With increased pressure from a growing human population, managers are challenged to understand how novel disturbances (e.g., climate change, increased water withdrawals, urbanization) may affect natural resources. The Sudbury River is a National Wild and Scenic River located in suburban Boston, Massachusetts (Northeastern US) with myriad impairments (e.g., mainstem impoundments, withdrawals, and urbanization) that is under increasing pressure from hydrologic alteration. We sampled fish, mussel, and macroinvertebrate assemblages in the Sudbury River and used species traits to investigate potential effects of past and future flow alteration on biota. Analysis of 33 years of stream gage data indicates continued hydrologic alteration of the Sudbury River, likely related to increased urbanization and water withdrawals over that time. These changes include a roughly 200% increase in rise rates of flows, an approximate 65% decrease in 1-day minimum flows, and a trend towards increasing high flow pulse counts. Biotic sampling in summer of 2014 demonstrated that the Sudbury River is now dominated by generalist species. Of five mussel species sampled, all are generalists in their habitat requirements. Though one mussel species of special concern was sampled, the most abundant species collected were the widespread Eastern elliptio (58%) and Eastern lampmussel (40%). We used the target fish community (TFC) model to assess the degree to which the fish assemblage deviated from that expected for a river with similar zoogeographic and physical features. Overall, the current community has a 22.7% similarity to the TFC. Of the four fluvial specialist species present in the TFC, only fallfish was sampled in our study. While the TFC showed that the historical assemblage was likely dominated by fluvial specialist and fluvial dependent species, the current assemblage is overwhelmingly dominated by macrohabitat generalists (90.6% of fishes sampled). These results are consistent with other studies that show shifts in assemblages from fluvial specialists to habitat generalists with hydrologic alteration. If the current trends continue, it is likely that biotic assemblages will experience increasing pressure from hydrologic alteration. While hydrologic alteration is likely impacting biotic assemblages in the Sudbury River, other factors such as high temperatures, low dissolved oxygen, high nutrients, low availability of high-quality habitat, and poor habitat connectivity may also be negatively impacting biotic assemblages. Comparisons to other rivers and a complete longitudinal habitat survey could help to identify availability of unique habitats and representativeness of this study. While this study suggests impacts of flow on biota, future studies with quantitative, habitat-specific sampling during different flow levels could help to directly identify links between hydrologic alteration and biotic impairment in the Sudbury River.
","language":"English","publisher":"U.S. Fish and Wildlife Service","usgsCitation":"Roy, A.H., Jane, S.F., Hazelton, P.D., Richards, T.A., Finn, J.T., and Randhir, T.O., 2016, Establishing links between streamflow and ecological integrity in the Sudbury River (Northeastern U.S.): Cooperator Science Series 122-2016, vi, 78 p.","productDescription":"vi, 78 p.","ipdsId":"IP-065793","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":340465,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":340464,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://digitalmedia.fws.gov/cdm/singleitem/collection/document/id/2152/rec/19"}],"country":"United States","state":"Massachussetts","otherGeospatial":"Sudbury River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -71.63497924804688,\n 42.13998671872691\n ],\n [\n -71.17767333984375,\n 42.13998671872691\n ],\n [\n -71.17767333984375,\n 42.5530802889558\n ],\n [\n -71.63497924804688,\n 42.5530802889558\n ],\n [\n -71.63497924804688,\n 42.13998671872691\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5901b1bae4b0c2e071a99b96","contributors":{"authors":[{"text":"Roy, Allison H. 0000-0002-8080-2729 aroy@usgs.gov","orcid":"https://orcid.org/0000-0002-8080-2729","contributorId":4240,"corporation":false,"usgs":true,"family":"Roy","given":"Allison","email":"aroy@usgs.gov","middleInitial":"H.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":693023,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jane, Stephen F.","contributorId":191442,"corporation":false,"usgs":false,"family":"Jane","given":"Stephen","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":693056,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hazelton, Peter D.","contributorId":171765,"corporation":false,"usgs":false,"family":"Hazelton","given":"Peter","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":693057,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Richards, Todd A.","contributorId":52266,"corporation":false,"usgs":true,"family":"Richards","given":"Todd","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":693058,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Finn, John T.","contributorId":43398,"corporation":false,"usgs":false,"family":"Finn","given":"John","email":"","middleInitial":"T.","affiliations":[{"id":16720,"text":"Department of Environmental Conservation, University of Massachusetts, Amherst, MA 01003-9485, USA","active":true,"usgs":false}],"preferred":false,"id":693059,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Randhir, Timothy O.","contributorId":191443,"corporation":false,"usgs":false,"family":"Randhir","given":"Timothy","email":"","middleInitial":"O.","affiliations":[],"preferred":false,"id":693060,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70187297,"text":"70187297 - 2016 - Participatory modeling and structured decision making","interactions":[],"lastModifiedDate":"2017-05-02T09:49:06","indexId":"70187297","displayToPublicDate":"2016-12-31T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Participatory modeling and structured decision making","docAbstract":"Structured decision making (SDM) provides a framework for making sound decisions even when faced with uncertainty, and is a transparent, defensible, and replicable method used to understand complex problems. A hallmark of SDM is the explicit incorporation of values and science, which often includes participation from multiple stakeholders, helping to garner trust and ultimately result in a decision that is more likely to be implemented. The core steps in the SDM process are used to structure thinking about natural resources management choices, and include: (1) properly defining the problem and the decision context, (2) determining the objectives that help describe the aspirations of the decision maker, (3) devising management actions or alternatives that can achieve those objectives, (4) evaluating the outcomes or consequences of each alternative on each of the objectives, (5) evaluating trade-offs, and (6) implementing the decision. Participatory modeling for SDM includes engaging stakeholders in some or all of the steps of the SDM process listed above. In addition, participatory modeling often is crucial for creating qualitative and quantitative models of how the system works, providing data for these models, and eliciting expert opinion when data are unavailable. In these ways, SDM provides a framework for decision making in natural resources management that includes participation from stakeholder groups throughout the process, including the modeling phase.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Environmental Modeling with Stakeholders","language":"English","publisher":"Springer","doi":"10.1007/978-3-319-25053-3_5","usgsCitation":"Robinson, K., and Fuller, A.K., 2016, Participatory modeling and structured decision making, chap. of Environmental Modeling with Stakeholders, p. 83-101, https://doi.org/10.1007/978-3-319-25053-3_5.","productDescription":"18 p.","startPage":"83","endPage":"101","ipdsId":"IP-060120","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":340717,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-12-17","publicationStatus":"PW","scienceBaseUri":"59099aaee4b0fc4e449157ec","contributors":{"authors":[{"text":"Robinson, Kelly F.","contributorId":140157,"corporation":false,"usgs":false,"family":"Robinson","given":"Kelly F.","affiliations":[{"id":6590,"text":"Department of Fisheries and Wildlife, Michigan State University","active":true,"usgs":false},{"id":473,"text":"New York Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true},{"id":13267,"text":"Warnell School of Forestry and Natural Resources, University of Georgia","active":true,"usgs":false}],"preferred":false,"id":693878,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fuller, Angela K. 0000-0002-9247-7468 afuller@usgs.gov","orcid":"https://orcid.org/0000-0002-9247-7468","contributorId":3984,"corporation":false,"usgs":true,"family":"Fuller","given":"Angela","email":"afuller@usgs.gov","middleInitial":"K.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":693229,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70182766,"text":"70182766 - 2016 - Regional geologic and petrologic framework for iron oxide ± apatite ± rare earth element and iron oxide copper-gold deposits of the Mesoproterozoic St. Francois Mountains terrane, southeast Missouri, USA","interactions":[],"lastModifiedDate":"2019-02-01T15:58:49","indexId":"70182766","displayToPublicDate":"2016-12-31T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1472,"text":"Economic Geology","active":true,"publicationSubtype":{"id":10}},"title":"Regional geologic and petrologic framework for iron oxide ± apatite ± rare earth element and iron oxide copper-gold deposits of the Mesoproterozoic St. Francois Mountains terrane, southeast Missouri, USA","docAbstract":"This paper provides an overview on the genesis of Mesoproterozoic igneous rocks and associated iron oxide ± apatite (IOA) ± rare earth element, iron oxide-copper-gold (IOCG), and iron-rich sedimentary deposits in the St. Francois Mountains terrane of southeast Missouri, USA. The St. Francois Mountains terrane lies along the southeastern margin of Laurentia as part of the eastern granite-rhyolite province. The province formed during two major pulses of igneous activity: (1) an older early Mesoproterozoic (ca. 1.50–1.44 Ga) episode of volcanism and granite plutonism, and (2) a younger middle Mesoproterozoic (ca. 1.33–1.30 Ga) episode of bimodal gabbro and granite plutonism. The volcanic rocks are predominantly high-silica rhyolite pyroclastic flows, volcanogenic breccias, and associated volcanogenic sediments with lesser amounts of basaltic to andesitic volcanic and associated subvolcanic intrusive rocks. The iron oxide deposits are all hosted in the early Mesoproterozoic volcanic and volcaniclastic sequences. Previous studies have characterized the St. Francois Mountains terrane as a classic, A-type within-plate granitic terrane. However, our new whole-rock geochemical data indicate that the felsic volcanic rocks are effusive derivatives from multicomponent source types, having compositional similarities to A-type within-plate granites as well as to S- and I-type granites generated in an arc setting. In addition, the volcanic-hosted IOA and IOCG deposits occur within bimodal volcanic sequences, some of which have volcanic arc geochemical affinities, suggesting an extensional tectonic setting during volcanism prior to emplacement of the ore-forming systems.
