The U.S. Geological Survey monthly water balance model (MWBM) was enhanced with the capability to simulate glaciers in order to make it more suitable for simulating cold region hydrology. The new model, MWBMglacier, is demonstrated in the heavily glacierized and ecologically important Copper River watershed in Southcentral Alaska. Simulated water budget components compared well to satellite‐based observations and ground measurements of streamflow, evapotranspiration, snow extent, and total water storage, with differences ranging from 0.2% to 7% of the precipitation flux. Nash Sutcliffe efficiency for simulated and observed streamflow was greater than 0.8 for six of eight stream gages. Snow extent matched satellite‐based observations with Nash Sutcliffe efficiency values of greater than 0.89 in the four Copper River ecoregions represented. During the simulation period 1949 to 2009, glacier ice melt contributed 25% of total runoff, ranging from 12% to 45% in different tributaries, and glacierized area was reduced by 6%. Statistically significant (p < 0.05) decreasing and increasing trends in annual glacier mass balance occurred during the multidecade cool and warm phases of the Pacific Decadal Oscillation, respectively, reinforcing the link between climate perturbations and glacier mass balance change. The simulations of glaciers and total runoff for a large, remote region of Alaska provide useful data to evaluate hydrologic, cryospheric, ecologic, and climatic trends. MWBM glacier is a valuable tool to understand when, and to what extent, streamflow may increase or decrease as glaciers respond to a changing climate.
","language":"English","publisher":"AGU","doi":"10.1029/2017JF004482","usgsCitation":"Valentin, M.M., Viger, R.J., Van Beusekom, A.E., Hay, L.E., Hogue, T.S., and Foks, N.L., 2018, Enhancement of a parsimonious water balance model to simulate surface hydrology in a glacierized watershed: Journal of Geophysical Research F: Earth Surface, v. 123, no. 5, p. 1116-1132, https://doi.org/10.1029/2017JF004482.","productDescription":"17 p.","startPage":"1116","endPage":"1132","ipdsId":"IP-094374","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37226,"text":"Core Science Analytics, Synthesis, and Libraries","active":true,"usgs":true},{"id":37273,"text":"Advanced Research Computing (ARC)","active":true,"usgs":true}],"links":[{"id":468839,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2017jf004482","text":"Publisher Index Page"},{"id":354424,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"123","issue":"5","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-05-23","publicationStatus":"PW","scienceBaseUri":"5b155d78e4b092d9651e1b3c","contributors":{"authors":[{"text":"Valentin, Melissa M.","contributorId":205172,"corporation":false,"usgs":false,"family":"Valentin","given":"Melissa","email":"","middleInitial":"M.","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":736281,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Viger, Roland J. 0000-0003-2520-714X rviger@usgs.gov","orcid":"https://orcid.org/0000-0003-2520-714X","contributorId":147818,"corporation":false,"usgs":true,"family":"Viger","given":"Roland","email":"rviger@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":false,"id":736280,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Van Beusekom, Ashley E. 0000-0002-6996-978X beusekom@usgs.gov","orcid":"https://orcid.org/0000-0002-6996-978X","contributorId":3992,"corporation":false,"usgs":true,"family":"Van Beusekom","given":"Ashley","email":"beusekom@usgs.gov","middleInitial":"E.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":736282,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hay, Lauren E. 0000-0003-3763-4595 lhay@usgs.gov","orcid":"https://orcid.org/0000-0003-3763-4595","contributorId":1287,"corporation":false,"usgs":true,"family":"Hay","given":"Lauren","email":"lhay@usgs.gov","middleInitial":"E.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":736283,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hogue, Terri S.","contributorId":205175,"corporation":false,"usgs":false,"family":"Hogue","given":"Terri","email":"","middleInitial":"S.","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":736284,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Foks, Nathan Leon","contributorId":194012,"corporation":false,"usgs":false,"family":"Foks","given":"Nathan","email":"","middleInitial":"Leon","affiliations":[],"preferred":false,"id":736285,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70200455,"text":"70200455 - 2018 - Alaska snowpack response to climate change: Statewide snowfall equivalent and snowpack water scenarios","interactions":[],"lastModifiedDate":"2018-10-18T13:45:55","indexId":"70200455","displayToPublicDate":"2018-05-22T13:45:44","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Alaska snowpack response to climate change: Statewide snowfall equivalent and snowpack water scenarios","docAbstract":"Climatically driven changes in snow characteristics (snowfall, snowpack, and snowmelt) will affect hydrologic and ecological systems in Alaska over the coming century, yet there exist no projections of downscaled future snow pack metrics for the state of Alaska. We updated historical and projected snow day fraction (PSF, the fraction of days with precipitation falling as snow) from McAfee et al. We developed modeled snowfall equivalent (SFE) derived from the product of snow-day fraction (PSF) and existing gridded precipitation for Alaska from Scenarios Network for Alaska and Arctic Planning (SNAP). We validated the assumption that modeled SFE approximates historical decadally