A potentiometric surface map of the South Coast aquifer near Santa Isabel, Puerto Rico, was created from data collected during a synoptic survey of groundwater levels at 55 wells from March 31 to April 17, 2014. Measured groundwater level values ranged from −22.8 to 185.4 feet above mean sea level. During the study period, cumulative rainfall of 0.65 inch was recorded in the study area. Measurements of instantaneous streamflow at 15 locations in streams and irrigation canals, and locations of irrigation ponds, provide additional information about the hydrologic setting. Results of the study indicate a cone of depression was present near the center and eastern parts of the Santa Isabel area of southern Puerto Rico, and a small, deeper cone of depression existed west of Santa Isabel and Rio Coamo. These cones of depression represent areas where the potentiometric surface was below mean sea level. The long-term persistence of such conditions could result in seawater intrusion and an increase in concentrations of total dissolved solids within the South Coast aquifer.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3455","collaboration":"Prepared in cooperation with the Puerto Rico Department of Natural and Environmental Resources","usgsCitation":"Ramos, F.A., and Santiago, A.A., 2020, Potentiometric surface and hydrologic conditions of the South Coast aquifer, Santa Isabel area, Puerto Rico, March–April, 2014: U.S. Geological Survey Scientific Investigations Map 3455, 4 p., 1 sheet, https://doi.org/10.3133/sim3455.","productDescription":"Pamphlet: vi, 4 p.; Sheet: 35.68 inches x 28.17 inches; Data Release","numberOfPages":"14","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-064406","costCenters":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":374025,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7NS0STQ","text":"USGS data release","linkHelpText":"Data and shapefiles for the potentiometric surface of the South Coast aquifer and hydrologic conditions in the Santa Isabel area, Puerto Rico, March–April 2014"},{"id":374019,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3455/coverthb.jpg"},{"id":374021,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3455/sim3455.pdf","text":"Pamphlet","size":"350 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3455 Pamphlet"},{"id":374022,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3455/sim3455_sheet.pdf","text":"Sheet 1—","size":"4.07 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3455 Sheet","linkHelpText":"Potentiometric Surface and Hydrologic Conditions of the South Coast Aquifer, Santa Isabel Area, Puerto Rico, March–April, 2014"}],"country":"United States","state":"Puerto Rico","otherGeospatial":"Santa Isabel Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -66.4779281616211,\n 17.932682319509986\n ],\n [\n -66.29854202270508,\n 17.932682319509986\n ],\n [\n -66.29854202270508,\n 18.029995361346103\n ],\n [\n -66.4779281616211,\n 18.029995361346103\n ],\n [\n -66.4779281616211,\n 17.932682319509986\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559
Nature's Notebook is a customizable program used by individual observers and Federal Government partners to document patterns in phenology—the timing of seasonal activity of plants and animals over the course of the calendar year. The USA National Phenology Network (USA-NPN) established Nature's Notebook in 2009 to create a standard approach for collecting phenology data on plants and animals across the country. Currently, about half of the data are submitted by independent backyard observers at individual sites and half are submitted by groups of participants as part of a Local Phenology Program. With support from the U.S. Geological Survey, the USA-NPN collects, organizes, and shares data on phenology. This information aids decision making, scientific discovery, and the development of a broader understanding of phenology.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20203022","issn":"","usgsCitation":"Posthumus, E.E., Miller, M.P., and Crimmins, T., 2020, Nature’s Notebook—A tool for recording the timing of seasonal activity of plants and animals: U.S. Geological Survey Fact Sheet 2020–3022, 4 p., https://doi.org/10.3133/fs20203022.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-112184","costCenters":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"links":[{"id":374070,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2020/3022/coverthb.jpg"},{"id":374068,"rank":3,"type":{"id":18,"text":"Project Site"},"url":"https://www.usanpn.org/","text":"USA National Phenology Network"},{"id":374114,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2020/3022/fs20203022.pdf","text":"Report","size":"2.89 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2020-3022"},{"id":374069,"rank":4,"type":{"id":18,"text":"Project Site"},"url":"https://www.naturesnotebook.org/","text":"Nature's Notebook"}],"country":"United States","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[-66.28243,18.51476],[-65.7713,18.42668],[-65.591,18.22803],[-65.84716,17.97591],[-66.59993,17.98182],[-67.18416,17.94655],[-67.24243,18.37446],[-67.10068,18.5206],[-66.28243,18.51476]]],[[[-155.54211,19.08348],[-155.68817,18.91619],[-155.93665,19.05939],[-155.90806,19.33888],[-156.07347,19.70294],[-156.02368,19.81422],[-155.85008,19.97729],[-155.91907,20.17395],[-155.86108,20.26721],[-155.78505,20.2487],[-155.40214,20.07975],[-155.22452,19.99302],[-155.06226,19.8591],[-154.80741,19.50871],[-154.83147,19.45328],[-155.22217,19.23972],[-155.54211,19.08348]]],[[[-156.07926,20.64397],[-156.41445,20.57241],[-156.58673,20.783],[-156.70167,20.8643],[-156.71055,20.92676],[-156.61258,21.01249],[-156.25711,20.91745],[-155.99566,20.76404],[-156.07926,20.64397]]],[[[-156.75824,21.17684],[-156.78933,21.06873],[-157.32521,21.09777],[-157.25027,21.21958],[-156.75824,21.17684]]],[[[-157.65283,21.32217],[-157.70703,21.26442],[-157.7786,21.27729],[-158.12667,21.31244],[-158.2538,21.53919],[-158.29265,21.57912],[-158.0252,21.71696],[-157.94161,21.65272],[-157.65283,21.32217]]],[[[-159.34512,21.982],[-159.46372,21.88299],[-159.80051,22.06533],[-159.74877,22.1382],[-159.5962,22.23618],[-159.36569,22.21494],[-159.34512,21.982]]],[[[-94.81758,49.38905],[-94.64,48.84],[-94.32914,48.67074],[-93.63087,48.60926],[-92.61,48.45],[-91.64,48.14],[-90.83,48.27],[-89.6,48.01],[-89.27292,48.01981],[-88.37811,48.30292],[-87.43979,47.94],[-86.46199,47.55334],[-85.65236,47.22022],[-84.87608,46.90008],[-84.77924,46.6371],[-84.54375,46.53868],[-84.6049,46.4396],[-84.3367,46.40877],[-84.14212,46.51223],[-84.09185,46.27542],[-83.89077,46.11693],[-83.61613,46.11693],[-83.46955,45.99469],[-83.59285,45.81689],[-82.55092,45.34752],[-82.33776,44.44],[-82.13764,43.57109],[-82.43,42.98],[-82.9,42.43],[-83.12,42.08],[-83.142,41.97568],[-83.02981,41.8328],[-82.69009,41.67511],[-82.43928,41.67511],[-81.27775,42.20903],[-80.24745,42.3662],[-78.93936,42.86361],[-78.92,42.965],[-79.01,43.27],[-79.17167,43.46634],[-78.72028,43.62509],[-77.73789,43.62906],[-76.82003,43.62878],[-76.5,44.01846],[-76.375,44.09631],[-75.31821,44.81645],[-74.867,45.00048],[-73.34783,45.00738],[-71.50506,45.0082],[-71.405,45.255],[-71.08482,45.30524],[-70.66,45.46],[-70.305,45.915],[-69.99997,46.69307],[-69.23722,47.44778],[-68.905,47.185],[-68.23444,47.35486],[-67.79046,47.06636],[-67.79134,45.70281],[-67.13741,45.13753],[-66.96466,44.8097],[-68.03252,44.3252],[-69.06,43.98],[-70.11617,43.68405],[-70.64548,43.09024],[-70.81489,42.8653],[-70.825,42.335],[-70.495,41.805],[-70.08,41.78],[-70.185,42.145],[-69.88497,41.92283],[-69.96503,41.63717],[-70.64,41.475],[-71.12039,41.49445],[-71.86,41.32],[-72.295,41.27],[-72.87643,41.22065],[-73.71,40.9311],[-72.24126,41.11948],[-71.945,40.93],[-73.345,40.63],[-73.982,40.628],[-73.95232,40.75075],[-74.25671,40.47351],[-73.96244,40.42763],[-74.17838,39.70926],[-74.90604,38.93954],[-74.98041,39.1964],[-75.20002,39.24845],[-75.52805,39.4985],[-75.32,38.96],[-75.07183,38.78203],[-75.05673,38.40412],[-75.37747,38.01551],[-75.94023,37.21689],[-76.03127,37.2566],[-75.72205,37.93705],[-76.23287,38.31921],[-76.35,39.15],[-76.54272,38.71762],[-76.32933,38.08326],[-76.99,38.23999],[-76.30162,37.91794],[-76.25874,36.9664],[-75.9718,36.89726],[-75.86804,36.55125],[-75.72749,35.55074],[-76.36318,34.80854],[-77.39763,34.51201],[-78.05496,33.92547],[-78.55435,33.86133],[-79.06067,33.49395],[-79.20357,33.15839],[-80.30132,32.50935],[-80.86498,32.0333],[-81.33629,31.44049],[-81.49042,30.72999],[-81.31371,30.03552],[-80.98,29.18],[-80.53558,28.47213],[-80.53,28.04],[-80.05654,26.88],[-80.08801,26.20576],[-80.13156,25.81677],[-80.38103,25.20616],[-80.68,25.08],[-81.17213,25.20126],[-81.33,25.64],[-81.71,25.87],[-82.24,26.73],[-82.70515,27.49504],[-82.85526,27.88624],[-82.65,28.55],[-82.93,29.1],[-83.70959,29.93656],[-84.1,30.09],[-85.10882,29.63615],[-85.28784,29.68612],[-85.7731,30.15261],[-86.4,30.4],[-87.53036,30.27433],[-88.41782,30.3849],[-89.18049,30.31598],[-89.59383,30.15999],[-89.41373,29.89419],[-89.43,29.48864],[-89.21767,29.29108],[-89.40823,29.15961],[-89.77928,29.30714],[-90.15463,29.11743],[-90.88022,29.14854],[-91.62678,29.677],[-92.49906,29.5523],[-93.22637,29.78375],[-93.84842,29.71363],[-94.69,29.48],[-95.60026,28.73863],[-96.59404,28.30748],[-97.14,27.83],[-97.37,27.38],[-97.38,26.69],[-97.33,26.21],[-97.14,25.87],[-97.53,25.84],[-98.24,26.06],[-99.02,26.37],[-99.3,26.84],[-99.52,27.54],[-100.11,28.11],[-100.45584,28.69612],[-100.9576,29.38071],[-101.6624,29.7793],[-102.48,29.76],[-103.11,28.97],[-103.94,29.27],[-104.45697,29.57196],[-104.70575,30.12173],[-105.03737,30.64402],[-105.63159,31.08383],[-106.1429,31.39995],[-106.50759,31.75452],[-108.24,31.75485],[-108.24194,31.34222],[-109.035,31.34194],[-111.02361,31.33472],[-113.30498,32.03914],[-114.815,32.52528],[-114.72139,32.72083],[-115.99135,32.61239],[-117.12776,32.53534],[-117.29594,33.04622],[-117.944,33.62124],[-118.4106,33.74091],[-118.51989,34.02778],[-119.081,34.078],[-119.43884,34.34848],[-120.36778,34.44711],[-120.62286,34.60855],[-120.74433,35.15686],[-121.71457,36.16153],[-122.54747,37.55176],[-122.51201,37.78339],[-122.95319,38.11371],[-123.7272,38.95166],[-123.86517,39.76699],[-124.39807,40.3132],[-124.17886,41.14202],[-124.2137,41.99964],[-124.53284,42.76599],[-124.14214,43.70838],[-124.02053,44.6159],[-123.89893,45.52341],[-124.07963,46.86475],[-124.39567,47.72017],[-124.68721,48.18443],[-124.5661,48.37971],[-123.12,48.04],[-122.58736,47.096],[-122.34,47.36],[-122.5,48.18],[-122.84,49],[-120,49],[-117.03121,49],[-116.04818,49],[-113,49],[-110.05,49],[-107.05,49],[-104.04826,48.99986],[-100.65,49],[-97.22872,49.0007],[-95.15907,49],[-95.15609,49.38425],[-94.81758,49.38905]]],[[[-153.00631,57.11584],[-154.00509,56.73468],[-154.5164,56.99275],[-154.67099,57.4612],[-153.76278,57.81657],[-153.22873,57.96897],[-152.56479,57.90143],[-152.14115,57.59106],[-153.00631,57.11584]]],[[[-165.57916,59.90999],[-166.19277,59.75444],[-166.84834,59.94141],[-167.45528,60.21307],[-166.46779,60.38417],[-165.67443,60.29361],[-165.57916,59.90999]]],[[[-171.73166,63.78252],[-171.11443,63.59219],[-170.49111,63.69498],[-169.68251,63.43112],[-168.68944,63.29751],[-168.77194,63.1886],[-169.52944,62.97693],[-170.29056,63.19444],[-170.67139,63.37582],[-171.55306,63.31779],[-171.79111,63.40585],[-171.73166,63.78252]]],[[[-155.06779,71.14778],[-154.34417,70.69641],[-153.90001,70.88999],[-152.21001,70.82999],[-152.27,70.60001],[-150.73999,70.43002],[-149.72,70.53001],[-147.61336,70.21403],[-145.68999,70.12001],[-144.92001,69.98999],[-143.58945,70.15251],[-142.07251,69.85194],[-140.98599,69.712],[-140.9925,66.00003],[-140.99777,60.3064],[-140.013,60.27684],[-139.039,60.00001],[-138.34089,59.56211],[-137.4525,58.905],[-136.47972,59.46389],[-135.47583,59.78778],[-134.945,59.27056],[-134.27111,58.86111],[-133.35555,58.41029],[-132.73042,57.69289],[-131.70781,56.55212],[-130.00778,55.91583],[-129.97999,55.285],[-130.53611,54.80275],[-131.08582,55.17891],[-131.96721,55.49778],[-132.25001,56.37],[-133.53918,57.17889],[-134.07806,58.12307],[-135.03821,58.18771],[-136.62806,58.21221],[-137.80001,58.5],[-139.86779,59.53776],[-140.82527,59.72752],[-142.57444,60.08445],[-143.95888,59.99918],[-145.92556,60.45861],[-147.11437,60.88466],[-148.22431,60.67299],[-148.01807,59.97833],[-148.57082,59.91417],[-149.72786,59.70566],[-150.60824,59.36821],[-151.71639,59.15582],[-151.85943,59.74498],[-151.40972,60.7258],[-150.34694,61.03359],[-150.62111,61.28442],[-151.89584,60.7272],[-152.57833,60.06166],[-154.01917,59.35028],[-153.28751,58.86473],[-154.23249,58.14637],[-155.30749,57.72779],[-156.30833,57.42277],[-156.5561,56.97998],[-158.11722,56.46361],[-158.43332,55.99415],[-159.60333,55.56669],[-160.28972,55.64358],[-161.22305,55.36473],[-162.23777,55.02419],[-163.06945,54.68974],[-164.78557,54.40417],[-164.94223,54.57222],[-163.84834,55.03943],[-162.87,55.34804],[-161.80417,55.89499],[-160.5636,56.00805],[-160.07056,56.41806],[-158.68444,57.01668],[-158.4611,57.21692],[-157.72277,57.57],[-157.55027,58.32833],[-157.04167,58.91888],[-158.19473,58.6158],[-158.51722,58.78778],[-159.05861,58.42419],[-159.71167,58.93139],[-159.98129,58.57255],[-160.35527,59.07112],[-161.355,58.67084],[-161.96889,58.67166],[-162.05499,59.26693],[-161.87417,59.63362],[-162.51806,59.98972],[-163.81834,59.79806],[-164.66222,60.26748],[-165.34639,60.5075],[-165.35083,61.0739],[-166.12138,61.50002],[-165.73445,62.075],[-164.91918,62.63308],[-164.56251,63.14638],[-163.75333,63.21945],[-163.06722,63.05946],[-162.26056,63.54194],[-161.53445,63.45582],[-160.77251,63.76611],[-160.95834,64.2228],[-161.51807,64.40279],[-160.77778,64.7886],[-161.39193,64.77724],[-162.45305,64.55944],[-162.75779,64.33861],[-163.54639,64.55916],[-164.96083,64.44695],[-166.42529,64.68667],[-166.845,65.0889],[-168.11056,65.67],[-166.70527,66.08832],[-164.47471,66.57666],[-163.65251,66.57666],[-163.7886,66.07721],[-161.67777,66.11612],[-162.48971,66.73557],[-163.71972,67.11639],[-164.43099,67.61634],[-165.39029,68.04277],[-166.76444,68.35888],[-166.20471,68.88303],[-164.43081,68.91554],[-163.16861,69.37111],[-162.93057,69.85806],[-161.9089,70.33333],[-160.9348,70.44769],[-159.03918,70.89164],[-158.11972,70.82472],[-156.58082,71.35776],[-155.06779,71.14778]]]]},\"properties\":{\"name\":\"United States\"}}]}","contact":"Office of the Associate Director, Ecosystems Mission Area
U.S Geological Survey
Mail Stop 300
12201 Sunrise Valley Drive
Reston, VA 20192
Near-field remote sensing of surface velocity and river discharge (discharge) were measured using coherent, continuous wave Doppler and pulsed radars. Traditional streamgaging requires sensors be deployed in the water column; however, near-field remote sensing has the potential to transform streamgaging operations through non-contact methods in the U.S. Geological Survey (USGS) and other agencies around the world. To differentiate from satellite or high-altitude platforms, near-field remote sensing is conducted from fixed platforms such as bridges and cable stays. Radar gages were collocated with 10 USGS streamgages in river reaches of varying hydrologic and hydraulic characteristics, where basin size ranged from 381 to 66,200 square kilometers. Radar-derived mean-channel (mean) velocity and discharge were computed using the probability concept and were compared to conventional instantaneous measurements and time series. To test the efficacy of near-field methods, radars were deployed for extended periods of time to capture a range of hydraulic conditions and environmental factors. During the operational phase, continuous time series of surface velocity, radar-derived discharge, and stage-discharge were recorded, computed, and transmitted contemporaneously and continuously in real time every 5 to 15 min. Minimum and maximum surface velocities ranged from 0.30 to 3.84 m per second (m/s); minimum and maximum radar-derived discharges ranged from 0.17 to 4890 cubic meters per second (m3/s); and minimum and maximum stage-discharge ranged from 0.12 to 4950 m3/s. Comparisons between radar and stage-discharge time series were evaluated using goodness-of-fit statistics, which provided a measure of the utility of the probability concept to compute discharge from a singular surface velocity and cross-sectional area relative to conventional methods. Mean velocity and discharge data indicate that velocity radars are highly correlated with conventional methods and are a viable near-field remote sensing technology that can be operationalized to deliver real-time surface velocity, mean velocity, and discharge.