","language":"English","publisher":"Society of Economic Geologists","doi":"10.2113/econgeo.111.8.1825","usgsCitation":"Day, W.C., Slack, J.F., Ayuso, R.A., and Seeger, C.M., 2016, Regional geologic and petrologic framework for iron oxide ± apatite ± rare earth element and iron oxide copper-gold deposits of the Mesoproterozoic St. Francois Mountains terrane, southeast Missouri, USA: Economic Geology, v. 111, no. 8, p. 1825-1858, https://doi.org/10.2113/econgeo.111.8.1825.","productDescription":"34 p. ","startPage":"1825","endPage":"1858","ipdsId":"IP-067457","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":336811,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Missouri","otherGeospatial":"Mesoproterozoic St. Francois Mountains ","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.97503662109375,\n 37.66425503616459\n ],\n [\n -91.51611328125,\n 37.6816466602918\n ],\n [\n -91.4886474609375,\n 37.58594229860422\n ],\n [\n -91.549072265625,\n 37.28716518793858\n ],\n [\n -91.571044921875,\n 36.760891249565624\n ],\n [\n -91.37603759765625,\n 36.53832942872818\n ],\n [\n -91.10687255859375,\n 36.58245213849012\n ],\n [\n -90.69488525390625,\n 36.53612263184686\n ],\n [\n -90.3900146484375,\n 36.551568887374\n ],\n [\n -90.076904296875,\n 36.55377524336089\n ],\n [\n -89.8846435546875,\n 36.56039393337068\n ],\n [\n -89.64569091796874,\n 36.53832942872818\n ],\n [\n -89.61273193359375,\n 36.586863023441836\n ],\n [\n -89.53582763671875,\n 36.62654964428433\n ],\n [\n -89.43145751953125,\n 36.57142382346277\n ],\n [\n -89.41497802734375,\n 36.63757008123925\n ],\n [\n -89.3408203125,\n 36.66621584042748\n ],\n [\n -89.25018310546875,\n 36.62434536776987\n ],\n [\n -89.20623779296875,\n 36.63316209558658\n ],\n [\n -89.197998046875,\n 36.83346996591303\n ],\n [\n -89.154052734375,\n 36.92793899776678\n ],\n [\n -89.17327880859375,\n 36.94989178681327\n ],\n [\n -89.2364501953125,\n 36.98280911070616\n ],\n [\n -89.25567626953125,\n 36.96964388918142\n ],\n [\n -89.373779296875,\n 37.00255267215955\n ],\n [\n -89.41223144531249,\n 37.046408899699564\n ],\n [\n -89.43145751953125,\n 37.092430683283474\n ],\n [\n -89.46990966796875,\n 37.19314268101434\n ],\n [\n -89.50286865234375,\n 37.23470197166817\n ],\n [\n -89.549560546875,\n 37.26312408340919\n ],\n [\n -89.56878662109375,\n 37.33304051804567\n ],\n [\n -89.461669921875,\n 37.385435182627226\n ],\n [\n -89.46441650390625,\n 37.411618795843026\n ],\n [\n -89.5166015625,\n 37.49883141715704\n ],\n [\n -89.593505859375,\n 37.65338320128765\n ],\n [\n -90.97503662109375,\n 37.66425503616459\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"111","issue":"8","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-11-16","publicationStatus":"PW","scienceBaseUri":"58ba8ebde4b0bcef64f0b93b","contributors":{"authors":[{"text":"Day, Warren C. 0000-0002-9278-2120 wday@usgs.gov","orcid":"https://orcid.org/0000-0002-9278-2120","contributorId":1308,"corporation":false,"usgs":true,"family":"Day","given":"Warren","email":"wday@usgs.gov","middleInitial":"C.","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"preferred":true,"id":673676,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Slack, John F. 0000-0001-6600-3130 jfslack@usgs.gov","orcid":"https://orcid.org/0000-0001-6600-3130","contributorId":1032,"corporation":false,"usgs":true,"family":"Slack","given":"John","email":"jfslack@usgs.gov","middleInitial":"F.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":673677,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ayuso, Robert A. 0000-0002-8496-9534 rayuso@usgs.gov","orcid":"https://orcid.org/0000-0002-8496-9534","contributorId":2654,"corporation":false,"usgs":true,"family":"Ayuso","given":"Robert","email":"rayuso@usgs.gov","middleInitial":"A.","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":680561,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Seeger, Cheryl M.","contributorId":63848,"corporation":false,"usgs":true,"family":"Seeger","given":"Cheryl","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":680562,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70173826,"text":"70173826 - 2016 - Improving our understanding of hydraulic-electrical relations: A case study of the surficial aquifer in Emirate Abu Dhabi","interactions":[],"lastModifiedDate":"2017-11-08T17:24:55","indexId":"70173826","displayToPublicDate":"2016-12-31T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"title":"Improving our understanding of hydraulic-electrical relations: A case study of the surficial aquifer in Emirate Abu Dhabi","docAbstract":"Transmissivity is a bulk hydraulic property that can be correlated with bulk electrical properties of an aquifer. In aquifers that are electrically-resistive relative to adjacent layers in a horizontally stratified sequence, transmissivity has been shown to correlate with bulk transverse resistance. Conversely, in aquifers that are electrically-conductive relative to adjacent layers, transmissivity has been shown to correlate with bulk longitudinal conductance. In both cases, previous investigations have relied on small datasets (on average less than eight observations) that have yielded coefficients of determination (R2) that are typically in the range of 0.6 to 0.7 to substantiate these relations. Compared to previous investigations, this paper explores hydraulic-electrical relations using a much larger dataset. Geophysical data collected from 26 boreholes in Emirate Abu Dhabi, United Arab Emirates, are used to correlate transmissivity modeled from neutron porosity logs to the bulk electrical properties of the surficial aquifer that are computed from deep-induction logs. Transmissivity is found to be highly correlated with longitudinal conductance. An R2 value of 0.853 is obtained when electrical effects caused by variations in pore-fluid salinity are taken into consideration.
","largerWorkType":{"id":24,"text":"Conference Paper"},"largerWorkTitle":"Symposium on the Application of Geophysics to Engineering and Environmental Problems 2016","conferenceTitle":"Symposium on the Application of Geophysics to Engineering and Environmental Problems","conferenceDate":"March 20-24, 2016","conferenceLocation":"Denver, CO","language":"English","publisher":"Society of Exploration Geophysicists and Environment and Engineering Geophysical Society","doi":"10.4133/SAGEEP.29-060","issn":"1554-8015","usgsCitation":"Ikard, S., and Kress, W.H., 2016, Improving our understanding of hydraulic-electrical relations: A case study of the surficial aquifer in Emirate Abu Dhabi, in Symposium on the Application of Geophysics to Engineering and Environmental Problems 2016, Denver, CO, March 20-24, 2016, p. 340-353, https://doi.org/10.4133/SAGEEP.29-060.","productDescription":"14 p.","startPage":"340","endPage":"353","ipdsId":"IP-070679","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":348522,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a0425bde4b0dc0b45b453d0","contributors":{"authors":[{"text":"Ikard, Scott 0000-0002-8304-4935 sikard@usgs.gov","orcid":"https://orcid.org/0000-0002-8304-4935","contributorId":171751,"corporation":false,"usgs":true,"family":"Ikard","given":"Scott","email":"sikard@usgs.gov","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":638521,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kress, Wade H. 0000-0002-6833-028X wkress@usgs.gov","orcid":"https://orcid.org/0000-0002-6833-028X","contributorId":1576,"corporation":false,"usgs":true,"family":"Kress","given":"Wade","email":"wkress@usgs.gov","middleInitial":"H.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":638522,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70179021,"text":"sir20165171 - 2016 - Hydrogeologic framework and characterization of the Truxton Aquifer on the Hualapai Reservation, Mohave County, Arizona","interactions":[],"lastModifiedDate":"2020-04-07T16:45:31.293325","indexId":"sir20165171","displayToPublicDate":"2016-12-30T20:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-5171","title":"Hydrogeologic framework and characterization of the Truxton Aquifer on the Hualapai Reservation, Mohave County, Arizona","docAbstract":"The U.S. Geological Survey, in cooperation with the Bureau of Reclamation, developed this study to determine an estimate of groundwater in storage in the Truxton aquifer on the Hualapai Reservation in northwestern Arizona. For this study, the Truxton aquifer is defined as the unconfined, saturated groundwater in the unconsolidated to semiconsolidated older and younger basin-fill deposits of the Truxton basin overlying bedrock. The physical characteristics of the Truxton aquifer have not been well characterized in the past. In particular, the depth to impermeable granite bedrock and thickness of the basin are known in only a few locations where water wells have penetrated into the granite. Increasing water demands on the Truxton aquifer by both tribal and nontribal water users have led to concern about the long-term sustainability of this water resource. The Hualapai Tribe currently projects an increase of their water needs from about 300 acre-feet (acre-ft) per year to about 780 acre-ft per year by 2050 to support the community of Peach Springs, Arizona, and the southern part of the reservation. This study aimed to quantitatively develop better knowledge of aquifer characteristics, including aquifer storage and capacity, using (1) surface resistivity data collected along transects and (2) analysis of existing geologic, borehole, precipitation, water use, and water-level data.
