Steep declines in North American monarch butterfly (Danaus plexippus) populations have prompted continent-wide conservation efforts. While monarch monitoring efforts have existed for years, we lack a comprehensive approach to monitoring population vital rates integrated with habitat quality to inform adaptive management and effective conservation strategies. Building a geographically and ecologically representative dataset of monarchs and their habitat will improve these efforts. These data will help track long-term changes in the distribution and abundance of monarchs and their habitats, refine population and habitat models, and illuminate how conservation activities affect monarchs and their habitats. The Monarch Conservation Science Partnership developed the Integrated Monarch Monitoring Program (IMMP) to profile breeding habitats and their use by monarchs in North America. A spatially balanced random sampling framework guides site selection, while also allowing opportunistic inclusion of sites chosen by participants, such as conservation areas. The IMMP weaves new protocols together with those from existing monitoring programs to improve data compatibility for assessing milkweed (Asclepias spp.) density, nectar resources, monarch reproduction and survival, and adult monarch habitat use. Participants may select a protocol subset according to interests or local monitoring objectives, thereby maximizing contributions. Conservation partners, including public and private land managers, academic researchers, and citizen scientists contribute data to a national dataset available for analyses at multiple scales. We describe the program and its development, implementation elements that make the program robust and feasible, participation to date, and how IMMP data can advance research and conservation for monarchs, pollinators, and their habitats.
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Water resource managers are faced with the challenge of developing long and short term (emergency) stream restoration efforts that rely on the most suitable channel geometry for project design. A geomorphic dataset of new (2016, n=5) and previous (1999–2006, n=96) estimates of bankfull discharge and channel dimensions at U.S. Geological Survey streamflow-gaging stations was compiled to present and contrast the glaciated and unglaciated noncarbonate settings of southern New York and Pennsylvania that included selected areas of Maryland. Empirical models were developed by using simple linear regressions that relate bankfull discharge and channel geometry to drainage area (regional curves). Significant relations (p<0.05) were able to explain variability with coefficient of determination (R2 ) values of 0.89 for bankfull discharge, 0.94 for cross-sectional area, 0.87 for bankfull width, and 0.83 for bankfull depth. These regression relations for the glaciated noncarbonate settings of northern Pennsylvania and southern New York were able to provide a slightly better fit than regional curve models developed previously for the entire noncarbonate region of Pennsylvania. Although, the analysis of covariance (ANCOVA) results for comparison between regression equations for the glaciated and unglaciated settings showed that except for the significant intercept of bankfull discharge versus drainage area (F=8.26, p-value<0.005), the regression equations are not significantly different between the glaciated and unglaciated setting of Pennsylvania and southern New York. Therefore, data stratification by glaciation does not improve regional curves relations developed previously for the noncarbonate (glaciated and unglaciated) and carbonate settings of Pennsylvania and Maryland. Further analysis that incorporates data stratification or multivariate approaches based on mean annual runoff, precipitation, slope, stream classification, or other relevant parameters may optimize the accuracy and utility of statewide models. The new estimates of bankfull discharge and channel dimensions at streamflowgaging sites and updated drainage areas from StreamStats were incorporated into previously developed regional curves to produce an updated set of regression relations of bankfull discharge and channel geometry for the noncarbonate and carbonate settings of Pennsylvania and Maryland.
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York\",\"nation\":\"USA \"}}]}","edition":"Version 1.1: July 2020; Version 1.0: July 2018","contact":"Director, Pennsylvania Water Science Center
U.S. Geological Survey
215 Limekiln Road
New Cumberland, PA 17070
The USGS California Water Science Center is heavily involved in the measurement of flow and water quality parameters in the San Francisco Estuary, with support from many partner agencies. The California Department of Water Resources (DWR), through the Interagency Ecological Program (IEP) is one of those agencies. This article describes the resulting efforts and methodologies and provides examples of some of the uses of the data sets for science and management interests.
The DWR/IEP-funded flow and water quality network provides high resolution data in both space and time, over a large portion of the San Francisco Estuary. This measurement network has evolved over the preceding decades, and proven invaluable for both management and science interests, with particular relevance to water supply and endangered species issues. Presented below are a summary of the measurement network, some of the methods being utilized, and some interesting conditions that became evident during the recent drought that spanned Water Years (WY) 2013-2016, and the wet WY2017 (water year spans Oct 1-Sept 30).
","language":"English","publisher":"California Department of Water Resources","usgsCitation":"Work, P.A., and Downing-Kunz, M.A., 2018, State of the network: Long-term, high-frequency flow and water quality data in the San Francisco Estuary, California: Interagency Ecological Program (IEP) Newsletter, v. 32, no. 1, p. 59-64.","productDescription":"6 p.","startPage":"59","endPage":"64","ipdsId":"IP-098804","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":375085,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":375084,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://www.usgs.gov/center-news/usgs-science-work-san-francisco-bay-estuary"},{"id":375083,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://water.ca.gov/Programs/Environmental-Services/Interagency-Ecological-Program"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay Estuary","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.1622314453125,\n 36.756490329505176\n ],\n [\n -120.86608886718749,\n 36.756490329505176\n ],\n [\n -120.86608886718749,\n 38.45789034424927\n ],\n [\n -123.1622314453125,\n 38.45789034424927\n ],\n [\n -123.1622314453125,\n 36.756490329505176\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"32","issue":"1","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Work, Paul A. 0000-0002-2815-8040 pwork@usgs.gov","orcid":"https://orcid.org/0000-0002-2815-8040","contributorId":168561,"corporation":false,"usgs":true,"family":"Work","given":"Paul","email":"pwork@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":744156,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Downing-Kunz, Maureen A. 0000-0002-4879-0318 mdowning-kunz@usgs.gov","orcid":"https://orcid.org/0000-0002-4879-0318","contributorId":3690,"corporation":false,"usgs":true,"family":"Downing-Kunz","given":"Maureen","email":"mdowning-kunz@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":744157,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70195971,"text":"sir20185033 - 2018 - Characterization of stormwater runoff from bridge decks in eastern Massachusetts, 2014–16","interactions":[],"lastModifiedDate":"2020-05-19T13:33:40.660565","indexId":"sir20185033","displayToPublicDate":"2020-05-19T09:40:00","publicationYear":"2018","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":"2018-5033","title":"Characterization of stormwater runoff from bridge decks in eastern Massachusetts, 2014–16","docAbstract":"The quality of stormwater runoff from bridge decks (hereafter referred to as “bridge-deck runoff”) was characterized in a field study from August 2014 through August 2016 in which concentrations of suspended sediment (SS) and total nutrients were monitored. These new data were collected to supplement existing highway-runoff data collected in Massachusetts which were deficient in bridge-deck runoff concentration data. Monitoring stations were installed at three bridges maintained by the Massachusetts Department of Transportation in eastern Massachusetts (State Route 2A in the city of Boston, Interstate 90 in the town of Weston, and State Route 20 near Quinsigamond Village in the city of Worcester). The bridges had annual average daily traffic volumes from 21,200 to 124,000 vehicles per day; the land use surrounding the monitoring stations was 25 to 67 percent impervious.
Automatic-monitoring techniques were used to collect more than 160 flow-proportional composite samples of bridge-deck runoff. Samples were analyzed for concentrations of SS, loss on ignition of suspended solids (LOI), particulate carbon (PC), total phosphorus (TP), total dissolved nitrogen (DN), and particulate nitrogen (PN). The distribution of particle size of SS also was determined for composite samples. Samples of bridge-deck runoff were collected year round during rain, mixed precipitation, and snowmelt runoff and with different dry antecedent periods throughout the 2-year sampling period.
At the three bridge-deck-monitoring stations, median concentrations of SS in composite samples of bridge-deck runoff ranged from 1,490 to 2,020 milligrams per liter (mg/L); however, the range of SS in individual composites was vast at 44 to 142,000 mg/L. Median concentrations of SS were similar in composite samples collected from the State Route 2A and Interstate 90 bridge (2,010 and 2,020 mg/L, respectively), and lowest at the State Route 20 bridge (1,490 mg/L). Concentrations of coarse sediment (greater than 0.25 millimeters in diameter) dominated the SS matrix by more than an order of magnitude. Concentrations of LOI and PC in composite samples ranged from 15 to 1,740 mg/L and 6.68 to 1,360 mg/L, respectively, and generally represented less than 10 and 3 percent of the median mass of SS, respectively. Concentrations of TP in composite samples ranged from 0.09 to 7.02 mg/L; median concentrations of TP ranged from 0.505 to 0.69 mg/L and were highest on the bridge on State Route 2A in Boston. Concentrations of total nitrogen (TN) (sum DN and PN) in composite samples were variable (0.36 to 29 mg/L). Median DN (0.64 to 0.90 mg/L) concentrations generally represented about 40 percent of the TN concentration at each bridge and were similar to annual volume-weighted mean concentrations of nitrogen in precipitation in Massachusetts.
Nonparametric statistical methods were used to test for differences between sample constituent concentrations among the three bridges. These results indicated that there are no statistically significant differences for concentrations of SS, LOI, PC, and TP among the three bridges (one-way analysis of variance test on rank-transformed data, 95-percent confidence level). Test results for concentrations of TN in composite samples indicated that concentrations of TN collected on State Route 20 near Quinsigamond Village were significantly higher than those concentrations collected on State Route 2A in Boston and Interstate 90 near Weston. Median concentrations of TN were about 93 and 55 percent lower at State Route 2A and at Interstate 90, respectively, compared to the median concentrations of TN at State Route 20.
Samples of sediment were collected from five fixed locations on each bridge on three occasions during dry weather to calculate semiquantitative distributions of sediment yields on the bridge surface relative to the monitoring location. Mean yields of bridge-deck sediment during this study for State Route 2A in Boston, Interstate 90 near Weston, and State Route 20 near Quinsigamond Village were 1,500, 250, and 5,700 pounds per curb-mile, respectively. Sediment yields at each sampling location varied widely (26 to 25,000 pounds per curb-mile) but were similar to yields reported elsewhere in Massachusetts and the United States. Yields calculated for each sampling location indicated that the sediment was not evenly distributed across each bridge in this study for plausible reasons such as bridge slope, vehicular tracking, and bridge deterioration.
Bridge-deck sediment quality was largely affected by the distribution of sediment particle size. Concentrations of TP in the fine sediment-size fraction (less than 0.0625 millimeter in diameter) of samples of bridge-deck sediment were about 6 times greater than in the coarse size fraction. Concentrations for many total-recoverable metals were 2 to 17 times greater in the fine size fraction compared to concentrations in the coarse size fraction (greater than or equal to 0.25 millimeter in diameter), and concentrations of total-recoverable copper and lead in the fine size fraction were 2 to 65 times higher compared to concentrations in the intermediate (greater than or equal to 0.0625 to 0.25 millimeter in diameter) or the coarse size fraction. However, the proportion of sediment particles less than 0.0625 millimeter in diameter in composite samples of bridge-deck runoff was small (median values range from 4 to 8 percent at each bridge) compared to the larger sediment particle-size mass. As a result, more than 50 percent of the sediment-associated TP, aluminum, chromium, manganese, and nickel was estimated to be associated with the coarse size fraction of the SS load. In contrast, about 95 percent of the estimated sediment-associated copper concentration was associated with the fine size fraction of the SS load.