","language":"English","publisher":"MDPI","doi":"10.3390/rs12081296","usgsCitation":"Fulton, J.W., Mason, C.A., Eggleston, J., Nicotra, M.J., Chiu, C., Henneberg, M.F., Best, H., Cederberg, J., Holnbeck, S.R., Lotspeich, R.R., Laveau, C., Moramarco, T., Jones, M.E., Gourley, J.J., and Wasielewski, D., 2020, Near-field remote sensing of surface velocity and river discharge using radars and the probability concept at 10 USGS streamgages: Remote Sensing, v. 12, no. 8, 1296, 28 p., https://doi.org/10.3390/rs12081296.","productDescription":"1296, 28 p.","ipdsId":"IP-116229","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":457013,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs12081296","text":"Publisher Index Page"},{"id":437020,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P98DC3DX","text":"USGS data release","linkHelpText":"Radar-based field measurements of surface velocity and discharge from 10 U.S. Geological Survey streamgages for various locations in the United States, 2002-19"},{"id":376065,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska, Colorado, Montana, New Mexico, North Dakota, Pennsylvania, Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -150.41793823242188,\n 64.67385671931967\n ],\n [\n -149.35501098632812,\n 64.67385671931967\n ],\n [\n -149.35501098632812,\n 64.95204645155167\n ],\n [\n -150.41793823242188,\n 64.95204645155167\n ],\n [\n -150.41793823242188,\n 64.67385671931967\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.93062591552734,\n 46.82590547324064\n ],\n [\n -113.84136199951172,\n 46.82590547324064\n ],\n [\n -113.84136199951172,\n 46.90055413151483\n ],\n [\n -113.93062591552734,\n 46.90055413151483\n ],\n [\n -113.93062591552734,\n 46.82590547324064\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.94003295898438,\n 39.65116946667103\n ],\n [\n -104.842529296875,\n 39.65116946667103\n ],\n [\n -104.842529296875,\n 39.733594087452055\n ],\n [\n -104.94003295898438,\n 39.733594087452055\n ],\n [\n -104.94003295898438,\n 39.65116946667103\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.63448905944824,\n 39.76263058076128\n ],\n [\n -105.611572265625,\n 39.76263058076128\n ],\n [\n -105.611572265625,\n 39.76639123109648\n ],\n [\n -105.63448905944824,\n 39.76639123109648\n ],\n [\n -105.63448905944824,\n 39.76263058076128\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.78662109375,\n 39.01224812224337\n ],\n [\n -108.25035095214844,\n 39.01224812224337\n ],\n [\n -108.25035095214844,\n 39.17957847932612\n ],\n [\n -108.78662109375,\n 39.17957847932612\n ],\n [\n -108.78662109375,\n 39.01224812224337\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -78.44650268554688,\n 38.896911474229526\n ],\n [\n -78.24806213378905,\n 38.896911474229526\n ],\n [\n -78.24806213378905,\n 39.01891695025239\n ],\n [\n -78.44650268554688,\n 39.01891695025239\n ],\n [\n -78.44650268554688,\n 38.896911474229526\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.13768005371092,\n 47.84035330156615\n ],\n [\n -96.92550659179688,\n 47.84035330156615\n ],\n [\n -96.92550659179688,\n 48.045955739960114\n ],\n [\n -97.13768005371092,\n 48.045955739960114\n ],\n [\n -97.13768005371092,\n 47.84035330156615\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.02664947509764,\n 36.106259853657704\n ],\n [\n -105.89378356933592,\n 36.106259853657704\n ],\n [\n -105.89378356933592,\n 36.23208902824811\n ],\n [\n -106.02664947509764,\n 36.23208902824811\n ],\n [\n -106.02664947509764,\n 36.106259853657704\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.54930114746094,\n 40.93063397096323\n ],\n [\n -76.35910034179688,\n 40.93063397096323\n ],\n [\n -76.35910034179688,\n 41.03171529379291\n ],\n [\n -76.54930114746094,\n 41.03171529379291\n ],\n [\n -76.54930114746094,\n 40.93063397096323\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.59146881103516,\n 45.58713413436411\n ],\n [\n -110.51525115966797,\n 45.58713413436411\n ],\n [\n -110.51525115966797,\n 45.685556521874766\n ],\n [\n -110.59146881103516,\n 45.685556521874766\n ],\n [\n -110.59146881103516,\n 45.58713413436411\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"12","issue":"8","noUsgsAuthors":false,"publicationDate":"2020-04-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Fulton, John W, 0000-0002-5335-0720","orcid":"https://orcid.org/0000-0002-5335-0720","contributorId":213630,"corporation":false,"usgs":true,"family":"Fulton","given":"John","middleInitial":"W,","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":791965,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mason, Christopher A. 0000-0001-9001-8244","orcid":"https://orcid.org/0000-0001-9001-8244","contributorId":225681,"corporation":false,"usgs":true,"family":"Mason","given":"Christopher","middleInitial":"A.","affiliations":[{"id":37759,"text":"VA/WV Water Science Center","active":true,"usgs":true}],"preferred":true,"id":791966,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Eggleston, Jack R. 0000-0001-6633-3041","orcid":"https://orcid.org/0000-0001-6633-3041","contributorId":204628,"corporation":false,"usgs":true,"family":"Eggleston","given":"Jack R.","affiliations":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"preferred":true,"id":791967,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nicotra, Matthew J. 0000-0002-0152-6261","orcid":"https://orcid.org/0000-0002-0152-6261","contributorId":225682,"corporation":false,"usgs":true,"family":"Nicotra","given":"Matthew","email":"","middleInitial":"J.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":791968,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chiu, C.-L.","contributorId":225683,"corporation":false,"usgs":false,"family":"Chiu","given":"C.-L.","email":"","affiliations":[{"id":12465,"text":"University of Pittsburgh","active":true,"usgs":false}],"preferred":false,"id":791969,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Henneberg, Mark F. 0000-0002-6991-1211 mfhenneb@usgs.gov","orcid":"https://orcid.org/0000-0002-6991-1211","contributorId":187481,"corporation":false,"usgs":true,"family":"Henneberg","given":"Mark","email":"mfhenneb@usgs.gov","middleInitial":"F.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":791970,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Best, Heather 0000-0003-0764-3060","orcid":"https://orcid.org/0000-0003-0764-3060","contributorId":225684,"corporation":false,"usgs":true,"family":"Best","given":"Heather","email":"","affiliations":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":791971,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Cederberg, Jay 0000-0001-6649-7353","orcid":"https://orcid.org/0000-0001-6649-7353","contributorId":219724,"corporation":false,"usgs":true,"family":"Cederberg","given":"Jay","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":791972,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Holnbeck, Stephen R. 0000-0001-7313-9298","orcid":"https://orcid.org/0000-0001-7313-9298","contributorId":225685,"corporation":false,"usgs":true,"family":"Holnbeck","given":"Stephen","email":"","middleInitial":"R.","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":791973,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Lotspeich, R. Russell 0000-0002-5572-9064 rlotspei@usgs.gov","orcid":"https://orcid.org/0000-0002-5572-9064","contributorId":3388,"corporation":false,"usgs":true,"family":"Lotspeich","given":"R.","email":"rlotspei@usgs.gov","middleInitial":"Russell","affiliations":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"preferred":false,"id":791974,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Laveau, Christopher 0000-0002-4009-1889","orcid":"https://orcid.org/0000-0002-4009-1889","contributorId":206046,"corporation":false,"usgs":true,"family":"Laveau","given":"Christopher","email":"","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":791975,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Moramarco, Tommaso 0000-0002-9870-1694","orcid":"https://orcid.org/0000-0002-9870-1694","contributorId":225686,"corporation":false,"usgs":false,"family":"Moramarco","given":"Tommaso","email":"","affiliations":[{"id":41180,"text":"IRPI-Consiglio Nazionale delle Ricerche","active":true,"usgs":false}],"preferred":false,"id":791976,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Jones, Mark E. 0000-0002-9242-1528","orcid":"https://orcid.org/0000-0002-9242-1528","contributorId":225687,"corporation":false,"usgs":true,"family":"Jones","given":"Mark","email":"","middleInitial":"E.","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":791977,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Gourley, Jonathan J 0000-0001-7363-3755","orcid":"https://orcid.org/0000-0001-7363-3755","contributorId":225540,"corporation":false,"usgs":false,"family":"Gourley","given":"Jonathan","email":"","middleInitial":"J","affiliations":[{"id":41158,"text":"NOAA/OAR/National Severe Storms Laboratory, Norman, OK, USA 73072","active":true,"usgs":false}],"preferred":false,"id":791978,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Wasielewski, Danny","contributorId":225688,"corporation":false,"usgs":false,"family":"Wasielewski","given":"Danny","affiliations":[{"id":41181,"text":"NOAA National Severe Storms Laboratory","active":true,"usgs":false}],"preferred":false,"id":791979,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}} ,{"id":70210161,"text":"70210161 - 2020 - The Landsat Burned Area algorithm and products for the conterminous United States","interactions":[],"lastModifiedDate":"2022-04-14T19:23:11.991912","indexId":"70210161","displayToPublicDate":"2020-04-20T10:12:38","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"The Landsat Burned Area algorithm and products for the conterminous United States","docAbstract":"Complete and accurate burned area map data are needed to document spatial and temporal patterns of fires, to quantify their drivers, and to assess the impacts on human and natural systems. In this study, we developed the Landsat Burned Area (BA) algorithm, an update from the Landsat Burned Area Essential Climate Variable (BAECV) algorithm. Here, we present the BA algorithm and products, changes relative to the BAECV algorithm and products, and updated validation metrics. We also present spatial and temporal patterns of burned area across the conterminous U.S., how burned area varies in relation to the number of operational Landsat sensors, and a comparison with other burned area datasets, including the BAECV, Monitoring Trends in Burn Severity (MTBS), GeoMAC, and Moderate Resolution Imaging Spectroradiometer (MODIS) MCD64A1.006 data. The BA algorithm identifies burned areas in analysis ready data (ARD) time-series of Landsat imagery from 1984 through 2018 using machine learning, thresholding, and image segmentation. Validation with reference data from high-resolution commercial satellite imagery resulted in omission and commission error rates averaging 19% and 41%, respectively. In comparison, validation with Landsat reference data had omission and commission error rates averaging 40% and 28%, respectively when burned areas in cultivated crops and pasture/hay land-cover types were excluded. Both validation tests documented lower commission error rates relative to the BAECV products. The amount of burned area detected varies not only in response to climate but also with the number of operational sensors and scenes collected. The combined amount of burned area detected by multiple sensors was larger than from any individual sensor, but there was no significant difference between individual sensors. Therefore, we used BA products from individual sensors to assess trends over time and all available sensors to compare with other existing BA products. From 1984 through 2018, annual burned area averaged 30,000 km2, ranged between 14,000 km2 in 1991 and 46,500 km2 in 2012, and increased over time at a rate of 356 km2/year. Compared to existing burned area products, the new Landsat BA products identified 29% more burned area than the BAECV products (1984–2015), 183% more than the MTBS/GeoMAC products (1984–2018), and 56% more than the MCD64A1.006 products (2003–2018). The products had similar patterns of year-to-year variability; the R2 values of linear regressions between annual burned area were >0.70 with the BAECV products and the MTBS/GeoMAC products, but somewhat lower for the MCD64A1.006 product (R2 = 0.66). The BA products are routinely produced as new Landsat data are collected and provide a unique data source to monitor and assess the spatial and temporal patterns and the impacts of fire.","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2020.111801","usgsCitation":"Hawbaker, T., Vanderhoof, M.K., Schmidt, G.L., Beal, Y.G., Picotte, J.J., Takacs, J., Falgout, J.T., and Dwyer, J.L., 2020, The Landsat Burned Area algorithm and products for the conterminous United States: Remote Sensing of Environment, v. 244, 111801, 24 p., https://doi.org/10.1016/j.rse.2020.111801.","productDescription":"111801, 24 p.","ipdsId":"IP-111890","costCenters":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":457018,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rse.2020.111801","text":"Publisher Index Page"},{"id":437022,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9F26LY6","text":"USGS data release","linkHelpText":"The Landsat Collection 2 Burned Area Products for the conterminous United States (ver. 2.0, April 2024)"},{"id":374927,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"geometry\": {\n \"type\": \"MultiPolygon\",\n \"coordinates\": [\n [\n [\n [\n -94.81758,\n 49.38905\n ],\n [\n -94.64,\n 48.84\n ],\n [\n -94.32914,\n 48.67074\n ],\n [\n -93.63087,\n 48.60926\n ],\n [\n -92.61,\n 48.45\n ],\n [\n -91.64,\n 48.14\n ],\n [\n -90.83,\n 48.27\n ],\n [\n -89.6,\n 48.01\n ],\n [\n -89.27292,\n 48.01981\n ],\n [\n -88.37811,\n 48.30292\n ],\n [\n -87.43979,\n 47.94\n ],\n [\n -86.46199,\n 47.55334\n ],\n [\n -85.65236,\n 47.22022\n ],\n [\n -84.87608,\n 46.90008\n ],\n [\n -84.77924,\n 46.6371\n ],\n [\n -84.54375,\n 46.53868\n ],\n [\n -84.6049,\n 46.4396\n ],\n [\n -84.3367,\n 46.40877\n ],\n [\n -84.14212,\n 46.51223\n ],\n [\n -84.09185,\n 46.27542\n ],\n [\n -83.89077,\n 46.11693\n ],\n [\n -83.61613,\n 46.11693\n ],\n [\n -83.46955,\n 45.99469\n ],\n [\n -83.59285,\n 45.81689\n ],\n [\n -82.55092,\n 45.34752\n ],\n [\n -82.33776,\n 44.44\n ],\n [\n -82.13764,\n 43.57109\n ],\n [\n -82.43,\n 42.98\n ],\n [\n -82.9,\n 42.43\n ],\n [\n -83.12,\n 42.08\n ],\n [\n -83.142,\n 41.97568\n ],\n [\n -83.02981,\n 41.8328\n ],\n [\n -82.69009,\n 41.67511\n ],\n [\n -82.43928,\n 41.67511\n ],\n [\n -81.27775,\n 42.20903\n ],\n [\n -80.24745,\n 42.3662\n ],\n [\n -78.93936,\n 42.86361\n ],\n [\n -78.92,\n 42.965\n ],\n [\n -79.01,\n 43.27\n ],\n [\n -79.17167,\n 43.46634\n ],\n [\n -78.72028,\n 43.62509\n ],\n [\n -77.73789,\n 43.62906\n ],\n [\n -76.82003,\n 43.62878\n ],\n [\n -76.5,\n 44.01846\n ],\n [\n -76.375,\n 44.09631\n ],\n [\n -75.31821,\n 44.81645\n ],\n [\n -74.867,\n 45.00048\n ],\n [\n -73.34783,\n 45.00738\n ],\n [\n -71.50506,\n 45.0082\n ],\n [\n -71.405,\n 45.255\n ],\n [\n -71.08482,\n 45.30524\n ],\n [\n -70.66,\n 45.46\n ],\n [\n -70.305,\n 45.915\n ],\n [\n -69.99997,\n 46.69307\n ],\n [\n -69.23722,\n 47.44778\n ],\n [\n -68.905,\n 47.185\n ],\n [\n -68.23444,\n 47.35486\n ],\n [\n -67.79046,\n 47.06636\n ],\n [\n -67.79134,\n 45.70281\n ],\n [\n -67.13741,\n 45.13753\n ],\n [\n -66.96466,\n 44.8097\n ],\n [\n -68.03252,\n 44.3252\n ],\n [\n -69.06,\n 43.98\n ],\n [\n -70.11617,\n 43.68405\n ],\n [\n -70.64548,\n 43.09024\n ],\n [\n -70.81489,\n 42.8653\n ],\n [\n -70.825,\n 42.335\n ],\n [\n -70.495,\n 41.805\n ],\n [\n -70.08,\n 41.78\n ],\n [\n -70.185,\n 42.145\n ],\n [\n -69.88497,\n 41.92283\n ],\n [\n -69.96503,\n 41.63717\n ],\n [\n -70.64,\n 41.475\n ],\n [\n -71.12039,\n 41.49445\n ],\n [\n -71.86,\n 41.32\n ],\n [\n -72.295,\n 41.27\n ],\n [\n -72.87643,\n 41.22065\n ],\n [\n -73.71,\n 40.9311\n ],\n [\n -72.24126,\n 41.11948\n ],\n [\n -71.945,\n 40.93\n ],\n [\n -73.345,\n 40.63\n ],\n [\n -73.982,\n 40.628\n ],\n [\n -73.95232,\n 40.75075\n ],\n [\n -74.25671,\n 40.47351\n ],\n [\n -73.96244,\n 40.42763\n ],\n [\n -74.17838,\n 39.70926\n ],\n [\n -74.90604,\n 38.93954\n ],\n [\n -74.98041,\n 39.1964\n ],\n [\n -75.20002,\n 39.24845\n ],\n [\n -75.52805,\n 39.4985\n ],\n [\n -75.32,\n 38.96\n ],\n [\n -75.07183,\n 38.78203\n ],\n [\n -75.05673,\n 38.40412\n ],\n [\n -75.37747,\n 38.01551\n ],\n [\n -75.94023,\n 37.21689\n ],\n [\n -76.03127,\n 37.2566\n ],\n [\n -75.72205,\n 37.93705\n ],\n [\n -76.23287,\n 38.31921\n ],\n [\n -76.35,\n 39.15\n ],\n [\n -76.54272,\n 38.71762\n ],\n [\n -76.32933,\n 38.08326\n ],\n [\n -76.99,\n 38.23999\n ],\n [\n -76.30162,\n 37.91794\n ],\n [\n -76.25874,\n 36.9664\n ],\n [\n -75.9718,\n 36.89726\n ],\n [\n -75.86804,\n 36.55125\n ],\n [\n -75.72749,\n 35.55074\n ],\n [\n -76.36318,\n 34.80854\n ],\n [\n -77.39763,\n 34.51201\n ],\n [\n -78.05496,\n 33.92547\n ],\n [\n -78.55435,\n 33.86133\n ],\n [\n -79.06067,\n 33.49395\n ],\n [\n -79.20357,\n 33.15839\n ],\n [\n -80.30132,\n 32.50935\n ],\n [\n -80.86498,\n 32.0333\n ],\n [\n -81.33629,\n 31.44049\n ],\n [\n -81.49042,\n 30.72999\n ],\n [\n -81.31371,\n 30.03552\n ],\n [\n -80.98,\n 29.18\n ],\n [\n -80.53558,\n 28.47213\n ],\n [\n -80.53,\n 28.04\n ],\n [\n -80.05654,\n 26.88\n ],\n [\n -80.08801,\n 26.20576\n ],\n [\n -80.13156,\n 25.81677\n ],\n [\n -80.38103,\n 25.20616\n ],\n [\n -80.68,\n 25.08\n ],\n [\n -81.17213,\n 25.20126\n ],\n [\n -81.33,\n 25.64\n ],\n [\n -81.71,\n 25.87\n ],\n [\n -82.24,\n 26.73\n ],\n [\n -82.70515,\n 27.49504\n ],\n [\n -82.85526,\n 27.88624\n ],\n [\n -82.65,\n 28.55\n ],\n [\n -82.93,\n 29.1\n ],\n [\n -83.70959,\n 29.93656\n ],\n [\n -84.1,\n 30.09\n ],\n [\n -85.10882,\n 29.63615\n ],\n [\n -85.28784,\n 29.68612\n ],\n [\n -85.7731,\n 30.15261\n ],\n [\n -86.4,\n 30.4\n ],\n [\n -87.53036,\n 30.27433\n ],\n [\n -88.41782,\n 30.3849\n ],\n [\n -89.18049,\n 30.31598\n ],\n [\n -89.59383,\n 30.15999\n ],\n [\n -89.41373,\n 29.89419\n ],\n [\n -89.43,\n 29.48864\n ],\n [\n -89.21767,\n 29.29108\n ],\n [\n -89.40823,\n 29.15961\n ],\n [\n -89.77928,\n 29.30714\n ],\n [\n -90.15463,\n 29.11743\n ],\n [\n -90.88022,\n 29.14854\n ],\n [\n -91.62678,\n 29.677\n ],\n [\n -92.49906,\n 29.5523\n ],\n [\n -93.22637,\n 29.78375\n ],\n [\n -93.84842,\n 29.71363\n ],\n [\n -94.69,\n 29.48\n ],\n [\n -95.60026,\n 28.73863\n ],\n [\n -96.59404,\n 28.30748\n ],\n [\n -97.14,\n 27.83\n ],\n [\n -97.37,\n 27.38\n ],\n [\n -97.38,\n 26.69\n ],\n [\n -97.33,\n 26.21\n ],\n [\n -97.14,\n 25.87\n ],\n [\n -97.53,\n 25.84\n ],\n [\n -98.24,\n 26.06\n ],\n [\n -99.02,\n 26.37\n ],\n [\n -99.3,\n 26.84\n ],\n [\n -99.52,\n 27.54\n ],\n [\n -100.11,\n 28.11\n ],\n [\n -100.45584,\n 28.69612\n ],\n [\n -100.9576,\n 29.38071\n ],\n [\n -101.6624,\n 29.7793\n ],\n [\n -102.48,\n 29.76\n ],\n [\n -103.11,\n 28.97\n ],\n [\n -103.94,\n 29.27\n ],\n [\n -104.45697,\n 29.57196\n ],\n [\n -104.70575,\n 30.12173\n ],\n [\n -105.03737,\n 30.64402\n ],\n [\n -105.63159,\n 31.08383\n ],\n [\n -106.1429,\n 31.39995\n ],\n [\n -106.50759,\n 31.75452\n ],\n [\n -108.24,\n 31.75485\n ],\n [\n -108.24194,\n 31.34222\n ],\n [\n -109.035,\n 31.34194\n ],\n [\n -111.02361,\n 31.33472\n ],\n [\n -113.30498,\n 32.03914\n ],\n [\n -114.815,\n 32.52528\n ],\n [\n -114.72139,\n 32.72083\n ],\n [\n -115.99135,\n 32.61239\n ],\n [\n -117.12776,\n 32.53534\n ],\n [\n -117.29594,\n 33.04622\n ],\n [\n -117.944,\n 33.62124\n ],\n [\n -118.4106,\n 33.74091\n ],\n [\n -118.51989,\n 34.02778\n ],\n [\n -119.081,\n 34.078\n ],\n [\n -119.43884,\n 34.34848\n ],\n [\n -120.36778,\n 34.44711\n ],\n [\n -120.62286,\n 34.60855\n ],\n [\n -120.74433,\n 35.15686\n ],\n [\n -121.71457,\n 36.16153\n ],\n [\n -122.54747,\n 37.55176\n ],\n [\n -122.51201,\n 37.78339\n ],\n [\n -122.95319,\n 38.11371\n ],\n [\n -123.7272,\n 38.95166\n ],\n [\n -123.86517,\n 39.76699\n ],\n [\n -124.39807,\n 40.3132\n ],\n [\n -124.17886,\n 41.14202\n ],\n [\n -124.2137,\n 41.99964\n ],\n [\n -124.53284,\n 42.76599\n ],\n [\n -124.14214,\n 43.70838\n ],\n [\n -124.02053,\n 44.6159\n ],\n [\n -123.89893,\n 45.52341\n ],\n [\n -124.07963,\n 46.86475\n ],\n [\n -124.39567,\n 47.72017\n ],\n [\n -124.68721,\n 48.18443\n ],\n [\n -124.5661,\n 48.37971\n ],\n [\n -123.12,\n 48.04\n ],\n [\n -122.58736,\n 47.096\n ],\n [\n -122.34,\n 47.36\n ],\n [\n -122.5,\n 48.18\n ],\n [\n -122.84,\n 49\n ],\n [\n -120,\n 49\n ],\n [\n -117.03121,\n 49\n ],\n [\n -116.04818,\n 49\n ],\n [\n -113,\n 49\n ],\n [\n -110.05,\n 49\n ],\n [\n -107.05,\n 49\n ],\n [\n -104.04826,\n 48.99986\n ],\n [\n -100.65,\n 49\n ],\n [\n -97.22872,\n 49.0007\n ],\n [\n -95.15907,\n 49\n ],\n [\n -95.15609,\n 49.38425\n ],\n [\n -94.81758,\n 49.38905\n ]\n ]\n ]\n ]\n },\n \"properties\": {\n \"name\": \"United States\"\n }\n }\n ]\n}","volume":"244","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hawbaker, Todd 0000-0003-0930-9154 tjhawbaker@usgs.gov","orcid":"https://orcid.org/0000-0003-0930-9154","contributorId":568,"corporation":false,"usgs":true,"family":"Hawbaker","given":"Todd","email":"tjhawbaker@usgs.gov","affiliations":[{"id":547,"text":"Rocky Mountain Geographic Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":789348,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vanderhoof, Melanie K. 0000-0002-0101-5533 mvanderhoof@usgs.gov","orcid":"https://orcid.org/0000-0002-0101-5533","contributorId":168395,"corporation":false,"usgs":true,"family":"Vanderhoof","given":"Melanie","email":"mvanderhoof@usgs.gov","middleInitial":"K.