averaged snow water equivalent (SWE) observations from snowcourse and Snow Telemetry (SNOTEL) sites. We present analyses of future downscaled PSF and two new products, October–March SFE and ratio of snow fall equivalent to precipitation (SFE:P) based on bias-corrected statistically downscaled projections of Coupled Model Intercomparison Project 5 (CMIP5) Global Climate Model (GCM) temperature and precipitation for the state of Alaska. We analyzed mid-century (2040–2069) and late-century (2070–2099) changes in PSF, SFE, and SFE:P relative to historical (1970–1999) mean temperature and present results for Alaska climate divisions and 12-digit Hydrologic Unit Code (HUC12) watersheds. Overall, estimated historical the SFE is reasonably well related to the observed SWE, with correlations over 0.75 in all decades, and correlations exceeding 0.9 in the 1960s and 1970s. In absolute terms, SFE is generally biased low compared to the observed SWE. PSF and SFE:P decrease universally across Alaska under both Representative Concentration Pathway (RCP) 4.5 and RCP 8.5 emissions scenarios, with the smallest changes for RCP 4.5 in 2040–2069 and the largest for RCP 8.5 in 2070–2099. The timing and magnitude of maximum decreases in PSF vary considerably with regional average temperature, with the largest changes in months at the beginning and end of the snow season. Mean SFE changes vary widely among climate divisions, ranging from decreases between −17 and −58% for late twenty-first century in southeast, southcentral, west coast and southwest Alaska to increases up to 21% on the North Slope. SFE increases most at highest elevations and latitudes and decreases most in coastal southern Alaska. SFE:P ratios indicate a broad switch from snow-dominated to transitional annual hydrology across most of southern Alaska by mid-century, and from transitional to rain-dominated watersheds in low elevation parts of southeast Alaska by the late twenty-first century.
","language":"English","publisher":"MDPI","doi":"10.3390/w10050668","usgsCitation":"Littell, J., McAfee, S., and Hayward, G.D., 2018, Alaska snowpack response to climate change: Statewide snowfall equivalent and snowpack water scenarios: Water, v. 10, no. 5, p. 1-16, https://doi.org/10.3390/w10050668.","productDescription":"Article 668; 16 p.","startPage":"1","endPage":"16","ipdsId":"IP-097141","costCenters":[{"id":107,"text":"Alaska Climate Science Center","active":true,"usgs":true}],"links":[{"id":468739,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w10050668","text":"Publisher Index Page"},{"id":358537,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"10","issue":"5","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-05-22","publicationStatus":"PW","scienceBaseUri":"5c10a9b9e4b034bf6a7e5403","contributors":{"authors":[{"text":"Littell, Jeremy S. 0000-0002-5302-8280","orcid":"https://orcid.org/0000-0002-5302-8280","contributorId":205907,"corporation":false,"usgs":true,"family":"Littell","given":"Jeremy","middleInitial":"S.","affiliations":[{"id":107,"text":"Alaska Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":748948,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McAfee, Stephanie A.","contributorId":167115,"corporation":false,"usgs":false,"family":"McAfee","given":"Stephanie A.","affiliations":[{"id":24618,"text":"Department of Geography, University of Nevada, Reno, Reno, NV","active":true,"usgs":false}],"preferred":false,"id":748949,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hayward, Gregory D.","contributorId":209846,"corporation":false,"usgs":false,"family":"Hayward","given":"Gregory","email":"","middleInitial":"D.","affiliations":[{"id":38010,"text":"US Forest Service, Alaska Region","active":true,"usgs":false}],"preferred":false,"id":748950,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70197202,"text":"70197202 - 2018 - Sampling the stream landscape: Improving the applicability of an ecoregion-level capture probability model for stream fishes","interactions":[],"lastModifiedDate":"2023-03-27T22:49:54.298718","indexId":"70197202","displayToPublicDate":"2018-05-22T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Sampling the stream landscape: Improving the applicability of an ecoregion-level capture probability model for stream fishes","docAbstract":"Temporal and spatial variability in streams result in heterogeneous gear capture probability (i.e., the proportion of available individuals identified) that confounds interpretation of data used to monitor fish abundance. We modeled tow-barge electrofishing capture probability at multiple spatial scales for nine Ozark Highland stream fishes. In addition to fish size, we identified seven reach-scale environmental characteristics associated with variable capture probability: stream discharge, water depth, conductivity, water clarity, emergent vegetation, wetted width–depth ratio, and proportion of riffle habitat. The magnitude of the relationship between capture probability and both discharge and depth varied among stream fishes. We also identified lithological characteristics among stream segments as a coarse-scale source of variable capture probability. The resulting capture probability model can be used to adjust catch data and derive reach-scale absolute abundance estimates across a wide range of sampling conditions with similar effort as used in more traditional fisheries surveys (i.e., catch per unit effort). Adjusting catch data based on variable capture probability improves the comparability of data sets, thus promoting both well-informed conservation and management decisions and advances in stream-fish ecology.
