Reduction in point sources of nitrogen has led to improvement in water quality of the Long Island Sound (LIS) since 2000, but changes in nonpoint sources are less clear. A significant yet poorly quantified nonpoint nitrogen source is the forested landscape. Because a large proportion of the LIS basin is forested, even small areal inputs from the forested landscape have a large cumulative effect on nitrogen loading to LIS. Atmospheric nitrogen deposition, the primary source of nitrogen to forested landscapes in LIS basin, has been declining for several decades. However, nitrogen export in streams does not necessarily mirror nitrogen deposition. To assess forest nitrogen export to LIS, we estimated annual average concentrations and fluxes of nitrate in 17 forested watersheds in and near the LIS basin. Average flow-normalized nitrate-nitrogen concentrations ranged from less than 0.05–0.43 mg per liter among all sites; annual flow-normalized yields ranged from 0.45 to 4.3 kg per hectare. Flow-normalized annual average concentrations and yields of nitrate between water years 1991–2021 did not monotonically increase or decrease at most watersheds. Where determined, the other major N species generally had comparable magnitude and trends. Based on the watersheds analyzed in this study, forested areas are not responding uniformly to the continued decline of atmospheric nitrogen deposition. The variability among sites may indicate that local-scale factors exert substantial influence over the magnitude and trends in nitrogen exports. One watershed that had increasing development showed an increasing trend in nitrate, but not in dissolved organic nitrogen.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2024JG008489","usgsCitation":"Spaetzel, A.B., Shanley, J.B., DeSimone, L.A., and Mullaney, J., 2025, Nitrate loads and concentrations from forested watersheds and implications for Long Island Sound: JGR Biogeosciences, v. 130, no. 4, e2024JG008489, 18 p., https://doi.org/10.1029/2024JG008489.","productDescription":"e2024JG008489, 18 p.","ipdsId":"IP-154905","costCenters":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":468,"text":"New Hampshire-Vermont Water Science Center","active":false,"usgs":true}],"links":[{"id":488666,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2024jg008489","text":"Publisher Index Page"},{"id":484067,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Connecticut, Massachusetts, New Hampshire, New York, Rhode Island, Vermont","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -71.28768451934559,\n 45.13511639993237\n ],\n [\n -75.10160526272159,\n 44.91381753996643\n ],\n [\n -74.79160802274902,\n 41.44157777621251\n ],\n [\n -73.57410086622542,\n 40.77932738343219\n ],\n [\n -71.39984137658877,\n 41.12239972907295\n ],\n [\n -71.28768451934559,\n 45.13511639993237\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"130","issue":"4","noUsgsAuthors":false,"publicationDate":"2025-03-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Spaetzel, Alana B. 0000-0002-9871-812X","orcid":"https://orcid.org/0000-0002-9871-812X","contributorId":240935,"corporation":false,"usgs":true,"family":"Spaetzel","given":"Alana","email":"","middleInitial":"B.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":932447,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shanley, James B. 0000-0002-4234-3437 jshanley@usgs.gov","orcid":"https://orcid.org/0000-0002-4234-3437","contributorId":1953,"corporation":false,"usgs":true,"family":"Shanley","given":"James","email":"jshanley@usgs.gov","middleInitial":"B.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":932448,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DeSimone, Leslie A. 0000-0003-0774-9607 ldesimon@usgs.gov","orcid":"https://orcid.org/0000-0003-0774-9607","contributorId":195635,"corporation":false,"usgs":true,"family":"DeSimone","given":"Leslie","email":"ldesimon@usgs.gov","middleInitial":"A.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"preferred":true,"id":932449,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mullaney, John R. 0000-0003-4936-5046","orcid":"https://orcid.org/0000-0003-4936-5046","contributorId":203254,"corporation":false,"usgs":true,"family":"Mullaney","given":"John R.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":932450,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70227357,"text":"70227357 - 2022 - Mapped predictions of manganese and arsenic in an alluvial aquifer using boosted regression trees","interactions":[],"lastModifiedDate":"2022-05-13T14:36:19.096668","indexId":"70227357","displayToPublicDate":"2021-12-24T07:09:15","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3825,"text":"Groundwater","active":true,"publicationSubtype":{"id":10}},"title":"Mapped predictions of manganese and arsenic in an alluvial aquifer using boosted regression trees","docAbstract":"Manganese (Mn) concentrations and the probability of arsenic (As) exceeding the drinking-water standard of 10 μg/L were predicted in the Mississippi River Valley alluvial aquifer (MRVA) using boosted regression trees (BRT). BRT, a type of ensemble-tree machine-learning model, were created using predictor variables that affect Mn and As distribution in groundwater. These variables included iron (Fe) concentrations and specific conductance predicted from previously developed BRT models, groundwater flux and age estimates from MODFLOW, and hydrologic characteristics. The models also included results from the first airborne geophysical survey conducted in the United States to target an entire aquifer system. Predictions of high Mn and As occurred where Fe was high. Predicted high Mn concentrations were correlated with fraction of young groundwater (less than 65 years) computed from MODFLOW results. High probabilities of As exceedance were predicted where groundwater was relatively old and airborne electromagnetic resistivity was high, typically proximal to streams. Two-variable partial-dependence plots and sensitivity analysis were used to provide insight into the factors controlling Mn and As distribution in groundwater. The maps of predicted Mn concentrations and As exceedance probabilities can be used to identify areas where these constituents may be high, and that could be targeted for further study. This paper shows that incorporation of a selected set of process-informed data, such as MODFLOW results and airborne geophysics, into a machine-learning model improves model interpretability. Incorporation of process-rich information into machine-learning models will likely be useful for addressing a wide range of problems of interest to groundwater hydrologists.
We present a geostatistics-based stochastic salinity estimation framework for the Montebello Oil Field that capitalizes on available total dissolved solids (TDS) data from groundwater samples as well as electrical resistivity (ER) data from borehole logging. Data from TDS samples (n = 4924) was coded into an indicator framework based on falling below four selected thresholds (500, 1000, 3000, and 10,000 mg/L). Collocated TDS-ER data from the surrounding groundwater basin were then employed to produce a kernel density estimator to establish conditional probabilities for ER data (n = 8 boreholes) falling below the selected TDS thresholds within the Montebello Oil Field area. Directional variograms were estimated from these indicator coded data, and 500 TDS realizations from conditional indicator simulation were generated for the subsurface region above the Montebello Oil Field reservoir. Simulations were summarized as 3D maps of median TDS, most likely salinity class, and probability for exceeding each of the specified TDS thresholds. Results suggested TDS was below 500 mg/L in most of the study area, with a trend toward higher values (500 to 1000 mg/L) to the southwest; consistent with the average regional groundwater flow direction. Discrete localized zones of TDS greater than 1000 mg/L were observed, with one of these zones in the greater than 10,000 mg/L range; however, these areas were not prevalent. The probabilistic approach used here is adaptable and is readily modified to include additional data and types and can be employed in time-lapse salinity modeling through Bayesian updating.
A random forest regression (RFR) model was applied to over 12,000 wells with measured fluoride (F) concentrations in untreated groundwater to predict F concentrations at depths used for domestic and public supply in basin-fill aquifers of the western United States. The model relied on twenty-two regional-scale environmental and surficial predictor variables selected to represent factors known to control F concentrations in groundwater. The testing model fit R2 and RMSE were 0.52 and 0.78 mg/L. Comparisons of measured to predicted proportions of four F-concentrations categories (<0.7 mg/L, 0.7–2 mg/L, >2 mg/L – 4 mg/L, and > 4 mg/L) indicate that the model performed well at making regional-scale predictions. Differences between measured and predicted proportions indicate underprediction of measured F at values by between 4 and 20 mg/L, representing less than 1% of the regional scale predicted values. These residuals most often map to geographic regions where local-scale processes including evaporative discharge in closed basins or intermittent streams concentrate fluoride in shallow groundwater. Despite this, the RFR model provides spatially continuous F predictions across the basin-fill aquifers where discrete samples are missing. Further, the predictions capture documented areas that exceed the F maximum contaminant level for drinking water of 4 mg/L and areas that are below the oral-health benchmark of 0.7 mg/L. These predictions can be used to estimate fluoride concentrations in unmonitored areas and to aid in identifying geographic areas that may require further investigation at localized scales.
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.
Study region: The study was conducted in the Northern Atlantic Coastal Plain aquifer system, eastern USA, an important water supply in a densely populated region.
Study focus: Manganese (Mn), an emerging health concern and common nuisance contaminant in drinking water, is mapped and modeled using the XGBoost machine learning method, predictions of pH and redox conditions from previous models, and other explanatory variables that describe the groundwater flow system and surface characteristics. Methods to address the imbalanced occurrence of elevated and low Mn concentrations are compared and used to more accurately predict concentrations of interest for human health and drinking water quality.
New hydrological insights for the region: Elevated Mn concentrations were more likely in shallow groundwater, close to recharge areas and in topographically low areas where soil or unsaturated processes influence groundwater quality. Predicted concentrations greater than the health threshold of 300 micrograms per liter extended across 17 % of the surficial aquifer area, but across <1% of the areas of underlying aquifers. pH and variables related to flow-system position and near-surface processes were more important predictors than the probability of low dissolved oxygen (DO). Mapped variable influence (SHAP values) showed that both pH and DO variables were related to hydrogeologic conditions. Class weights, which improved the predictive ability for elevated Mn without altering the data, was the preferred method to address class imbalance.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ejrh.2021.100925","usgsCitation":"DeSimone, L.A., and Ransom, K.M., 2021, Manganese in the Northern Atlantic Coastal Plain aquifer system, eastern USA—Modeling regional occurrence with pH, redox, and machine learning: Journal of Hydrology: Regional Studies, v. 37, 100925, 20 p., https://doi.org/10.1016/j.ejrh.2021.100925.","productDescription":"100925, 20 p.","ipdsId":"IP-126500","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":37273,"text":"Advanced Research Computing (ARC)","active":true,"usgs":true}],"links":[{"id":450397,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ejrh.2021.100925","text":"Publisher Index Page"},{"id":436146,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9M64CD1","text":"USGS data release","linkHelpText":"Data used to model and map manganese in the Northern Atlantic Coastal Plain aquifer system, eastern USA"},{"id":390662,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.er.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland, New Jersey, New York, North Carolina, Pennsylvania, Virginia","city":"Baltimore, New York, Philadelphia, Richmond, Washington D.C.","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -72.1142578125,\n 41.22824901518529\n ],\n [\n -73.63037109375,\n 40.94671366508002\n ],\n [\n -75.816650390625,\n 39.78321267821705\n ],\n [\n -78.321533203125,\n 38.30718056188316\n ],\n [\n -78.079833984375,\n 35.200744801724014\n ],\n [\n -77.069091796875,\n 35.06597313798418\n ],\n [\n -76.80541992187499,\n 34.94899072578227\n ],\n [\n -76.475830078125,\n 35.092945313732635\n ],\n [\n -76.387939453125,\n 35.34425514918409\n ],\n [\n -76.036376953125,\n 35.29943548054545\n ],\n [\n -75.509033203125,\n 35.84453450421662\n ],\n [\n -75.882568359375,\n 36.43012234551576\n ],\n [\n -75.904541015625,\n 37.055177106660814\n ],\n [\n -75.860595703125,\n 37.28279464911045\n ],\n [\n -75.201416015625,\n 38.07404145941957\n ],\n [\n -74.893798828125,\n 38.496593518947584\n ],\n [\n -75.289306640625,\n 39.16414104768742\n ],\n [\n -74.94873046875,\n 39.138581990583525\n ],\n [\n -75.069580078125,\n 38.976492485539396\n ],\n [\n -74.87182617187499,\n 38.865374851611634\n ],\n [\n -74.124755859375,\n 39.715638134796336\n ],\n [\n -73.883056640625,\n 40.38839687388361\n ],\n [\n -74.058837890625,\n 40.50544628405211\n ],\n [\n -71.74072265625,\n 40.98819156349393\n ],\n [\n -72.1142578125,\n 41.22824901518529\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"37","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"DeSimone, Leslie A. 0000-0003-0774-9607 ldesimon@usgs.gov","orcid":"https://orcid.org/0000-0003-0774-9607","contributorId":195635,"corporation":false,"usgs":true,"family":"DeSimone","given":"Leslie","email":"ldesimon@usgs.gov","middleInitial":"A.","affiliations":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":825412,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ransom, Katherine Marie 0000-0001-6195-7699","orcid":"https://orcid.org/0000-0001-6195-7699","contributorId":239552,"corporation":false,"usgs":true,"family":"Ransom","given":"Katherine","email":"","middleInitial":"Marie","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":825413,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70204915,"text":"sir20195090 - 2019 - Tritium as an indicator of modern, mixed, and premodern groundwater age","interactions":[],"lastModifiedDate":"2019-09-05T09:14:28","indexId":"sir20195090","displayToPublicDate":"2019-09-05T10:00:00","publicationYear":"2019","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":"2019-5090","title":"Tritium as an indicator of modern, mixed, and premodern groundwater age","docAbstract":"Categorical classification of groundwater age is often used for the assessment and understanding of groundwater resources. This report presents a tritium-based age classification system for the conterminous United States based on tritium (3H) thresholds that vary in space and time: modern (recharged in 1953 or later), if the measured value is larger than an upper threshold; premodern (recharged prior to 1953) if the measured value is smaller than a lower threshold; or mixed if the measured value is between the two thresholds. Inclusion of spatially varying thresholds, rather than a single threshold, accounts for the observed systematic variation in 3H deposition across the United States. Inclusion of time-varying thresholds, rather than a single threshold, accounts for the date of sampling given the radioactive decay of 3H.