Version 1.0.2 of the Stochastic Empirical Loading and Dilution Model was used to simulate long-term (29–30-year) concentrations and annual yields of SS, TP, and TN in bridge-deck runoff and in discharges from a hypothetical stormwater treatment best-management practice structure. Three methods (traditional statistics, robust statistics, and L-moments) were used to calculate statistics for stochastic simulations because the high variability in measured concentration values during the field study resulted in extreme simulated concentrations. Statistics of each dataset, including the average, standard deviation, and skew of the common (base 10) logarithms, for each of the three bridges, and for a lumped dataset, were calculated and used for simulations; statistics representing the median of statistics calculated for the three bridges also were used for simulations. These median statistics were selected for the interpretive simulations so that the simulations could be used to estimate concentrations and yields from other, unmonitored bridges in Massachusetts. Comparisons of the standard and robust statistics indicated that simulation results with either method would be similar, which indicated that the large variability in simulated results was not caused by a few outliers. Comparison to statistics calculated by the L-moments methods indicated that L-moments do not produce extreme concentrations; however, they also do not produce results that represent the bulk of concentration data.
The runoff-quality risk analysis indicated that bridge-deck runoff would exceed discharge standards commonly used for large, advanced wastewater treatment plants, but that commonly used stormwater best-management practices may reduce the percentage of exceedances by one-half. Results of simulations indicated that long-term average yields of TN, TP, and SS may be about 21.4, 6.44, and 40,600 pounds per acre per year, respectively. These yields are about 1.3, 3.4, and 16 times simulated ultra-urban highway yields in Massachusetts; however, simulations indicated that use of a best-management practice structure to treat bridge-deck runoff may reduce discharge yields to about 10, 2.8, and 4,300, pounds per acre per year, respectively.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185033","isbn":"978-1-4113-4222-4","usgsCitation":"Smith, K.P., Sorenson, J.R., and Granato, G.E., 2018, Characterization of stormwater runoff from bridge decks in eastern Massachusetts, 2014–16: U.S. Geological Survey Scientific Investigations Report 2018–5033, 73 p., https://doi.org/10.3133/sir20185033.","productDescription":"xiii, 73 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-088034","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":374915,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5033/sir20185033.pdf","text":"Report","size":"4.01 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5033"},{"id":353906,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5033/coverthb.jpg"}],"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 -71.98516845703125,\n 41.97582726102573\n ],\n [\n -70.7904052734375,\n 41.97582726102573\n ],\n [\n -70.7904052734375,\n 42.827638636242284\n ],\n [\n -71.98516845703125,\n 42.827638636242284\n ],\n [\n -71.98516845703125,\n 41.97582726102573\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
Director, New Jersey Water Science Center
U.S. Geological Survey
3450 Princeton Pike
Lawrenceville, NJ 08648
The use of water in the United States is arguably one of the most important factors determining water availability at any specific place and time. Numerous local, State, and Federal entities develop, compile, and report water-use data, which can lead to confusing or conflicting information. This report was authored jointly by the U.S. Geological Survey (USGS) and Bureau of Reclamation (Reclamation) to compare and contrast the two agencies’ water-use information programs in the Colorado River Basin. The report also describes the legal drivers for each program, clarifies confusing terminology, compares the methods used, and contrasts the information reported by each agency. This detailed comparison demonstrates that these two Federal agencies have different missions, different programmatic drivers, and different user communities, all of which lead to different approaches to water-use data collection, analysis, and reporting. This report highlights those differences and explains why the USGS and Reclamation programs exist and how the data serve different user communities. Even though the two water-use programs are different by design and purpose, the program comparison presented in this report has identified opportunities for closer coordination and sharing of information between the USGS and Reclamation, as well as program components where agency collaboration can improve water-use estimate methodologies. This comparison effort emphasizes that it is incumbent upon each agency to clearly define the meaning of the terms used and the appropriate application of the reported information to avoid confusion or the accidental misuse of the information. An additional benefit of this comparison effort is the formation of a joint USGS/Reclamation water-use team that will continue to investigate opportunities to expand and coordinate future water-use data compilation and reporting.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185021","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Bruce, B.W., Prairie, J.R., Maupin, M.A., Dodds, J.R., Eckhardt, D.W., Ivahnenko, T.I., Matuska, P.J., Evenson, E.J., and Harrison, A.D., 2018, Comparison of U.S. Geological Survey and Bureau of Reclamation water-use reporting in the Colorado River Basin (ver. 1.1, September 2019): U.S. Geological Survey Scientific Investigations Report 2018–5021, 41 p., https://doi.org/10.3133/sir20185021.\n","productDescription":"vi, 41 p.","numberOfPages":"50","onlineOnly":"Y","ipdsId":"IP-089692","costCenters":[{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true}],"links":[{"id":353709,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5021/sir20185021.pdf","text":"Report","size":"10.1 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U.S. Geological Survey
988 National Center
12201 Sunrise Valley Drive
Reston, VA 20192
Sediment pulses can cause widespread, complex changes to rivers and coastal regions. Quantifying landscape response to sediment-supply changes is a long-standing problem in geomorphology, but the unanticipated nature of most sediment pulses rarely allows for detailed measurement of associated landscape processes and evolution. The intentional removal of two large dams on the Elwha River (Washington, USA) exposed ~30 Mt of impounded sediment to fluvial erosion, presenting a unique opportunity to quantify source-to-sink river and coastal responses to a massive sediment-source perturbation. Here we evaluate geomorphic evolution during and after the sediment pulse, presenting a 5-year sediment budget and morphodynamic analysis of the Elwha River and its delta. Approximately 65% of the sediment was eroded, of which only ~10% was deposited in the fluvial system. This restored fluvial supply of sand, gravel, and wood substantially changed the channel morphology. The remaining ~90% of the released sediment was transported to the coast, causing ~60 ha of delta growth. Although metrics of geomorphic change did not follow simple time-coherent paths, many signals peaked 1–2 years after the start of dam removal, indicating combined impulse and step-change disturbance responses.
","language":"English","publisher":"Springer Nature","doi":"10.1038/s41598-018-30817-8","usgsCitation":"Ritchie, A.C., Warrick, J.A., East, A.E., Magirl, C.S., Stevens, A.W., Bountry, J.A., Randle, T.J., Curran, C.A., Hilldale, R.C., Duda, J.J., Miller, I.M., Pess, G.R., Eidam, E., Foley, M.M., McCoy, R., and Ogston, A.S., 2018, Morphodynamic evolution following sediment release from the world’s largest dam removal: Scientific Reports, v. 8, 13279, 13 p., https://doi.org/10.1038/s41598-018-30817-8.","productDescription":"13279, 13 p.","ipdsId":"IP-093205","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true},{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":468150,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-018-30817-8","text":"Publisher Index Page"},{"id":366979,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Elwha Dam, Elwha River, Olympic National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.61679077148438,\n 47.96050238891509\n ],\n [\n -123.61679077148438,\n 48.15600899174947\n ],\n [\n -123.475341796875,\n 48.15600899174947\n ],\n [\n -123.475341796875,\n 47.96050238891509\n ],\n [\n -123.61679077148438,\n 47.96050238891509\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","noUsgsAuthors":false,"publicationDate":"2018-09-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Ritchie, Andrew C. aritchie@usgs.gov","contributorId":4984,"corporation":false,"usgs":true,"family":"Ritchie","given":"Andrew","email":"aritchie@usgs.gov","middleInitial":"C.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":769402,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Warrick, Jonathan A. 0000-0002-0205-3814 jwarrick@usgs.gov","orcid":"https://orcid.org/0000-0002-0205-3814","contributorId":167736,"corporation":false,"usgs":true,"family":"Warrick","given":"Jonathan","email":"jwarrick@usgs.gov","middleInitial":"A.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":769403,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"East, Amy E. 0000-0002-9567-9460 aeast@usgs.gov","orcid":"https://orcid.org/0000-0002-9567-9460","contributorId":196364,"corporation":false,"usgs":true,"family":"East","given":"Amy","email":"aeast@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":769404,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Magirl, Christopher S. 0000-0002-9922-6549 magirl@usgs.gov","orcid":"https://orcid.org/0000-0002-9922-6549","contributorId":1822,"corporation":false,"usgs":true,"family":"Magirl","given":"Christopher","email":"magirl@usgs.gov","middleInitial":"S.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true},{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":769405,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stevens, Andrew W. 0000-0003-2334-129X astevens@usgs.gov","orcid":"https://orcid.org/0000-0003-2334-129X","contributorId":139313,"corporation":false,"usgs":true,"family":"Stevens","given":"Andrew","email":"astevens@usgs.gov","middleInitial":"W.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":769406,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bountry, Jennifer A.","contributorId":30114,"corporation":false,"usgs":false,"family":"Bountry","given":"Jennifer","email":"","middleInitial":"A.","affiliations":[{"id":7183,"text":"U.S. Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":769407,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Randle, Timothy J.","contributorId":90994,"corporation":false,"usgs":false,"family":"Randle","given":"Timothy","email":"","middleInitial":"J.","affiliations":[{"id":7183,"text":"U.S. Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":769408,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Curran, Christopher A. 0000-0001-8933-416X ccurran@usgs.gov","orcid":"https://orcid.org/0000-0001-8933-416X","contributorId":1650,"corporation":false,"usgs":true,"family":"Curran","given":"Christopher","email":"ccurran@usgs.gov","middleInitial":"A.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":769409,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hilldale, Robert C.","contributorId":139315,"corporation":false,"usgs":false,"family":"Hilldale","given":"Robert","email":"","middleInitial":"C.","affiliations":[{"id":6736,"text":"Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":769410,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Duda, Jeffrey J. 0000-0001-7431-8634 jduda@usgs.gov","orcid":"https://orcid.org/0000-0001-7431-8634","contributorId":148954,"corporation":false,"usgs":true,"family":"Duda","given":"Jeffrey","email":"jduda@usgs.gov","middleInitial":"J.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":772301,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Miller, Ian M. 0000-0002-3289-6337","orcid":"https://orcid.org/0000-0002-3289-6337","contributorId":41951,"corporation":false,"usgs":false,"family":"Miller","given":"Ian","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":769412,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Pess, George R.","contributorId":13501,"corporation":false,"usgs":false,"family":"Pess","given":"George","email":"","middleInitial":"R.","affiliations":[{"id":6578,"text":"National Marine Fisheries Service, Seattle, WA 98112, USA","active":true,"usgs":false}],"preferred":false,"id":769413,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Eidam, Emily","contributorId":139311,"corporation":false,"usgs":false,"family":"Eidam","given":"Emily","email":"","affiliations":[{"id":12729,"text":"UW","active":true,"usgs":false}],"preferred":false,"id":769414,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Foley, Melissa M. 0000-0002-5832-6404 mfoley@usgs.gov","orcid":"https://orcid.org/0000-0002-5832-6404","contributorId":4861,"corporation":false,"usgs":true,"family":"Foley","given":"Melissa","email":"mfoley@usgs.gov","middleInitial":"M.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":769415,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"McCoy, Randall","contributorId":194430,"corporation":false,"usgs":false,"family":"McCoy","given":"Randall","affiliations":[],"preferred":false,"id":769416,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Ogston, Andrea S.","contributorId":12119,"corporation":false,"usgs":true,"family":"Ogston","given":"Andrea","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":769417,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}} ,{"id":70205455,"text":"70205455 - 2018 - Thresholds of lake and reservoir connectivity in river networks control nitrogen removal","interactions":[],"lastModifiedDate":"2020-09-01T14:05:16.435219","indexId":"70205455","displayToPublicDate":"2019-07-17T18:32:09","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2842,"text":"Nature Communications","active":true,"publicationSubtype":{"id":10}},"title":"Thresholds of lake and reservoir connectivity in river networks control nitrogen removal","docAbstract":"Lakes, reservoirs, and other ponded waters are ubiquitous features of the aquatic landscape, yet their cumulative role in nitrogen removal in large river basins is often unclear. Here we use predictive modeling, together with comprehensive river water quality, land use, and hydrography datasets, to examine and explain the influences of more than 18,000 ponded waters on nitrogen removal through river networks of the Northeastern United States. Thresholds in pond density where ponded waters become important features to regional nitrogen removal are identified and shown to vary according to a ponded waters’ relative size, network position, and degree of connectivity to the river network, which suggests worldwide importance of these new metrics. Consideration of the interacting physical and biological factors, along with thresholds in connectivity, reveal where, why, and how much ponded waters function differently than streams in removing nitrogen, what regional water quality outcomes may result, and in what capacity management strategies could most effectively achieve desired nitrogen loading reduction.
