{"pageNumber":"242","pageRowStart":"6025","pageSize":"25","recordCount":41062,"records":[{"id":70219451,"text":"70219451 - 2021 - Physics‐based evaluation of the maximum magnitude of potential earthquakes induced by the Hutubi (China) underground gas storage","interactions":[],"lastModifiedDate":"2021-04-22T17:57:05.216862","indexId":"70219451","displayToPublicDate":"2021-03-25T08:05:19","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7501,"text":"JGR Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Physics‐based evaluation of the maximum magnitude of potential earthquakes induced by the Hutubi (China) underground gas storage","docAbstract":"<div class=\"article-section__content en main\"><p>The world’s largest underground gas storage facility in Hutubi (HUGS), China, is a unique case where cyclic gas injection‐extraction induced both seismicity and ground deformation. To assess the potential for future induced seismicity, we develop a framework physically based on a well‐constrained hydro‐geomechanical model and on fully coupled poroelastic simulations. We first interpret the spatiotemporal distribution and focal mechanisms of induced earthquakes and use these to estimate the magnitude and location of the largest potential earthquake. The sharp increase in seismicity was controlled by poroelastic loading on secondary southwest‐dipping thrust faults with spatial scales too small to be resolved by 3D seismic surveys. Both operational and local geological factors affect the seismic productivity at the HUGS site, distinguishing it from most cases of seismicity induced by wastewater disposal and hydraulic fracturing. We then conduct slip tendency analyses for major faults imaged by the seismic data, including the largest reservoir‐bounding Hutubi fault hydraulically connected to injection wells. The reactivation potentials of these imaged faults are estimated to be extremely low. Accordingly, future seismicity would most likely occur on failure‐prone secondary faults in regions with positive stress perturbation due to poroelastic loading. The maximum magnitude likely depends on the spatial scales of the secondary faults. As the occurrence of detected earthquakes is spatially and temporally consistent with the simulated evolution of Coulomb stress perturbation, the location of the largest potential earthquake probably depends on the sizes of the poroelastic stressing regions.</p></div>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020JB021379","usgsCitation":"Jiang, G., Liu, L., Barbour, A.J., Lu, R., and Yang, H., 2021, Physics‐based evaluation of the maximum magnitude of potential earthquakes induced by the Hutubi (China) underground gas storage: JGR Solid Earth, v. 126, e2020JB021379, 24 p., https://doi.org/10.1029/2020JB021379.","productDescription":"e2020JB021379, 24 p.","ipdsId":"IP-115519","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":384929,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"China","city":"Hutubi","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              87.00485229492188,\n              44.189589676678736\n            ],\n            [\n              86.85516357421874,\n              44.08758502824516\n            ],\n            [\n              87.12844848632812,\n              43.96514454266273\n            ],\n            [\n              87.29461669921875,\n              44.119634452910205\n            ],\n            [\n              87.00485229492188,\n              44.189589676678736\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"126","noUsgsAuthors":false,"publicationDate":"2021-04-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Jiang, Guoyan 0000-0002-6602-7295","orcid":"https://orcid.org/0000-0002-6602-7295","contributorId":256973,"corporation":false,"usgs":false,"family":"Jiang","given":"Guoyan","email":"","affiliations":[{"id":51926,"text":"CUHK","active":true,"usgs":false}],"preferred":false,"id":813617,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Liu, Lin","contributorId":92950,"corporation":false,"usgs":false,"family":"Liu","given":"Lin","email":"","affiliations":[{"id":36342,"text":"Earth System Science Programme, Faculty of Science, Chinese University of Hong Kong, Hong Kong, China","active":true,"usgs":false}],"preferred":false,"id":813618,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barbour, Andrew J. 0000-0002-6890-2452 abarbour@usgs.gov","orcid":"https://orcid.org/0000-0002-6890-2452","contributorId":197158,"corporation":false,"usgs":true,"family":"Barbour","given":"Andrew","email":"abarbour@usgs.gov","middleInitial":"J.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":813619,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lu, Renqi","contributorId":256974,"corporation":false,"usgs":false,"family":"Lu","given":"Renqi","email":"","affiliations":[{"id":51929,"text":"CEA","active":true,"usgs":false}],"preferred":false,"id":813620,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Yang, Hongfeng","contributorId":256975,"corporation":false,"usgs":false,"family":"Yang","given":"Hongfeng","email":"","affiliations":[{"id":51926,"text":"CUHK","active":true,"usgs":false}],"preferred":false,"id":813621,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70262318,"text":"70262318 - 2021 - Suitability of an upper Mississippi River tributary for invasive carp reproduction","interactions":[],"lastModifiedDate":"2025-01-22T16:06:39.189719","indexId":"70262318","displayToPublicDate":"2021-03-25T00:00:00","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Suitability of an upper Mississippi River tributary for invasive carp reproduction","docAbstract":"<p><span>Invasive carp are expanding throughout the upper Mississippi River basin and are of great concern due to their potential economic and ecological impacts. Identification of spawning locations provides critical information on recruitment sources to evaluate potential management strategies. Our objective was to create and validate a spawning habitat suitability model of the Des Moines River, Iowa, during low-, average-, and high-water-level conditions. Backwater availability, abundance of hardpoints (structures that create turbulence), river gradient and sinuosity, water temperature, and continuously free-flowing river lengths were used as model parameters. The model was compared to back-calculated spawning locations from invasive carp eggs collected in 2014–2015. Turbulent hardpoints, river sinuosity, and gradient were not significant predictors of invasive carp spawning locations, and backwater availability in the 25 river kilometers downstream of each reach was inversely correlated with invasive carp spawning locations. Invasive carp eggs were not caught in 2014 despite optimal spawning conditions, revealing that spawning may have high interannual variation. This study suggests that predicting invasive carp reproduction may require variables in addition to those currently proposed.</span></p>","language":"English","publisher":"American Fisheries Society","doi":"10.1002/nafm.10551","usgsCitation":"Camacho, C., Sullivan, C., Weber, M., and Pierce, C., 2021, Suitability of an upper Mississippi River tributary for invasive carp reproduction: North American Journal of Fisheries Management, v. 43, no. 1, p. 12-24, https://doi.org/10.1002/nafm.10551.","productDescription":"13 p.","startPage":"12","endPage":"24","ipdsId":"IP-081177","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":480927,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Iowa","otherGeospatial":"Des Moines 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 \"}}]}","volume":"43","issue":"1","noUsgsAuthors":false,"publicationDate":"2021-03-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Camacho, Carlos A.","contributorId":348841,"corporation":false,"usgs":false,"family":"Camacho","given":"Carlos A.","affiliations":[{"id":6911,"text":"Iowa State University","active":true,"usgs":false}],"preferred":false,"id":923827,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sullivan, Christopher J.","contributorId":348842,"corporation":false,"usgs":false,"family":"Sullivan","given":"Christopher J.","affiliations":[{"id":6911,"text":"Iowa State University","active":true,"usgs":false}],"preferred":false,"id":923828,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Weber, Michael J.","contributorId":348844,"corporation":false,"usgs":false,"family":"Weber","given":"Michael J.","affiliations":[{"id":6911,"text":"Iowa State University","active":true,"usgs":false}],"preferred":false,"id":923829,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pierce, Clay 0000-0001-5088-5431 cpierce@usgs.gov","orcid":"https://orcid.org/0000-0001-5088-5431","contributorId":150492,"corporation":false,"usgs":true,"family":"Pierce","given":"Clay","email":"cpierce@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":923826,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70219098,"text":"sir20205120 - 2021 - Assessment of water quality and discharge in the Herring River, Wellfleet, Massachusetts, November 2015 to September 2017","interactions":[],"lastModifiedDate":"2021-03-24T22:26:41.479816","indexId":"sir20205120","displayToPublicDate":"2021-03-24T15:35:00","publicationYear":"2021","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":"2020-5120","displayTitle":"Assessment of Water Quality and Discharge in the Herring River, Wellfleet, Massachusetts, November 2015 to September 2017","title":"Assessment of water quality and discharge in the Herring River, Wellfleet, Massachusetts, November 2015 to September 2017","docAbstract":"<p>The U.S. Geological Survey, Cape Cod National Seashore of the National Park Service, and Friends of Herring River cooperated from 2015 to 2017 to assess nutrient concentrations and fluxes across the ocean-estuary boundary at a dike on the Herring River in Wellfleet, Massachusetts. The purpose of this assessment was to characterize environmental conditions prior to a future removal of the dike, which has restricted saltwater inputs into the Herring River watershed for more than 100 years. Water temperature, dissolved oxygen, pH, and specific conductance were monitored continuously, and flow-weighted composite samples were collected approximately twice per month at the ocean-estuary boundary. Bidirectional discharge was computed for the U.S. Geological Survey Herring River at Chequessett Neck Road at Wellfleet, Massachusetts, streamgage (011058798) by using a stage-area rating and index-velocity ratings developed with acoustic Doppler current profile measurements made upstream and downstream from the dike. LOADEST regression modeling software was used to estimate nutrient fluxes (loads) from composite, paired nutrient concentration and discharge data in conjunction with continuous discharge data. Temperature, dissolved oxygen, pH, and specific conductance were also monitored continuously on two tributaries to the Herring River, Pole Dike Creek and Bound Brook, from late-May 2016 to mid-June 2017. Composite or discrete water samples were collected from the tributaries approximately twice per month in most months from late-May 2016 to mid-June 2017 and analyzed for total nitrogen, total phosphorus, and dissolved organic carbon.</p><p>Flow-weighted concentrations of ammonium, nitrate, and total nitrogen on the Herring River at the dike on the ebb tide generally varied between 0.01 and 0.1, 0.003 and 0.03, and 0.3 and 0.7 milligram per liter as nitrogen, respectively. Flow-weighted concentrations of orthophosphate, total dissolved phosphorus, and total phosphorus generally varied between 0.002 and 0.02, 0.003 and 0.06, and 0.03 and 0.1 milligram per liter as phosphorus, respectively, on the ebb tide. Flow-weighted concentrations of silicate and dissolved organic carbon on the ebb tide generally varied between 0.08 and 3.0 milligrams per liter of silica (silicon dioxide), and 1.7 and 5.6 milligrams per liter of carbon, respectively. Ebb tide concentrations of nitrate were highest in winter and lowest in summer. By contrast, ebb tide concentrations of phosphorus species were highest in late summer and early fall and lowest in winter. Silica and dissolved organic carbon did not exhibit systematic variation in seasonal concentrations. There was uncertainty in estimates of nutrient fluxes, but the LOADEST-estimated fluxes indicated that annual (and in almost all cases seasonal) exports (ebb tides) exceeded inputs (flood tides). Ebb tide concentrations of ammonium, nitrate, total nitrogen, and silica were positively correlated with antecedent cumulative 7-day precipitation.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205120","collaboration":"Prepared in cooperation with the National Park Service and Friends of Herring River","usgsCitation":"Huntington, T.G., Spaetzel, A.B., Colman, J.A., Kroeger, K.D., and Bradley, R.T., 2021, Assessment of water quality and discharge in the Herring River, Wellfleet, Massachusetts, November 2015 to September 2017: U.S. Geological Survey Scientific Investigations Report 2020–5120, 59 p., https://doi.org/10.3133/sir20205120.","productDescription":"Report: x, 59 p.; Data Release","numberOfPages":"59","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-106718","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":384601,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5120/coverthb.jpg"},{"id":384603,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9BKW4BX","text":"USGS data release","linkHelpText":"Tidal daily discharge and quality assurance data supporting an assessment of water quality and discharge in the Herring River, Wellfleet, Massachusetts, November 2015–September 2017"},{"id":384602,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5120/sir20205120.pdf","text":"Report","size":"3.78 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5120"}],"country":"United States","state":"Massachusetts","city":"Wellfleet","otherGeospatial":"Herring River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -70.07801055908203,\n              41.93318868195924\n            ],\n            [\n              -69.99870300292969,\n              41.93318868195924\n            ],\n            [\n              -69.99870300292969,\n              41.98833256890643\n            ],\n            [\n              -70.07801055908203,\n              41.98833256890643\n            ],\n            [\n              -70.07801055908203,\n              41.93318868195924\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_nweng@usgs.gov\" data-mce-href=\"mailto:dc_nweng@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/centers/new-england-water\" data-mce-href=\"https://www.usgs.gov/centers/new-england-water\">New England Water Science Center</a><br>U.S. Geological Survey<br>10 Bearfoot Road<br>Northborough, MA 01532</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Methods of Measuring Discharge and Water Quality and Estimating Nutrient Fluxes</li><li>Results</li><li>Summary and Conclusions</li><li>References Cited</li><li>Appendix 1. LOADEST Models Selected and Bias Statistics for Estimating Nutrient Fluxes Across the Ocean-Estuary Boundary on the Herring River at Chequessett Neck Road, Wellfleet, Massachusetts</li><li>Appendix 2. LOADEST Regression Equations Used To Estimate Nutrient Loads Across the Ocean-Estuary Boundary on the Herring River at Chequessett Neck Road, Wellfleet, Massachusetts</li></ul>","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"publishedDate":"2021-03-24","noUsgsAuthors":false,"publicationDate":"2021-03-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Huntington, Thomas G. 0000-0002-9427-3530 thunting@usgs.gov","orcid":"https://orcid.org/0000-0002-9427-3530","contributorId":117440,"corporation":false,"usgs":true,"family":"Huntington","given":"Thomas","email":"thunting@usgs.gov","middleInitial":"G.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":812775,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Spaetzel, Alana B. 0000-0002-9871-812X","orcid":"https://orcid.org/0000-0002-9871-812X","contributorId":240935,"corporation":false,"usgs":true,"family":"Spaetzel","given":"Alana","email":"","middleInitial":"B.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":812776,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Colman, John A. 0000-0001-9327-0779 jacolman@usgs.gov","orcid":"https://orcid.org/0000-0001-9327-0779","contributorId":2098,"corporation":false,"usgs":true,"family":"Colman","given":"John","email":"jacolman@usgs.gov","middleInitial":"A.","affiliations":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":812777,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kroeger, Kevin D. 0000-0002-4272-2349 kkroeger@usgs.gov","orcid":"https://orcid.org/0000-0002-4272-2349","contributorId":1603,"corporation":false,"usgs":true,"family":"Kroeger","given":"Kevin","email":"kkroeger@usgs.gov","middleInitial":"D.","affiliations":[{"id":41100,"text":"Coastal and Marine Hazards and Resources Program","active":true,"usgs":true}],"preferred":true,"id":812778,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bradley, Robert T. 0000-0002-9440-8853","orcid":"https://orcid.org/0000-0002-9440-8853","contributorId":255672,"corporation":false,"usgs":true,"family":"Bradley","given":"Robert","email":"","middleInitial":"T.