The efficacy of the tritium-based age classification system was evaluated at national and regional scales. The system was evaluated at a national scale by classifying samples from 1,788 public-supply wells distributed across 19 principal aquifers and comparing those results with expectations based on hydrogeologic principles. The regional-scale data are from five paired networks of shallow and deep wells (287 wells). As expected, modern groundwater is more prevalent in shallow wells than in deeper wells, in fractured-rock and carbonate aquifers as compared to clastic aquifers, in unconfined areas as compared to confined areas, and in humid climates as compared to arid climates. The results from a tritium-based age classification system compared favorably with the results of 14 previous studies of groundwater ages that used different age tracers and analytical methods. The wells and samples from the Cambrian-Ordovician aquifer that had been analyzed using a more complex multi-tracer analysis were also analyzed using the tritium-based age classification system, and there was a close match between the two methods. The results from these various studies suggest that the tritium-based age classification system may be informative as a screening tool prior to selecting more expensive and complex age-dating tracers and methods, or to provide an explanatory variable for other water-quality data where more complex methods or tracers are not available.
This work improves on previous groundwater age classification using 3H by developing methods that (1) determine 3H thresholds for groundwater recharged in 1953 or later that minimize the misclassification of modern samples as mixed; (2) determine a pre-1953 threshold to estimate premodern background concentrations; and (3) add a mixed category to classify samples that are clearly neither entirely modern nor entirely premodern. As with any tritium-based approach, it can fail when the 3H record in precipitation does not accurately reflect the record of 3H in recharge
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/sir20195090","usgsCitation":"Lindsey, B.D., Jurgens, B.C., and Belitz, K., 2019, Tritium as an indicator of modern, mixed, and premodern groundwater age: U.S. Geological Survey Scientific Investigations Report 2019–5090, 18 p., https://doi.org/10.3133/sir20195090.","productDescription":"vii, 18 p.","onlineOnly":"Y","ipdsId":"IP-097386","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes 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U.S. Geological Survey
2201 Sunrise Valley Drive, MS 413
Reston, VA 20192-0002
Wastewater disposal associated with rapid population growth and development on Cape Cod, Massachusetts, during the past several decades has resulted in widespread contamination of groundwater with nitrogen. As a result, water quality in many of the streams, lakes, and coastal embayments on Cape Cod is impaired by excess nitrogen. To reduce nitrogen loads to these impaired water bodies, watershed-based planning is currently [2019] underway following a regional strategy, the section 208 areawide water-quality management plan update for Cape Cod. In the updated plan, traditional (sewering) and alternative wastewater management options are under consideration for restoring water quality in impaired surface-water bodies. Permeable reactive barriers, which are reactive zones emplaced below the water table for passive treatment of groundwater contaminants, are one of the alternatives being considered by Cape Cod towns as a potentially cost-effective technology for the removal of nitrogen from groundwater. However, the effectiveness of permeable reactive barriers depends on local conditions, and site-specific hydrologic and water-quality data are needed to inform the decision to install a permeable reactive barrier in a given location. These data are not available in most locations on Cape Cod; consequently, site assessments are needed before selecting this treatment option.
To address this need, the U.S. Environmental Protection Agency, U.S. Geological Survey, and Cape Cod Commission formed a technical team in 2015 to develop and evaluate a hydrologic site-assessment approach for permeable reactive barrier installation. The approach developed by the technical team includes a preliminary regional assessment followed by a phased onsite investigation. The approach was intended to provide the hydrologic data needed to make informed decisions on site suitability and to support installation and monitoring should the site be deemed appropriate for a permeable reactive barrier. The factors that were evaluated to characterize local hydrologic conditions and inform site selection included groundwater flow directions and rates, depth to the water table, hydraulic conductivity and degree of heterogeneity of the aquifer, spatial distribution and concentration of nitrate and oxidation-reduction-sensitive constituents, thickness and depth of the treatment zone, distance to downgradient water bodies, and access for drilling and permeable reactive barrier installation. The approach was demonstrated on Cape Cod by conducting a preliminary assessment of 27 sites, from which 5 sites were selected for onsite investigations. Results indicated that the site-assessment approach was successful for screening sites and characterizing the geologic, hydrologic, and water-quality conditions at the sites selected for onsite investigations. Overall, the phased assessment evaluated in this study provided an efficient means of obtaining the hydrologic information needed to determine if a site was suitable for permeable reactive barrier installation on Cape Cod for the passive treatment of nitrogen in groundwater.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195047","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Barbaro, J.R., Belaval, M., Truslow, D.B., LeBlanc, D.R., Cambareri, T.C., and Michaud, S.C., 2019, Hydrologic site assessment for passive treatment of groundwater nitrogen with permeable reactive barriers, Cape Cod, Massachusetts: U.S. Geological Survey Scientific Investigations Report 2019–5047, 39 p., https://doi.org/10.3133/sir20195047.","productDescription":"viii, 39 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-104222","costCenters":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":365261,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5047/coverthb.jpg"},{"id":365262,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5047/sir20195047.pdf","text":"Report","size":"2.58 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019-5047"}],"country":"United States","state":"Massachusetts","otherGeospatial":"Cape Cod","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -70.24932861328125,\n 42.06356771883277\n ],\n [\n -70.2081298828125,\n 42.02481360781777\n ],\n [\n -70.1806640625,\n 42.01665183556825\n ],\n [\n -70.16693115234375,\n 42.032974332441405\n ],\n [\n -70.18890380859375,\n 42.04317376494972\n ],\n [\n -70.16143798828125,\n 42.06356771883277\n ],\n [\n -70.11199951171875,\n 42.04113400940807\n ],\n [\n -70.07904052734375,\n 41.92475971933975\n ],\n [\n -70.0653076171875,\n 41.89818843043047\n ],\n [\n -70.0543212890625,\n 41.920672548686824\n ],\n [\n -70.02960205078125,\n 41.92271616673922\n ],\n [\n -70.0213623046875,\n 41.887965758804484\n ],\n [\n -70.00762939453125,\n 41.81021999190292\n ],\n [\n -70.07080078125,\n 41.777456667491066\n ],\n [\n -70.125732421875,\n 41.76106872528616\n ],\n [\n -70.16693115234375,\n 41.75492216766298\n ],\n [\n -70.20263671875,\n 41.748775021355044\n ],\n [\n -70.257568359375,\n 41.7180304600481\n ],\n [\n -70.279541015625,\n 41.72828028223453\n ],\n [\n -70.345458984375,\n 41.74262728637672\n ],\n [\n -70.44158935546875,\n 41.75287318430239\n ],\n [\n -70.49102783203125,\n 41.77336007442076\n ],\n [\n -70.55145263671875,\n 41.775408403663285\n ],\n [\n -70.587158203125,\n 41.748775021355044\n ],\n [\n -70.6201171875,\n 41.73647896274239\n ],\n [\n -70.65582275390625,\n 41.68316883525891\n ],\n [\n -70.6475830078125,\n 41.64213096472801\n ],\n [\n -70.653076171875,\n 41.60312076451184\n ],\n [\n -70.64208984375,\n 41.57436130598913\n ],\n [\n -70.78765869140625,\n 41.47771800887871\n ],\n [\n -70.94146728515625,\n 41.42625319507269\n ],\n [\n -70.94970703125,\n 41.409775832009565\n ],\n [\n -70.86181640625,\n 41.41801503608024\n ],\n [\n -70.784912109375,\n 41.4509614012039\n ],\n [\n -70.653076171875,\n 41.51680395810118\n ],\n [\n -70.6201171875,\n 41.541477666790286\n ],\n [\n -70.5487060546875,\n 41.53531012183376\n ],\n [\n -70.48828125,\n 41.54764462357737\n ],\n [\n -70.4443359375,\n 41.588742636696765\n ],\n [\n -70.43060302734375,\n 41.60517452129933\n ],\n [\n -70.39764404296875,\n 41.60722821271717\n ],\n [\n -70.367431640625,\n 41.61749568924243\n ],\n [\n -70.3125,\n 41.6257084937525\n ],\n [\n -70.26580810546875,\n 41.60928183876483\n ],\n [\n -70.24108886718749,\n 41.6257084937525\n ],\n [\n -70.17791748046875,\n 41.65239288426814\n ],\n [\n -70.13946533203124,\n 41.65034063112266\n ],\n [\n -70.06805419921875,\n 41.66470503009207\n ],\n [\n -70.015869140625,\n 41.668808555620586\n ],\n [\n -69.98016357421875,\n 41.65239288426814\n ],\n [\n -70.0103759765625,\n 41.566141964768384\n ],\n [\n -70.0103759765625,\n 41.539421883822854\n ],\n [\n -69.9884033203125,\n 41.54764462357737\n ],\n [\n -69.98016357421875,\n 41.59490508367679\n ],\n [\n -69.92523193359375,\n 41.68316883525891\n ],\n [\n -69.93072509765625,\n 41.81431422987254\n ],\n [\n -69.97467041015625,\n 41.94927724511655\n ],\n [\n -70.048828125,\n 42.039094188385945\n ],\n [\n -70.13397216796875,\n 42.07783959017503\n ],\n [\n -70.21087646484375,\n 42.08803181932636\n ],\n [\n -70.24932861328125,\n 42.06356771883277\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
331 Commerce Road, Suite 2
Pembroke, NH 03275-3718
Water samples from 50 domestic wells located <1 km (proximal) and >1 km (distal) from shale-gas wells in upland areas of the Marcellus Shale region were analyzed for chemical, isotopic, and groundwater-age tracers. Uplands were targeted because natural mixing with brine and hydrocarbons from deep formations is less common in those areas compared to valleys. CH4-isotope, predrill CH4-concentration, and other data indicate that one proximal sample (5% of proximal samples) contains thermogenic CH4 (2.6 mg/L) from a relatively shallow source (Catskill/Lock Haven Formations) that appears to have been mobilized by shale-gas production activities. Another proximal sample contains five other volatile hydrocarbons (0.03–0.4 μg/L), including benzene, more hydrocarbons than in any other sample. Modeled groundwater-age distributions, calibrated to 3H, SF6, and 14C concentrations, indicate that water in that sample recharged prior to shale-gas development, suggesting that land-surface releases associated with shale-gas production were not the source of those hydrocarbons, although subsurface leakage from a nearby gas well directly into the groundwater cannot be ruled out. Age distributions in the samples span ∼20 to >10000 years and have implications for relating occurrences of hydrocarbons in groundwater to land-surface releases associated with recent shale-gas production and for the time required to flush contaminants from the system.