The surface resistivity surveys indicated that the depth to granite along the survey lines varied from less than 100 feet (ft) to more than 1,300 ft below land surface on the Hualapai Reservation. The top of the granite bedrock is consistent with the erosional character of the Truxton basin and exhibits deep paleochannels filled with basin-fill deposits consistent with the results of surface resistivity surveys and borehole logs from wells. The estimated average saturated thickness of the Truxton aquifer on the Hualapai Reservation is about 330 ft (with an estimated range of 260 to 390 ft), based on both resistivity results and the depth to water in wells. The saturated thickness might be greater in parts of the Truxton aquifer where paleochannels are incised into the granite underlying the basin-fill sediments. The estimated groundwater storage of the Truxton aquifer on the Hualapai Reservation ranges from 420,000 to 940,000 acre-ft and does not include groundwater storage in the aquifer outside the Hualapai Reservation boundary. In addition, the calculation of total storage in the Truxton aquifer does not determine nor indicate the availability and sustainability of that groundwater as a long-term resource. These results compared well with studies done on alluvial-basin aquifers in areas adjacent to this study. The part of the Truxton aquifer on the Hualapai Reservation represents about 20 percent of the entire aquifer.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165171","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Bills, D.J., and Macy, J.P., 2016, Hydrologic framework and characterization of the Truxton aquifer on the Hualapai Reservation, Mohave County, Arizona (ver. 2.0, December 2017): U.S. Geological Survey Scientific Investigations Report 2016–5171, 50 p., https://doi.org/10.3133/sir20165171.","productDescription":"vi, 50 p.","numberOfPages":"57","onlineOnly":"Y","ipdsId":"IP-074915","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":373792,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20205017","text":"Scientific Investigations Report 2020-5017","linkHelpText":" - Geophysical Surveys, Hydrogeologic Characterization, and Groundwater Flow Model for the Truxton Basin and Hualapai Plateau, Northwestern Arizona"},{"id":373791,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20205025","text":"Scientific Investigations Report 2020-5025","linkHelpText":" - Hydrogeologic Characterization of the Hualapai Plateau on the Western Hualapai Indian Reservation, Northwestern Arizona"},{"id":332711,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5171/coverthb_.jpg"},{"id":332712,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5171/sir20165171v2.pdf","text":"Report","size":"7.75 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5171 Report PDF"},{"id":349915,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2016/5171/versionHist.txt","text":"Version History","size":"2 KB","linkFileType":{"id":2,"text":"txt"},"description":"SIR 2016-5171 Version History"}],"country":"United States","state":"Arizona","county":"Mojave County","otherGeospatial":"Hualapai Reservation, Truxton Aquifer","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.994384765625,\n 35.55457449014312\n ],\n [\n -112.994384765625,\n 36.05798104702501\n ],\n [\n -112.2308349609375,\n 36.05798104702501\n ],\n [\n -112.2308349609375,\n 35.55457449014312\n ],\n [\n -112.994384765625,\n 35.55457449014312\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: Originally posted December 30, 2016; Version 2.0: December 14, 2017","contact":"Director,
Arizona Water Science Center
U.S. Geological Survey
520 N. Park Avenue
Tucson, AZ 85719
Elevation data derived from light detection and ranging present challenges for hydrologic modeling as the elevation surface includes bridge decks and elevated road features overlaying culvert drainage structures. In reality, water is carried through these structures; however, in the elevation surface these features impede modeled overland surface flow. Thus, a hydrologically-enforced elevation surface is needed for hydrodynamic modeling. In the Delaware River Basin, hydrologic-enforcement techniques were used to modify elevations to simulate how constructed drainage structures allow overland surface flow. By calculating residuals between unfilled and filled elevation surfaces, artificially pooled depressions that formed upstream of constructed drainage structure features were defined, and elevation values were adjusted by generating transects at the location of the drainage structures. An assessment of each hydrologically-enforced drainage structure was conducted using field-surveyed culvert and bridge coordinates obtained from numerous public agencies, but it was discovered the disparate drainage structure datasets were not comprehensive enough to assess all remotely located depressions in need of hydrologic-enforcement. Alternatively, orthoimagery was interpreted to define drainage structures near each depression, and these locations were used as reference points for a quantitative hydrologic-enforcement assessment. The orthoimagery-interpreted reference points resulted in a larger corresponding sample size than the assessment between hydrologic-enforced transects and field-surveyed data. This assessment demonstrates the viability of rules-based hydrologic-enforcement that is needed to achieve hydrologic connectivity, which is valuable for hydrodynamic models in sensitive coastal regions. Hydrologic-enforced elevation data are also essential for merging with topographic/bathymetric elevation data that extend over vulnerable urbanized areas and dynamic coastal regions.
","language":"English","publisher":"Coastal Education and Research Foundation","doi":"10.2112/SI76-009","usgsCitation":"Poppenga, S.K., and Worstell, B.B., 2016, Hydrologic connectivity: Quantitative assessments of hydrologic-enforced drainage structures in an elevation model: Journal of Coastal Research, v. Special Issue 76, p. 90-106, https://doi.org/10.2112/SI76-009.","productDescription":"17 p.","startPage":"90","endPage":"106","ipdsId":"IP-059049","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":470306,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://www.bioone.org/doi/10.2112/SI76-009","text":"External Repository"},{"id":332787,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"Special Issue 76","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"586cc690e4b0f5ce109fa943","contributors":{"authors":[{"text":"Poppenga, Sandra K. 0000-0002-2846-6836 spoppenga@usgs.gov","orcid":"https://orcid.org/0000-0002-2846-6836","contributorId":3327,"corporation":false,"usgs":true,"family":"Poppenga","given":"Sandra","email":"spoppenga@usgs.gov","middleInitial":"K.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"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":657389,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Worstell, Bruce B. 0000-0001-8927-3336 worstell@usgs.gov","orcid":"https://orcid.org/0000-0001-8927-3336","contributorId":1815,"corporation":false,"usgs":true,"family":"Worstell","given":"Bruce","email":"worstell@usgs.gov","middleInitial":"B.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":657390,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70178049,"text":"fs20163088 - 2016 - The 3D elevation program - Precision agriculture and other farm practices","interactions":[],"lastModifiedDate":"2018-02-15T16:10:39","indexId":"fs20163088","displayToPublicDate":"2016-12-27T10:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-3088","title":"The 3D elevation program - Precision agriculture and other farm practices","docAbstract":"A founding motto of the Natural Resources Conservation Service (NRCS), originally the Soil Conservation Service (SCS), explains that “If we take care of the land, it will take care of us.” Digital elevation models (DEMs; see fig. 1) are derived from light detection and ranging (lidar) data and can be processed to derive values such as slope angle, aspect, and topographic curvature. These three measurements are the principal parameters of the NRCS LidarEnhanced Soil Survey (LESS) model, which improves the precision of soil surveys, by more accurately displaying the slopes and soils patterns, while increasing the objectivity and science in line placement. As combined resources, DEMs, LESS model outputs, and similar derived datasets are essential for conserving soil, wetlands, and other natural resources managed and overseen by the NRCS and other Federal and State agencies.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20163088","usgsCitation":"Sugarbaker, L.J., and Carswell, W.J., Jr., 2016, The 3D Elevation Program—Precision agriculture and other farm practices: U.S. Geological Survey Fact Sheet 2016–3088, 2 p., https://dx.doi.org/10.3133/fs20163088.","productDescription":"2 p.","onlineOnly":"N","ipdsId":"IP-072256","costCenters":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"links":[{"id":332363,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2016/3088/coverthb.jpg"},{"id":332364,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2016/3088/fs20163088.pdf","text":"Report","size":"409 KB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2016-3088"}],"contact":"Director, National Geospatial Program
U.S. Geological Survey
12201 Sunrise Valley Drive
MS 511 National Center
Reston, VA 20192
Email: 3DEP@usgs.gov
http://www.usgs.gov/ngpo/
http://nationalmap.gov/3DEP/
1.Recently, estimators have been developed to estimate occupancy probabilities when false-positive detections occur during presence-absence surveys. Some of these estimators combine different types of survey data to improve estimates of occupancy. With these estimators, there is a tradeoff between the number of sample units surveyed, and the number and type of surveys at each sample unit. Guidance on efficient design of studies when false positives occur is unavailable.
2.For a range of scenarios, I identified survey designs that minimized the mean square error of the estimate of occupancy. I considered an approach that uses one survey method and two observation states and an approach that uses two survey methods. For each approach, I used numerical methods to identify optimal survey designs when model assumptions were met and parameter values were correctly anticipated, when parameter values were not correctly anticipated, and when the assumption of no unmodelled detection heterogeneity was violated.