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":812779,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70218832,"text":"sir20205106 - 2021 - Assessment of contaminant trends in plumes and wells and monitoring network optimization at the Badger Army Ammunition Plant, Sauk County, Wisconsin","interactions":[],"lastModifiedDate":"2021-03-24T21:57:54.814314","indexId":"sir20205106","displayToPublicDate":"2021-03-24T09:50:00","publicationYear":"2021","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":"2020-5106","displayTitle":"Assessment of Contaminant Trends in Plumes and Wells and Monitoring Network Optimization at the Badger Army Ammunition Plant, Sauk County, Wisconsin","title":"Assessment of contaminant trends in plumes and wells and monitoring network optimization at the Badger Army Ammunition Plant, Sauk County, Wisconsin","docAbstract":"<p>Soil and groundwater at the Badger Army Ammunition Plant (BAAP), Sauk County, Wisconsin, were affected by several contaminants as a result of production and waste disposal practices common during its operation from 1942 to 1975. Three distinct plumes of contaminated groundwater originate on BAAP property and extend off-site, as identified by previous studies. Routine sampling of groundwater quality from a network of monitoring wells and off-site private wells has been performed since 1990, although the number of wells monitored and the monitoring frequency have varied as the approved monitoring plan was modified. During the period of monitoring from 1990 to 2018, numerous site investigations and remedial actions were conducted to address the sources of contamination, contaminated soils, and groundwater. Concentrations of contaminants reportedly decreased between 2000 and 2012 within all three plumes. Five or six contaminants of concern (COCs) were identified for each of the three plumes. An independent assessment of the contaminant plumes and of the monitoring network was conducted using groundwater-quality data collected from more than 600 wells between 2000 and 2018.</p><p>In a study conducted by the U.S. Geological Survey (USGS), in cooperation with the Army Environmental Command, a consistent data aggregation and interpolation scheme was applied to derive the likely maximum groundwater plume extents in four 3-year time periods between 2000 and 2018. The plume extent was defined by the Enforcement Standard for each COC and represents the maximum concentration observed in each 3-year time period. The plume boundary analysis shows that the spatial extent of groundwater contamination decreased for most COCs during the study period. Some plume boundaries are not well delineated by the existing monitoring network, particularly the downgradient edge of the Propellant Burning Ground plume. Maps identify the plume boundary in each time period, the sampling well network used to delineate the plume, and wells that were sampled in the 2010–12 period but not sampled in the 2015–18 period.</p><p>A series of statistical analyses using the Monitoring and Remediation Optimization System, version 3.0, program were applied to the available COC concentration data for two distinct periods, 2000 to 2012 and 2013 to 2018, with the break between periods coinciding with changes to the monitoring network in 2013. Trends in the concentration of COCs in individual wells varied, although generally more wells had decreasing than had increasing concentrations for most COCs in both time periods. The exceptions were ethyl ether in the 2004–12 period and 2,6-dinitrotoluene in the 2013–18 period, for which more wells had an increasing trend. Spatial moment analysis of concentration data from the well network was used to assess the stability of each plume for the COCs. During the 2000–12 period, most of the contaminant plumes for which data were sufficient to complete the analysis were either decreasing or stable in mass and size. The exceptions were carbon tetrachloride (associated solely with the Propellant Burning Ground plume) and 2,4-dinitrotoluene and 2,6-dinitrotoluene (in the Deterrent Burning Ground plume), which showed an increasing trend in mass. No COCs showed an increasing trend in plume mass in the 2013–18 period. Some wells with increasing trends in concentration or with concentrations greater than the enforcement standard are near the tail of a plume, where increased monitoring may be of value to better define future plume boundaries. A spatial optimization analysis covering the 2013–18 period identified six wells that provided information redundant to that from other wells. A temporal optimization analysis identified optimal sampling frequencies for 125 wells. Remedial actions directed at the Propellant Burning Ground plume coincided with a general decrease in plume mass and size, although in specific areas and depths, the plume size for specific contaminants may still be increasing.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205106","collaboration":"Prepared in cooperation with the Army Environmental Command","usgsCitation":"Pajerowski, M., Goodling, P., and Metes, M., 2021, Assessment of contaminant trends in plumes and wells and monitoring network optimization at the Badger Army Ammunition Plant, Sauk County, Wisconsin: U.S. Geological Survey Scientific Investigations Report 2020–5106, 80 p., https://doi.org/10.3133/sir20205106.","productDescription":"Report: x, 80 p.; Data Release; 16 Plates","numberOfPages":"80","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-118955","costCenters":[{"id":41514,"text":"Maryland-Delaware-District of Columbia  Water Science Center","active":true,"usgs":true}],"links":[{"id":384411,"rank":4,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2020/5106/sir20205106_plates.pdf","text":"Plates 1 through 16","size":"189 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":384401,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5106/coverthb.jpg"},{"id":384402,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5106/sir20205106.pdf","text":"Report","size":"10.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5106"},{"id":384403,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P97UKYNR","text":"USGS data release","linkHelpText":"Groundwater quality and plume boundaries for select contaminants of concern at Badger Army Ammunition Plant, Wisconsin (2000–2018)"}],"country":"United States","state":"Wisconsin","county":"Sauk County","otherGeospatial":"Badger Army Ammunition Plant","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -89.77375030517578,\n              43.30694264971061\n            ],\n            [\n              -89.67041015625,\n              43.30694264971061\n            ],\n            [\n              -89.67041015625,\n              43.420634784134876\n            ],\n            [\n              -89.77375030517578,\n              43.420634784134876\n            ],\n            [\n              -89.77375030517578,\n              43.30694264971061\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_md@usgs.gov\" data-mce-href=\"mailto:dc_md@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/centers/md-de-dc-water\" data-mce-href=\"https://www.usgs.gov/centers/md-de-dc-water\">MD-DE-DC Water Science Center</a><br>U.S. Geological Survey<br>5522 Research Park Drive<br>Baltimore, MD 21228</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Study Approach</li><li>Assessment of Contaminant Trends in Plumes and Wells</li><li>Monitoring Network Optimization</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"publishedDate":"2021-03-24","noUsgsAuthors":false,"publicationDate":"2021-03-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Pajerowski, Matthew 0000-0001-7931-6902 mgpajero@usgs.gov","orcid":"https://orcid.org/0000-0001-7931-6902","contributorId":3726,"corporation":false,"usgs":true,"family":"Pajerowski","given":"Matthew","email":"mgpajero@usgs.gov","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia  Water Science Center","active":true,"usgs":true}],"preferred":true,"id":812341,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Goodling, Phillip J. 0000-0001-5715-8579","orcid":"https://orcid.org/0000-0001-5715-8579","contributorId":239738,"corporation":false,"usgs":true,"family":"Goodling","given":"Phillip","email":"","middleInitial":"J.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia  Water Science Center","active":true,"usgs":true}],"preferred":true,"id":812342,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Metes, Marina J. 0000-0002-6797-9837","orcid":"https://orcid.org/0000-0002-6797-9837","contributorId":204835,"corporation":false,"usgs":true,"family":"Metes","given":"Marina","middleInitial":"J.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia  Water Science Center","active":true,"usgs":true}],"preferred":true,"id":812343,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70220559,"text":"70220559 - 2021 - Across borders: External factors and prior behaviour influence North Pacific albatross associations with fishing vessels","interactions":[],"lastModifiedDate":"2021-06-30T18:56:32.323965","indexId":"70220559","displayToPublicDate":"2021-03-24T07:45:58","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2163,"text":"Journal of Applied Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Across borders: External factors and prior behaviour influence North Pacific albatross associations with fishing vessels","docAbstract":"<ol class=\"\"><li>Understanding encounters between marine predators and fisheries across national borders and outside national jurisdictions offers new perspectives on unwanted interactions to inform ocean management and predator conservation. Although seabird–fisheries overlap has been documented at many scales, remote identification of vessel encounters has lagged because vessel movement data often are lacking.</li><li>Here, we reveal albatrosses–fisheries associations throughout the North Pacific Ocean. We identified commercial fishing operations using Global Fishing Watch data and algorithms to detect fishing vessels. We compiled GPS tracks of adult black-footed<span>&nbsp;</span><i>Phoebastria nigripes</i><span>&nbsp;</span>and Laysan<span>&nbsp;</span><i>Phoebastria</i><span>&nbsp;</span><i>immutabilis</i><span>&nbsp;</span>albatrosses, and juvenile short-tailed albatrosses<span>&nbsp;</span><i>Phoebastria albatrus</i>. We quantified albatrosses-vessel encounters based on the assumed distance that birds perceive a vessel (≤30&nbsp;km), and associations when birds approached vessels (≤3&nbsp;km). For each event we quantified bird behaviour, environmental conditions and vessel characteristics and then applied Boosted Regression Tree models to identify drivers and the duration of these associations.</li><li>In regions of greater fishing effort short-tailed and Laysan albatrosses associated with fishing vessels more frequently. However, fishing method (e.g. longline, trawl) and flag nation did not influence association prevalence nor the duration short-tailed albatrosses attended fishing vessels. Laysan albatrosses were more likely to approach longer vessels. Black-footed albatrosses were the most likely to approach vessels (61.9%), but limited vessel encounters (<i>n</i>&nbsp;=&nbsp;21) prevented evaluation of meaningful explanatory models for this species of high bycatch concern.</li><li>Temporal variables (time of day and month) and bird behavioural state helped explain when short-tailed albatrosses were in close proximity to a vessel, but environmental conditions were more important for explaining interaction duration. Laysan albatrosses were more likely to associate with vessels while searching and during the last 60% (by time) of their trips.</li><li>Our results provide specific species–fisheries insight regarding contributing factors of high-risk associations that could lead to bycatch of albatrosses within national waters and on the high seas.</li><li><i>Policy implications</i>. Given the availability of Global Fishing Watch data, our analysis can be applied to other marine predators—if tracking data are available—to identify spatio-temporal patterns, vessel specific attributes and predator behaviours associated with fishing vessel associations, thus enabling predictive modelling and targeted mitigation measures.</li></ol>","language":"English","publisher":"British Ecological Society","doi":"10.1111/1365-2664.13849","usgsCitation":"Orben, R.A., Adams, J., Hester, M.M., Shaffer, S.A., Suryan, R.M., Deguchi, T., Ozaki, K., Sato, F., Young, L.C., Clatterbuck, C.A., Conners, M.G., Kroodsma, D.A., and Torres, L., 2021, Across borders: External factors and prior behaviour influence North Pacific albatross associations with fishing vessels: Journal of Applied Ecology, v. 58, no. 6, p. 1272-1283, https://doi.org/10.1111/1365-2664.13849.","productDescription":"12 p.","startPage":"1272","endPage":"1283","ipdsId":"IP-113755","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":488866,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://scholarworks.sjsu.edu/faculty_rsca/2998","text":"Publisher Index Page"},{"id":385757,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"58","issue":"6","noUsgsAuthors":false,"publicationDate":"2021-03-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Orben, Rachael A 0000-0002-0802-407X","orcid":"https://orcid.org/0000-0002-0802-407X","contributorId":221851,"corporation":false,"usgs":false,"family":"Orben","given":"Rachael","email":"","middleInitial":"A","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":816013,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Adams, Josh 0000-0003-3056-925X","orcid":"https://orcid.org/0000-0003-3056-925X","contributorId":213442,"corporation":false,"usgs":true,"family":"Adams","given":"Josh","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":816014,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hester, Michelle M. 0000-0002-0769-5904","orcid":"https://orcid.org/0000-0002-0769-5904","contributorId":197785,"corporation":false,"usgs":false,"family":"Hester","given":"Michelle","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":816015,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shaffer, Scott A. 0000-0002-7751-5059","orcid":"https://orcid.org/0000-0002-7751-5059","contributorId":202761,"corporation":false,"usgs":false,"family":"Shaffer","given":"Scott","email":"","middleInitial":"A.","affiliations":[{"id":24620,"text":"San Jose State University","active":true,"usgs":false}],"preferred":false,"id":816016,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Suryan, Robert M. 0000-0003-0755-8317","orcid":"https://orcid.org/0000-0003-0755-8317","contributorId":221852,"corporation":false,"usgs":false,"family":"Suryan","given":"Robert","email":"","middleInitial":"M.","affiliations":[{"id":40443,"text":"Oregon State University, NOAA","active":true,"usgs":false}],"preferred":false,"id":816017,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Deguchi, Tomo 0000-0001-8005-9114","orcid":"https://orcid.org/0000-0001-8005-9114","contributorId":258227,"corporation":false,"usgs":false,"family":"Deguchi","given":"Tomo","email":"","affiliations":[{"id":52255,"text":"Division of Avian Conservation, Yamashina Institute for Ornithology, Abiko, Chiba, Japan","active":true,"usgs":false}],"preferred":false,"id":816018,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ozaki, Kiyoaki 0000-0002-1056-231X","orcid":"https://orcid.org/0000-0002-1056-231X","contributorId":124594,"corporation":false,"usgs":false,"family":"Ozaki","given":"Kiyoaki","email":"","affiliations":[],"preferred":false,"id":816019,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sato, Fumio 0000-0002-0092-4479","orcid":"https://orcid.org/0000-0002-0092-4479","contributorId":255224,"corporation":false,"usgs":false,"family":"Sato","given":"Fumio","email":"","affiliations":[{"id":51492,"text":"Division of Avian Conservation, Yamashina Institute for Ornithology, 115 Konoyama, Abiko, Chiba 270-11, Japan","active":true,"usgs":false}],"preferred":false,"id":816020,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Young, Lindsay C.","contributorId":149044,"corporation":false,"usgs":false,"family":"Young","given":"Lindsay","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":816021,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Clatterbuck, Corey A. 0000-0003-1351-8565","orcid":"https://orcid.org/0000-0003-1351-8565","contributorId":202763,"corporation":false,"usgs":false,"family":"Clatterbuck","given":"Corey","email":"","middleInitial":"A.","affiliations":[{"id":24620,"text":"San Jose State University","active":true,"usgs":false}],"preferred":false,"id":816022,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Conners, Melinda G. 0000-0003-0572-0026","orcid":"https://orcid.org/0000-0003-0572-0026","contributorId":214869,"corporation":false,"usgs":false,"family":"Conners","given":"Melinda","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":816023,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Kroodsma, David A 0000-0002-1752-9141","orcid":"https://orcid.org/0000-0002-1752-9141","contributorId":258228,"corporation":false,"usgs":false,"family":"Kroodsma","given":"David","email":"","middleInitial":"A","affiliations":[{"id":52256,"text":"Global Fishing Watch, Washington, DC, USA","active":true,"usgs":false}],"preferred":false,"id":816024,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Torres, Leigh G 0000-0002-2643-3950","orcid":"https://orcid.org/0000-0002-2643-3950","contributorId":258229,"corporation":false,"usgs":false,"family":"Torres","given":"Leigh G","affiliations":[{"id":52257,"text":"Marine Mammal Institute, Department of Fisheries and Wildlife, Oregon State University, Newport, OR, USA","active":true,"usgs":false}],"preferred":false,"id":816025,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}}