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":789349,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schmidt, Gail L. 0000-0002-9684-8158 gschmidt@usgs.gov","orcid":"https://orcid.org/0000-0002-9684-8158","contributorId":3475,"corporation":false,"usgs":true,"family":"Schmidt","given":"Gail","email":"gschmidt@usgs.gov","middleInitial":"L.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":789350,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Beal, Yen-Ju G. 0000-0002-5538-5687 ygbeal@usgs.gov","orcid":"https://orcid.org/0000-0002-5538-5687","contributorId":5328,"corporation":false,"usgs":true,"family":"Beal","given":"Yen-Ju","email":"ygbeal@usgs.gov","middleInitial":"G.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":789463,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Picotte, Joshua J. 0000-0002-4021-4623 jpicotte@usgs.gov","orcid":"https://orcid.org/0000-0002-4021-4623","contributorId":4626,"corporation":false,"usgs":true,"family":"Picotte","given":"Joshua","email":"jpicotte@usgs.gov","middleInitial":"J.","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":789352,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Takacs, Joshua 0000-0003-1509-5498 jdtakacs@usgs.gov","orcid":"https://orcid.org/0000-0003-1509-5498","contributorId":194380,"corporation":false,"usgs":true,"family":"Takacs","given":"Joshua","email":"jdtakacs@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":789353,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Falgout, Jeff T. 0000-0002-7108-477X jfalgout@usgs.gov","orcid":"https://orcid.org/0000-0002-7108-477X","contributorId":4957,"corporation":false,"usgs":true,"family":"Falgout","given":"Jeff","email":"jfalgout@usgs.gov","middleInitial":"T.","affiliations":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":true,"id":789354,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Dwyer, John L. 0000-0002-8281-0896 dwyer@usgs.gov","orcid":"https://orcid.org/0000-0002-8281-0896","contributorId":3481,"corporation":false,"usgs":true,"family":"Dwyer","given":"John","email":"dwyer@usgs.gov","middleInitial":"L.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":789355,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70210710,"text":"70210710 - 2020 - Acoustic Sediment Estimation Toolbox (ASET): A software package for calibrating and processing TRDI ADCP data to compute suspended-sediment transport in sandy rivers","interactions":[],"lastModifiedDate":"2020-06-18T14:36:43.859337","indexId":"70210710","displayToPublicDate":"2020-04-20T09:30:06","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1315,"text":"Computers & Geosciences","printIssn":"0098-3004","active":true,"publicationSubtype":{"id":10}},"title":"Acoustic Sediment Estimation Toolbox (ASET): A software package for calibrating and processing TRDI ADCP data to compute suspended-sediment transport in sandy rivers","docAbstract":"Quantifying suspended-sediment transport is critical for a variety of disciplines related to the management of water resources. However, the number of gauging stations and monitoring networks in most rivers around the world is insufficient to improve understanding of river dynamics and support water resource management decisions. This is mainly due to the high operational costs and intensive labor involved in traditional sediment measurement techniques, especially in sand bed rivers where coarse material varies spatially in the river cross section. Recently, the acoustic surrogate method has received attention as a potentially accurate surrogate technology for estimating suspended-sediment concentrations. In addition, the acoustic surrogate method, through use of acoustic Doppler current profilers (ADCPs), has the advantage of being able to simultaneously measure the flow velocity field and cross-sectional area when moving-boat measurements are performed. In spite of the important advances made in the implementation of this technique, there are no widely-available, free tools for processing the ADCP acoustic signal cross section measurements which include options to extrapolate velocity and sediment in unmeasured ADCP zones and develop calibrations with physical samples. This paper presents a new software called Acoustic Sediment Estimation Toolbox (ASET), which enables the user to develop a calibration between the acoustic signal collected with a down-looking Teledyne RD Instruments ADCP and sediment concentrations determined using traditional sediment sampling techniques. Moreover, ASET software uses dynamic ADCP measurements to estimate the total suspended-sediment transport through a river cross section. The theoretical framework and data processing routines applied by each module in ASET are presented. Finally, a comparison is made between the results obtained by ASET and by traditional methodologies for computing suspended-sediment transport in a large river system (Paraná River, Argentina).","language":"English","publisher":"Elsevier","doi":"10.1016/j.cageo.2020.104499","usgsCitation":"Dominguez Ruben, L.G., Szupiany, R., Latosinski, F., Lopez Weibel, C., Wood, M.S., and Boldt, J.A., 2020, Acoustic Sediment Estimation Toolbox (ASET): A software package for calibrating and processing TRDI ADCP data to compute suspended-sediment transport in sandy rivers: Computers & Geosciences, v. 140, https://doi.org/10.1016/j.cageo.2020.104499.","productDescription":"104499, 13 p.","startPage":"Article 104499","ipdsId":"IP-102073","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true},{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":375680,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Argentina","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[-65.5,-55.2],[-66.45,-55.25],[-66.95992,-54.89681],[-67.56244,-54.87001],[-68.63335,-54.8695],[-68.63401,-52.63637],[-68.25,-53.1],[-67.75,-53.85],[-66.45,-54.45],[-65.05,-54.7],[-65.5,-55.2]]],[[[-64.96489,-22.07586],[-64.37702,-22.79809],[-63.98684,-21.99364],[-62.84647,-22.03499],[-62.68506,-22.24903],[-60.84656,-23.88071],[-60.02897,-24.0328],[-58.80713,-24.77146],[-57.77722,-25.16234],[-57.63366,-25.60366],[-58.61817,-27.12372],[-57.60976,-27.3959],[-56.4867,-27.5485],[-55.69585,-27.38784],[-54.78879,-26.62179],[-54.62529,-25.73926],[-54.13005,-25.54764],[-53.62835,-26.12487],[-53.64874,-26.92347],[-54.49073,-27.47476],[-55.16229,-27.88192],[-56.2909,-28.85276],[-57.62513,-30.21629],[-57.87494,-31.01656],[-58.14244,-32.0445],[-58.13265,-33.04057],[-58.34961,-33.26319],[-58.42707,-33.90945],[-58.49544,-34.43149],[-57.22583,-35.28803],[-57.36236,-35.97739],[-56.73749,-36.41313],[-56.78829,-36.90157],[-57.74916,-38.18387],[-59.23186,-38.72022],[-61.23745,-38.92842],[-62.33596,-38.82771],[-62.12576,-39.4241],[-62.33053,-40.17259],[-62.14599,-40.6769],[-62.7458,-41.02876],[-63.77049,-41.16679],[-64.73209,-40.80268],[-65.11804,-41.06431],[-64.97856,-42.058],[-64.30341,-42.35902],[-63.75595,-42.04369],[-63.45806,-42.56314],[-64.3788,-42.87356],[-65.1818,-43.49538],[-65.32882,-44.50137],[-65.56527,-45.03679],[-66.50997,-45.03963],[-67.29379,-45.5519],[-67.58055,-46.30177],[-66.59707,-47.03392],[-65.64103,-47.23613],[-65.98509,-48.13329],[-67.16618,-48.69734],[-67.81609,-49.86967],[-68.72875,-50.26422],[-69.13854,-50.73251],[-68.81556,-51.7711],[-68.14999,-52.34998],[-68.57155,-52.29944],[-69.49836,-52.14276],[-71.9148,-52.00902],[-72.3294,-51.42596],[-72.30997,-50.67701],[-72.97575,-50.74145],[-73.32805,-50.37879],[-73.41544,-49.31844],[-72.64825,-48.87862],[-72.33116,-48.24424],[-72.44736,-47.73853],[-71.91726,-46.88484],[-71.55201,-45.56073],[-71.65932,-44.97369],[-71.22278,-44.78424],[-71.3298,-44.40752],[-71.79362,-44.20717],[-71.46406,-43.78761],[-71.91542,-43.40856],[-72.1489,-42.25489],[-71.7468,-42.05139],[-71.91573,-40.83234],[-71.68076,-39.80816],[-71.41352,-38.91602],[-70.81466,-38.553],[-71.11863,-37.57683],[-71.12188,-36.65812],[-70.36477,-36.00509],[-70.38805,-35.16969],[-69.81731,-34.19357],[-69.81478,-33.27389],[-70.0744,-33.09121],[-70.53507,-31.36501],[-69.91901,-30.33634],[-70.01355,-29.36792],[-69.65613,-28.45914],[-69.00123,-27.52121],[-68.29554,-26.89934],[-68.5948,-26.50691],[-68.386,-26.18502],[-68.41765,-24.51855],[-67.32844,-24.0253],[-66.98523,-22.98635],[-67.10667,-22.73592],[-66.27334,-21.83231],[-64.96489,-22.07586]]]]},\"properties\":{\"name\":\"Argentina\"}}]}","volume":"140","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Dominguez Ruben, Lucas Gerardo","contributorId":225404,"corporation":false,"usgs":false,"family":"Dominguez Ruben","given":"Lucas","email":"","middleInitial":"Gerardo","affiliations":[{"id":41098,"text":"Littoral National University, Argentina","active":true,"usgs":false}],"preferred":false,"id":791058,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Szupiany, Ricardo","contributorId":225405,"corporation":false,"usgs":false,"family":"Szupiany","given":"Ricardo","affiliations":[{"id":41098,"text":"Littoral National University, Argentina","active":true,"usgs":false}],"preferred":false,"id":791059,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Latosinski, Francisco","contributorId":225406,"corporation":false,"usgs":false,"family":"Latosinski","given":"Francisco","affiliations":[{"id":41099,"text":"National Scientific and Technical Research Council, Argentina","active":true,"usgs":false}],"preferred":false,"id":791060,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lopez Weibel, Cecilia","contributorId":225407,"corporation":false,"usgs":false,"family":"Lopez Weibel","given":"Cecilia","affiliations":[{"id":32938,"text":"Littoral National University","active":true,"usgs":false}],"preferred":false,"id":791061,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wood, Molly S. 0000-0002-5184-8306 mswood@usgs.gov","orcid":"https://orcid.org/0000-0002-5184-8306","contributorId":788,"corporation":false,"usgs":true,"family":"Wood","given":"Molly","email":"mswood@usgs.gov","middleInitial":"S.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"preferred":true,"id":791062,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Boldt, Justin A. 0000-0002-0771-3658","orcid":"https://orcid.org/0000-0002-0771-3658","contributorId":207849,"corporation":false,"usgs":true,"family":"Boldt","given":"Justin","email":"","middleInitial":"A.","affiliations":[{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true},{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":791063,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70209677,"text":"70209677 - 2020 - A critical assessment of human-impact indices based on anthropogenic pollen indicators","interactions":[],"lastModifiedDate":"2020-04-21T14:49:32.79993","indexId":"70209677","displayToPublicDate":"2020-04-19T09:46:12","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3219,"text":"Quaternary Science Reviews","active":true,"publicationSubtype":{"id":10}},"title":"A critical assessment of human-impact indices based on anthropogenic pollen indicators","docAbstract":"Anthropogenic pollen indicators in pollen records are an established tool for reconstructing the history of human impacts on vegetation and landscapes. They are also used to disentangle the influence of human activities and climatic variability on ecosystems. The comprehensive anthropogenic pollen-indicator approach developed by Behre (1981) has been widely used, including beyond its original geographical scope of Central and Western Europe. Uncritical adoption of this approach for other areas is risky because adventives (plants introduced with agriculture) in Central Europe can be apophytes (native plants favoured by human disturbances) in other regions. This problem can be addressed by identifying region-specific, anthropogenic-indicator pollen types and/or developing region-specific, human-impact indices from pollen assemblages. However, understanding of regional variation in the timing and intensity of human impacts is limited by the lack of standardization, validation and intercomparison of such regional approaches. Here we review the most common European anthropogenic pollen-indicator approaches to assess their performance at six sites spanning a continental gradient over the boreal, temperate and Mediterranean biomes. Specifically, we evaluate the human-indicator approaches by using independent archaeological evidence and models. We present new insights into how these methodologies can assist in the interpretation of pollen records as well as into how a careful selection of pollen types and/or indices according to the specific geographical scope of each study is key to obtain meaningful reconstructions of anthropogenic activity through time. The evaluated approaches generally perform better in the regions for which they were developed. However, we find marked differences in their capacity to identify human impact, while some approaches do not perform well even in the regions for which they were developed, others might be used, with due caution, outside their original areas or biomes. We conclude that alongside the increasing wealth of pollen datasets a need to develop novel tools may assist numeric human impact reconstructions.","language":"English","publisher":"Elsevier","doi":"10.1016/j.quascirev.2020.106291","collaboration":"","usgsCitation":"Deza-Araujo, M., Morales-Molino, C., Tinner, W., Henne, P., Heitz, C., Pezzatti, G.B., Hafner, A., and Conedera, M., 2020, A critical assessment of human-impact indices based on anthropogenic pollen indicators: Quaternary Science Reviews, v. 236, https://doi.org/10.1016/j.quascirev.2020.106291.","productDescription":"106291, 12 p.","startPage":"","ipdsId":"IP-115699","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":457030,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.quascirev.2020.106291","text":"Publisher Index Page"},{"id":374154,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"236","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Deza-Araujo, Mara 0000-0001-9628-771X","orcid":"https://orcid.org/0000-0001-9628-771X","contributorId":224223,"corporation":false,"usgs":false,"family":"Deza-Araujo","given":"Mara","email":"","affiliations":[{"id":40840,"text":"Swiss Federal Institute for Forest, Snow, and Landscape Research (WSL)","active":true,"usgs":false}],"preferred":false,"id":787479,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Morales-Molino, Cesar 0000-0002-9464-862X","orcid":"https://orcid.org/0000-0002-9464-862X","contributorId":224224,"corporation":false,"usgs":false,"family":"Morales-Molino","given":"Cesar","email":"","affiliations":[{"id":38843,"text":"University of Bern, Switzerland","active":true,"usgs":false}],"preferred":false,"id":787480,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tinner, Willy 0000-0001-7352-0144","orcid":"https://orcid.org/0000-0001-7352-0144","contributorId":169167,"corporation":false,"usgs":false,"family":"Tinner","given":"Willy","email":"","affiliations":[{"id":25430,"text":"University of Bern","active":true,"usgs":false}],"preferred":false,"id":787481,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Henne, Paul D. 0000-0003-1211-5545 phenne@usgs.gov","orcid":"https://orcid.org/0000-0003-1211-5545","contributorId":169166,"corporation":false,"usgs":true,"family":"Henne","given":"Paul D.","email":"phenne@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":787482,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Heitz, Caroline 0000-0001-7188-6775","orcid":"https://orcid.org/0000-0001-7188-6775","contributorId":224225,"corporation":false,"usgs":false,"family":"Heitz","given":"Caroline","email":"","affiliations":[{"id":38843,"text":"University of Bern, Switzerland","active":true,"usgs":false}],"preferred":false,"id":787483,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pezzatti, Gianni B 0000-0003-2564-3435","orcid":"https://orcid.org/0000-0003-2564-3435","contributorId":224226,"corporation":false,"usgs":false,"family":"Pezzatti","given":"Gianni","email":"","middleInitial":"B","affiliations":[{"id":40840,"text":"Swiss Federal Institute for Forest, Snow, and Landscape Research (WSL)","active":true,"usgs":false}],"preferred":false,"id":787484,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hafner, Albert 0000-0003-2159-8569","orcid":"https://orcid.org/0000-0003-2159-8569","contributorId":224227,"corporation":false,"usgs":false,"family":"Hafner","given":"Albert","email":"","affiliations":[{"id":38843,"text":"University of Bern, Switzerland","active":true,"usgs":false}],"preferred":false,"id":787485,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Conedera, Marco 0000-0003-3980-2142","orcid":"https://orcid.org/0000-0003-3980-2142","contributorId":194727,"corporation":false,"usgs":false,"family":"Conedera","given":"Marco","email":"","affiliations":[],"preferred":false,"id":787486,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70209696,"text":"70209696 - 2020 - Inferring surface flow velocities in sediment-laden Alaskan rivers from optical image sequences acquired from a helicopter","interactions":[],"lastModifiedDate":"2020-04-21T16:53:17.461883","indexId":"70209696","displayToPublicDate":"2020-04-18T11:48:25","publicationYear":"2020","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":"Inferring surface flow velocities in sediment-laden Alaskan rivers from optical image sequences acquired from a helicopter","docAbstract":"The remote, inaccessible location of many rivers in Alaska creates a compelling need for remote sensing approaches to streamflow monitoring. Motivated by this objective, we evaluated the potential to infer flow velocities from optical image sequences acquired from a helicopter deployed above two large, sediment-laden rivers. Rather than artificial seeding, we used an ensemble correlation particle image velocimetry (PIV) algorithm to track the movement of boil vortices that upwell suspended sediment and produce a visible contrast at the water surface. This study introduced a general, modular workflow for image preparation (stabilization and geo-referencing), preprocessing (filtering and contrast enhancement), analysis (PIV), and postprocessing (scaling PIV output and assessing accuracy via comparison to field measurements). Applying this method to images acquired with a digital mapping camera and an inexpensive video camera highlighted the importance of image enhancement and the need to resample the data to an appropriate, coarser pixel size and a lower frame rate. We also developed a Parameter Optimization for PIV (POP) framework to guide selection of the interrogation area (IA) and frame rate for a particular application. POP results indicated that the performance of the PIV algorithm was highly robust and that relatively large IAs (64–320 pixels) and modest frame rates (0.5–2 Hz) yielded strong agreement (