3.Under the approach with two observation states, false positive detections increased the number of recommended surveys, relative to standard occupancy models. If parameter values could not be anticipated, pessimism about detection probabilities avoided poor designs. Detection heterogeneity could require more or fewer repeat surveys, depending on parameter values. If model assumptions were met, the approach with two survey methods was inefficient. However, with poor anticipation of parameter values, with detection heterogeneity, or with removal sampling schemes, combining two survey methods could improve estimates of occupancy.
4.Ignoring false positives can yield biased parameter estimates, yet false positives greatly complicate the design of occupancy studies. Specific guidance for major types of false-positive occupancy models, and for two assumption violations common in field data, can conserve survey resources. This guidance can be used to design efficient monitoring programs and studies of species occurrence, species distribution, or habitat selection, when false positives occur during surveys.
","language":"English","doi":"10.1111/2041-210X.12617","usgsCitation":"Clement, M., 2016, Designing occupancy studies when false-positive detections occur: Methods in Ecology and Evolution, v. 7, no. 12, p. 1529-1547, https://doi.org/10.1111/2041-210X.12617.","productDescription":"19 p.","startPage":"1529","endPage":"1547","ipdsId":"IP-073228","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":470312,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/2041-210x.12617","text":"Publisher Index Page"},{"id":332545,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":332511,"type":{"id":15,"text":"Index Page"},"url":"https://onlinelibrary.wiley.com/doi/10.1111/2041-210X.12617/abstract"}],"volume":"7","issue":"12","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2016-08-18","publicationStatus":"PW","scienceBaseUri":"58638bd3e4b0cd2dabe7beac","contributors":{"authors":[{"text":"Clement, Matthew mclement@usgs.gov","contributorId":138815,"corporation":false,"usgs":true,"family":"Clement","given":"Matthew","email":"mclement@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":656555,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70179254,"text":"ofr20161211 - 2016 - Development of a study design and implementation plan to estimate juvenile salmon survival in Lookout Point Reservoir and other reservoirs of the Willamette Project, western Oregon","interactions":[],"lastModifiedDate":"2017-01-02T09:56:52","indexId":"ofr20161211","displayToPublicDate":"2016-12-23T12:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-1211","title":"Development of a study design and implementation plan to estimate juvenile salmon survival in Lookout Point Reservoir and other reservoirs of the Willamette Project, western Oregon","docAbstract":"Survival estimates for juvenile salmon and steelhead fry in reservoirs impounded by high head dams are coveted data by resource managers. However, this information is difficult to obtain because these fish are too small for tagging using conventional methods such as passive-integrated transponders or radio or acoustic transmitters. We developed a study design and implementation plan to conduct a pilot evaluation that would assess the performance of two models for estimating fry survival in a field setting. The first model is a staggered-release recovery model that was described by Skalski and others (2009) and Skalski (2016). The second model is a parentage-based tagging N-mixture model that was developed and described in this document. Both models are conceptually and statistically sound, but neither has been evaluated in the field. In this document we provide an overview of a proposed study for 2017 in Lookout Point Reservoir, Oregon, that will evaluate survival of Chinook salmon fry using both models. This approach will allow us to test each model and compare survival estimates, to determine model performance and better understand these study designs using field-collected data.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161211","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers and the Oregon Department of Fish and Wildlife","usgsCitation":"Kock, T.J., Perry, R.W., Monzyk, F.R., Pope, A.C., and Plumb, J.M., 2016, Development of a study design and implementation plan to estimate juvenile salmon survival in Lookout Point Reservoir and other reservoirs of the Willamette Project, western Oregon: U.S. Geological Survey Open-File Report 2016–1211, 25 p., https://doi.org/10.3133/ofr20161211.","productDescription":"iv, 25 p.","numberOfPages":"34","onlineOnly":"Y","ipdsId":"IP-079919","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":332514,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1211/coverthb.jpg"},{"id":332515,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1211/ofr20161211.pdf","text":"Report","size":"6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1211 Report PDF"}],"country":"United States","state":"Oregon","otherGeospatial":"Dexter Dam, Dexter Reservoir, Lookout Point Reservoir, Lookout Point Dam, Middle Fork Willamette River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.89718627929688,\n 43.91768033000405\n ],\n [\n -122.81410217285155,\n 43.98589821991874\n ],\n [\n -122.64244079589842,\n 43.929055415997134\n ],\n [\n -122.5140380859375,\n 43.82808744469062\n ],\n [\n -122.63626098632812,\n 43.77059798257491\n ],\n [\n -122.75711059570312,\n 43.854830911225235\n ],\n [\n -122.89718627929688,\n 43.91768033000405\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115
http://wfrc.usgs.gov/
Recent advances in suspended-sediment monitoring tools and surrogate technologies have greatly improved the ability to quantify suspended-sediment concentrations and to estimate daily, seasonal, and annual suspended-sediment fluxes from rivers to coastal waters. However, little is known about the chemical composition of suspended sediment, and how it may vary spatially between water bodies and temporally within a single system owing to climate, seasonality, land use, and other natural and anthropogenic drivers. Many water-quality contaminants, such as organic and inorganic chemicals, nutrients, and pathogens, preferentially partition in sediment rather than water. Suspended sediment-bound chemical concentrations may be undetected during analysis of unfiltered water samples, owing to small water sample volumes and analytical limitations. Quantification of suspended sediment‑bound chemical concentrations is needed to improve estimates of total chemical concentrations, chemical fluxes, and exposure levels of aquatic organisms and humans in receiving environments. Despite these needs, few studies or monitoring programs measure the chemical composition of suspended sediment, largely owing to the difficulty in consistently obtaining samples of sufficient quality and quantity for laboratory analysis.
A field protocol is described here utilizing continuous‑flow centrifugation for the collection of suspended sediment for chemical analysis. The centrifuge used for development of this method is small, lightweight, and portable for the field applications described in this protocol. Project scoping considerations, deployment of equipment and system layout options, and results from various field and laboratory quality control experiments are described. The testing confirmed the applicability of the protocol for the determination of many inorganic and organic chemicals sorbed on suspended sediment, including metals, pesticides, polycyclic aromatic hydrocarbons, and polychlorinated biphenyls. The particle-size distribution of the captured sediment changes to a more fine-grained sample during centrifugation, and the necessity to account for this change when extrapolating chemical concentrations on the centrifuged sediment sample to the environmental water system is discussed.
The data produced using this method will help eliminate a data gap of suspended sediment-bound chemical concentrations, and will support management decisions, such as chemical source-control efforts or in-stream restoration activities. When coupled with streamflow and sediment flux data, it will improve estimates of riverine chemical fluxes, and will aid in assessing the importance and impacts of suspended sediment-bound chemicals to downstream freshwater and coastal marine ecosystems.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Section D: Water quality in Book 1: Collection of water data by direct measurement","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm1D6","collaboration":"Prepared in cooperation with the National Water Quality Monitoring Council and Washington State Department of Ecology","usgsCitation":"Conn, K.E., Dinicola, R.S., Black, R.W., Cox, S.E., Sheibley, R.W., Foreman, J.R., Senter, C.A., and Peterson, N.T., 2016, Continuous-flow centrifugation to collect suspended sediment for chemical analysis: U.S. Geological Survey Techniques and Methods, book 1, chap. D6, 31 p., plus appendixes, https://doi.org/10.3133/tm1D6.","productDescription":"Report: viii, 31 p.; Appendixes: A-E","numberOfPages":"44","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-079905","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":332505,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/tm/01/d6/tm1d6_appendixb.pdf","text":"Appendix B","size":"100 KB","linkFileType":{"id":1,"text":"pdf"},"description":"TM1-D6 Appendix B"},{"id":332503,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/01/d6/tm1d6.pdf","text":"Report","size":"2.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"TM1-D6 Report PDF"},{"id":332504,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/tm/01/d6/tm1d6_appendixa.xlsx","text":"Appendix A","size":"102 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"TM1-D6 Appendix A"},{"id":332506,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/tm/01/d6/tm1d6_appendixc.pdf","text":"Appendix C","size":"142 KB","linkFileType":{"id":1,"text":"pdf"},"description":"TM1-D6 Appendix C"},{"id":332507,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/tm/01/d6/tm1d6_appendixd.pdf","text":"Appendix D","size":"145 KB","linkFileType":{"id":1,"text":"pdf"},"description":"TM1-D6 Appendix D"},{"id":332508,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/tm/01/d6/tm1d6_appendixe.pdf","text":"Appendix E","size":"930 KB","linkFileType":{"id":1,"text":"pdf"},"description":"TM1-D6 Appendix E"},{"id":332502,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/01/d6/coverthb.jpg"}],"publicComments":"This report is Chapter 6 of Section D: Water quality in Book 1: Collection of water data by direct measurement.","contact":"Director, Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402
http://wa.water.usgs.gov
Suspended-sediment and total phosphorus loads were computed for two sites in the Upper Klamath Basin on the Wood and Williamson Rivers, the two main tributaries to Upper Klamath Lake. High temporal resolution turbidity and acoustic backscatter data were used to develop surrogate regression models to compute instantaneous concentrations and loads on these rivers. Regression models for the Williamson River site showed strong correlations of turbidity with total phosphorus and suspended-sediment concentrations (adjusted coefficients of determination [Adj R2]=0.73 and 0.95, respectively). Regression models for the Wood River site had relatively poor, although statistically significant, relations of turbidity with total phosphorus, and turbidity and acoustic backscatter with suspended sediment concentration, with high prediction uncertainty. Total phosphorus loads for the partial 2014 water year (excluding October and November 2013) were 39 and 28 metric tons for the Williamson and Wood Rivers, respectively. These values are within the low range of phosphorus loads computed for these rivers from prior studies using water-quality data collected by the Klamath Tribes. The 2014 partial year total phosphorus loads on the Williamson and Wood Rivers are assumed to be biased low because of the absence of data from the first 2 months of water year 2014, and the drought conditions that were prevalent during that water year. Therefore, total phosphorus and suspended-sediment loads in this report should be considered as representative of a low-water year for the two study sites. Comparing loads from the Williamson and Wood River monitoring sites for November 2013–September 2014 shows that the Williamson and Sprague Rivers combined, as measured at the Williamson River site, contributed substantially more suspended sediment to Upper Klamath Lake than the Wood River, with 4,360 and 1,450 metric tons measured, respectively.