,{"id":70231210,"text":"70231210 - 2021 - Forecasting ecological responses for wetland restoration planning in Florida's Everglades","interactions":[],"lastModifiedDate":"2022-05-04T13:25:44.781534","indexId":"70231210","displayToPublicDate":"2021-03-24T06:46:04","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Forecasting ecological responses for wetland restoration planning in Florida's Everglades","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-serif\"><div id=\"ab0010\" class=\"abstract author\" lang=\"en\"><div id=\"as0010\"><p id=\"sp0035\">The Everglades wetland was once a river of grass, with water flowing slowly through the sawgrass, southward across the landscape. As developers took hold of south Florida, water was sent away from the heart of the Everglades through canals and levees to protect the former wetland for residential and agricultural development. In the 1990s, planning began to restore the Everglades in what is the largest hydrologic restoration undertaking in the world. With billions of taxpayer dollars at stake, restoration planners benefit from forecasting tools to inform restoration planning. To meet this need, scientists developed predictive ecological models and other decision support tools tailored to this dynamic ecosystem as well as to the needs of restoration planning teams. Predictive modeling has been able to take advantage of well-understood relationships between species of interest and hydrologic dynamics in the Everglades. Recent modeling advances include multi-species approaches that consider interactions among species as well as explicit consideration of trade-offs among species from potential water management actions. Scientists are also starting to look at ecosystem-wide vulnerabilities with explicit consideration of future change such as sea level rise. Modeling tools and approaches continue to be refined to meet decision making needs for Everglades restoration. However, more work is needed to consider additional complexities of this dynamic wetland as well as to consider the broader socio-environmental system.</p></div></div></div>","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/B978-0-12-821139-7.00032-5","usgsCitation":"Romanach, S., and Pearlstine, L.G., 2021, Forecasting ecological responses for wetland restoration planning in Florida's Everglades, chap. <i>of</i> Reference module in earth systems and environmental sciences, https://doi.org/10.1016/B978-0-12-821139-7.00032-5.","ipdsId":"IP-124270","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":400022,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Everglades","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -81.947021484375,\n              25.030861410390447\n            ],\n            [\n              -79.7222900390625,\n              25.030861410390447\n            ],\n            [\n              -79.7222900390625,\n              26.799557733065352\n            ],\n            [\n              -81.947021484375,\n              26.799557733065352\n            ],\n            [\n              -81.947021484375,\n              25.030861410390447\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Romanach, Stephanie 0000-0003-0271-7825","orcid":"https://orcid.org/0000-0003-0271-7825","contributorId":220761,"corporation":false,"usgs":true,"family":"Romanach","given":"Stephanie","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":842039,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pearlstine, Leonard G.","contributorId":34751,"corporation":false,"usgs":false,"family":"Pearlstine","given":"Leonard","email":"","middleInitial":"G.","affiliations":[{"id":12462,"text":"U.S. Department of the Interior, National Park Service","active":true,"usgs":false}],"preferred":false,"id":842040,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70219153,"text":"70219153 - 2021 - Exploring VIIRS continuity with MODIS in an expedited capability for monitoring drought-related vegetation conditions","interactions":[],"lastModifiedDate":"2021-03-29T11:57:38.134952","indexId":"70219153","displayToPublicDate":"2021-03-23T11:47:45","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Exploring VIIRS continuity with MODIS in an expedited capability for monitoring drought-related vegetation conditions","docAbstract":"<p><span>Vegetation has been effectively monitored using remote sensing time-series vegetation index (VI) data for several decades. Drought monitoring has been a common application with algorithms tuned to capturing anomalous temporal and spatial vegetation patterns. Drought stress models, such as the Vegetation Drought Response Index (VegDRI), often use VIs like the Normalized Difference Vegetation Index (NDVI). The EROS expedited Moderate Resolution Imaging Spectroradiometer (eMODIS)-based, 7-day NDVI composites are integral to the VegDRI. As MODIS satellite platforms (Terra and Aqua) approach mission end, the Visible Infrared Imaging Radiometer Suite (VIIRS) presents an alternate NDVI source, with daily collection, similar band passes, and moderate spatial resolution. This study provides a statistical comparison between EROS expedited VIIRS (eVIIRS) 375-m and eMODIS 250-m and tests the suitability of replacing MODIS NDVI with VIIRS NDVI for drought monitoring and vegetation anomaly detection. For continuity with MODIS NDVI, we calculated a geometric mean regression adjustment algorithm using 375-m resolution for an eMODIS-like NDVI (eVIIRS’) eVIIRS’ = 0.9887 × eVIIRS − 0.0398. The resulting statistical comparisons (eVIIRS’ vs. eMODIS NDVI) showed correlations consistently greater than 0.84 throughout the three years studied. The eVIIRS’ VegDRI results characterized similar drought patterns and hotspots to the eMODIS-based VegDRI, with near zero bias.</span></p>","language":"English","publisher":"MDPI","doi":"10.3390/rs13061210","usgsCitation":"Benedict, T.D., Brown, J.F., Boyte, S., Howard, D., Fuchs, B., Wardlow, B.D., Tadesse, T., and Evenson, K., 2021, Exploring VIIRS continuity with MODIS in an expedited capability for monitoring drought-related vegetation conditions: Remote Sensing, v. 13, no. 6, 1210, 17 p., https://doi.org/10.3390/rs13061210.","productDescription":"1210, 17 p.","ipdsId":"IP-126651","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":452960,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs13061210","text":"Publisher Index Page"},{"id":384696,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United  States","state":"Kansas","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -98.61328125,\n              37.68382032669382\n            ],\n            [\n              -94.833984375,\n              37.68382032669382\n            ],\n            [\n              -94.833984375,\n              39.977120098439634\n            ],\n            [\n              -98.61328125,\n              39.977120098439634\n            ],\n            [\n              -98.61328125,\n              37.68382032669382\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"13","issue":"6","noUsgsAuthors":false,"publicationDate":"2021-03-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Benedict, Trenton D 0000-0001-8672-2204","orcid":"https://orcid.org/0000-0001-8672-2204","contributorId":256662,"corporation":false,"usgs":false,"family":"Benedict","given":"Trenton","email":"","middleInitial":"D","affiliations":[{"id":51826,"text":"KBR, Inc. Contractor to the USGS Earth Resources Observation & Science (EROS) Center","active":true,"usgs":false}],"preferred":false,"id":812983,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brown, Jesslyn F. 0000-0002-9976-1998 jfbrown@usgs.gov","orcid":"https://orcid.org/0000-0002-9976-1998","contributorId":176609,"corporation":false,"usgs":true,"family":"Brown","given":"Jesslyn","email":"jfbrown@usgs.gov","middleInitial":"F.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":812984,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Boyte, Stephen P. 0000-0002-5462-3225","orcid":"https://orcid.org/0000-0002-5462-3225","contributorId":205374,"corporation":false,"usgs":true,"family":"Boyte","given":"Stephen P.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":812985,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Howard, Daniel 0000-0002-7563-7538","orcid":"https://orcid.org/0000-0002-7563-7538","contributorId":256667,"corporation":false,"usgs":false,"family":"Howard","given":"Daniel","affiliations":[{"id":51826,"text":"KBR, Inc. Contractor to the USGS Earth Resources Observation & Science (EROS) Center","active":true,"usgs":false}],"preferred":false,"id":812986,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fuchs, Brian","contributorId":192359,"corporation":false,"usgs":false,"family":"Fuchs","given":"Brian","email":"","affiliations":[],"preferred":false,"id":812987,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wardlow, Brian D. 0000-0002-4767-581X","orcid":"https://orcid.org/0000-0002-4767-581X","contributorId":191403,"corporation":false,"usgs":false,"family":"Wardlow","given":"Brian","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":812988,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Tadesse, Tsegaye 0000-0002-4102-1137","orcid":"https://orcid.org/0000-0002-4102-1137","contributorId":147617,"corporation":false,"usgs":false,"family":"Tadesse","given":"Tsegaye","email":"","affiliations":[],"preferred":false,"id":812989,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Evenson, Kirk","contributorId":256674,"corporation":false,"usgs":false,"family":"Evenson","given":"Kirk","email":"","affiliations":[{"id":51826,"text":"KBR, Inc. Contractor to the USGS Earth Resources Observation & Science (EROS) Center","active":true,"usgs":false}],"preferred":false,"id":812990,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70223101,"text":"70223101 - 2021 - Assessment of sea lamprey (Petromyzon marinus) diet using DNA metabarcoding of feces","interactions":[],"lastModifiedDate":"2021-08-11T14:40:29.799032","indexId":"70223101","displayToPublicDate":"2021-03-23T09:32:42","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Assessment of sea lamprey (<i>Petromyzon marinus</i>) diet using DNA metabarcoding of feces","title":"Assessment of sea lamprey (Petromyzon marinus) diet using DNA metabarcoding of feces","docAbstract":"<p><span>Sea lamprey (</span><span><i>Petromyzon marinus</i></span><span>) are invasive in the Laurentian Great Lakes, parasitize large-bodied fishes, and therefore are the focus of an international control program. However, damage caused by sea lamprey to modern day fish stocks remains uncertain because diet analysis of juvenile sea lamprey has been challenging; they feed on blood and are difficult to randomly sample in the lakes. Here, both challenges were addressed by showing that DNA metabarcoding of fecal material can be used to identify the diet of actively feeding juvenile sea lamprey, and can also be used to determine what non-feeding adult sea lamprey captured in streams fed on while parasitizing fish. Fecal samples from juvenile sea lamprey that were feeding on lake trout in northern Lake Huron overwhelmingly contained lake trout (</span><span><i>Salvelinus namaycush</i></span><span>) DNA (90%), while smaller percentages contained lake whitefish (</span><span><i>Coregonus clupeaformis</i></span><span>; 5%) and longnose sucker (</span><span><i>Catostomus</i><i>&nbsp;catostomus</i></span><span>; 5%) DNA. Fecal samples from adult sea lamprey captured from a tributary to northern Lake Huron overwhelmingly contained longnose and white sucker DNA (</span><i>Catostomus</i><span>&nbsp;spp.; 80%), while a smaller percentage contained lake trout DNA (10%). Diet composition of adult sea lamprey sampled in the tributary (Black Mallard Creek) was more diverse than juvenile diet composition. DNA metabarcoding suggests that&nbsp;</span><i>Catostomus</i><span>&nbsp;spp. may be an important host fish in northern Lake Huron for sea lamprey prior to spawning. Future research could investigate how diet varies across years and lakes and the prevalence and sources of DNA contamination. Application of DNA metabarcoding for diet assessment may be practical for identifying populations of invasive sea lamprey that feed on highly valued fishes and help guide restoration of lampreys worldwide.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2021.107605","usgsCitation":"Johnson, N.S., Lewandoski, S.A., and Merkes, C.M., 2021, Assessment of sea lamprey (Petromyzon marinus) diet using DNA metabarcoding of feces: Ecological Indicators, v. 125, 107605, 9 p., https://doi.org/10.1016/j.ecolind.2021.107605.","productDescription":"107605, 9 p.","ipdsId":"IP-127616","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":452962,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolind.2021.107605","text":"Publisher Index Page"},{"id":387856,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan","otherGeospatial":"Hammond Bay, Lake Huron","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -83.99459838867188,\n              45.49431506693786\n            ],\n            [\n              -83.9520263671875,\n              45.53232688809725\n            ],\n            [\n              -83.97880554199219,\n              45.58761466314763\n            ],\n            [\n              -84.06257629394531,\n              45.6029894122523\n            ],\n            [\n              -84.11819458007811,\n              45.58569252333191\n            ],\n            [\n              -84.12574768066406,\n              45.558294879426235\n            ],\n            [\n              -84.11338806152344,\n              45.511640093571096\n            ],\n            [\n              -84.07424926757812,\n              45.49238973487207\n            ],\n            [\n              -84.02549743652344,\n              45.50057194157223\n            ],\n            [\n              -83.99459838867188,\n              45.49431506693786\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"125","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Johnson, Nicholas S. 0000-0002-7419-6013 njohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-7419-6013","contributorId":597,"corporation":false,"usgs":true,"family":"Johnson","given":"Nicholas","email":"njohnson@usgs.gov","middleInitial":"S.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":820952,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lewandoski, Sean A.","contributorId":221007,"corporation":false,"usgs":false,"family":"Lewandoski","given":"Sean","email":"","middleInitial":"A.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":820953,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Merkes, Christopher M. 0000-0001-8191-627X cmerkes@usgs.gov","orcid":"https://orcid.org/0000-0001-8191-627X","contributorId":139516,"corporation":false,"usgs":true,"family":"Merkes","given":"Christopher","email":"cmerkes@usgs.gov","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":820954,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70222609,"text":"70222609 - 2021 - Geological constraints on the mechanisms of slow earthquakes","interactions":[],"lastModifiedDate":"2021-08-09T13:57:48.415744","indexId":"70222609","displayToPublicDate":"2021-03-23T08:54:52","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9136,"text":"Nature Reviews Earth and Environment","active":true,"publicationSubtype":{"id":10}},"title":"Geological constraints on the mechanisms of slow earthquakes","docAbstract":"<p><span>The recognition of slow earthquakes in geodetic and seismological data has transformed the understanding of how plate motions are accommodated at major plate boundaries. Slow earthquakes, which slip more slowly than regular earthquakes but faster than plate motion velocities, occur in a range of tectonic and metamorphic settings. They exhibit spatiotemporal associations with large seismic events that indicate a causal relation between modes of slip at different slip rates. Defining the physical controls on slow earthquakes is, therefore, critical for understanding fault and shear zone mechanics. In this Review, we synthesize geological observations of a suite of ancient structures that were active in tectonic settings comparable to where slow earthquakes are observed today. At inferred slow earthquake regions, a range of grain-scale deformation mechanisms accommodated slip at low effective stresses. Material heterogeneity and the geometric complexity of structures that formed at different inferred strain rates are common to faults and shear zones in multiple tectonic environments, and might represent key limiting factors of slow earthquake slip rates. Further geological work is needed to resolve how the spectrum of slow earthquake slip rates can arise from different grain-scale deformation mechanisms and whether there is one universal rate-limiting mechanism that defines slow earthquake slip.</span></p>","language":"English","publisher":"Nature Publications","doi":"10.1038/s43017-021-00148-w","usgsCitation":"Kirkpatrick, J.D., Fagereng, A., and Shelly, D.R., 2021, Geological constraints on the mechanisms of slow earthquakes: Nature Reviews Earth and Environment, v. 2, p. 285-301, https://doi.org/10.1038/s43017-021-00148-w.","productDescription":"17 p.","startPage":"285","endPage":"301","ipdsId":"IP-124320","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":467251,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://orca.cardiff.ac.uk/id/eprint/140270/","text":"External Repository"},{"id":387780,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"2","noUsgsAuthors":false,"publicationDate":"2021-03-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Kirkpatrick, James D.","contributorId":202603,"corporation":false,"usgs":false,"family":"Kirkpatrick","given":"James","email":"","middleInitial":"D.","affiliations":[{"id":6646,"text":"McGill University","active":true,"usgs":false}],"preferred":false,"id":820736,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fagereng, Ake","contributorId":261903,"corporation":false,"usgs":false,"family":"Fagereng","given":"Ake","email":"","affiliations":[{"id":53076,"text":"School of Earth & Ocean Sciences, Cardiff University, Cardiff, CF10 3AT, UK","active":true,"usgs":false}],"preferred":false,"id":820737,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shelly, David R. 0000-0003-2783-5158 dshelly@usgs.gov","orcid":"https://orcid.org/0000-0003-2783-5158","contributorId":206750,"corporation":false,"usgs":true,"family":"Shelly","given":"David","email":"dshelly@usgs.gov","middleInitial":"R.