The bedrock geology of the Mount Ascutney 7.5- x 15-minute quadrangle consists of highly deformed and metamorphosed Mesoproterozoic through Devonian metasedimentary and meta-igneous rocks intruded by rocks of the Mesozoic White Mountain Igneous Suite. In the west, Mesoproterozoic gneisses of the Mount Holly Complex are the oldest rocks and form the northeastern flank of the Chester dome. The allochthonous Cambrian through Ordovician rocks include the Moretown and Cram Hill Formations and the North River Igneous Suite; these rocks structurally overlie the Chester dome along the Keyes Mountain thrust fault. Silurian and Devonian metasedimentary and metavolcanic rocks of the Connecticut Valley trough (CVT) unconformably overlie the pre-Silurian rocks. The easternmost extent of the CVT in New Hampshire is exposed in the Meriden antiform. Ordovician to Silurian and Devonian metasedimentary rocks of the Bronson Hill anticlinorium structurally overlie the CVT along the Monroe thrust fault. The oldest part of the Bronson Hill anticlinorium, called the Bronson Hill arc, consists of Ordovician metamorphosed volcanic, plutonic, and sedimentary rocks of the Ammonoosuc Volcanics, the Partridge Formation, and the Oliverian Plutonic Suite. The rocks of the Bronson Hill arc may be partly correlative with the pre-Silurian rocks above the Chester dome and are exposed in two fault-bounded structural belts (Cornish City and Claremont belts) and in the Sugar River dome. Collectively, these belts form the regional Orfordville anticlinorium, Hardscrabble synclinorium, and the western part of the broader Bronson Hill anticlinorium in western New Hampshire. Silurian to Devonian metasedimentary rocks of the Clough Quartzite, and Fitch and Littleton Formations unconformably overlie the rocks of the Bronson Hill arc. Devonian granitic and pegmatitic dikes and sills of the New Hampshire Plutonic Suite intruded previously deformed rocks. Post-tectonic Cretaceous plutonic and volcanic rocks of the Ascutney Mountain Intrusive Complex underlie Mount Ascutney. Because of the historically significant scientific research, and its prominence in the landscape, Mount Ascutney is commonly regarded as Vermont’s most famous volcano.
The bedrock geology was mapped to study the tectonic history of the area and to provide a framework for ongoing characterization of the bedrock of Vermont and New Hampshire. This Scientific Investigations Map of the Mount Ascutney 7.5- x 15-minute quadrangle consists of sheets 1 and 2 as well as a geographic information system (GIS) database that includes bedrock geologic units, faults, outcrops, structural geologic information, geochemistry, and photographs. Sheet 1 of the report includes a bedrock geologic map, a correlation of map units, and a description of map units. Sheet 2 includes a discussion of the geology, references, three cross sections from the geologic map on sheet 1, igneous rock geochemistry results of the main map units from the Mount Ascutney stock, a tectonic map showing major structural features, and a structural domain map showing the orientation and distribution of brittle features.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3440","collaboration":"Prepared in cooperation with the State of Vermont, Vermont Agency of Natural Resources, Vermont Geological Survey; State of New Hampshire, Department of Environmental Services, New Hampshire Geological Survey; and the National Park Service","usgsCitation":"Walsh, G.J., Valley, P.M., Thompson, P.J., Ratcliffe, N.M., Proctor, B.P., and Sicard, K.R., 2020, Bedrock geologic map of the Mount Ascutney 7.5- x 15-minute quadrangle, Windsor County, Vermont, and Sullivan County, New Hampshire (ver. 1.1, April 2020): U.S. Geological Survey Scientific Investigations Map 3440, 2 sheets, scale 1:24,000, https://doi.org/10.3133/sim3440.","productDescription":"2 Sheets: 61.00 x 40.81 inches and 57.00 x 40.50 inches; Read Me; Spatial Data; Metadata; Companion Files","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-090096","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":374082,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sim/3440/versionHist.txt","text":"Version History","size":"2.17 KB","linkFileType":{"id":2,"text":"txt"}},{"id":374079,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3440/coverthb4.jpg"},{"id":374081,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3440/sim3440_sheet2.pdf","text":"Sheet 2","size":"27.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":""},{"id":374080,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3440/sim3440_sheet1.pdf","text":"Sheet 1","size":"26.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3440"},{"id":374083,"rank":5,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sim/3440/sim3440_readme.txt","text":"Read Me","size":"13.1 KB","linkFileType":{"id":2,"text":"txt"}},{"id":374087,"rank":9,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sim/3440/sim3440_MountAscutney_openaccess.zip","text":"Open Access","size":"6.09 MB","linkFileType":{"id":6,"text":"zip"}},{"id":374086,"rank":8,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sim/3440/sim3440_MountAscutney_metadata.zip","text":"Metadata","size":"366 KB","linkFileType":{"id":6,"text":"zip"}},{"id":374085,"rank":7,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/sim/3440/sim3440_MountAscutney_database.zip","text":"Database","size":"6.58 MB","linkFileType":{"id":6,"text":"zip"}},{"id":374084,"rank":6,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sim/3440/sim3440_MountAscutney_basemap.zip","text":"Base Map","size":"43.7 MB","linkFileType":{"id":6,"text":"zip"}},{"id":374088,"rank":10,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sim/3440/sim3440_MountAscutney_photos.zip","text":"Photos","size":"577 MB","linkFileType":{"id":6,"text":"zip"}}],"country":"United States","state":"New Hampshire, Vermont","county":"Sullivan County, Windsor County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -72.5,\n 43.375\n ],\n [\n -72.25,\n 43.375\n ],\n [\n -72.25,\n 43.5\n ],\n [\n -72.5,\n 43.5\n ],\n [\n -72.5,\n 43.375\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"","edition":"Version 1.1: April 2020; Version 1.0: April 2020","contact":"Florence Bascom Geoscience Center
U.S. Geological Survey
926A National Center
12201 Sunrise Valley Drive
Reston, VA 20192
The Caney Mountain cave crayfish (Orconectes stygocaneyi) is one of North America's rarest crayfish, endemic to one cave in southern Missouri, USA. The species is listed as 'critically imperiled' by Missouri, and 'threatened' by the American Fisheries Society. Previously, only 15 crayfish have been observed in Mud Cave, and only two have been collected (for original species description). We aimed to collect the first natural history data on the species and search adjacent caves and springs for additional populations. Twelve visual searches and supplemental trapping over four years, in all seasons, yielded 69 O. stygocaneyi (including 11 young-of-year) observations and capture of 22 crayfish, including one ovigerous female. Visual searches of nearby caves and springs yielded no O. stygocaneyi records. However, multiple surveys of those caves and springs, using environmental DNA detected the species in one additional cave adjacent to Mud Cave, but only during spring high flow events when the caves may be ephemerally connected. Orconectes stygocaneyi's distribution is among the most restricted of any North American crayfish, and further evaluation of its conservation status designations might be warranted. Long term conservation of O. stygocaneyi would benefit from management practices promoting sustained, unimpacted surface runoff within Mud Cave's recharge area.
","language":"English","publisher":"International Association of Astacology","doi":"10.5869/fc.2020.v25-1.047","usgsCitation":"DiStefano, R., Ashley, D., Brewer, S.K., Mouser, J., and Neimiller, M., 2020, Preliminary investigation of the critically imperiled Caney Mountain cave crayfish Orconectes stygocaneyi Hobbs III, 2001 (Decapoda: Cambaridae) in Missouri, USA: Freshwater Crayfish, v. 25, no. 1, p. 47-57, https://doi.org/10.5869/fc.2020.v25-1.047.","productDescription":"11 p.","startPage":"47","endPage":"57","ipdsId":"IP-113351","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":396037,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Missouri","otherGeospatial":"Mud Lake","volume":"25","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-04-15","publicationStatus":"PW","contributors":{"authors":[{"text":"DiStefano, Robert J.","contributorId":213268,"corporation":false,"usgs":false,"family":"DiStefano","given":"Robert J.","affiliations":[{"id":16971,"text":"Missouri Department of Conservation","active":true,"usgs":false}],"preferred":false,"id":834913,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ashley, D.C.","contributorId":244487,"corporation":false,"usgs":false,"family":"Ashley","given":"D.C.","email":"","affiliations":[{"id":48915,"text":"Missouri Western State University","active":true,"usgs":false}],"preferred":false,"id":834914,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brewer, Shannon K. 0000-0002-1537-3921 skbrewer@usgs.gov","orcid":"https://orcid.org/0000-0002-1537-3921","contributorId":2252,"corporation":false,"usgs":true,"family":"Brewer","given":"Shannon","email":"skbrewer@usgs.gov","middleInitial":"K.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":834915,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mouser, J.B.","contributorId":244447,"corporation":false,"usgs":false,"family":"Mouser","given":"J.B.","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":834916,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Neimiller, M.","contributorId":279385,"corporation":false,"usgs":false,"family":"Neimiller","given":"M.","email":"","affiliations":[{"id":36730,"text":"University of Alabama","active":true,"usgs":false}],"preferred":false,"id":834917,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70214078,"text":"70214078 - 2020 - HESS opinions: Beyond the long-term water balance: Evolving Budyko's supply–demand framework for the Anthropocene towards a global synthesis of land-surface fluxes under natural and human-altered watersheds","interactions":[],"lastModifiedDate":"2020-09-22T16:00:25.192871","indexId":"70214078","displayToPublicDate":"2020-04-17T10:02:25","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1928,"text":"Hydrology and Earth System Sciences","active":true,"publicationSubtype":{"id":10}},"title":"HESS opinions: Beyond the long-term water balance: Evolving Budyko's supply–demand framework for the Anthropocene towards a global synthesis of land-surface fluxes under natural and human-altered watersheds","docAbstract":"Global hydroclimatic conditions have been substantially altered over the past century by anthropogenic influences that arise from the warming global climate and from local/regional anthropogenic disturbances. Traditionally, studies have used coupling of multiple models to understand how land-surface water fluxes vary due to changes in global climatic patterns and local land-use changes. We argue that because the basis of the Budyko framework relies on the supply and demand concept, the framework could be effectively adapted and extended to quantify the role of drivers – both changing climate and local human disturbances – in altering the land-surface response across the globe. We review the Budyko framework, along with these potential extensions, with the intent of furthering the applicability of the framework to emerging hydrologic questions. Challenges in extending the Budyko framework over various spatio-temporal scales and the use of global datasets to evaluate the water balance at these various scales are also discussed.
","language":"English","publisher":"European Geosciences Union","doi":"10.5194/hess-24-1975-2020","usgsCitation":"Sankarasubramanian, A., Wang, D., Archfield, S.A., Reitz, M., Vogel, R., Mazrooei, A., and Mukhopadhyaya, S., 2020, HESS opinions: Beyond the long-term water balance: Evolving Budyko's supply–demand framework for the Anthropocene towards a global synthesis of land-surface fluxes under natural and human-altered watersheds: Hydrology and Earth System Sciences, v. 24, p. 1975-1984, https://doi.org/10.5194/hess-24-1975-2020.","productDescription":"10 p.","startPage":"1975","endPage":"1984","ipdsId":"IP-116284","costCenters":[{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":457044,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/hess-24-1975-2020","text":"Publisher Index Page"},{"id":378673,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"24","noUsgsAuthors":false,"publicationDate":"2020-04-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Sankarasubramanian, A. 0000-0002-7668-1311","orcid":"https://orcid.org/0000-0002-7668-1311","contributorId":241034,"corporation":false,"usgs":false,"family":"Sankarasubramanian","given":"A.","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":799382,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wang, Dingbao","contributorId":166993,"corporation":false,"usgs":false,"family":"Wang","given":"Dingbao","email":"","affiliations":[{"id":18879,"text":"University of Central Florida","active":true,"usgs":false}],"preferred":false,"id":799383,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Archfield, Stacey A. 0000-0002-9011-3871 sarch@usgs.gov","orcid":"https://orcid.org/0000-0002-9011-3871","contributorId":1874,"corporation":false,"usgs":true,"family":"Archfield","given":"Stacey","email":"sarch@usgs.gov","middleInitial":"A.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":true,"id":799384,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Reitz, Meredith 0000-0001-9519-6103 mreitz@usgs.gov","orcid":"https://orcid.org/0000-0001-9519-6103","contributorId":196694,"corporation":false,"usgs":true,"family":"Reitz","given":"Meredith","email":"mreitz@usgs.gov","affiliations":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":799385,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vogel, Richard M","contributorId":241035,"corporation":false,"usgs":false,"family":"Vogel","given":"Richard M","affiliations":[{"id":6936,"text":"Tufts University","active":true,"usgs":false}],"preferred":false,"id":799386,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mazrooei, Amirhossein","contributorId":241036,"corporation":false,"usgs":false,"family":"Mazrooei","given":"Amirhossein","email":"","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":799387,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Mukhopadhyaya, Sudarshana","contributorId":241037,"corporation":false,"usgs":false,"family":"Mukhopadhyaya","given":"Sudarshana","email":"","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":799388,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70209734,"text":"70209734 - 2020 - A graphical causal model for resolving species identity effects and biodiversity–ecosystem function correlations","interactions":[],"lastModifiedDate":"2020-08-04T14:03:10.552315","indexId":"70209734","displayToPublicDate":"2020-04-17T09:21:10","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"A graphical causal model for resolving species identity effects and biodiversity–ecosystem function correlations","docAbstract":"Identifying and clearly communicating the drivers of ecosystem function is a crucially important goal for both basic and applied ecology. This has proven difficult because the putative causes (e.g., environment, species identity, biodiversity, and functional traits) are numerous and correlated. The problem is exacerbated by a lack of a formal framework for unambiguously relating theoretical language to precise, quantitative expressions of that language. Using a formal framework for the graphical expression of complex causal hypotheses, we developed a causal diagram of the concepts required to comprehensively test whether hypothesized sets of functional traits mediate the relationship between community structure and ecosystem function. We then used causal analysis, simulations, and field data to develop and test analytical strategies for understanding how community structure influences ecosystem functions via functional traits. Formal causal analysis showed that biodiversity–ecosystem function correlations are non‐causal associations. Using simulations, we showed how biodiversity correlations and species identity effects can arise from misspecification or incomplete mediation by functional trait composites. We also found that different types of model misspecification result in different patterns of residuals, which may be used to diagnose gaps in functional trait hypotheses. Treating the model misspecifications eliminated associations between species identity or biodiversity and ecosystem function. Finally, we provide an example of the analysis of field data to demonstrate how to use these insights to conduct a research program that has the goal of understanding the mechanistic trait relationships that link community structure to ecosystem function.","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecy.3070","usgsCitation":"Schoolmaster, D.R., Zirbel, C.R., and Cronin, J.P., 2020, A graphical causal model for resolving species identity effects and biodiversity–ecosystem function correlations: Ecology, v. 101, no. 8, e03070, 14 p., https://doi.org/10.1002/ecy.3070.","productDescription":"e03070, 14 p.","ipdsId":"IP-113577","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":374218,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"101","issue":"8","noUsgsAuthors":false,"publicationDate":"2020-06-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Schoolmaster, Donald R. Jr. 0000-0003-0910-4458 schoolmasterd@usgs.gov","orcid":"https://orcid.org/0000-0003-0910-4458","contributorId":4746,"corporation":false,"usgs":true,"family":"Schoolmaster","given":"Donald","suffix":"Jr.","email":"schoolmasterd@usgs.gov","middleInitial":"R.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":787702,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zirbel, Chad R 0000-0002-9289-1722","orcid":"https://orcid.org/0000-0002-9289-1722","contributorId":224302,"corporation":false,"usgs":false,"family":"Zirbel","given":"Chad","email":"","middleInitial":"R","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":787703,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cronin, James P. 0000-0001-6791-5828 jcronin@usgs.gov","orcid":"https://orcid.org/0000-0001-6791-5828","contributorId":5834,"corporation":false,"usgs":true,"family":"Cronin","given":"James","email":"jcronin@usgs.gov","middleInitial":"P.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":787704,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70209613,"text":"sir20205034 - 2020 - Updated study reporting levels (SRLs) for trace-element data collected for the California Groundwater Ambient Monitoring and Assessment (GAMA) Program Priority Basin Project, October 2009–October 2018","interactions":[],"lastModifiedDate":"2020-04-20T14:38:56.39101","indexId":"sir20205034","displayToPublicDate":"2020-04-16T14:28:17","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-5034","displayTitle":"Updated Study Reporting Levels (SRLs) for Trace-Element Data Collected for the California Groundwater Ambient Monitoring and Assessment (GAMA) Program Priority Basin Project, October 2009–October 2018","title":"Updated study reporting levels (SRLs) for trace-element data collected for the California Groundwater Ambient Monitoring and Assessment (GAMA) Program Priority Basin Project, October 2009–October 2018","docAbstract":"Groundwater samples have been collected in California as part of statewide investigations of groundwater quality conducted by the U.S. Geological Survey for the Groundwater Ambient Monitoring and Assessment (GAMA) Priority Basin Project (PBP) since 2004. The GAMA-PBP is being conducted in cooperation with the California State Water Resources Control Board to assess and monitor the quality of groundwater resources used for public and domestic drinking-water supply and to improve public knowledge of groundwater quality in California. Quality-control samples (including but not limited to field, equipment, and source-solution blanks) were collected to evaluate and quantify the quality of the groundwater sample results.