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2016-0422","usgsCitation":"Mollenhauer, R., Mouser, J.B., and Brewer, S.K., 2018, Sampling the stream landscape: Improving the applicability of an ecoregion-level capture probability model for stream fishes: Canadian Journal of Fisheries and Aquatic Sciences, v. 75, no. 10, p. 1614-1625, https://doi.org/10.1139/cjfas-2016-0422.","productDescription":"12 p.","startPage":"1614","endPage":"1625","ipdsId":"IP-079903","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":468741,"rank":2,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/1807/87924","text":"External Repository"},{"id":354387,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas, Missouri, Oklahoma","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -95.09031466610114,\n 36.913206107808435\n ],\n [\n -95.09031466610114,\n 36.02798264227451\n ],\n [\n -93.63459116212798,\n 36.02798264227451\n ],\n [\n -93.63459116212798,\n 36.913206107808435\n ],\n [\n -95.09031466610114,\n 36.913206107808435\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"75","issue":"10","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b155d7ae4b092d9651e1b4c","contributors":{"authors":[{"text":"Mollenhauer, Robert","contributorId":176540,"corporation":false,"usgs":false,"family":"Mollenhauer","given":"Robert","affiliations":[],"preferred":false,"id":735984,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mouser, Joshua B.","contributorId":205087,"corporation":false,"usgs":false,"family":"Mouser","given":"Joshua","email":"","middleInitial":"B.","affiliations":[{"id":37027,"text":"Oklahoma Cooperative Fish and Wildlife Research Unit, Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":735985,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brewer, Shannon K. 0000-0002-1537-3921 skbrewer@usgs.gov","orcid":"https://orcid.org/0000-0002-1537-3921","contributorId":2252,"corporation":false,"usgs":true,"family":"Brewer","given":"Shannon","email":"skbrewer@usgs.gov","middleInitial":"K.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":735983,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70196645,"text":"ofr20181065 - 2018 - Streamflow, water quality, and constituent loads and yields, Scituate Reservoir Drainage Area, Rhode Island, water year 2015","interactions":[],"lastModifiedDate":"2018-05-22T10:00:35","indexId":"ofr20181065","displayToPublicDate":"2018-05-21T16:15:00","publicationYear":"2018","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":"2018-1065","title":"Streamflow, water quality, and constituent loads and yields, Scituate Reservoir Drainage Area, Rhode Island, water year 2015","docAbstract":"Streamflow and concentrations of sodium and chloride estimated from records of specific conductance were used to calculate loads of sodium and chloride during water year (WY) 2015 (October 1, 2014, through September 30, 2015) for tributaries to the Scituate Reservoir, Rhode Island. Streamflow and water-quality data used in the study were collected by the U.S. Geological Survey and the Providence Water Supply Board. Streamflow was measured or estimated by the U.S. Geological Survey following standard methods at 23 streamgages; 14 of these streamgages are equipped with instrumentation capable of continuously monitoring water level, specific conductance, and water temperature. Water-quality samples were collected at 36 sampling stations by the Providence Water Supply Board and at 14 continuous-record streamgages by the U.S. Geological Survey during WY 2015 as part of a long-term sampling program; all stations are in the Scituate Reservoir drainage area. Water-quality data collected by the Providence Water Supply Board are summarized by using values of central tendency and are used, in combination with measured (or estimated) streamflows, to calculate loads and yields (loads per unit area) of selected water-quality constituents for WY 2015.
The largest tributary to the reservoir (the Ponaganset River, which was monitored by the U.S. Geological Survey) contributed a mean streamflow of 25 cubic feet per second to the reservoir during WY 2015. For the same time period, annual mean streamflows measured (or estimated) for the other monitoring stations in this study ranged from about 0.38 to about 14 cubic feet per second. Together, tributaries (equipped with instrumentation capable of continuously monitoring specific conductance) transported about 1,500,000 kilograms of sodium and 2,400,000 kilograms of chloride to the Scituate Reservoir during WY 2015; sodium and chloride yields for the tributaries ranged from 8,000 to 54,000 kilograms per square mile and from 12,000 to 91,000 kilograms per square mile, respectively.