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":820803,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70218995,"text":"pp1842DD - 2021 - The effects of management practices on grassland birds—Lark Sparrow (Chondestes grammacus)","interactions":[{"subject":{"id":70218995,"text":"pp1842DD - 2021 - The effects of management practices on grassland birds—Lark Sparrow (Chondestes grammacus)","indexId":"pp1842DD","publicationYear":"2021","noYear":false,"chapter":"DD","displayTitle":"The Effects of Management Practices on Grassland Birds—Lark Sparrow (<i>Chondestes grammacus</i>)","title":"The effects of management practices on grassland birds—Lark Sparrow (Chondestes grammacus)"},"predicate":"IS_PART_OF","object":{"id":70203022,"text":"pp1842 - 2019 - The effects of management practices on grassland birds","indexId":"pp1842","publicationYear":"2019","noYear":false,"title":"The effects of management practices on grassland birds"},"id":1}],"isPartOf":{"id":70203022,"text":"pp1842 - 2019 - The effects of management practices on grassland birds","indexId":"pp1842","publicationYear":"2019","noYear":false,"title":"The effects of management practices on grassland birds"},"lastModifiedDate":"2023-12-20T20:56:32.615583","indexId":"pp1842DD","displayToPublicDate":"2021-03-23T08:45:33","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":331,"text":"Professional Paper","code":"PP","onlineIssn":"2330-7102","printIssn":"1044-9612","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1842","chapter":"DD","displayTitle":"The Effects of Management Practices on Grassland Birds—Lark Sparrow (<i>Chondestes grammacus</i>)","title":"The effects of management practices on grassland birds—Lark Sparrow (Chondestes grammacus)","docAbstract":"<p>Keys to Lark Sparrow (<i>Chondestes grammacus</i>) management include providing open grasslands with sparse-to-moderate herbaceous and litter cover and a woody component and allowing occasional burning or moderate grazing. Lark Sparrows have been reported to use habitats with 10–63 centimeters (cm) average vegetation height, 10–54 percent grass cover, 9–25 percent forb cover, 4–18 percent shrub cover, 16–38 percent bare ground, 12–45 percent litter cover, and less than or equal to 1 cm litter depth.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1842DD","usgsCitation":"Shaffer, J.A., Igl, L.D., Johnson, D.H., Sondreal, M.L., Goldade, C.M., Parkin, B.D., and Euliss, B.R., 2021, The effects of management practices on grassland birds—Lark Sparrow (<i>Chondestes grammacus</i>), chap. DD <i>of</i> Johnson, D.H., Igl, L.D., Shaffer, J.A., and DeLong, J.P., eds., The effects of management practices on grassland birds: U.S. Geological Survey Professional Paper 1842, 16 p., https://doi.org/10.3133/pp1842DD.","productDescription":"iv, 21 p.","numberOfPages":"30","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-095209","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":384458,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1842/dd/coverthb.jpg"},{"id":384459,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1842/dd/pp1842dd.pdf","text":"Report","size":"2.09 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1842–DD"}],"contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/npwrc\" data-mce-href=\"https://www.usgs.gov/centers/npwrc\">Northern Prairie Wildlife Research Center</a> <br>U.S. Geological Survey<br>8711 37th Street Southeast <br>Jamestown, ND&nbsp;58401</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Capsule Statement</li><li>Breeding Range</li><li>Suitable Habitat</li><li>Area Requirements and Landscape Associations</li><li>Brood Parasitism by Cowbirds and Other Species</li><li>Breeding-Season Phenology and Site Fidelity</li><li>Species’ Response to Management</li><li>Management Recommendations from the Literature</li><li>References</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2021-03-23","noUsgsAuthors":false,"publicationDate":"2021-03-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Shaffer, Jill A. 0000-0003-3172-0708","orcid":"https://orcid.org/0000-0003-3172-0708","contributorId":223126,"corporation":false,"usgs":true,"family":"Shaffer","given":"Jill A.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":812419,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Igl, Lawrence D. 0000-0003-0530-7266","orcid":"https://orcid.org/0000-0003-0530-7266","contributorId":223125,"corporation":false,"usgs":true,"family":"Igl","given":"Lawrence","email":"","middleInitial":"D.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":812420,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Douglas H. 0000-0002-7778-6641","orcid":"https://orcid.org/0000-0002-7778-6641","contributorId":220516,"corporation":false,"usgs":true,"family":"Johnson","given":"Douglas H.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":812421,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sondreal, Marriah L.","contributorId":73532,"corporation":false,"usgs":true,"family":"Sondreal","given":"Marriah","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":812422,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Goldade, Christopher M.","contributorId":90668,"corporation":false,"usgs":true,"family":"Goldade","given":"Christopher M.","affiliations":[],"preferred":false,"id":812423,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Parkin, Barry D.","contributorId":216020,"corporation":false,"usgs":false,"family":"Parkin","given":"Barry","email":"","middleInitial":"D.","affiliations":[{"id":39297,"text":"former U.S. Geological Survey employee","active":true,"usgs":false}],"preferred":false,"id":812424,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Euliss, Betty R.","contributorId":191881,"corporation":false,"usgs":false,"family":"Euliss","given":"Betty","email":"","middleInitial":"R.","affiliations":[{"id":24583,"text":"former USGS employee","active":true,"usgs":false}],"preferred":false,"id":812425,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70219127,"text":"70219127 - 2021 - Evaluating low flow patterns, drivers and trends in the Delaware River Basin","interactions":[],"lastModifiedDate":"2021-04-08T15:21:33.345833","indexId":"70219127","displayToPublicDate":"2021-03-23T08:28:42","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating low flow patterns, drivers and trends in the Delaware River Basin","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-serif\"><div id=\"ab010\" class=\"abstract author\" lang=\"en\"><div id=\"as010\"><p id=\"sp0010\">In the humid, temperate Delaware River Basin (DRB) where water availability is generally reliable, summer low flows can cause competition between various human and ecological water uses. As temperatures continue to rise, population increases and development expands, it is critical to understand historical low flow variability to anticipate and plan for future flows. Using a sample of 325 U.S. Geological Survey gages, we evaluated spatial patterns in several low flow metrics, the biophysical and climatic drivers of these metrics, and trends in low flows for two periods: 1950-2018 and 1980-2018. We calculated the annual 7-day low flow and date, low flow deficit as the departure below a long-term daily flow threshold and the number of discrete low flow periods below this threshold. We also aggregated several climate metrics to watershed scale and used existing watershed properties quantifying land cover, topography, soils, geology, and human activity. Random forest models were used to assess the hierarchy of variable importance in explaining mean-annual low flow variability for each low flow metric using all gages. We find muted regional patterns in mean-annual low flow and low flow variability, likely due to the myriad of anthropogenic, landscape, and flow modifications that obscure flow regimes from their natural characteristics. In contrast, individual years show markedly different spatial patterns in low flow magnitude and severity. Coincident with increases in precipitation, 7-day low flows have generally increased and low flow deficits decreased for both 1950-2018 and 1980-2018 periods. However, 7-day low flows have decreased in the Coastal Plain physiographic province where water use and impervious area have increased in recent decades, highlighting the effects of land and water management on low flows. With continued change expected in the DRB, additional research needs are highlighted to enable estimation of future low flows and to plan for periods of prolonged low flow.</p></div></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2021.126246","usgsCitation":"Hammond, J., and Fleming, B.J., 2021, Evaluating low flow patterns, drivers and trends in the Delaware River Basin: Journal of Hydrology, v. 598, 126246, 13 p., https://doi.org/10.1016/j.jhydrol.2021.126246.","productDescription":"126246, 13 p.","ipdsId":"IP-119782","costCenters":[{"id":41514,"text":"Maryland-Delaware-District of Columbia  Water Science Center","active":true,"usgs":true}],"links":[{"id":452969,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jhydrol.2021.126246","text":"Publisher Index Page"},{"id":436442,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P92UYECV","text":"USGS data release","linkHelpText":"Annual low flow, climate and watershed properties for 325 USGS gages in and near the Delaware River Basin"},{"id":384673,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Delaware, New Jersey, New York, Pennsylvania","otherGeospatial":"Delaware River Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -77.080078125,\n              40.622291783092706\n            ],\n            [\n              -76.86035156249999,\n              39.317300373271024\n            ],\n            [\n              -75.69580078125,\n              38.436379603\n            ],\n            [\n              -75.08056640625,\n              38.40194908237822\n            ],\n            [\n              -74.454345703125,\n              38.71980474264237\n            ],\n            [\n              -73.927001953125,\n              40.16208338164617\n            ],\n            [\n              -74.00390625,\n              41.409775832009565\n            ],\n            [\n              -74.50927734375,\n              42.00032514831621\n            ],\n            [\n              -75.289306640625,\n              41.934976500546604\n            ],\n            [\n              -76.058349609375,\n              41.46742831254425\n            ],\n            [\n              -77.080078125,\n              40.622291783092706\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"598","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hammond, John C. 0000-0002-4935-0736","orcid":"https://orcid.org/0000-0002-4935-0736","contributorId":223108,"corporation":false,"usgs":true,"family":"Hammond","given":"John C.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia  Water Science Center","active":true,"usgs":true}],"preferred":true,"id":812887,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fleming, Brandon J. 0000-0001-9649-7485 bjflemin@usgs.gov","orcid":"https://orcid.org/0000-0001-9649-7485","contributorId":4115,"corporation":false,"usgs":true,"family":"Fleming","given":"Brandon","email":"bjflemin@usgs.gov","middleInitial":"J.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":812888,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70219162,"text":"70219162 - 2021 - Natural and anthropogenic geochemical tracers to investigate residence times and groundwater–surface-water interactions in an urban alluvial aquifer","interactions":[],"lastModifiedDate":"2021-03-29T12:54:34.606575","indexId":"70219162","displayToPublicDate":"2021-03-23T07:51:21","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Natural and anthropogenic geochemical tracers to investigate residence times and groundwater–surface-water interactions in an urban alluvial aquifer","docAbstract":"<p><span>A multi-component geochemical dataset was collected from groundwater and surface-water bodies associated with the urban Fountain Creek alluvial aquifer, Colorado, USA, to facilitate analysis of recharge sources, geochemical interactions, and groundwater-residence times. Results indicate that groundwater can be separated into three distinct geochemical zones based on location within the flow system and proximity to surface water, and these zones can be used to infer sources of recharge and groundwater movement through the aquifer. Rare-earth-element concentrations and detections of wastewater-indicator compounds indicate the presence of effluent from wastewater-treatment plants in both groundwater and surface water. Effluent presence in groundwater indicates that streams in the area lose to groundwater in some seasons and are a source of focused groundwater recharge. Distributions of pharmaceuticals and wastewater-indicator compounds also inform an understanding of groundwater–surface-water interactions. Noble-gas isotopes corroborate rare-earth-element data in indicating geochemical evolution within the aquifer from recharge area to discharge area and qualitatively indicate variable groundwater-residence times and mixing with pre-modern groundwater. Quantitative groundwater-residence times calculated from&nbsp;</span><sup>3</sup><span>H/</span><sup>3</sup><span>He, SF</span><sub>6</sub><span>, and lumped-parameter modeling generally are less than 20 years, but the presence of mixing with older groundwater of an unknown age is also indicated at selected locations. Future investigations would benefit by including groundwater-age tracers suited to quantification of mixing for both young (years to decades) and old (centuries and millennia) groundwater. This multi-faceted analysis facilitated development of a conceptual model for the investigated groundwater-flow system and illustrates the application of an encompassing suite of analytes in exploring hydrologic and geochemical interactions in complex systems.&nbsp;</span></p>","language":"English","publisher":"MDPI","doi":"10.3390/w13060871","usgsCitation":"Newman, C.P., Paschke, S.S., and Keith, G.L., 2021, Natural and anthropogenic geochemical tracers to investigate residence times and groundwater–surface-water interactions in an urban alluvial aquifer: Water, v. 13, no. 6, 30 p., https://doi.org/10.3390/w13060871.","productDescription":"30 p.","ipdsId":"IP-118155","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":452974,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w13060871","text":"Publisher Index Page"},{"id":436443,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P99SPQM2","text":"USGS data release","linkHelpText":"Environmental-tracer modeling to support hydrogeochemical evaluation of the Fountain Creek Alluvial Aquifer, El Paso County, Colorado, 2018-2019"},{"id":384712,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United  States","state":"Colorado","city":"Colorado Springs","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -105.2490234375,\n              38.61687046392973\n            ],\n            [\n              -104.1888427734375,\n              38.61687046392973\n            ],\n            [\n              -104.1888427734375,\n              39.16839998800286\n            ],\n            [\n              -105.2490234375,\n              39.16839998800286\n            ],\n            [\n              -105.2490234375,\n              38.61687046392973\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"13","issue":"6","noUsgsAuthors":false,"publicationDate":"2021-03-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Newman, Connor P. 0000-0002-6978-3440","orcid":"https://orcid.org/0000-0002-6978-3440","contributorId":222596,"corporation":false,"usgs":true,"family":"Newman","given":"Connor","email":"","middleInitial":"P.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":813075,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Paschke, Suzanne S. 0000-0002-3471-4242 spaschke@usgs.gov","orcid":"https://orcid.org/0000-0002-3471-4242","contributorId":1347,"corporation":false,"usgs":true,"family":"Paschke","given":"Suzanne","email":"spaschke@usgs.gov","middleInitial":"S.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":813076,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Keith, Gabrielle L. 0000-0002-2304-8504 gkeith@usgs.gov","orcid":"https://orcid.org/0000-0002-2304-8504","contributorId":256699,"corporation":false,"usgs":true,"family":"Keith","given":"Gabrielle","email":"gkeith@usgs.gov","middleInitial":"L.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":813077,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70259605,"text":"70259605 - 2021 - Assessment of a claimed ultra-low frequency electromagnetic (ULFEM) earthquake precursor","interactions":[],"lastModifiedDate":"2024-10-17T12:04:01.889156","indexId":"70259605","displayToPublicDate":"2021-03-23T07:01:24","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1803,"text":"Geophysical Journal International","active":true,"publicationSubtype":{"id":10}},"title":"Assessment of a claimed ultra-low frequency electromagnetic (ULFEM) earthquake precursor","docAbstract":"<p class=\"chapter-para\">The rate of occurrence of anomalous ultra-low frequency electromagnetic (ULFEM) pulses has been claimed to have increased days to weeks prior to the M5.4 2007 and M4.0 2010 Alum Rock earthquakes. We re-examine the previously reported ultra-low frequency (ULF: 0.01–10&nbsp;Hz) magnetic data recorded at a QuakeFinder site located 9&nbsp;km from the earthquake hypocentre, and compare to data from a nearby Stanford-USGS site located 42&nbsp;km from the hypocentre, to analyse the characteristics of the pulses and assess their origin. Using pulse definitions and pulse-counting algorithms analogous to those previously reported, we corroborate the increase in pulse counts before the 2007 Alum Rock earthquake at the QuakeFinder station, but we note that the number of pulses depends on chosen temporal and amplitude detection thresholds. These thresholds are arbitrary because we lack a clear physical model or basis for their selection. We do not see the same increase in pulse counts before the 2010 Alum Rock earthquake at the QuakeFinder or Stanford-USGS stations. In addition, the majority of pulses in the QuakeFinder data and Stanford-USGS data do not match temporally, indicating the pulses lack a common origin and are not from lightning or solar-driven ionospheric/magnetospheric disturbances. Our assessment of the temporal distribution of pulse counts shows pulse counts increase during peak human activity hours, suggesting these pulses result from local cultural noise and are not tectonic in origin. The many unknowns about the character and even existence of precursory earthquake pulses means that standard numerical and statistical tests cannot easily be applied. Yet here we show that exhaustive investigation of many different aspects of ULFEM signals can be used to properly characterize their origin.