Surrogate techniques have proven useful at the two study sites, particularly in using turbidity to compute suspended-sediment concentrations in the Williamson River. This proof-of-concept effort for computing total phosphorus concentrations using turbidity at the Williamson and Wood River sites also has shown that with additional samples over a wide range of flow regimes, high-temporal-resolution total phosphorus loads can be estimated on a daily, monthly, and annual basis, along with uncertainties for total phosphorus and suspended-sediment concentrations computed using regression models. Sediment-corrected backscatter at the Wood River has potential for estimating suspended-sediment loads from the Wood River Valley as well, with additional analysis of the variable streamflow measured at that site. Suspended-sediment and total phosphorus loads with a high level of temporal resolution will be useful to water managers, restoration practitioners, and scientists in the Upper Klamath Basin working toward the common goal of decreasing nutrient and sediment loads in Upper Klamath Lake.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165167","collaboration":"Prepared in cooperation with the Bureau of Reclamation and the Klamath Tribes","usgsCitation":"Schenk, L.N., Anderson, C.W., Diaz, Paul, and Stewart, M.A., 2016, Evaluating external nutrient and suspended-sediment loads to Upper Klamath Lake, Oregon, using surrogate regressions with real-time turbidity and acoustic backscatter data: U.S. Geological Survey Scientific Investigations Report 2016–5167, 46 p., https://doi.org/10.3133/sir20165167.","productDescription":"vii, 46 p.","numberOfPages":"58","onlineOnly":"Y","ipdsId":"IP-075160","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":332500,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5167/sir20165167.pdf","text":"Report","size":"6.5","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5167 Report PDF"},{"id":332499,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5167/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 -122.3,\n 42.0\n ],\n [\n -122.3,\n 43.3\n ],\n [\n -120.4,\n 43.3\n ],\n [\n -120.4,\n 42.0\n ],\n [\n -122.3,\n 42.0\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201
http://or.water.usgs.gov
Estimates of juvenile salmon survival are important data for fishery managers in the Yakima River Basin. Radiotelemetry studies during 2012–14 showed that tagged juvenile Chinook salmon (Oncorhynchus tshawytscha) that passed through the fish bypass at Roza Dam had lower survival than fish that passed through other routes at the dam. That study also identified flow-survival relationships in the reaches between the Roza Dam tailrace and Sunnyside Dam. During 2012–14, survival also was estimated through reaches downstream of Sunnyside Dam, but generally, sample sizes were low and the estimates were imprecise. In 2016, we conducted an evaluation using acoustic cameras and acoustic telemetry to build on information collected during the previous study. The goal of the 2016 research was to identify areas where mortality occurs in the fish bypass at Roza Dam, and to estimate reach-specific survival in reaches downstream of the dam. The 2016 study included juvenile Chinook salmon and coho salmon (O. kisutch).
Three acoustic cameras were used to observe fish behavior (1) near the entrances to the fish bypass, (2) at a midway point in the fish bypass (convergence vault), and (3) at the bypass outfall. In total, 504 hours of acoustic camera footage was collected at these locations. We determined that smolt-sized fish (95–170 millimeters [mm]) were present in the highest proportions at each location, but predator-sized fish (greater than 250 mm) also were present at each site. Fish presence generally peaked during nighttime hours and crepuscular periods, and was low during daytime hours. In the convergence vault, smolt-sized fish exhibited holding behavior patterns, which may explain why some fish delayed while passing through the bypass.
Some of the acoustic-tagged fish were delayed in the fish bypass following release, but there was no evidence to suggest that they experienced higher mortality than fish that were released at the bypass outfall or downstream of the dam. Most of the tagged fish that were released in the fish bypass moved downstream and re-entered the river within 12 hours, but 9.8 percent of the Chinook salmon and 15.7 percent of the coho salmon remained in the bypass for 2.5–17.4 days. We developed a set of models for Chinook salmon and coho salmon and used model selection to determine if release site was an important predictor of survival of tagged fish. The models that provided the best fit to the Chinook salmon and coho salmon datasets did not include release site as a covariate. Furthermore, survival estimates for groups of fish from the various release sites were nearly identical for both species. Based on these observations, it appears that passage through the fish bypass did not result in increased mortality relative to groups of fish released downstream of the bypass.
Juvenile Chinook salmon migrated downstream faster than juvenile coho salmon and survival for each species varied with release timing. Median travel time from release at Roza Dam to arrival at a detection gate located at river kilometer (rkm) 527.8 on the Columbia River was 15.4 days for Chinook salmon and 37.4 days for coho salmon. Cumulative survival from Roza Dam to the Columbia River detection gate ranged from 0.299 to 0.678 for Chinook salmon, and from 0.321 to 0.627 for coho salmon. Survival was highest for both species when tagged fish were released in mid-April and lowest when tagged fish were released in early-May. Reach-specific survival estimates were standardized to create estimates that described survival per 100 rkm, which showed that survival was very low (less than 0.500) for some release groups, particularly in the Roza, Sunnyside, and Chandler diversion reaches. A more extensive analysis of reach-specific survival is planned for this dataset, which should provide insights into covariates that affected survival during 2016.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161210","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Kock, T.J., Perry, R.W., and Hansen, A.C., 2016, Survival of juvenile Chinook salmon and coho salmon in the Roza Dam fish bypass and in downstream reaches of the Yakima River, Washington, (ver. 1.1, April 2017): U.S. Geological Survey Open-File Report 2016–1210, 32 p., https://doi.org/10.3133/ofr20161210.","productDescription":"vi, 32 p.","numberOfPages":"42","onlineOnly":"Y","ipdsId":"IP-079554","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":332490,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1210/ofr20161210.pdf","text":"Report","size":"9.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1210 Report PDF"},{"id":339521,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2016/1210/versionHist.txt","text":"Version 1.1","size":"3 KB","linkFileType":{"id":2,"text":"txt"},"description":"OFR 2016-1210 Version History"},{"id":339519,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1210/coverthb3.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Roza Dam, Yakima River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.53076171875,\n 46.14178273759234\n ],\n [\n -121.53076171875,\n 47.46523622438362\n ],\n [\n -119.04235839843749,\n 47.46523622438362\n ],\n [\n -119.04235839843749,\n 46.14178273759234\n ],\n [\n -121.53076171875,\n 46.14178273759234\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: Originally posted December 22, 2016; Version 1.1: April 10, 2017","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115
https://wfrc.usgs.gov/
Discharge from springs in Florida is sourced from aquifers, such as the Upper Floridan aquifer, which is overlain by an upper confining unit that locally can have properties of an aquifer. Water levels in aquifers are affected by several factors, such as precipitation, recharge, and groundwater withdrawals, which in turn can affect discharge from springs. Therefore, identifying groundwater sources and recharge characteristics can be important in assessing how these factors might affect flows and water levels in springs and can be informative in broader applications such as groundwater modeling. Recharge characteristics include the residence time of water at the surface, apparent age of recharge, and recharge water temperature.
The groundwater sources and recharge characteristics of three springs that discharge from the banks of the Suwannee River in northern Florida were assessed for this study: Bell Springs, White Springs, and Suwannee Springs. Sources of groundwater were also assessed for a 150-foot-deep well finished within the Upper Floridan aquifer, hereafter referred to as the UFA well. Water samples were collected for geochemical analyses in November 2012 and October 2013 from the three springs and the UFA well. Samples were analyzed for a suite of major ions, dissolved gases, and isotopes of sulfur, strontium, oxygen, and hydrogen. Daily means of water level and specific conductance at White Springs were continuously recorded from October 2012 through December 2013 by the Suwannee River Water Management District. Suwannee River stage at White Springs was computed on the basis of stage at a U.S. Geological Survey streamgage about 2.4 miles upstream. Water levels in two wells, located about 2.5 miles northwest and 13 miles southeast of White Springs, were also used in the analyses.