","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.9b01440","usgsCitation":"McMahon, P.B., Lindsey, B.D., Conlon, M.D., Hunt, A.G., Belitz, K., Jurgens, B., and Varela, B.A., 2019, Hydrocarbons in upland groundwater, Marcellus Shale Region, Northeastern Pennsylvania and Southern New York, USA: Environmental Science & Technology, v. 53, no. 14, p. 8027-8035, https://doi.org/10.1021/acs.est.9b01440.","productDescription":"9 p.","startPage":"8027","endPage":"8035","ipdsId":"IP-104959","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true},{"id":5078,"text":"Southwest Regional Director's Office","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"links":[{"id":437401,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93M7JCD","text":"USGS data release","linkHelpText":"Data Release for Hydrocarbons in Upland Groundwater, Marcellus Shale Region, Northeastern Pennsylvania and Southern New York, USA"},{"id":365631,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York, Pennsylvania","volume":" 53","issue":"14","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-06-27","publicationStatus":"PW","contributors":{"authors":[{"text":"McMahon, Peter B. 0000-0001-7452-2379 pmcmahon@usgs.gov","orcid":"https://orcid.org/0000-0001-7452-2379","contributorId":724,"corporation":false,"usgs":true,"family":"McMahon","given":"Peter","email":"pmcmahon@usgs.gov","middleInitial":"B.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":766203,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lindsey, Bruce D. 0000-0002-7180-4319 blindsey@usgs.gov","orcid":"https://orcid.org/0000-0002-7180-4319","contributorId":175346,"corporation":false,"usgs":true,"family":"Lindsey","given":"Bruce","email":"blindsey@usgs.gov","middleInitial":"D.","affiliations":[{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":766204,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Conlon, Matthew D. 0000-0001-8266-9610 mconlon@usgs.gov","orcid":"https://orcid.org/0000-0001-8266-9610","contributorId":201291,"corporation":false,"usgs":true,"family":"Conlon","given":"Matthew","email":"mconlon@usgs.gov","middleInitial":"D.","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":766205,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hunt, Andrew G. 0000-0002-3810-8610 ahunt@usgs.gov","orcid":"https://orcid.org/0000-0002-3810-8610","contributorId":1582,"corporation":false,"usgs":true,"family":"Hunt","given":"Andrew","email":"ahunt@usgs.gov","middleInitial":"G.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":766206,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Belitz, Kenneth 0000-0003-4481-2345","orcid":"https://orcid.org/0000-0003-4481-2345","contributorId":201889,"corporation":false,"usgs":true,"family":"Belitz","given":"Kenneth","affiliations":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":true,"id":766207,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jurgens, Bryant C. 0000-0002-1572-113X","orcid":"https://orcid.org/0000-0002-1572-113X","contributorId":203409,"corporation":false,"usgs":true,"family":"Jurgens","given":"Bryant","middleInitial":"C.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":766208,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Varela, Brian A. 0000-0001-9849-6742 bvarela@usgs.gov","orcid":"https://orcid.org/0000-0001-9849-6742","contributorId":178091,"corporation":false,"usgs":true,"family":"Varela","given":"Brian","email":"bvarela@usgs.gov","middleInitial":"A.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":766209,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70204697,"text":"70204697 - 2019 - Estimating domestic well locations and populations served in the contiguous U.S. for years 2000 and 2010","interactions":[],"lastModifiedDate":"2019-08-09T12:10:34","indexId":"70204697","displayToPublicDate":"2019-06-06T12:02:38","publicationYear":"2019","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":"Estimating domestic well locations and populations served in the contiguous U.S. for years 2000 and 2010","docAbstract":"Domestic wells provide drinking water supply for approximately 40 million people in the United States. Knowing the location of these wells, and the populations they serve, is important for identifying heavily used aquifers, locations susceptible to contamination, and populations potentially impacted by poor-quality groundwater. The 1990 census was the last nationally consistent survey of a home’s source of water, and has not been surveyed since. This paper presents a method for projecting the population dependent on domestic wells for years after 1990, using information from the 1990 census along with population data from subsequent censuses. The method is based on the “domestic ratio” at the census block-group level, defined here as the number of households dependent on domestic wells divided by the total population. Analysis of 1990 data (>220,000 block-groups) indicates that the domestic ratio is a function of the household density. As household density increases, the domestic ratio decreases, once a household density threshold is met. The 1990 data were used to develop a relationship between household density and the domestic ratio. The fitted model, along with household density data from 2000 and 2010, was used to estimate domestic ratios for each decadal year. In turn, the number of households dependent on domestic wells was estimated at the block-group level for 2000 and 2010. High-resolution census-block population data were used to refine the spatial distribution of domestic-well usage and to convert the data into population numbers. The results are presented in two downloadable raster datasets for each decadal year. It is estimated that the total population using domestic-well water in the contiguous U.S. increased 1.5% from 1990 to 2000 to a total of 37.25 million people and increased slightly from 2000 to 2010 to 37.29 million people.","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2019.06.036","usgsCitation":"Johnson, T., Belitz, K., and Lombard, M.A., 2019, Estimating domestic well locations and populations served in the contiguous U.S. for years 2000 and 2010: Science of the Total Environment, v. 687, p. 1261-1273, https://doi.org/10.1016/j.scitotenv.2019.06.036.","productDescription":"13 p.","startPage":"1261","endPage":"1273","ipdsId":"IP-101767","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":466,"text":"New England Water Science 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0000-0003-4481-2345","orcid":"https://orcid.org/0000-0003-4481-2345","contributorId":201889,"corporation":false,"usgs":true,"family":"Belitz","given":"Kenneth","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":true,"id":768106,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lombard, Melissa A. 0000-0001-5924-6556 mlombard@usgs.gov","orcid":"https://orcid.org/0000-0001-5924-6556","contributorId":198254,"corporation":false,"usgs":true,"family":"Lombard","given":"Melissa","email":"mlombard@usgs.gov","middleInitial":"A.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":768107,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70178728,"text":"sir20165156 - 2017 - Magnitude of flood flows for selected annual exceedance probabilities for streams in Massachusetts","interactions":[],"lastModifiedDate":"2017-05-10T16:40:49","indexId":"sir20165156","displayToPublicDate":"2017-05-10T17:10:00","publicationYear":"2017","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":"2016-5156","title":"Magnitude of flood flows for selected annual exceedance probabilities for streams in Massachusetts","docAbstract":"The U.S. Geological Survey, in cooperation with the Massachusetts Department of Transportation, determined the magnitude of flood flows at selected annual exceedance probabilities (AEPs) at streamgages in Massachusetts and from these data developed equations for estimating flood flows at ungaged locations in the State. Flood magnitudes were determined for the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent AEPs at 220 streamgages, 125 of which are in Massachusetts and 95 are in the adjacent States of Connecticut, New Hampshire, New York, Rhode Island, and Vermont. AEP flood flows were computed for streamgages using the expected moments algorithm weighted with a recently computed regional skewness coefficient for New England.
Regional regression equations were developed to estimate the magnitude of floods for selected AEP flows at ungaged sites from 199 selected streamgages and for 60 potential explanatory basin characteristics. AEP flows for 21 of the 125 streamgages in Massachusetts were not used in the final regional regression analysis, primarily because of regulation or redundancy. The final regression equations used generalized least squares methods to account for streamgage record length and correlation. Drainage area, mean basin elevation, and basin storage explained 86 to 93 percent of the variance in flood magnitude from the 50- to 0.2-percent AEPs, respectively. The estimates of AEP flows at streamgages can be improved by using a weighted estimate that is based on the magnitude of the flood and associated uncertainty from the at-site analysis and the regional regression equations. Weighting procedures for estimating AEP flows at an ungaged site on a gaged stream also are provided that improve estimates of flood flows at the ungaged site when hydrologic characteristics do not abruptly change.
Urbanization expressed as the percentage of imperviousness provided some explanatory power in the regional regression; however, it was not statistically significant at the 95-percent confidence level for any of the AEPs examined. The effect of urbanization on flood flows indicates a complex interaction with other basin characteristics. Another complicating factor is the assumption of stationarity, that is, the assumption that annual peak flows exhibit no significant trend over time. The results of the analysis show that stationarity does not prevail at all of the streamgages. About 27 percent of streamgages in Massachusetts and about 42 percent of streamgages in adjacent States with 20 or more years of systematic record used in the study show a significant positive trend at the 95-percent confidence level. The remaining streamgages had both positive and negative trends, but the trends were not statistically significant. Trends were shown to vary over time. In particular, during the past decade (2004–2013), peak flows were persistently above normal, which may give the impression of positive trends. Only continued monitoring will provide the information needed to determine whether recent increases in annual peak flows are a normal oscillation or a true trend.
The analysis used 37 years of additional data obtained since the last comprehensive study of flood flows in Massachusetts. In addition, new methods for computing flood flows at streamgages and regionalization improved estimates of flood magnitudes at gaged and ungaged locations and better defined the uncertainty of the estimates of AEP floods.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165156","collaboration":"Prepared in cooperation with the Massachusetts Department of Transportation","usgsCitation":"Zarriello, P.J., 2017, Magnitude of flood flows at selected annual exceedance probabilities for streams in Massachusetts: U.S. Geological Survey Scientific Investigations Report 2016–5156, 54 p., https://doi.org/10.3133/sir20165156.","productDescription":"Report: ix, 54 p.; Tables; 1 Appendix","numberOfPages":"68","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-065274","costCenters":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"links":[{"id":341058,"rank":9,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2016/5156/sir20165156_table11.csv","text":"Table 11","size":"47.9 KB","linkFileType":{"id":7,"text":"csv"},"linkHelpText":"- Magnitude and variance of selected flood 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\"}}]}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
State and local water-resource managers need modeling tools to help them manage and protect water-supply resources for both human consumption and ecological needs. The U.S. Geological Survey, in cooperation with the Massachusetts Department of Environmental Protection, has developed a decision-support tool to estimate the effects of reservoirs on natural streamflow. The Massachusetts Reservoir Simulation Tool is a model that simulates the daily water balance of a reservoir. The reservoir simulation tool provides estimates of daily outflows from reservoirs and compares the frequency, duration, and magnitude of the volume of outflows from reservoirs with estimates of the unaltered streamflow that would occur if no dam were present. This tool will help environmental managers understand the complex interactions and tradeoffs between water withdrawals, reservoir operational practices, and reservoir outflows needed for aquatic habitats.
