{"pageNumber":"219","pageRowStart":"5450","pageSize":"25","recordCount":68807,"records":[{"id":70218310,"text":"70218310 - 2020 - Quantifying microplastics in Indiana’s Lake Michigan watershed and submerged aquatic vegetation","interactions":[],"lastModifiedDate":"2021-02-25T13:52:31.418965","indexId":"70218310","displayToPublicDate":"2021-02-23T07:49:41","publicationYear":"2020","noYear":false,"publicationType":{"id":25,"text":"Newsletter"},"title":"Quantifying microplastics in Indiana’s Lake Michigan watershed and submerged aquatic vegetation","docAbstract":"Environmental breakdown of plastics produces synthetic microfibers, a class of microplastics that are most prevalent in surface waters. A main source of these pollutants is wastewater treatment plants which discharge into surface waters, including those that flow into Lake Michigan. Microplastics can settle into aquatic sediment or exist for lengths of time in the swash zone of the lakes; they can be ingested by organisms or concentrated in algae or other lake plankton, among other possibilities.  As part of a larger Great Lakes study of the growth and senescence of submerged aquatic vegetation (SAV), the loads of synthetic microfibers in the SAV have been determined from Lake Michigan samples collected during the summer months of 2018, 2019 and 2020, and from various samples collected in the watershed and along the shoreline in Northwest Indiana. In order to effectively address microplastics pollution, a complete understanding of the distribution and fate of these pollutants is needed; this project is working toward that goal.","language":"English","publisher":"Indiana Water Monitoring Council","usgsCitation":"Peller, J.R., Nevers, M., Byappanahalli, M., and Evans, M.A., 2020, Quantifying microplastics in Indiana’s Lake Michigan watershed and submerged aquatic vegetation, 52 p.","productDescription":"52 p.","ipdsId":"IP-125045","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":383620,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":383615,"type":{"id":15,"text":"Index Page"},"url":"https://www.inwmc.net/wp-content/uploads/2021/02/2020-Indiana-Water-Report.pdf"}],"country":"United 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,{"id":70229515,"text":"70229515 - 2020 - Landsat surface reflectance validation site selection","interactions":[],"lastModifiedDate":"2022-03-11T15:35:55.452537","indexId":"70229515","displayToPublicDate":"2021-02-17T09:31:32","publicationYear":"2020","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Landsat surface reflectance validation site selection","docAbstract":"<p><span>An investigation was conducted to determine optimal locations within the continental United States for insitu measurements to validate the U.S. Landsat Analysis Ready Data (ARD) Surface Reflectance product. Site assessment involved analysis of aerosol optical depth, precipitable water vapor, land cover, cloud cover, and elevation models. Nineteen sites were selected for further month-by-month ranking to identify those sites most likely to capture simple or complex atmosphere.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"IGARSS 2020 - 2020 IEEE international geoscience and remote sensing symposium","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"IEEE","doi":"10.1109/IGARSS39084.2020.9323374","usgsCitation":"Maddox, E.M., and Zavesky, L.D., 2020, Landsat surface reflectance validation site selection, <i>in</i> IGARSS 2020 - 2020 IEEE international geoscience and remote sensing symposium, p. 6133-6136, https://doi.org/10.1109/IGARSS39084.2020.9323374.","productDescription":"4 p.","startPage":"6133","endPage":"6136","ipdsId":"IP-115451","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":397023,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Maddox, Emily M. 0000-0001-5649-1193","orcid":"https://orcid.org/0000-0001-5649-1193","contributorId":288315,"corporation":false,"usgs":true,"family":"Maddox","given":"Emily","email":"","middleInitial":"M.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":837721,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zavesky, Landon Douglas 0000-0003-1109-8149","orcid":"https://orcid.org/0000-0003-1109-8149","contributorId":288316,"corporation":false,"usgs":true,"family":"Zavesky","given":"Landon","email":"","middleInitial":"Douglas","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":837722,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70216974,"text":"ofr20201148 - 2020 - 2020 drought in New England","interactions":[],"lastModifiedDate":"2021-02-11T19:15:14.115573","indexId":"ofr20201148","displayToPublicDate":"2021-02-11T13:00:00","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-1148","displayTitle":"2020 Drought in New England","title":"2020 drought in New England","docAbstract":"<p>Below average and infrequent rainfall from May through September 2020 led to an extreme hydrologic drought across much of New England, with some areas experiencing a flash drought, reflecting its quick onset. The U.S. Geological Survey (USGS) recorded record-low streamflow and groundwater levels throughout the region. In September, the U.S. Department of Agriculture (2020) declared Aroostook County in Maine and Hillsborough and Merrimack Counties in New Hampshire as crop disaster areas. By the beginning of October, 166 community water systems and 5 municipalities in New Hampshire, more than 100 municipalities in Massachusetts, and several community water supplies in Connecticut, Maine, and Rhode Island had mandatory water restrictions in place.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201148","usgsCitation":"Lombard, P.J., Barclay, J.R., and McCarthy, D.E., 2020, 2020 drought in New England (ver. 1.1, February 2021): U.S. Geological Survey Open-File Report 2020–1148, 12 p., https://doi.org/10.3133/ofr20201148.","productDescription":"Report: 12 p.; 3 Figures; 2 Tables","numberOfPages":"12","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-124096","costCenters":[{"id":466,"text":"New England Water Science 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01532</p>","tableOfContents":"<ul><li>Highlights</li><li>Study Area</li><li>Drought Definitions</li><li>Drought Severity</li><li>Meteorological Drought</li><li>U.S. Geological Survey Streamflow and Groundwater-Level Monitoring Networks in New England</li><li>Data Analysis</li><li>Hydrologic Drought of 2020</li><li>Groundwater Conditions</li><li>Comparison of Streamflow Statistics to Previous Droughts</li><li>Provisional Nature of the Data</li><li>Acknowledgments</li><li>Summary</li><li>References Cited</li><li>Appendix 1. U.S. Geological Survey Streamgages and Groundwater Observation Wells Used To Analyze Drought Conditions in New England in 2020</li></ul>","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"publishedDate":"2020-12-22","revisedDate":"2021-02-11","noUsgsAuthors":false,"publicationDate":"2020-12-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Lombard, Pamela J. 0000-0002-0983-1906","orcid":"https://orcid.org/0000-0002-0983-1906","contributorId":203509,"corporation":false,"usgs":true,"family":"Lombard","given":"Pamela","email":"","middleInitial":"J.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":807141,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barclay, Janet R. 0000-0003-1643-6901 jbarclay@usgs.gov","orcid":"https://orcid.org/0000-0003-1643-6901","contributorId":222437,"corporation":false,"usgs":true,"family":"Barclay","given":"Janet","email":"jbarclay@usgs.gov","middleInitial":"R.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":807142,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Crozier, Dee-Ann E. 0000-0003-0526-3013","orcid":"https://orcid.org/0000-0003-0526-3013","contributorId":245837,"corporation":false,"usgs":true,"family":"Crozier","given":"Dee-Ann","email":"","middleInitial":"E.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":807143,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70217177,"text":"tm4F5 - 2020 - DGMETA (version 1)—Dissolved gas modeling and environmental tracer analysis computer program","interactions":[],"lastModifiedDate":"2024-02-01T18:43:12.976311","indexId":"tm4F5","displayToPublicDate":"2021-01-08T11:31:29","publicationYear":"2020","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-F5","displayTitle":"DGMETA (Version 1): Dissolved Gas Modeling and Environmental Tracer Analysis Computer Program","title":"DGMETA (version 1)—Dissolved gas modeling and environmental tracer analysis computer program","docAbstract":"<p class=\"x_Pa33\"><span>DGMETA (Dissolved Gas Modeling and Environmental Tracer Analysis) is a Microsoft Excel-based computer program that is used for modeling air-water equilibrium conditions from measurements of dissolved gases and for computing concentrations of environmental tracers that rely on air-water equilibrium model results. DGMETA can solve for the temperature, salinity, excess air, fractionation of gases, or pressure/elevation of water when it is equilibrated with the atmosphere. Models are calibrated inversely using one or more measurements of dissolved gases such as helium, neon, argon, krypton, xenon, and nitrogen. Excess nitrogen gas, originating from denitrification or other sources, also can be included as a fitted parameter or as a separate calculation from the dissolved gas modeling results. DGMETA uses the air-water equilibrium models to separate measured concentrations of gases and isotopes of gases into components that are used for tracing water in the environment. DGMETA calculates atmospheric dry-air mole fractions (mixing ratios) for transient atmospheric gas tracers such as chlorofluorocarbons, sulfur hexafluoride, and bromotrifluoromethane (Halon-1301); and concentrations of tritiogenic helium-3 and radiogenic helium-4, which accumulate from the decay of tritium in water and the decay of uranium and thorium in rocks, respectively.&nbsp;</span></p><p class=\"x_Pa33\"><span>Sample data can be graphed to identify applicable models of excess air, samples that contain excess nitrogen gas, or samples that have partially degassed, for example. Monte Carlo analysis of errors associated with dissolved gas equilibrium model results can be carried through computations of environmental tracer concentrations to provide robust estimates of error. In addition, graphical routines for separating helium sources using helium isotopes are included to refine estimates of tritiogenic helium-3 when terrigenic helium from mantle or crustal sources is present in samples. Environmental tracer concentrations and their errors computed from DGMETA can be used with other programs, such as TracerLPM (Jurgens and others, 2012), to determine groundwater ages and biogeochemical reaction rates. DGMETA also produces output files in a format that meets the U.S. Geological Survey open data requirements for documentation of model inputs and outputs.&nbsp;</span></p><p class=\"x_Pa33\"><span>DGMETA is a versatile and adaptable program that allows users to add solubility data for new gases, modify the existing set of gas solubility data, modify the default set of gases used for modeling, choose calculations based on real (non-ideal) gas behavior, and select various concentration units for data entry and results to match laboratory reports and study objectives. DGMETA comes with a set of gases widely used in hydrology and oceanography and many gases include multiple solubilities from previous work. Seventeen dissolved gases are included in the default version of the program: noble gases (helium, neon, argon, krypton, and xenon), reactive gases (nitrogen, oxygen, methane, carbon dioxide, carbon monoxide, hydrogen, and nitrous oxide), and environmental tracers (chlorofluorocarbon-11, chlorofluorocarbon-12, chlorofluorocarbon-113, sulfur hexafluoride, and Halon-1301).</span></p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm4F5","collaboration":"National Water Quality Assessment Project","usgsCitation":"Jurgens, B.C., Böhlke, J., Haase, K., Busenberg, E., Hunt, A.G., and Hansen, J.A., 2020, DGMETA (version 1)—Dissolved gas modeling and environmental tracer analysis computer program: U.S. Geological Survey Techniques and Methods 4-F5, 50 p., https://doi.org/10.3133/tm4F5.","productDescription":"Report: viii, 50 p.; Software Release","onlineOnly":"Y","ipdsId":"IP-100912","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":436689,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9NQ1RFY","text":"USGS data release","linkHelpText":"DGMETA (Version 1): Dissolved Gas Modeling and Environmental Tracer Analysis Computer Program"},{"id":382045,"rank":3,"type":{"id":35,"text":"Software Release"},"url":"https://code.usgs.gov/cawsc/DGMETA","text":"DGMETA","linkHelpText":"- DGMETA (Dissolved Gas Modeling and Environmental Tracer Analysis) is a Microsoft Excel-based computer program that is used for modeling air-water equilibrium conditions from measurements of dissolved gases and for computing concentrations of environmental tracers that rely on air-water equilibrium model results."},{"id":382038,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/04/f05/coverthb.jpg"},{"id":382039,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/04/f05/tm4f5.pdf","text":"Report","size":"8.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"TM 4-F5"}],"contact":"<p><a href=\"mailto:gs-w_opp_nawqa_science_team@usgs.gov\" data-mce-href=\"mailto:gs-w_opp_nawqa_science_team@usgs.gov\">NAWQA Science Team</a><br>U.S. Geological Survey<br>12201 Sunrise Valley Drive, MS 413<br>Reston, VA 20192–0002</p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Methods</li><li>Program Description</li><li>Examples</li><li>Installation Notes</li><li>Disclaimer</li><li>References Cited</li></ul>","publishedDate":"2021-01-08","noUsgsAuthors":false,"publicationDate":"2021-01-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Jurgens, Bryant C. 0000-0002-1572-113X bjurgens@usgs.gov","orcid":"https://orcid.org/0000-0002-1572-113X","contributorId":127842,"corporation":false,"usgs":true,"family":"Jurgens","given":"Bryant","email":"bjurgens@usgs.gov","middleInitial":"C.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":807830,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Böhlke, J. K. 0000-0001-5693-6455","orcid":"https://orcid.org/0000-0001-5693-6455","contributorId":173577,"corporation":false,"usgs":true,"family":"Böhlke","given":"J. K.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":false,"id":807831,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haase, Karl B. 0000-0002-6897-6494 khaase@usgs.gov","orcid":"https://orcid.org/0000-0002-6897-6494","contributorId":205943,"corporation":false,"usgs":true,"family":"Haase","given":"Karl","email":"khaase@usgs.gov","middleInitial":"B.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":807832,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Busenberg, Eurybiades ebusenbe@usgs.gov","contributorId":2271,"corporation":false,"usgs":true,"family":"Busenberg","given":"Eurybiades","email":"ebusenbe@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":807833,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hunt, Andrew G. 0000-0002-3810-8610 ahunt@usgs.gov","orcid":"https://orcid.org/0000-0002-3810-8610","contributorId":1582,"corporation":false,"usgs":true,"family":"Hunt","given":"Andrew","email":"ahunt@usgs.gov","middleInitial":"G.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":807834,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hansen, Jeffrey A. 0000-0002-2185-1686 jahansen@usgs.gov","orcid":"https://orcid.org/0000-0002-2185-1686","contributorId":247521,"corporation":false,"usgs":false,"family":"Hansen","given":"Jeffrey A.","email":"jahansen@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":807835,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70217055,"text":"fs20203070 - 2020 - Early warning pesticide monitoring in Nevada’s surface waters","interactions":[],"lastModifiedDate":"2020-12-31T16:40:07.217712","indexId":"fs20203070","displayToPublicDate":"2020-12-31T11:15:00","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-3070","displayTitle":"Early Warning Pesticide Monitoring in Nevada’s Surface Waters","title":"Early warning pesticide monitoring in Nevada’s surface waters","docAbstract":"<p>A pesticide is a substance, or mixture of substances, used to kill or control insects, weeds, plant diseases, and other pest organisms. Commercial pesticide applicators, farmers, and homeowners apply about 1.1 billion pounds of pesticides annually to agricultural land, non-crop land, and urban areas throughout the United States. Although intended for beneficial uses, there are also risks associated with pesticide applications, including contamination of groundwater and surface-water resources, which can adversely affect aquatic life and water supplies. Pesticides can contaminate groundwater and surface water directly through point sources (spills, disposal sites, or pesticide drift during an application). The main avenue of contamination, however, is indirect by non-point sources, which include agricultural and urban runoff, erosion, leaching from application sites, and precipitation that has become contaminated by upwind applications.