123021414571,\n 33.81848745598903\n ],\n [\n -77.49960057459164,\n 34.229007941502374\n ],\n [\n -77.20942075405912,\n 34.57053494448374\n ],\n [\n -78.04925882655441,\n 35.593623760054015\n ],\n [\n -79.61149509648914,\n 36.3847977489354\n ],\n [\n -80.69994996842892,\n 36.980415621762745\n ],\n [\n -81.2368093995407,\n 36.697683304342775\n ],\n [\n -81.66006417146134,\n 35.81807327161229\n ],\n [\n -80.92321025597303,\n 33.67553987083947\n ],\n [\n -80.06864524456462,\n 32.587876038945694\n ],\n [\n -79.52179800853753,\n 32.86310990611119\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"205","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Qian, Song S. 0000-0002-2346-4903","orcid":"https://orcid.org/0000-0002-2346-4903","contributorId":306033,"corporation":false,"usgs":false,"family":"Qian","given":"Song","email":"","middleInitial":"S.","affiliations":[{"id":62440,"text":"Department of Environmental Sciences, University of Toledo, Toledo, OH 43606","active":true,"usgs":false}],"preferred":false,"id":874463,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kennen, Jonathan G. 0000-0002-5426-4445 jgkennen@usgs.gov","orcid":"https://orcid.org/0000-0002-5426-4445","contributorId":574,"corporation":false,"usgs":true,"family":"Kennen","given":"Jonathan G.","email":"jgkennen@usgs.gov","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":874464,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"May, Jason 0000-0002-5699-2112","orcid":"https://orcid.org/0000-0002-5699-2112","contributorId":224991,"corporation":false,"usgs":false,"family":"May","given":"Jason","affiliations":[{"id":41015,"text":"Deceased (ex-USGS)","active":true,"usgs":false}],"preferred":false,"id":874465,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Freeman, Mary 0000-0001-7615-6923 mcfreeman@usgs.gov","orcid":"https://orcid.org/0000-0001-7615-6923","contributorId":3528,"corporation":false,"usgs":true,"family":"Freeman","given":"Mary","email":"mcfreeman@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":874466,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cuffney, Thomas F 0000-0003-1164-5560","orcid":"https://orcid.org/0000-0003-1164-5560","contributorId":306032,"corporation":false,"usgs":false,"family":"Cuffney","given":"Thomas","email":"","middleInitial":"F","affiliations":[],"preferred":false,"id":874467,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70224564,"text":"70224564 - 2021 - Assessing the ecological functionality and integrity of natural ponds, excavated ponds and stormwater basins for conserving amphibian diversity","interactions":[],"lastModifiedDate":"2021-09-28T12:39:50.555431","indexId":"70224564","displayToPublicDate":"2021-08-20T07:34:48","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3871,"text":"Global Ecology and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Assessing the ecological functionality and integrity of natural ponds, excavated ponds and stormwater basins for conserving amphibian diversity","docAbstract":"Wetlands provide ecological functionality by maintaining and promoting regional biodiversity supporting quality habitat for aquatic organisms. Globally, habitat loss, fragmentation and degradation due to increases in agricultural activities and urban development have reduced or altered geographically isolated wetlands, thus reducing biodiversity. The objective of this study was to assess the relative ecological function and integrity of natural ponds, excavated ponds and stormwater basins in the New Jersey Pinelands, located in the northeastern United States by comparing hydrologic conditions, water quality, pesticide concentrations (water, sediment and tissue) and wetland assemblages including amphibians. Twenty-four wetlands were selected based on surrounding land-use and sampled for a variety of abiotic and biotic variables. Abiotic and biotic wetland variables were similar between natural and excavated ponds, with notable differences between the ponds and stormwater basins. Natural and excavated ponds displayed characteristic Pinelands water quality (low pH, high organic carbon, and low pesticide concentrations), exhibited high ecological integrity and supported native ampbibians. Stormwater basins and degraded ponds surrounded by altered land-use exhibited degraded water quality (high pH, high pesticide concentrations) and were dominated by non-native and introduced plants and amphibians. Results from this study can broadly inform resource conservation strategies for amphibians and other communities with a diverse range of habitat requirements, particularly in areas where conservation and development are competing priorities. To conserve biodiversity in changing landscapes, wetlands with similar functionality and land-use characteristics need to be identified and managed to preserve water quality for species of conservation concern.
The Sandy Hook Unit, Gateway National Recreation Area (hereafter Sandy Hook) in New Jersey is a 10-kilometer-long spit visited by thousands of people each year who take advantage of the historical and natural resources and recreational opportunities. The historical and natural resources are threatened by global climate change, including sea-level rise (SLR), changes in precipitation and groundwater recharge, and changes in the frequency and severity of coastal storms. Fresh groundwater resources are important to the ecosystems of Sandy Hook. The Bayside Holly Forest, one of only two known old-growth American holly (Ilex opaca) maritime forests, is particularly vulnerable to global climate change because of the proximity of the water table to land surface in low-lying areas and the potential for saltwater intrusion and inundation.