The GAMA-PBP previously determined study reporting levels (SRLs) for trace-element results based primarily on field blanks collected in California from May 2004 through March 2013. SRLs are raised reporting levels used to reduce the likelihood of reporting false detections attributable to contamination bias. The purpose of this report is to identify any changes in the pattern or magnitude of concentrations or detections in field blanks since the last evaluation that would require changing or ending the use of SRLs implemented in October 2009. Constituents analyzed were aluminum, antimony, arsenic, barium, beryllium, boron, cadmium, chromium, hexavalent chromium, cobalt, copper, iron, lead, lithium, manganese, molybdenum, nickel, selenium, silver, strontium, thallium, uranium, vanadium, and zinc.
For this review, data from 167 field blanks collected from October 2009 through October 2018 by the GAMA-PBP for trace elements were compiled. Based on a consistent pattern of decreasing cobalt and manganese concentrations in field blanks from 2009 to 2013, the GAMA-PBP decided to reevaluate all trace-element SRLs, effectively setting an end date for previously defined SRLs. Beginning October 2013, SRLs would be determined from field-blank data collected through October 2018. The detection frequency and upper limit of potential contamination bias (BD-90/90) were determined from field blanks for each trace element. The BD-90/90, that is, the upper 90-percent confidence limit of the 90th percentile concentration of potential extrinsic contamination, was calculated by assuming the binomial probability distribution. These results were compared to each constituent’s detection limit to determine whether an SRL was necessary to minimize the potential for detections in the groundwater samples, attributed principally to contamination bias. Results of the evaluation were used to set SRLs for trace-element data collected by the GAMA-PBP between October 2013 and October 2018. Trace elements prescribed an SRL based on this review were hexavalent chromium, cobalt, copper, lead, and zinc. This review also resulted in the removal of SRLs from iron, manganese, molybdenum, and nickel. Although an SRL for hexavalent chromium could not be evaluated in the earlier reviews because the data were not collected regularly until 2015, one was established herein as 0.34 micrograms per liter (µg/L). The SRL for cobalt, as previously implemented, had been to reject all results; it was changed to 0.16 µg/L following a reduction in cobalt field-blank detection frequency resulting from mitigation steps, starting in 2014, aimed at reducing contamination bias introduced by high-capacity capsule filters used during sample collection. The SRL for copper did not change, and the SRL for lead changed very little based on this review. Lastly, the SRL for zinc was lowered from 6.2 µg/L to 3.9 µg/L.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205034","collaboration":"A product of the California Groundwater Ambient Monitoring and Assessment ProgramDirector, California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
This five-year science plan outlines short-term and long-term goals for improving three-dimensional seismic velocity models in the greater San Francisco Bay region as well as how to foster a community effort in reaching those goals. The short-term goals focus on improving the current U.S. Geological Survey San Francisco Bay region geologic and seismic velocity model using existing data. The long-term goals focus on acquiring new data and leveraging better analytic tools to improve the model and characterize the uncertainty. The plan describes opportunities for contributions by members of the community to develop these seismic velocity models, provides current and potential users with general information on where efforts will likely be focused to improve these models and how new versions of the models will be released, and outlines funding needs and obstacles for improving and maintaining such models. Several aspects of this plan, including how to foster a community effort, are independent of the geographic region and apply to other similar efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201019","collaboration":"","usgsCitation":"Aagaard, B.T., Graymer, R.W., Thurber, C.H., Rodgers, A.J., Taira, T., Catchings, R.D., Goulet, C.A., and Plesch, A., 2020, Science plan for improving three-dimensional seismic velocity models in the San Francisco Bay region, 2019–24: U.S. Geological Survey Open-File Report 2020–1019, 37 p., https://doi.org/10.3133/ofr20201019.","productDescription":"vi, 37 p.","onlineOnly":"Y","ipdsId":"IP-112680","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":374023,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1019/coverthb.jpg"},{"id":374024,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1019/ofr20201019.pdf","text":"Report","size":"4.18 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1019"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.74999999999999,\n 36.527294814546245\n ],\n [\n -120.498046875,\n 36.527294814546245\n ],\n [\n -120.498046875,\n 39.11301365149975\n ],\n [\n -123.74999999999999,\n 39.11301365149975\n ],\n [\n -123.74999999999999,\n 36.527294814546245\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Geologic Hazards Science Center
U.S. Geological Survey
MS 966, Box 25046
Denver, CO 80225
Ecological research and management programs are increasingly using autonomous monitoring units (AMUs) to collect large volumes of acoustic and/or photo data to address pressing management objectives or research goals. The data management requirements of an AMU-based monitoring effort are often overwhelming, with a considerable amount of processing to translate raw data into models and analyses that have research and management utility. We created the r package AMMonitor to simplify the process of moving from remotely collected data to analysis and results, using a comprehensive SQLite database for data management that tracks all components of a remote monitoring program. This framework enables the tracking of analyses and research/management objectives through time. We illustrate the AMMonitor approach with the example of evaluating an occurrence-based management objective for a target species. First, we provide an overview of the database and data management approach. Next, we illustrate a few available workflows: temporally adaptive sampling, automated detection of species sounds from acoustic recordings and aggregation of automated detections into an encounter history for use in an occupancy analysis, the outcome of which can be analysed with respect to the motivating management objective. Without a comprehensive framework for efficiently moving from raw remote monitoring data collection to results and analysis, monitoring programs are limited in their capacity to systematically characterize ecological processes and inform management decisions through time. AMMonitor provides an option for such a framework. Code, comprehensive documentation, and step-by-step examples are available online at https://code.usgs.gov/vtcfwru/AMMonitor
There is a pressing need to monitor and understand the rapid land change happening around the world. The U.S. Geological Survey is developing a new capability, called Land Change Monitoring, Assessment, and Projection (LCMAP), to innovate the understanding of land change. This capability is the Earth Resources Observation and Science Center's foundation for an integrated U.S. Geological Survey-wide land change science framework. LCMAP supports the development of consistent data and land cover products spanning large geographic extents, over extended periods, and at a higher frequency than in the past. LCMAP provides solutions to the science and management communities’ growing need for an improved understanding of the fundamental drivers of land change, the consequences of change in human and natural systems, and feedbacks associated with land change processes.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20203024","usgsCitation":"Rover, J., Brown, J.F., Auch, R.F., Sayler, K.L., Sohl, T.L., Tollerud, H.J., and Xian, G.Z., 2020, Land change monitoring, assessment, and projection: U.S. Geological Survey Fact Sheet 2020–3024, 4 p., https://doi.org/10.3133/fs20203024.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"N","ipdsId":"IP-115689 ","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":374013,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2020/3024/coverthb.jpg"},{"id":374014,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2020/3024/fs20203024.pdf","text":"Report","size":"16.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2020–3024"}],"contact":"Customer Service, Earth Resources Observation and Science Center (EROS)
U.S. Geological Survey
47914 252d Street
Sioux Falls, SD 57198
https://www.usgs.gov/land-resources/eros/lcmap
","tableOfContents":"Passive groundwater sampling is defined as the collection of a water sample from a well without the use of purging by a pump or retrieval by a bailer (Interstate Technology and Regulatory Council [ITRC], 2006; American Society for Testing and Materials [ASTM], 2014). No purging means that advection of water is not involved in collecting the water sample from the well. Passive samplers rely on diffusion as the primary process that drives their collection of chemical constituents. Diffusion is the transport of chemicals caused by the presence of a chemical gradient. Chemicals tend to move or diffuse from areas of higher concentration to areas of lower concentration to reach an average or equilibrium concentration. Passive sampling of groundwater relies on the ambient exchange of groundwater in the formation with water in the screened or open interval of a well. In this report, the term formation is used to describe all saturated hydrogeologic units that yield water to a well. If the well opening is unclogged and free of a film of deposits from physical turbidity or chemical precipitation, then the exchange of groundwater is likely adequate, and the water in the open interval will be representative of water in the formation. In some cases, the passive sample from the well opening can be more representative of groundwater from the formation than a sample collected by pumping if pumping induces mixing of water in the open interval with stagnant casing water that has undergone chemical alteration (Harte and others, 2018). In most cases, passive sampling will better represent the ambient groundwater chemistry flowing through the open interval of a well because pumping may capture water of different chemistry from downgradient or lateral areas that would not normally pass through the well. Three basic types of passive samplers are discussed in this report. The first type of passive sampler is the equilibrium-membrane type, which includes a semi-permeable membrane through which chemicals diffuse or permeate. Permeation is simply the process of water or chemicals moving through openings in the membrane. The authors contend that permeation is dominated by diffusion for many of the passive samplers discussed in this report. Some passive equilibrium-membrane-type samplers allow most types of chemical constituents through, whereas others allow the diffusion of only selected groups of chemicals. Once the chemical constituents are inside the membrane, they are retained by the equilibration of concentrations inside the sampler with those outside the sampler. The second type of passive sampler is an equilibrium-thief type, which has no semi-permeable membrane. Chemical constituents simply move through the openings in the body of the sampler either initially through advection and dispersion or over time primarily by diffusion. Chemical constituents reach equilibrium between the water in the sampler and the water in the well and are captured in the sampler when the sampler is closed. The third type of passive sampler is an accumulation-type sampler that contains sorptive media. Selected chemical constituents are sorbed onto the media that the sampler contains for later extraction and analysis. Although passive samplers have been available for more than 15 years (from present [2020]), their use by U.S. Geological Survey (USGS) hydrologists and hydrologic technicians to monitor groundwater quality largely has been limited to selected research studies. The authors believe that this may be the result of (1) a lack of exposure of most USGS personnel to passive samplers and the uses of these samplers and (2) the lack of a USGS-approved protocol for the proper use of these samplers by USGS personnel. This report is an effort to fill those two needs. The focus of this report is on hydraulic, hydrologic, and chemical considerations in the application of passive samplers and interpretation of groundwater chemistry results obtained using passive samplers in wells. This report describes the differences between purging and passive sampling methods in groundwater and explains how and why passive samplers work. The report points out the advantages and limitations of passive samplers in general and for each particular type of passive sampler. Important considerations to be taken into account prior to the use of passive samplers are discussed, such as defining the data-quality objectives, the water-quality constituents to be sampled, sample volumes required for analysis, well construction of the sampling network, and the geologic formations that will be sampled. Potential applications of passive samplers also are discussed, such as chemical-vertical profiling of wells. A general field protocol for the deployment, recovery, and sample collection using these devices is described, and some overall guidance for the practitioner with application examples is given. Comparison methods used to evaluate results from passive sampling versus purge sampling also are discussed.
","largerWorkTitle":"","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm1D8","collaboration":"","usgsCitation":"Imbrigiotta, T.E., and Harte, P.T., 2020, Passive sampling of groundwater wells for determination of water chemistry: U.S. Geological Survey Techniques and Methods, chap. 8, section D, book 1, 80 p., https://doi.org/10.3133/tm1d8.\n","productDescription":"ix, 80 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-082895","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":373983,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/01/d8/coverthb.jpg"},{"id":373984,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/01/d8/tm1d8.pdf","text":"Report","size":"4.50 MB","linkFileType":{"id":1,"text":"pdf"},"description":"TM 1-D8"}],"publicComments":"This report is Chapter 8 of Section D: Water quality in Book 1: Collection of water data by direct measurement","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
Director, New Jersey Water Science Center
U.S. Geological Survey
3450 Princeton Pike, Suite 110
Lawrenceville, NJ 08648
Groundwater piezometers and lake stilling wells were deployed as paired sets at 10 locations in Upper Klamath Lake in south-central Oregon from May to October 2017 to measure hydraulic heads in and beneath the lake. Continuous water-level data from piezometers and stilling wells were then used to calculate the vertical hydraulic gradient (VHG) across the sediment-water interface to determine the direction and relative magnitude of the movement of water between the lake and underlying sediments. Over the study period, heads in lake-bed sediments closely tracked lake levels, both decreasing from spring into autumn. Instantaneous VHG was highly dynamic at all sites and exhibited high-frequency (less than 1 day to less than 1 hour) variations in magnitude and direction. Instantaneous and weekly mean VHG values often exceeded, but were commonly within, the range of measurement uncertainty (VHG less than +0.009 foot per foot [ft/ft] and greater than -0.009 ft/ft). 63 percent of instantaneous VHG values and 66 percent of weekly mean VHG values were within this range. Study period mean VHG was within measurement uncertainty at seven of the nine sites that had continuous water-level data, but two littoral sites (LC03 and LS01) had positive (upward) values greater than measurement uncertainty and are likely locations of vertical groundwater seepage. Data collected in this study provide new information about the hydraulic conditions at the sediment-water interface in UKL and demonstrate that sediment-groundwater exchange in UKL is spatially and temporally heterogeneous.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205029","collaboration":"","usgsCitation":"Corson-Dosch, N.T., 2020, Benthic vertical hydraulic gradients in Upper Klamath Lake, Oregon, 2017: U.S. Geological Survey Scientific Investigations Report 2020–5029, 22 p., https://doi.org/10.3133/sir20205029.","productDescription":"Report: v, 22 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-102002","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":374017,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7668CGD","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Depth-to-water data and calculated vertical hydraulic gradient at the sediment-water interface in Upper Klamath Lake, Oregon, 2017"},{"id":374016,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5029/sir20205029.pdf","text":"Report","size":"2.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5029"},{"id":374015,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5029/coverthb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Upper Klamath Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.08694458007812,\n 42.218347726793304\n ],\n [\n -121.77246093750001,\n 42.218347726793304\n ],\n [\n -121.77246093750001,\n 42.61273829368574\n ],\n [\n -122.08694458007812,\n 42.61273829368574\n ],\n [\n -122.08694458007812,\n 42.218347726793304\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201
Drought, coupled with rising temperatures, is an emerging threat to many forest types across the globe. At least to a degree, we expect management actions that reduce competition (e.g., thinning, prescribed fire, or both) to improve growth of residual trees during drought. The influences of management actions and drought on individual tree growth may be measured with high precision using tree-rings. Here, we summarize tree-ring-based assessments of the effectiveness of thinning and prescribed fire as drought adaptation tools, with special consideration for how these findings might apply to dry coniferous forests in the southwestern United States. The existing literature suggests that thinning treatments generally improve individual tree growth responses to drought, though the literature specific to southwestern coniferous forests is sparse. Assessments from studies beyond the southwestern United States indicate treatment effectiveness varies by thinning intensity, timing of the drought relative to treatments, and individualistic species responses. Several large-scale studies appear to conflict on specifics of how site aridity influences sensitivity to drought following thinning. Prescribed fire effects in the absence of thinning has received much less attention in terms of subsequent drought response. There are limitations for using tree-ring data to estimate drought responses (e.g., difficulties scaling up observations to stand- and landscape-levels). However, tree-rings describe an important dimension of drought effects for individual trees, and when coupled with additional information, such as stable isotopes, aid our understanding of key physiological mechanisms that underlie forest drought response.