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20203070","collaboration":"Prepared in cooperation with the Nevada Department of Agriculture","usgsCitation":"Huntington, J.M., Entz, D.C., and Thodal, C.E., 2020, Early warning pesticide monitoring in Nevada’s surface waters: U.S. Geological Survey Fact Sheet 2020–3070, 6 p., https://doi.org/10.3133/fs20203070.","productDescription":"6 p.","numberOfPages":"6","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-116736","costCenters":[{"id":465,"text":"Nevada Water Science 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 \"}}]}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/nv-water\" data-mce-href=\"https://www.usgs.gov/centers/nv-water\">Nevada Water Science Center</a><br>U.S. Geological Survey<br>2730 N. Deer Run Road<br>Carson City, Nevada 89701</p><p><a href=\"../contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Introduction</li><li>Nevada Pesticide Monitoring and Early Warning Program</li><li>Results and Discussion</li><li>Summary</li><li>Acknowledgments</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2020-12-31","noUsgsAuthors":false,"publicationDate":"2020-12-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Huntington, Jena M. 0000-0002-9291-1404 jmhunt@usgs.gov","orcid":"https://orcid.org/0000-0002-9291-1404","contributorId":2294,"corporation":false,"usgs":true,"family":"Huntington","given":"Jena","email":"jmhunt@usgs.gov","middleInitial":"M.","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":807418,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Entz, Derek C.","contributorId":245977,"corporation":false,"usgs":false,"family":"Entz","given":"Derek","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":807419,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thodal, Carl E. 0000-0003-0782-3280 cethodal@usgs.gov","orcid":"https://orcid.org/0000-0003-0782-3280","contributorId":2292,"corporation":false,"usgs":true,"family":"Thodal","given":"Carl","email":"cethodal@usgs.gov","middleInitial":"E.","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":807420,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70215999,"text":"70215999 - 2020 - The response of streams to changes in atmospheric deposition of sulfur and nitrogen in the Adirondack Mountains","interactions":[],"lastModifiedDate":"2021-10-01T15:52:52.924612","indexId":"70215999","displayToPublicDate":"2020-12-31T10:48:48","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"seriesTitle":{"id":9141,"text":"Final Report","active":true,"publicationSubtype":{"id":2}},"seriesNumber":"20-19","title":"The response of streams to changes in atmospheric deposition of sulfur and nitrogen in the Adirondack Mountains","docAbstract":"<p>Acidic deposition is the result of upwind sulfur (S) and nitrogen (N) emissions into the atmosphere from human activities. Environmental impacts from acidic deposition across forested landscapes include acidification of soil and drainage water, depletion of available soil nutrient bases, and impacts to and changes in forest and aquatic species composition and biodiversity. Acidic deposition can mobilize aluminum (Al) from soil-to-soil solution and subsequently to drainage water in forms that can be toxic to aquatic life. When exposed to decreasing levels of acidic deposition, which has been occurring in New York since the late 1970s, some soils and drainage waters have become gradually less acidic. Remaining questions relate to effects on stream resources, anticipated resource recovery under increasingly lower levels of deposition, and the levels of deposition (target loads, TLs) needed to reach a range of stream ecosystem recovery targets. Environmental scientists commonly estimate thresholds of air pollutant emissions and resulting atmospheric deposition at which adverse ecological effects are manifested. This analysis is often done using critical loads (CL) and/or TLs, using approaches that account for the spatial and temporal aspects of acidification and recovery. Exceedance represents the extent to which current levels of acidic deposition exceed the level expected to cause ecological harm. The research reported here is intended to help address S and N deposition TLs and ecosystem recovery of Adirondack streams, a resource that has been less thoroughly investigated than lakes. The overarching goal of this work is to highlight key considerations that will help inform decision-makers and ecosystem managers who are responsible for environmental policy in New York State and beyond. Salient aspects of stream TL modeling are discussed with an aim of informing not only scientists, but also policymakers, ecosystem managers, and nonscientists who are required to make decisions related to the effects of acidic deposition on natural ecosystems. Analyses reported herein quantify relations among chemical indicators and metrics of fish community health and biodiversity in streams of the Adirondack Park. This information is used to indicate levels of atmospheric deposition necessary to alleviate harmful effects on fish populations. Results of this investigation provide a framework that can be applied to better understand how modeled stream acid neutralizing capacity (ANC) values that are developed to support TL investigations can be adjusted to reflect high-flow ANC values that may be associated with toxic conditions. Since process models are often calibrated to a low-flow or average flow condition, the magnitude and spatial extent of TL exceedances increase substantially when episodic acidification is considered.</p>","language":"English","publisher":"New York State Energy Research and Development Authority","usgsCitation":"Driscoll, C., Shao, S., Sullivan, T.J., McDonnell, T.C., Baldigo, B.P., Burns, D., and Lawrence, G.B., 2020, The response of streams to changes in atmospheric deposition of sulfur and nitrogen in the Adirondack Mountains: Final Report 20-19, 166 p.","productDescription":"166 p.","ipdsId":"IP-103637","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":390128,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":390127,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://www.nyserda.ny.gov/-/media/Files/Publications/Research/Environmental/20-19-Responses-of-Streams-in-the-Adirondack-Mountains.pdf"}],"country":"United States","state":"New York","otherGeospatial":"Adirondack Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -74.00390625,\n              43.11702412135048\n            ],\n            [\n              -73.41064453125,\n              43.44494295526125\n            ],\n            [\n              -73.3447265625,\n              44.000717834282774\n            ],\n            [\n              -73.32275390625,\n              44.32384807250689\n            ],\n            [\n              -73.6083984375,\n              44.84029065139799\n            ],\n            [\n              -74.014892578125,\n              44.933696389694674\n            ],\n            [\n              -74.564208984375,\n              44.793530904744074\n            ],\n            [\n              -75.091552734375,\n              44.53567453241317\n            ],\n            [\n              -75.487060546875,\n              44.06390660801779\n            ],\n            [\n              -75.35522460937499,\n              43.492782808225\n            ],\n            [\n              -74.893798828125,\n              43.18114705939968\n            ],\n            [\n              -74.520263671875,\n              43.068887774169625\n            ],\n            [\n              -74.00390625,\n              43.11702412135048\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Driscoll, Charles T.","contributorId":240874,"corporation":false,"usgs":false,"family":"Driscoll","given":"Charles T.","affiliations":[{"id":5082,"text":"Syracuse University","active":true,"usgs":false}],"preferred":false,"id":803731,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shao, Shuai","contributorId":222597,"corporation":false,"usgs":false,"family":"Shao","given":"Shuai","email":"","affiliations":[{"id":5082,"text":"Syracuse University","active":true,"usgs":false}],"preferred":false,"id":803735,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sullivan, Timothy J.","contributorId":196720,"corporation":false,"usgs":false,"family":"Sullivan","given":"Timothy","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":803732,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McDonnell, Todd C.","contributorId":127622,"corporation":false,"usgs":false,"family":"McDonnell","given":"Todd","email":"","middleInitial":"C.","affiliations":[{"id":7087,"text":"Scientist, E&S Environmental Chemistry Inc, Corvallis OR","active":true,"usgs":false}],"preferred":false,"id":803736,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Baldigo, Barry P. 0000-0002-9862-9119 bbaldigo@usgs.gov","orcid":"https://orcid.org/0000-0002-9862-9119","contributorId":1234,"corporation":false,"usgs":true,"family":"Baldigo","given":"Barry","email":"bbaldigo@usgs.gov","middleInitial":"P.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":803733,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Burns, Douglas A. 0000-0001-6516-2869","orcid":"https://orcid.org/0000-0001-6516-2869","contributorId":202943,"corporation":false,"usgs":true,"family":"Burns","given":"Douglas A.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":37778,"text":"WMA - 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,{"id":70217210,"text":"70217210 - 2020 - Potentiometric surface maps of selected confined aquifers in southern Maryland and Maryland's eastern shore, 2019","interactions":[],"lastModifiedDate":"2021-09-30T15:54:38.216304","indexId":"70217210","displayToPublicDate":"2020-12-31T10:47:46","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"seriesTitle":{"id":128,"text":"Open-File Report","active":false,"publicationSubtype":{"id":2}},"seriesNumber":"20-02-01","title":"Potentiometric surface maps of selected confined aquifers in southern Maryland and Maryland's eastern shore, 2019","docAbstract":"<p>This report presents potentiometric-surface maps of the Aquia and Magothy aquifers and the Upper Patapsco, Lower Patapsco, and Patuxent aquifer systems using water levels measured during the fall season of 2019. The potentiometric surface maps show water levels ranging from 56 feet above sea level to 163 feet below sea level in the Aquia aquifer, from 87 feet above sea level to 119 feet below sea level in the Magothy aquifer, from 114 feet above sea level to 120 feet below sea level in the Upper Patapsco aquifer system, from 136 feet above sea level to 174 feet below sea level in the Lower Patapsco aquifer system, and from 168 feet above sea level to 184 feet below sea level in the Patuxent aquifer system.</p><p>Cones of depression have formed around locations with significant aquifer withdrawals. The Aquia aquifer has depressed water levels around well fields at Lexington Park, Solomons Island, and central Talbot County. Cones of depression have formed in the Magothy aquifer around well fields at Waldorf, Arnold, and Easton. The Upper Patapsco aquifer system has depressed water levels around well fields in the Annapolis-Arnold area, Waldorf, the Lexington Park-Leonardtown area, and at Easton. The Lower Patapsco aquifer system has depressed water levels around well fields at Severndale, Broad Creek, Arnold, and Crofton Meadows as well as in central and western Charles County. Cones of depression have formed in the Patuxent aquifer system around well fields at Dorsey Road, Crofton, Arnold, northwestern Charles County, and at the Chalk Point power plant. </p>","language":"English","publisher":"Maryland Department of Natural Resources","usgsCitation":"Staley, A.W., Andreasen, D.C., and Marchand, E.H., 2020, Potentiometric surface maps of selected confined aquifers in southern Maryland and Maryland's eastern shore, 2019: Open-File Report 20-02-01, iii, 37 p.","productDescription":"iii, 37 p.","ipdsId":"IP-120572","costCenters":[{"id":41514,"text":"Maryland-Delaware-District of Columbia  Water Science Center","active":true,"usgs":true}],"links":[{"id":390041,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":390040,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://www.mgs.md.gov/reports/OFR_20-02-01.pdf"}],"country":"United 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,{"id":70220610,"text":"70220610 - 2020 - Council monitoring and assessment program (CMAP): Common monitoring program attributes and methodologies for the Gulf of Mexico Region","interactions":[],"lastModifiedDate":"2021-05-21T15:45:26.898403","indexId":"70220610","displayToPublicDate":"2020-12-31T10:37:21","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5134,"text":"NOAA Technical Memorandum","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"285","title":"Council monitoring and assessment program (CMAP): Common monitoring program attributes and methodologies for the Gulf of Mexico Region","docAbstract":"<p>Executive Summary Under the Resources and Ecosystem Sustainability, Tourist Opportunities, and Revived Economies of the Gulf Coast States Act of 2012 (RESTORE Act), the Gulf Coast Ecosystem Restoration Council (RESTORE Council or Council) is required to report on the progress of funded projects and programs. Systematic monitoring of restoration at the project-specific and programmatic-levels (i.e., watershed and Gulf of Mexico) enables consistent reporting and gives the public confidence that the restoration investments selected by the RESTORE Council will be evaluated and adaptively managed accordingly. Monitoring information that has been collected at different spatial and temporal scales can be used as the foundation to illustrate progress towards comprehensive ecosystem restoration goals and objectives that promote holistic Gulf of Mexico recovery (see ‘RESTORE Council Background’ at the beginning of this report for additional Council information). </p><p>Federal, state and local agencies, universities, private industry, and non-governmental organizations (NGOs) have conducted and are conducting extensive monitoring activities around the Gulf of Mexico. In addition, each RESTORE Council-funded project will, at a minimum, perform project-specific monitoring. This collection of monitoring activities was inventoried and compiled into a framework of tools and resources by the Council-funded RESTORE Council Monitoring and Assessment Program (CMAP). CMAP was designed and funded to inventory and integrate existing water quality and habitat monitoring and mapping efforts to support discovery and accessibility of existing monitoring data and ensure the collected information is made available to support management decisions. Results of CMAP Inventory queries can be used to identify opportunities for efficiencies and support crossprogram review of performance across Gulf of Mexico ecosystem recovery efforts. </p><p>The fundamental approach being used to inform the build out of the CMAP Gulf of Mexico water quality monitoring, habitat monitoring, and mapping framework includes: 1. Adopt, or construct as needed, a comprehensive inventory of existing habitat and water quality observation, monitoring, and mapping programs in the Gulf of Mexico (hereafter referred to as the “Inventory”; NOAA and USGS, 2019a); 2. Evaluate the suitability/applicability of each program and its existing and prospective data for use in restoration activities; 3. Develop a process to use the Inventory to conduct gap assessments; 4. Develop a catalog of baseline assessments conducted in the Gulf of Mexico (NOAA and USGS, 2019b); and 5. Develop a searchable monitoring information portal/database to enable access to collected information and products.