At the stations where water-quality samples were collected by the Providence Water Supply Board, the medians of the median concentrations were the following: for chloride, 29.5 milligrams per liter; for nitrite, 0.002 milligrams per liter as nitrogen; for nitrate, 0.05 milligrams per liter as nitrogen; for orthophosphate, 0.08 milligrams per liter as phosphate; and for total coliform bacteria and Escherichia coli, 440 and 20 colony forming units per 100 milliliters, respectively. The medians of the median daily loads (and yields) of chloride, nitrite, nitrate, orthophosphate, and total coliform and Escherichia coli bacteria were 170 kilograms per day (79 kilograms per day per square mile), 14 grams per day (5.2 grams per day per square mile), 670 grams per day (190 grams per day per square mile), 640 grams per day (210 grams per day per square mile), 18,000 million colony forming units per day (7,600 million colony forming units per day per square mile), and 1,200 million colony forming units per day (810 million colony forming units per day per square mile), respectively.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181065","collaboration":"Prepared in cooperation with the Providence Water Supply Board","usgsCitation":"Smith, K.P., 2018, Streamflow, water quality, and constituent loads and yields, Scituate Reservoir drainage area, Rhode Island, water year 2015: U.S. Geological Survey Open-File Report 2018–1065, 28 p., https://doi.org/10.3133/ofr20181065.","productDescription":"Report: v, 28 p.; Data release","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-088040","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":354074,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7FJ2FR5","text":"USGS data release","description":"USGS data release","linkHelpText":"Water Quality data from the Providence Water Supply Board for tributary streams to the Scituate Reservoir, water year 2015"},{"id":354073,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1065/ofr20181065.pdf","text":"Report","size":"1.16 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1065"},{"id":354072,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1065/coverthb2.jpg"}],"country":"United States","state":"Rhode Island","otherGeospatial":"Scituate Reservoir","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -71.61334991455077,\n 41.72546174412562\n ],\n [\n -71.59687042236328,\n 41.73571038089891\n ],\n [\n -71.57112121582031,\n 41.75978824099475\n ],\n [\n -71.5481185913086,\n 41.784369074958185\n ],\n [\n -71.5536117553711,\n 41.82173436916421\n ],\n [\n -71.55635833740234,\n 41.83145600892532\n ],\n [\n -71.5536117553711,\n 41.842199261672384\n ],\n [\n -71.55979156494139,\n 41.85652079326776\n ],\n [\n -71.5707778930664,\n 41.862146232018134\n ],\n [\n -71.59000396728514,\n 41.862146232018134\n ],\n [\n -71.60923004150389,\n 41.877485822442324\n ],\n [\n -71.61128997802734,\n 41.907642945005215\n ],\n [\n -71.6421890258789,\n 41.918373400143004\n ],\n [\n -71.66622161865234,\n 41.91173095014917\n ],\n [\n -71.66416168212889,\n 41.886687809812926\n ],\n [\n -71.66622161865234,\n 41.857543637121026\n ],\n [\n -71.67377471923828,\n 41.854986496815044\n ],\n [\n -71.6861343383789,\n 41.8744181988335\n ],\n [\n -71.69265747070311,\n 41.87262868373214\n ],\n [\n -71.70398712158203,\n 41.86674849564142\n ],\n [\n -71.72321319580077,\n 41.88719899247718\n ],\n [\n -71.73282623291016,\n 41.89435512030307\n ],\n [\n -71.75617218017578,\n 41.895888471963744\n ],\n [\n -71.77196502685547,\n 41.88771017105127\n ],\n [\n -71.76578521728516,\n 41.87237303462768\n ],\n [\n -71.77265167236328,\n 41.854986496815044\n ],\n [\n -71.76647186279297,\n 41.83145600892532\n ],\n [\n -71.7685317993164,\n 41.82122266302155\n ],\n [\n -71.76990509033202,\n 41.81457011105642\n ],\n [\n -71.75754547119139,\n 41.79358445913614\n ],\n [\n -71.74655914306639,\n 41.78129698585321\n ],\n [\n -71.7348861694336,\n 41.77464028786307\n ],\n [\n -71.71634674072264,\n 41.771567732673454\n ],\n [\n -71.7033004760742,\n 41.76081263047197\n ],\n [\n -71.69300079345702,\n 41.75620274904767\n ],\n [\n -71.6861343383789,\n 41.74185877811425\n ],\n [\n -71.6744613647461,\n 41.741346434162764\n ],\n [\n -71.6476821899414,\n 41.73775991204249\n ],\n [\n -71.63875579833983,\n 41.727511602285894\n ],\n [\n -71.61334991455077,\n 41.72546174412562\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