","language":"English","publisher":"Frontiers","doi":"10.3389/ffgc.2020.00041","usgsCitation":"van Mantgem, P., Kerhoulas, L., Sherriff, R.L., and Wenderott, Z.J., 2020, Tree-ring evidence of forest management moderating drought responses: Implications for dry, coniferous forests in the southwestern United States: Frontiers in Forests and Global Change, v. 3, 41, 7 p., https://doi.org/10.3389/ffgc.2020.00041.","productDescription":"41, 7 p.","ipdsId":"IP-114937","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":457070,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/ffgc.2020.00041","text":"Publisher Index Page"},{"id":376947,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, California, New Mexico, Nevada, Utah","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -102.9638671875,\n 32.13840869677249\n ],\n [\n -102.9638671875,\n 37.020098201368114\n ],\n [\n -109.2041015625,\n 37.09023980307208\n ],\n [\n -109.16015624999999,\n 41.21172151054787\n ],\n [\n -111.0498046875,\n 41.04621681452063\n ],\n [\n -111.1376953125,\n 42.00032514831621\n ],\n [\n -124.1455078125,\n 42.13082130188811\n ],\n [\n -124.76074218749999,\n 40.58058466412761\n ],\n [\n -123.662109375,\n 37.71859032558816\n ],\n [\n -120.89355468749999,\n 34.379712580462204\n ],\n [\n -117.20214843749999,\n 32.58384932565662\n ],\n [\n -114.78515624999999,\n 32.731840896865684\n ],\n [\n -111.0498046875,\n 31.316101383495624\n ],\n [\n -108.10546875,\n 31.240985378021307\n ],\n [\n -108.10546875,\n 31.840232667909365\n ],\n [\n -105.8203125,\n 31.840232667909365\n ],\n [\n -105.732421875,\n 32.21280106801518\n ],\n [\n -102.9638671875,\n 32.13840869677249\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"3","noUsgsAuthors":false,"publicationDate":"2020-04-15","publicationStatus":"PW","contributors":{"authors":[{"text":"van Mantgem, Phillip J. 0000-0002-3068-9422","orcid":"https://orcid.org/0000-0002-3068-9422","contributorId":204320,"corporation":false,"usgs":true,"family":"van Mantgem","given":"Phillip J.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":794668,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kerhoulas, Lucy P","contributorId":236908,"corporation":false,"usgs":false,"family":"Kerhoulas","given":"Lucy P","affiliations":[{"id":47564,"text":"Humboldt State University, Department of Forestry and Wildland Resources, Arcata, CA, USA","active":true,"usgs":false}],"preferred":false,"id":794669,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sherriff, Rosemary L.","contributorId":204199,"corporation":false,"usgs":false,"family":"Sherriff","given":"Rosemary","email":"","middleInitial":"L.","affiliations":[{"id":7067,"text":"Humboldt State University","active":true,"usgs":false}],"preferred":false,"id":794670,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wenderott, Zachary James 0000-0002-4669-770X","orcid":"https://orcid.org/0000-0002-4669-770X","contributorId":236909,"corporation":false,"usgs":true,"family":"Wenderott","given":"Zachary","email":"","middleInitial":"James","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":794671,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70227129,"text":"70227129 - 2020 - Methods for rapidly estimating velocity precision from GNSS time series in the presence of temporal correlation: A new method and comparison of existing methods","interactions":[],"lastModifiedDate":"2022-01-03T15:57:57.793919","indexId":"70227129","displayToPublicDate":"2020-04-15T08:04:06","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2312,"text":"Journal of Geophysical Research","active":true,"publicationSubtype":{"id":10}},"title":"Methods for rapidly estimating velocity precision from GNSS time series in the presence of temporal correlation: A new method and comparison of existing methods","docAbstract":"Time series of position estimates from Global Navigational Satellite System (GNSS) are used to measure the velocities of points on the surface of the Earth. Along with the velocity estimates, a measure of the precision is needed to assess the quality of the velocity measurement. Here, I evaluate rate uncertainties provided by four different methods that have been applied to geodetic time series. The most rigorous approach uses a data covariance that incorporates a variety of noise processes relevant to geodetic time series but is computationally demanding. Two other approaches are efficient algorithms and are used widely, but both can provide less rigorous estimates of the rate uncertainty. I propose and evaluate a fourth method, which provides estimates of rate uncertainty closer to the rigorous approach but is significantly less computationally demanding. I have evaluated all three methods against the more rigorous method using both simulations and time series from 190 GNSS sites. For data best characterized as having a flicker type noise process, one of the widely used methods overestimates the uncertainty by up to a factor of 2, while the other widely used method underestimates the uncertainty by less than a factor of 2. For a random-walk process, both methods underestimate the rate uncertainty by a factor of 3 to 5.
Bathymetric and velocimetric data were collected by the U.S. Geological Survey, in cooperation with the Missouri Department of Transportation, near 10 bridges at 9 highway crossings of the Missouri River between Kansas City and St. Louis, Missouri, from May 22 to 31, 2017. A multibeam echosounder mapping system was used to obtain channel-bed elevations for river reaches ranging from 1,550 to 1,840 feet longitudinally and generally extending laterally across the active channel from bank to bank during moderate flood flow conditions. These surveys indicate the channel conditions at the time of the surveys and provide characteristics of scour holes that may be useful in the development of predictive guidelines or equations for scour holes. These data also may be useful to the Missouri Department of Transportation as a low to moderate flood flow comparison to help assess the bridges for stability and integrity issues with respect to bridge scour during floods.
Bathymetric data were collected around every pier that was in water, except those at the edge of water, and scour holes were observed at most surveyed piers. Occasionally, the scour hole near a pier was difficult to discern from nearby bed features. The observed scour holes at the surveyed bridges were generally examined with respect to shape and depth.
Although exposure of parts of substructural support elements was observed at several piers, at most sites the exposure likely can be considered minimal compared to the overall substructure that remains buried in bed material at these piers. The notable exceptions are piers 4 and 5 at structure K0999 on Missouri State Highway 41 at Miami, Mo.; piers 2 and 3 at structure G0069 on Missouri State Highway 240 at Glasgow, Mo.; and pier 5 at structure A4574 on Missouri State Highway 5 at Boonville, Mo. At these structures, the bed-material thickness between the bottom of the scour hole and bedrock was less than 6 feet.
Pier size, nose shape, and alignment to flow had a profound effect on the size of the scour hole observed for a given pier. Narrow piers having round or sharp noses that were aligned with flow often had scour holes that were difficult to discern from nearby bed features, whereas piers having wide or blunt noses resulted in larger, deeper scour holes. Several structures had piers that were skewed to primary approach flow, and scour holes near these piers generally indicated deposition on the leeward side of the pier and greater depth on the side of the pier with impinging flow. A riprap blanket constructed in 2015 around pier 4 of structures L0550 and A4497 on U.S. Highway 54 at Jefferson City, Mo., effectively mitigates the scour observed near those piers in previous surveys.
Previous bathymetric surveys exist for all the sites examined in this study. Bathymetric surfaces from a nonflood survey in 2013 and a flood survey in July 2011 at most of the sites are compared to the 2017 survey surfaces. The average channel-bed elevation at structure A4574 was remarkably similar in all three surveys and higher than what might be implied by a trendline along the reach between Kansas City and St. Louis, which may indicate this site is at or near a local feature that controls sediment deposition and scour.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205018","collaboration":"Prepared in cooperation with the Missouri Department of Transportation","usgsCitation":"Huizinga, R.J., 2020, Bathymetric and velocimetric surveys at highway bridges crossing the Missouri River between Kansas City and St. Louis, Missouri, May 22–31, 2017: U.S. Geological Survey Scientific Investigations Report 2020–5018, 104 p., https://doi.org/10.3133/sir20205018.\n","productDescription":"Report: x, 104 p.; Data Releases","numberOfPages":"118","onlineOnly":"Y","ipdsId":"IP-110170","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":373939,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9L6GW57","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Bathymetry and velocity data from surveys at highway bridges crossing the Missouri River in Kansas City, Missouri, March 2010 through May 2017"},{"id":372633,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5018/coverthb.jpg"},{"id":373938,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5018/sir20205018.pdf","text":"Report","size":"23.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5018"},{"id":373940,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P94M4US7","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Bathymetry and velocity data from surveys at highway bridges crossing the Missouri River between Kansas City and St. Louis, Missouri, January 2010 through May 2017"}],"country":"United States","state":"Missouri","city":"Kansas City, St. Louis","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.142822265625,\n 38.805470223177466\n ],\n [\n -91.12060546875,\n 38.92522904714054\n ],\n [\n -92.16430664062499,\n 39.08743603215884\n ],\n [\n -93.2958984375,\n 39.04478604850143\n ],\n [\n -94.119873046875,\n 39.12153746241925\n ],\n [\n -94.68017578125,\n 39.198205348894795\n ],\n [\n -94.63623046875,\n 38.91668153637508\n ],\n [\n -94.04296874999999,\n 38.865374851611634\n ],\n [\n -93.109130859375,\n 38.79690830348427\n ],\n [\n -92.274169921875,\n 38.85682013474361\n ],\n [\n -91.91162109375,\n 38.81403111409755\n ],\n [\n -91.29638671875,\n 38.69408504756833\n ],\n [\n -90.648193359375,\n 38.659777730712534\n ],\n [\n -90.186767578125,\n 38.57393751557591\n ],\n [\n -90.142822265625,\n 38.805470223177466\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
1400 Independence Road
Rolla, MO 65401
Black abalone Haliotis cracherodii Leach, 1814 are known to feed on drift plant macrodetritus moved about in the intertidal zone by waves and currents. Drift capture is a trait shared by at least several other abalone species. Drift materials are entrapped beneath the anterior foot and held for ingestion. The quantitative significance of feeding on entrapped drift macrodetritus for black abalone is unknown. Furthermore, there are no published data on the extent to which local and mesoscale spatial distributions of source plant populations influence the composition of drift plant material in black abalone diet as acquired by entrapment. From February 1982 through March 2019, occurrences of macrodetrital entrapment by black abalone were observed in nine rocky intertidal study plots, with a summed surface area of 2,054 m2, on the periphery of San Nicolas Island (SNI), California (Island centroid at ∼33.25°, –119.50°). A small preliminary survey and 27 complete surveys were performed during the study period (mean of ∼1.4 y between complete surveys). During the study, more than 1.5 × 105 black abalone were examined. The total likely included repeated observations of many individuals as a result of the known longevity and limited mobility of the species. Of those observed, ∼1.65 × 103 black abalone were recorded as apparently ingesting entrapped items. Frequency data were dominated (∼95% of all records) by three species of kelp Macrocystis pyrifera (Linnaeus) C. Agardh; commonly known as “giant kelp”, Egregia menziesii (Turner), and Eisenia arborea Areschoug. Of those, giant kelp was the most frequently observed entrapped category (∼76%). Living, attached giant kelp is rarely observed in intertidal habitats at SNI, and it follows that utilization of giant kelp by black abalone requires physical importation of the kelp from other locations. Frequencies of occurrence of giant kelp entrapment by individual study site were clearly associated with the relative surface canopy sizes and persistence patterns of offshore kelp forests adjacent (≤2 km) to the respective study sites. The pattern suggests that subsidies of drift giant kelp to black abalone diet involve mesoscale physical processes largely proximate to SNI but probably not subsidies from more distant locations such as other islands or the California mainland. Utilization of other frequently recorded kelps as food by black abalone likely involves spatial subsidies as well, but on smaller scales of distance (∼10–100 m for E. arborea; ∼0–100 m for E. menziesii). In the context of the imperiled status of black abalone, recovery actions may include outplants of captive-reared animals or transplantation of wild animals from other populations. For such actions, data from SNI suggest a need for consideration of scales of separation among release locations and nearby populations of the three apparently predominant kelp species in black abalone diet.
The Fort Berthold Reservation is in west-central North Dakota and home to the Three Affiliated Tribes. The primary water-resources concerns on the Fort Berthold Reservation are associated with the different types of land uses from agricultural activities and the rapid development of oil and gas resources in western North Dakota. The Three Affiliated Tribes Environmental Department identified the need for long-term water-quality monitoring throughout the Fort Berthold Reservation to better understand the potential effects on surface-water and groundwater quality and to determine if water quality is changing with time. The U.S. Geological Survey, in cooperation with the Three Affiliated Tribes, identified surface-water sites and groundwater wells that represent the water resources in major drainages and the most utilized aquifers on the reservation. A water-quality monitoring program was designed to address data gaps and provide consistent long-term data that can be used to identify potential effects on water quality. During 2014–17, the initial water-quality sampling efforts associated with this program were completed. The efforts provide a current (2019) characterization of water-quality conditions in surface water and groundwater and can assist in establishing a long-term water-quality monitoring program
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205020","collaboration":"Prepared in cooperation with the Three Affiliated Tribes","usgsCitation":"Lundgren, R.F., and Iorio, M.J., 2020, Characterization of surface-water and groundwater quality on the Fort Berthold Reservation, North Dakota, 2014–17: U.S. Geological Survey Scientific Investigations Report 2020–5020, 37 p., https://doi.org/10.3133/sir20205020.","productDescription":"Report: vii, 37 p.; 1 Table; 6 Appendix Tables","numberOfPages":"50","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-112739","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":373821,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5020/sir20205020.pdf","text":"Report","size":"8.60 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5020"},{"id":373822,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2020/5020/sir20205020_table2.xlsx","text":"Table 2","size":"16.1 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2020–5020 Table 2","linkHelpText":"– Site information for groundwater wells sampled on Fort Berthold Reservation, North Dakota, 2014–17"},{"id":373824,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5020/sir20205020_appendix_table1.2.xlsx","text":"Appendix Table 1.2","size":"30.0 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2020–5020 Appendix Table 1.2","linkHelpText":"– Quality-assurance data collected for additional constituents on Fort Berthold Reservation, North Dakota, 2014–17"},{"id":373825,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5020/sir20205020_appendix_table1.3.xlsx","text":"Appendix Table 1.3","size":"30.5 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2020–5020 Appendix Table 1.3","linkHelpText":"– Summary statistics for water-quality constituents analyzed but not selected for additional discussion in surface water on Fort Berthold Reservation, 2014–17"},{"id":373826,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5020/sir20205020_appendix_table1.4.xlsx","text":"Appendix Table 1.4","size":"21.3 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2020–5020 Appendix Table 1.4","linkHelpText":"– Summary statistics for historical water-quality constituents at surface-water sites on Fort Berthold Reservation, August 1966 through April 2014"},{"id":373827,"rank":8,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5020/sir20205020_appendix_table1.5.xlsx","text":"Appendix Table 1.5","size":"31.1 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2020–5020 Appendix Table 1.5","linkHelpText":"– Summary statistics for water-quality constituents analyzed but not selected for additional discussion in groundwater on Fort Berthold Reservation, 2014–17"},{"id":373828,"rank":9,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5020/sir20205020_appendix_table2.1.xlsx","text":"Appendix Table 2.1","size":"593 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2020–5020 Appendix Table 2.1","linkHelpText":"– Summary statistics for historical water-quality constituents in major aquifers on Fort Berthold Reservation, North Dakota"},{"id":373823,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5020/sir20205020_appendix_table1.1.xlsx","text":"Appendix Table 1.1","size":"18.8 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2020–5020 Appendix Table 1.1","linkHelpText":"– Quality-assurance data collected for selected constituents on Fort Berthold Reservation, North Dakota, 2014–17"},{"id":373820,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5020/coverthb.jpg"}],"country":"United States","state":"North Dakota","otherGeospatial":" Fort Berthold Reservation","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -102.79632568359374,\n 47.428087261714275\n ],\n [\n -101.84326171874999,\n 47.42622912485741\n ],\n [\n -101.84875488281249,\n 47.68018294648414\n ],\n [\n -101.87896728515624,\n 48.004625021133904\n ],\n [\n -102.79632568359374,\n 48.01381248943335\n ],\n [\n -102.79632568359374,\n 47.428087261714275\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Dakota Water Science Center
U.S. Geological Survey
821 East Interstate Avenue
Bismarck, ND 58503
1608 Mountain View Road
Rapid City, SD 57702
Streamflow observations can be used to understand, predict, and contextualize hydrologic, ecological, and biogeochemical processes and conditions in streams. Stream gages are point measurements along rivers where streamflow is measured, and are often used to infer upstream watershed‐scale processes. When stream gages read zero, this may indicate that the stream has dried at this location; however, zero‐flow readings can also be caused by a wide range of other factors. Our ability to identify whether or not a zero‐flow gage reading indicates a dry fluvial system has far reaching environmental implications. Incorrect identification and interpretation by the data user can lead to inaccurate hydrologic, ecological, and/or biogeochemical predictions from models and analyses. Here, we describe several causes of zero‐flow gage readings: frozen surface water, flow reversals, instrument error, and natural or human‐driven upstream source losses or bypass flow. For these examples, we discuss the implications of zero‐flow interpretations. We also highlight additional methods for determining flow presence, including direct observations, statistical methods, and hydrologic models, which can be applied to interpret causes of zero‐flow gage readings and implications for reach‐ and watershed‐scale dynamics. Such efforts are necessary to improve our ability to understand and predict surface flow activation, cessation, and connectivity across river networks. Developing this integrated understanding of the wide range of possible meanings of zero‐flows will only attain greater importance in a more variable and changing hydrologic climate.