</p>","language":"English","publisher":"National Oceanic and Atmospheric Administration (NOAA)","doi":"10.25923/vxay-xz10","usgsCitation":"Bosch, J., Burkart, H.B., Chivoiu, B., Clark, R., Clement, C., Enwright, N., Giordano, S., Jeffrey, C., Johnson, E., Hart, R., Hile, S.D., Howell, J.S., Laurenzano, C., Lee, M., McCloskey, T., McTigue, T., Meyers, M.B., Miller, K.E., Mize, S., Monaco, M.E., Owen, K., Rebich, R., Rendon, S.H., Robertson, A., Sample, T., Sanks, K.M., Steyer, G., Suir, K., Swarzenski, C.M., and Thurman, H.R., 2020, Council monitoring and assessment program (CMAP): Common monitoring program attributes and methodologies for the Gulf of Mexico Region: NOAA Technical Memorandum 285, ii, 87 p., https://doi.org/10.25923/vxay-xz10.","productDescription":"ii, 87 p.","ipdsId":"IP-120968","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":385844,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alabama, Florida, Georgia, Louisiana, Mississippi, Texas","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -81.5625,\n              31.259769987394286\n            ],\n            [\n              -87.95654296875,\n              31.70947636001935\n            ],\n            [\n              -91.0986328125,\n              31.80289258670676\n            ],\n            [\n              -92.59277343749999,\n              31.090574094954192\n            ],\n            [\n              -96.3720703125,\n              30.240086360983426\n            ],\n            [\n              -98.61328125,\n              28.38173504322308\n            ],\n            [\n              -98.10791015625,\n              26.2145910237943\n            ],\n            [\n              -97.14111328125,\n              25.859223554761407\n            ],\n            [\n              -80.9033203125,\n              24.647017162630366\n            ],\n            [\n              -79.8046875,\n              25.423431426334222\n            ],\n            [\n              -79.78271484375,\n              27.254629577800063\n            ],\n            [\n              -81.2109375,\n              30.619004797647808\n            ],\n            [\n              -81.5625,\n              31.259769987394286\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bosch, Julie","contributorId":218503,"corporation":false,"usgs":false,"family":"Bosch","given":"Julie","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":816148,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burkart, Heidi B","contributorId":258254,"corporation":false,"usgs":false,"family":"Burkart","given":"Heidi","email":"","middleInitial":"B","affiliations":[{"id":52262,"text":"CSS, Inc.; 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,{"id":70215354,"text":"70215354 - 2020 - Smallmouth buffalo (Ictiobus bubalus) growth across a 1200km human use and ecological disturbance gradient in the Upper Mississippi River System","interactions":[],"lastModifiedDate":"2021-10-01T15:35:34.106947","indexId":"70215354","displayToPublicDate":"2020-12-31T10:25:19","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":9371,"text":"Mississippi River Restoration Program","active":true,"publicationSubtype":{"id":1}},"displayTitle":"Smallmouth buffalo (<i>Ictiobus bubalus</i>) growth across a 1200km human use and ecological disturbance gradient in the Upper Mississippi River System","title":"Smallmouth buffalo (Ictiobus bubalus) growth across a 1200km human use and ecological disturbance gradient in the Upper Mississippi River System","docAbstract":"Smallmouth buffalo (Ictiobus bubalus) is a common and widely distributed large-bodied species of the family Catostomidae.  It inhabits large rivers and reservoirs of the eastern continental United States (east of the continental Divide) and is most abundant and common in the large rivers of the Midwest and Central Plains, though it does occur as far north and east as the Hudson Bay drainage and as far south and west as Arizona (Edwards and Twoney 1982).\n\nHistorically, smallmouth buffalo were an important component of commercial fisheries on both the Mississippi and Illinois Rivers.  However, following the introduction of common carp (Cyprinus carpio) in the mid-1800s (Carlander 1954), the construction of a system of navigation dams on Upper Mississippi and Illinois River in the 1930s (USGS 1999), and water quality/pollution issues through the 1980s (Weiner 2010), the role of smallmouth buffalo in the overall UMRS fish community and commercial fishery has generally diminished relative to historical standards.  Still, smallmouth buffalo remains an important and valued component of the UMRS commercial fishery.\n\nThe study area is represented by three study reaches on the Illinois River and three study reaches on the Upper Mississippi River (Figure 1).  Collectively, these study reaches represent nearly 1200 river km and exist across strong and pronounced ecological and disturbance gradients.  For example, habitat composition, water quality, commercial navigation intensity, aquatic plant prominence, and the number and abundance of nonnative fish species vary strongly across the study domain, with northern Mississippi River reaches exhibiting less navigation traffic, better water quality, markedly greater aquatic plant prominence, more diverse habitat composition, and comparably much smaller numbers of nonnative species than the lower Mississippi River study reach and those on the Illinois River (USGS 1999; Johnson and Hagerty [eds] 2008; Irons et al. 2009).\n\nLong term monitoring efforts conducted under the auspices of the Upper Mississippi River Restoration program over the past 27 years have provided tremendous insights into shifts and changes of the overall UMRS fish community (Ickes et al. 2005; Garvey et al. 2010; Schramm and Ickes 2016).  However, these monitoring efforts observe only the most basic aspects of the UMRS fish community (i.e., catch, length, weight, distribution, and occurrence).  To gain a greater understanding of forces driving community level shifts and changes, more directed study is needed on the functional attributes of fish populations (i.e., growth, mortality, recruitment).  Collectively, these functional attributes of populations are termed population dynamics and/or vital rates.\n\nIt is important to note, the population dynamics of fishes in large rivers is generally poorly understood, especially for non-game species (Ickes 2018).  The prevailing view is that abiotic factors largely govern inter-annual population dynamics, typically based upon rather short-term observations and correlations with assorted abiotic river attributes that vary on a seasonal or annual basis (for example, Risotto and Turner 1985).  However, the role that longer-term abiotic factors play in regulating population abundance, or that biotic factors internal to the population (e.g., spawner-recruit dynamics, growth dynamics) or external to the population (e.g., predator-prey dynamics, sympatric competitors, disease) remain poorly understood.  Achieving a greater understanding of these dynamics is important for stock, game, and invasive species management.\n\nIn 2017, as part of a larger study designed to gain vital population rate information for smallmouth buffalo in the Upper Mississippi and Illinois Rivers (“Smallmouth Buffalo population demographics of the Upper Mississippi River System”; UMRR LTRM 2018SOW project items 2018MMBF1-2018MMBF6) annual growth patterns in smallmouth buffalo were determined and evaluated.  This was accomplished by measuring growth histories recorded in annual growth increments on hard bony parts (here otoliths), a method known generically as biochronology, and somewhat analogous to dendrochronology practiced by foresters.  These methods allow one to generate time-series of annual growth histories that depend upon age, year class (i.e., cohort), and annual environmental conditions experienced by the population over time (Weisberg, 1993).\n\nBiochronology methods were used to develop a 36-year time series of smallmouth buffalo growth in the Upper Mississippi and Illinois Rivers across a 1200 km ecological and human use disturbance gradient.  Annual growth intervals were identified and measured from otoliths to determine fish age and growth history.  A mixed model that parses the growth increment into age and year effects was fit to these data.\n\nGiven the pronounced ecological and disturbance gradients inherent to the UMRS and the study domain, an a priori expectation of differing patterns in growth is accepted as a null hypothesis to test.\n\nThe goal of this study was to model smallmouth buffalo growth as a function of the age of the fish and the growth year in which the growth was gained.  The primary modeling objective was to parse growth observed on each annulus into a portion attributable to the age of the fish and the portion attributable to the year in which the growth was gained.  In effect, this modeling approach removes the somewhat trivial age effects on growth so that a non-confounded growth year effect can be gained.  Results attributable to growth year provide a time series of growth information that is of the same duration as the oldest fish observed and solely reflects environmental influences on growth.  These model responses can then be investigated relative to environmental covariate time-series suspected of influencing growth of smallmouth buffalo in the Upper Mississippi and Illinois Rivers (e.g., temperature, discharge, population density, population mortality, forage availability, sympatric competition, habitat composition, navigation intensity, nonnative fish prominence, etc.).  Thus, the primary scientific objective was to investigate if and how smallmouth buffalo growth varies in accordance with innate ecological and disturbance gradients across the study domain.","language":"English","publisher":"US Army Corps of Engineers","usgsCitation":"Ickes, B., 2020, Smallmouth buffalo (Ictiobus bubalus) growth across a 1200km human use and ecological disturbance gradient in the Upper Mississippi River System: Mississippi River Restoration Program, 16 p.","productDescription":"16 p.","ipdsId":"IP-111767","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":390126,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":390125,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://umesc.usgs.gov/reports_publications/ltrmp_rep_list.html"}],"country":"United States","state":"Illinois, Iowa, Minnesota, Missouri, Wisconsin","otherGeospatial":"Illinois 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,{"id":70227729,"text":"70227729 - 2020 - Identifying and assessing priority transboundary aquifers along the United States- Mexico border","interactions":[],"lastModifiedDate":"2022-03-22T15:07:45.460807","indexId":"70227729","displayToPublicDate":"2020-12-31T10:06:58","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":9366,"text":"CCAST Case Study on Actionable Science","active":true,"publicationSubtype":{"id":1}},"title":"Identifying and assessing priority transboundary aquifers along the United States- Mexico border","docAbstract":"<p>Many of the 15 million inhabitants along the United States-Mexico border derive fresh water from transboundary aquifers straddling and extending far beyond the political boundary separating the two countries. The previous lack of a large-scale cooperative and structured data collection effort and groundwater management strategy for the region has left border communities with little information on current and future groundwater supplies. In 2006, the U.S. Federal Government enacted the United States – Mexico Transboundary Aquifer Assessment Act (Public Law 109–448) to address this issue. </p>","language":"English","publisher":"U.S. Bureau of Reclamation","usgsCitation":"Pasley, N.K., 2020, Identifying and assessing priority transboundary aquifers along the United States- Mexico border: CCAST Case Study on Actionable Science, HTML Document.","productDescription":"HTML Document","ipdsId":"IP-123237","costCenters":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":397397,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":394960,"type":{"id":15,"text":"Index Page"},"url":"https://usbr.maps.arcgis.com/apps/MapSeries/index.html?appid=659fa1717014452aa67e88e228e28c12"}],"country":"Mexico, United States","state":"Chihuahua, New Mexico, Texas","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -107.5341796875,\n              30.44867367928756\n            ],\n            [\n              -104.69970703125,\n              30.44867367928756\n            ],\n            [\n              -104.69970703125,\n              32.194208672875384\n            ],\n            [\n              -107.5341796875,\n              32.194208672875384\n            ],\n            [\n              -107.5341796875,\n              30.44867367928756\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Pasley, Nathaniel Kyle 0000-0001-7441-495X","orcid":"https://orcid.org/0000-0001-7441-495X","contributorId":272301,"corporation":false,"usgs":true,"family":"Pasley","given":"Nathaniel","email":"","middleInitial":"Kyle","affiliations":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":831941,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70216703,"text":"70216703 - 2020 - Assessing the state of water resource knowledge and tools for future planning in the lower Rio Grande-Rio Bravo Basin","interactions":[],"lastModifiedDate":"2021-10-01T14:53:10.862751","indexId":"70216703","displayToPublicDate":"2020-12-31T09:51:38","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":9366,"text":"CCAST Case Study on Actionable Science","active":true,"publicationSubtype":{"id":1}},"title":"Assessing the state of water resource knowledge and tools for future planning in the lower Rio Grande-Rio Bravo Basin","docAbstract":"<p>The Rio Grande/Rio Bravo Basin (hereinafter referred to as the Rio Grande) is a transboundary basin, with the Rio Grande forming the border between the United States and Mexico for approximately 2,034 km. The waters of the Rio Grande serve as a critical drinking source for 13 million people, connecting numerous population centers representing diverse backgrounds and cultures along its length. Cross-border ecosystems and communities make water management strategies particularly challenging. With different regulations and societal interests in the two countries, developing effective water-management strategies is challenging and requires the coordination of diverse interested parties representing different government agencies, institutions, and stakeholder groups with varying and sometimes conflicting objectives. To better evaluate the human and environmental water needs (environmental flows) of this constrained river system, an improved understanding of past and present water management objectives, policies, allocation practices, and water use is needed. </p>","language":"English","publisher":"Collaborative Conservation and Adaptation Strategy Toolbox (CCAST)","usgsCitation":"Casarez, I.R., Sandoval-Solis, S., and Ortiz-Partida, J.P., 2020, Assessing the state of water resource knowledge and tools for future planning in the lower Rio Grande-Rio Bravo Basin: CCAST Case Study on Actionable Science, HTML Document.","productDescription":"HTML Document","ipdsId":"IP-123346","costCenters":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":390121,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":390120,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://usbr.maps.arcgis.com/apps/MapSeries/index.html?appid=fdb848b819c94e2e8b1a800e7a5fc54c"}],"country":"Mexico, United States","otherGeospatial":"Lower Rio Grande-Río Bravo Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -108.80859375,\n              30.29701788337205\n            ],\n            [\n              -104.67773437499999,\n              30.29701788337205\n            ],\n            [\n              -104.67773437499999,\n              32.10118973232094\n            ],\n            [\n              -108.80859375,\n              32.10118973232094\n            ],\n            [\n              -108.80859375,\n              30.29701788337205\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Casarez, Ilana Renae 0000-0001-7690-3802","orcid":"https://orcid.org/0000-0001-7690-3802","contributorId":228961,"corporation":false,"usgs":true,"family":"Casarez","given":"Ilana","email":"","middleInitial":"Renae","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":805942,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sandoval-Solis, Samuel 0000-0003-0329-3243","orcid":"https://orcid.org/0000-0003-0329-3243","contributorId":257770,"corporation":false,"usgs":false,"family":"Sandoval-Solis","given":"Samuel","email":"","affiliations":[{"id":7082,"text":"University of California - Davis","active":true,"usgs":false}],"preferred":false,"id":824529,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ortiz-Partida, Jose P.","contributorId":266181,"corporation":false,"usgs":false,"family":"Ortiz-Partida","given":"Jose","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":824530,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70230002,"text":"70230002 - 2020 - Biology characterization breakout report","interactions":[],"lastModifiedDate":"2022-03-23T14:35:20.517308","indexId":"70230002","displayToPublicDate":"2020-12-31T09:31:17","publicationYear":"2020","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Biology characterization breakout report","docAbstract":"The primary goal of the biology characterization breakout group was to identify the strategies, tools, data priorities, and key partnerships needed to conduct baseline biological characterizations of deep-sea benthic environments across the U.S. EEZ in the Pacific. Discussions focused primarily on priorities for the\ncharacterization of deep-water (>200-meter depths) benthic biological communities; however, the group also emphasized that such characterizations need to be linked to efforts to characterize the overlying water column. The group was tasked with identifying how to prioritize exploration and characterization efforts, including how to identify priority geographic areas and specific methodologies needed to execute exploration activities. The expert community that provided input included representatives from various stakeholder groups actively working on deep-sea issues across the Pacific, including researchers and managers from government agencies, academic institutions, nongovernmental institutions, and the private sector. This report provides a summary of specific guidance identified as key for the successful exploration of deep-sea benthic habitats within the U.S. EEZ in the Pacific, as well as in adjacent international waters.