The shallow groundwater-flow system on Sandy Hook is dominated by recharge from precipitation, fresh groundwater discharge to evapotranspiration (ET), discharge to surface seeps, and submarine groundwater discharge (groundwater discharging directly to the ocean). A three-dimensional groundwater-flow model that simulates the shallow groundwater-flow system and interaction with surrounding saltwater boundaries was constructed to simulate multi-density groundwater flow, treating the freshwater/saltwater transition zone as a sharp interface that represents the half-seawater surface.
Groundwater-flow simulations completed for this study include a Baseline scenario, three SLR scenarios (0.2, 0.4, and 0.6 meter [m]), two Recharge scenarios—a 10-percent Increased Recharge scenario and a 10-percent Decreased Recharge scenario—and a scenario with 0.6 m of SLR and 10-percent increase in recharge. The Recharge scenarios indicate the system is not sensitive to a 10-percent increase or decrease in recharge from the Baseline scenario. In the SLR scenarios, SLR causes the water table to rise, resulting in increased fresh groundwater discharge to ET and seeps, and reduced submarine discharge compared to the Baseline scenario. The increased discharge to ET and seeps causes the magnitude of water-table rise to be less than that of SLR, which in turn causes the thickness of the freshwater lens to thin, reducing the depth to the half-seawater surface. Water-table rise associated with SLR diminishes the thickness of the unsaturated zone; comparing the Baseline and the 0.6-m SLR scenarios, the area where the simulated water table is above land surface increases by 50.6 hectares, from about 0.9 to 7.4 percent of the land area of Sandy Hook. Areas where the simulated water table is above land surface are likely to be emergent wetlands and contain freshwater if they are tens of meters or more from the shoreline. The steady-state simulations indicate that the percentage of land where the half-seawater surface is less than 9 m below the water table increases from about 2.5 percent (20 hectares) to about 9 percent (74 hectares) with 0.6 m of SLR. In low-lying areas close to the Sandy Hook Bay shoreline, the half-seawater surface is simulated to be as much as 20 m closer to the water table with SLR of 0.6 m. Transient salinization, if any, of shallow groundwater from increased frequency or severity of storm-driven inundation is not included in the analysis.
Natural resources on Sandy Hook, particularly the Bayside Holly Forest, may be adversely affected by the rising water table associated with SLR. Freshwater emergent wetlands may increase in area at the expense of other ecosystem assemblages occurring in or on the edges of low-lying enclosed depressions. Cultural resources close to the water table, such as existing basements of structures, may be adversely affected.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205080","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Carleton, G.B., Charles, E.G., Fiore, A.R., and Winston, R.B., 2021, Simulation of water-table response to sea-level rise and change in recharge, Sandy Hook unit, Gateway National Recreation Area, New Jersey: U.S. Geological Survey Scientific Investigations Report 2020–5080, 91 p., https://doi.org/10.3133/sir20205080.","productDescription":"Report: ix, 91 p.; Data Release","numberOfPages":"91","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-081081","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":387036,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20205117","text":"Scientific Investigations Report 2020–5117","linkHelpText":"- Simulation of Water-Table and Freshwater/Saltwater Interface Response to Climate-Change-Driven Sea-Level Rise and Changes in Recharge at Fire Island National Seashore, New York"},{"id":387037,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20205104","text":"Scientific Investigations Report 2020–5104","linkHelpText":"- Simulated Effects of Sea-Level Rise on the Shallow, Fresh Groundwater System of Assateague Island, Maryland and Virginia"},{"id":387032,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7BP018M","text":"USGS data release","linkHelpText":"MODFLOW-2005 with SWI2 used to evaluate the water-table response to sea-level rise and change in recharge, Sandy Hook Unit, Gateway National Recreation Area, New Jersey"},{"id":387033,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5080/coverthb.jpg"},{"id":387034,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5080/sir20205080.pdf","text":"Report","size":"19.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5080"}],"country":"United States","state":"New Jersey","otherGeospatial":"Gateway National Recreation Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.04716491699219,\n 40.39467254512293\n ],\n [\n -73.95927429199219,\n 40.39467254512293\n ],\n [\n -73.95927429199219,\n 40.49239284038429\n ],\n [\n -74.04716491699219,\n 40.49239284038429\n ],\n [\n -74.04716491699219,\n 40.39467254512293\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New Jersey Water Science Center
U.S. Geological Survey
3450 Princeton Pike
Lawrenceville, NJ 08648