","language":"English","publisher":"Nature","doi":"10.1038/s41467-018-05156-x","usgsCitation":"Schmadel, N.M., Harvey, J., Alexander, R., Schwarz, G., Moore, R., Eng, K., Gomez-Velez, J., Boyer, E.W., and Scott, D., 2018, Thresholds of lake and reservoir connectivity in river networks control nitrogen removal: Nature Communications, v. 9, 2779, 10 p., https://doi.org/10.1038/s41467-018-05156-x.","productDescription":"2779, 10 p.","ipdsId":"IP-093046","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":468151,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41467-018-05156-x","text":"Publisher Index Page"},{"id":367536,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Connecticut, Delaware, District of Columbia, Maine, Maryland, Massachusetts, New Hampshire, New Jersey, New York, Pennsylvania, Rhode island, Vermont, West Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -66.884765625,\n 44.37098696297173\n ],\n [\n -66.884765625,\n 44.99588261816546\n ],\n [\n -67.67578124999999,\n 45.82879925192134\n ],\n [\n -67.8515625,\n 47.368594345213374\n ],\n [\n -69.2138671875,\n 47.517200697839414\n ],\n [\n -71.19140625,\n 45.398449976304086\n ],\n [\n -71.8505859375,\n 44.99588261816546\n ],\n [\n -74.3994140625,\n 45.182036837015886\n ],\n [\n -76.81640625,\n 42.74701217318067\n ],\n [\n -77.6953125,\n 40.81380923056958\n ],\n [\n -79.40917968749999,\n 39.40224434029275\n ],\n [\n -79.27734374999999,\n 37.50972584293751\n ],\n [\n -78.9697265625,\n 36.914764288955936\n ],\n [\n -75.234375,\n 36.38591277287651\n ],\n [\n -73.125,\n 40.111688665595956\n ],\n [\n -69.2578125,\n 41.11246878918088\n ],\n [\n -66.884765625,\n 44.37098696297173\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-07-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Schmadel, Noah M.","contributorId":219098,"corporation":false,"usgs":false,"family":"Schmadel","given":"Noah","email":"","middleInitial":"M.","affiliations":[{"id":39961,"text":"USGS Post-Doc","active":true,"usgs":false}],"preferred":false,"id":771257,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harvey, Judson","contributorId":219097,"corporation":false,"usgs":true,"family":"Harvey","given":"Judson","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":771256,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Alexander, Richard 0000-0001-9166-0626 ralex@usgs.gov","orcid":"https://orcid.org/0000-0001-9166-0626","contributorId":219099,"corporation":false,"usgs":true,"family":"Alexander","given":"Richard","email":"ralex@usgs.gov","affiliations":[],"preferred":true,"id":771258,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schwarz, Gregory E. 0000-0002-9239-4566 gschwarz@usgs.gov","orcid":"https://orcid.org/0000-0002-9239-4566","contributorId":219100,"corporation":false,"usgs":true,"family":"Schwarz","given":"Gregory E.","email":"gschwarz@usgs.gov","affiliations":[],"preferred":false,"id":771259,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Moore, Richard","contributorId":219101,"corporation":false,"usgs":true,"family":"Moore","given":"Richard","affiliations":[],"preferred":true,"id":771260,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Eng, Ken 0000-0001-6838-5849 keng@usgs.gov","orcid":"https://orcid.org/0000-0001-6838-5849","contributorId":3580,"corporation":false,"usgs":true,"family":"Eng","given":"Ken","email":"keng@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":771261,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gomez-Velez, Jesus D.","contributorId":219103,"corporation":false,"usgs":false,"family":"Gomez-Velez","given":"Jesus D.","affiliations":[{"id":39962,"text":"Department of Earth & Environmental Science, New Mexico Institute of Mining and Technology, Socorro, New Mexico, USA","active":true,"usgs":false}],"preferred":false,"id":771262,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Boyer, Elizabeth W.","contributorId":44659,"corporation":false,"usgs":false,"family":"Boyer","given":"Elizabeth","email":"","middleInitial":"W.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":771263,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Scott, Durelle","contributorId":219088,"corporation":false,"usgs":false,"family":"Scott","given":"Durelle","affiliations":[{"id":39959,"text":"Virginia Tech.","active":true,"usgs":false}],"preferred":false,"id":771264,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70195984,"text":"tm4B5 - 2018 - Guidelines for determining flood flow frequency — Bulletin 17C","interactions":[{"subject":{"id":70275162,"text":"70275162 - 1982 - Guidelines for determining flood flow frequency: Bulletin #17B of the Hydrology Subcommittee","indexId":"70275162","publicationYear":"1982","noYear":false,"title":"Guidelines for determining flood flow frequency: Bulletin #17B of the Hydrology Subcommittee"},"predicate":"SUPERSEDED_BY","object":{"id":70195984,"text":"tm4B5 - 2018 - Guidelines for determining flood flow frequency — Bulletin 17C","indexId":"tm4B5","publicationYear":"2018","noYear":false,"title":"Guidelines for determining flood flow frequency — Bulletin 17C"},"id":1}],"lastModifiedDate":"2024-03-28T13:15:23.826606","indexId":"tm4B5","displayToPublicDate":"2019-07-16T10:55:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"4-B5","title":"Guidelines for determining flood flow frequency — Bulletin 17C","docAbstract":"Accurate estimates of flood frequency and magnitude are a key component of any effective nationwide flood risk management and flood damage abatement program. In addition to accuracy, methods for estimating flood risk must be uniformly and consistently applied because management of the Nation’s water and related land resources is a collaborative effort involving multiple actors including most levels of government and the private sector.
Flood frequency guidelines have been published in the United States since 1967, and have undergone periodic revisions. In 1967, the U.S. Water Resources Council presented a coherent approach to flood frequency with Bulletin 15, “A Uniform Technique for Determining Flood Flow Frequencies.” The method it recommended involved fitting the log-Pearson Type III distribution to annual peak flow data by the method of moments.
The first extension and update of Bulletin 15 was published in 1976 as Bulletin 17, “Guidelines for Determining Flood Flow Frequency” (Guidelines). It extended the Bulletin 15 procedures by introducing methods for dealing with outliers, historical flood information, and regional skew. Bulletin 17A was published the following year to clarify the computation of weighted skew. The next revision of the Bulletin, the Bulletin 17B, provided a host of improvements and new techniques designed to address situations that often arise in practice, including better methods for estimating and using regional skew, weighting station and regional skew, detection of outliers, and use of the conditional probability adjustment.
The current version of these Guidelines are presented in this document, denoted Bulletin 17C. It incorporates changes motivated by four of the items listed as “Future Work” in Bulletin 17B and 30 years of post-17B research on flood processes and statistical methods. The updates include: adoption of a generalized representation of flood data that allows for interval and censored data types; a new method, called the Expected Moments Algorithm, which extends the method of moments so that it can accommodate interval data; a generalized approach to identification of low outliers in flood data; and an improved method for computing confidence intervals.
Federal agencies are requested to use these Guidelines in all planning activities involving water and related land resources. State, local, and private organizations are encouraged to use these Guidelines to assure uniformity in the flood frequency estimates that all agencies concerned with flood risk should use for Federal planning decisions.
This revision is adopted with the knowledge and understanding that review of these procedures will be ongoing. Updated methods will be adopted when warranted by experience and by examination and testing of new techniques.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Section B: Surface water in Book 4: Hydrologic analysis and interpretation","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm4B5","isbn":"978-1-4113-4223-1","usgsCitation":"England, J.F., Jr., Cohn, T.A., Faber, B.A., Stedinger, J.R., Thomas, W.O., Jr., Veilleux, A.G., Kiang, J.E., and Mason, R.R., Jr., 2018, Guidelines for determining flood flow frequency — Bulletin 17C (ver. 1.1, May 2019): U.S. Geological Survey Techniques and Methods, book 4, chap. B5, 148 p., https://doi.org/10.3133/tm4B5.","productDescription":"xiii, 148 p.","numberOfPages":"168","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-065340","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":352936,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://acwi.gov/hydrology/Frequency/b17c/","text":"Advisory Committee on Water Information - Bulletin 17C"},{"id":352416,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/04/b05/tm4b5.pdf","text":"Report","size":"29.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"TM 4-B5"},{"id":352415,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/04/b05/coverthb2.jpg"},{"id":399694,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_107081.htm"},{"id":363942,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/tm/04/b05/versionHist.pdf","size":"153 KB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Georgia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.5178,\n 33.9703\n ],\n [\n -83.8928,\n 33.9703\n ],\n [\n -83.8928,\n 34.2625\n ],\n [\n -84.5178,\n 34.2625\n ],\n [\n -84.5178,\n 33.9703\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.1: May 31, 2019","publicComments":"This report is Chapter 5 of Section B: Surface water in Book 4: Hydrologic analysis and interpretation.","contact":"Chief, Analysis and Prediction Branch
Integrated Modeling and Prediction Division
Water Mission Area
U.S. Geological Survey
12201 Sunrise Valley Drive
Mail Stop 415
Reston, VA 20192
Executive Summary
Drainage for agricultural production over the past 150 years has been an integral component of human-driven change to Minnesota’s rural landscapes.