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Report on the Workshop to Identify National Ocean Exploration Priorities in the Pacific","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Consortium for Ocean Leadership","usgsCitation":"Demopoulos, A., Wagner, D., Baco-Taylor, A., Itano, D., Amon, D., Cordes, E.E., Levin, L., Edwards, P.H., Kosaki, R., Pomponi, S., and Gittings, S., 2020, Biology characterization breakout report, <i>in</i> Report on the Workshop to Identify National Ocean Exploration Priorities in the Pacific, p. 22-27.","productDescription":"6 p.","startPage":"22","endPage":"27","ipdsId":"IP-123141","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":397460,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":397443,"type":{"id":15,"text":"Index Page"},"url":"https://oceanleadership.org/discovery/ocean-exploration-pacific-priorities-workshop/"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Demopoulos, Amanda 0000-0003-2096-4694","orcid":"https://orcid.org/0000-0003-2096-4694","contributorId":221145,"corporation":false,"usgs":true,"family":"Demopoulos","given":"Amanda","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":838616,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wagner, Daniel","contributorId":289143,"corporation":false,"usgs":false,"family":"Wagner","given":"Daniel","affiliations":[{"id":16938,"text":"Conservation International","active":true,"usgs":false}],"preferred":false,"id":838617,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Baco-Taylor, Amy","contributorId":289145,"corporation":false,"usgs":false,"family":"Baco-Taylor","given":"Amy","email":"","affiliations":[{"id":7092,"text":"Florida State University","active":true,"usgs":false}],"preferred":false,"id":838618,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Itano, David","contributorId":289147,"corporation":false,"usgs":false,"family":"Itano","given":"David","email":"","affiliations":[{"id":62057,"text":"Western Pacific Fishery Management Council","active":true,"usgs":false}],"preferred":false,"id":838619,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Amon, Diva","contributorId":289148,"corporation":false,"usgs":false,"family":"Amon","given":"Diva","email":"","affiliations":[{"id":39858,"text":"Natural History Museum London","active":true,"usgs":false}],"preferred":false,"id":838620,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cordes, Erik E.","contributorId":37623,"corporation":false,"usgs":false,"family":"Cordes","given":"Erik","email":"","middleInitial":"E.","affiliations":[{"id":16710,"text":"Temple University, Department of Biology","active":true,"usgs":false}],"preferred":false,"id":838621,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Levin, Lisa","contributorId":289149,"corporation":false,"usgs":false,"family":"Levin","given":"Lisa","affiliations":[{"id":38264,"text":"Scripps Institution of Oceanography","active":true,"usgs":false}],"preferred":false,"id":838622,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Edwards, Peter H.","contributorId":206598,"corporation":false,"usgs":false,"family":"Edwards","given":"Peter","email":"","middleInitial":"H.","affiliations":[{"id":35748,"text":"U. of Leicester","active":true,"usgs":false}],"preferred":false,"id":838623,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kosaki, Randall","contributorId":289151,"corporation":false,"usgs":false,"family":"Kosaki","given":"Randall","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":838624,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Pomponi, Shirley","contributorId":289153,"corporation":false,"usgs":false,"family":"Pomponi","given":"Shirley","email":"","affiliations":[{"id":15312,"text":"Florida Atlantic University","active":true,"usgs":false}],"preferred":false,"id":838625,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Gittings, Steve","contributorId":289154,"corporation":false,"usgs":false,"family":"Gittings","given":"Steve","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":838626,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70210826,"text":"70210826 - 2020 - Recent planform changes in the Upper Mississippi River","interactions":[],"lastModifiedDate":"2021-11-03T14:42:36.620726","indexId":"70210826","displayToPublicDate":"2020-12-31T09:03:48","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5000,"text":"Long Term Resource Monitoring Technical Report","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"LTRM-2019GC8","title":"Recent planform changes in the Upper Mississippi River","docAbstract":"Geomorphic changes in the Upper Mississippi River (UMR) have long been a concern of river agencies charged with maintaining and restoring river habitat (GREAT 1980; Jackson et al. 1981; USFWS 1992). Large meandering alluvial rivers like the UMR are expected to constantly change and adjust their fluvial landforms within their riparian corridors as a result of the natural interaction of hydrologic processes, sediment movement, and vegetation over time. However, present geomorphic changes in the UMR reflect altered hydrologic, hydraulic, and sediment conditions caused by regulated flows, constructed agricultural levees and navigation dams, altered land use in the watershed, and climate change.  Levees reduce lateral hydrologic and sediment connectivity between channels and floodplains on many tributaries and on the Mississippi River downstream of Pool 13.  Between each of the dams are a repeating series of landforms associated with tailwater, intermediate, and impounded conditions. The dams maintain a minimum water level, thus creating many off-channel areas that act as sediment traps. Whereas high-head dams cut off sedimentological connectivity longitudinally through the river corridor (Skalak et al., 2013), low head dams on the UMR only slightly altered transport longitudinally. Deltaic-like sedimentation can be common in the impounded sections of dammed rivers. Erosion of relict land surfaces that remained above the raised impounded water levels has been the dominant change in UMR impounded sections due to increased wind fetch leading to increased wave action.  Even though upland sources of sediment from tributaries have decreased over the middle to late 20th century, increased annual precipitation, the interplay of increased variability in flood magnitudes from year to year, and more fall and winter flooding have likely changed erosion and sedimentation patterns in the UMR (Belby, et al., 2019). Paradoxically, monitoring and research indicates that the concentration of some water column constituents like total suspended solids and phosphorous has decreased during the 1991 to 2014 time period (Kreiling and Houser, 2016).  In areas prone to increased sedimentation, bed elevations rise and thereby water depths are reduced at a given discharge, resulting in loss of fish habitat. Sediment deposition or erosion further influences water exchange rates between main channel and off-channel areas in the river by increasing resistance in connecting channels or enlarging existing connecting channels. Water depth and water exchange rates are the most prominent features describing habitat quality in the UMR (De Jager et al. 2018), and in some cases, the trajectory of planform change from heightened deposition promises to threaten deep backwater habitats particularly important for overwintering fish.\n\nAlthough information on the rate of vertical change in bed elevation is needed for a complete assessment of geomorphic change associated with the loss of deep backwater habitats, mapping planform changes over time (i.e., lateral changes between the land-water boundary) provide needed information on the location, potential cause, and progressive direction of deposition, especially in the mid sections between dams where deltaic processes are the most pronounced. Several types of planform changes have been observed and identified as concerns. For example, island loss in the large impounded areas of the upper part of the UMR was one of the concerns identified by river managers in the 1980s and 90s, and subsequently island construction became a common form of restoration implemented by the Upper Mississippi River Restoration (UMRR) Program (USACE 2012). Other subtler planform changes, such as channel bank erosion and delta formation in backwaters, are perceived to be important, but have largely gone unquantified.  A systemwide reconnaissance of the UMR and IWW conducted in 1998 concluded that 14-percent of the river banks were eroding (Nakato and Anderson 1998).  However, stabilization of existing river banks has never been widely pursued as a restoration measure, due to the high cost and uncertain benefits.   Delta formation reduces the amount of backwater habitat; however, the deltas maintain and create a mix of riparian and aquatic habitats, and that is generally considered to be beneficial for wildlife and fish.  If recent hydrologic trends of more frequent and longer duration flood events continue, a better understanding of planform changes can help in describing past changes, and then be used to forecast potential future trajectories of change. If UMR resource managers determine that past and forecasted conditions are undesirable, then UMRR projects could be identified and prioritized to address those concerns.\n\nVegetative cover associations with landform changes have been used to detect and quantify planform changes in many rivers (Johnson 1985; Hiatt 2015; Volte et al. 2015). Freyer and Jefferson (2013) completed such a study in Pool 6 of the UMR using the landcover data from 12 dates over a 115-yr period, including the 1989, 2000, and 2010/2011 landcover/use (LCU) data from the UMRR Program. Planform change detected over the last 20 years represented by the UMRR Program data best reflect present-day geomorphic patterns, rates and processes. Changes occurring prior to dam construction and changes occurring soon after dam construction are likely not the same as those happening now, 50-70 years after dam construction and creation of the impoundments (McHenry et al., 1984; Bhowmik and Adams, 1986; WEST Consultants, 2000). \n\nThe LCU data from each of the 1989, 2000, and 2010/2011 imagery was developed using similar methods and is available in a Geographical Information System (GIS) for the entire UMR and therefore provides the opportunity for a more comprehensive planform change analysis. This study used GIS overlays of LCU classes to map and quantify changes in planform features over two periods, looking specifically for depositional areas where terrestrial and wetland vegetation expanded at the expense of open water. The land expansion was grouped into four possible process-based types common in large floodplain rivers, some following that used by Lewin et al. (2017). The four types include: crevasse deltas emanating from a breach from a main channel through a natural levee or narrow floodplain into backwaters (crevasse deltas), tributary deltas expanding into backwaters (tributary deltas), deltaic bars at the upstream end of impoundments (impounded deltas), and linear-like bars extending from the downstream ends of narrow levees and remnant floodplains (bar-tail limbs). The methods deployed for change detection addressed possible errors from a variety of sources.","language":"English","publisher":"US Army Corps of Engineers, Upper Mississippi River Restoration (UMRR) Program","usgsCitation":"Rogala, J.T., Fitzpatrick, F., and Hendrickson, J.S., 2020, Recent planform changes in the Upper Mississippi River: Long Term Resource Monitoring Technical Report LTRM-2019GC8, 33 p.","productDescription":"33 p.","ipdsId":"IP-113610","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":391325,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":391323,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://umesc.usgs.gov/documents/publications/2020/rogala_a_2020.html"}],"country":"United States","state":"Illinois, Iowa, Minnesota, Missouri, Wisconsin","otherGeospatial":"Upper Mississippi River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -90,\n              38.58252615935333\n            ],\n            [\n              -91.0546875,\n              40.07807142745009\n            ],\n            [\n              -90,\n              41.86956082699455\n            ],\n            [\n              -90.8349609375,\n              43.29320031385282\n            ],\n            [\n              -91.2744140625,\n              44.465151013519616\n            ],\n            [\n              -93.55957031249999,\n              46.01222384063236\n            ],\n            [\n              -93.4716796875,\n              46.619261036171515\n            ],\n            [\n              -95.1416015625,\n              46.46813299215554\n            ],\n            [\n              -94.52636718749999,\n              45.24395342262324\n            ],\n            [\n              -93.251953125,\n              44.55916341529182\n            ],\n            [\n              -91.93359375,\n              43.866218006556394\n            ],\n            [\n              -91.1865234375,\n              42.4234565179383\n            ],\n            [\n              -90.791015625,\n              42.22851735620852\n            ],\n            [\n              -91.14257812499999,\n              41.705728515237524\n            ],\n            [\n              -91.669921875,\n              41.07935114946899\n            ],\n            [\n              -91.97753906249999,\n              39.842286020743394\n            ],\n            [\n              -91.318359375,\n              38.89103282648846\n            ],\n            [\n              -90,\n              38.58252615935333\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Rogala, James T. 0000-0002-1954-4097 jrogala@usgs.gov","orcid":"https://orcid.org/0000-0002-1954-4097","contributorId":2651,"corporation":false,"usgs":true,"family":"Rogala","given":"James","email":"jrogala@usgs.gov","middleInitial":"T.