In this report, precipitation data from 2002 to 2012 from the hourly gridded Next-Generation Radar (NEXRAD)-based Multisensor Precipitation Estimate (MPE) precipitation product are compared to precipitation data from two rain gage networks—an automated tipping bucket network of 25 rain gages operated by the U.S. Geological Survey (USGS) and 51 rain gages from the volunteer-operated Community Collaborative Rain, Hail, and Snow (CoCoRaHS) network—in and near DuPage County, Illinois, at a daily time step to test for long-term differences in space, time, and distribution. The NEXRAD–MPE data that are used are from the fifty 2.5-mile grid cells overlying the rain gages from the other networks. Because of the challenges of measuring of frozen precipitation, the analysis period is separated between days with or without the chance of freezing conditions. The NEXRAD–MPE and tipping-bucket rain gage precipitation data are adjusted to account for undercatch by multiplying by a previously determined factor of 1.14. Under nonfreezing conditions, the three precipitation datasets are broadly similar in cumulative depth and distribution of daily values when the data are combined spatially across the networks. However, the NEXRAD–MPE data indicate a significant trend relative to both rain gage networks as a function of distance from the NEXRAD radar just south of the study area. During freezing conditions, of the USGS network rain gages only the heated gages were considered, and these gages indicate substantial mean undercatch of 50 and 61 percent compared to the NEXRAD–MPE and the CoCoRaHS gages, respectively. The heated USGS rain gages also indicate substantially lower quantile values during freezing conditions, except during the most extreme (highest) events. Because NEXRAD precipitation products are continually evolving, the report concludes with a discussion of recent changes in those products and their potential for improved precipitation estimation. An appendix provides an analysis of spatially combined NEXRAD–MPE precipitation data as a function of temperature at an hourly time scale and indicates, among other results, that most precipitation in the study area occurs at moderate temperatures of 30 to 74 degrees Fahrenheit. However, when precipitation does occur, its intensity increases with temperature to about 86 degrees Fahrenheit.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181061","collaboration":"Prepared in cooperation with the DuPage County Stormwater Management Department","usgsCitation":"Spies, R.R., Over, T.M., and Ortel, T.W., 2018, Comparison of NEXRAD multisensor precipitation estimates to rain gage observations in and near DuPage County, Illinois, 2002–12: U.S. Geological Survey Open-File Report 2018–1061, 30 p., https://doi.org/10.3133/ofr20181061. ","productDescription":"v, 30 p.","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-057485","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":354281,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1061/coverthb.jpg","text":"Report"},{"id":354282,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1061/ofr20181061.pdf","text":"Report","size":"5.61 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1061"}],"country":"United States","state":"Illinois","county":"DuPage County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.33,\n 41.5833\n ],\n [\n -87.8333,\n 41.5833\n ],\n [\n -87.8333,\n 42.1667\n ],\n [\n -88.33,\n 42.1667\n ],\n [\n -88.33,\n 41.5833\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
405 North Goodwin Avenue
Urbana, IL 61801
Human impacts on rivers threaten the natural function of riverine ecosystems. This paper assesses how channel confinement affects the scour depth and spatial extent of bed disturbance and discusses the implications of these results for salmon-redd disturbance in gravel-bedded rivers. Two-dimensional hydrodynamic models of relatively confined and unconfined reaches of the Cedar River in Washington State, USA, were constructed with surveyed bathymetry and available airborne lidar data then calibrated and verified with field observations of water-surface elevation and streamflow velocity. Simulations showed greater water depths and velocities in the confined reach and greater areas of low-velocity inundation in the unconfined reach at high flows. Data on previously published scour depth of bed disturbance during high flows were compared to simulated bed shear stress to construct a probabilistic logistic-regression model of bed disturbance, which was applied to spatial patterns of simulated bed shear stress to quantify the extent of likely bed disturbance to the burial depth of sockeye and Chinook salmon redds. The disturbance depth was not observed to differ between confined and unconfined reaches; however, results indicated the spatial extent of disturbance to a given depth in the confined reach was roughly twice as large as in the unconfined reach.