Benefits of drainage
Historically, poorly drained soils across much of the State would often remain saturated or flooded after spring snowmelt, preventing timely farm operations such as tilling and planting crops (Arneman, 1963). Installation of agricultural drainage, both surface ditches and subsurface drainage, accelerated transport of water off farm fields and imparted producers higher crop yields (Beauchamp, 1987; Stoner and others, 1993). Agricultural drainage offered many other benefits such as preventing crop drown out, aerating the soil profile for improved plant growth, limiting surface runoff and soil erosion, and allowing farmers better access to croplands (Fausey and others, 1987). Without agricultural drainage on much of Minnesota’s croplands, it would have been difficult to realize high enough crop yields to remain economically viable.
Environmental concerns
While drainage of Minnesota croplands provided the benefits mentioned above, several environmental concerns result. These include wetland loss, degradation of downstream water quality, and reduced [potential for] recharge.
Early agricultural drainage efforts (pre-20th century) led to the disappearance of much of Minnesota’s natural wetlands. Increased focus on preventing or mitigating wetland loss over the last 50 years has helped curtail further losses, even as agricultural drainage proceeds. Prior to establishment of Minnesota statehood, wetlands accounted for more than 10 million acres in Minnesota, including prairie wetlands, peatlands, and forest wetlands that comprised approximately 19 percent of the total land area (Palmer, 1915; King, 1980). In 2018, only half of Minnesota’s pre-settlement wetlands remain, mostly in parts of the State that have not experienced widespread drainage, such as northern Minnesota.
Water-quality monitoring has shown that agricultural drainage, in particular the practice of subsurface drainage, provides a direct flow path for nutrient (nitrogen and soluble phosphorus) losses to surface water resources. The negative consequences of agricultural drainage on surface water quality are well documented (for example, Dinnes and others, 2002; Kladivko and others, 2004; Richards and others, 2008; Rozemeijer and others, 2010; Schottler and others, 2013). Agricultural basins with a high percentage of agricultural drainage have been implicated as part of the cause of the Gulf of Mexico hypoxia zone due to excessive nitrogen export (Goolsby and Battaglin, 2001; Randall and Mulla, 2001).
The connection of hydrological effects of agricultural subsurface drainage on groundwater recharge and aquifers, on the other hand, has not been well-established. Agricultural subsurface drainage intercepts infiltrating water below croplands and directly discharges the water to nearby surface waters. However, the size of the water balance shift from drained water that would have evapotranspired or run off the land to drained water that would recharge underlying aquifers has been poorly characterized (Schuh, 2008).
Drain Tiles and Groundwater
Given the poor accounting of subsurface drainage effects on groundwater resources, the Minnesota Ground Water Association (MGWA) deemed it imperative that we document these effects so that groundwater resources in agricultural regions with substantial drainage can be effectively managed. This white paper documents the relations of drain tiles and groundwater resources and discusses the historical significance of agricultural drainage practices, the recognized positive benefits and potential negative consequences of agricultural drainage practices, and the gaps in understanding of the connections between agricultural drainage and groundwater resources.
The major messages emerged from the findings of this white paper are:
In 2015, approximately 8,720 million gallons per day (Mgal/d) of water was withdrawn from groundwater and surface-water sources in Louisiana, a 2.6 percent increase from 2010. Total groundwater withdrawals were about 1,750 Mgal/d, an increase of 12 percent from 2010, and total surface-water withdrawals were about 6,970 Mgal/d, an increase of 0.44 percent from 2010 to 2015.
Total water withdrawals, in Mgal/d, in 2015 for the various categories of use were as follows: public supply—715, industry—2,155, power generation—4,265, rural domestic—39, livestock—6, rice irrigation—825, general irrigation—225, and aquaculture—490. From 2010 to 2015, Louisiana’s total withdrawals for public supply decreased by 3.4 percent, industry increased by 5.7 percent, power generation decreased by 3.9 percent, rural domestic decreased by 4.1 percent, livestock decreased by 21 percent, rice irrigation increased by 20 percent, general irrigation decreased by 6.0 percent, and aquaculture increased by 58 percent.
About 48 percent (approximately 850 Mgal/d) of all groundwater withdrawn was from the Chicot aquifer system and 22 percent (approximately 385 Mgal/d) was withdrawn from the Mississippi River alluvial aquifer. Since 2010, withdrawals from the Chicot aquifer system increased by 30 percent and withdrawals from the Mississippi River alluvial aquifer decreased by 2.9 percent.
About 70 percent (4,905 Mgal/d) of all surface water withdrawn was from the Mississippi River mainstem. This value represents a 1.1-percent decrease in withdrawals from 2010 to 2015.
All water-withdrawal and water-use data presented in this report should be considered estimates. Because of rounding, totals and percentages presented in the tables, figures, and text in the report may differ slightly from totals or percentages calculated individually
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Pierre 0000-0002-3967-9036 psargent@usgs.gov","orcid":"https://orcid.org/0000-0002-3967-9036","contributorId":1228,"corporation":false,"usgs":true,"family":"Sargent","given":"B.","email":"psargent@usgs.gov","middleInitial":"Pierre","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":758608,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70201558,"text":"sim3402 - 2018 - Surficial materials of Massachusetts—A 1:24,000-scale geologic map database","interactions":[],"lastModifiedDate":"2022-02-03T15:37:52.987287","indexId":"sim3402","displayToPublicDate":"2019-03-01T11:30:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3402","displayTitle":"Surficial Materials of Massachusetts—A 1:24,000-Scale Geologic Map Database","title":"Surficial materials of Massachusetts—A 1:24,000-scale geologic map database","docAbstract":"The surficial materials geologic map database defines the distribution of nonlithified earth materials at the land surface in the 189 7.5-minute, 1:24,000-scale quadrangles that cover the Commonwealth of Massachusetts (index map). Across the State, these materials range in thickness from a few feet to more than 500 feet (ft). In some places, surficial materials are absent where bedrock is at the land surface. The geologic map database differentiates surficial materials of Quaternary age on the basis of their lithologic characteristics (such as grain size and sedimentary structures), constructional geomorphic features, stratigraphic relationships, and age. The mapped distribution of surficial materials defines the areas of exposed bedrock and the boundaries between glacial till, glacial stratified deposits, and overlying postglacial deposits at a 1:24,000-scale level of accuracy.
Most of the surficial materials in Massachusetts are deposits of the last two continental ice sheets that covered all of New England in the latter part of the Pleistocene ice age. The glacial deposits are divided into two broad categories, glacial till and moraine deposits, and glacial stratified deposits. Widespread till deposits were laid down directly on bedrock or on semi-consolidated coastal plain strata by glacier ice. Tills in thick-till (>15 ft thick) drumlin landforms are found in all parts of the State. Areas of shallow bedrock contain thin discontinuous till deposits and numerous bedrock outcrops, and are located chiefly in rocky upland areas. Moraine deposits related to glacial ice lobes of the last ice sheet are located mostly in southeastern Massachusetts. Glacial stratified deposits are concentrated in valleys and lowland areas and were laid down by glacial meltwater in streams, lakes, and the sea in front of the retreating ice margin during the last deglaciation. Postglacial deposits, primarily flood-plain alluvium and swamp deposits, make up a lesser proportion of the unconsolidated materials.
The geodatabase included with this report contains MapUnitPolys, MapUnitOverlayPolys, and OverlayPolys, which show the distribution of geologic units that cover the entire map area and are intended for use at quadrangle scale (1:24,000). These data layers can be clipped by quadrangle or by town boundary. Unlike the units in conventional geologic maps, the digitally defined MapUnitOverlayPolys are arranged in order according to superposition. The polygons for till and bedrock are on the bottom and are overlain by the succeeding stratified deposits; these materials are shown everywhere they occur, including beneath postglacial deposits such as swamp deposits, and also beneath water bodies. The postglacial deposits are on top because these materials overlie the other, older deposits. Instructions for using the digital files are included in the README file. A series of map figures in the pamphlet illustrates the stacking of geologic units in a portion of the Mount Toby quadrangle. The BaseMaps folder contains the 1:24,000-scale topographic base map images (1944–1977 editions) used for this compilation.
This report supersedes U.S. Geological Survey Open-File Reports 2006-1260-A, -B, -C, -D, -E, -F, -G, and -I.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3402","collaboration":"Prepared in cooperation with the Commonwealth of Massachusetts, Massachusetts Geological Survey and Executive Office for Administration and Finance","usgsCitation":"Stone, J.R., Stone, B.D., DiGiacomo-Cohen, M.L., and Mabee, S.B., comps., 2018, Surficial materials of Massachusetts—A 1:24,000-scale geologic map database: U.S. Geological Survey Scientific Investigations Map 3402, 189 sheets, scale 1:24,000; index map, scale 1:250,000; 58-p. pamphlet; and geodatabase files, https://doi.org/10.3133/sim3402.","productDescription":"Pamphlet: iv, 58 p.; Index Map; Quandrangle Map Sheets; Metadata; Read Me; Spatial Data","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-066389","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":361110,"rank":9,"type":{"id":23,"text":"Spatial 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MB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- sim3402_simple.zip contains an automatic translation of most of the contents of SIM3402.gdb into simple flat shapefiles, and contains metadata"},{"id":361232,"rank":10,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sim/3402/sim3402_open.zip","text":"Geodatabase","size":"311 MB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- sim3402_open.zip contains a complete, automatic translation of SIM3402.gdb into shapefiles and other files, and contains metadata"},{"id":361577,"rank":8,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sim/3402/sim3402_metadata.xml","text":"SIM 3402 - Metadata","size":"29.6 KB xml"},{"id":361200,"rank":7,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sim/3402/sim3402_metadata.txt","text":"SIM 3402 - Metadata","size":"35.1 KB","linkFileType":{"id":2,"text":"txt"}},{"id":361199,"rank":6,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3402/sim3402_quadranglespdfs.zip","text":"Maps of Quadrangles 1–189","size":"3.12 GB","linkFileType":{"id":6,"text":"zip"}},{"id":361334,"rank":5,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3402/sim3402_quadrangle","text":"Individual Quadrangle Map Sheets","size":"938 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":361201,"rank":4,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3402/sim3402_index_map.pdf","text":"Index Map","size":"25.9 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":361100,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3402/sim3402.pdf","text":"Report Pamphlet","size":"22.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3402"}],"country":"United 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\"}}]}","contact":"Florence Bascom Geoscience Center
(Formerly Eastern Geology and Paleoclimate Science Center)
U.S. Geological Survey
926A National Center
12201 Sunrise Valley Drive
Reston, VA 20192
High productivity temperate wetlands that accrete peat via belowground biomass (peatlands) may be managed for climate mitigation benefits due to their global distribution and notably negative emissions of atmospheric carbon dioxide (CO2) through rapid storage of carbon (C) in anoxic soils. Net emissions of additional greenhouse gases (GHG)—methane (CH4) and nitrous oxide (N2O)—are more difficult to predict and monitor due to fine-scale temporal and spatial variability, but can potentially reverse the climate mitigation benefits resulting from CO2 uptake. To support management decisions and modeling, we collected continuous 96 hour high frequency GHG flux data for CO2, CH4 and N2O at multiple scales—static chambers (1 Hz) and eddy covariance (10 Hz)—during peak productivity in a well-studied, impounded coastal peatland in California's Sacramento Delta with high annual rates of C fluxes, sequestering 2065 ± 150 g CO2 m−2 y−1 and emitting 64.5 ± 2.4 g CH4 m−2 y−1. Chambers (n = 6) showed strong spatial variability along a hydrologic gradient from inlet to interior plots. Daily (24 hour) net CO2 uptake (NEE) was highest near inlet locations and fell dramatically along the flowpath (−25 to −3.8 to +2.64 g CO2 m−2 d−1). In contrast, daily net CH4 flux increased along the flowpath (0.39 to 0.62 to 0.88 g CH4 m−2d−1), such that sites of high daily CO2 uptake were sites of low CH4 emission. Distributed, continuous chamber data exposed five novel insights, and at least two important datagaps for wetland GHG management, including: (1) increasing dominance of CH4 ebullition fluxes (15%–32% of total) along the flowpath and (2) net negative N2O flux across all sites as measured during a 4 day period of peak biomass (−1.7 mg N2O m−2 d−1; 0.51 g CO2 eq m−2 d−1). The net negative emissions of re-established peat-accreting wetlands are notably high, but may be poorly estimated by models that do not consider within-wetland spatial variability due to water flowpaths.