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":791606,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fitzpatrick, Faith A. 0000-0002-9748-7075","orcid":"https://orcid.org/0000-0002-9748-7075","contributorId":209612,"corporation":false,"usgs":true,"family":"Fitzpatrick","given":"Faith A.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":791607,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hendrickson, Jon S.","contributorId":177520,"corporation":false,"usgs":false,"family":"Hendrickson","given":"Jon","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":791608,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70226640,"text":"70226640 - 2020 - Yellowstone River Compact Commission sixty-ninth annual report 2020","interactions":[],"lastModifiedDate":"2022-04-18T13:57:50.299897","indexId":"70226640","displayToPublicDate":"2020-12-31T08:51:05","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5883,"text":"Cooperator Report","active":true,"publicationSubtype":{"id":1}},"title":"Yellowstone River Compact Commission sixty-ninth annual report 2020","docAbstract":"<p>No abstract available.</p>","language":"English","publisher":"Yellowstone River Compact Commission","usgsCitation":"Davidson, S., 2020, Yellowstone River Compact Commission sixty-ninth annual report 2020: Cooperator Report, vi, 38 p.","productDescription":"vi, 38 p.","ipdsId":"IP-127113","costCenters":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"links":[{"id":398916,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":398915,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.usgs.gov/mission-areas/water-resources/science/yellowstone-river-compact-commission-annual-reports?qt-science_center_objects=0#qt-science_center_objects"}],"country":"United States","state":"Montana, North Dakota, Wyoming","otherGeospatial":"Yellowstone River basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -103.6669921875,\n              48.03401915864286\n            ],\n            [\n              -103.86474609375,\n              48.48748647988415\n            ],\n            [\n              -104.56787109374999,\n              48.531157010976706\n            ],\n            [\n              -106.9189453125,\n              47.15984001304432\n            ],\n            [\n              -110.61035156249999,\n              46.63435070293566\n            ],\n            [\n              -111.51123046875,\n              46.118941506107056\n            ],\n            [\n              -111.15966796875,\n              45.1510532655634\n            ],\n            [\n              -110.36865234374999,\n              44.19795903948531\n            ],\n            [\n              -108.96240234375,\n              42.73087427928485\n            ],\n            [\n              -107.75390625,\n              42.48830197960227\n            ],\n            [\n              -106.45751953125,\n              43.16512263158296\n            ],\n            [\n              -105.18310546875,\n              44.574817404670306\n            ],\n            [\n              -103.6669921875,\n              48.03401915864286\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Davidson, Seth 0000-0002-9548-468X","orcid":"https://orcid.org/0000-0002-9548-468X","contributorId":218042,"corporation":false,"usgs":true,"family":"Davidson","given":"Seth","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":827570,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70240818,"text":"70240818 - 2020 - He-CO2-N2 isotope and relative abundance characterization of geothermal fluids from the Ethiopian Rift","interactions":[],"lastModifiedDate":"2023-03-01T14:53:18.719283","indexId":"70240818","displayToPublicDate":"2020-12-31T08:36:37","publicationYear":"2020","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"displayTitle":"He-CO<sub>2</sub>-N<sub>2</sub> isotope and relative abundance characterization of geothermal fluids from the Ethiopian Rift","title":"He-CO2-N2 isotope and relative abundance characterization of geothermal fluids from the Ethiopian Rift","docAbstract":"<p>We report He-CO<sub>2</sub>-N<sub>2</sub> isotopic and relative abundances in free gases and dissolved gas phase of geothermal fluids from the Ethiopian Rift. Fluid samples were collected from ~30 geothermal localities from three key regions throughout rifted and non-rifted areas of Ethiopia. The majority of samples, including off-rift samples, indicate a strong contribution of mantle-derived He-C-N to the fluid samples. Helium (<sup>3</sup>He/<sup>4</sup>He) and δ15N-(N<sub>2</sub>) isotope anomalies are highest (&gt; 15.9RA and &gt; +5.0‰, respectively) at a single locality in south Afar (Sodere), but the maximum δ13C-(CO<sub>2</sub>) (-0.78‰) is found east of Lake Shalla in the Lake District of the Main Ethiopian Rift. High <sup>3</sup>He/<sup>4</sup>He values, consistent with mantle plume contributions, are also evident in fluids from the Lake District, where fluids from the Lake Shalla site extend up to 15.5RA. CO<sub>2</sub>/<sup>3</sup>He values span over four orders of magnitude while δ13C-(CO<sub>2</sub>) values cluster mostly between mantle-like values of -4 and -7‰; only samples east of Lake Shalla display more positive values. Atmospheric-derived nitrogen has likely influenced a number of measured δ15N-(N<sub>2</sub>) values but following a correction for atmospheric-contamination, the majority of samples reveal positive values (up to 6.5‰) which appear to be coupled to high <sup>3</sup>He/<sup>4</sup>He values. In regions affected by upwelling mantle plumes, such high values have been interpreted to reflect deep mantle inputs of recycled nitrogen. </p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings World Geothermal Congress 2020+1","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"World Geothermal Congress 2020","conferenceLocation":"Reykjavik, Iceland","language":"English","usgsCitation":"Halldorsson, S.A., Scarsi, P., Abebe, T., Evans, T., Kulongoski, J.T., Castillo, P.R., and Barry, P., 2020, He-CO2-N2 isotope and relative abundance characterization of geothermal fluids from the Ethiopian Rift, <i>in</i> Proceedings World Geothermal Congress 2020+1, Reykjavik, Iceland, 6 p.","productDescription":"6 p.","ipdsId":"IP-112494","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":413534,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":413533,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.geothermal-energy.org/cpdb/record_detail.php?id=33392","linkFileType":{"id":5,"text":"html"}}],"country":"Ethiopia","otherGeospatial":"Ethiopian Rift","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              42,\n              10\n            ],\n            [\n              36,\n              10\n            ],\n            [\n              36,\n              6\n            ],\n            [\n              42,\n              6\n            ],\n            [\n              42,\n              10\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Halldorsson, S. 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R.","contributorId":302629,"corporation":false,"usgs":false,"family":"Castillo","given":"P.","email":"","middleInitial":"R.","affiliations":[{"id":65520,"text":"Scripps Institution of Oceanography, UCSD, La Jolla, CA, USA","active":true,"usgs":false}],"preferred":false,"id":864920,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Barry, P. H.","contributorId":302630,"corporation":false,"usgs":false,"family":"Barry","given":"P. H.","affiliations":[{"id":65521,"text":"Woods Hole Oceanographic Institution, Woods Hole, MA, USA","active":true,"usgs":false}],"preferred":false,"id":864921,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70233244,"text":"70233244 - 2020 - Mars Subsurface Water Ice Mapping 2.0 data products and results","interactions":[],"lastModifiedDate":"2022-07-20T13:33:53.80749","indexId":"70233244","displayToPublicDate":"2020-12-31T08:33:17","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Mars Subsurface Water Ice Mapping 2.0 data products and results","docAbstract":"This work describes the results of the Mars Subsurface Water Ice Mapping (SWIM) project, with results on the distribution of ice on Mars from geomorphic, radar, and thermal analyses.","language":"English","publisher":"Planetary Science Institute","usgsCitation":"Putzig, N.E., Morgan, G.A., Bain, Z.M., Hollibaugh Baker, D.M., Bramson, A.M., Courville, S.W., Dundas, C., Hoover, R.H., Nerozzi, S., Pathare, A.V., Perry, M.R., Petersen, E.I., Sizemore, H.G., Campbell, B.A., Mastrogiuseppe, M., Mellon, M.T., and Smith, I.B., 2020, Mars Subsurface Water Ice Mapping 2.0 data products and results, HTML Document.","productDescription":"HTML Document","ipdsId":"IP-126866","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":404112,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":403995,"type":{"id":15,"text":"Index Page"},"url":"https://swim.psi.edu/SWIM2Products.php"}],"otherGeospatial":"Mars","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Putzig, Nathaniel E","contributorId":269987,"corporation":false,"usgs":false,"family":"Putzig","given":"Nathaniel","email":"","middleInitial":"E","affiliations":[{"id":24584,"text":"PSI","active":true,"usgs":false}],"preferred":false,"id":846888,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Morgan, Gareth A 0000-0002-9513-8736","orcid":"https://orcid.org/0000-0002-9513-8736","contributorId":229487,"corporation":false,"usgs":false,"family":"Morgan","given":"Gareth","email":"","middleInitial":"A","affiliations":[{"id":24584,"text":"PSI","active":true,"usgs":false}],"preferred":false,"id":846889,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bain, Zachary M","contributorId":293261,"corporation":false,"usgs":false,"family":"Bain","given":"Zachary","email":"","middleInitial":"M","affiliations":[{"id":24584,"text":"PSI","active":true,"usgs":false}],"preferred":false,"id":846890,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hollibaugh Baker, David M","contributorId":293262,"corporation":false,"usgs":false,"family":"Hollibaugh Baker","given":"David","email":"","middleInitial":"M","affiliations":[{"id":40052,"text":"NASA Goddard","active":true,"usgs":false}],"preferred":false,"id":846891,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bramson, Ali M 0000-0003-4903-0916","orcid":"https://orcid.org/0000-0003-4903-0916","contributorId":201618,"corporation":false,"usgs":false,"family":"Bramson","given":"Ali","email":"","middleInitial":"M","affiliations":[{"id":27205,"text":"U. 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,{"id":70217619,"text":"70217619 - 2020 - Estuarine habitat use by White Sturgeon (Acipenser transmontanus)","interactions":[],"lastModifiedDate":"2021-01-25T14:20:17.003115","indexId":"70217619","displayToPublicDate":"2020-12-31T08:11:20","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7563,"text":"San Francisco Estuary & Watershed Science","active":true,"publicationSubtype":{"id":10}},"title":"Estuarine habitat use by White Sturgeon (Acipenser transmontanus)","docAbstract":"<p><span>White Sturgeon (</span><i>Acipenser transmontanus)</i><span>, a species of concern in the San Francisco Estuary, is in relatively low abundance due to a variety of factors.&nbsp; The purpose of our study was to identify the estuarine habitat used by White Sturgeon to aid in the conservation and management of the species locally and across its range. We seasonally sampled sub-adult and adult White Sturgeon in the central estuary using setlines across a habitat gradient representative of three primary structural elements: shallow wetland channels (mean sample depth = 2 m), shallow open-water shoal (mean sample depth = 2 m), and deep open-water channel (mean sample depth = 7 m). We found that the shallow open-water shoal and deep open-water channel habitats were consistently occupied by White Sturgeon in spring, summer, and fall across highly variable water quality conditions, whereas the shallow wetland channel habitat was essentially unoccupied. We conclude that sub-adult and adult White Sturgeon inhabit estuaries in at least spring, summer, and fall and that small, shallow wetland channels are relatively unoccupied.</span></p>","language":"English","publisher":"University of California Davis","doi":"10.15447/sfews.2020v18iss4art4","usgsCitation":"Patton, O., Violette, V.L., Young, M.J., and Feyrer, F.V., 2020, Estuarine habitat use by White Sturgeon (Acipenser transmontanus): San Francisco Estuary & Watershed Science, v. 18, no. 4, 4, 10 p., https://doi.org/10.15447/sfews.2020v18iss4art4.","productDescription":"4, 10 p.","ipdsId":"IP-118307","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":454602,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.15447/sfews.2020v18iss4art4","text":"Publisher Index Page"},{"id":382537,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -123.07983398437499,\n              37.23907530202184\n            ],\n            [\n              -121.322021484375,\n              37.23907530202184\n            ],\n            [\n              -121.322021484375,\n              38.42777351132902\n            ],\n            [\n              -123.07983398437499,\n              38.42777351132902\n            ],\n            [\n              -123.07983398437499,\n              37.23907530202184\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"18","issue":"4","noUsgsAuthors":false,"publicationDate":"2020-12-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Patton, Oliver 0000-0002-2911-7718","orcid":"https://orcid.org/0000-0002-2911-7718","contributorId":218217,"corporation":false,"usgs":true,"family":"Patton","given":"Oliver","email":"","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":808917,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Violette, Veronica L. 0000-0002-7390-4655 vviolette@usgs.gov","orcid":"https://orcid.org/0000-0002-7390-4655","contributorId":222824,"corporation":false,"usgs":true,"family":"Violette","given":"Veronica","email":"vviolette@usgs.gov","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":808918,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Young, Matthew J. 0000-0001-9306-6866 mjyoung@usgs.gov","orcid":"https://orcid.org/0000-0001-9306-6866","contributorId":206255,"corporation":false,"usgs":true,"family":"Young","given":"Matthew","email":"mjyoung@usgs.gov","middleInitial":"J.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":808919,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Feyrer, Frederick V. 0000-0003-1253-2349 ffeyrer@usgs.gov","orcid":"https://orcid.org/0000-0003-1253-2349","contributorId":178379,"corporation":false,"usgs":true,"family":"Feyrer","given":"Frederick","email":"ffeyrer@usgs.gov","middleInitial":"V.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":808920,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70217288,"text":"70217288 - 2020 - Occurrence of a suite of stream-obligate amphibians in timberlands of Mendocino County, California, examined using environmental DNA","interactions":[],"lastModifiedDate":"2021-01-18T14:03:09.638748","indexId":"70217288","displayToPublicDate":"2020-12-31T08:01:43","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2901,"text":"Northwestern Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"Occurrence of a suite of stream-obligate amphibians in timberlands of Mendocino County, California, examined using environmental DNA","docAbstract":"<div class=\"div0\"><div class=\"row ArticleContentRow\"><p id=\"ID0EF\" class=\"first\">Stream-obligate amphibians are important indicators of ecosystem health in the Pacific Northwest, but distributional information to improve forest management is lacking in many regions. We analyzed archived DNA extracted from water samples in 60 pools in streams on private timberlands in Mendocino County, California, for 3 California Species of Special Concern—Coastal Tailed Frogs (<i>Ascaphus truei</i>), Foothill Yellow-legged Frogs (<i>Rana boylii</i>), and Southern Torrent Salamanders (<i>Rhyacotriton variegatus</i>)—to better understand their distributions in the region. Detection probabilities for eDNA of Foothill Yellow-legged Frogs and Coastal Tailed Frogs were positively influenced by water temperature. eDNA occurrence for both frogs was affected by whether silt or organic matter was a dominant substrate in the sampled pool, and Foothill Yellow-legged Frog eDNA occurrence was also affected by water temperature. Foothill Yellow-legged Frog eDNA occurrence had a strong, positive association with water temperature, with occurrence unlikely below 14°C and very likely above 16°C, and a positive association with silt or organic substrates in pools, which was likely an indicator of higher-order stream reaches. In contrast, Coastal Tailed Frogs had a negative association with silt or organic substrates. Historical visual detections were generally congruent with findings using eDNA, but differences highlight important areas for further study. We did not detect Southern Torrent Salamanders using eDNA at any sites. Our study reinforces that ecological relationships of these species are varied, and shows the importance of maintaining the integrity of streams with diverse characteristics for conserving stream amphibians.