A sensitivity analysis of the daily water balance equation was performed to identify physical and operational features of reservoirs that could have the greatest effect on reservoir outflows. For the purpose of this report, uncontrolled releases of water (spills or spillage) over the reservoir spillway were considered to be a proxy for reservoir outflows directly below the dam. The ratio of average withdrawals to the average inflows had the largest effect on spillage patterns, with the highest withdrawals leading to the lowest spillage. The size of the surface area relative to the drainage area of the reservoir also had an effect on spillage; reservoirs with large surface areas have high evaporation rates during the summer, which can contribute to frequent and long periods without spillage, even in the absence of water withdrawals. Other reservoir characteristics, such as variability of inflows, groundwater interactions, and seasonal demand patterns, had low to moderate effects on the frequency, duration, and magnitude of spillage. The reservoir simulation tool was used to simulate 35 single- and multiple-reservoir systems in Massachusetts over a 44-year period (water years 1961 to 2004) under two water-use scenarios. The no-pumping scenario assumes no water withdrawal pumping, and the pumping scenario incorporates average annual pumping rates from 2000 to 2004. By comparing the results of the two scenarios, the total streamflow alteration can be parsed into the portion of streamflow alteration caused by the presence of a reservoir and the additional streamflow alteration caused by the level of water use of the system.
For each reservoir system, the following metrics were computed to characterize the frequency, duration, and magnitude of reservoir outflow volumes compared with unaltered streamflow conditions: (1) the median number of days per year in which the reservoir did not spill, (2) the median duration of the longest consecutive period of no-spill days per year, and (3) the lowest annual flow duration exceedance probability at which the outflows are significantly different from estimated unaltered streamflow at the 95-percent confidence level. Most reservoirs in the study do not spill during the summer months even under no-pumping conditions. The median number of days during which there was no spillage was less than 365 for all reservoirs in the study, indicating that, even under reported pumping conditions, the reservoirs refill to full volume and spill at least once during nondrought years, typically in the spring.
Thirteen multiple-reservoir systems consisting of two or three hydrologically connected reservoirs were included in the study. Because operating rules used to manage multiple-reservoir systems are not available, these systems were simulated under two pumping scenarios, one in which water transfers between reservoirs are minimal and one in which reservoirs continually transferred water to intermediate or terminal reservoirs. These two scenarios provided upper and lower estimates of spillage under average pumping conditions from 2000 to 2004.
For sites with insufficient data to simulate daily water balances, a proxy method to estimate the three spillage metrics was developed. A series of 4,000 Monte Carlo simulations of the reservoir water balance were run. In each simulation, streamflow, physical reservoir characteristics, and daily climate inputs were randomly varied. Tobit regression equations that quantify the relation between streamflow alteration and physical and operational characteristics of reservoirs were developed from the results of the Monte Carlo simulations and can be used to estimate each of the three spillage metrics using only the withdrawal ratio and the ratio of the surface area to the drainage area, which are available statewide for all reservoirs.
A graphical user-interface for the Massachusetts Reservoir Simulation Tool was developed in a Microsoft Access environment. The simulation tool contains information for 70 reservoirs in Massachusetts and allows for simulation of additional scenarios than the ones considered in this report, including controlled releases, dam seepage and leakage, demand management plans, and alternative water withdrawal and transfer rules.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165123","collaboration":"Prepared in cooperation with the Massachusetts Department of Environmental Protection","usgsCitation":"Levin, S.B., 2016, Effects of water-supply reservoirs on streamflow in Massachusetts: U.S. Geological Survey Scientific Investigations Report 2016–5123, 35 p., https://dx.doi.org/10.3133/sir20165123.","productDescription":"Report: vii, 35 p.; Software or Model Page","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-067115","costCenters":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"links":[{"id":329303,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/ofr20161136","text":"Open-File Report 2016–1136","description":"Open-File Report 2016-1136","linkHelpText":"- Massachusetts Reservoir Simulation Tool—User’s 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\"}}]}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
Or visit our Web site at:
http://newengland.water.usgs.gov/
A Presidential disaster was declared in northwestern Massachusetts, following flooding from tropical storm Irene on August 28, 2011. During the storm, 3 to 10 inches of rain fell on soils that were susceptible to flash flooding because of wet antecedent conditions. The gage height at one U.S. Geological Survey streamgage rose nearly 20 feet in less than 4 hours because of the combination of saturated soils and intense rainfall. On August 28, 2011, in the Deerfield and Hoosic River Basins in northwestern Massachusetts, new peaks of record were set at six of eight U.S. Geological Survey long-term streamgages with 46 to 100 years of record. Additionally, high-water marks were surveyed and indirect measurements of peak discharge were calculated at two discontinued streamgages in the Deerfield and Hoosic River Basins with 24 and 61 years of record, respectively. This data resulted in new historic peaks of record at the two discontinued streamgages from tropical storm Irene.
\nPeak flows that resulted from tropical storm Irene (August 28, 2011) were determined at the U.S. Geological Survey streamgages by using stage-discharge rating curves and indirect computation methods. For six streamgages, indirect computation methods were used to compute the peak flows. Peak flows from tropical storm Irene had annual exceedance probabilities (AEPs) that ranged from 5.4 percent to less than 0.2 percent at 10 streamgages in northwestern Massachusetts.
\nDischarges calculated for select AEPs as a part of this study were compared with discharges published for the same AEPs in the effective Federal Emergency Management Agency flood insurance studies (FISs) for communities in the study area. Discharges estimated for the 10-, 2-, 1-, and 0.2-percent AEPs at two streamgages on the main stem of the Deerfield River ranged from about 3 percent lower to 14 percent higher than discharges in the FISs. AEP discharges calculated for two streamgages on tributaries to the Deerfield River were 27 to 89 percent higher than the FISs. For the four streamgages in the Hoosic River Basin, the 10-, 2-, 1-, and 0.2-percent AEP discharges calculated ranged from about 33 percent lower to 5 percent higher than the FISs.
\nThe simulated 1-percent AEP discharge water-surface elevations (nonregulatory) from recent (2015–16) hydraulic models for river reaches in the study area, which include the Deerfield, Green, and North Rivers in the Deerfield River Basin and the Hoosic River in the Hoosic River Basin, were compared with water-surface profiles in the FISs. The water-surface elevation comparisons were generally done downstream and upstream from bridges, dams, and major tributaries. The simulated 1-percent AEP discharge water-surface elevations of the recent hydraulic studies averaged 2.2, 2.3, 0.3, and 0.7 ft higher than water-surface elevations in the FISs for the Deerfield, Green, North, and Hoosic Rivers, respectively. The differences in water-surface elevations between the recent (2015–16) hydraulic studies and the FISs likely are because of (1) improved land elevation data from light detection and ranging (lidar) data collected in 2012, (2) detailed surveying of hydraulic structures and cross sections throughout the river reaches in 2012–13 (reflecting structure and cross section changes during the last 30–35 years), (3) updated hydrology analyses (30–35 water years of additional peak flow data at streamgages), and (4) high-water marks from the 2011 tropical storm Irene flood being used for model calibration.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165027","collaboration":"Prepared in cooperation with the Federal Emergency Management Agency","usgsCitation":"Bent, G.C., Olson, S.A., and Massey, A.J., 2016, Tropical storm Irene flood of August 2011 in northwestern Massachusetts: U.S. Geological Survey Scientific Investigations Report 2016–5027, 28 p., https://dx.doi.org/10.3133/sir20165027.","productDescription":"v, 28 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-067697","costCenters":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"links":[{"id":327911,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5027/coverthb.jpg"},{"id":327912,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5027/sir20165027.pdf","text":"Report","size":"1.21 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5027"}],"country":"United States","state":"Massachusetts","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -72.61688232421875,\n 42.731378652044185\n ],\n [\n -72.60452270507812,\n 42.718263627309774\n ],\n [\n -72.58804321289061,\n 42.693539313660004\n ],\n [\n -72.55989074707031,\n 42.653656930109726\n ],\n [\n -72.55302429199219,\n 42.64153569439977\n ],\n [\n -72.5592041015625,\n 42.628906895633456\n ],\n [\n -72.55851745605469,\n 42.61122227199062\n ],\n [\n -72.56813049316406,\n 42.603641609996586\n ],\n [\n -72.57637023925781,\n 42.59606002548659\n ],\n [\n -72.58049011230469,\n 42.59454359788448\n ],\n [\n -72.57980346679686,\n 42.58493869951935\n ],\n [\n -72.57568359375,\n 42.578871685346364\n ],\n [\n -72.57431030273438,\n 42.560161341916064\n ],\n [\n -72.58323669433594,\n 42.54296310520116\n ],\n [\n -72.59078979492188,\n 42.52677220056902\n ],\n [\n -72.60246276855469,\n 42.50804623455747\n ],\n [\n -72.62718200683594,\n 42.50500906265383\n ],\n [\n -72.652587890625,\n 42.50956476517422\n ],\n [\n -72.6800537109375,\n 42.51766297209017\n ],\n [\n -72.69515991210938,\n 42.52879629320373\n ],\n [\n -72.70683288574219,\n 42.51766297209017\n ],\n [\n -72.71781921386719,\n 42.50754004948742\n ],\n [\n -72.74116516113281,\n 42.49387150323448\n ],\n [\n -72.78923034667969,\n 42.47817430242153\n ],\n [\n -72.80845642089844,\n 42.46753847696729\n ],\n [\n -72.82699584960938,\n 42.50500906265383\n ],\n [\n -72.84347534179688,\n 42.52069952914966\n ],\n [\n -72.85308837890624,\n 42.53638605645048\n ],\n [\n -72.89840698242188,\n 42.55055114674488\n ],\n [\n -72.90252685546875,\n 42.54448078729858\n ],\n [\n -72.90390014648438,\n 42.53739795519656\n ],\n [\n -72.94166564941406,\n 42.53638605645048\n ],\n [\n -72.94647216796874,\n 42.525760129656845\n ],\n [\n -72.96363830566406,\n 42.51968735985934\n ],\n [\n -72.97531127929688,\n 42.53588010092859\n ],\n [\n -72.9876708984375,\n 42.54852775918642\n ],\n [\n -73.00277709960938,\n 42.55560932868032\n ],\n [\n -73.01239013671875,\n 42.562184352321886\n ],\n [\n -73.02200317382812,\n 42.57027573801005\n ],\n [\n -73.02818298339844,\n 42.58645536081647\n ],\n [\n -73.04054260253906,\n 42.601619944327965\n ],\n [\n -73.04672241210938,\n 42.605157816197334\n ],\n [\n -73.06938171386719,\n 42.58696090638245\n ],\n [\n -73.06800842285156,\n 42.5798828953732\n ],\n [\n -73.06869506835938,\n 42.560161341916064\n ],\n [\n -73.05770874023438,\n 42.54144538620976\n ],\n [\n -73.05770874023438,\n 42.53486817758702\n ],\n [\n -73.07212829589844,\n 42.52677220056902\n ],\n [\n -73.10508728027344,\n 42.51158941527828\n ],\n [\n -73.11126708984375,\n 42.49690921618136\n ],\n [\n -73.14628601074219,\n 42.50500906265383\n ],\n [\n -73.15864562988281,\n 42.49944053092116\n ],\n [\n -73.16963195800781,\n 42.489820989777066\n ],\n [\n -73.18954467773438,\n 42.48830197960227\n ],\n [\n -73.21563720703125,\n 42.49032731830467\n ],\n [\n -73.22181701660156,\n 42.50905859240087\n ],\n [\n -73.22181701660156,\n 42.52829027619378\n ],\n [\n -73.21769714355469,\n 42.54448078729858\n ],\n [\n -73.21151733398436,\n 42.553586105099654\n ],\n [\n -73.20533752441406,\n 42.56370156708076\n ],\n [\n -73.19366455078125,\n 42.587971985214814\n ],\n [\n -73.201904296875,\n 42.58594981115061\n ],\n [\n -73.23211669921875,\n 42.58493869951935\n ],\n [\n -73.24928283691406,\n 42.5995982130586\n ],\n [\n -73.25889587402344,\n 42.5995982130586\n ],\n [\n -73.26301574707031,\n 42.58746644784856\n ],\n [\n -73.32069396972655,\n 42.59252163701558\n ],\n [\n -73.26507568359375,\n 42.74600367786244\n ],\n [\n -72.61688232421875,\n 42.731378652044185\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
Or visit our Web site at:
http://newengland.water.usgs.gov
Streamflow and concentrations of sodium and chloride estimated from records of specific conductance were used to calculate loads of sodium and chloride during water year (WY) 2014 (October 1, 2013, through September 30, 2014) for tributaries to the Scituate Reservoir, Rhode Island. Streamflow and water-quality data used in the study were collected by the U.S. Geological Survey and the Providence Water Supply Board in the cooperative study. Streamflow was measured or estimated by the U.S. Geological Survey following standard methods at 23 streamgages; 14 of these streamgages are equipped with instrumentation capable of continuously monitoring water level, specific conductance, and water temperature. Water-quality samples were collected at 37 sampling stations by the Providence Water Supply Board and at 14 continuous-record streamgages by the U.S. Geological Survey during WY 2014 as part of a long-term sampling program; all stations are in the Scituate Reservoir drainage area. Water-quality data collected by the Providence Water Supply Board are summarized by using values of central tendency and are used, in combination with measured (or estimated) streamflows, to calculate loads and yields (loads per unit area) of selected water-quality constituents for WY 2014.