","language":"English","publisher":"IOP Science","doi":"10.1088/1748-9326/aaae74","usgsCitation":"Windham-Myers, L., Bergamaschi, B.A., Anderson, F.A., Knox, S., Miller, R., and Fujii, R., 2018, Potential for negative emissions of greenhouse gases (CO2, CH4 and N2O) through coastal peatland re-establishment: Novel insights from high frequency flux data at meter and kilometer scales: Environmental Research Letters, v. 13, no. 4, p. 1-14, https://doi.org/10.1088/1748-9326/aaae74.","productDescription":"Article 045005; 14 p.","startPage":"1","endPage":"14","ipdsId":"IP-091738","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":468152,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/1748-9326/aaae74","text":"Publisher Index Page"},{"id":361209,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento–San Joaquin Delta","volume":"13","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Windham-Myers, Lisamarie 0000-0003-0281-9581 lwindham-myers@usgs.gov","orcid":"https://orcid.org/0000-0003-0281-9581","contributorId":2449,"corporation":false,"usgs":true,"family":"Windham-Myers","given":"Lisamarie","email":"lwindham-myers@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":757069,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bergamaschi, Brian A. 0000-0002-9610-5581 bbergama@usgs.gov","orcid":"https://orcid.org/0000-0002-9610-5581","contributorId":140776,"corporation":false,"usgs":true,"family":"Bergamaschi","given":"Brian","email":"bbergama@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":757070,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anderson, Frank A. 0000-0002-1418-4678","orcid":"https://orcid.org/0000-0002-1418-4678","contributorId":203975,"corporation":false,"usgs":true,"family":"Anderson","given":"Frank","email":"","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":757071,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Knox, Sarah 0000-0003-2255-5835","orcid":"https://orcid.org/0000-0003-2255-5835","contributorId":167493,"corporation":false,"usgs":false,"family":"Knox","given":"Sarah","affiliations":[{"id":24725,"text":"Ecosystem Science Division, Department of Environmental Science","active":true,"usgs":false}],"preferred":false,"id":757072,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Miller, Robin 0000-0002-1875-0390 romiller@usgs.gov","orcid":"https://orcid.org/0000-0002-1875-0390","contributorId":213190,"corporation":false,"usgs":true,"family":"Miller","given":"Robin","email":"romiller@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":757073,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fujii, Roger 0000-0002-4616-7231 rfujii@usgs.gov","orcid":"https://orcid.org/0000-0002-4616-7231","contributorId":213191,"corporation":false,"usgs":true,"family":"Fujii","given":"Roger","email":"rfujii@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":757074,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70201780,"text":"70201780 - 2018 - Landsat benefiting society for fifty years","interactions":[{"subject":{"id":70268821,"text":"70268821 - 2018 - Addressing the water consumption riddle","indexId":"70268821","publicationYear":"2018","noYear":false,"title":"Addressing the water consumption riddle"},"predicate":"IS_PART_OF","object":{"id":70201780,"text":"70201780 - 2018 - Landsat benefiting society for fifty years","indexId":"70201780","publicationYear":"2018","noYear":false,"title":"Landsat benefiting society for fifty years"},"id":1},{"subject":{"id":70268822,"text":"70268822 - 2018 - After the fire: Landsat helps map the way forward","indexId":"70268822","publicationYear":"2018","noYear":false,"title":"After the fire: Landsat helps map the way forward"},"predicate":"IS_PART_OF","object":{"id":70201780,"text":"70201780 - 2018 - Landsat benefiting society for fifty years","indexId":"70201780","publicationYear":"2018","noYear":false,"title":"Landsat benefiting society for fifty years"},"id":2}],"lastModifiedDate":"2025-07-08T14:19:17.321439","indexId":"70201780","displayToPublicDate":"2019-02-01T13:24:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"title":"Landsat benefiting society for fifty years","docAbstract":"Since 1972, data acquired by the Landsat series of satellites have become integral to land management for both government and the private sector, providing scientists and decision makers with key information about agricultural productivity, ice sheet dynamics, urban growth, forest monitoring, natural resource management, water quality, and supporting disaster response.
Landsat 9 continues the mission of unrivaled space-based Earth observation and will lead the Landsat program into its second half century of Earth imagery provided to users, worldwide, at no charge. More than 8 million Landsat scenes held in the USGS archive to date are used in conjunction with advanced geographic information systems, image processing software, and cloud computing capabilities to enable Landsat users to study changes on the Earth’s surface across continental regions and extended time periods.
The Operational Land Imager 2 (OLI-2) and the Thermal Infrared Sensor 2 (TIRS-2) instruments onboard Landsat 9 —which replicate the technologically-advanced instruments introduced onboard Landsat 8—allow for the collection of continuous high-quality data required for advancing Earth applications, including our ability to map surface temperature and surface water quality.
Landsat 9 will build on the Landsat legacy, achieving a half-century record of global Earth observations.
","language":"English","publisher":"NASA","usgsCitation":"Rocchio, L., Connot, P., Young, S., Ramsayer, K., Owen, L., Bouchard, M., and Barnes, C., 2018, Landsat benefiting society for fifty years, 60 p.","productDescription":"60 p.","onlineOnly":"Y","ipdsId":"IP-103742","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":361030,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":399495,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://landsat.gsfc.nasa.gov/wp-content/uploads/2019/02/Case_Studies_Book2018_Landsat_Final_12x9web.pdf","linkFileType":{"id":1,"text":"pdf"}}],"publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Rocchio, Laura E. P.","contributorId":212822,"corporation":false,"usgs":false,"family":"Rocchio","given":"Laura E. P.","affiliations":[],"preferred":false,"id":756680,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Connot, Peggy 0000-0002-8474-8096","orcid":"https://orcid.org/0000-0002-8474-8096","contributorId":212823,"corporation":false,"usgs":true,"family":"Connot","given":"Peggy","email":"","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":756681,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Young, Steve 0000-0002-7904-9696","orcid":"https://orcid.org/0000-0002-7904-9696","contributorId":212824,"corporation":false,"usgs":true,"family":"Young","given":"Steve","email":"","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":756682,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ramsayer, Kate","contributorId":212825,"corporation":false,"usgs":false,"family":"Ramsayer","given":"Kate","email":"","affiliations":[],"preferred":false,"id":756683,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Owen, Linda 0000-0002-1734-5406","orcid":"https://orcid.org/0000-0002-1734-5406","contributorId":212826,"corporation":false,"usgs":true,"family":"Owen","given":"Linda","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":756684,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bouchard, Michelle 0000-0002-6353-3491 mbouchard@usgs.gov","orcid":"https://orcid.org/0000-0002-6353-3491","contributorId":3765,"corporation":false,"usgs":true,"family":"Bouchard","given":"Michelle","email":"mbouchard@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":756685,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Barnes, Christopher 0000-0002-4608-4364 christopher.barnes.ctr@usgs.gov","orcid":"https://orcid.org/0000-0002-4608-4364","contributorId":198908,"corporation":false,"usgs":true,"family":"Barnes","given":"Christopher","email":"christopher.barnes.ctr@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":756686,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70268821,"text":"70268821 - 2018 - Addressing the water consumption riddle","interactions":[{"subject":{"id":70268821,"text":"70268821 - 2018 - Addressing the water consumption riddle","indexId":"70268821","publicationYear":"2018","noYear":false,"title":"Addressing the water consumption riddle"},"predicate":"IS_PART_OF","object":{"id":70201780,"text":"70201780 - 2018 - Landsat benefiting society for fifty years","indexId":"70201780","publicationYear":"2018","noYear":false,"title":"Landsat benefiting society for fifty years"},"id":1}],"isPartOf":{"id":70201780,"text":"70201780 - 2018 - Landsat benefiting society for fifty years","indexId":"70201780","publicationYear":"2018","noYear":false,"title":"Landsat benefiting society for fifty years"},"lastModifiedDate":"2025-07-08T13:59:09.032588","indexId":"70268821","displayToPublicDate":"2019-02-01T08:54:44","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"title":"Addressing the water consumption riddle","docAbstract":"No abstract available.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Landsat benefiting society for fifty years","largerWorkSubtype":{"id":1,"text":"Federal Government Series"},"language":"English","publisher":"NASA","usgsCitation":"Connot, P., and Young, S., 2018, Addressing the water consumption riddle, 8 p.","productDescription":"8 p.","startPage":"25","endPage":"32","ipdsId":"IP-103651","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":491775,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Connot, Peggy 0000-0002-8474-8096","orcid":"https://orcid.org/0000-0002-8474-8096","contributorId":212823,"corporation":false,"usgs":true,"family":"Connot","given":"Peggy","email":"","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":942242,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Young, Steve 0000-0002-7904-9696","orcid":"https://orcid.org/0000-0002-7904-9696","contributorId":212824,"corporation":false,"usgs":true,"family":"Young","given":"Steve","email":"","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":942241,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70200801,"text":"70200801 - 2018 - Controls on deep direct-use thermal energy storage (DDU-TES) in the Portland Basin, Oregon, USA","interactions":[],"lastModifiedDate":"2019-12-22T14:18:33","indexId":"70200801","displayToPublicDate":"2019-01-30T09:42:15","publicationYear":"2018","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Controls on deep direct-use thermal energy storage (DDU-TES) in the Portland Basin, Oregon, USA","docAbstract":"Aquifer Thermal Energy Storage is being evaluated as a complementary technology to Deep Direct-Use for the Portland Basin, Oregon, USA. Aquifers can be used to efficiently distribute and store heat for seasonal use. The use of injection-extraction well pairs precludes the need to store or dispose of large volumes of pumped groundwater or to obtain a consumptive groundwater right. Injection temperatures vary seasonally, and well pairs can operate in continuous (single direction of flow) or cyclic (seasonal reversal of flow) modes. The target injection aquifers are the lowest Columbia River Basalt Group interflow zones, which are thermally and hydraulically separated from the overlying aquifer system, minimizing heat loss. A new aquifer thermal energy storage design tool allows assessment of thermal storage and recovery using: (1) system design parameters (e.g., well spacing and pumping rate), (2) thermal and hydraulic property values, and (3) regional groundwater flow rates. In continuous mode, extracted water temperature trends towards the flow-weighted average temperature of injected water over time, with the injected signal significantly lagged and damped. By controlling well spacing and temperature of delivered water (possibly using supplemental heating) continuous mode provides steady reliable warm water to end-users year-round. In cyclic mode, there is an advectively and conductively heated zone near the hot well and a cooled zone near the cool well, with temperatures substantially above and below the flow-weighted average injection temperature, respectively. In cyclic mode, during extraction, water temperatures start high or low, depending on the well, and temperatures trend towards the average injection temperature over the season. For the Columbia River Basalt Group in the Portland Basin, the quantity and quality of heat delivered depends most strongly on operational schedule, well spacing, mode of operation, and heterogeneity of the injection horizon.