</p></div></div>","language":"English","publisher":"Society for Northwestern Vertebrate Biology","doi":"10.1898/1051-1733-101.3.194","usgsCitation":"Halstead, B., Goldberg, C.S., Douglas, R.B., Kleeman, P.M., and Ulrich, D.W., 2020, Occurrence of a suite of stream-obligate amphibians in timberlands of Mendocino County, California, examined using environmental DNA: Northwestern Naturalist, v. 101, no. 3, p. 194-209, https://doi.org/10.1898/1051-1733-101.3.194.","productDescription":"16 p.","startPage":"194","endPage":"209","ipdsId":"IP-113753","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":382260,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","county":"Mendocino 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Brian J. 0000-0002-5535-6528 bhalstead@usgs.gov","orcid":"https://orcid.org/0000-0002-5535-6528","contributorId":3051,"corporation":false,"usgs":true,"family":"Halstead","given":"Brian J.","email":"bhalstead@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":808287,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Goldberg, Caren S.","contributorId":76879,"corporation":false,"usgs":false,"family":"Goldberg","given":"Caren","email":"","middleInitial":"S.","affiliations":[{"id":5132,"text":"Washington State University, Pullman","active":true,"usgs":false}],"preferred":false,"id":808288,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Douglas, Robert B","contributorId":247757,"corporation":false,"usgs":false,"family":"Douglas","given":"Robert","email":"","middleInitial":"B","affiliations":[{"id":49643,"text":"Mendocino Redwood Company, LLC, PO Box 489/32601 Holquist Lane, Fort Bragg, CA 95347 USA","active":true,"usgs":false}],"preferred":false,"id":808289,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kleeman, Patrick M. 0000-0001-6567-3239 pkleeman@usgs.gov","orcid":"https://orcid.org/0000-0001-6567-3239","contributorId":3948,"corporation":false,"usgs":true,"family":"Kleeman","given":"Patrick","email":"pkleeman@usgs.gov","middleInitial":"M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":808290,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ulrich, David W","contributorId":247758,"corporation":false,"usgs":false,"family":"Ulrich","given":"David","email":"","middleInitial":"W","affiliations":[{"id":49644,"text":"Mendocino Redwood Company, LLC, PO Box 996/850 Kunzler Ranch Road, Ukiah, CA 95482 USA","active":true,"usgs":false}],"preferred":false,"id":808291,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70217884,"text":"70217884 - 2020 - Assessment of methods for soil monitoring in the Adirondack region of New York","interactions":[],"lastModifiedDate":"2021-02-09T13:33:48.676583","indexId":"70217884","displayToPublicDate":"2020-12-31T07:30:49","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Assessment of methods for soil monitoring in the Adirondack region of New York","docAbstract":"Repeated sampling to detect changes in forest soils was rarely used before 1990, but the value of soil monitoring in understanding environmental change is becoming well established.  The growing number of resampling studies has shown that sampling designs and procedures must be adapted to the objectives of the monitoring program and the soils being monitored.  In the Adirondack region, current priorities include the response of soils to large increases, and more recently, large decreases in acidic deposition, and changes driven by trending climate such as altered pools of soil organic carbon, as well as other unforeseen factors that will occur in the future.  \nTo improve methods and assess the feasibility of long-term soil monitoring in the Adirondack region, the United States Geological Survey (USGS) conducted a pilot project to evaluate a new sampling method for characterizing soils on a watershed basis.  Results obtained with this new approach, referred to as the ADK sampling method, was compared to methods used in previous sampling conducted in 2004 as part of the Western Adirondack Stream Survey (WASS), and also to previous high-replication pit sampling in the North and South Tributary watersheds of Buck Creek (North Buck and South Buck). The number of sampling locations and spatial distribution of sampling points within watersheds differed among the methods, although pit excavation was used to obtain samples in all cases.  In addition, this investigation evaluated the use of small diameter corers as a means to measure forest floor mass with greater accuracy and precision than commonly used methods such as pit excavation.\nSufficient statistical power to detect ecologically relevant changes in upper profile horizons (Oe, Oa and upper 10 cm of the B) were achieved with the ADK sampling method that utilized 18 pit excavations per watershed.  The sampling locations were organized within each watershed into three study areas (six sampling locations per study area) that represented the primary types of landscape within the watershed.  Sampling at 18 locations per watershed was found to be nearly as effective at detecting changes as sampling at 28 locations per watershed.   Numerous significant changes (P < 0.10) were detected with both 18 and 28 sampling locations at sampling intervals of 12 to 16 years.  The relationship between soil data obtained with the ADK method and stream chemistry at the base of the watershed suggested that this approach adequately characterized soil variability within the watershed for the purpose of studying soil-stream linkages.  Significant changes in upper B horizon calcium (P < 0.10) and Oa horizon aluminum (P < 0.01) were detected when the data from the four WASS watersheds were combined with the two Buck Creek watersheds, which suggested that there would be value in resampling other WASS watersheds previously sampled in 2004 to support a regional assessment.\nStudy results support small diameter cores as a useful method to monitor changes in the organic matter mass of the forest floor.  This method showed high reproducibility in repeated sampling tests and lower spatial variability in sample data than traditional approaches when compared on a watershed basis. Soil coring is also faster and requires less equipment than pit excavation methods, which makes it more conducive to sampling over large areas.   However, organic matter mass of the forest floor determined by coring was consistently less than the values obtained by the ADK sampling method that used pit sampling and vertical horizon measurements, and also literature values of a previous Adirondack study that utilized pit sampling in which the entire horizon was collected over a measured area.  However, a high correlation (R2 = 0.87) occurred between organic matter content (expressed as Mg ha-1) determined by coring and the ADK sampling method.  Differing methods with regard to where sample could be collected, and how organic matter was collected for chemical analysis were the likely reasons for differences in quantification of forest floor organic mass. \nCollection of forest floor cores in conjunction with the ADK method is recommended to provide improved sensitivity in detecting changes in the forest floor in proximity of where full analyses of the soil profile are being done.  This duel sampling approach represents an optimized method for measuring and understanding how Adirondack soils will change in the future.","language":"English","publisher":"NYS Energy Research and Development Authority","collaboration":"New York State Energy Research and Development Authority","usgsCitation":"Lawrence, G.B., and Antidormi, M.R., 2020, Assessment of methods for soil monitoring in the Adirondack region of New York, vi, 37 p.","productDescription":"vi, 37 p.","ipdsId":"IP-111655","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":383152,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":383151,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.nyserda.ny.gov/About/Publications/Research-and-Development-Technical-Reports/Environmental-Research-and-Development-Technical-Reports"}],"country":"United States","state":"New York","otherGeospatial":"Adirondack region","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -75.69580078125001,\n              43.77109381775648\n            ],\n            [\n              -75.06958007812501,\n              42.988576458321816\n            ],\n            [\n              -73.32275390625,\n              43.11702412135048\n            ],\n            [\n              -73.1689453125,\n              45.07352060670971\n            ],\n            [\n              -74.89379882812501,\n              44.91035917458492\n            ],\n            [\n              -75.69580078125001,\n              43.77109381775648\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lawrence, Gregory B. 0000-0002-8035-2350 glawrenc@usgs.gov","orcid":"https://orcid.org/0000-0002-8035-2350","contributorId":867,"corporation":false,"usgs":true,"family":"Lawrence","given":"Gregory","email":"glawrenc@usgs.gov","middleInitial":"B.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":810044,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Antidormi, Michael R. 0000-0002-3967-1173 mantidormi@usgs.gov","orcid":"https://orcid.org/0000-0002-3967-1173","contributorId":150722,"corporation":false,"usgs":true,"family":"Antidormi","given":"Michael","email":"mantidormi@usgs.gov","middleInitial":"R.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":810097,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70220285,"text":"70220285 - 2020 - The next frontier: Making research more reproducible","interactions":[],"lastModifiedDate":"2021-04-30T12:21:02.781787","indexId":"70220285","displayToPublicDate":"2020-12-31T07:20:45","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2501,"text":"Journal of Water Resources Planning and Management","active":true,"publicationSubtype":{"id":10}},"title":"The next frontier: Making research more reproducible","docAbstract":"Science and engineering rest on the concept of reproducibility. An important question for any study is: are the results reproducible? Can the results be recreated independently by other researchers or professionals? Research results need to be independently reproduced and validated before they are accepted as fact or theory. Across numerous fields like psychology, computer systems, and water resources there are problems to reproduce research results (Aarts et al. 2015; Collberg et al. 2014; Hutton et al. 2016; Stagge et al. 2019; Stodden et al. 2018). This editorial examines the challenges to reproduce research results and suggests community practices to overcome these challenges. Coordination is needed among the authors, journals, funders and institutions that produce, publish, and report research. Making research more reproducible will allow researchers, professionals, and students to more quickly understand and apply research in follow-on efforts and advance the field.","language":"English","publisher":"American Society of Civil Engineers","doi":"10.1061/(ASCE)WR.1943-5452.0001215","usgsCitation":"Rosenberg, D.E., Filion, Y., Teasley, R., Sandoval-Solis, S., Hecht, J.S., van Zyl, J.E., McMahon, G.F., Horsburgh, J., Kasprzyk, J.R., and Tarboton, D.G., 2020, The next frontier: Making research more reproducible: Journal of Water Resources Planning and Management, v. 146, no. 6, 4 p., https://doi.org/10.1061/(ASCE)WR.1943-5452.0001215.","productDescription":"4 p.","ipdsId":"IP-112233","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":454610,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1061/(asce)wr.1943-5452.0001215","text":"Publisher Index Page"},{"id":385407,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"146","issue":"6","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Rosenberg, David E. 0000-0003-2163-2907","orcid":"https://orcid.org/0000-0003-2163-2907","contributorId":257767,"corporation":false,"usgs":false,"family":"Rosenberg","given":"David","email":"","middleInitial":"E.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":815003,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Filion, Yves","contributorId":257768,"corporation":false,"usgs":false,"family":"Filion","given":"Yves","email":"","affiliations":[{"id":40753,"text":"Queen's University","active":true,"usgs":false}],"preferred":false,"id":815004,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Teasley, Rebecca","contributorId":257769,"corporation":false,"usgs":false,"family":"Teasley","given":"Rebecca","email":"","affiliations":[{"id":34699,"text":"University of Minnesota-Duluth","active":true,"usgs":false}],"preferred":false,"id":815005,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sandoval-Solis, Samuel 0000-0003-0329-3243","orcid":"https://orcid.org/0000-0003-0329-3243","contributorId":257770,"corporation":false,"usgs":false,"family":"Sandoval-Solis","given":"Samuel","email":"","affiliations":[{"id":7082,"text":"University of California - Davis","active":true,"usgs":false}],"preferred":false,"id":815006,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hecht, Jory Seth 0000-0002-9485-3332","orcid":"https://orcid.org/0000-0002-9485-3332","contributorId":257771,"corporation":false,"usgs":true,"family":"Hecht","given":"Jory","email":"","middleInitial":"Seth","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":815007,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"van Zyl, Jakobus E.","contributorId":257774,"corporation":false,"usgs":false,"family":"van Zyl","given":"Jakobus","email":"","middleInitial":"E.","affiliations":[{"id":52116,"text":"Univ. of Auckland","active":true,"usgs":false}],"preferred":false,"id":815008,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McMahon, George F.","contributorId":257776,"corporation":false,"usgs":false,"family":"McMahon","given":"George","email":"","middleInitial":"F.","affiliations":[{"id":36715,"text":"Arcadis","active":true,"usgs":false}],"preferred":false,"id":815009,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Horsburgh, J. S. 0000-0002-0768-3196","orcid":"https://orcid.org/0000-0002-0768-3196","contributorId":248851,"corporation":false,"usgs":false,"family":"Horsburgh","given":"J. S.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":815010,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kasprzyk, Joseph R. 0000-0002-6344-6478","orcid":"https://orcid.org/0000-0002-6344-6478","contributorId":257779,"corporation":false,"usgs":false,"family":"Kasprzyk","given":"Joseph","email":"","middleInitial":"R.","affiliations":[{"id":16144,"text":"University of Colorado-Boulder","active":true,"usgs":false}],"preferred":false,"id":815011,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Tarboton, David G. 0000-0002-1998-3479","orcid":"https://orcid.org/0000-0002-1998-3479","contributorId":257780,"corporation":false,"usgs":false,"family":"Tarboton","given":"David","email":"","middleInitial":"G.