</p>","language":"English","publisher":"Oxford Academic","doi":"10.1093/gji/ggab530","usgsCitation":"Wang, C., Christman, L., Klemperer, S., Glen, J.M., McPhee, D., and Bin, C., 2021, Assessment of a claimed ultra-low frequency electromagnetic (ULFEM) earthquake precursor: Geophysical Journal International, v. 229, no. 3, p. 2081-2095, https://doi.org/10.1093/gji/ggab530.","productDescription":"15 p.","startPage":"2081","endPage":"2095","ipdsId":"IP-136197","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":467252,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/gji/ggab530","text":"Publisher Index Page"},{"id":462937,"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        \"coordinates\": [\n          [\n            [\n              -122.74855580223482,\n              37.923464830974424\n            ],\n            [\n              -122.74855580223482,\n              37.22689363596939\n            ],\n            [\n              -121.73781361473472,\n              37.22689363596939\n            ],\n            [\n              -121.73781361473472,\n              37.923464830974424\n            ],\n            [\n              -122.74855580223482,\n              37.923464830974424\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"229","issue":"3","noUsgsAuthors":false,"publicationDate":"2021-03-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Wang, Can","contributorId":345181,"corporation":false,"usgs":false,"family":"Wang","given":"Can","email":"","affiliations":[{"id":82515,"text":"Institute of Geophysics, China Earthquake Administration, Beijing 100081, P.R. China","active":true,"usgs":false}],"preferred":false,"id":915919,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Christman, Lilianna","contributorId":345182,"corporation":false,"usgs":false,"family":"Christman","given":"Lilianna","email":"","affiliations":[],"preferred":false,"id":915920,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Klemperer, Simon","contributorId":345183,"corporation":false,"usgs":false,"family":"Klemperer","given":"Simon","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":915921,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Glen, Jonathan M.G. 0000-0002-3502-3355 jglen@usgs.gov","orcid":"https://orcid.org/0000-0002-3502-3355","contributorId":176530,"corporation":false,"usgs":true,"family":"Glen","given":"Jonathan","email":"jglen@usgs.gov","middleInitial":"M.G.","affiliations":[{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":915922,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McPhee, Darcy 0000-0002-5177-3068 dmcphee@usgs.gov","orcid":"https://orcid.org/0000-0002-5177-3068","contributorId":2621,"corporation":false,"usgs":true,"family":"McPhee","given":"Darcy","email":"dmcphee@usgs.gov","affiliations":[{"id":412,"text":"National Cooperative Geologic Mapping Program","active":false,"usgs":true}],"preferred":true,"id":915923,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bin, Chen","contributorId":345184,"corporation":false,"usgs":false,"family":"Bin","given":"Chen","email":"","affiliations":[{"id":82515,"text":"Institute of Geophysics, China Earthquake Administration, Beijing 100081, P.R. 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,{"id":70219057,"text":"tm6H1 - 2021 - The basin characterization model—A regional water balance software package","interactions":[],"lastModifiedDate":"2021-03-25T18:39:35.720713","indexId":"tm6H1","displayToPublicDate":"2021-03-22T12:41:35","publicationYear":"2021","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":"6-H1","displayTitle":"The Basin Characterization Model—A Regional Water Balance Software Package","title":"The basin characterization model—A regional water balance software package","docAbstract":"<p>This report documents the computer software package, Basin Characterization Model, version 8 (BCMv8)—a monthly, gridded, regional water-balance model—and provides detailed operational instructions and example applications. After several years of many applications and uses of a previous version, CA-BCM, published in 2014, the BCMv8 was refined to improve the accuracy of the water-balance components, particularly the recharge estimate, which is the most difficult to accurately assess. The improvement of the various water-balance components targeted the actual evapotranspiration component, which, in turn, reduced the uncertainty of the recharge estimate. The improvement of this component was enabled by the availability of a national, gridded actual-evapotranspiration product from the U.S. Geological Survey that was unique in its scope to combine remotely sensed spatial variability and ground-based long-term water-balance constraints. This dataset provided the ability to assess monthly actual evapotranspiration for 62 vegetation types and to perform regional calibration in watersheds throughout California with the objective of closing the water balance using improved estimates for each component. The refinements, including vegetation-specific evapotranspiration, enabled the development of applications that could explore various aspects of landscape disturbance, such as wildfire, forest management, or urbanization. The improvements to BCMv8 also provided the ability to assess long-term sustainability of water resources under a variety of management applications or future climate projections.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm6H1","collaboration":"Prepared in cooperation with California Department of Water Resources","usgsCitation":"Flint, L.E., Flint, A.L., and Stern, M.A., 2021, The basin characterization model—A regional water balance software package: U.S. Geological Survey Techniques and Methods 6–H1, 85 p., https://doi.org/10.3133/tm6H1.","productDescription":"x, 85 p.","numberOfPages":"85","onlineOnly":"Y","ipdsId":"IP-101075","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":436445,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9K23J25","text":"USGS data release","linkHelpText":"Future Climate and Hydrology from Twenty 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 \"}}]}","contact":"<p><a href=\"mailto:dc_ca@usgs.gov\" data-mce-href=\"mailto:dc_ca@usgs.gov\">Director</a>,<br><a href=\"https://ca.water.usgs.gov/\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://ca.water.usgs.gov\">California Water Science Center</a><br><a data-mce-href=\"https://usgs.gov\" href=\"https://usgs.gov\" target=\"_blank\" rel=\"noopener\">U.S. Geological Survey</a><br>6000 J Street, Placer Hall<br>Sacramento, California 95819</p>","tableOfContents":"<ul><li>Preface</li><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Description of Computer Software Basin Characterization Model</li><li>Developing a BCMv8 Water Balance for a Basin</li><li>Developing a New BCMv8</li><li>Model Uncertainties and Limitations</li><li>Example Applications</li><li>Summary</li><li>References Cited</li><li>Appendixes</li></ul>","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2021-03-22","noUsgsAuthors":false,"publicationDate":"2021-03-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Flint, Lorraine E. 0000-0002-7868-441X lflint@usgs.gov","orcid":"https://orcid.org/0000-0002-7868-441X","contributorId":1184,"corporation":false,"usgs":true,"family":"Flint","given":"Lorraine","email":"lflint@usgs.gov","middleInitial":"E.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":812619,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Flint, Alan L. 0000-0002-5118-751X aflint@usgs.gov","orcid":"https://orcid.org/0000-0002-5118-751X","contributorId":1492,"corporation":false,"usgs":true,"family":"Flint","given":"Alan","email":"aflint@usgs.gov","middleInitial":"L.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":812620,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stern, Michelle A. 0000-0003-3030-7065 mstern@usgs.gov","orcid":"https://orcid.org/0000-0003-3030-7065","contributorId":4244,"corporation":false,"usgs":true,"family":"Stern","given":"Michelle","email":"mstern@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":812621,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70219088,"text":"70219088 - 2021 - Mapping climate change vulnerability of aquatic-riparian ecosystems using decision-relevant indicators","interactions":[],"lastModifiedDate":"2021-03-23T13:13:09.442898","indexId":"70219088","displayToPublicDate":"2021-03-22T08:10:00","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Mapping climate change vulnerability of aquatic-riparian ecosystems using decision-relevant indicators","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-serif\"><div id=\"ab010\" class=\"abstract author\" lang=\"en\"><div id=\"as010\"><p id=\"sp0010\">Climate change has and is projected to continue to alter historical regimes of temperature, precipitation, and hydrology. To assess the vulnerability of climate change from a land management perspective and spatially identify where the most extreme changes are anticipated to occur, we worked in collaboration with land managers to develop a climate change vulnerability map for the midwestern United States with a focus on riparian systems.&nbsp;<span>The map is intended for use by regional administrators to help them work across various program areas (e.g. fisheries, endangered species) to prioritize locations needing support for adaptation planning. The tool can also be utilized locally by managers to better understand the effects that projected climate scenarios have on the hydrology of management units as they develop adaptation strategies. The vulnerability map is watershed-based (360 watershed units within the region) and combines 15 climate change indicators that were selected by&nbsp;U.S. Fish and Wildlife Service&nbsp;natural resource managers based upon known and anticipated effects to species and habitats. The projected change in each of these indicators from the historical period (1986–2005) to the future period (2040–2059) was aggregated into a composite score for each watershed. Landscape-scale metrics reflective of a watershed’s adaptive capacity were combined with the climate change indicators to produce a vulnerability score. We found sub-regional variation in vulnerability to climate change with the greatest vulnerability in Iowa, central Illinois, and northwest Ohio. Greater vulnerability was seen in the higher greenhouse gas concentration scenario, Representative Concentration Pathway (RCP) 8.5 compared to the lower greenhouse gas concentration scenario RCP 4.5, when looking at the mean of the five downscaled climate models used in this study. By quantifying and mapping climate change vulnerability, natural resource managers can better understand the degree of vulnerability for individual watersheds and identify areas of prioritization in regional and local planning efforts.</span></p></div></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2021.107581","usgsCitation":"Delaney, J., Bouska, K.L., Eash, J.D., Heglund, P.J., and Allstadt, A.A., 2021, Mapping climate change vulnerability of aquatic-riparian ecosystems using decision-relevant indicators: Ecological Indicators, v. 125, 107581, 12 p., https://doi.org/10.1016/j.ecolind.2021.107581.","productDescription":"107581, 12 p.","ipdsId":"IP-120781","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":452981,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolind.2021.107581","text":"Publisher Index Page"},{"id":436448,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9AL7GZM","text":"USGS data release","linkHelpText":"Model Inputs: Midwest Climate Change Vulnerability Assessment for the U.S. Fish and Wildlife Service"},{"id":384577,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Iowa, Illinois, Indiana, Michigan, Minnesota, Missouri, Ohio, Wisconsin","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[-87.800477,42.49192],[-87.812461,42.232278],[-87.511043,41.696535],[-87.187651,41.629653],[-86.616978,41.896625],[-86.321803,42.310743],[-86.208309,42.762789],[-86.540916,43.633158],[-86.25395,44.64808],[-86.066745,44.905685],[-85.780439,44.977932],[-85.540497,45.210169],[-85.641652,44.810816],[-85.520205,44.960347],[-85.477423,44.813781],[-85.355478,45.282774],[-84.91585,45.393115],[-85.110884,45.526285],[-84.94565,45.708621],[-85.011433,45.757962],[-84.204218,45.627116],[-84.095905,45.497298],[-83.488826,45.355872],[-83.291346,45.062597],[-83.435822,45.000012],[-83.277213,44.7167],[-83.335248,44.357995],[-83.890145,43.934672],[-83.909479,43.672622],[-83.618602,43.628891],[-83.227093,43.981003],[-82.833103,44.036851],[-82.643166,43.852468],[-82.423086,42.988728],[-82.509935,42.637294],[-82.648776,42.550401],[-82.630922,42.64211],[-82.780817,42.652232],[-83.431103,41.757457],[-82.481214,41.381342],[-81.69325,41.514161],[-80.533774,41.973475],[-80.518991,40.638801],[-80.667957,40.582496],[-80.619297,40.26517],[-80.88036,39.620706],[-81.656138,39.277355],[-81.874857,38.881174],[-82.068864,38.984878],[-82.318111,38.457876],[-82.569368,38.406258],[-82.923694,38.750076],[-83.301951,38.598178],[-83.512571,38.701716],[-83.762445,38.652103],[-84.212904,38.805707],[-84.445242,39.114461],[-84.744149,39.147458],[-84.888873,39.066376],[-84.816506,38.80532],[-85.448862,38.713368],[-85.415272,38.555416],[-85.816164,38.282969],[-86.042354,37.958018],[-86.33281,38.182938],[-86.634271,37.843845],[-86.810913,37.99715],[-87.065388,37.810481],[-87.402632,37.942267],[-87.666522,37.827455],[-87.921744,37.907885],[-88.158374,37.639948],[-88.063311,37.515755],[-88.450127,37.411717],[-88.490068,37.067874],[-89.058036,37.188767],[-89.171881,37.068184],[-89.202607,36.601576],[-89.343753,36.630991],[-89.429311,36.481875],[-89.55264,36.577178],[-89.527029,36.341679],[-89.703511,36.243412],[-89.615128,36.113816],[-89.733095,36.000608],[-90.368718,35.995812],[-90.075934,36.281485],[-90.157136,36.484317],[-94.617919,36.499414],[-94.605734,39.122204],[-95.082714,39.516712],[-94.876344,39.806894],[-95.382957,40.027112],[-95.870481,40.71248],[-95.929889,41.415155],[-96.096186,41.547192],[-96.077543,41.777824],[-96.628741,42.757532],[-96.448134,43.104452],[-96.598396,43.495074],[-96.453049,43.500415],[-96.452948,45.268925],[-96.835451,45.586129],[-96.587093,45.816445],[-96.559271,46.058272],[-96.789572,46.639079],[-96.851293,47.589264],[-97.139497,48.153108],[-97.108655,48.691484],[-97.238387,48.982631],[-95.153711,48.998903],[-95.153314,49.384358],[-94.974286,49.367738],[-94.555835,48.716207],[-93.741843,48.517347],[-92.984963,48.623731],[-92.634931,48.542873],[-92.698824,48.494892],[-92.341207,48.23248],[-92.066269,48.359602],[-91.542512,48.053268],[-90.88548,48.245784],[-90.703702,48.096009],[-89.489226,48.014528],[-90.86827,47.5569],[-92.058888,46.809938],[-91.942988,46.679939],[-90.880358,46.957661],[-90.78804,46.844886],[-90.920813,46.637432],[-90.398478,46.575832],[-88.982483,46.99883],[-88.400224,47.379551],[-87.816958,47.471998],[-87.730804,47.449112],[-88.349952,47.076377],[-88.462349,46.786711],[-88.167373,46.9588],[-87.915943,46.909508],[-87.619747,46.79821],[-87.366767,46.507303],[-86.850111,46.434114],[-86.188024,46.654008],[-84.964652,46.772845],[-84.969464,46.47629],[-84.177428,46.52692],[-84.097766,46.256512],[-84.247687,46.17989],[-83.931175,46.017871],[-83.63498,46.103953],[-83.49484,45.999541],[-84.345451,45.946569],[-84.656567,46.052654],[-84.820557,45.868293],[-85.047028,46.020603],[-85.528403,46.087121],[-85.663966,45.967013],[-86.278007,45.942057],[-86.687208,45.634253],[-86.532989,45.882665],[-86.92106,45.697868],[-87.018902,45.838886],[-88.027103,44.578992],[-87.943801,44.529693],[-87.428144,44.890738],[-87.021088,45.296541],[-87.73063,43.893862],[-87.910172,43.236634],[-87.800477,42.49192]]],[[[-88.684434,48.115785],[-88.447236,48.182916],[-89.022736,47.858532],[-89.255202,47.876102],[-88.684434,48.115785]]],[[[-86.880572,45.331467],[-86.956192,45.351179],[-86.82177,45.427602],[-86.880572,45.331467]]]]},\"properties\":{\"name\":\"Iowa\",\"nation\":\"USA  \"}}]}","volume":"125","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Delaney, John T. 0000-0003-1038-0265","orcid":"https://orcid.org/0000-0003-1038-0265","contributorId":255630,"corporation":false,"usgs":true,"family":"Delaney","given":"John","middleInitial":"T.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":812688,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bouska, Kristen L. 0000-0002-4115-2313 kbouska@usgs.gov","orcid":"https://orcid.org/0000-0002-4115-2313","contributorId":178005,"corporation":false,"usgs":true,"family":"Bouska","given":"Kristen","email":"kbouska@usgs.gov","middleInitial":"L.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":812689,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Eash, Josh D.","contributorId":193103,"corporation":false,"usgs":false,"family":"Eash","given":"Josh","email":"","middleInitial":"D.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":true,"id":812690,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Heglund, Patricia J.","contributorId":149499,"corporation":false,"usgs":false,"family":"Heglund","given":"Patricia","email":"","middleInitial":"J.","affiliations":[{"id":17755,"text":"U.S. Fish and Wildlife Service, Upper Midwest Environmental Sciences Center","active":true,"usgs":false}],"preferred":false,"id":812691,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Allstadt, Andrew A","contributorId":255631,"corporation":false,"usgs":false,"family":"Allstadt","given":"Andrew","email":"","middleInitial":"A","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":812692,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70241493,"text":"70241493 - 2021 - Scalability and performance tradeoffs in quantifying relationships between elevation and tidal wetland plant communities","interactions":[],"lastModifiedDate":"2023-03-22T11:38:40.872953","indexId":"70241493","displayToPublicDate":"2021-03-22T06:33:27","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":13621,"text":"Marine Progress Series","active":true,"publicationSubtype":{"id":10}},"title":"Scalability and performance tradeoffs in quantifying relationships between elevation and tidal wetland plant communities","docAbstract":"<p class=\"abstract_block\">Elevation is a major driver of plant ecology and sediment dynamics in tidal wetlands, so accurate and precise spatial data are essential for assessing wetland vulnerability to sea-level rise and making forecasts. We performed survey-grade elevation and vegetation surveys of the Global Change Research Wetland, a brackish microtidal wetland in the Chesapeake Bay estuary, Maryland (USA), to both intercompare unbiased digital elevation model (DEM) creation techniques and to describe niche partitioning of several common tidal wetland plant species. We identified a tradeoff between scalability and performance in creating unbiased DEMs, with more data-intensive methods such as kriging performing better than 3 more scalable methods involving post-processing of light detection and ranging (LiDAR)-based DEMs. The LiDAR Elevation Correction with Normalized Difference Vegetation Index (LEAN) method provided a compromise between scalability and performance, although it underpredicted variability in elevation. In areas where native plants dominated, the sedge<span>&nbsp;</span><i>Schoenoplectus americanus</i><span>&nbsp;</span>occupied more frequently flooded areas (median: 0.22, 95% range: 0.09 to 0.31 m relative to North America Vertical Datum of 1988 [NAVD88]) and the grass<span>&nbsp;</span><i>Spartina patens</i>, less frequently flooded (0.27, 0.1 to 0.35 m NAVD88). Non-native<span>&nbsp;</span><i>Phragmites australis</i><span>&nbsp;</span>dominated at lower elevations more than the native graminoids, but had a wide flooding tolerance, encompassing both their ranges (0.19, -0.05 to 0.36 m NAVD88). The native shrub<span>&nbsp;</span><i>Iva frutescens</i><span>&nbsp;</span>also dominated at lower elevations (0.20, 0.04 to 0.30 m NAVD88), despite being previously described as a high marsh species. These analyses not only provide valuable context for the temporally rich but spatially restricted data collected at a single well-studied site, but also provide broad insight into mapping techniques and species zonation.