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Geothermal's role in today's energy: Geothermal Resources Council Annual Meeting (GRC 2018)","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Geothermal Resources Council","usgsCitation":"Burns, E.R., Cladouhos, T.T., Williams, C., and Bershaw, 2018, Controls on deep direct-use thermal energy storage (DDU-TES) in the Portland Basin, Oregon, USA, in Geothermal's role in today's energy: Geothermal Resources Council Annual Meeting (GRC 2018), v. 42, p. 132-168.","productDescription":"36 p.","startPage":"132","endPage":"168","ipdsId":"IP-098120","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":365811,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":365760,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.proceedings.com/42374.html"}],"country":"United States","state":"Oregon","otherGeospatial":"Portland Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.28857421875,\n 44.55133484083592\n ],\n [\n -122.34374999999999,\n 44.55133484083592\n ],\n [\n -122.34374999999999,\n 45.805828539928356\n ],\n [\n -123.28857421875,\n 45.805828539928356\n ],\n [\n -123.28857421875,\n 44.55133484083592\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"42","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Burns, Erick R. 0000-0002-1747-0506 eburns@usgs.gov","orcid":"https://orcid.org/0000-0002-1747-0506","contributorId":192154,"corporation":false,"usgs":true,"family":"Burns","given":"Erick","email":"eburns@usgs.gov","middleInitial":"R.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":750584,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cladouhos, Trenton T.","contributorId":66801,"corporation":false,"usgs":true,"family":"Cladouhos","given":"Trenton","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":766659,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Williams, C.F. 0000-0003-2196-5496","orcid":"https://orcid.org/0000-0003-2196-5496","contributorId":20401,"corporation":false,"usgs":true,"family":"Williams","given":"C.F.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":false,"id":766660,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bershaw","contributorId":217372,"corporation":false,"usgs":false,"family":"Bershaw","email":"","affiliations":[],"preferred":false,"id":766661,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70201743,"text":"70201743 - 2018 - Time-dependent pore filling","interactions":[],"lastModifiedDate":"2019-02-11T14:38:39","indexId":"70201743","displayToPublicDate":"2019-01-28T14:39:27","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Time-dependent pore filling","docAbstract":"Capillarity traps fluids in porous media during immiscible fluid displacement. Most field situations involve relatively long time scales, such as hydrocarbon migration into reservoirs, resource recovery, nonaqueous phase liquid remediation, geological CO2 storage, and sediment‐atmosphere interactions. Yet laboratory studies and numerical simulations of capillary phenomena rarely consider the impact of time on these processes. We use time‐lapse microphotography to record the evolution of saturation in air‐ or hydrocarbon‐filled capillary tubes submerged in water to investigate long‐term pore filling phenomena beyond imbibition. Microphotographic sequences capture a lively pore filling history where various concurrent physical phenomena coexist. Dissolution and diffusion play a central role. Observations indicate preferential transport of the wetting liquid along corners, vapor condensation, capillary flow induced by asymmetrical interfaces, and interface pinning that defines the diffusion length. Other processes include internal snap‐offs, fluid redistribution, and changes in wettability as fluids dissolve into each other. Overall, the rate of pore filling is diffusion‐controlled for a given interfacial configuration; diffusive transport takes place at a constant rate for pinned interfaces and is proportional to the square root of time for free interfaces where the diffusion length increases with time.
","language":"English","publisher":"AGU","doi":"10.1029/2018WR023066","usgsCitation":"Sun, Z., Jang, J., and Santamarina, J.C., 2018, Time-dependent pore filling: Water Resources Research, v. 54, no. 12, p. 10242-10253, https://doi.org/10.1029/2018WR023066.","productDescription":"12 p.","startPage":"10242","endPage":"10253","ipdsId":"IP-087788","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":468153,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2018wr023066","text":"Publisher Index Page"},{"id":360762,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"54","issue":"12","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2018-12-26","publicationStatus":"PW","scienceBaseUri":"5c5022c0e4b0708288f7e7c5","contributors":{"authors":[{"text":"Sun, Zhonghao","contributorId":211899,"corporation":false,"usgs":false,"family":"Sun","given":"Zhonghao","email":"","affiliations":[],"preferred":false,"id":755163,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jang, Junbong 0000-0001-5500-7558 jjang@usgs.gov","orcid":"https://orcid.org/0000-0001-5500-7558","contributorId":189400,"corporation":false,"usgs":true,"family":"Jang","given":"Junbong","email":"jjang@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":755164,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Santamarina, J. Carlos","contributorId":189401,"corporation":false,"usgs":false,"family":"Santamarina","given":"J.","email":"","middleInitial":"Carlos","affiliations":[],"preferred":false,"id":755165,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70201996,"text":"70201996 - 2018 - Predicting geogenic arsenic in drinking water wells in glacial aquifers, north-central USA: Accounting for depth-dependent features","interactions":[],"lastModifiedDate":"2019-02-04T16:32:24","indexId":"70201996","displayToPublicDate":"2019-01-01T16:32:18","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Predicting geogenic arsenic in drinking water wells in glacial aquifers, north-central USA: Accounting for depth-dependent features","docAbstract":"Chronic exposure to arsenic (As) via drinking groundwater is a human health concern worldwide. Probabilities of elevated geogenic As concentrations in groundwater were predicted in complex, glacial aquifers in Minnesota, north‐central USA, a region that commonly has elevated As concentrations in well water. Maps of elevated As hazard were created for depths typical of drinking water supply and with well construction attributes common for domestic wells. Conventional variables describing aquifer properties and materials, position on the hydrologic landscape, and soil geochemistry were among the most influential for predicting the probability of elevated As. We also found that certain well construction attributes were influential in predicting As hazard. Smaller distances between the top of the well screen and overlying aquitard (proximity) and shorter well screen lengths were each associated with higher probabilities of elevated As. Influential predictor variables, which are either mapped across the region or are well construction attributes, are proxies in the model for measurable physical or geochemical causes of elevated As (e.g., redox condition, till or aquifer sediment chemistry, and water chemistry), which are not mapped across the region. Our setting shares some important characteristics with deltaic and other high‐As aquifers in Southeast Asia: late Quaternary age, complex layering of coarse‐ and fine‐grained materials, low‐As sediment concentrations, and geochemical controls on As mobilization. Translating three‐dimensional geologic and geochemical understanding of As mobility to quantifiable variables for modeling with powerful, flexible statistical tools could improve predictions and help identify safer groundwater supply options in the USA, Southeast Asia, and elsewhere.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2018WR023106","usgsCitation":"Erickson, M., Elliott, S.M., Christenson, C., and Krall, A.L., 2018, Predicting geogenic arsenic in drinking water wells in glacial aquifers, north-central USA: Accounting for depth-dependent features: Water Resources Research, v. 54, no. 12, p. 10172-10187, https://doi.org/10.1029/2018WR023106.","productDescription":"16 p.","startPage":"10172","endPage":"10187","ipdsId":"IP-090485","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":468158,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2018wr023106","text":"Publisher Index Page"},{"id":437637,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F77H1HH8","text":"USGS data release","linkHelpText":"Groundwater arsenic data and ASCII grids for predicting elevated arsenic in northwestern and 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result in reduced pH and higher levels of CO2 in the ocean, a process known as ocean acidification. Understanding the effects of ocean acidification (OA) on fishes will be important to predicting and mitigating its consequences. Anadromous species such as salmonids may be especially at risk because of their rapid movements between fresh water and seawater, which could minimize their ability to acclimate. In the present study, we examine the effect of future OA on the salinity tolerance and early seawater growth of Atlantic salmon Salmo salar smolts. Exposure to 610 and 1010 μatm CO2 did not alter salinity tolerance but did result in slightly lower plasma chloride levels in smolts exposed to seawater compared with controls (390 μatm). Gill Na+–K+‐ATPase activity, plasma cortisol, glucose and haematocrit after seawater exposure were not altered by elevated CO2. Growth rate in the first 2 weeks of seawater exposure was greater at 1010 μatm CO2than under control conditions. This study of the effects of OA on S. salar during the transition from fresh water to seawater indicates that elevated CO2 is not likely to affect osmoregulation negatively and may improve early growth in seawater.
","language":"English","publisher":"Wiley","doi":"10.1111/jfb.13656","usgsCitation":"McCormick, S.D., and Regish, A.M., 2018, Effects of ocean acidification on salinity tolerance and seawater growth of Atlantic salmon Salmo salar smolts: Journal of Fish Biology, v. 93, no. 3, p. 560-566, https://doi.org/10.1111/jfb.13656.","productDescription":"7 p.","startPage":"560","endPage":"566","ipdsId":"IP-092140","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":468159,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/jfb.13656","text":"Publisher Index Page"},{"id":360994,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"93","issue":"3","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2018-09-26","publicationStatus":"PW","contributors":{"authors":[{"text":"McCormick, Stephen D. 0000-0003-0621-6200 smccormick@usgs.gov","orcid":"https://orcid.org/0000-0003-0621-6200","contributorId":139214,"corporation":false,"usgs":true,"family":"McCormick","given":"Stephen","email":"smccormick@usgs.gov","middleInitial":"D.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":756553,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Regish, Amy M. 0000-0003-4747-4265 aregish@usgs.gov","orcid":"https://orcid.org/0000-0003-4747-4265","contributorId":5415,"corporation":false,"usgs":true,"family":"Regish","given":"Amy","email":"aregish@usgs.gov","middleInitial":"M.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":756554,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70201703,"text":"70201703 - 2018 - Geospatial data for developing nutrient SPARROW models for the Midcontinental region of Canada and the United States","interactions":[],"lastModifiedDate":"2019-02-01T14:01:54","indexId":"70201703","displayToPublicDate":"2019-01-01T14:01:49","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"seriesTitle":{"id":295,"text":"Technical Report","active":false,"publicationSubtype":{"id":4}},"seriesNumber":"OCRE-TR-2018-014","title":"Geospatial data for developing nutrient SPARROW models for the Midcontinental region of Canada and the United States","docAbstract":"Through the International Watersheds Initiative of the International Joint Commission (IJC), the SpatiallyReferenced Regressions on Watershed attributes (SPARROW) model developed by the U.S. Geological Survey (USGS) is being applied to the Great Lakes, Rainy River – Lake of the Woods and Red-Assiniboine basins. The objective of this binational application of the SPARROW model is to better understand and quantify the sources of phosphorus (P) and nitrogen (N) that contribute to regional water-quality issues like algal blooms and eutrophication in Lake Erie and other parts of the Great Lakes, as well as Lake of the Woods. Led by the IJC, a team of researchers from the National Research Council of Canada – Ocean, Coastal and River Engineering Research Centre, USGS, and IJC are extending the SPARROW modelling work previously completed for the Red-Assiniboine basin and the U.S. portions of the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy river basins to cover all of the Great Lakes, Rainy River – Lake of the Woods and RedAssiniboine basins. The current effort is termed the Midcontinent SPARROW modelling study.