The largest tributary to the reservoir (the Ponaganset River, which was monitored by the U.S. Geological Survey) contributed a mean streamflow of 23 cubic feet per second to the reservoir during WY 2014. For the same time period, annual mean streamflows measured (or estimated) for the other monitoring stations in this study ranged from about 0.35 to about 14 cubic feet per second. Together, tributaries (equipped with instrumentation capable of continuously monitoring specific conductance) transported about 1,200,000 kilograms of sodium and 2,100,000 kilograms of chloride to the Scituate Reservoir during WY 2014; sodium and chloride yields for the tributaries ranged from 7,700 to 45,000 kilograms per year per square mile and from 12,000 to 75,000 kilograms per year per square mile, respectively.
At the stations where water-quality samples were collected by the Providence Water Supply Board, the median of the median chloride concentrations was 24 milligrams per liter, median nitrite concentration was 0.002 milligrams per liter as nitrogen (N), median nitrate concentration was 0.01 milligrams per liter as N, median orthophosphate concentration was 0.07 milligrams per liter as phosphate, and median concentrations of total coliform bacteria and Escherichia coli were 320 and 20 colony forming units per 100 milliliters, respectively. The medians of the median daily loads (and yields) of chloride, nitrite, nitrate, orthophosphate, and total coliform and Escherichia coli bacteria were 62 kilograms per day (42 kilograms per day per square mile), 19 grams per day (6.1 grams per day per square mile), 79 grams per day (36 grams per day per square mile), 380 grams per day (150 grams per day per square mile), 13,000 million colony forming units per day (8,300 million colony forming units per day per square mile), and 1,000 million colony forming units per day (470 million colony forming units per day per square mile), respectively.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161051","collaboration":"Prepared in cooperation with the Providence Water Supply Board","usgsCitation":"Smith, K.P., 2016, Streamflow, water quality, and constituent loads and yields, Scituate Reservoir drainage area, Rhode Island, water year 2014: U.S. Geological Survey Open-File Report 2016–1051, 31 p., https://dx.doi.org/10.3133/ofr20161051.","productDescription":"Report: v, 31 p.; Appendix 1","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-069938","costCenters":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"links":[{"id":320747,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1051/ofr20161051.pdf","text":"Report","size":"11.1 (MB)","linkFileType":{"id":1,"text":"pdf"},"description":"OF 2016-1051"},{"id":320748,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2016/1051/ofr20161051_appendix1.xlsx","text":"Appendix 1","linkFileType":{"id":3,"text":"xlsx"},"description":"Appendix 1","linkHelpText":"Appendix 1. Water-quality data collected by the Providence Water Supply Board at 37 monitoring stations in the Scituate Reservoir drainage area, Rhode Island, water year 2014. Excel (30 KB)"},{"id":320746,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1051/coverthb.jpg"}],"country":"United States","state":"Rhode Island","otherGeospatial":"Scituate Reservoir","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -71.7572021484375,\n 41.738784653087464\n ],\n [\n -71.7572021484375,\n 41.90304362629451\n ],\n [\n -71.55567169189453,\n 41.90304362629451\n ],\n [\n -71.55567169189453,\n 41.738784653087464\n ],\n [\n -71.7572021484375,\n 41.738784653087464\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
or visit our Web site at:
http://newengland.water.usgs.gov
Dilution of aluminum discharged to reservoirs in filter-backwash effluents at water-treatment facilities in Massachusetts was investigated by a field study and computer simulation. Determination of dilution is needed so that permits for discharge ensure compliance with water-quality standards for aquatic life. The U.S. Environmental Protection Agency chronic standard for aluminum, 87 micrograms per liter (μg/L), rather than the acute standard, 750 μg/L, was used in this investigation because the time scales of chronic exposure (days) more nearly match rates of change in reservoir concentrations than do the time scales of acute exposure (hours).
Whereas dilution factors are routinely computed for effluents discharged to streams solely on the basis of flow of the effluent and flow of the receiving stream, dilution determination for effluents discharged to reservoirs is more complex because (1), compared to streams, additional water is available for dilution in reservoirs during low flows as a result of reservoir flushing and storage during higher flows, and (2) aluminum removal in reservoirs occurs by aluminum sedimentation during the residence time of water in the reservoir. Possible resuspension of settled aluminum was not considered in this investigation. An additional concern for setting discharge standards is the substantial concentration of aluminum that can be naturally present in ambient surface waters, usually in association with dissolved organic carbon (DOC), which can bind aluminum and keep it in solution.
A method for dilution determination was developed using a mass-balance equation for aluminum and considering sources of aluminum from groundwater, surface water, and filter-backwash effluents and losses caused by sedimentation, water withdrawal, and spill discharge from the reservoir. The method was applied to 13 reservoirs. Data on aluminum and DOC concentrations in reservoirs and influent water were collected during the fall of 2009. Complete reservoir volume was determined to be available for mixing on the basis of vertical and horizontal aluminum-concentration profiling. Losses caused by settling of aluminum were assumed to be proportional to aluminum concentration and reservoir area. The constant of proportionality, as a function of DOC concentration, was established by simulations in each of five reservoirs that differed in DOC concentration.
In addition to computing dilution factors, the project determined dilution factors that would be protective with the same statistical basis (frequency of exceedance of the chronic standard) as dilutions computed for streams at the 7-day-average 10-year-recurrence annual low flow (the 7Q10). Low-flow dilutions are used for permitting so that receiving waters are protected even at the worst-case flow levels. The low-flow dilution factors that give the same statistical protection are the lowest annual 7-day-average dilution factors with a recurrence of 10 years, termed 7DF10s. Determination of 7DF10 values for reservoirs required that long periods of record be simulated so that dilution statistics could be determined. Dilution statistics were simulated for 13 reservoirs from 1960 to 2004 using U.S. Geological Survey Firm-Yield Estimator software to model reservoir inputs and outputs and present-day values of filter-effluent discharge and aluminum concentration.
Computed settling velocities ranged from 0 centimeters per day (cm/d) at DOC concentrations of 15.5 milligrams per liter (mg/L) to 21.5 cm/d at DOC concentrations of 2.7 mg/L. The 7DF10 values were a function of aluminum effluent discharged. At current (2009) effluent discharge rates, the 7DF10 values varied from 1.8 to 115 among the 13 reservoirs. In most cases, the present-day (2009) discharge resulted in receiving water concentrations that did not exceed the standard at the 7DF10. Exceptions were one reservoir with a very small area and three reservoirs with high concentrations of DOC. Maximum permissible discharges were determined for water-treatment plants by adjusting discharges upward in simulations until the 7DF10 resulted in reservoir concentrations that just met the standard. In terms of aluminum flux, these discharges ranged from 0 to 28 kilograms of aluminum per day.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20115136","collaboration":"Prepared in cooperation with the Massachusetts Department of Environmental Protection","usgsCitation":"Colman, J.A., Massey, A.J., and Levin, S.B., 2016, Determination of dilution factors for discharge of aluminum-containing wastes by public water-supply treatment facilities into lakes and reservoirs in Massachusetts (ver. 1.1, December 2016): U.S. Geological Survey Scientific Investigations Report 2011–5136, 36 p., https://pubs.usgs.gov/sir/2011/5136.","productDescription":"vi, 36 p.","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"links":[{"id":116564,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2011/5136/images/coverthb.jpg"},{"id":94131,"rank":100,"type":{"id":15,"text":"Index 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\"}}]}","edition":"Version 1.0: Originally posted September 16, 2011; Version 1.1: December 30, 2016","contact":"Director, Massachusetts-Rhode Island Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
(508) 490-5000
http://ma.water.usgs.gov
The U.S. Geological Survey, in cooperation with the Town of Framingham, Massachusetts, has investigated the potential of proposed groundwater withdrawals at the Birch Road well site to affect nearby surface water bodies and wetlands, including Lake Cochituate, the Sudbury River, and the Great Meadows National Wildlife Refuge in east-central Massachusetts. In 2012, the U.S. Geological Survey developed a Phase 1 numerical groundwater model of a complex glacial-sediment aquifer to synthesize hydrogeologic information and simulate potential future pumping scenarios. The model was developed with MODFLOW-NWT, an updated version of a standard USGS numerical groundwater flow modeling program that improves solution of unconfined groundwater flow problems. The groundwater model and investigations of the aquifer improved understanding of groundwater–surface-water interaction and the effects of groundwater withdrawals on surface-water bodies and wetlands in the study area. The initial work also revealed a need for additional information and model refinements to better understand this complex aquifer system.
\nIn this second phase of the study, the original groundwater flow model was revised to improve representation of groundwater and surface-water hydrology, stabilize the model, and reduce model error. The model was simplified by reducing the number of layers from 5 to 3 and adding the MODFLOW lake package (LAK) to simulate Lake Cochituate and Pod Meadow Pond and better represent interaction between the lakes and the aquifer. Model revisions improved stability and shortened run times, allowing use of automated parameter estimation software (PEST) to further refine the model hydraulic parameters and reduce simulation errors.