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":815012,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70216911,"text":"sir20205118 - 2020 - Hydrogeology, numerical simulation of groundwater flow, and effects of future water use and drought for reach 1 of the Washita River alluvial aquifer, Roger Mills and Custer Counties, western Oklahoma, 1980–2015","interactions":[],"lastModifiedDate":"2020-12-30T20:18:58.899472","indexId":"sir20205118","displayToPublicDate":"2020-12-30T13:15:00","publicationYear":"2020","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":"2020-5118","displayTitle":"Hydrogeology, Numerical Simulation of Groundwater Flow, and Effects of Future Water Use and Drought for Reach 1 of the Washita River Alluvial Aquifer, Roger Mills and Custer Counties, Western Oklahoma, 1980–2015","title":"Hydrogeology, numerical simulation of groundwater flow, and effects of future water use and drought for reach 1 of the Washita River alluvial aquifer, Roger Mills and Custer Counties, western Oklahoma, 1980–2015","docAbstract":"<p>The Washita River alluvial aquifer is a valley-fill and terrace alluvial aquifer along the valley of the Washita River in western Oklahoma that provides a productive source of groundwater for agricultural irrigation and water supply. The Oklahoma Water Resources Board (OWRB) has designated the westernmost section of the aquifer in Roger Mills and Custer Counties, Okla., as reach 1 of the Washita River alluvial aquifer; reach 1 is the focus of this report. The OWRB issued an order on November&nbsp;13, 1990, that established the maximum annual yield (MAY; 120,320 acre-feet per year [acre-ft/yr]) and equal-proportionate-share (EPS) pumping rate (2.0 acre-feet per acre per year [(acre-ft/acre)/yr]) for reach 1 of the Washita River alluvial aquifer. The MAY and EPS were based on hydrologic investigations that evaluated the effects of potential groundwater withdrawals on groundwater availability in the Washita River alluvial aquifer. Every 20 years, the OWRB is statutorily required to update the hydrologic investigation on which the MAY and EPS were based. Because 30&nbsp;years have elapsed since the last order was issued, the U.S. Geological Survey, in cooperation with the OWRB, conducted a new hydrologic investigation and evaluated the effects of potential groundwater withdrawals on groundwater flow and availability in the Washita River alluvial aquifer.</p><p>The Washita River is the primary source of inflow to Foss Reservoir, a Bureau of Reclamation reservoir constructed in 1961 for flood control, water supply, and recreation. Foss Reservoir provides water for Bessie, Clinton, New Cordell, and Hobart, Okla. Nearly 98 percent of the total groundwater use from the Washita River alluvial aquifer during 1967 to 2015 was for irrigation; other uses of groundwater in the study area include public supply, mining, and agriculture.</p><p>A hydrogeologic framework was developed for the Washita River alluvial aquifer and included the physical characteristics of the aquifer, the geologic setting, the hydraulic properties of hydrogeologic units, the potentiometric surface (water table), and groundwater-flow directions at a scale that captures the regional controls on groundwater flow. The Washita River alluvial aquifer consists of alluvium and terrace deposits that were transported primarily by water and range from clay to gravel in size. The terrace includes windblown deposits of silt size and, in some cases, contains gravel laid down at several levels along former courses of present-day rivers.</p><p>A conceptual flow model is a simplified description of the aquifer system that includes hydrologic boundaries, major inflow and outflow sources of the groundwater-flow system, and a conceptual water budget with the estimated mean flows between those hydrologic boundaries. During the study period&nbsp;1980–2015, mean annual groundwater withdrawals, predominantly used for agricultural irrigation, totaled 5,502&nbsp;acre-ft/yr, or 14 percent of aquifer outflows. When applied across the 132-square-mile aquifer area used for modeling purposes (84,366 acres), mean annual recharge of 3.15&nbsp;inches per year corresponds to a mean annual recharge volume of 22,169 acre-ft/yr, or 56 percent of aquifer inflows. The annual saturated-zone evapotranspiration outflow was 11,828 acre-ft/yr for the Washita River alluvial aquifer, or about 30 percent of aquifer outflows. For the Washita River alluvial aquifer, lateral flow was 17,157 acre-ft/yr, or 44&nbsp;percent of the aquifer inflows. The conceptual flow model and hydrogeologic framework were used to conceptualize, design, and build the numerical groundwater-flow model.</p><p>A numerical groundwater-flow model of the Washita River alluvial aquifer was constructed by using MODFLOW-2005. The Washita River alluvial aquifer groundwater-model grid was spatially discretized into 350-foot (ft) cells and two layers. Layer 1 represented the undifferentiated alluvium and terrace deposits of Quaternary age, and layer 2 represented the bedrock of Permian age, which was given a uniform nominal thickness of 100 ft. The groundwater-simulation period was temporally discretized into 433 monthly transient stress periods, representing January&nbsp;1980 to December&nbsp;2015. An initial 365-day steady-state stress period was configured to represent mean annual inflows and outflows from the Washita River alluvial aquifer for the study period. The groundwater-flow model was calibrated manually and by automated adjustment of model inputs by using PEST++. Calibration targets for the Washita River alluvial aquifer model included groundwater-level observations and reservoir-stage observations, as well as base-flow and stream-seepage estimates.</p><p>Three groundwater-availability scenarios were used in the calibrated groundwater model to (1) estimate the EPS pumping rate that retains the saturated thickness that meets the minimum 20-year life of the aquifer, (2) quantify the effects of projected pumping rates on groundwater storage over a 50-year period, and (3) evaluate how projected pumping rates extended 50 years into the future and sustained hypothetical drought conditions over a 10-year period affect base flow and groundwater in storage. The results of the groundwater-availability scenarios could be used by the OWRB to reevaluate the established MAY of groundwater from the Washita River alluvial aquifer.</p><p>EPS scenarios for the Washita River alluvial aquifer were run for periods of 20, 40, and 50 years. The 20-, 40-, and&nbsp;50-year EPS pumping rates under normal recharge conditions were 1.7, 1.6, and 1.6 (acre-ft/acre)/yr, respectively.&nbsp;Given the aquifer area used for modeling purposes (84,366 acres), these rates correspond to annual yields of 142,579, 134,986, and 134,986 acre-ft/yr, respectively. Groundwater storage at the end of the 20-year EPS scenario was about 281,000&nbsp;acre-feet (acre-ft), or about 306,000 acre-ft (52 percent) less than the starting storage. Considering the land-surface area of the Washita River alluvial aquifer and using a specific yield of 0.12, this decrease in storage was equivalent to a mean groundwater-level decline of about 30&nbsp;ft. The Washita River downstream from Foss Reservoir and most of the streams in the study area were dry at the end of the 20-year EPS scenario. Foss Reservoir stage was below the dead-pool stage of 1,597 ft after about 7 years of pumping in the 20-year EPS scenario.</p><p>Four projected 50-year groundwater-use scenarios were used to simulate the effects of selected well withdrawal rates on groundwater storage in the Washita River alluvial aquifer. These four scenarios used (1) no groundwater use, (2) groundwater use at the 2015 pumping rate, (3) mean groundwater use for the simulation period, and (4) increasing groundwater use. Groundwater storage after 50 years with no groundwater use was 545,249 acre-ft, or 693 acre-ft (0.1 percent) greater than the initial groundwater storage; this groundwater storage increase is equivalent to a mean groundwater-level increase of 0.1 ft. Groundwater storage at the end of the 50-year period with 2015 pumping rates was 543,831 acre-ft, or 723 acre-ft (0.1 percent) less than the initial storage; this groundwater storage decrease is equivalent to a mean groundwater-level decrease of 0.1 ft. Groundwater storage after 50 years with the mean pumping rate for the study period was 543,202 acre-ft, or 1,349 acre-ft (0.2 percent) less than the initial groundwater storage; this groundwater storage decrease is equivalent to a mean groundwater-level decrease of 0.1 ft. Groundwater storage at the end of the 50-year period with an increasing demand groundwater-pumping rate, which was 38&nbsp;percent greater than the 2015 groundwater-pumping rate, was 542,584 acre-ft, or 1,967 acre-ft (0.4 percent) less than the initial storage; this groundwater storage decrease is equivalent to a mean groundwater-level decrease of 0.2 ft.</p><p>A hypothetical 10-year-drought scenario was used to simulate the effects of a prolonged period of reduced recharge on groundwater storage in the Washita River alluvial aquifer and Foss Reservoir stage and storage. To simulate the hypothetical drought, recharge in the calibrated model was reduced by 50 percent during the simulated drought period (1983–1992). Groundwater storage at the end of the drought period in December&nbsp;1992 was 562,000 acre-ft, or 36,000 acre-ft (6 percent) less than the groundwater storage of the calibrated groundwater model (598,000 acre-ft). At the end of the hypothetical drought, the largest changes in saturated thickness (as great as 43.5 ft) were in the area upgradient from Foss Reservoir, particularly in the terrace at the model boundary. Substantial decreases in the Foss Reservoir stage began during the fall of 1985 in conjunction with base-flow decreases of up to 100 percent at U.S. Geological Survey streamgage 07324200 Washita River near Hammon, Okla. These lake-stage declines outpaced groundwater-level declines in the surrounding aquifer. The minimum Foss Reservoir storage simulated during the drought period was 77,954 acre-ft, which was a decrease of 46 percent from the nondrought storage.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205118","collaboration":"Prepared in cooperation with the Oklahoma Water Resources Board","usgsCitation":"Ellis, J.H., Ryter, D.W., Fuhrig, L.T., Spears, K.W., Mashburn, S.L., and Rogers, I.M.J., 2020, Hydrogeology, numerical simulation of groundwater flow, and effects of future water use and drought for reach 1 of the Washita River alluvial aquifer, Roger Mills and Custer Counties, western Oklahoma, 1980–2015: U.S. Geological Survey Scientific Investigations Report 2020–5118, 81 p., https://doi.org/10.3133/sir20205118.","productDescription":"Report: xi, 81 p.; Data Release","numberOfPages":"98","onlineOnly":"Y","ipdsId":"IP-116035","costCenters":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":381399,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9PKMG6U","text":"USGS data release","description":"USGS Data Release","linkHelpText":"MODFLOW-NWT model used in simulation of groundwater flow, and analysis of projected water use for the Washita River alluvial aquifer, western Oklahoma"},{"id":381398,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5118/sir20205118.pdf","text":"Report","size":"18.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5118"},{"id":381397,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5118/coverthb.jpg"}],"country":"United States","state":"Oklahoma","county":"Roger Mills County, Custer County","otherGeospatial":"Washita River alluvial aquifer","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-98.6305,35.812],[-98.6308,35.6387],[-98.6307,35.552],[-98.6199,35.552],[-98.6209,35.4639],[-98.8338,35.4653],[-98.9399,35.4659],[-99.0455,35.4654],[-99.1517,35.4658],[-99.3629,35.4649],[-99.3631,35.508],[-99.5755,35.5085],[-99.576,35.42],[-100.0009,35.4223],[-100.0014,35.4558],[-100.0011,35.6197],[-100.001,35.64],[-100.0015,35.8008],[-100.0015,35.8782],[-99.9742,35.8921],[-99.9566,35.8959],[-99.947,35.9009],[-99.938,35.9037],[-99.9272,35.9074],[-99.9228,35.9115],[-99.9177,35.9175],[-99.9132,35.9234],[-99.911,35.928],[-99.9082,35.9325],[-99.9049,35.9371],[-99.9038,35.9462],[-99.9045,35.9562],[-99.9051,35.9589],[-99.899,35.9698],[-99.894,35.9748],[-99.8522,36.0051],[-99.8398,36.0115],[-99.829,36.0107],[-99.8227,36.0089],[-99.8152,36.0026],[-99.8078,35.9949],[-99.8019,35.9827],[-99.8019,35.9737],[-99.8051,35.9618],[-99.809,35.9518],[-99.8111,35.9364],[-99.8099,35.9287],[-99.8087,35.9246],[-99.8007,35.9174],[-99.7938,35.9102],[-99.788,35.8962],[-99.784,35.8921],[-99.7725,35.8867],[-99.76,35.885],[-99.7521,35.8824],[-99.7372,35.8738],[-99.7258,35.8653],[-99.7189,35.8626],[-99.7149,35.854],[-99.6979,35.855],[-99.6774,35.847],[-99.6615,35.847],[-99.6558,35.8457],[-99.6416,35.8444],[-99.6291,35.84],[-99.6149,35.84],[-99.6042,35.8478],[-99.6002,35.8519],[-99.5929,35.8551],[-99.5855,35.8574],[-99.577,35.8588],[-99.5623,35.8621],[-99.5578,35.8675],[-99.5562,35.8825],[-99.5416,35.903],[-99.532,35.9076],[-99.5241,35.9185],[-99.5156,35.9281],[-99.5067,35.9481],[-99.5061,35.9535],[-99.5085,35.9608],[-99.5085,35.9649],[-99.5045,35.9703],[-99.4995,35.974],[-99.4876,35.9795],[-99.4785,35.9899],[-99.4638,35.9995],[-99.4445,36.01],[-99.4303,36.016],[-99.4144,36.0169],[-99.3928,36.017],[-99.3809,36.017],[-99.3808,35.8991],[-99.374,35.8991],[-99.3736,35.8111],[-99.0571,35.8112],[-98.7366,35.8118],[-98.6305,35.812]]]},\"properties\":{\"name\":\"Custer\",\"state\":\"OK\"}}]}","contact":"<p>Director, <a data-mce-href=\"https://www.usgs.gov/centers/tx-water/\" href=\"https://www.usgs.gov/centers/tx-water/\">Oklahoma-Texas Water Science Center</a><br>U.S. Geological Survey<br>1505 Ferguson Lane <br>Austin, Texas 78754–4501 </p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Geologic Units and Hydrogeology of the Study Area</li><li>Hydrogeologic Framework of the Washita River Alluvial Aquifer</li><li>Conceptual Flow Model</li><li>Simulation of Groundwater Flow</li><li>Groundwater-Availability Scenarios</li><li>Model Limitations</li><li>Summary</li><li>Selected References</li></ul>","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2020-12-30","noUsgsAuthors":false,"publicationDate":"2020-12-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Ellis, John H. 0000-0001-7161-3136 jellis@usgs.gov","orcid":"https://orcid.org/0000-0001-7161-3136","contributorId":177759,"corporation":false,"usgs":true,"family":"Ellis","given":"John","email":"jellis@usgs.gov","middleInitial":"H.","affiliations":[],"preferred":false,"id":806921,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ryter, Derek W. 0000-0002-2488-626X dryter@usgs.gov","orcid":"https://orcid.org/0000-0002-2488-626X","contributorId":3395,"corporation":false,"usgs":true,"family":"Ryter","given":"Derek","email":"dryter@usgs.gov","middleInitial":"W.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true}],"preferred":true,"id":806922,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fuhrig, Leland T. 0000-0001-5694-9061 lfuhrig@usgs.gov","orcid":"https://orcid.org/0000-0001-5694-9061","contributorId":195830,"corporation":false,"usgs":true,"family":"Fuhrig","given":"Leland","email":"lfuhrig@usgs.gov","middleInitial":"T.","affiliations":[{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true}],"preferred":true,"id":806923,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Spears, Kyle W.","contributorId":245727,"corporation":false,"usgs":false,"family":"Spears","given":"Kyle","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":806924,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mashburn, Shana L. 0000-0001-5163-778X shanam@usgs.gov","orcid":"https://orcid.org/0000-0001-5163-778X","contributorId":2140,"corporation":false,"usgs":true,"family":"Mashburn","given":"Shana","email":"shanam@usgs.gov","middleInitial":"L.","affiliations":[{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true}],"preferred":true,"id":806925,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rogers, Ian M.J. 0000-0001-8492-5358","orcid":"https://orcid.org/0000-0001-8492-5358","contributorId":46036,"corporation":false,"usgs":true,"family":"Rogers","given":"Ian","email":"","middleInitial":"M.J.","affiliations":[{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true}],"preferred":true,"id":806926,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70217224,"text":"70217224 - 2020 - Outburst floods","interactions":[],"lastModifiedDate":"2021-01-25T17:03:31.359169","indexId":"70217224","displayToPublicDate":"2020-12-30T11:02:20","publicationYear":"2020","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Outburst floods","docAbstract":"<p><span>Outbursts from impounded water bodies produce large, hazardous, and geomorphically significant floods affecting the Earth as well as other planetary surfaces. Two broad classes of impoundments are: (1) valleys blocked by ice, landslides, constructed dams, and volcanic materials; and (2) closed basins such as tectonic depressions, calderas, meteor craters, and those rimmed by glaciers and moraines. In some environments, floods emanate from subglacial and subterranean sources. Outburst floods are geomorphically important over geologic time because large flows achieve exceptional shear stress and stream power values, thus forming some of the most spectacular landscapes in the solar system.