","language":"English","publisher":"Wiley","doi":"10.1002/wat2.1436","usgsCitation":"Zimmer, M., Kaiser, K.E., Blaszczak, J., Zipper, S., Hammond, J., Fritz, K.M., Costigan, K., Hosen, J.D., Godsey, S., Allen, G.H., Kampf, S.K., Burrow, R., Krabbenhoft, C., Dodds, W., Hale, R., Olden, J., Shanafield, M., DelVecchia, A., Ward, A.S., Mims, M.C., Datry, T., Bogan, M.A., Boersma, K., Busch, M., Jones, N.M., Burgin, A., and Allen, D., 2020, Zero or not? Causes and consequences of zero-flow stream gage readings: WIREs Water, v. 7, no. 3, e1436, 25 p., https://doi.org/10.1002/wat2.1436.","productDescription":"e1436, 25 p.","ipdsId":"IP-112480","costCenters":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"links":[{"id":457103,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/wat2.1436","text":"External Repository"},{"id":437027,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9R84W5K","text":"USGS data release","linkHelpText":"Contiguous US and Global streamflow gages measuring zero flow"},{"id":437026,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9AB3KL9","text":"USGS data release","linkHelpText":"Sub-annual streamflow responses to rainfall and snowmelt inputs in snow-dominated watersheds of the western U.S."},{"id":375452,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"3","noUsgsAuthors":false,"publicationDate":"2020-04-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Zimmer, Margaret 0000-0001-8287-1923","orcid":"https://orcid.org/0000-0001-8287-1923","contributorId":225158,"corporation":false,"usgs":false,"family":"Zimmer","given":"Margaret","affiliations":[{"id":41054,"text":"Earth and Planetary Sciences, University of California, Santa Cruz, CA, 95064, USA","active":true,"usgs":false}],"preferred":false,"id":790580,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kaiser, Kendra E. 0000-0003-1773-6236","orcid":"https://orcid.org/0000-0003-1773-6236","contributorId":211475,"corporation":false,"usgs":false,"family":"Kaiser","given":"Kendra","email":"","middleInitial":"E.","affiliations":[{"id":38255,"text":"Boise State Unviersity","active":true,"usgs":false}],"preferred":false,"id":790581,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Blaszczak, Joanna 0000-0001-5122-0829","orcid":"https://orcid.org/0000-0001-5122-0829","contributorId":225159,"corporation":false,"usgs":false,"family":"Blaszczak","given":"Joanna","email":"","affiliations":[{"id":41055,"text":"Natural Resources and Environmental Science, University of Nevada, Reno, NV 89557, USA","active":true,"usgs":false}],"preferred":false,"id":790582,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zipper, Samuel 0000-0002-8735-5757","orcid":"https://orcid.org/0000-0002-8735-5757","contributorId":225160,"corporation":false,"usgs":false,"family":"Zipper","given":"Samuel","email":"","affiliations":[{"id":41056,"text":"Kansas Geological Survey, University of Kansas, Lawrence KS 66047, USA","active":true,"usgs":false}],"preferred":false,"id":790583,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"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":790584,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fritz, Ken M. 0000-0002-3831-2531","orcid":"https://orcid.org/0000-0002-3831-2531","contributorId":203959,"corporation":false,"usgs":false,"family":"Fritz","given":"Ken","email":"","middleInitial":"M.","affiliations":[{"id":36773,"text":"USEPA NERL","active":true,"usgs":false}],"preferred":false,"id":790585,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Costigan, Katie H.","contributorId":166700,"corporation":false,"usgs":false,"family":"Costigan","given":"Katie H.","affiliations":[],"preferred":false,"id":790586,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hosen, Jacob D.","contributorId":149188,"corporation":false,"usgs":false,"family":"Hosen","given":"Jacob","email":"","middleInitial":"D.","affiliations":[{"id":17663,"text":"Chesapeake Biological Laboratory, University of Maryland Center for Environmental Science, Solomons, Maryland, United States","active":true,"usgs":false}],"preferred":false,"id":790587,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Godsey, Sarah E","contributorId":223120,"corporation":false,"usgs":false,"family":"Godsey","given":"Sarah E","affiliations":[{"id":38154,"text":"Idaho State University","active":true,"usgs":false}],"preferred":false,"id":790588,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Allen, George H. 0000-0001-8301-5301","orcid":"https://orcid.org/0000-0001-8301-5301","contributorId":225161,"corporation":false,"usgs":false,"family":"Allen","given":"George","middleInitial":"H.","affiliations":[{"id":41057,"text":"Department of Geography, Texas A&M University, College Station, TX, 77843","active":true,"usgs":false}],"preferred":false,"id":790589,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Kampf, Stephanie K. 0000-0001-8991-2679","orcid":"https://orcid.org/0000-0001-8991-2679","contributorId":225146,"corporation":false,"usgs":false,"family":"Kampf","given":"Stephanie","email":"","middleInitial":"K.","affiliations":[{"id":41048,"text":"Associate Professor, Department of Ecosystem Science and Sustainability, Colorado State University","active":true,"usgs":false}],"preferred":false,"id":790590,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Burrow, Ryan 0000-0002-3296-1864","orcid":"https://orcid.org/0000-0002-3296-1864","contributorId":225162,"corporation":false,"usgs":false,"family":"Burrow","given":"Ryan","email":"","affiliations":[{"id":41058,"text":"Australian Rivers Institute, Griffith University, Brisbane, Queensland, Australia 4111","active":true,"usgs":false}],"preferred":false,"id":790591,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Krabbenhoft, Corey 0000-0002-2630-8287","orcid":"https://orcid.org/0000-0002-2630-8287","contributorId":225163,"corporation":false,"usgs":false,"family":"Krabbenhoft","given":"Corey","email":"","affiliations":[{"id":41059,"text":"College of Arts and Sciences and Research and Education in Energy, Environment and Water (RENEW) Institute, University at Buffalo, Buffalo, NY 14228","active":true,"usgs":false}],"preferred":false,"id":790592,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Dodds, Walter 0000-0002-6666-8930","orcid":"https://orcid.org/0000-0002-6666-8930","contributorId":225164,"corporation":false,"usgs":false,"family":"Dodds","given":"Walter","email":"","affiliations":[{"id":41060,"text":"Division of Biology, Kansas State University, Manhattan, KS 66502","active":true,"usgs":false}],"preferred":false,"id":790593,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Hale, Rebecca 0000-0002-3552-3691","orcid":"https://orcid.org/0000-0002-3552-3691","contributorId":195753,"corporation":false,"usgs":false,"family":"Hale","given":"Rebecca","email":"","affiliations":[{"id":12865,"text":"Smithsonian Institute","active":true,"usgs":false}],"preferred":false,"id":790594,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Olden, Julian D.","contributorId":202893,"corporation":false,"usgs":false,"family":"Olden","given":"Julian D.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":790595,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Shanafield, Margaret","contributorId":196916,"corporation":false,"usgs":false,"family":"Shanafield","given":"Margaret","email":"","affiliations":[],"preferred":false,"id":790596,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"DelVecchia, Amanda 0000-0003-4252-5991","orcid":"https://orcid.org/0000-0003-4252-5991","contributorId":225165,"corporation":false,"usgs":false,"family":"DelVecchia","given":"Amanda","email":"","affiliations":[{"id":41061,"text":"Flathead Lake Biological Station, University of Montana, Polson, MT 59860","active":true,"usgs":false}],"preferred":false,"id":790597,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Ward, Adam S","contributorId":191363,"corporation":false,"usgs":false,"family":"Ward","given":"Adam","email":"","middleInitial":"S","affiliations":[],"preferred":false,"id":790598,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Mims, Meryl C. 0000-0003-0570-988X","orcid":"https://orcid.org/0000-0003-0570-988X","contributorId":209951,"corporation":false,"usgs":false,"family":"Mims","given":"Meryl","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":790599,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Datry, Thibault 0000-0003-1390-6736","orcid":"https://orcid.org/0000-0003-1390-6736","contributorId":225166,"corporation":false,"usgs":false,"family":"Datry","given":"Thibault","email":"","affiliations":[{"id":41062,"text":"Centre de Lyon-Villeurbanne, 69626 Villeurbanne CEDEX, France","active":true,"usgs":false}],"preferred":false,"id":790600,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Bogan, Michael A.","contributorId":196745,"corporation":false,"usgs":false,"family":"Bogan","given":"Michael","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":790601,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Boersma, Kate 0000-0002-0707-3283","orcid":"https://orcid.org/0000-0002-0707-3283","contributorId":225167,"corporation":false,"usgs":false,"family":"Boersma","given":"Kate","email":"","affiliations":[{"id":41063,"text":"Department of Biology, University of San Diego, San Diego, CA 92105, USA","active":true,"usgs":false}],"preferred":false,"id":790602,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Busch, Michelle 0000-0003-4536-3000","orcid":"https://orcid.org/0000-0003-4536-3000","contributorId":225168,"corporation":false,"usgs":false,"family":"Busch","given":"Michelle","email":"","affiliations":[{"id":41064,"text":"Department of Biology, University of Oklahoma, Norman OK, 73019","active":true,"usgs":false}],"preferred":false,"id":790603,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Jones, Nathan M.","contributorId":177996,"corporation":false,"usgs":false,"family":"Jones","given":"Nathan","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":790604,"contributorType":{"id":1,"text":"Authors"},"rank":25},{"text":"Burgin, Amy","contributorId":140223,"corporation":false,"usgs":false,"family":"Burgin","given":"Amy","email":"","affiliations":[{"id":13420,"text":"Wright State Univ.","active":true,"usgs":false}],"preferred":false,"id":790605,"contributorType":{"id":1,"text":"Authors"},"rank":26},{"text":"Allen, Daniel C. 0000-0002-0451-0564","orcid":"https://orcid.org/0000-0002-0451-0564","contributorId":225169,"corporation":false,"usgs":false,"family":"Allen","given":"Daniel","middleInitial":"C.","affiliations":[{"id":41064,"text":"Department of Biology, University of Oklahoma, Norman OK, 73019","active":true,"usgs":false}],"preferred":false,"id":790606,"contributorType":{"id":1,"text":"Authors"},"rank":27}]}} ,{"id":70209684,"text":"70209684 - 2020 - Viral, bacterial, and protozoan pathogens and fecal markers in wells supplying groundwater to public water systems in Minnesota, USA","interactions":[],"lastModifiedDate":"2020-04-21T16:00:50.510735","indexId":"70209684","displayToPublicDate":"2020-04-12T10:57:26","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3716,"text":"Water Research","onlineIssn":"1879-2448","printIssn":"0043-1354","active":true,"publicationSubtype":{"id":10}},"title":"Viral, bacterial, and protozoan pathogens and fecal markers in wells supplying groundwater to public water systems in Minnesota, USA","docAbstract":"Drinking water supply wells can be contaminated by a broad range of waterborne pathogens. However, groundwater assessments frequently measure microbial indicators or a single pathogen type, which provides a limited characterization of potential health risk. This study assessed contamination of wells by testing for viral, bacterial, and protozoan pathogens and fecal markers. Wells supplying groundwater to community and noncommunity public water systems in Minnesota, USA (n = 145) were sampled every other month over one or two years and tested using 23 qPCR assays. Eighteen genetic targets were detected at least once, and microbiological contamination was widespread (96% of 145 wells, 58% of 964 samples). The sewage-associated microbial indicators HF183 and pepper mild mottle virus were detected frequently. Human or zoonotic pathogens were detected in 70% of wells and 21% of samples by qPCR, with Salmonella and Cryptosporidium detected more often than viruses. Samples positive by qPCR for adenovirus (HAdV), enterovirus, or Salmonella were analyzed by culture and for genotype or serotype. qPCR-positive Giardia and Cryptosporidium samples were analyzed by immunofluorescent assay (IFA), and IFA and qPCR concentrations were correlated. Comparisons of indicator and pathogen occurrence at the time of sampling showed that total coliforms, HF183, and Bacteroidales-like HumM2 had high specificity and negative predictive values but generally low sensitivity and positive predictive values. Pathogen-HF183 ratios in sewage have been used to estimate health risks from HF183 concentrations in surface water, but in our groundwater samples Cryptosporidium oocyst:HF183 and HAdV:HF183 ratios were approximately 10,000 times higher than ratios reported for sewage. qPCR measurements provided a robust characterization of microbiological water quality, but interpretation of qPCR data in a regulatory context is challenging because few studies link qPCR measurements to health risk.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.watres.2020.115814","collaboration":"","usgsCitation":"Stokdyk, J.P., Firnstahl, A.D., Walsh, J.F., Spencer, S.K., de Lambert, J.R., Anderson, A., Rezania, L.W., Kieke, B.A., and Borchardt, M.A., 2020, Viral, bacterial, and protozoan pathogens and fecal markers in wells supplying groundwater to public water systems in Minnesota, USA: Water Research, v. 178, 115814, 10 p., https://doi.org/10.1016/j.watres.2020.115814.","productDescription":"115814, 10 p.","ipdsId":"IP-114409","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":374158,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-92.204691,46.704041],[-92.205192,46.698341],[-92.183091,46.695241],[-92.176091,46.686341],[-92.204092,46.666941],[-92.201592,46.656641],[-92.207092,46.651941],[-92.242493,46.649241],[-92.256592,46.658741],[-92.270592,46.650741],[-92.274392,46.657441],[-92.286192,46.660342],[-92.287392,46.667342],[-92.291292,46.668142],[-92.292192,46.663308],[-92.294033,46.074377],[-92.332912,46.062697],[-92.35176,46.015685],[-92.372717,46.014198],[-92.410649,46.027259],[-92.428555,46.024241],[-92.442259,46.016177],[-92.453373,45.992913],[-92.464512,45.985038],[-92.461138,45.980216],[-92.469354,45.973811],[-92.527052,45.983245],[-92.548459,45.969056],[-92.551186,45.95224],[-92.60246,45.940815],[-92.614314,45.934529],[-92.638824,45.934166],[-92.638474,45.925971],[-92.659549,45.922937],[-92.676167,45.912072],[-92.675737,45.907478],[-92.707702,45.894901],[-92.734039,45.868108],[-92.739278,45.84758],[-92.765146,45.830183],[-92.757815,45.806574],[-92.776496,45.790014],[-92.784621,45.764196],[-92.809837,45.744172],[-92.869193,45.717568],[-92.870025,45.697272],[-92.875488,45.689014],[-92.887929,45.639006],[-92.882529,45.610216],[-92.886442,45.598679],[-92.883749,45.575483],[-92.871082,45.567581],[-92.823309,45.560934],[-92.770223,45.566939],[-92.726082,45.541112],[-92.726677,45.514462],[-92.702224,45.493046],[-92.680234,45.464344],[-92.653549,45.455346],[-92.646602,45.441635],[-92.650422,45.398507],[-92.664102,45.393309],[-92.676961,45.380137],[-92.678223,45.373604],[-92.70272,45.358472],[-92.698967,45.336374],[-92.709968,45.321302],[-92.737122,45.300459],[-92.761013,45.289028],[-92.760615,45.278827],[-92.751659,45.26591],[-92.760249,45.2496],[-92.751708,45.218666],[-92.763908,45.204866],[-92.767408,45.190166],[-92.764872,45.182812],[-92.752404,45.173916],[-92.757707,45.155466],[-92.739584,45.115598],[-92.744938,45.108309],[-92.791528,45.079647],[-92.803079,45.060978],[-92.793282,45.047178],[-92.770362,45.033803],[-92.76206,45.02432],[-92.771231,45.001378],[-92.769445,44.97215],[-92.754603,44.955767],[-92.750645,44.937299],[-92.758701,44.908979],[-92.774571,44.898084],[-92.773946,44.889997],[-92.764133,44.875905],[-92.769102,44.862167],[-92.765278,44.837186],[-92.78043,44.812589],[-92.785206,44.792303],[-92.805287,44.768361],[-92.807988,44.75147],[-92.787906,44.737432],[-92.737259,44.717155],[-92.700948,44.693751],[-92.660988,44.660884],[-92.632105,44.649027],[-92.619779,44.634195],[-92.621456,44.615017],[-92.601516,44.612052],[-92.586216,44.600088],[-92.569434,44.603539],[-92.549777,44.58113],[-92.549957,44.568988],[-92.540551,44.567258],[-92.518358,44.575183],[-92.493808,44.566063],[-92.481001,44.568276],[-92.455105,44.561886],[-92.433256,44.5655],[-92.399281,44.558292],[-92.361518,44.558935],[-92.336114,44.554004],[-92.314071,44.538014],[-92.302466,44.516487],[-92.302215,44.500298],[-92.291005,44.485464],[-92.232472,44.445434],[-92.195378,44.433792],[-92.124513,44.422115],[-92.111085,44.413948],[-92.078605,44.404869],[-92.056486,44.402729],[-92.038147,44.388731],[-91.970266,44.365842],[-91.941311,44.340978],[-91.92559,44.333548],[-91.918625,44.322671],[-91.913534,44.311392],[-91.924613,44.291815],[-91.896388,44.27469],[-91.896008,44.262871],[-91.88704,44.251772],[-91.892698,44.231105],[-91.877429,44.212921],[-91.872369,44.199167],[-91.829167,44.17835],[-91.808064,44.159262],[-91.751747,44.134786],[-91.721552,44.130342],[-91.710597,44.12048],[-91.708207,44.105186],[-91.69531,44.09857],[-91.68153,44.0974],[-91.667006,44.086964],[-91.647873,44.064109],[-91.638115,44.063285],[-91.610487,44.04931],[-91.59207,44.031372],[-91.507121,44.01898],[-91.48087,44.008145],[-91.463515,44.009041],[-91.432522,43.996827],[-91.407395,43.965148],[-91.385785,43.954239],[-91.366642,43.937463],[-91.357426,43.917231],[-91.347741,43.911964],[-91.338141,43.897664],[-91.320605,43.888491],[-91.310991,43.867381],[-91.284138,43.847065],[-91.262436,43.792166],[-91.244135,43.774667],[-91.255431,43.744876],[-91.255932,43.729849],[-91.268455,43.709824],[-91.273252,43.666623],[-91.271749,43.654929],[-91.262397,43.64176],[-91.268748,43.615348],[-