\nModel simulations indicate that under average base-flow conditions, the Birch Road wells have a small effect on flow in the Sudbury River during most months, even at the maximum pumping rate of 4.9 ft3/s (3.17 Mgal/d). Maximum percent streamflow depletion in the Sudbury River caused by simulated pumping takes place during simulated drought conditions, when streamflow decreased by as much as 21 percent under maximum continuous pumping. Simulations also indicate that groundwater withdrawals at the Birch Road site could be managed so that adverse streamflow impacts are substantially ameliorated. Under the most ecologically conservative simulated drought conditions, simulated streamflow depletion was reduced from 21 percent to 3 percent by pumping at the maximum rate for 6 months rather than for 12 months. Simulations that return 10 percent of the Birch Road well withdrawals to Pod Meadow Pond indicate a modest reduction in the Sudbury River streamflow depletion and provide a larger percentage increase to streamflow just downstream of the pond. The groundwater model also indicates that well locations can have a large effect on the sustainable pumping rate and so should be chosen carefully. The model provides a tool for evaluating alternative pumping rates and schedules not included in this analysis.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155174","collaboration":"Prepared in cooperation with the Town of Framingham, Massachusetts","usgsCitation":"Eggleston, J.R., Zarriello, P.J., and Carlson, C.S., 2015, Groundwater and surface-water interaction and effects of pumping in a complex glacial-sediment aquifer, Phase 2, east-central Massachusetts: U.S. Geological Survey Scientific Investigations Report 2015–5174, 38 p., https://dx.doi.org/10.3133/sir20155174.","productDescription":"viii, 38 p.","numberOfPages":"50","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-070584","costCenters":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"links":[{"id":312906,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5174/sir20155174.pdf","text":"Report","size":"2.42 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5174"},{"id":312905,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5174/coverthb.jpg"}],"country":"United States","state":"Massachusetts","city":"Framingham","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -71.40366554260254,\n 42.311021393971345\n ],\n [\n -71.40366554260254,\n 42.357085148806945\n ],\n [\n -71.36615753173828,\n 42.357085148806945\n ],\n [\n -71.36615753173828,\n 42.311021393971345\n ],\n [\n -71.40366554260254,\n 42.311021393971345\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
Or visit our Web site at:
http://newengland.water.usgs.gov
Water use, such as withdrawals, wastewater return flows, and interbasin transfers, can alter streamflow regimes, water quality, and the integrity of aquatic habitat and affect the availability of water for human and ecosystem needs. To provide the information needed to determine alteration of streamflows and pond water levels in southeastern Massachusetts, existing groundwater models of the Plymouth-Carver region and western (Sagamore flow lens) and eastern (Monomoy flow lens) Cape Cod were used to delineate subbasins and simulate long-term average and average monthly streamflows and pond levels for a series of water-use conditions. Model simulations were used to determine the extent to which streamflows and pond levels were altered by comparing simulated streamflows and pond levels under predevelopment conditions with streamflows and pond levels under pumping only and pumping with wastewater return flow conditions. The pumping and wastewater return flow rates used in this study are the same as those used in previously published U.S. Geological Survey studies in southeastern Massachusetts and represent the period from 2000 to 2005. Streamflow alteration for the nontidal portions of streams in southeastern Massachusetts was evaluated within and at the downstream outlets of 78 groundwater subbasins delineated for this study. Evaluation of streamflow alteration at subbasin outlets is consistent with the approach used by the U.S. Geological Survey for the topographically derived subbasins in the rest of Massachusetts.
\nThe net effect of pumping and wastewater return flows on streamflows and pond levels varied by location and included no change in areas minimally affected by water use, decreases in areas affected more by pumping than by wastewater return flows, or increases in areas affected more by wastewater return flows than by pumping. Simulated alterations to long-term average streamflows at subbasin outlets in response to pumping with wastewater return flows were within about 10 percent of predevelopment streamflows for most of the subbasins in the study area. Alterations ranged from a decrease (depletion) of 43.9 percent at an unnamed tributary to Salt Pond in the Plymouth-Carver region to an increase (surcharge) of 18.2 percent at an unnamed tributary to the Centerville River on western Cape Cod. In general, the relative effects of pumping and wastewater return flows typically were larger in the subbasins with low streamflows than in the subbasins with high streamflows, and there were more depleted streamflows than surcharged streamflows. Increases in streamflows in response to wastewater return flows were generally largest in subbasins with a high density of septic systems or a centralized wastewater treatment facility. For average monthly conditions, streamflow alteration results were similar spatially to results for long-term average conditions. However, differences in the extent of alteration by month were observed; percentage streamflow depletions in most subbasins typically were greatest during the low-streamflow months of August and October.
\nThe percentages of the total number of ponds affected by pumping with wastewater return flows under long-term average conditions in the modeled areas were 28 percent for the Plymouth-Carver region, 67 percent for western Cape Cod, and 75 percent for eastern Cape Cod. Pond-level alterations ranged from a decrease of 4.6 feet at Great South Pond in the Plymouth Carver region to an increase of 0.9 feet at Wequaquet Lake in western Cape Cod. The magnitudes of monthly alterations to pond water levels were fairly consistent throughout the year.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155168","collaboration":"Prepared in cooperation with the Massachusetts Department of Environmental Protection","usgsCitation":"Carlson, C.S., Walter, D.A., and Barbaro, J.R., 2015, Simulated responses of streams and ponds to groundwater withdrawals and wastewater return flows in southeastern Massachusetts: U.S. Geological Survey Scientific Investigations Report 2015–5168, 60 p., https://dx.doi.org/10.3133/sir20155168.","productDescription":"Report: vii, 60 p.; 2 Tables; 2 Appendixes","numberOfPages":"72","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-065841","costCenters":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"links":[{"id":312500,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5168/sir20155168_appendix2_gis.zip","text":"Appendix 2 - Shapefiles and spreadsheet files","size":"15.8 MB","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2015-5168"},{"id":312497,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5168/coverthb2.jpg"},{"id":312501,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5168/sir20155168_appendix3_gis.zip","text":"Appendix 3 - Shapefiles and spreadsheet files","size":"3.3 MB","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2015-5168"},{"id":312498,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5168/sir20155168.pdf","text":"Report","size":"8.41 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5168"},{"id":312499,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2015/5168/sir20155168_tables3-4.xlsx","text":"Tables 3-4","size":"52 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2015-5168","linkHelpText":"Table 3. Stream identification, landscape characteristics, and Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
Or visit our Web site at:
http://newengland.water.usgs.gov
Studies from North Carolina (NC) indicate that increasing concentrations of total phosphorus (TP) and other constituents are correlated to adverse effects on stream ecosystems as evidenced by differences in benthic macroinvertebrate populations in streams across the state. As a result, stringent in-stream criteria based on the Water Quality Assessed by Benthic macroinvertebrate health ratings (WQABI) have been proposed for regulating TP concentrations in stormwater discharges and for selecting stormwater best management practices (BMPs). The WQABI criteria concentrations may not be suitable for evaluating stormwater discharges because they are based on baseflow concentration statistics, the criteria do not include a clearly defined allowable exceedance frequency, and there are substantial uncertainties in estimating the quality of runoff, BMP discharge, and receiving waters for sites without monitoring data.
\nThe Stochastic Empirical Loading and Dilution Model (SELDM), which was developed by the U.S. Geological Survey in cooperation with the Federal Highway Administration, was used to simulate the quality of runoff, BMP discharge, and receiving waters to evaluate risks for water-quality exceedances with different criteria concentrations, allowable exceedance frequencies, and selected water-quality statistics. Water-quality data from two neighboring basins in the Piedmont ecoregion in NC were used to simulate in-stream stormwater quality. Data collected at 15 sites in NC were used to simulate runoff quality. Statistics for stochastic modeling of volume reduction, hydrograph extension, and water-quality treatment by BMPs, were used to simulate potential effect of these treatments on discharge quality and downstream stormwater quality. Results of these long-term 30-year simulations were used to evaluate criteria concentrations, the potential frequency of water-quality exceedances, and the effect of data selection on risks for water-quality exceedances.
\nThe simulations indicate that the potential frequency for exceeding instream and stormwater discharge criteria depend on the detailed definition of the criteria and the data that are selected for simulating water quality. Data and simulation results indicate that the baseflow concentrations do not represent stormwater concentrations, even in predominantly forested basins. There is substantial uncertainty in applying stormwater statistics to unmonitored sites, even if these statistics are applied to neighboring basins such as in this example. Over a period of several years (or more) it would be impossible to meet many of the proposed instream and stormwater discharge quality criteria unless these criteria include an allowable exceedance frequency because stormwater concentrations commonly vary by orders of magnitude. Selection of BMPs by using concentration reduction as the sole criteria may underestimate potential benefits of BMPs that also provide volume reduction, which reduces discharge loads, and hydrograph extension, which increases the dilution of runoff into a larger proportion of the upstream stormflow.
\nResults of this study indicate the potential benefits of the multi-decade simulations that SELDM provides because these simulations quantify risks and uncertainties that affect decisions made with available data and statistics. Results of the SELDM simulations indicate that the WQABI criteria concentrations may be too stringent for evaluating the stormwater quality in receiving streams, highway runoff, and BMP discharges; especially with the substantial uncertainties inherent in selecting representative data.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the 2015 International Conference on Ecology and Transportation (ICOET 2015)","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"2015 International conference on ecology and transportation","conferenceDate":"September 20, 2015","conferenceLocation":"Raleigh, NC","language":"English","publisher":"Center for Transportation and the Environment","usgsCitation":"Granato, G.E., and Jones, S.C., 2015, Estimating the risks for adverse effects of total phosphorus in receiving streams with the Stochastic Empirical Loading and Dilution Model (SELDM), in Proceedings of the 2015 International Conference on Ecology and Transportation (ICOET 2015), Raleigh, NC, September 20, 2015, p. 1-19.","productDescription":"19 p.","startPage":"1","endPage":"19","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065909","costCenters":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"links":[{"id":311831,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"566175cae4b06a3ea36c56a5","contributors":{"authors":[{"text":"Granato, Gregory E. 0000-0002-2561-9913 ggranato@usgs.gov","orcid":"https://orcid.org/0000-0002-2561-9913","contributorId":147346,"corporation":false,"usgs":true,"family":"Granato","given":"Gregory","email":"ggranato@usgs.gov","middleInitial":"E.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":false,"id":579637,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jones, Susan C. 0000-0002-5891-5209","orcid":"https://orcid.org/0000-0002-5891-5209","contributorId":64716,"corporation":false,"usgs":false,"family":"Jones","given":"Susan","email":"","middleInitial":"C.","affiliations":[{"id":34302,"text":"Federal Highway Administration (United States)","active":true,"usgs":false}],"preferred":false,"id":579638,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70155818,"text":"sir20155108 - 2015 - Flood-Inundation Maps for the North River in Colrain, Charlemont, and Shelburne, Massachusetts, From the Confluence of the East and West Branch North Rivers to the Deerfield River","interactions":[],"lastModifiedDate":"2019-12-30T14:31:00","indexId":"sir20155108","displayToPublicDate":"2015-10-27T12:15:00","publicationYear":"2015","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":"2015-5108","title":"Flood-Inundation Maps for the North River in Colrain, Charlemont, and Shelburne, Massachusetts, From the Confluence of the East and West Branch North Rivers to the Deerfield River","docAbstract":"A series of 10 digital flood-inundation maps were developed for a 3.3-mile reach of the North River in Colrain, Charlemont, and Shelburne, Massachusetts, by the U.S. Geological Survey in cooperation with the Federal Emergency Management Agency. The coverage of the maps extends from the confluence of the East and West Branch North Rivers to the Deerfield River. Peak-flow estimates at the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities were computed for the reach from updated flood-frequency analyses. These peak flows were routed through a one-dimensional step-backwater hydraulic model to obtain the corresponding peak water-surface elevations and to place the tropical storm Irene flood of August 28, 2011, into historical context. The hydraulic model was calibrated by using the current [2015] stage-discharge relation at the U.S. Geological Survey streamgage North River at Shattuckville, MA (station number 01169000), and from documented high-water marks from the tropical storm Irene flood, which had a peak flow with approximately a 0.2-percent annual exceedance probability.
\nA hydraulic model was used to compute water-surface profiles for 10 flood stages referenced to the streamgage and ranging from 6.6 feet (ft; 464.5 ft North American Vertical Datum of 1988 [which is approximately bankfull]) to 18.3 ft (476.2 ft North American Vertical Datum of 1988 [which is the stage of the 0.2-percent annual exceedance probability peak flow and exceeds the maximum recorded water level at the streamgage and the National Weather Service major flood stage of 13.0 ft]. The mapped stages of 6.6 to 18.3 ft were selected to match the stages of flows for bankfull; the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities; and an incremental stage of 17.0 ft. The simulated water-surface profiles were combined with a geographic information system digital elevation model derived from light detection and ranging (lidar) data with a 0.5-ft vertical accuracy to create a set of flood-inundation maps.