This report describes the data used to develop the Midcontinent SPARROW models, specifically the sources of original data, assembling the data, and the processing and harmonization required between the U.S. and Canada data needed to produce these models. Details provided include the:
The majority of the geospatial data collection and processing was required for Canadian datasets because many of the U.S. datasets were already assembled for previous SPARROW model applications in the U.S. The task of harmonizing data between the U.S. and Canada was important to ensure consistency of the datasets used in the models. The harmonized digital stream network, delineated catchments and input data for each catchment (i.e., source and delivery variables), created for the Midcontinent SPARROW models, are available for download at url: https://doi.org/10.4224/300.0001.
","language":"English","publisher":"National Research Council Canada","doi":"10.4224/23004810","usgsCitation":"Vouk, I., Burcher, R.S., Johnston, C.M., Jenkinson, R.W., Saad, D.A., Gaiot, J.S., Benoy, G.A., Robertson, D.M., and Laitta, M., 2018, Geospatial data for developing nutrient SPARROW models for the Midcontinental region of Canada and the United States: Technical Report OCRE-TR-2018-014, 57 p., https://doi.org/10.4224/23004810.","productDescription":"57 p.","ipdsId":"IP-096418","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":360921,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Vouk, Ivana 0000-0002-9134-6933","orcid":"https://orcid.org/0000-0002-9134-6933","contributorId":211795,"corporation":false,"usgs":false,"family":"Vouk","given":"Ivana","email":"","affiliations":[{"id":38321,"text":"National Research Council Canada","active":true,"usgs":false}],"preferred":false,"id":754916,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burcher, Richard S.","contributorId":211796,"corporation":false,"usgs":false,"family":"Burcher","given":"Richard","email":"","middleInitial":"S.","affiliations":[{"id":38321,"text":"National Research Council Canada","active":true,"usgs":false}],"preferred":false,"id":754918,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnston, Craig M. cmjohnst@usgs.gov","contributorId":1814,"corporation":false,"usgs":true,"family":"Johnston","given":"Craig","email":"cmjohnst@usgs.gov","middleInitial":"M.","affiliations":[{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":754917,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jenkinson, R. Wayne","contributorId":211797,"corporation":false,"usgs":false,"family":"Jenkinson","given":"R.","email":"","middleInitial":"Wayne","affiliations":[{"id":38322,"text":"International Joint Commission","active":true,"usgs":false}],"preferred":false,"id":754919,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Saad, David A. 0000-0001-6559-6181 dasaad@usgs.gov","orcid":"https://orcid.org/0000-0001-6559-6181","contributorId":204667,"corporation":false,"usgs":true,"family":"Saad","given":"David","email":"dasaad@usgs.gov","middleInitial":"A.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":754915,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gaiot, John S.","contributorId":211798,"corporation":false,"usgs":false,"family":"Gaiot","given":"John","email":"","middleInitial":"S.","affiliations":[{"id":16762,"text":"Ontario Ministry of Natural Resources and Forestry","active":true,"usgs":false}],"preferred":false,"id":754920,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Benoy, Glenn A. 0000-0001-6530-7220","orcid":"https://orcid.org/0000-0001-6530-7220","contributorId":172405,"corporation":false,"usgs":false,"family":"Benoy","given":"Glenn","email":"","middleInitial":"A.","affiliations":[{"id":13361,"text":"International Joint Commission, Washington DC","active":true,"usgs":false}],"preferred":false,"id":754921,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Robertson, Dale M. 0000-0001-6799-0596","orcid":"https://orcid.org/0000-0001-6799-0596","contributorId":204668,"corporation":false,"usgs":true,"family":"Robertson","given":"Dale","email":"","middleInitial":"M.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":754922,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Laitta, Michael","contributorId":212258,"corporation":false,"usgs":false,"family":"Laitta","given":"Michael","affiliations":[{"id":38322,"text":"International Joint Commission","active":true,"usgs":false}],"preferred":false,"id":755883,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70201868,"text":"70201868 - 2018 - Water","interactions":[],"lastModifiedDate":"2019-02-01T13:34:43","indexId":"70201868","displayToPublicDate":"2019-01-01T13:34:38","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Water","docAbstract":"Ensuring a reliable supply of clean freshwater to individuals, communities, and ecosystems, together with effective management of floods and droughts, is the foundation of human and ecological health. The water sector is also central to the economy and contributes significantly to the resilience of many other sectors, including agriculture, energy, urban environments, and industry.
Water systems face considerable risk, even without anticipated future climate changes. Limited surface water storage, as well as a limited ability to make use of long-term drought forecasts and to trade water across uses and basins, has led to a significant depletion of aquifers in many regions in the United States. Across the Nation, much of the critical water and wastewater infrastructure is nearing the end of its useful life. To date, no comprehensive assessment exists of the climate-related vulnerability of U.S. water infrastructure (including dams, levees, aqueducts, sewers, and water and wastewater distribution and treatment systems), the potential resulting damages, or the cost of reconstruction and recovery. Paleoclimate information (reconstructions of past climate derived from ice cores or tree rings) shows that over the last 500 years, North America has experienced pronounced wet/dry regime shifts that sometimes persisted for decades. Because such protracted exposures to extreme floods or droughts in different parts of the country are extraordinary compared to events experienced in the 20th century, they are not yet incorporated in water management principles and practice. Anticipated future climate change will exacerbate this risk in many regions.
A central challenge to water planning and management is learning to plan for plausible future climate conditions that are wider in range than those experienced in the 20th century. Doing so requires approaches that evaluate plans over many possible futures instead of just one, incorporate real-time monitoring and forecast products to better manage extremes when they occur, and update policies and engineering principles with the best available geoscience-based understanding of planetary change. While this represents a break from historical practice, recent examples of adaptation responses undertaken by large water management agencies, including major metropolitan water utilities and the U.S. Army Corps of Engineers, are promising.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Impacts, Risks, and Adaptation in the United States: Fourth National Climate Assessment, Volume II","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"U.S. Global Change Research Program","doi":"10.7930/NCA4.2018.CH3","usgsCitation":"Lall, U., Johnson, T.M., Colohan, P., AghaKouchak, A., Brown, C., McCabe, G.J., Pulwarty, R., and Arumugam, S., 2018, Water, 29 p., https://doi.org/10.7930/NCA4.2018.CH3.","productDescription":"29 p.","startPage":"145","endPage":"173","ipdsId":"IP-103820","costCenters":[{"id":505,"text":"Office of the AD Climate and Land-Use Change","active":true,"usgs":true}],"links":[{"id":360919,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"editors":[{"text":"Reidmiller, David 0000-0001-9321-7548","orcid":"https://orcid.org/0000-0001-9321-7548","contributorId":212241,"corporation":false,"usgs":true,"family":"Reidmiller","given":"David","email":"","affiliations":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":755874,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Avery, C. 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C.","contributorId":212246,"corporation":false,"usgs":false,"family":"Stewart","given":"B.","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":755880,"contributorType":{"id":2,"text":"Editors"},"rank":7}],"authors":[{"text":"Lall, Upmanu 0000-0003-0529-8128","orcid":"https://orcid.org/0000-0003-0529-8128","contributorId":212142,"corporation":false,"usgs":false,"family":"Lall","given":"Upmanu","email":"","affiliations":[{"id":7171,"text":"Columbia University","active":true,"usgs":false}],"preferred":false,"id":755620,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Thomas M.","contributorId":174200,"corporation":false,"usgs":false,"family":"Johnson","given":"Thomas","email":"","middleInitial":"M.","affiliations":[{"id":16984,"text":"University of Illinois at Urbana-Champaign","active":true,"usgs":false}],"preferred":false,"id":755621,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Colohan, Peter","contributorId":212143,"corporation":false,"usgs":false,"family":"Colohan","given":"Peter","email":"","affiliations":[{"id":38436,"text":"National Oceanic and Atmospheric Administration","active":true,"usgs":false}],"preferred":false,"id":755622,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"AghaKouchak, Amir","contributorId":140736,"corporation":false,"usgs":false,"family":"AghaKouchak","given":"Amir","email":"","affiliations":[{"id":13550,"text":"Civil & Environmental Engineering, University of California Irvine","active":true,"usgs":false}],"preferred":false,"id":755623,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brown, Casey L.","contributorId":177116,"corporation":false,"usgs":false,"family":"Brown","given":"Casey L.","affiliations":[],"preferred":false,"id":755624,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McCabe, Gregory J. 0000-0002-9258-2997 gmccabe@usgs.gov","orcid":"https://orcid.org/0000-0002-9258-2997","contributorId":200854,"corporation":false,"usgs":true,"family":"McCabe","given":"Gregory","email":"gmccabe@usgs.gov","middleInitial":"J.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":755619,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pulwarty, Roger","contributorId":212144,"corporation":false,"usgs":false,"family":"Pulwarty","given":"Roger","affiliations":[{"id":38436,"text":"National Oceanic and Atmospheric Administration","active":true,"usgs":false}],"preferred":false,"id":755625,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Arumugam, Sankar","contributorId":212145,"corporation":false,"usgs":false,"family":"Arumugam","given":"Sankar","email":"","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":755626,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70202365,"text":"70202365 - 2018 - Informing our successors: What botanical information for Santa Cruz Island will researchers and conservation managers in the century ahead need the most?","interactions":[],"lastModifiedDate":"2019-03-01T13:32:35","indexId":"70202365","displayToPublicDate":"2019-01-01T13:32:29","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3746,"text":"Western North American Naturalist","onlineIssn":"1944-8341","printIssn":"1527-0904","active":true,"publicationSubtype":{"id":10}},"title":"Informing our successors: What botanical information for Santa Cruz Island will researchers and conservation managers in the century ahead need the most?","docAbstract":"Climate changes are predicted to drive changes in plant species composition and vegetation cover around the world. Preserved specimens and other botanical information that we gather today—a period future practitioners may look back on as an early stage of modern anthropogenic climate change—will be of value to conservation managers and conservation biologists in the decades and centuries ahead. Here, we present suggestions for the systematic collection, long-term curation (in museums, herbaria, and other research institutions), and maintenance of plant specimens, along with associated data and analyses on the plants and vegetation present today and in the past. The primary aim of this systematic survey is to provide information of high value to conservation researchers and managers both in the near term (the next several years) and through the century to come. Such a systematic survey would build on a strong foundation of research and adaptive management on the island. It would fill gaps in less well-studied groups of organisms and identify environmental, ecological, and cultural factors related to current patterns of distribution. It would also archive previously collected data, photographs, and other materials which would otherwise gradually degrade and become inaccessible. As a case study, we use Santa Cruz Island, California, which is managed for conservation. We are confident that the same approach may be applied to other lands and waters around the world. We argue that there is a particular need to collect and archive herbarium specimens and seeds from today's populations, activities largely overlooked in recent decades. We encourage conservation researchers and managers to consider what information will be most important for future managers and to help launch studies, monitoring programs, and collections to prepare their successors for success.