</p>","language":"English","publisher":"Inter-Research Science Publisher","doi":"10.3354/meps13683","usgsCitation":"Holmquist, J., Schile-Beers, L., Buffington, K., Lu, M., Mozdzer, T.J., Riera, J., Weller, D.E., Williams, M., and Megonigal, J., 2021, Scalability and performance tradeoffs in quantifying relationships between elevation and tidal wetland plant communities: Marine Progress Series, v. 666, p. 57-72, https://doi.org/10.3354/meps13683.","productDescription":"16 p.","startPage":"57","endPage":"72","ipdsId":"IP-127317","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":452993,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/meps13683","text":"Publisher 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,{"id":70219519,"text":"70219519 - 2021 - A roadmap for sampling and scaling biological nitrogen fixation in terrestrial ecosystems","interactions":[],"lastModifiedDate":"2021-06-30T18:00:05.022669","indexId":"70219519","displayToPublicDate":"2021-03-21T08:48:19","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2717,"text":"Methods in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"A roadmap for sampling and scaling biological nitrogen fixation in terrestrial ecosystems","docAbstract":"<ol class=\"\"><li>Accurately quantifying rates and patterns of biological nitrogen fixation (BNF) in terrestrial ecosystems is essential to characterize ecological and biogeochemical interactions, identify mechanistic controls, improve BNF representation in conceptual and numerical modelling, and forecast nitrogen limitation constraints on future carbon (C) cycling.</li><li>While many resources address the technical advantages and limitations of different methods for measuring BNF, less systematic consideration has been given to the broader decisions involved in planning studies, interpreting data, and extrapolating results. Here, we present a conceptual and practical road map to study design, study execution, data analysis and scaling, outlining key considerations at each step.</li><li>We address issues including defining N‐fixing niches of interest, identifying important sources of temporal and spatial heterogeneity, designing a sampling scheme (including method selection, measurement conditions, replication, and consideration of hotspots and hot moments), and approaches to analysing, scaling and reporting BNF. We also review the comparability of estimates derived using different approaches in the literature, and provide sample R code for simulating symbiotic BNF data frames and upscaling.</li><li>Improving and standardizing study design at each of these stages will improve the accuracy and interpretability of data, define limits of extrapolation, and facilitate broader use of BNF data for downstream applications. We highlight aspects—such as quantifying scales of heterogeneity, statistical approaches for dealing with non‐normality, and consideration of rates versus ecological significance—that are ripe for further development.</li></ol>","language":"English","publisher":"British Ecological Society","doi":"10.1111/2041-210X.13586","usgsCitation":"Soper, F.M., Taylor, B., Winbourne, J., Wong, M., Dynarski, K.A., Reis, C., Peoples, M., Cleveland, C., Reed, S., Menge, D., and Perakis, S.S., 2021, A roadmap for sampling and scaling biological nitrogen fixation in terrestrial ecosystems: Methods in Ecology and Evolution, v. 12, no. 6, p. 1122-1137, https://doi.org/10.1111/2041-210X.13586.","productDescription":"16 p.","startPage":"1122","endPage":"1137","ipdsId":"IP-123011","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":452995,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/2041-210x.13586","text":"Publisher Index Page"},{"id":385009,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","issue":"6","noUsgsAuthors":false,"publicationDate":"2021-03-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Soper, Fiona M.","contributorId":207085,"corporation":false,"usgs":false,"family":"Soper","given":"Fiona","email":"","middleInitial":"M.","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":813907,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Taylor, Benton 0000-0002-9834-9192","orcid":"https://orcid.org/0000-0002-9834-9192","contributorId":245071,"corporation":false,"usgs":false,"family":"Taylor","given":"Benton","email":"","affiliations":[{"id":49081,"text":"Smithsonian Environmental Research Center, Edgewater, MD, 21037 USA","active":true,"usgs":false}],"preferred":false,"id":813908,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Winbourne, Joy","contributorId":257256,"corporation":false,"usgs":false,"family":"Winbourne","given":"Joy","email":"","affiliations":[{"id":51994,"text":"Boston U","active":true,"usgs":false}],"preferred":false,"id":813909,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wong, Michelle","contributorId":257257,"corporation":false,"usgs":false,"family":"Wong","given":"Michelle","email":"","affiliations":[{"id":51995,"text":"Cary Inst","active":true,"usgs":false}],"preferred":false,"id":813911,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dynarski, Katherine A 0000-0001-5101-9666","orcid":"https://orcid.org/0000-0001-5101-9666","contributorId":225403,"corporation":false,"usgs":false,"family":"Dynarski","given":"Katherine","email":"","middleInitial":"A","affiliations":[{"id":12711,"text":"UC Davis","active":true,"usgs":false}],"preferred":false,"id":813910,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Reis, Carla R. G.","contributorId":240660,"corporation":false,"usgs":false,"family":"Reis","given":"Carla R. G.","affiliations":[{"id":48124,"text":"Center for Earth System Science, National Institute for Space Research (INPE), Av. dos Astronautas 1758, São José dos Campos, São Paulo 12227-010, Brazil","active":true,"usgs":false}],"preferred":false,"id":813912,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Peoples, Mark","contributorId":257258,"corporation":false,"usgs":false,"family":"Peoples","given":"Mark","email":"","affiliations":[{"id":36909,"text":"CSIRO","active":true,"usgs":false}],"preferred":false,"id":813913,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Cleveland, Cory","contributorId":257259,"corporation":false,"usgs":false,"family":"Cleveland","given":"Cory","affiliations":[{"id":48908,"text":"U Montana","active":true,"usgs":false}],"preferred":false,"id":813914,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Reed, Sasha C. 0000-0002-8597-8619","orcid":"https://orcid.org/0000-0002-8597-8619","contributorId":205372,"corporation":false,"usgs":true,"family":"Reed","given":"Sasha C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":813915,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Menge, Duncan 0000-0003-4736-9844","orcid":"https://orcid.org/0000-0003-4736-9844","contributorId":241126,"corporation":false,"usgs":false,"family":"Menge","given":"Duncan","email":"","affiliations":[{"id":7171,"text":"Columbia University","active":true,"usgs":false}],"preferred":false,"id":813916,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Perakis, Steven S. 0000-0003-0703-9314 sperakis@usgs.gov","orcid":"https://orcid.org/0000-0003-0703-9314","contributorId":145528,"corporation":false,"usgs":true,"family":"Perakis","given":"Steven","email":"sperakis@usgs.gov","middleInitial":"S.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":813917,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70224589,"text":"70224589 - 2021 - SFRmaker and Linesink-Maker: Rapid construction of streamflow routing networks from hydrography data","interactions":[],"lastModifiedDate":"2021-09-29T12:25:14.233179","indexId":"70224589","displayToPublicDate":"2021-03-21T07:21:40","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3825,"text":"Groundwater","active":true,"publicationSubtype":{"id":10}},"title":"SFRmaker and Linesink-Maker: Rapid construction of streamflow routing networks from hydrography data","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Groundwater models have evolved to encompass more aspects of the water cycle, but the incorporation of realistic boundary conditions representing surface water remains time-consuming and error-prone. We present two Python packages that robustly automate this process using readily available hydrography data as the primary input. SFRmaker creates input for the MODFLOW SFR package, while Linesink-maker creates linesink string input for the GFLOW analytic element program. These programs can reduce weeks or even months of manual effort to a few minutes of execution time, and carry the added advantages of reduced potential for error, improved reproducibility and facilitation of step-wise modeling through reduced dependency on a particular conceptual model or discretization. Two real-world examples at the county to multi-state scales are presented.</p></div></div>","language":"English","publisher":"The National Groundwater Association","doi":"10.1111/gwat.13095","usgsCitation":"Leaf, A.T., Fienen, M., and Reeves, H.W., 2021, SFRmaker and Linesink-Maker: Rapid construction of streamflow routing networks from hydrography data: Groundwater, v. 59, no. 5, p. 761-771, https://doi.org/10.1111/gwat.13095.","productDescription":"11 p.","startPage":"761","endPage":"771","ipdsId":"IP-122353","costCenters":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true},{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":452999,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/gwat.13095","text":"Publisher Index Page"},{"id":436450,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9U2T031","text":"USGS data release","linkHelpText":"SFRmaker"},{"id":436449,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P99QSDDX","text":"USGS data release","linkHelpText":"Linesink-maker"},{"id":389941,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"59","issue":"5","noUsgsAuthors":false,"publicationDate":"2021-04-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Leaf, Andrew T. 0000-0001-8784-4924 aleaf@usgs.gov","orcid":"https://orcid.org/0000-0001-8784-4924","contributorId":5156,"corporation":false,"usgs":true,"family":"Leaf","given":"Andrew","email":"aleaf@usgs.gov","middleInitial":"T.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":824219,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fienen, Michael N. 0000-0002-7756-4651","orcid":"https://orcid.org/0000-0002-7756-4651","contributorId":245632,"corporation":false,"usgs":true,"family":"Fienen","given":"Michael N.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":824220,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reeves, Howard W. 0000-0001-8057-2081 hwreeves@usgs.gov","orcid":"https://orcid.org/0000-0001-8057-2081","contributorId":2307,"corporation":false,"usgs":true,"family":"Reeves","given":"Howard","email":"hwreeves@usgs.gov","middleInitial":"W.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":824221,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70146231,"text":"sir20135225 - 2021 - Simulation of groundwater flow in the aquifer system of the Anacostia River and surrounding watersheds, Washington, D.C., Maryland, and Virginia","interactions":[],"lastModifiedDate":"2021-03-22T11:45:33.624013","indexId":"sir20135225","displayToPublicDate":"2021-03-19T13:45:00","publicationYear":"2021","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":"2013-5225","displayTitle":"Simulation of Groundwater Flow in the Aquifer System of the Anacostia River and Surrounding Watersheds, Washington, D.C., Maryland, and Virginia","title":"Simulation of groundwater flow in the aquifer system of the Anacostia River and surrounding watersheds, Washington, D.C., Maryland, and Virginia","docAbstract":"<p>The U.S. Geological Survey, in cooperation with the District Department of Energy &amp; Environment, Water Quality Division, is investigating the hydrogeology of the tidal Anacostia River watershed within Washington, D.C., with the goal of improving understanding of the groundwater-flow system and the interaction of groundwater and surface water in the watershed. To help meet this goal, a three-dimensional steady-state groundwater-flow model for the Anacostia River and surrounding watersheds in Washington, D.C., Maryland, and Virginia was constructed. The goal of the modeling study was to quantify the rate and pattern of groundwater flow to the tidal Anacostia River. The model domain includes weathered and unweathered rocks of the Piedmont Physiographic Province and the southeast-dipping sediments of the Atlantic Coastal Plain Physiographic Province. The model includes processes of recharge, evapotranspiration, withdrawals from wells, and base flow to streams, rivers, and tidal waters. Final model calibration was achieved by using the objective parameter estimation and sensitivity analysis capabilities of UCODE_2005. Simulated gradients in the surficial aquifer in the vicinity of the tidal Anacostia River indicate that flow is predominantly toward the river, with changes in the magnitude and direction of the gradients from the northeast, where the Anacostia River enters Washington, D.C., to the southwest, toward the confluence with the tidal Potomac River. Flow paths to the tidal Anacostia River from the north are largely horizontal through the surficial aquifer and Patuxent aquifer. From the south, the flow paths toward the river originate in the elevated topographic areas southeast of the river and pass through the surficial aquifer and Patapsco confining unit, lower Patapsco aquifer/Arundel Clay, and to some extent, the Patuxent aquifer. Groundwater-flow rates to and from the tidal rivers (Potomac and Anacostia) are generally greatest near the land-water boundary, where the gradient in the water table is greatest, and diminish toward the middle of the tidal river channels. The tidal rivers are predominantly areas of groundwater discharge, although there are areas where tidal waters are recharging the subsurface, typically where small variations or depressions in the topography produce small locally reversed gradients in the water table. Substantial recharge of tidal waters to the groundwater system is observed for the tidal Potomac where the upper Patapsco aquifer subcrops south of Washington, D.C. Water budget calculations indicate that inflows to the groundwater system beneath the tidal Anacostia River are predominantly from the land area of Washington, D.C., followed by tidal surface water and flows from lower layers. Outflows are largely to the tidal Anacostia River, with a smaller part going to the land area underlying Washington, D.C.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135225","usgsCitation":"Raffensperger, J.P., Voronin, L.M., and Dieter, C.A., 2021, Simulation of groundwater flow in the aquifer system of the Anacostia River and surrounding watersheds, Washington, D.C., Maryland, and Virginia: U.S. Geological Survey Scientific Investigations Report 2013–5225, 59 p., https://doi.org/10.3133/sir20135225.","productDescription":"vii, 59 p.","numberOfPages":"59","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-051429","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":41514,"text":"Maryland-Delaware-District of Columbia  Water Science Center","active":true,"usgs":true}],"links":[{"id":384505,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2013/5225/coverthb.jpg"},{"id":384506,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5225/sir20135225.pdf","text":"Report","size":"8.29 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2013-5225"}],"country":"United States","state":"Delaware, Maryland, Washington D.C.","otherGeospatial":"Anacostia River and surrounding watersheds","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -77.70355224609375,\n              38.89958342598271\n            ],\n            [\n              -76.44287109375,\n              38.1777509666256\n            ],\n            [\n              -75.498046875,\n              39.14710270770074\n            ],\n            [\n              -76.72027587890625,\n              39.715638134796336\n            ],\n            [\n              -77.70355224609375,\n              38.89958342598271\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/md-de-dc-water\" data-mce-href=\"https://www.usgs.gov/centers/md-de-dc-water\">Maryland-Delaware-D.C. Water Science Center</a><br>U.S. Geological Survey<br>5522 Research Park Drive<br>Catonsville, MD 21228</p><p><a href=\"https://pubs.er.usgs.gov/contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Hydrogeologic Framework</li><li>Groundwater-Flow-Model Development</li><li>Model Calibration and Sensitivity Analysis Approach</li><li>Model Evaluation</li><li>Model Limitations and Suggestions for Additional Work</li><li>Summary and Conclusions</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"publishedDate":"2021-03-19","noUsgsAuthors":false,"publicationDate":"2021-03-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Raffensperger, Jeff P. 0000-0001-9275-6646 jpraffen@usgs.gov","orcid":"https://orcid.org/0000-0001-9275-6646","contributorId":140239,"corporation":false,"usgs":true,"family":"Raffensperger","given":"Jeff P.","email":"jpraffen@usgs.gov","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia  Water Science Center","active":true,"usgs":true}],"preferred":false,"id":544870,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Voronin, Lois M. 0000-0002-1064-1675 lvoronin@usgs.gov","orcid":"https://orcid.org/0000-0002-1064-1675","contributorId":1475,"corporation":false,"usgs":true,"family":"Voronin","given":"Lois","email":"lvoronin@usgs.gov","middleInitial":"M.