91.232707,43.583533],[-91.232812,43.564842],[-91.243214,43.550722],[-91.243183,43.540309],[-91.232941,43.523967],[-91.218292,43.514434],[-91.217706,43.50055],[-96.453049,43.500415],[-96.453067,45.298115],[-96.489065,45.357071],[-96.521787,45.375645],[-96.562142,45.38609],[-96.617726,45.408092],[-96.680454,45.410499],[-96.692541,45.417338],[-96.731396,45.45702],[-96.76528,45.521414],[-96.857751,45.605962],[-96.844211,45.639583],[-96.835769,45.649648],[-96.760866,45.687518],[-96.745086,45.701576],[-96.662595,45.738682],[-96.641941,45.759871],[-96.627778,45.786239],[-96.583085,45.820024],[-96.574517,45.843098],[-96.561334,45.945655],[-96.57035,45.963595],[-96.57794,46.026874],[-96.559271,46.058272],[-96.554507,46.083978],[-96.557952,46.102442],[-96.56692,46.11475],[-96.563043,46.119512],[-96.571439,46.12572],[-96.56926,46.133686],[-96.579453,46.147601],[-96.577952,46.165843],[-96.587408,46.178164],[-96.584372,46.204155],[-96.59755,46.227733],[-96.598645,46.241626],[-96.590942,46.250183],[-96.59887,46.26069],[-96.595014,46.275135],[-96.60136,46.30413],[-96.599761,46.330386],[-96.619991,46.340135],[-96.618147,46.344295],[-96.629211,46.352654],[-96.644335,46.351908],[-96.646341,46.360982],[-96.655206,46.365964],[-96.658436,46.373391],[-96.666028,46.374566],[-96.669132,46.390037],[-96.680687,46.407383],[-96.688082,46.40788],[-96.701358,46.420584],[-96.703078,46.429467],[-96.718074,46.438255],[-96.715557,46.463232],[-96.73627,46.48138],[-96.737798,46.489785],[-96.733612,46.497224],[-96.737702,46.50077],[-96.738475,46.525793],[-96.744341,46.533006],[-96.743003,46.54294],[-96.74883,46.558127],[-96.744436,46.56596],[-96.746442,46.574078],[-96.772446,46.600129],[-96.774094,46.613288],[-96.78995,46.631531],[-96.790663,46.649112],[-96.798823,46.658071],[-96.792958,46.677427],[-96.784339,46.685054],[-96.790906,46.70297],[-96.779252,46.727429],[-96.784279,46.732993],[-96.781216,46.740944],[-96.787466,46.756753],[-96.784314,46.766973],[-96.796195,46.789881],[-96.795756,46.807795],[-96.801446,46.810401],[-96.80016,46.819664],[-96.787657,46.827817],[-96.789663,46.832306],[-96.779347,46.843672],[-96.781358,46.879363],[-96.768458,46.879563],[-96.767358,46.883663],[-96.773558,46.884763],[-96.776558,46.895663],[-96.759241,46.918223],[-96.761757,46.934663],[-96.78312,46.925482],[-96.79038,46.929398],[-96.791558,46.944464],[-96.797734,46.9464],[-96.798737,46.962399],[-96.821852,46.969372],[-96.82318,46.999965],[-96.834221,47.006671],[-96.829499,47.021537],[-96.818557,47.02778],[-96.821422,47.032842],[-96.819321,47.0529],[-96.824479,47.059682],[-96.818175,47.104193],[-96.827344,47.120144],[-96.824807,47.124968],[-96.831547,47.142017],[-96.822377,47.162744],[-96.829637,47.17497],[-96.826962,47.182802],[-96.838806,47.197894],[-96.832789,47.203911],[-96.838806,47.22502],[-96.832946,47.237588],[-96.83766,47.240876],[-96.835368,47.250428],[-96.841672,47.258164],[-96.838997,47.267716],[-96.842531,47.269531],[-96.844088,47.289981],[-96.832884,47.30449],[-96.841958,47.316907],[-96.835845,47.321014],[-96.835845,47.335914],[-96.852417,47.366241],[-96.848907,47.370565],[-96.852676,47.374973],[-96.846925,47.376891],[-96.840621,47.389881],[-96.845492,47.394179],[-96.844919,47.399815],[-96.863593,47.418775],[-96.85748,47.440457],[-96.859868,47.470926],[-96.85471,47.478281],[-96.85853,47.489934],[-96.851653,47.497098],[-96.851367,47.509037],[-96.866363,47.524893],[-96.85471,47.535973],[-96.859153,47.566355],[-96.853689,47.570381],[-96.856373,47.575749],[-96.851293,47.589264],[-96.856903,47.602329],[-96.855421,47.60875],[-96.873671,47.613654],[-96.871005,47.616832],[-96.879496,47.620576],[-96.882393,47.633489],[-96.888573,47.63845],[-96.882376,47.649025],[-96.88697,47.653049],[-96.887126,47.666369],[-96.895271,47.67357],[-96.899352,47.689473],[-96.908928,47.688722],[-96.907266,47.693976],[-96.920119,47.710383],[-96.923544,47.718201],[-96.919471,47.722515],[-96.932809,47.737139],[-96.928505,47.748037],[-96.934173,47.752412],[-96.939179,47.768397],[-96.9644,47.782995],[-96.957283,47.790147],[-96.966068,47.797297],[-96.975131,47.798326],[-96.980579,47.805614],[-96.979327,47.824533],[-96.986685,47.837639],[-96.998295,47.841724],[-96.998144,47.858882],[-97.005557,47.863977],[-97.002456,47.868677],[-97.023156,47.874978],[-97.019355,47.880278],[-97.024955,47.886878],[-97.019155,47.889778],[-97.024955,47.894978],[-97.020155,47.900478],[-97.024955,47.908178],[-97.017254,47.905678],[-97.015354,47.910278],[-97.023754,47.915878],[-97.018054,47.918078],[-97.035754,47.930179],[-97.036054,47.939379],[-97.054554,47.946279],[-97.052454,47.957179],[-97.061454,47.96358],[-97.053553,47.991612],[-97.064289,47.998508],[-97.066762,48.009558],[-97.063012,48.013179],[-97.072239,48.019107],[-97.068987,48.026267],[-97.072257,48.048068],[-97.097772,48.07108],[-97.103052,48.071669],[-97.099431,48.082106],[-97.105226,48.09044],[-97.104872,48.097851],[-97.109535,48.104723],[-97.123205,48.106648],[-97.120702,48.114987],[-97.131956,48.139563],[-97.141401,48.14359],[-97.138911,48.157793],[-97.146745,48.168556],[-97.141474,48.179099],[-97.146233,48.186054],[-97.134372,48.210434],[-97.136304,48.228984],[-97.141254,48.234668],[-97.135763,48.237596],[-97.138765,48.244991],[-97.127276,48.253323],[-97.131846,48.267589],[-97.11657,48.279661],[-97.12216,48.290056],[-97.128862,48.292882],[-97.122072,48.300865],[-97.132443,48.315489],[-97.127601,48.323319],[-97.134854,48.331314],[-97.131145,48.339722],[-97.147748,48.359905],[-97.140106,48.380479],[-97.145592,48.394195],[-97.135012,48.406735],[-97.142849,48.419471],[-97.1356,48.424369],[-97.139173,48.430528],[-97.134229,48.439797],[-97.137689,48.447583],[-97.132746,48.459942],[-97.144116,48.469212],[-97.141397,48.476256],[-97.144981,48.481571],[-97.140291,48.484722],[-97.138864,48.494362],[-97.148133,48.503384],[-97.153076,48.524148],[-97.150481,48.536877],[-97.163105,48.543855],[-97.160863,48.549236],[-97.152459,48.552326],[-97.158638,48.564067],[-97.149616,48.569876],[-97.14974,48.579516],[-97.142915,48.583733],[-97.143684,48.597066],[-97.137504,48.612268],[-97.132931,48.61338],[-97.130089,48.621166],[-97.125639,48.620919],[-97.125269,48.629694],[-97.108466,48.632658],[-97.111921,48.642918],[-97.100551,48.658614],[-97.102652,48.664793],[-97.097708,48.68395],[-97.118286,48.700573],[-97.116185,48.709348],[-97.136083,48.727763],[-97.139488,48.746611],[-97.151289,48.757428],[-97.147478,48.763698],[-97.154854,48.774515],[-97.157093,48.790024],[-97.163535,48.79507],[-97.165624,48.809627],[-97.180028,48.81845],[-97.177747,48.824815],[-97.181116,48.832741],[-97.173811,48.838309],[-97.175618,48.853105],[-97.187362,48.867598],[-97.185738,48.87222],[-97.197982,48.880341],[-97.197982,48.898332],[-97.210541,48.90439],[-97.211161,48.916649],[-97.217992,48.919735],[-97.218666,48.931781],[-97.224505,48.9341],[-97.232147,48.948955],[-97.230859,48.960891],[-97.239209,48.968684],[-97.237297,48.985696],[-97.230833,48.991303],[-97.229039,49.000687],[-95.153711,48.998903],[-95.15335,49.383079],[-95.126467,49.369439],[-95.058404,49.35317],[-95.014415,49.356405],[-94.988908,49.368897],[-94.957465,49.370186],[-94.854245,49.324154],[-94.816222,49.320987],[-94.824291,49.308834],[-94.82516,49.294283],[-94.797244,49.214284],[-94.797527,49.197791],[-94.773223,49.120733],[-94.750221,49.099763],[-94.750218,48.999992],[-94.718932,48.999991],[-94.683069,48.883929],[-94.684217,48.872399],[-94.692527,48.86895],[-94.693044,48.853392],[-94.685681,48.840119],[-94.701968,48.831778],[-94.704284,48.824284],[-94.694974,48.809206],[-94.694312,48.789352],[-94.690889,48.778066],[-94.651765,48.755913],[-94.645164,48.749975],[-94.645083,48.744143],[-94.61901,48.737374],[-94.58715,48.717599],[-94.549069,48.714653],[-94.533057,48.701262],[-94.452332,48.692444],[-94.438701,48.694889],[-94.416191,48.710948],[-94.384221,48.711806],[-94.342758,48.703382],[-94.308446,48.710239],[-94.290737,48.707747],[-94.260541,48.696381],[-94.251169,48.683514],[-94.254643,48.663888],[-94.250497,48.656654],[-94.224276,48.649527],[-94.091244,48.643669],[-94.065775,48.646104],[-94.035616,48.641018],[-94.006933,48.643193],[-93.944221,48.632294],[-93.91153,48.634673],[-93.840754,48.628548],[-93.824144,48.610724],[-93.806763,48.577616],[-93.811201,48.542385],[-93.818253,48.530046],[-93.794454,48.516021],[-93.656652,48.515731],[-93.643091,48.518294],[-93.628865,48.53121],[-93.612844,48.521876],[-93.60587,48.522472],[-93.594379,48.528793],[-93.547191,48.528684],[-93.467504,48.545664],[-93.460798,48.550552],[-93.456675,48.561834],[-93.465199,48.590659],[-93.438494,48.59338],[-93.405269,48.609344],[-93.395022,48.603303],[-93.371156,48.605085],[-93.362132,48.613832],[-93.35324,48.613378],[-93.349095,48.624935],[-93.254854,48.642784],[-93.207398,48.642474],[-93.178095,48.623339],[-93.088438,48.627597],[-92.984963,48.623731],[-92.954876,48.631493],[-92.95012,48.630419],[-92.949839,48.608269],[-92.929614,48.606874],[-92.909947,48.596313],[-92.894687,48.594915],[-92.728046,48.53929],[-92.657881,48.546263],[-92.634931,48.542873],[-92.625739,48.518189],[-92.631117,48.508252],[-92.627237,48.503383],[-92.636696,48.499428],[-92.654039,48.501635],[-92.661418,48.496557],[-92.698824,48.494892],[-92.712562,48.463013],[-92.687998,48.443889],[-92.656027,48.436709],[-92.507285,48.447875],[-92.475585,48.418793],[-92.456325,48.414204],[-92.456389,48.401134],[-92.47675,48.37176],[-92.469948,48.351836],[-92.437825,48.309839],[-92.416285,48.295463],[-92.369174,48.220268],[-92.336831,48.235383],[-92.269742,48.248241],[-92.273706,48.256747],[-92.294541,48.27156],[-92.292999,48.276404],[-92.301451,48.288608],[-92.294527,48.306454],[-92.306309,48.316442],[-92.304561,48.322977],[-92.295412,48.323957],[-92.288994,48.342991],[-92.26228,48.354933],[-92.222813,48.349203],[-92.216983,48.345114],[-92.206803,48.345596],[-92.203684,48.352063],[-92.178418,48.351881],[-92.177354,48.357228],[-92.145049,48.365651],[-92.143583,48.356121],[-92.083513,48.353865],[-92.077961,48.358253],[-92.055228,48.359213],[-92.045734,48.347901],[-92.046562,48.33474],[-92.037721,48.333183],[-92.030872,48.325824],[-92.000133,48.321355],[-92.01298,48.297391],[-92.006577,48.265421],[-91.989545,48.260214],[-91.976903,48.244626],[-91.971056,48.247667],[-91.971779,48.252977],[-91.954432,48.251678],[-91.952209,48.244394],[-91.957683,48.242683],[-91.957798,48.232989],[-91.941838,48.230602],[-91.915772,48.238871],[-91.89347,48.237699],[-91.884691,48.227321],[-91.867882,48.219095],[-91.864382,48.207031],[-91.815772,48.211748],[-91.809038,48.206013],[-91.79181,48.202492],[-91.789011,48.196549],[-91.756637,48.205022],[-91.749075,48.198844],[-91.741932,48.199122],[-91.742313,48.204491],[-91.714931,48.19913],[-91.711611,48.1891],[-91.721413,48.180255],[-91.724584,48.170657],[-91.705318,48.170775],[-91.70726,48.153661],[-91.698174,48.141643],[-91.699981,48.13184],[-91.712226,48.116883],[-91.703524,48.113548],[-91.682845,48.122118],[-91.687623,48.111698],[-91.676876,48.107264],[-91.665208,48.107011],[-91.653261,48.114137],[-91.653571,48.109567],[-91.640175,48.096926],[-91.559272,48.108268],[-91.552962,48.103012],[-91.569746,48.093348],[-91.575471,48.066294],[-91.575672,48.048791],[-91.567254,48.043719],[-91.488646,48.068065],[-91.45033,48.068806],[-91.437582,48.049248],[-91.429642,48.048608],[-91.391128,48.057075],[-91.370872,48.06941],[-91.365143,48.066968],[-91.340159,48.073236],[-91.332589,48.069331],[-91.26638,48.078713],[-91.214428,48.10294],[-91.190461,48.124891],[-91.183207,48.122235],[-91.176181,48.125811],[-91.137733,48.14915],[-91.139402,48.154738],[-91.092258,48.173101],[-91.082731,48.180756],[-91.024208,48.190072],[-90.976955,48.219452],[-90.914971,48.230603],[-90.88548,48.245784],[-90.875107,48.237784],[-90.847352,48.244443],[-90.839176,48.239511],[-90.836313,48.176963],[-90.832589,48.173765],[-90.821115,48.184709],[-90.817698,48.179569],[-90.804207,48.177833],[-90.796596,48.159373],[-90.777917,48.163801],[-90.778031,48.148723],[-90.79797,48.136894],[-90.787305,48.134196],[-90.789919,48.129902],[-90.76911,48.116585],[-90.761555,48.100133],[-90.751608,48.090968],[-90.641596,48.103515],[-90.626886,48.111846],[-90.59146,48.117546],[-90.582217,48.123784],[-90.55929,48.121683],[-90.555845,48.117069],[-90.569763,48.106951],[-90.567482,48.101178],[-90.556838,48.096008],[-90.487077,48.099082],[-90.467712,48.108818],[-90.438449,48.098747],[-90.403219,48.105114],[-90.374542,48.090942],[-90.367658,48.094577],[-90.344234,48.094447],[-90.330052,48.102399],[-90.312386,48.1053],[-90.289337,48.098993],[-90.224692,48.108148],[-90.188679,48.107947],[-90.176605,48.112445],[-90.136191,48.112136],[-90.116259,48.104303],[-90.073873,48.101138],[-90.023595,48.084708],[-90.015057,48.067188],[-90.008446,48.068396],[-89.997852,48.057567],[-89.99305,48.028404],[-89.97718,48.023501],[-89.968255,48.014482],[-89.954605,48.011516],[-89.95059,48.015901],[-89.934489,48.015628],[-89.915341,47.994866],[-89.897414,47.987599],[-89.873286,47.985419],[-89.868153,47.989898],[-89.847571,47.992442],[-89.842568,48.001368],[-89.830385,48.000284],[-89.820483,48.014665],[-89.797744,48.014505],[-89.763967,48.022969],[-89.724048,48.018996],[-89.721038,48.017965],[-89.724044,48.013675],[-89.716114,48.016441],[-89.716417,48.010251],[-89.702528,48.006325],[-89.673798,48.01151],[-89.667128,48.007421],[-89.657051,48.009954],[-89.649057,48.003853],[-89.617867,48.010947],[-89.611678,48.017529],[-89.607821,48.006566],[-89.594749,48.004332],[-89.582117,47.996314],[-89.564288,48.00293],[-89.489226,48.014528],[-89.495344,48.002356],[-89.541521,47.992841],[-89.551555,47.987305],[-89.555015,47.974849],[-89.572315,47.967238],[-89.58823,47.9662],[-89.611412,47.980731],[-89.624559,47.983153],[-89.631825,47.980039],[-89.640129,47.96793],[-89.638285,47.954275],[-89.697619,47.941288],[-89.793539,47.891358],[-89.85396,47.873997],[-89.87158,47.874194],[-89.923649,47.862062],[-89.930844,47.857723],[-89.92752,47.850825],[-89.933899,47.84676],[-89.974296,47.830514],[-90.072025,47.811105],[-90.075559,47.803303],[-90.1168,47.79538],[-90.16079,47.792807],[-90.178755,47.786414],[-90.187636,47.77813],[-90.248794,47.772763],[-90.323446,47.753771],[-90.332686,47.746387],[-90.437712,47.731612],[-90.441912,47.726404],[-90.458365,47.7214],[-90.537105,47.703055],[-90.551291,47.690266],[-90.735927,47.624343],[-90.86827,47.5569],[-90.907494,47.532873],[-90.914247,47.522639],[-90.939072,47.514532],[-91.032945,47.458236],[-91.045646,47.456525],[-91.097569,47.413888],[-91.128131,47.399619],[-91.146958,47.381464],[-91.156513,47.378816],[-91.188772,47.340082],[-91.238658,47.304976],[-91.262512,47.27929],[-91.288478,47.26596],[-91.326019,47.238993],[-91.357803,47.206743],[-91.418805,47.172152],[-91.477351,47.125667],[-91.497902,47.122579],[-91.518793,47.108121],[-91.573817,47.089917],[-91.591508,47.068684],[-91.626824,47.049953],[-91.644564,47.026491],[-91.666477,47.014297],[-91.704649,47.005246],[-91.780675,46.945881],[-91.806851,46.933727],[-91.841349,46.925215],[-91.883238,46.905728],[-91.914984,46.883836],[-91.952985,46.867037],[-92.094089,46.787839],[-92.088289,46.773639],[-92.06449,46.745439],[-92.025789,46.710839],[-92.01529,46.706469],[-92.020289,46.704039],[-92.03399,46.708939],[-92.08949,46.74924],[-92.10819,46.74914],[-92.13789,46.73954],[-92.14329,46.73464],[-92.141291,46.72524],[-92.146291,46.71594],[-92.167291,46.719941],[-92.189091,46.717541],[-92.204691,46.704041]]]},\"properties\":{\"name\":\"Minnesota\",\"nation\":\"USA \"}}]}","volume":"178","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Stokdyk, Joel P. 0000-0003-2887-6277 jstokdyk@usgs.gov","orcid":"https://orcid.org/0000-0003-2887-6277","contributorId":193848,"corporation":false,"usgs":true,"family":"Stokdyk","given":"Joel","email":"jstokdyk@usgs.gov","middleInitial":"P.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":787506,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Firnstahl, Aaron D. 0000-0003-2686-7596 afirnstahl@usgs.gov","orcid":"https://orcid.org/0000-0003-2686-7596","contributorId":168296,"corporation":false,"usgs":true,"family":"Firnstahl","given":"Aaron","email":"afirnstahl@usgs.gov","middleInitial":"D.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":787507,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Walsh, James F.","contributorId":214333,"corporation":false,"usgs":false,"family":"Walsh","given":"James","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":787508,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Spencer, Susan K.","contributorId":210972,"corporation":false,"usgs":false,"family":"Spencer","given":"Susan","email":"","middleInitial":"K.","affiliations":[{"id":38162,"text":"United States Department of Agriculture Agricultural Research Service","active":true,"usgs":false}],"preferred":false,"id":787509,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"de Lambert, Jane R.","contributorId":214334,"corporation":false,"usgs":false,"family":"de Lambert","given":"Jane","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":787510,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Anderson, Anita C.","contributorId":214336,"corporation":false,"usgs":false,"family":"Anderson","given":"Anita C.","affiliations":[],"preferred":false,"id":787511,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rezania, Lih-in W.","contributorId":214337,"corporation":false,"usgs":false,"family":"Rezania","given":"Lih-in","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":787512,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kieke, Burney A","contributorId":195802,"corporation":false,"usgs":false,"family":"Kieke","given":"Burney","email":"","middleInitial":"A","affiliations":[],"preferred":false,"id":787513,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Borchardt, Mark A. 0000-0002-6471-2627","orcid":"https://orcid.org/0000-0002-6471-2627","contributorId":151033,"corporation":false,"usgs":false,"family":"Borchardt","given":"Mark","email":"","middleInitial":"A.","affiliations":[{"id":6684,"text":"USDA Forest Service, Southern Research Station, Aiken, SC","active":true,"usgs":false}],"preferred":false,"id":787514,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ]}