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Reference Module in Earth Systems and Environmental Sciences","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Elsevier","doi":"10.1016/B978-0-12-818234-5.00007-9","usgsCitation":"O'Connor, J., Clague, J.J., Walder, J.S., Manville, V., and Beebee, R.A., 2020, Outburst floods, chap. <i>of</i> Reference Module in Earth Systems and Environmental Sciences, HTML Document, https://doi.org/10.1016/B978-0-12-818234-5.00007-9.","productDescription":"HTML Document","ipdsId":"IP-120078","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":382557,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"O'Connor, Jim E. 0000-0002-7928-5883 oconnor@usgs.gov","orcid":"https://orcid.org/0000-0002-7928-5883","contributorId":140771,"corporation":false,"usgs":true,"family":"O'Connor","given":"Jim E.","email":"oconnor@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":false,"id":808096,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Clague, John J.","contributorId":191448,"corporation":false,"usgs":false,"family":"Clague","given":"John","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":808097,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Walder, Joseph S. 0000-0003-3523-2998 jswalder@usgs.gov","orcid":"https://orcid.org/0000-0003-3523-2998","contributorId":247681,"corporation":false,"usgs":true,"family":"Walder","given":"Joseph","email":"jswalder@usgs.gov","middleInitial":"S.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":808098,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Manville, Vernon","contributorId":247682,"corporation":false,"usgs":false,"family":"Manville","given":"Vernon","affiliations":[{"id":49608,"text":"University of Leeds, Leeds, United Kingdom","active":true,"usgs":false}],"preferred":false,"id":808099,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Beebee, Robin A. 0000-0002-2976-7294 rbeebee@usgs.gov","orcid":"https://orcid.org/0000-0002-2976-7294","contributorId":5778,"corporation":false,"usgs":true,"family":"Beebee","given":"Robin","email":"rbeebee@usgs.gov","middleInitial":"A.","affiliations":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":808100,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70226833,"text":"70226833 - 2020 - Introduction of the Oriental Weatherfish, Misgurnus anguillicaudatus (Cantor, 1842) in the United States","interactions":[],"lastModifiedDate":"2021-12-15T13:17:33.085282","indexId":"70226833","displayToPublicDate":"2020-12-30T07:16:31","publicationYear":"2020","noYear":false,"publicationType":{"id":25,"text":"Newsletter"},"publicationSubtype":{"id":30,"text":"Newsletter"},"title":"Introduction of the Oriental Weatherfish, Misgurnus anguillicaudatus (Cantor, 1842) in the United States","docAbstract":"Although this fish had been present in the then United States (US) territory of Hawaii since the late 19th century, a growing number of collections in the contiguous US over a century later in the 2000s is noteworthy.  The Oriental Weatherfish, also often referred to as the weather loach or dojo, is native to eastern Asia from Siberia to Vietnam thus covering a wide climatic range from subtropical to temperate.  Primarily a freshwater species, it is typically found in cool, slow-moving streams with silty or muddy substrates. Individuals can reach 28 cm standard length but usually range from 10-20 cm with females generally larger than males.  This species has a very slender body shape with a mottled coloration pattern of brown to green markings and a rounded caudal fin.  Surrounding its small inferior mouth are 10 barbels and prey consists of small benthic invertebrates including aquatic insects.  It is known to bury itself in the substrate to survive periods of drought as well as breathe air using its intestine as an accessory respiratory organ.\nThe occurrence of this species in Hawaii beginning in the late 1800s was likely due to Asian immigrants bringing it with them as a food source.  Misgurnus was later used in the state as a baitfish.  The introduction of this species in the contiguous US occurred in 1939 when it was imported into the state of Michigan from Japan for the aquarium trade.  The first collection made in open waters was from the Shiawassee River, northwest of Detroit, Michigan in 1958 and are believed to have escaped from a nearby aquaculture breeding facility.  Based on the linear extent of captures in the Shiawassee River, the fish had likely been present for years prior to its discovery.  By 1985, specimens had also been collected from California, Idaho, Oregon, and Washington.  Since then, collections have been made in 15 additional states, mostly in the Atlantic (including Gulf of Mexico) and Great Lakes drainages.  Collections from the Mississippi River basin have been limited to the upper Illinois River in Illinois, and the upper Ohio drainage in central Ohio and southwest New York.  Overall, M. anguillicaudatus has been collected in the following states (with year of first collection): Hawaii (~1870), Michigan (1958), California (1963), Oregon (1977), Washington (1978), Idaho (1985), Illinois (1987), Florida (1988), Tennessee (1995), New York (2001), Indiana (2002), Louisiana (2005), Maryland (2007), Alabama (2009), North Carolina (2009), New Jersey (2007), Pennsylvania (2017), Ohio (2019), and Virginia (2019).  An anecdotal report states that it may also be present in Utah.  Misgurnus anguillicaudatus has been reported as established with stable populations in most of the locations of these states although some are small in the reported number of individuals or range extent.  Exceptions may be Maryland, Tennessee, and Virginia where only a few specimens have been reported.  Three areas in particular appear to be undergoing either substantial range expansions or further introductions.  These areas include the upper Illinois River and various waters of both western peninsular Florida and southeastern New York.  Because of the limited number of reports yet broad fragmented distribution of M. anguillicaudatus in the US, each population is likely the result of a separate introduction as opposed to dispersal from the earliest collection location.  A majority of the collection locations are clustered in or near large metropolitan areas which reflects probable releases by aquarium hobbyists.","largerWorkType":{"id":25,"text":"Newsletter"},"largerWorkTitle":"Invasive and Introduced Species Section Newsletter","largerWorkSubtype":{"id":30,"text":"Newsletter"},"language":"English","publisher":"American Fisheries Society","usgsCitation":"Benson, A.J., 2020, Introduction of the Oriental Weatherfish, Misgurnus anguillicaudatus (Cantor, 1842) in the United States, v. 23, no. 2, p. 5-6.","productDescription":"2 p.","startPage":"5","endPage":"6","ipdsId":"IP-120881","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":392946,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":392932,"type":{"id":15,"text":"Index Page"},"url":"https://introducedfish.fisheries.org/wp-content/uploads/2020/11/IISS_Newletter_September2020.pdf"}],"volume":"23","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Benson, Amy J. 0000-0002-4517-1466 abenson@usgs.gov","orcid":"https://orcid.org/0000-0002-4517-1466","contributorId":3836,"corporation":false,"usgs":true,"family":"Benson","given":"Amy","email":"abenson@usgs.gov","middleInitial":"J.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":828424,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70217046,"text":"ofr20201142 - 2020 - Changing storm conditions in response to projected 21st century climate change and the potential impact on an arctic barrier island–lagoon system—A pilot study for Arey Island and Lagoon, eastern Arctic Alaska","interactions":[],"lastModifiedDate":"2020-12-30T12:49:16.90443","indexId":"ofr20201142","displayToPublicDate":"2020-12-29T16:50:00","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-1142","displayTitle":"Changing Storm Conditions in Response to Projected 21st Century Climate Change and the Potential Impact on an Arctic Barrier Island–Lagoon System—A Pilot Study for  Arey Island and Lagoon, Eastern Arctic Alaska","title":"Changing storm conditions in response to projected 21st century climate change and the potential impact on an arctic barrier island–lagoon system—A pilot study for Arey Island and Lagoon, eastern Arctic Alaska","docAbstract":"<h1>Executive Summary</h1><p><span>Arey Lagoon, located in eastern Arctic Alaska, supports a highly productive ecosystem, where soft substrate and coastal wet sedge fringing the shores are feeding grounds and nurseries for a variety of marine fish and waterfowl. The lagoon is partially protected from the direct onslaught of Arctic Ocean waves by a barrier island chain (Arey Island) which in itself provides important habitat for migratory shorebirds and waterfowl. In this work,&nbsp;</span><span>numerically modeled waves and water levels are computed under the provision of sea-level rise and changing conditions brought about by 21st century climate variability. Model results, supported by observations, are used to assess the stability of the barrier chain and spatiotemporal changes in flood patterns across fringing coastal wet sedge areas. The results aim to support studies that investigate the possibility of new biological succession trajectories and loss or increase of habitat areas.&nbsp;</span></p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201142","collaboration":"Prepared in cooperation with and funded in part by the Arctic Landscape Conservation Cooperation (ALCC)","usgsCitation":"Erikson, L.H., Gibbs, A.E., Richmond, B.M., Storlazzi, C.D., Jones, B.M., and Ohman, K.A., 2020, Changing storm conditions in response to projected 21st century climate change and the potential impact on an arctic barrier island–lagoon system—A pilot study for Arey Island and Lagoon, eastern Arctic Alaska: U.S. Geological Survey Open-File Report 2020–1142, 68, p., https://doi.org/10.3133/ofr20201142.","productDescription":"Report: x, 68 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-079323","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":381735,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9LGYO2Q","text":"USGS data release","linkHelpText":"Modeled 21st century storm surge, waves, and coastal flood hazards and supporting oceanographic and geological field data (2010 and 2011) for Arey and Barter Islands, Alaska and vicinity"},{"id":381739,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1142/coverthb.jpg"},{"id":381740,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1142/ofr20201142.pdf","text":"Report","size":"8.98 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1142"}],"country":"United States","state":"Alaska","otherGeospatial":"Arey Island and Lagoon","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -144.09805297851562,\n              70.03559723423488\n            ],\n            [\n              -143.6407470703125,\n              70.03559723423488\n            ],\n            [\n              -143.6407470703125,\n              70.13476515043729\n            ],\n            [\n              -144.09805297851562,\n              70.13476515043729\n            ],\n            [\n              -144.09805297851562,\n              70.03559723423488\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"http://www.usgs.gov/centers/pcmsc/\" data-mce-href=\"http://www.usgs.gov/centers/pcmsc/\">Pacific Coastal and Marine Science Center </a><br>U.S. Geological Survey<br>Pacific Science Center<br>2885 Mission St.<br>Santa Cruz, CA 95060</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Executive Summary</li><li>Introduction</li><li>Clarification of Key Terms</li><li>Study Area</li><li>Data and Methods</li><li>Field Observations and Model Evaluation</li><li>Results</li><li>Summary of Findings and Conclusions</li><li>References Cited</li><li>Appendix 1. Documented historical and model hind-cast storm events in the vicinity of Arey Island and Lagoon</li><li>Appendix 2. Model Settings</li><li>Appendix 3. Field Data</li></ul>","publishedDate":"2020-12-29","noUsgsAuthors":false,"publicationDate":"2020-12-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Erikson, Li H. 0000-0002-8607-7695 lerikson@usgs.gov","orcid":"https://orcid.org/0000-0002-8607-7695","contributorId":149963,"corporation":false,"usgs":true,"family":"Erikson","given":"Li","email":"lerikson@usgs.gov","middleInitial":"H.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":807354,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gibbs, Ann E. 0000-0002-0883-3774 agibbs@usgs.gov","orcid":"https://orcid.org/0000-0002-0883-3774","contributorId":2644,"corporation":false,"usgs":true,"family":"Gibbs","given":"Ann","email":"agibbs@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":807355,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Richmond, Bruce M. 0000-0002-0056-5832 brichmond@usgs.gov","orcid":"https://orcid.org/0000-0002-0056-5832","contributorId":2459,"corporation":false,"usgs":true,"family":"Richmond","given":"Bruce","email":"brichmond@usgs.gov","middleInitial":"M.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":807356,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Storlazzi, Curt D. 0000-0001-8057-4490","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":229614,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt D.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":807357,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jones, Benjamin M. 0000-0002-1517-4711 bjones@usgs.gov","orcid":"https://orcid.org/0000-0002-1517-4711","contributorId":2286,"corporation":false,"usgs":true,"family":"Jones","given":"Benjamin","email":"bjones@usgs.gov","middleInitial":"M.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"preferred":true,"id":807358,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ohman, Karin","contributorId":245939,"corporation":false,"usgs":false,"family":"Ohman","given":"Karin","affiliations":[{"id":49372,"text":"former USGS now with Michael Baker International","active":true,"usgs":false}],"preferred":false,"id":807359,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70217101,"text":"70217101 - 2020 - Geologic map of the Butte City 7.5' Quadrangle, Butte County, Idaho","interactions":[],"lastModifiedDate":"2021-01-06T13:43:34.296321","indexId":"70217101","displayToPublicDate":"2020-12-29T07:40:29","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Geologic map of the Butte City 7.5' Quadrangle, Butte County, Idaho","docAbstract":"The geologic map of the Butte City 7.5’ quadrangle is based on mapping summarized in the 1:100,000 scale map of the Idaho National Laboratory, U.S. Geological Survey Miscellaneous Investigations Map I-2330, by Kuntz and others, 1994. New surficial geologic mapping was completed by National Association of Geoscience Teachers (NAGT) interns, Evan Martin (2015) and Samuel Helmuth (2017). Previously published maps and associated data, by various authors, including Kuntz, M.A., Betty Skipp, M.A. Lanphere, W.E. Scott, K.L. Pierce, G.B. Dalrymple, L.A. Morgan, D.E. Champion, G.F. Embree, W.R. Page, R.P. Smith, W.R. Hackett, and D.W. Rodgers from 1994 to 2017, were incorporated into this project. The U. S. Geological Survey (USGS) Idaho National Laboratory Project Office, a field office of the Idaho Water Science Center, conducts subsurface investigations to study the Snake River aquifer at the Idaho National Laboratory. Many subsurface basalts erupted from vents exposed at the surface. Tracing the flows from the surface to the subsurface provides data for numerical models of groundwater flow and contaminant transport.","language":"English","publisher":"Idaho Geological Survey","collaboration":"U.S. Department of Energy; Idaho Geological Survey; National Association of Geoscience Teachers (NAGT)","usgsCitation":"Helmuth, S.L., Martin, E., Hodges, M., and Champion, D.E., 2020, Geologic map of the Butte City 7.5' Quadrangle, Butte County, Idaho, 42.00 x 32.00 inches.","productDescription":"42.00 x 32.00 inches","ipdsId":"IP-091036","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":381945,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":381914,"type":{"id":15,"text":"Index Page"},"url":"https://www.idahogeology.org/product/t-20-04"}],"country":"United States","state":"Idaho","county":"Butte 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