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/24705357.2018.1457986","usgsCitation":"Christiana R. Czuba, Czuba, J.A., Magirl, C.S., Gendaszek, A.S., and Konrad, C.P., 2018, Effect of river confinement on depth and spatial extent of bed disturbance affecting salmon redds: Journal of Ecohydraulics, v. 2, no. 2, p. 1-14, https://doi.org/10.1080/24705357.2018.1457986.","productDescription":"14 p.","startPage":"1","endPage":"14","ipdsId":"IP-066545","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true},{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":359514,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Cedar River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.29499816894531,\n 47.357431944587034\n ],\n [\n -121.62620544433592,\n 47.357431944587034\n ],\n [\n -121.62620544433592,\n 47.58717856130287\n ],\n [\n -122.29499816894531,\n 47.58717856130287\n ],\n [\n -122.29499816894531,\n 47.357431944587034\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"2","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-05-21","publicationStatus":"PW","scienceBaseUri":"5befe5bde4b045bfcadf7f44","contributors":{"authors":[{"text":"Christiana R. Czuba","contributorId":203544,"corporation":false,"usgs":false,"family":"Christiana R. Czuba","affiliations":[{"id":36650,"text":"not affiliated, formerly with WAWSC","active":true,"usgs":false}],"preferred":false,"id":731752,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Czuba, Jonathan A. 0000-0002-9485-2604","orcid":"https://orcid.org/0000-0002-9485-2604","contributorId":150072,"corporation":false,"usgs":true,"family":"Czuba","given":"Jonathan","email":"","middleInitial":"A.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":731749,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Magirl, Christopher S. 0000-0002-9922-6549 magirl@usgs.gov","orcid":"https://orcid.org/0000-0002-9922-6549","contributorId":1822,"corporation":false,"usgs":true,"family":"Magirl","given":"Christopher","email":"magirl@usgs.gov","middleInitial":"S.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true},{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":731748,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gendaszek, Andrew S. 0000-0002-2373-8986 agendasz@usgs.gov","orcid":"https://orcid.org/0000-0002-2373-8986","contributorId":3509,"corporation":false,"usgs":true,"family":"Gendaszek","given":"Andrew","email":"agendasz@usgs.gov","middleInitial":"S.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":731750,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Konrad, Christopher P. 0000-0002-7354-547X cpkonrad@usgs.gov","orcid":"https://orcid.org/0000-0002-7354-547X","contributorId":1716,"corporation":false,"usgs":true,"family":"Konrad","given":"Christopher","email":"cpkonrad@usgs.gov","middleInitial":"P.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":731751,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70196922,"text":"ofr20181082 - 2018 - Analysis of groundwater response to tidal fluctuations, Operable Unit 2, Area 8, Naval Base Kitsap, Keyport, Washington","interactions":[],"lastModifiedDate":"2018-10-30T17:48:39","indexId":"ofr20181082","displayToPublicDate":"2018-05-21T00:00:00","publicationYear":"2018","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":"2018-1082","title":"Analysis of groundwater response to tidal fluctuations, Operable Unit 2, Area 8, Naval Base Kitsap, Keyport, Washington","docAbstract":"Operable Unit 2, Area 8, at Naval Base Kitsap, Keyport is the site of a former chrome-plating facility that released metals (primarily chromium and cadmium), chlorinated volatile organic compounds, and petroleum compounds into the local environment. To ensure long-term protectiveness, as stipulated in the Fourth Five-Year Review for the site, Naval Facilities Engineering Command Northwest collaborated with the U.S. Environmental Protection Agency, the Washington State Department of Ecology, and the Suquamish Tribe, to collect data to monitor the contamination left in place and to ensure the site does not pose a risk to human health or the environment. To support these efforts, refined information was needed on the interaction of fresh groundwater with seawater in response to the up-to 13-ft tidal fluctuations at this nearshore site adjacent to Port Orchard Bay. The information was analyzed to meet the primary objective of this investigation, which was to determine the optimal time during the semi-diurnal and the neap-spring tidal cycles to sample groundwater for freshwater contaminants in Area 8 monitoring wells.
Groundwater levels and specific conductance in five monitoring wells, along with marine water-levels (tidal levels) in Port Orchard Bay, were monitored every 15 minutes during a 3-week duration to determine how nearshore groundwater responds to tidal forcing. Time series data were collected from October 24, 2017, to November 16, 2017, a period that included neap and spring tides. Vertical profiles of specific conductance were also measured once in the screened interval of each well prior to instrument deployment to determine if a freshwater/saltwater interface was present in the well during that particular time.
The vertical profiles of specific conductance were measured only one time during an ebbing tide at approximately the top, middle, and bottom of the saturated thickness within the screened interval of each well. The landward-most well, MW8-8, was completely freshwater, while one of the most seaward wells, MW8-9, was completely saline. A distinct saltwater interface was measured in the three other shallow wells (MW8-11, MW8-12, and MW8-14), with the topmost groundwater occurring fresh underlain by higher conductivity water.