Major ion concentrations were used to differentiate water from the springs and Upper Floridan aquifer into three groups: Bell Springs, UFA well, and White and Suwannee Springs. When considered together, evidence from water-level, specific conductance, major-ion concentration, and isotope data indicated that groundwater at Bell Springs and the UFA well was a mixture of surface water and groundwater from the upper confining unit, and that groundwater at White and Suwannee Springs was a mixture of surface water, groundwater from the upper confining unit, and groundwater from the Upper Floridan aquifer. Higher concentrations of magnesium in groundwater samples at the UFA well than in samples at Bell Springs might indicate less mixing with surface water at the UFA well than at Bell Springs. Characteristics of surface-water recharge, such as residence time at the surface, apparent age, and recharge water temperature, were estimated on the basis of isotopic ratios, and dissolved concentrations of gases such as argon, tritium, and sulfur hexafluoride. Oxygen and deuterium isotopic ratios were consistent with rapid recharge by rainwater for samples collected in 2012, and longer residence time at the surface (ponding) for samples collected in 2013. Apparent ages of groundwater samples, computed on the basis of tritium activity and sulfur hexafluoride concentration, indicated groundwater recharge occurred after the late 1980s; however, the estimated apparent ages likely represent the average of ages of multiple sources. Recharge since the 1980s is consistent with groundwater from shallow sources, such as the upper confining unit and Upper Floridan aquifer. Recharge water temperature computed for the three springs and UFA well averaged 20.1 degrees Celsius, which is similar to the mean annual air temperature of 20.6 degrees Celsius at a nearby weather station for 1960–2014.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161190","collaboration":"Prepared in cooperation with the Suwannee River Water Management District","usgsCitation":"Stamm, J.F., and McBride, W.S., 2016, Sources of groundwater and characteristics of surface-water recharge at Bell, White, and Suwannee Springs, Florida: 2012–13: U.S. Geological Survey Open-File Report 2016–1190, 27 p., https://doi.org/10.3133/ofr20161190.","productDescription":"vii, 27 p.","numberOfPages":"40","onlineOnly":"Y","ipdsId":"IP-066218","costCenters":[{"id":270,"text":"FLWSC-Tampa","active":true,"usgs":true}],"links":[{"id":332418,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1190/coverthb.jpg"},{"id":332419,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1190/ofr20161190.pdf","text":"Report","size":"1.73 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016–1190"}],"country":"United States","state":"Florida","otherGeospatial":"Bell Spring, Suwannee Spring, White Spring","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.033333,\n 30.583333\n ],\n [\n -83.033333,\n 30.166667\n ],\n [\n -82.616667,\n 30.166667\n ],\n [\n -82.616667,\n 30.583333\n ],\n [\n -83.033333,\n 30.583333\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
Accurate measurements of fluvial sediment are important for assessing stream ecological health, calculating flood levels, computing sediment budgets, and managing and protecting water resources. Sediment-enriched rivers in Minnesota are a concern among Federal, State, and local governments because turbidity and sediment-laden waters are the leading impairments and affect more than 6,000 miles of rivers in Minnesota. The suspended sediment in the lower Minnesota River is deleterious, contributing about 75 to 90 percent of the suspended sediment being deposited into Lake Pepin. The Saint Paul District of the U.S. Army Corps of Engineers and the Lower Minnesota River Watershed District collaborate to maintain a navigation channel on the lower 14.7 miles of the Minnesota River through scheduled dredging operations. The Minnesota Pollution Control Agency has adopted a sediment-reduction strategy to reduce sediment in the Minnesota River by 90 percent by 2040.
The U.S. Geological Survey, in cooperation with the U.S. Army Corps of Engineers, the Minnesota Pollution Control Agency, and the Lower Minnesota River Watershed District, collected suspended-sediment, bedload, and particle-size samples at five sites in the lower Minnesota River Basin during water years 2011 through 2014 and surrogate measurements of acoustic backscatter at one of these sites on the lower Minnesota River during water years 2012 through 2016 to quantify sediment loads and improve understanding of sediment-transport relations. Annual sediment loads were computed for calendar years 2011 through 2014.
Data collected from water years 2011 through 2014 indicated that two tributaries, Le Sueur River and High Island Creek, had the highest sediment yield and concentrations of suspended sediment. These tributaries also had greater stream gradients than the sites on the Minnesota River. Suspended fines were greater than suspended sand at all sites in the study area. The range of median particle sizes matched the range for stream gradients from greatest to smallest. Bedload ranged from 3 to 20 percent of the total load at the Le Sueur River, Minnesota River at Mankato, and High Island Creek and was less than 1 percent of the total load at the Minnesota River near Jordan and at Fort Snelling State Park. The reach of the Minnesota River between Mankato and Jordan is a major source of sediment, with the sediment yield at Jordan being two and a half times greater than at Mankato. Between Jordan and Fort Snelling, the sediment yield decreases substantially, which indicates that the Minnesota River in this reach is a sink for sediment. Surrogate measurements (acoustic backscatter) collected with suspended-sediment concentration data from water years 2012 through 2016 from the Minnesota River at Fort Snelling State Park indicated strong relations between the acoustic backscatter and suspended-sediment concentrations. These results point to the dynamic nature of sediment aggradation, degradation, and transport in the Minnesota River Basin. The analyses described in this report will improve the understanding of sediment-transport relations and sediment budgets in the Minnesota River Basin.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165174","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers, Minnesota Pollution Control Agency, and Lower Minnesota River Watershed District","usgsCitation":"Groten, J.T., Ellison, C.A., and Hendrickson, J.S., 2016, Suspended-sediment concentrations, bedload, particle sizes, surrogate measurements, and annual sediment loads for selected sites in the lower Minnesota River Basin, water years 2011 through 2016: U.S. Geological Survey Scientific Investigations Report 2016–5174, 29 p., https://doi.org/10.3133/sir20165174.","productDescription":"Report: viii, 29 p.; Appendix Tables","numberOfPages":"42","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-077057","costCenters":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"links":[{"id":332354,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5174/coverthb.jpg"},{"id":332355,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5174/sir20165174.pdf","text":"Report","size":"1.87 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016–5174"},{"id":332356,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5174/sir20165174_appendix_tables.xlsx","text":"Appendix Tables","size":"240 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2016–5174 Appendix 1"}],"country":"United States","state":"Minnesota","otherGeospatial":"Minnesota River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -95.56732177734375,\n 43.97898113341921\n ],\n [\n -95.56732177734375,\n 44.853921768268805\n ],\n [\n -93.22723388671875,\n 44.853921768268805\n ],\n [\n -93.22723388671875,\n 43.97898113341921\n ],\n [\n -95.56732177734375,\n 43.97898113341921\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Minnesota Water Science Center
U.S. Geological Survey
2280 Woodale Drive
Mounds View, Minnesota 55112
The U.S. Geological Survey, in cooperation with the New England Interstate Water Pollution Control Commission and the Vermont Department of Environmental Conservation, estimated daily and 9-month concentrations and fluxes of total and dissolved phosphorus, total nitrogen, chloride, and total suspended solids from 1990 (or first available date) through 2014 for 18 tributaries of Lake Champlain. Estimates of concentration and flux, provided separately in Medalie (2016), were made by using the Weighted Regressions on Time, Discharge, and Season (WRTDS) regression model and update previously published WRTDS model results with recent data. Assessment of progress towards meeting phosphorus-reduction goals outlined in the Lake Champlain management plan relies on annual estimates of phosphorus flux. The percent change in annual concentration and flux is provided for two time periods. The R package EGRETci was used to estimate the uncertainty of the trend estimate. Differences in model specification and function between this study and previous studies that used WRTDS to estimate concentration and flux using data from Lake Champlain tributaries are described.
Winter data were too sparse and nonrepresentative to use for estimates of concentration and flux but were sufficient for estimating the percentage of total annual flux over the period of record. Median winter-to-annual fractions ranged between 21 percent for total suspended solids and 27 percent for dissolved phosphorus. The winter contribution was largest for all constituents from the Mettawee River and smallest from the Ausable River.
For the full record (1991 through 2014 for total and dissolved phosphorus and chloride and 1993 through 2014 for nitrogen and total suspended solids), 6 tributaries had decreasing trends in concentrations of total phosphorus, and 12 had increasing trends; concentrations of dissolved phosphorus decreased in 6 and increased in 8 tributaries; fluxes of total phosphorus decreased in 5 and increased in 10 tributaries; and fluxes of dissolved phosphorus decreased in 4 and increased in 10 tributaries (where the number of increasing and decreasing trends does not add up to 18, the remainder of tributaries had no trends). Concentrations and fluxes of nitrogen decreased in 10 and increased in 4 tributaries and of chloride decreased in 2 and increased in 15 tributaries. Concentrations of total suspended solids decreased in 4 and increased in 8 tributaries, and fluxes of total suspended solids decreased in 3 and increased in 11 tributaries.