\nThe availability of the flood-inundation maps, combined with information regarding near-real-time stage from the U.S. Geological Survey North River at Shattuckville, MA streamgage can provide emergency management personnel and residents with information that is critical for flood response activities, such as evacuations and road closures, and postflood recovery efforts. The flood-inundation maps are nonregulatory, but provide Federal, State, and local agencies and the public with estimates of the potential extent of flooding during selected peak-flow events. Introduction
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155108","collaboration":"Prepared in cooperation with the Federal Emergency Management Agency","usgsCitation":"Bent, G.C., Lombard, P.J., and Dudley, R.W., 2015, Flood-inundation maps for the North River in Colrain, Charlemont, and Shelburne, Massachusetts, from the confluence of the East and West Branch North Rivers to the Deerfield River: U.S. Geological Survey Scientific Investigations Report 2015–5108, 16 p., appendixes, https://dx.doi.org/10.3133/sir20155108.","productDescription":"Report: v, 15 p.; Appendixes: 1-2; Application site; Metadata; Spacial data","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-061968","costCenters":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"links":[{"id":310349,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5108/sir20155108.pdf","text":"Report","size":"4.54 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5108"},{"id":310384,"rank":6,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sir/2015/5108/attachments/sir20155108_flood-inundation-gis.zip","text":"Flood Inundation - GIS","size":"4.64 MB","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2015-5108"},{"id":310385,"rank":7,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sir/2015/5108/attachments/sir20155108_flood-inundation-gis-metadata.xml","text":"Flood Inundation - GIS Metadata (xml)","size":"12.5 KB","description":"SIR 2015-5108"},{"id":310386,"rank":8,"type":{"id":4,"text":"Application Site"},"url":"https://wimcloud.usgs.gov/apps/FIM/FloodInundationMapper.html","text":"Flood Inundation Mapper","linkFileType":{"id":5,"text":"html"}},{"id":310383,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5108/attachments/sir20155108_appendix2-shapefiles.zip","text":"Appendix 2 - Shapefiles","size":"31 KB","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2015-5108"},{"id":310382,"rank":4,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sir/2015/5108/attachments/sir20155108_appendix2-metadata.xml","text":"Appendix 2 - Metadata (xml)","size":"11.8 KB","description":"SIR 2015-5108"},{"id":310350,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5108/attachments/sir20155108_app1.xlsx","text":"Appendix 1","size":"13.4 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2015-5108"},{"id":310629,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5108/images/coverthb.jpg"}],"country":"United States","state":"Massachusetts","city":"Colrain, Charlemont, Shelburne, Shattuckville","otherGeospatial":"North River, Deerfield River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.0810546875,\n 42.285437007491545\n ],\n [\n -72.421875,\n 42.285437007491545\n ],\n [\n -72.421875,\n 42.70665956351041\n ],\n [\n -73.0810546875,\n 42.70665956351041\n ],\n [\n -73.0810546875,\n 42.285437007491545\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
Or visit our Web site at
http://newengland.water.usgs.gov/
Decisionmakers need information about the quality and quantity of stormwater runoff, the risk for adverse effects of runoff on receiving waters, and the potential effectiveness of mitigation measures to reduce these risks. The Stochastic Empirical Loading and Dilution Model (SELDM) uses Monte Carlo methods to generate stormflows, concentrations, and loads from a highway site and an upstream basin to provide needed risk-based information. SELDM was designed to help inform water-management decisions for streams and lakes receiving runoff from a highway or other land-use site. The purpose of this paper is to provide a brief description of SELDM and a hypothetical case study demonstrating the type of risk-based information that SELDM can provide. Total nitrogen (TN) and total phosphorus (TP) were selected as example constituents because nutrients are a common concern throughout the Nation and data for receiving waters, highway runoff, and the performance of best management practices (BMPs) are readily available for these constituents.
\nThe case study is hypothetical, but was formulated by using actual data from selected monitoring sites in New England. Data representing streamflow and water-quality were collected at U.S. Geological Survey (USGS) streamgage 01208950 Sasco Brook near Southport, CT, which has a drainage area of 7.38 square miles. In this hypothetical case study a 4-lane highway would replace the current 2-lane road and would have a contributing area of 2.2 acres between the topographic basin divides. Concentrations of TN and TP in highway runoff were simulated with data from USGS highway-runoff monitoring station 423027071291301 along State Route 2 in Littleton Massachusetts. Results of a highway-runoff analysis are shown in relation to three hypothetical discharge criteria for TN and two hypothetical discharge criteria for TP. The risks for exceeding TN discharge criteria of 3, 5, and 8 mg/L for highway runoff are 7.4, 0.83, and 0.13 percent of 1,721 runoff events that may occur during a stochastic 30-year simulation. If a grassy swale is used to treat the runoff, the risks for TN exceedances are reduced to 3.2, 0.33 and 0.03 percent, respectively. The risks for exceeding TP discharge criteria of 0.1 and 0.5 mg/L for highway runoff are 49 and 1.2 percent, respectively. If a grassy swale is used to treat the runoff, the risks for TP exceedances are 57 and 0.8 percent, respectively. The risks for the 0.1 mg/L criterion increase because swales can be a source of TP if pavement concentrations are low. The risks for the 0.5 mg/L criterion decrease because the swale is effective for reducing high TP concentrations. Although the results are mixed for storm-event concentrations, the grassy swale effectively reduces annual loads. Annual loads from the swale are, on average, about 49 percent of highway loads for TN and 62 percent of highway loads of TP because the swale reduces high runoff concentrations and stormflow volumes. Analysis of upstream and downstream concentrations indicates that runoff from the site of interest does not have a substantial effect on instream stormflow concentrations in this example simulation.
","conferenceTitle":"StormCon","conferenceDate":"08/6/2015","conferenceLocation":"Austin, TX","language":"English","publisher":"Forester Media Inc.","publisherLocation":"Santa Barbara, CA","collaboration":"Federal Highway Administration","usgsCitation":"Granato, G.E., and Jones, S.C., 2015, A case study demonstrating analysis of stormflows, concentrations, and loads of nutrients in highway runoff and swale discharge with the Stochastic Empirical Loading and Dilution Model (SELDM), StormCon, Austin, TX, 08/6/2015, p. 1-10.","productDescription":"10 p.","startPage":"1","endPage":"10","numberOfPages":"10","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063178","costCenters":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"links":[{"id":308099,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":307902,"type":{"id":11,"text":"Document"},"url":"https://webdmamrl.er.usgs.gov/g1/FHWA/Presentations/GranatoJones2015StormCon.pdf"}],"publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55f7e19ee4b05d6c4e4fa951","contributors":{"authors":[{"text":"Granato, Gregory E. 0000-0002-2561-9913 ggranato@usgs.gov","orcid":"https://orcid.org/0000-0002-2561-9913","contributorId":147346,"corporation":false,"usgs":true,"family":"Granato","given":"Gregory","email":"ggranato@usgs.gov","middleInitial":"E.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"preferred":false,"id":571336,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jones, Susan C. 0000-0002-5891-5209","orcid":"https://orcid.org/0000-0002-5891-5209","contributorId":64716,"corporation":false,"usgs":false,"family":"Jones","given":"Susan","email":"","middleInitial":"C.","affiliations":[{"id":34302,"text":"Federal Highway Administration (United States)","active":true,"usgs":false}],"preferred":false,"id":571337,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70147396,"text":"ofr20151080 - 2015 - Methods for evaluating potential sources of chloride in surface waters and groundwaters of the conterminous United States","interactions":[],"lastModifiedDate":"2018-04-03T11:36:56","indexId":"ofr20151080","displayToPublicDate":"2015-09-04T13:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-1080","title":"Methods for evaluating potential sources of chloride in surface waters and groundwaters of the conterminous United States","docAbstract":"Chloride exists as a major ion in most natural waters, but many anthropogenic sources are increasing concentrations of chloride in many receiving waters. Although natural concentrations in continental waters can be as high as 200,000 milligrams per liter, chloride concentrations that are suitable for freshwater ecology, human consumption, and agricultural and industrial water uses commonly are on the order of 10 to 1,000 milligrams per liter. “Road salt” frequently is identified as the sole source of anthropogenic chloride, but only about 30 percent of the salt consumed and released to the environment is used for deicing. Furthermore, several studies in Southern States where the use of deicing salt is minimal also show anthropogenic chloride in rising concentrations and in strong correlation to imperviousness and road density. This is because imperviousness and road density also are strongly correlated to population density. The term “road salt” is a misnomer because deicers applied to parking lots, sidewalks, and driveways can be a substantial source of chloride in some catchments because these land covers are comparable to roadways as a percentage of the total impervious area and commonly receive higher salt application rates than some roadways. Other sources of anthropogenic chloride include wastewater, dust control on unpaved roads, fertilizer, animal waste, irrigation, aquaculture, energy production wastes, and landfill leachates. The assumption that rising chloride concentrations in surface water or groundwater is indicative of contamination by deicing chemicals rather than one or more other potential sources may preclude the identification of toxic, carcinogenic, mutagenic, or endocrine-disrupting contaminants that are associated with many sources of elevated chloride concentrations. Once the sources of anthropogenic chloride in an area of interest have been identified and measured, water and solute budgets can be estimated to guide decisionmakers to identify and apply potential mitigation measures that can reduce the problem.
\nScientists, engineers, regulators, and decisionmakers need information about potential sources of chloride, water and solute budgets, and methods for collecting water-quality data to help identify potential sources. This information is needed to evaluate potential sources of chloride in areas where chloride may have adverse ecological effects or may degrade water supplies used for drinking water, agriculture, or industry. Knowledge of potential sources will help decisionmakers identify the best mitigation measures to reduce the total background chloride load, thereby reducing the potential for water-quality exceedances that occur because of superposition on rising background concentrations. Also, knowledge of potential sources may help decisionmakers identify the potential for the presence of contaminants that have toxic, carcinogenic, mutagenic, or endocrine-disrupting effects at concentrations that are lower by orders of magnitude than the chloride concentrations in the source water. This report is a comprehensive synthesis of relevant information, but it is not the result of an exhaustive search for literature on each topic. The potential adverse effects of chloride on infrastructure and the environment are not discussed in this report because these issues have been extensively documented elsewhere.
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U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
Or visit our Web site at:
http://newengland.water.usgs.gov
Hydrologic data and conditions throughout Rhode Island during water year 2014 are presented in this report. Stream discharge and groundwater level conditions varied geographically across the State. Ten streamgages reached record-low minimum monthly mean discharges during the year, and a record-high maximum groundwater level was observed at one groundwater well.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151127","usgsCitation":"Verdi, R.J., and Socolow, R.S., 2015, Hydrologic conditions in Rhode Island during water year 2014: U.S. Geological Survey Open-File Report 2015–1127, 8 p., https://dx.doi.org/10.3133/ofr20151127.","productDescription":"iv, 8 p.","numberOfPages":"16","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-065518","costCenters":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"links":[{"id":305738,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1127/coverthb.jpg"},{"id":305739,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1127/ofr20151127.pdf","text":"Report","size":"875 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1127"}],"country":"United States","state":"Rhode 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U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
http://ma.water.usgs.gov
http://ri.water.usgs.gov
The Scituate Reservoir is the primary source of drinking water for more than 60 percent of the population of Rhode Island. Water-quality and streamflow data collected at 37 surface-water monitoring stations in the Scituate Reservoir drainage area, Rhode Island, from October 2001 through September 2012, water years (WYs) 2002-12, were analyzed to determine water-quality conditions and constituent loads in the drainage area. Trends in water quality, including physical properties and concentrations of constituents, were investigated for the same period and for a longer period from October 1982 through September 2012 (WYs 1983-2012). Water samples were collected and analyzed by the Providence Water Supply Board, the agency that manages the Scituate Reservoir. Streamflow data were collected by the U.S. Geological Survey. Median values and other summary statistics for pH, color, turbidity, alkalinity, chloride, nitrite, nitrate, total coliform bacteria, Escherichia coli (E. coli), and orthophosphate were calculated for WYs 2003-12 for all 37 monitoring stations. Instantaneous loads and yields (loads per unit area) of total coliform bacteria and E. coli, chloride, nitrite, nitrate, and orthophosphate were calculated for all sampling dates during WYs 2003-12 for 23 monitoring stations with streamflow data. Values of physical properties and concentrations of constituents were compared with State and Federal water-quality standards and guidelines and were related to streamflow, land-use characteristics, varying classes of timber operations, and impervious surface areas.