Lag times between minimum spring-tide level and minimum groundwater levels in wells ranged from about 2 to 4.5 hours in the less-than 20-ft deep wells screened across the water table, and was about 7 hours for the single 48-ft deep well screened below the water table. Those lag times were surprisingly long considering the wells are all located within 200-ft of the shoreline and the local geology is largely coarse-grained glacial outwash deposits. Various manmade subsurface features, such as slurry walls and backfilled excavations, likely influence and confuse the connectivity between seawater and groundwater.
The specific-conductance time-series data showed clear evidence of substantial saltwater intrusion into the screened intervals of most shallow wells. Unexpectedly, the intrusion was associated with the neap part of the tidal cycle around November 13–16, when relatively low barometric pressure and high southerly winds led to the highest high and low tides measured during the monitoring period. The data consistently indicated that the groundwater had the lowest specific conductance (was least mixed with seawater) during the prior neap tides around October 30, the same period when the shallow groundwater levels were lowest. Although the specific conductance response is somewhat different between wells, the data do suggest that it is the heights of the actual high-high and low-low tides, regardless of whether or not they occur during the neap or spring part of the cycle, that allows seawater intrusion into the nearshore aquifer at Area 8.
With all the data taken into consideration, the optimal time for sampling the shallow monitoring wells at Area 8 would be centered on a 2–5-hour period following the predicted low-low tide during neap tide, with due consideration of local atmospheric pressure and wind conditions that have the potential to generate tides that can be substantially higher than those predicted from lunar-solar tidal forces. The optimal time for sampling the deeper monitoring wells at Area 8 would be during the 6–8-hour period following a predicted low-low tide, also during the neap tide part of the tidal cycle. The specific time window to sample each well following a low tide can be found in table 5. Those periods are when groundwater in the wells is most fresh and least diluted by seawater intrusion. In addition to timing, consideration should be given to collecting undisturbed samples from the top of the screened interval (or top of the water table if below the top of the interval) to best characterize contaminant concentrations in freshwater. A downhole conductivity probe could be used to identify the saltwater interface, above which would be the ideal depth for sampling.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181082","collaboration":"Prepared in cooperation with the Department of the Navy, Naval Facilities Engineering Command, Northwest","usgsCitation":"Opatz, C.C., and Dinicola, R.S., 2018, Analysis of groundwater response to tidal fluctuations, Operable Unit 2, Area 8, Naval Base Kitsap, Keyport, Washington: U.S. Geological Survey Open-File Report 2018-1082, 20 p., https://doi.org/10.3133/ofr20181082.","productDescription":"Report: iv, 20 p.","onlineOnly":"Y","ipdsId":"IP-095017","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":354378,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1082/coverthb.jpg"},{"id":354379,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1082/ofr20181082.pdf","text":"Report","size":"3.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1082"},{"id":358998,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7JW8D5S","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Groundwater and Tidal Time Series Data, Operable Unit 2, Area 8, Naval Base Kitsap, Keyport, Washington"}],"country":"United States","state":"Washington","city":"Keyport","otherGeospatial":"Naval Base Kitsap","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.64913558959962,\n 47.683072220525\n ],\n [\n -122.59180068969725,\n 47.683072220525\n ],\n [\n -122.59180068969725,\n 47.72627665811123\n ],\n [\n -122.64913558959962,\n 47.72627665811123\n ],\n [\n -122.64913558959962,\n 47.683072220525\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402
Natural resource managers who oversee the Nation’s resources require data to support informed decision-making at a variety of spatial and temporal scales that often cross typical jurisdictional boundaries such as states, agency regions, and watersheds. These data come from multiple agencies, programs, and sources, often with their own methods and standards for data collection and organization. Coordinating standards and methods is often prohibitively time-intensive and expensive. MonitoringResources.org offers a suite of tools and resources that support coordination of monitoring efforts, cost-effective planning, and sharing of knowledge among organizations. The website was developed by the Pacific Northwest Aquatic Monitoring Partnership—a collaboration of Federal, state, tribal, local, and private monitoring programs—and the U.S. Geological Survey (USGS), with funding from the Bonneville Power Administration and USGS. It is a key component of a coordinated monitoring and information network.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20183015","usgsCitation":"Bayer, J.M., Scully, R.A., and Weltzin, J.F., 2018, MonitoringResources.org—Supporting coordinated and cost-effective natural resource monitoring across organizations: U.S. Geological Survey Fact Sheet 2018–3015, 2 p., https://doi.org/10.3133/fs20183015.","productDescription":"2 p.","onlineOnly":"Y","ipdsId":"IP-091401","costCenters":[{"id":433,"text":"National Phenology Network","active":true,"usgs":true}],"links":[{"id":354360,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2018/3015/fs20183015.pdf","text":"Report","size":"2.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Fact Sheet 2018-3015"},{"id":354359,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2018/3015/coverthb.jpg"}],"contact":"The U.S. Geological Survey, in cooperation with the Southwest Florida Water Management District, initiated a study to quantify the inflows and outflows in the Floral City, Inverness, and Hernando pools of the Tsala Apopka Lake Basin in Citrus County, Florida. This study assesses hydrologic changes in pool stages, groundwater levels, spring flows, and streamflows caused by the diversion of streamflow from the Withlacoochee River to the Tsala Apopka Lake Basin through water-control structures. A surface-water/groundwater flow model was developed using hydraulic parameters for lakes, streams, the unsaturated zone, and the underlying surficial and Upper Floridan aquifers estimated using an inverse modeling calibration technique. After calibration, the model was used to assess the relation between inflows and outflows in the Tsala Apopka Lake Basin and changes in pool stages.