Although time intervals for the percent changes from this report are not completely synchronous with those from previous studies, the numbers of and specific tributaries with overall negative percent changes in concentration and flux are similar. Concentration estimates of total phosphorus in the Winooski River were used to trace whether changes in trends between a previous study and the current study were due generally to differences in model specifications or differences from 4 years of additional data. The Winooski River analysis illustrates several things: that keeping all model specifications equal, concentration estimates increased from 2010 to 2014; the effects of a smoothing algorithm used in the current study that was not available previously; that narrowing model half-window widths increased year-to-year variations; and that the change from an annual to a 9-month basis by omitting winter estimates changed a few individual points but not the overall shape of the flow-normalized curve. Similar tests for other tributaries showed that the primary effect of differences in model specifications between the previous and current studies was perhaps to increase scatter over time but that changes in trends generally were the result of 4 years of additional data rather than artifacts of model differences.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161200","collaboration":"Prepared in cooperation with the New England Interstate Water Pollution Control Commission and the Vermont Department of Environmental Conservation","usgsCitation":"Medalie, Laura, 2016, Concentration, flux, and trend estimates with uncertainty for nutrients, chloride, and total suspended solids in tributaries of Lake Champlain, 1990–2014: U.S. Geological Survey Open-File Report 2016–1200, 22 p., https://doi.org/10.3133/ofr20161200.","productDescription":"Report: iv, 22 p.; Data Release","numberOfPages":"26","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-076110","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":438482,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7RN360M","text":"USGS data release","linkHelpText":"Estimates of annual and daily concentration and flux of nutrients, chloride, and suspended sediment in tributaries of Lake Champlain, 1990 through 2014"},{"id":332328,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7RN360M","text":"USGS data release - Estimates of annual and daily concentration and flux of nutrients, chloride, and total suspended solids in tributaries of Lake Champlain, 1990 through 2014","description":"Usgs Data Release"},{"id":332327,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1200/ofr20161200.pdf","text":"Report","size":"858 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016–1200"},{"id":332326,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1200/coverthb.jpg"}],"country":"United States","state":"New York, Vermont","otherGeospatial":"Lake Champlain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.597412109375,\n 44.01454613545038\n ],\n [\n -73.00140380859375,\n 44.01454613545038\n ],\n [\n -73.00140380859375,\n 45.00365115687186\n ],\n [\n -73.597412109375,\n 45.00365115687186\n ],\n [\n -73.597412109375,\n 44.01454613545038\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
331 Commerce Way
Pembroke, NH 03275
http://newengland.water.usgs.gov
","tableOfContents":"The passage of Hurricane Matthew across the central and eastern regions of North Carolina and South Carolina during October 7–9, 2016, resulted in heavy rainfall that caused major flooding in parts of the eastern Piedmont in North Carolina and coastal regions of both States. Rainfall totals of 3 to 8 inches and 8 to more than 15 inches were widespread throughout the central and eastern regions, respectively. U.S. Geological Survey streamgages recorded peaks of record at 26 locations, including 11 sites with long-term periods of 30 or more years of record. A total of 44 additional locations had peak streamflows that ranked in the top 5 for the period of record. Additionally, among 23 U.S. Geological Survey streamgages within the affected basins in North Carolina where stage-only data are collected, new peak stages were recorded at 5 locations during the flooding. U.S. Geological Survey personnel made 102 streamflow measurements at 60 locations in both States to verify, update, or extend existing rating curves (which are used to determine stage-discharge relations) during the October 2016 flood event.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161205","usgsCitation":"Weaver, J.C., Feaster, T.D., and Robbins, J.C., 2016, Preliminary peak stage and streamflow data at selected streamgaging stations in North Carolina and South Carolina for flooding following Hurricane Matthew, October 2016: U.S. Geological Survey Open-File Report 2016–1205, 38 p., https://doi.org/10.3133/ofr20161205.","productDescription":"v, 38 p.","numberOfPages":"48","onlineOnly":"Y","ipdsId":"IP-081734","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":332170,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1205/coverthb.jpg"},{"id":332171,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1205/ofr20161205.pdf","text":"Report","size":"4.31 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 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Carolina\",\"nation\":\"USA \"}}]}","contact":"Director, South Atlantic Water Science Center
U.S. Geological Survey
720 Gracern Road
Stephenson Center, Suite 129
Columbia, SC 29210
http://www.usgs.gov/water/southatlantic/
Ohio’s water resources support a complex web of human activities and nature—clean and abundant water is needed for drinking, recreation, farming, and industry, as well as for fish and wildlife needs. Although rainfall in normal years can support these activities and needs, occasional floods and droughts can disrupt streamflow, groundwater, water availability, water quality, recreation, and aquatic habitats. Ohio is bordered by the Ohio River and Lake Erie; it has over 44,000 miles of streams and more than 60,000 lakes and ponds (State of Ohio, 1994). Nearly all of the rural population obtains drinking water from groundwater sources.
The U.S. Geological Survey (USGS) works in cooperation with local, State, and other Federal agencies, as well as universities, to furnish decisionmakers, policy makers, USGS scientists, and the general public with reliable scientific information and tools to assist them in management, stewardship, and use of Ohio’s natural resources. The diversity of scientific expertise among USGS personnel enables them to carry out large- and small-scale multidisciplinary studies. The USGS is unique among government organizations because it has neither regulatory nor developmental authority—its sole product is impartial, credible, relevant, and timely scientific information, equally accessible and available to everyone. The USGS Ohio Water Science Center provides reliable hydrologic and water-related ecological information to aid in the understanding of the use and management of the Nation’s water resources, in general, and Ohio’s water resources, in particular. This fact sheet provides an overview of current (2016) or recently completed USGS studies and data activities pertaining to water resources in Ohio. More information regarding projects of the USGS Ohio Water Science Center is available at http://oh.water.usgs.gov/.
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\"}}]}","contact":"Director, Ohio Water Science Center
6460 Busch Blvd, Suite 100
Columbus, OH 43229
Phone (614) 430-7700
http://oh.water.usgs.gov/
Most animals live in seasonal environments and experience very different conditions throughout the year. Behavioral strategies like migration, hibernation, and a life cycle adapted to the local seasonality help to cope with fluctuations in environmental conditions. Thus, how an individual utilizes the environment depends both on the current availability of habitat and the behavioral prerequisites of the individual at that time. While the increasing availability and richness of animal movement data has facilitated the development of algorithms that classify behavior by movement geometry, changes in the environmental correlates of animal movement have so far not been exploited for a behavioral annotation. Here, we suggest a method that uses these changes in individual–environment associations to divide animal location data into segments of higher ecological coherence, which we term niche segmentation. We use time series of random forest models to evaluate the transferability of habitat use over time to cluster observational data accordingly. We show that our method is able to identify relevant changes in habitat use corresponding to both changes in the availability of habitat and how it was used using simulated data, and apply our method to a tracking data set of common teal (Anas crecca). The niche segmentation proved to be robust, and segmented habitat suitability outperformed models neglecting the temporal dynamics of habitat use. Overall, we show that it is possible to classify animal trajectories based on changes of habitat use similar to geometric segmentation algorithms. We conclude that such an environmentally informed classification of animal trajectories can provide new insights into an individuals' behavior and enables us to make sensible predictions of how suitable areas might be connected by movement in space and time.