\nTributaries in the Scituate Reservoir drainage area for WYs 2003-12 were slightly acidic (median pH of all stations equal to 6.1) and contained low median concentrations of chloride (22 milligrams per liter [mg/L]), nitrate (0.01 mg/L as nitrogen), nitrite (0.001 mg/L as nitrogen), and orthophosphate (0.02 milligrams per liter as phosphorus [mg/L as P]). Turbidity and alkalinity values also were low with medians of 0.57 nephelometric turbidity units and 5.1 mg/L as calcium carbonate, respectively. Total coliform bacteria and E. coli were detected in most samples from all stations, but median concentrations were generally low-43 colony-forming units per 100 milliliters (mL) and 15 colony-forming units per 100 milliliters, respectively.
\nMedian values of several physical properties and median concentrations of several constituents correlated positively with the percentages of developed land and negatively with the percentages of forest cover in the drainage areas above the monitoring stations. Median concentrations of chloride correlated positively with the percentages of impervious land use in the subbasins of monitoring stations, likely reflecting the effects of deicing compounds applied to roadways during winter maintenance. Median concentrations of alkalinity also correlated positively with the percentage of impervious land use, which may be related to the deterioration of fabricated structures containing calcium carbonate. Median values of color correlated positively with the percentage of wetland area in the subbasins of monitoring stations, reflecting the natural sources of color in tributaries. Streamflows were negatively correlated with turbidity and concentrations of total coliform bacteria and E. coli, possibly reflecting seasonal patterns in which relatively high values of these properties and constituents occur during warmer low-flow conditions late in the water year. Similar seasonal patterns were observed for pH, alkalinity, and color. Negative correlations between concentrations of chloride and streamflow also were significant, indicating that deicing salts from roadways and other impervious surfaces that lack direct connection to the tributaries are likely infiltrating to the groundwater and discharging to some of the tributaries late in the water year. While salt-laden runoff directly enters some of the tributaries at roadway crossings, most of the roadway runoff infiltrates into the adjacent berms throughout the drainage area. Statistically significant correlations were not identified between various degrees of tree-canopy reduction caused by timber operations in the subbasins and median values or concentrations of water-quality properties.
\nLoads and yields of chloride, nitrate, nitrite, orthophosphate, and bacteria varied at monitoring stations in the Scituate Reservoir drainage area in WYs 2003-12. Loads generally were greater at stations in the Barden Reservoir and the Regulating Reservoir Subbasins that have larger drainage areas than in subbasins with smaller drainage areas. Subbasin yields of fecal-indicator bacteria and orthophosphate generally were largest in the Westconnaug Reservoir Subbasin, and subbasin yields for chloride, nitrate, and nitrite were largest in the Moswansicut Reservoir Subbasin in the northeastern part of the drainage area.
\nUpward trends in pH were identified for nearly half of the monitoring stations for WYs 1983-2012 and may reflect regional reductions in acid precipitation. Many upward trends in alkalinity also were identified for both the WYs 1983-2012 and for WYs 2003-12 periods and are likely related to the natural weathering of structures containing concrete or, in some cases, the application of lime or fertilizers on agriculture lands. Significant trends in chloride concentrations at most stations during WYs 1983-2012 were upward; however, results for WYs 2003-12 substantiate few significant upward trends and, in a few cases, downward trends were identified in several tributary drainage areas.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155058","collaboration":"Prepared in cooperation with the Providence Water Supply Board","usgsCitation":"Smith, K.P., 2015, Water-quality trends in the Scituate reservoir drainage area, Rhode Island, 1983-2012: U.S. Geological Survey Scientific Investigations Report 2015-5058, viii, 56 p., https://doi.org/10.3133/sir20155058.","productDescription":"viii, 56 p.","numberOfPages":"70","onlineOnly":"N","additionalOnlineFiles":"Y","temporalStart":"1983-01-01","temporalEnd":"2012-12-31","ipdsId":"IP-045415","costCenters":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"links":[{"id":301097,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20155058.jpg"},{"id":301094,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2015/5058/"},{"id":301095,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5058/pdf/sir2015-5058.pdf","text":"Report","size":"13.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5058 Report"},{"id":301096,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5058/attachments/sir2015-5058_appendix.xlsx","text":"Appendix 1","size":"700 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2015-5058 Appendix 1","linkHelpText":"Values for water-quality data collected by the Providence Water Supply Board at 37 monitoring stations in the Scituate Reservoir drainage area, water years 1983–2012."}],"country":"United States","state":"Rhode Island","otherGeospatial":"Scituate Reservoir","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -71.79290771484375,\n 41.72623044860004\n ],\n [\n -71.8011474609375,\n 41.937019660425264\n ],\n [\n -71.54296874999999,\n 41.937019660425264\n ],\n [\n -71.553955078125,\n 41.734429390721\n ],\n [\n -71.79290771484375,\n 41.72623044860004\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55780020e4b032353cbeb6b7","contributors":{"authors":[{"text":"Smith, Kirk P. 0000-0003-0269-474X kpsmith@usgs.gov","orcid":"https://orcid.org/0000-0003-0269-474X","contributorId":1516,"corporation":false,"usgs":true,"family":"Smith","given":"Kirk","email":"kpsmith@usgs.gov","middleInitial":"P.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"preferred":true,"id":545577,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70148001,"text":"ofr20151085 - 2015 - Simulation of nitrogen attenuation in a subterranean estuary, representative of the southern coast of Cape Cod, Massachusetts","interactions":[],"lastModifiedDate":"2015-06-09T14:59:54","indexId":"ofr20151085","displayToPublicDate":"2015-06-09T15:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-1085","title":"Simulation of nitrogen attenuation in a subterranean estuary, representative of the southern coast of Cape Cod, Massachusetts","docAbstract":"A two-dimensional model was developed by the U.S. Geological Survey, in cooperation with the U.S. Environmental Protection Agency, to assess flow and chemical reaction associated with groundwater discharge through the subterranean estuary representative of coastal salt ponds of southern Cape Cod. The model simulated both the freshwater and saltwater flow systems and accounted for density-dependent flow, tidal fluctuation, and chemical reactivity among oxygen, dissolved organic carbon, nitrate, and ammonia. Not previously incorporated into one model, the interaction of these effects can now be simulated in the subterranean estuary context.
\nAn analysis of the flow system under mean-tide conditions was conducted first to provide the initial conditions for a subsequent analysis that included the effects of tidal fluctuations. Tidal fluctuations were simulated with a repeated couplet that represented a high tide-low tide sequence and alternating locations of head-dependent flux boundaries placed along the simulated seabed, above and below the levels of the respective high and low tides.
\nBoundary conditions for chemical species included nitrate in recharge, and oxygen and organic matter (including organic nitrogen) in infiltrating solutions of head-dependent boundaries. Reaction chemistry was limited to oxidative degradation of organic matter (including remineralization of ammonia) with oxygen or nitrate as electron acceptors and nitrification of ammonia in the presence of oxygen.
\nSimulations using the SEAWAT-2000 computer program resulted in two mixing zones-between freshwater and saltwater in a deep saltwater wedge and in an intertidal salt zone, which results from tidal fluctuation. The mixing zones are the principal locations where nitrogen attenuation reactions occurred-between organic matter in the saltwater zones of the aquifer and nitrate in the freshwater zone.
\nIn mean-tide PHT3D model simulations, 15 percent of nitrogen that is recharged was attenuated because of reaction with dissolved organic matter, a denitrification reaction that reduces nitrate to nitrogen gas. When a fluctuating tide was simulated, the amount of recharged nitrogen that was denitrified increased to 20 percent.
\nChemical reaction was controlled by the rate of mixing of freshwater and saltwater, which contained the reactants nitrate and dissolved organic matter, respectively, necessary for nitrogen attenuation reactions to take place. Reaction occurred in both the deep saltwater wedge and in an increased denitrification. However, mixing may also have been enhanced partly by numerical dispersion.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151085","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Colman, J.A., Carlson, C.S., and Robinson, C., 2015, Simulation of nitrogen attenuation in a subterranean estuary, representative of the southern coast of Cape Cod, Massachusetts: U.S. Geological Survey Open-File Report 2015-1085, vi, 30 p., https://doi.org/10.3133/ofr20151085.","productDescription":"vi, 30 p.","numberOfPages":"40","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-056161","costCenters":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"links":[{"id":301100,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20151085.jpg"},{"id":301098,"rank":1,"type":{"id":15,"text":"Index 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concentrations of sodium and chloride estimated from records of specific conductance were used to calculate loads of sodium and chloride during water year (WY) 2013 (October 1, 2012, through September 30, 2013) for tributaries to the Scituate Reservoir, Rhode Island. Streamflow and water-quality data used in the study were collected by the U.S. Geological Survey (USGS) or the Providence Water Supply Board (PWSB) in the cooperative study. Streamflow was measured or estimated by the USGS following standard methods at 23 streamgages; 14 of these streamgages are equipped with instrumentation capable of continuously monitoring water level, specific conductance, and water temperature. Water-quality samples were collected at 37 sampling stations by the PWSB and at 14 continuous-record streamgages by the USGS during WY 2013 as part of a long-term sampling program; all stations are in the Scituate Reservoir drainage area. Water-quality data collected by the PWSB are summarized by using values of central tendency and are used, in combination with measured (or estimated) streamflows, to calculate loads and yields (loads per unit area) of selected water-quality constituents for WY 2013.
\nThe largest tributary to the reservoir (the Ponaganset River, which was monitored by the USGS) contributed a mean streamflow of 30 cubic feet per second (ft3/s) to the reservoir during WY 2013. For the same time period, annual mean1 streamflows measured (or estimated) for the other monitoring stations in this study ranged from about 0.45 to about 19 ft3/s. Together, tributaries (equipped with instrumentation capable of continuously monitoring specific conductance) transported about 1,300,000 kilograms (kg) of sodium and 2,100,000 kg of chloride to the Scituate Reservoir during WY 2013; sodium and chloride yields for the tributaries ranged from 8,600 to 58,000 kilograms per square mile (kg/mi2) and from 14,000 to 97,000 kg/mi2, respectively.
\nAt the stations where water-quality samples were collected by the PWSB, the median of the median chloride concentrations was 18 milligrams per liter (mg/L), median nitrite concentration was 0.002 mg/L as nitrogen (N), median nitrate concentration was less than 0.01 mg/L as N, median orthophosphate concentration was 0.128 mg/L as phosphate, and median concentrations of total coliform bacteria and Escherichia coli (E. coli) were 330 and 15 colony-forming units per 100 milliliters (CFU/100mL), respectively. The medians of the median daily loads (and yields) of chloride, nitrite, nitrate, orthophosphate, and total coliform and E. coli bacteria were 100 kilograms per day (kg/d; 50 kilograms per day per square mile [kg/d/mi2]), 10 grams per day (g/d; 5.1 grams per day per square mile [g/d/mi2]), 73 g/d (28 g/d/mi2), 720 g/d (320 g/d/mi2), 21,000 colony-forming units per day (CFU×106/d; 8,700 CFU×106/d/mi2), and 1,000 CFU×106/d (510 CFU×106/d/mi2), respectively.
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