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":544871,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dieter, Cheryl A. 0000-0002-5786-4091 cadieter@usgs.gov","orcid":"https://orcid.org/0000-0002-5786-4091","contributorId":2058,"corporation":false,"usgs":true,"family":"Dieter","given":"Cheryl","email":"cadieter@usgs.gov","middleInitial":"A.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia  Water Science Center","active":true,"usgs":true}],"preferred":true,"id":544872,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70219037,"text":"ofr20211023 - 2021 - Black abalone surveys at Naval Base Ventura County, San Nicolas Island, California—2020, annual report","interactions":[],"lastModifiedDate":"2021-03-19T22:20:55.486396","indexId":"ofr20211023","displayToPublicDate":"2021-03-19T13:42:37","publicationYear":"2021","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":"2021-1023","displayTitle":"Black Abalone Surveys at Naval Base Ventura County, San Nicolas Island, California: 2020, Annual Report","title":"Black abalone surveys at Naval Base Ventura County, San Nicolas Island, California—2020, annual report","docAbstract":"<p>The U.S. Geological Survey monitors a suite of intertidal black abalone sites at San Nicolas Island, California, in cooperation with the U.S. Navy, which owns the island. The nine rocky intertidal sites were established in 1980 to study the potential impact of translocated sea otters on the intertidal black abalone population at the island. The sites were monitored from 1981 to 1997, usually annually or biennially. Monitoring resumed in 2001 and has been completed annually since then. At the time of this report, the work is conducted by the Western Ecological Research Center’s Santa Cruz Field Station, Santa Cruz, California. The study sites became particularly important, from a management perspective, after a virulent disease decimated black abalone populations throughout southern California beginning in the mid-1980s. The disease, withering syndrome, was first observed on San Nicolas Island in 1992 and during the next few years, it reduced the population there by more than 99 percent. The species was subsequently listed as endangered under the Endangered Species Act in 2009.</p><p>The subject of this report is the 2020 monitoring cycle of the sites and how the current status fits into the long-term data at San Nicolas Island. Since 2001, the monitored population has increased twelvefold to approximately 9.6 percent of the pre-disease level. This increase has resulted from generally higher levels of recruitment than seen in the first two decades of monitoring, punctuated by a few unexplained high recruitment events. Most of the population growth has been at two of the nine sites (sites 7 and 8). This pattern continued in 2020, but with increasing numbers at all sites and the highest number of abalone counted and measured island-wide since 1993. Recruitment rates have fallen since a peak in 2017, but 2020 continued to show moderate levels of additional recruitment. The distance between adjacent black abalone has decreased substantially since it was first consistently measured in 2005, potentially indicating that the abalone are close enough to one another to reproduce successfully. Sand burial can have devastating localized consequences to black abalone, but there is evidence suggesting that they may be able to escape periodic sand inundation if suitable refugia exist. These data suggest that monitoring can inform adaptive management of the resource by base resource managers.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211023","collaboration":"Prepared in cooperation with the U.S. Navy","usgsCitation":"Kenner, M.C., 2021, Black abalone surveys at Naval Base Ventura County, San Nicolas Island, California—2020, annual report: U.S. Geological Survey Open-File Report 2021–1023, 33 p., https://doi.org/10.3133/ofr20211023.","productDescription":"vii, 33 p.","numberOfPages":"33","onlineOnly":"Y","ipdsId":"IP-125069","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":384507,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1023/covrthb.jpg"},{"id":384508,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1023/ofr20211023.pdf","text":"Report","size":"5 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":384509,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1023/ofr20211023.xml"},{"id":384510,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1023/images"}],"country":"United States","state":"California","otherGeospatial":"San Nicolas Island","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -119.59442138671875,\n              33.20996748987798\n            ],\n            [\n              -119.42928314208984,\n              33.20996748987798\n            ],\n            [\n              -119.42928314208984,\n              33.28806392819752\n            ],\n            [\n              -119.59442138671875,\n              33.28806392819752\n            ],\n            [\n              -119.59442138671875,\n              33.20996748987798\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director,<br><a href=\"https://www.usgs.gov/%20centers/%20werc\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/ centers/ werc\">Western Ecological Research Center</a><br><a href=\"https://usgs.gov/\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://usgs.gov\">U.S. Geological Survey</a><br>3020 State University Drive East<br>Sacramento, California 95819</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Methods</li><li>Sites</li><li>Results</li><li>Discussion and Conclusions</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2021-03-19","noUsgsAuthors":false,"publicationDate":"2021-03-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Kenner, Michael C. 0000-0003-4659-461X","orcid":"https://orcid.org/0000-0003-4659-461X","contributorId":208151,"corporation":false,"usgs":true,"family":"Kenner","given":"Michael","email":"","middleInitial":"C.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":812526,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70223703,"text":"70223703 - 2021 - The 2018 update of the US National Seismic Hazard Model: Ground motion models in the central and eastern US","interactions":[],"lastModifiedDate":"2021-09-02T12:58:27.982991","indexId":"70223703","displayToPublicDate":"2021-03-19T07:56:09","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1436,"text":"Earthquake Spectra","active":true,"publicationSubtype":{"id":10}},"title":"The 2018 update of the US National Seismic Hazard Model: Ground motion models in the central and eastern US","docAbstract":"<p><span>The United States Geological Survey (USGS) National Seismic Hazard Model (NSHM) is the scientific foundation of seismic design regulations in the United States and is regularly updated to consider the best available science and data. The 2018 update of the conterminous US NSHM includes major changes to the underlying ground motion models (GMMs). Most of the changes are motivated by the new multi-period response spectra requirements of seismic design regulations that use hazard results for 22 spectral periods and 8 site classes. In the central and eastern United States (CEUS), the 2018 NSHM incorporates 31 new GMMs for hard-rock site conditions&nbsp;</span><span class=\"equationTd\"><span id=\"MathJax-Element-1-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot; display=&quot;inline&quot; id=&quot;math1-8755293021993837&quot; overflow=&quot;scroll&quot; altimg=&quot;eq-00001.gif&quot;><mrow><mo stretchy=&quot;false&quot;>(</mo><msub><mrow><mi>V</mi></mrow><mrow><mi>S</mi><mn>30</mn></mrow></msub><mo>=</mo><mn>3000</mn><mspace width=&quot;0.25em&quot; /><mi mathvariant=&quot;normal&quot;>m</mi><mo stretchy=&quot;false&quot;>/</mo><mi mathvariant=&quot;normal&quot;>s</mi><mo stretchy=&quot;false&quot;>)</mo></mrow></math>\"><span id=\"math1-8755293021993837\" class=\"math\"><span><span id=\"MathJax-Span-2\" class=\"mrow\"><span id=\"MathJax-Span-3\" class=\"mrow\"><span id=\"MathJax-Span-4\" class=\"mo\">(</span><span id=\"MathJax-Span-5\" class=\"msub\"><span id=\"MathJax-Span-6\" class=\"mrow\"><span id=\"MathJax-Span-7\" class=\"mi\">V</span></span><span id=\"MathJax-Span-8\" class=\"mrow\"><span id=\"MathJax-Span-9\" class=\"mi\">S</span><span id=\"MathJax-Span-10\" class=\"mn\">30</span></span></span><span id=\"MathJax-Span-11\" class=\"mo\">=</span><span id=\"MathJax-Span-12\" class=\"mn\">3000</span><span id=\"MathJax-Span-13\" class=\"mspace\"></span><span id=\"MathJax-Span-14\" class=\"mi\">m</span><span id=\"MathJax-Span-15\" class=\"mo\">/</span><span id=\"MathJax-Span-16\" class=\"mi\">s</span><span id=\"MathJax-Span-17\" class=\"mo\">)</span></span></span></span></span><span class=\"MJX_Assistive_MathML\">(VS30=3000m/s)</span></span></span><span>, including the Next Generation Attenuation (NGA)-East GMMs. New aleatory variability and site-effect models, both specific to the CEUS, are applied to all median hard-rock GMMs. This article documents the changes to the USGS GMM selection criteria and provides details on the new CEUS GMMs used in the 2018 NSHM update. The median GMMs, their weights, epistemic uncertainty, and aleatory variability are compared with those considered in prior NSHMs. This article further provides implementation details on the CEUS site-effect model, which allows conversion of hard-rock ground motions to other site conditions in the CEUS for the first time in NSHMs. Compared with the 2014 NSHM hard-rock ground motions, the weighted average of median GMMs increases for large magnitude events at middle to large distance range, epistemic uncertainty increases in almost all situations, but aleatory variability is not significantly different. Finally, the total effect on hazard is demonstrated for an assumed earthquake source model in the CEUS, which shows an increased ring of ground motions in the vicinity of the New Madrid seismic zone and decreased ground motions near the East Tennessee seismic zone.</span></p>","language":"English","publisher":"Sage Pubs","doi":"10.1177/8755293021993837","usgsCitation":"Rezaeian, S., Powers, P.M., Shumway, A., Petersen, M.D., Luco, N., Frankel, A.D., Moschetti, M.P., Thompson, E.M., and McNamara, D., 2021, The 2018 update of the US National Seismic Hazard Model: Ground motion models in the central and eastern US: Earthquake Spectra, v. 37, no. 1, p. 1354-1390, https://doi.org/10.1177/8755293021993837.","productDescription":"37 p.","startPage":"1354","endPage":"1390","ipdsId":"IP-123714","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":486985,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1177/8755293021993837","text":"Publisher Index Page"},{"id":388801,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"37","issue":"1","noUsgsAuthors":false,"publicationDate":"2021-03-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Rezaeian, Sanaz 0000-0001-7589-7893 srezaeian@usgs.gov","orcid":"https://orcid.org/0000-0001-7589-7893","contributorId":4395,"corporation":false,"usgs":true,"family":"Rezaeian","given":"Sanaz","email":"srezaeian@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":822387,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Powers, Peter M. 0000-0003-2124-6184 pmpowers@usgs.gov","orcid":"https://orcid.org/0000-0003-2124-6184","contributorId":176814,"corporation":false,"usgs":true,"family":"Powers","given":"Peter","email":"pmpowers@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":822388,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shumway, Allison M. 0000-0003-1142-7141 ashumway@usgs.gov","orcid":"https://orcid.org/0000-0003-1142-7141","contributorId":147862,"corporation":false,"usgs":true,"family":"Shumway","given":"Allison","email":"ashumway@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":822389,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Petersen, Mark D. 0000-0001-8542-3990 mpetersen@usgs.gov","orcid":"https://orcid.org/0000-0001-8542-3990","contributorId":1163,"corporation":false,"usgs":true,"family":"Petersen","given":"Mark","email":"mpetersen@usgs.gov","middleInitial":"D.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":822390,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Luco, Nico 0000-0002-5763-9847 nluco@usgs.gov","orcid":"https://orcid.org/0000-0002-5763-9847","contributorId":145730,"corporation":false,"usgs":true,"family":"Luco","given":"Nico","email":"nluco@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":822391,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Frankel, Arthur D. 0000-0001-9119-6106 afrankel@usgs.gov","orcid":"https://orcid.org/0000-0001-9119-6106","contributorId":146285,"corporation":false,"usgs":true,"family":"Frankel","given":"Arthur","email":"afrankel@usgs.gov","middleInitial":"D.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":822392,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Moschetti, Morgan P. 0000-0001-7261-0295 mmoschetti@usgs.gov","orcid":"https://orcid.org/0000-0001-7261-0295","contributorId":1662,"corporation":false,"usgs":true,"family":"Moschetti","given":"Morgan","email":"mmoschetti@usgs.gov","middleInitial":"P.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":822393,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Thompson, Eric M. 0000-0002-6943-4806 emthompson@usgs.gov","orcid":"https://orcid.org/0000-0002-6943-4806","contributorId":150897,"corporation":false,"usgs":true,"family":"Thompson","given":"Eric","email":"emthompson@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":822394,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"McNamara, Daniel 0000-0001-6860-0350","orcid":"https://orcid.org/0000-0001-6860-0350","contributorId":265165,"corporation":false,"usgs":false,"family":"McNamara","given":"Daniel","affiliations":[{"id":24583,"text":"former USGS employee","active":true,"usgs":false}],"preferred":false,"id":822395,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70219101,"text":"70219101 - 2021 - Dating fault damage along the eastern Denali fault zone with hematite (U-Th)/He thermochronometry","interactions":[],"lastModifiedDate":"2021-03-25T11:47:28.121179","indexId":"70219101","displayToPublicDate":"2021-03-19T07:19:35","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1427,"text":"Earth and Planetary Science Letters","active":true,"publicationSubtype":{"id":10}},"title":"Dating fault damage along the eastern Denali fault zone with hematite (U-Th)/He thermochronometry","docAbstract":"<p><span>Unraveling complex slip histories in fault damage zones to understand relations among deformation, hydrothermal alteration, and surface uplift remains a challenge. The dextral eastern Denali fault zone (EDFZ; southwest Yukon, Canada) bounds the Kluane Ranges and hosts a variety of fault-related rocks, including hematite fault surfaces, which have been exhumed through the brittle regime over a protracted period of geologic time. Scanning electron microscopy-based microtextural observations and hematite (U-Th)/He (hematite He) thermochronometry from these surfaces indicate multiple generations of foliated, high-aspect ratio hematite plates. Single-aliquot hematite He dates (</span><span class=\"math\"><span id=\"MathJax-Element-2-Frame\" class=\"MathJax_SVG\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mi is=&quot;true&quot;>n</mi><mo linebreak=&quot;goodbreak&quot; linebreakstyle=&quot;after&quot; is=&quot;true&quot;>=</mo><mn is=&quot;true&quot;>38</mn></math>\"><span class=\"MJX_Assistive_MathML\">n=38</span></span></span><span>) from 11 samples range from 11.5 ± 3.2 Ma (2</span><i>σ</i><span>) to 3.4 ± 2.1 Ma and exhibit moderate inter- and intrasample dispersion. A subset of dates is 15-20 Myr younger than previously published apatite (U-Th)/He dates from collocated host rocks, despite similar closure temperatures, precluding a simple ambient cooling interpretation for our hematite He data. Mixture modeling defines hematite He date populations at ∼8 Ma, ∼6 Ma, and ∼4 Ma, and when combined with microtextural observations, supports episodes of hydrothermal alteration and fault reactivation at aseismic to subseismic slip rates. There is no evidence that hematite experienced deformation- or hydrothermal fluid-related He loss. Hematite He dates overlap previously documented Kluane Ranges surface uplift and shifting dynamics of the Yakutat microplate, pinpointing fault networks and deformation processes that accommodate regional deformation in response to far-field plate boundary processes.