","language":"English","publisher":"Ecological Society of America","publisherLocation":"Washington, D.C.","doi":"10.1002/ecs2.1498","usgsCitation":"van Toor, M., Newman, S.H., Takekawa, J.Y., Wegmann, M., and Safi, K., 2016, Temporal segmentation of animal trajectories informed by habitat use: Ecosphere, v. 7, no. 10, e01498;16 p., https://doi.org/10.1002/ecs2.1498.","productDescription":"e01498;16 p.","ipdsId":"IP-066487","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":470318,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.1498","text":"Publisher Index Page"},{"id":332260,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"10","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2016-10-20","publicationStatus":"PW","scienceBaseUri":"58590007e4b03639a6025e25","contributors":{"authors":[{"text":"van Toor, Marielle L.","contributorId":177537,"corporation":false,"usgs":false,"family":"van Toor","given":"Marielle L.","affiliations":[],"preferred":false,"id":656114,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Newman, Scott H.","contributorId":101372,"corporation":false,"usgs":true,"family":"Newman","given":"Scott","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":656115,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Takekawa, John Y. 0000-0003-0217-5907 john_takekawa@usgs.gov","orcid":"https://orcid.org/0000-0003-0217-5907","contributorId":176168,"corporation":false,"usgs":true,"family":"Takekawa","given":"John","email":"john_takekawa@usgs.gov","middleInitial":"Y.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":656116,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wegmann, Martin","contributorId":177540,"corporation":false,"usgs":false,"family":"Wegmann","given":"Martin","email":"","affiliations":[],"preferred":false,"id":656117,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Safi, Kamran","contributorId":83036,"corporation":false,"usgs":true,"family":"Safi","given":"Kamran","affiliations":[],"preferred":false,"id":656118,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70177032,"text":"sir20165148 - 2016 - Mechanisms of aquatic species invasions across the South Atlantic Landscape Conservation Cooperative region","interactions":[],"lastModifiedDate":"2016-12-15T16:03:23","indexId":"sir20165148","displayToPublicDate":"2016-12-15T15:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-5148","title":"Mechanisms of aquatic species invasions across the South Atlantic Landscape Conservation Cooperative region","docAbstract":"Invasive species are a global issue, and the southeastern United States is not immune to the problems they present. Therefore, various analyses using modeling and exploratory statistics were performed on the U.S. Geological Survey Nonindigenous Aquatic Species (NAS) Database with the primary objective of determining the most appropriate use of presence-only data as related to invasive species in the South Atlantic Landscape Conservation Cooperative (SALCC) region. A hierarchical model approach showed that a relatively small amount of high-quality data from planned surveys can be used to leverage the information in presence-only observations, having a broad spatial coverage and high biases of observer detection and in site selection. Because a variety of sampling protocols can be used in planned surveys, this approach to the analysis of presence-only data is widely applicable. An important part of the management of natural landscapes is the preservation of designated protected areas. When the hydrologic connection was considered in this analysis, the number of potential invaders that could spread to each protected area within the SALCC region was greatly increased, with a mean exceeding 30 species and the maximum reaching 57 species. Nearly all protected areas are hydrologically connected to at least 20 nonindigenous aquatic species. To examine possible factors which may contribute to nonindigenous aquatic species richness in the SALCC region, a set of exploratory statistics was employed. The best statistical model that included a combination of three anthropogenic variables (densities of housing, roads, and reservoirs) and two environmental variables (elevation range and longitude) explained approximately 62 percent of the variation in introduced species richness. Highest nonindigenous aquatic species richness occurred in the more upland, mountainous regions, where elevation range favored reservoirs and attracted urban centers. Lastly, patterns seen in a diffusion model may reflect less about the diffusion process of the organism and more about the opportunistic nature of the data collection process. These results of the model are considered exploratory in nature.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165148","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service and the South Atlantic Landscape Conservation Cooperative","usgsCitation":"Benson, A.J., Stith, B.M., and Engel, V.C., 2016, Mechanisms of aquatic species invasions across the South Atlantic Landscape Conservation Cooperative region: U.S. Geological Survey Scientific Investigations Report 2016–5148, 68 p., https://doi.org/10.3133/sir20165148.","productDescription":"Report: viii, 68 p.; Data Release","numberOfPages":"80","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-074281","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":332134,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5148/coverthb.jpg"},{"id":332136,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F75X2721","text":"USGS data release - 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U.S. Geological Survey
7920 NW 71st Street
Gainesville, FL 32653
https://www.usgs.gov/centers/wetland-and-aquatic-research-center-warc
","tableOfContents":"A multireaction chemical equilibria geothermometry (MEG) model applicable to high-temperature geothermal systems has been developed over the past three decades. Given sufficient data, this model provides more constraint on calculated reservoir temperatures than classical chemical geothermometers that are based on either the concentration of silica (SiO2), or the ratios of cation concentrations. A set of 23 chemical analyses from Ojo Caliente Spring and 22 analyses from other thermal features in the Lower Geyser Basin of Yellowstone National Park are used to examine the sensitivity of calculated reservoir temperatures using the GeoT MEG code (Spycher et al. 2013, 2014) to quantify the effects of solute concentrations, degassing, and mineral assemblages on calculated reservoir temperatures. Results of our analysis demonstrate that the MEG model can resolve reservoir temperatures within approximately ±15°C, and that natural variation in fluid compositions represents a greater source of variance in calculated reservoir temperatures than variations caused by analytical uncertainty (assuming ~5% for major elements). The analysis also suggests that MEG calculations are particularly sensitive to variations in silica concentration, the concentrations of the redox species Fe(II) and H2S, and that the parameters defining steam separation and CO2 degassing from the liquid may be adequately determined by numerical optimization. Results from this study can provide guidance for future applications of MEG models, and thus provide more reliable information on geothermal energy resources during exploration.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2016.10.010","usgsCitation":"King, J.M., Hurwitz, S., Lowenstern, J.B., Nordstrom, D.K., and McCleskey, R.B., 2016, Multireaction equilibrium geothermometry: A sensitivity analysis using data from the Lower Geyser Basin, Yellowstone National Park, USA: Journal of Volcanology and Geothermal Research, v. 328, p. 105-114, https://doi.org/10.1016/j.jvolgeores.2016.10.010.","productDescription":"9 p.","startPage":"105","endPage":"114","ipdsId":"IP-080520","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":335171,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Montana, Wyoming","otherGeospatial":"Yellowstone National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.42333984375,\n 43.40903821777055\n ],\n [\n -109.62158203125,\n 43.40903821777055\n ],\n [\n -109.62158203125,\n 45.251688256117646\n ],\n [\n -111.42333984375,\n 45.251688256117646\n ],\n [\n -111.42333984375,\n 43.40903821777055\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"328","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"589ffefbe4b099f50d3e0447","contributors":{"authors":[{"text":"King, Jonathan M. 0000-0003-0834-2200","orcid":"https://orcid.org/0000-0003-0834-2200","contributorId":179317,"corporation":false,"usgs":false,"family":"King","given":"Jonathan","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":663297,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hurwitz, Shaul 0000-0001-5142-6886 shaulh@usgs.gov","orcid":"https://orcid.org/0000-0001-5142-6886","contributorId":2169,"corporation":false,"usgs":true,"family":"Hurwitz","given":"Shaul","email":"shaulh@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":663295,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lowenstern, Jacob B. 0000-0003-0464-7779 jlwnstrn@usgs.gov","orcid":"https://orcid.org/0000-0003-0464-7779","contributorId":2755,"corporation":false,"usgs":true,"family":"Lowenstern","given":"Jacob","email":"jlwnstrn@usgs.gov","middleInitial":"B.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":663296,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nordstrom, D. 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Blaine 0000-0002-2521-8052 rbmccles@usgs.gov","orcid":"https://orcid.org/0000-0002-2521-8052","contributorId":147399,"corporation":false,"usgs":true,"family":"McCleskey","given":"R.","email":"rbmccles@usgs.gov","middleInitial":"Blaine","affiliations":[{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":663298,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70179087,"text":"70179087 - 2016 - Impacts of the Deepwater Horizon oil spill on deep-sea coral-associated sediment communities","interactions":[],"lastModifiedDate":"2016-12-15T13:29:18","indexId":"70179087","displayToPublicDate":"2016-12-15T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2663,"text":"Marine Ecology Progress Series","active":true,"publicationSubtype":{"id":10}},"title":"Impacts of the Deepwater Horizon oil spill on deep-sea coral-associated sediment communities","docAbstract":"Cold-water corals support distinct populations of infauna within surrounding sediments that provide vital ecosystem functions and services in the deep sea. Yet due to their sedentary existence, infauna are vulnerable to perturbation and contaminant exposure because they are unable to escape disturbance events. While multiple deep-sea coral habitats were injured by the 2010 Deepwater Horizon (DWH) oil spill, the extent of adverse effects on coral-associated sediment communities is unknown. In 2011, sediments were collected adjacent to several coral habitats located 6 to 183 km from the wellhead in order to quantify the extent of impact of the DWH spill on infaunal communities. Higher variance in macrofaunal abundance and diversity, and different community structure (higher multivariate dispersion) were associated with elevated hydrocarbon concentrations and contaminants at sites closest to the wellhead (MC294, MC297, and MC344), consistent with impacts from the spill. In contrast, variance in meiofaunal diversity was not significantly related to distance from the wellhead and no other community metric (e.g. density or multivariate dispersion) was correlated with contaminants or hydrocarbon concentrations. Concentrations of polycyclic aromatic hydrocarbons (PAH) provided the best statistical explanation for observed macrofaunal community structure, while depth and presence of fine-grained mud best explained meiofaunal community patterns. Impacts associated with contaminants from the DWH spill resulted in a patchwork pattern of infaunal community composition, diversity, and abundance, highlighting the role of variability as an indicator of disturbance. These data represent a useful baseline for tracking post-spill recovery of these deep-sea communities.
","language":"English","publisher":"Inter-Research","doi":"10.3354/meps11905","usgsCitation":"Demopoulos, A.W., Bourque, J.R., Cordes, E.E., and Stamler, K., 2016, Impacts of the Deepwater Horizon oil spill on deep-sea coral-associated sediment communities: Marine Ecology Progress Series, v. 561, p. 51-68, https://doi.org/10.3354/meps11905.","productDescription":"18 p.","startPage":"51","endPage":"68","ipdsId":"IP-073329","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":332167,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"561","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5853ba36e4b0e2663625f2a6","contributors":{"authors":[{"text":"Demopoulos, Amanda W.J. 0000-0003-2096-4694 ademopoulos@usgs.gov","orcid":"https://orcid.org/0000-0003-2096-4694","contributorId":145681,"corporation":false,"usgs":true,"family":"Demopoulos","given":"Amanda","email":"ademopoulos@usgs.gov","middleInitial":"W.J.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":656000,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bourque, Jill R. 0000-0003-3809-2601 jbourque@usgs.gov","orcid":"https://orcid.org/0000-0003-3809-2601","contributorId":5452,"corporation":false,"usgs":true,"family":"Bourque","given":"Jill","email":"jbourque@usgs.gov","middleInitial":"R.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":656001,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cordes, Erik E.","contributorId":37623,"corporation":false,"usgs":false,"family":"Cordes","given":"Erik","email":"","middleInitial":"E.","affiliations":[{"id":16710,"text":"Temple University, Department of Biology","active":true,"usgs":false}],"preferred":false,"id":656002,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stamler, Katherine kstamler@usgs.gov","contributorId":177508,"corporation":false,"usgs":true,"family":"Stamler","given":"Katherine","email":"kstamler@usgs.gov","affiliations":[],"preferred":true,"id":656003,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}