","language":"English","publisher":"Monte L. Bean Life Science Museum, Brigham Young University","doi":"10.3398/064.078.0427","usgsCitation":"Randall, J.M., McEachern, K., Knapp, J., Power, P., Junak, S., Gill, K., Knapp, D., and Guilliams, M., 2018, Informing our successors: What botanical information for Santa Cruz Island will researchers and conservation managers in the century ahead need the most?: Western North American Naturalist, v. 78, no. 4, p. 888-901, https://doi.org/10.3398/064.078.0427.","productDescription":"14 p.","startPage":"888","endPage":"901","ipdsId":"IP-087994","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":361651,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"78","issue":"4","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Randall, John M.","contributorId":210310,"corporation":false,"usgs":false,"family":"Randall","given":"John","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":758014,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McEachern, Kathryn 0000-0003-2631-8247 kathryn_mceachern@usgs.gov","orcid":"https://orcid.org/0000-0003-2631-8247","contributorId":146324,"corporation":false,"usgs":true,"family":"McEachern","given":"Kathryn","email":"kathryn_mceachern@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":758013,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Knapp, John","contributorId":213552,"corporation":false,"usgs":false,"family":"Knapp","given":"John","email":"","affiliations":[{"id":7041,"text":"The Nature Conservancy","active":true,"usgs":false}],"preferred":false,"id":758015,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Power, Paula","contributorId":213553,"corporation":false,"usgs":false,"family":"Power","given":"Paula","email":"","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":758016,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Junak, Steve","contributorId":213554,"corporation":false,"usgs":false,"family":"Junak","given":"Steve","email":"","affiliations":[{"id":38789,"text":"Santa Barbara Botanic Garden","active":true,"usgs":false}],"preferred":false,"id":758017,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gill, Kristina","contributorId":213555,"corporation":false,"usgs":false,"family":"Gill","given":"Kristina","email":"","affiliations":[{"id":38789,"text":"Santa Barbara Botanic Garden","active":true,"usgs":false}],"preferred":false,"id":758018,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Knapp, Denise","contributorId":213556,"corporation":false,"usgs":false,"family":"Knapp","given":"Denise","email":"","affiliations":[{"id":38789,"text":"Santa Barbara Botanic Garden","active":true,"usgs":false}],"preferred":false,"id":758019,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Guilliams, Matt","contributorId":213557,"corporation":false,"usgs":false,"family":"Guilliams","given":"Matt","email":"","affiliations":[{"id":38789,"text":"Santa Barbara Botanic Garden","active":true,"usgs":false}],"preferred":false,"id":758020,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70201869,"text":"70201869 - 2018 - Coastal effects","interactions":[],"lastModifiedDate":"2019-02-01T13:30:46","indexId":"70201869","displayToPublicDate":"2019-01-01T13:30:41","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Coastal effects","docAbstract":"The Coasts chapter of the Third National Climate Assessment, published in 2014, focused on coastal lifelines at risk, economic disruption, uneven social vulnerability, and vulnerable ecosystems. This Coastal Effects chapter of the Fourth National Climate Assessment updates those themes, with a focus on integrating the socioeconomic and environmental impacts and consequences of a changing climate. Specifically, the chapter builds on the threat of rising sea levels exacerbating tidal and storm surge flooding, the state of coastal ecosystems, and the treatment of social vulnerability by introducing the implications for social equity.
U.S. coasts are dynamic environments and economically vibrant places to live and work. As of 2013, coastal shoreline counties were home to 133.2 million people, or 42% of the population. The coasts are economic engines that support jobs in defense, fishing, transportation, and tourism industries; contribute substantially to the U.S. gross domestic product; and serve as hubs of commerce, with seaports connecting the country with global trading partners. Coasts are home to diverse ecosystems such as beaches, intertidal zones, reefs, seagrasses, salt marshes, estuaries, and deltas that support a range of important services including fisheries, recreation, and coastal storm protection. U.S. coasts span three oceans, as well as the Gulf of Mexico, the Great Lakes, and Pacific and Caribbean islands.
The social, economic, and environmental systems along the coasts are being affected by climate change. Threats from sea level rise (SLR) are exacerbated by dynamic processes such as high tide and storm surge flooding (Ch. 19: Southeast, KM 2), erosion (Ch. 26: Alaska, KM 2), waves and their effects, saltwater intrusion into coastal aquifers and elevated groundwater tables (Ch. 27: Hawaiʻi & Pacific Islands, KM 1; Ch. 3: Water, KM 1), local rainfall (Ch. 3: Water, KM 1), river runoff (Ch. 3: Water, KM 1), increasing water and surface air temperatures (Ch. 9: Oceans, KM 3), and ocean acidification (see Ch. 2: Climate, KM 3 and Ch. 9: Oceans, KM 1, 2, and 3 for more information on ocean acidification, hypoxia, and ocean warming).
Although storms, floods, and erosion have always been hazards, in combination with rising sea levels they now threaten approximately $1 trillion in national wealth held in coastal real estate and the continued viability of coastal communities that depend on coastal water, land, and other resources for economic health and cultural integrity (Ch. 15: Tribes, KM 1 and 2).
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Impacts, Risks, and Adaptation in the United States: Fourth National Climate Assessment, Volume II","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"U.S. Global Change Research Program","doi":"10.7930/NCA4.2018.CH8","usgsCitation":"Fleming, E., Payne, J., Sweet, W.V., Craghan, M., Haines, J.W., Finzi Hart, J., Stiller, H., and Sutton-Grier, A., 2018, Coastal effects, 31 p., https://doi.org/10.7930/NCA4.2018.CH8.","productDescription":"31 p.","startPage":"322","endPage":"352","ipdsId":"IP-103835","costCenters":[{"id":501,"text":"Office of Science Quality and Integrity","active":true,"usgs":true}],"links":[{"id":360918,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"editors":[{"text":"Reidmiller, David 0000-0001-9321-7548","orcid":"https://orcid.org/0000-0001-9321-7548","contributorId":212241,"corporation":false,"usgs":true,"family":"Reidmiller","given":"David","email":"","affiliations":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":755867,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Avery, C. 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C.","contributorId":212246,"corporation":false,"usgs":false,"family":"Stewart","given":"B.","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":755873,"contributorType":{"id":2,"text":"Editors"},"rank":7}],"authors":[{"text":"Fleming, Elizabeth","contributorId":212146,"corporation":false,"usgs":false,"family":"Fleming","given":"Elizabeth","email":"","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":755627,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Payne, Jeffrey","contributorId":212147,"corporation":false,"usgs":false,"family":"Payne","given":"Jeffrey","email":"","affiliations":[{"id":38436,"text":"National Oceanic and Atmospheric Administration","active":true,"usgs":false}],"preferred":false,"id":755628,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sweet, William V. 0000-0002-0149-8336","orcid":"https://orcid.org/0000-0002-0149-8336","contributorId":212148,"corporation":false,"usgs":false,"family":"Sweet","given":"William","email":"","middleInitial":"V.","affiliations":[{"id":38436,"text":"National Oceanic and Atmospheric Administration","active":true,"usgs":false}],"preferred":false,"id":755629,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Craghan, Michael","contributorId":212149,"corporation":false,"usgs":false,"family":"Craghan","given":"Michael","email":"","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":755630,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Haines, John W. 0000-0002-6475-8924 jhaines@usgs.gov","orcid":"https://orcid.org/0000-0002-6475-8924","contributorId":509,"corporation":false,"usgs":true,"family":"Haines","given":"John","email":"jhaines@usgs.gov","middleInitial":"W.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":755631,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Finzi Hart, Juliette 0000-0003-3179-2699","orcid":"https://orcid.org/0000-0003-3179-2699","contributorId":206104,"corporation":false,"usgs":true,"family":"Finzi Hart","given":"Juliette","email":"","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":755632,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Stiller, Heidi","contributorId":212150,"corporation":false,"usgs":false,"family":"Stiller","given":"Heidi","email":"","affiliations":[{"id":38436,"text":"National Oceanic and Atmospheric Administration","active":true,"usgs":false}],"preferred":false,"id":755633,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sutton-Grier, Ariana","contributorId":204025,"corporation":false,"usgs":false,"family":"Sutton-Grier","given":"Ariana","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":755634,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70202208,"text":"70202208 - 2018 - Assessment of carbon dioxide piscicide treatments","interactions":[],"lastModifiedDate":"2019-02-14T12:40:42","indexId":"70202208","displayToPublicDate":"2019-01-01T12:40:36","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Assessment of carbon dioxide piscicide treatments","docAbstract":"Few chemicals are approved to control or eradicate nuisance fish populations in the United States. Carbon dioxide (CO2) is currently being developed and studied as a new piscicide option for nonselective population control. This study evaluated dry ice (solid state CO2) as a simple CO2 delivery method during winter piscicide applications. Nonnative Silver Carp Hypophthalmichthys molitrix, Bighead Carp H. nobilis, and native Fathead Minnow Pimephales promelas were overwintered together in ice‐covered ponds treated with 25 kg dry ice/100,000 L (low treatment) or 50 kg dry ice/100,000 L (high treatment). Overwinter fish survival was significantly reduced in ponds treated with dry ice relative to untreated control ponds. Fathead Minnows were less susceptible to CO2exposure than the carps, with 26–96% survival in low‐treatment ponds and 4–68% survival in high‐treatment ponds. Silver Carp and Bighead Carp were more sensitive to CO2 treatments and no individuals of either species survived in ponds with the high‐treatment level. Water samples were also collected in all ponds throughout this study, and we observed notably higher Silver Carp and Bighead Carp environmental DNA (eDNA) concentrations in dry‐ice‐treated ponds relative to untreated control ponds. Distinct changes in eDNA trends correlated with fish mortality, and results indicate that eDNA sampling could be a useful indicator of piscicide efficacy. This study demonstrates that CO2 administered as dry ice is an effective under‐ice piscicide method.
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