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.epsl.2021.116872","usgsCitation":"McDermott, R.G., Ault, A.K., and Caine, J., 2021, Dating fault damage along the eastern Denali fault zone with hematite (U-Th)/He thermochronometry: Earth and Planetary Science Letters, v. 563, 116872, 11 p., https://doi.org/10.1016/j.epsl.2021.116872.","productDescription":"116872, 11 p.","ipdsId":"IP-122292","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":453016,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.epsl.2021.116872","text":"Publisher Index Page"},{"id":384629,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United  States","state":"Alaska","otherGeospatial":"Denali fault zone","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -150.732421875,\n              59.31076795603884\n            ],\n            [\n              -141.416015625,\n              59.31076795603884\n            ],\n            [\n              -141.416015625,\n              62.02152819100765\n            ],\n            [\n              -150.732421875,\n              62.02152819100765\n            ],\n            [\n              -150.732421875,\n              59.31076795603884\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"563","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"McDermott, Robert G. 0000-0002-2550-0322","orcid":"https://orcid.org/0000-0002-2550-0322","contributorId":218595,"corporation":false,"usgs":false,"family":"McDermott","given":"Robert","email":"","middleInitial":"G.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":812787,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ault, Alexis K. 0000-0001-6361-3179","orcid":"https://orcid.org/0000-0001-6361-3179","contributorId":218596,"corporation":false,"usgs":false,"family":"Ault","given":"Alexis","email":"","middleInitial":"K.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":812788,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Caine, Jonathan Saul 0000-0002-7269-6989 jscaine@usgs.gov","orcid":"https://orcid.org/0000-0002-7269-6989","contributorId":199295,"corporation":false,"usgs":true,"family":"Caine","given":"Jonathan Saul","email":"jscaine@usgs.gov","affiliations":[],"preferred":true,"id":812789,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70222613,"text":"70222613 - 2021 - A numerical study of wave-driven mean flows and setup dynamics at a coral reef-lagoon system","interactions":[],"lastModifiedDate":"2021-08-09T13:25:19.177377","indexId":"70222613","displayToPublicDate":"2021-03-18T08:22:36","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9137,"text":"Journal of Geophysical Research-Oceans","active":true,"publicationSubtype":{"id":10}},"title":"A numerical study of wave-driven mean flows and setup dynamics at a coral reef-lagoon system","docAbstract":"<div class=\"article-section__content en main\"><p>Two-dimensional mean wave-driven flow and setup dynamics were investigated at a reef-lagoon system at Ningaloo Reef, Western Australia, using the numerical wave-flow model, SWASH. Phase-resolved numerical simulations of the wave and flow fields, validated with highly detailed field observations (including &gt;10 sensors through the energetic surf zone), were used to quantify the main mechanisms that govern the mean momentum balances and resulting mean current and setup patterns, with particular attention to the role of nonlinear wave shapes. Momentum balances from the phase-resolved model indicated that onshore flows near the reef crest were primarily driven by the wave force (dominated by radiation stress gradients) due to intense breaking, whereas the flow over the reef flat and inside the lagoon and channels was primarily driven by a pressure gradient. Wave setup inside the lagoon was primarily controlled by the wave force and bottom stress. The bottom stress reduced the setup on the reef flat and inside the lagoon. Excluding the bottom stress contribution in the setup balance resulted in an over prediction of the wave-setup inside the lagoon by up to 200–370%. The bottom stress was found to be caused by the combined presence of onshore directed wave-driven currents and (nonlinear) waves. Exclusion of the bottom stress contribution from nonlinear wave shapes led to an over prediction of the setup inside the lagoon by approximately 20–40%. The inclusion of the nonlinear wave shape contribution to the bottom stress term was found to be particularly relevant in reef regions that experience a net onshore mass flux over the reef crest.</p></div>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020JC016811","usgsCitation":"Rijnsdorp, D.P., Buckley, M.L., da Silva, R., Cuttler, M., Hansen, J., Lowe, R., Green, R.H., and Storlazzi, C.D., 2021, A numerical study of wave-driven mean flows and setup dynamics at a coral reef-lagoon system: Journal of Geophysical Research-Oceans, v. 126, no. 4, e2020JC016811, 22 p., https://doi.org/10.1029/2020JC016811.","productDescription":"e2020JC016811, 22 p.","ipdsId":"IP-122175","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":453029,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2020jc016811","text":"Publisher Index Page"},{"id":387775,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"126","issue":"4","noUsgsAuthors":false,"publicationDate":"2021-04-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Rijnsdorp, Dirk P.","contributorId":261463,"corporation":false,"usgs":false,"family":"Rijnsdorp","given":"Dirk","email":"","middleInitial":"P.","affiliations":[{"id":17614,"text":"Delft University of Technology","active":true,"usgs":false}],"preferred":false,"id":820750,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Buckley, Mark L. 0000-0002-1909-4831","orcid":"https://orcid.org/0000-0002-1909-4831","contributorId":203481,"corporation":false,"usgs":true,"family":"Buckley","given":"Mark","email":"","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":820751,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"da Silva, Renan","contributorId":243607,"corporation":false,"usgs":false,"family":"da Silva","given":"Renan","affiliations":[{"id":48753,"text":"Deltares and UWA","active":true,"usgs":false}],"preferred":false,"id":820752,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cuttler, Mike","contributorId":261910,"corporation":false,"usgs":false,"family":"Cuttler","given":"Mike","email":"","affiliations":[{"id":53078,"text":"UWA","active":true,"usgs":false}],"preferred":false,"id":820753,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hansen, Jeff","contributorId":149139,"corporation":false,"usgs":false,"family":"Hansen","given":"Jeff","affiliations":[],"preferred":false,"id":820754,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lowe, Ryan","contributorId":177845,"corporation":false,"usgs":false,"family":"Lowe","given":"Ryan","affiliations":[],"preferred":false,"id":820755,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Green, Rebecca H.","contributorId":208503,"corporation":false,"usgs":false,"family":"Green","given":"Rebecca","email":"","middleInitial":"H.","affiliations":[{"id":24588,"text":"The University of Western Australia","active":true,"usgs":false}],"preferred":false,"id":820756,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Storlazzi, Curt D. 0000-0001-8057-4490","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":213610,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt","middleInitial":"D.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":820757,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70241892,"text":"70241892 - 2021 - A comparison between generalized least squares regression and top-kriging for homogeneous cross-correlated flood regions","interactions":[],"lastModifiedDate":"2023-03-30T12:08:50.610487","indexId":"70241892","displayToPublicDate":"2021-03-18T07:06:08","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1927,"text":"Hydrological Sciences Journal","active":true,"publicationSubtype":{"id":10}},"title":"A comparison between generalized least squares regression and top-kriging for homogeneous cross-correlated flood regions","docAbstract":"<div class=\"hlFld-Abstract\"><div class=\"abstractSection abstractInFull\"><p>Spatial cross-correlation among flood sequences impacts the accuracy of regional predictors. Our study investigates this impact for two regionalization procedures, generalized least squares (GLS) regression and top-kriging (TK), which deal with cross-correlation in two fundamentally different ways and therefore might be associated with different accuracy and uncertainty of predicted flood quantiles. We perform a Monte Carlo experiment based on a dataset of annual maximum flood series for 20 catchments in a hydrologically homogeneous region. Based on a log-Pearson type III parent distribution, we generate 3000 realizations of the region with different degrees of cross-correlation. For each realization, GLS and TK are applied in leave-one-out cross-validation to predict at-site flood quantiles. Our study shows that (a) TK outperforms GLS when catchment area is the only catchment descriptor used for predicting “true” population (theoretical) flood quantiles, regardless of the level of cross-correlation, and (b) GLS and TK perform similarly when multiple catchment descriptors are used.</p></div></div>","language":"English","publisher":"Taylor and Francis","doi":"10.1080/02626667.2021.1879389","usgsCitation":"Simone, P., Salinas, J.L., Stedinger, J.R., Farmer, W., Lun, D., Viglione, A., Bloschl, G., and Castellarin, A., 2021, A comparison between generalized least squares regression and top-kriging for homogeneous cross-correlated flood regions: Hydrological Sciences Journal, v. 66, no. 2, p. 565-579, https://doi.org/10.1080/02626667.2021.1879389.","productDescription":"15 p.","startPage":"565","endPage":"579","ipdsId":"IP-109767","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":453039,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/02626667.2021.1879389","text":"Publisher Index Page"},{"id":414953,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"66","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-03-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Simone, Persiano 0000-0002-9857-738X","orcid":"https://orcid.org/0000-0002-9857-738X","contributorId":303797,"corporation":false,"usgs":false,"family":"Simone","given":"Persiano","email":"","affiliations":[{"id":65911,"text":"University of Bologna","active":true,"usgs":false}],"preferred":false,"id":868114,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Salinas, Jose Luis","contributorId":303798,"corporation":false,"usgs":false,"family":"Salinas","given":"Jose","email":"","middleInitial":"Luis","affiliations":[{"id":65912,"text":"Vienna University of Technology","active":true,"usgs":false}],"preferred":false,"id":868115,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stedinger, Jery Russell","contributorId":303799,"corporation":false,"usgs":false,"family":"Stedinger","given":"Jery","email":"","middleInitial":"Russell","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":868116,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Farmer, William H. 0000-0002-2865-2196","orcid":"https://orcid.org/0000-0002-2865-2196","contributorId":223181,"corporation":false,"usgs":true,"family":"Farmer","given":"William H.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":868117,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lun, David","contributorId":303800,"corporation":false,"usgs":false,"family":"Lun","given":"David","email":"","affiliations":[{"id":65912,"text":"Vienna University of Technology","active":true,"usgs":false}],"preferred":false,"id":868118,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Viglione, Alberto","contributorId":176326,"corporation":false,"usgs":false,"family":"Viglione","given":"Alberto","email":"","affiliations":[],"preferred":false,"id":868119,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bloschl, Gunter","contributorId":303801,"corporation":false,"usgs":false,"family":"Bloschl","given":"Gunter","email":"","affiliations":[{"id":65912,"text":"Vienna University of Technology","active":true,"usgs":false}],"preferred":false,"id":868120,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Castellarin, Attilio","contributorId":138747,"corporation":false,"usgs":false,"family":"Castellarin","given":"Attilio","email":"","affiliations":[{"id":12516,"text":"Dept. DICAM, Sch of CE, U of Bol, Italy","active":true,"usgs":false}],"preferred":false,"id":868121,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70219197,"text":"70219197 - 2021 - Lava effusion rate evolution and erupted volume during the 2018 Kīlauea lower East Rift Zone eruption","interactions":[],"lastModifiedDate":"2021-03-30T11:50:15.466149","indexId":"70219197","displayToPublicDate":"2021-03-18T06:44:09","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1109,"text":"Bulletin of Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"Lava effusion rate evolution and erupted volume during the 2018 Kīlauea lower East Rift Zone eruption","docAbstract":"<p><span>The 2018 eruption on the lower East Rift Zone of Kīlauea Volcano produced one of the largest and most destructive lava flows in Hawai’i during the past 200 years. Over the course of more than 3 months, twenty-four fissures erupted, and the rate of lava effusion varied by two orders of magnitude, with significant implications for evolving flow behavior and hazards. Syn-eruptive data were collected to quantify these changes in lava effusion rate, including video of flow through channels and digital elevation models acquired using small unoccupied aircraft systems, airborne lidar, and airborne single-pass interferometric synthetic aperture radar. Topographic data through time allowed calculation of subaerial lava flow volume and time-averaged discharge rate over the course of the eruption, which we integrated with pre- and post-eruption bathymetric surveys. Repeat videos of the near-vent channel were analyzed with particle velocimetry to extract flow velocities, and these were combined with open channel flow theory to calculate a time series of instantaneous effusion rates. Results show a general increase in dense rock equivalent (DRE) effusion rate from ~7 to ~100 m</span><sup>3</sup><span>/s from early to late May for the whole flow field and ≥ 200 m</span><sup>3</sup><span>/s by mid-June after the eruption had focused at a primary vent. By the end of the eruption in August, 0.9–1.4 km</span><sup>3</sup><span>&nbsp;DRE of lava had erupted, with 0.4 km</span><sup>3</sup><span>&nbsp;deposited on land and at least 0.5 km</span><sup>3</sup><span>&nbsp;offshore. The trends in effusion rate through time reflect magmatic processes in the connected summit and rift zone system that controlled eruption rate, with resulting implications for lava flow dynamics and hazards.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s00445-021-01443-6","usgsCitation":"Dietterich, H., Diefenbach, A., Soule, S.A., Zoeller, M.H., Patrick, M.R., Major, J., and Lundgren, P., 2021, Lava effusion rate evolution and erupted volume during the 2018 Kīlauea lower East Rift Zone eruption: Bulletin of Volcanology, v. 83, no. 25, 18 p., https://doi.org/10.1007/s00445-021-01443-6.","productDescription":"18 p.","ipdsId":"IP-122554","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":488679,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://digitalcommons.uri.edu/gsofacpubs/2493","text":"External Repository"},{"id":384747,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United  States","state":"Hawaii","otherGeospatial":"Kīlauea volcano, Hawaii volcanoes National Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -155.0507354736328,\n              19.321511226817176\n            ],\n            [\n              -155.25054931640625,\n              19.369454073094243\n            ],\n            [\n              -155.35011291503906,\n              19.39082944712291\n            ],\n            [\n              -155.4242706298828,\n              19.204186382298897\n            ],\n            [\n              -155.39749145507812,\n              19.191217165341648\n            ],\n            [\n              -155.12832641601562,\n              19.2748506284423\n            ],\n            [\n              -155.0507354736328,\n              19.321511226817176\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"83","issue":"25","noUsgsAuthors":false,"publicationDate":"2021-03-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Dietterich, Hannah R. 0000-0001-7898-4343","orcid":"https://orcid.org/0000-0001-7898-4343","contributorId":212771,"corporation":false,"usgs":true,"family":"Dietterich","given":"Hannah R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":813189,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Diefenbach, Angela K. 0000-0003-0214-7818","orcid":"https://orcid.org/0000-0003-0214-7818","contributorId":204743,"corporation":false,"usgs":true,"family":"Diefenbach","given":"Angela K.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":813190,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Soule, S. Adam 0000-0002-4691-6300","orcid":"https://orcid.org/0000-0002-4691-6300","contributorId":221052,"corporation":false,"usgs":false,"family":"Soule","given":"S.","email":"","middleInitial":"Adam","affiliations":[{"id":36711,"text":"Woods Hole Oceanographic Institution","active":true,"usgs":false}],"preferred":false,"id":813191,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zoeller, Michael H. 0000-0003-4716-8567","orcid":"https://orcid.org/0000-0003-4716-8567","contributorId":214557,"corporation":false,"usgs":true,"family":"Zoeller","given":"Michael","email":"","middleInitial":"H.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":813192,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Patrick, Matthew R. 0000-0002-8042-6639 mpatrick@usgs.gov","orcid":"https://orcid.org/0000-0002-8042-6639","contributorId":2070,"corporation":false,"usgs":true,"family":"Patrick","given":"Matthew","email":"mpatrick@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":813193,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Major, J. J. 0000-0003-2449-4466","orcid":"https://orcid.org/0000-0003-2449-4466","contributorId":29461,"corporation":false,"usgs":true,"family":"Major","given":"J. J.","affiliations":[{"id":157,"text":"Cascades Volcano Observatory","active":false,"usgs":true}],"preferred":true,"id":813194,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lundgren, Paul R. 0000-0002-6771-2876","orcid":"https://orcid.org/0000-0002-6771-2876","contributorId":215622,"corporation":false,"usgs":false,"family":"Lundgren","given":"Paul","middleInitial":"R.","affiliations":[{"id":36276,"text":"JPL","active":true,"usgs":false}],"preferred":false,"id":813195,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
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