Simulation results using the calibrated surface-water/groundwater flow model showed that leakage rates from the pools to the Upper Floridan aquifer were largest at the deep lake cells and that these leakage rates to the Upper Floridan aquifer were the highest in the model area. Downward leakage to the Upper Floridan aquifer occurred beneath most of the extent of the Floral City, Inverness, and Hernando pools. These leakage rates depended on the lakebed leakance and the difference between lake stages and heads in the Upper Floridan aquifer. Leakage rates were higher for the Floral City pool than for the Inverness pool, and higher for the Inverness pool than for the Hernando pool. Lakebed leakance was higher for the Floral City pool than for the Hernando pool, and higher for the Hernando pool than for the Inverness pool.
Simulation results showed that the average recharge rate to the surficial aquifer was 10.3 inches per year for the 2004 to 2012 simulation period. Areas that recharge the surficial aquifer covered about 86 percent of the model area. Simulations identified areas along segments of the Withlacoochee River and within land-surface depressions that receive water from the surficial aquifer. Recharge rates were largest in physiographic regions having a deep water table. Simulated heads in the Upper Floridan aquifer indicated the general flow directions in the active flow model area were from the northeast toward the southwest and then westward toward the coast, and from the southeast toward the northwest and then westward toward the coast, consistent with flow directions inferred from the estimated potentiometric surface map for May 2010. The largest inflow in the water budget of the Upper Floridan aquifer was downward leakage from the overlying hydrogeologic unit. The largest outflow in the water budget of the Upper Floridan aquifer was spring flow.
The calibrated surface-water and groundwater flow model was used to simulate hydrologic scenarios that included changes in rainfall rates, projected increases in groundwater pumping rates for 2025 and 2035, no flow for the 2004–12 period through the eight water-control structures in the Tsala Apopka Lake Basin, and the removal of the Inglis Dam and the Inglis Bypass Spillway on Lake Rousseau. Scenario simulation results were compared to annual average calibrated water levels and flows from 2004 to 2012. Simulated declines in the Tsala Apopka Lake pool stages under the 10-percent lower rainfall scenario were about 0.8, 0.3, and 1.3 feet (ft) for the Floral City, Inverness, and Hernando pools, respectively. Simulated groundwater levels under the same scenario declined up to 5.4 ft in the surficial aquifer and up to 2.9 ft in the Upper Floridan aquifer. Under the projected increases in groundwater pumping rates for 2035 that represented an increase of 36 percent from average 2004 to 2012 pumping rates, the simulated declines in the Floral City, Inverness, and Hernando pool stages were, in downstream order, 0.02, 0.06, and 0.04 ft. The largest drawdown under the projected increases in groundwater pumping rates for 2035 was 2.1 ft in the surficial aquifer and about 1.8 ft in the Upper Floridan aquifer. A scenario of decreased rainfall by 10 percent caused greater declines in water levels and pool stages than projected increases in groundwater pumping rates. The simulation with no flow through the eight Tsala Apopka Lake water-control structures resulted in simulated declines in average pool stage of 1.8, 1.9, and 0.5 ft in the Floral City, Inverness, and Hernando pools, respectively. The simulated removal of the two water-control structures in Lake Rousseau caused flow to increase at Rainbow Springs by 28 cubic feet per second, an increase of 4.7 percent from the average calibrated flow for 2004 to 2012.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185055","collaboration":"Prepared in cooperation with the Southwest Florida Water Management District","usgsCitation":"Sepúlveda, N., Fulkerson, M., Basso, R., and Ryan, P.J., 2018, Effects of surface-water and groundwater inflows and outflows on the hydrology of the Tsala Apopka Lake Basin in Citrus County, Florida: U.S. Geological Survey Scientific Investigations Report 2018–5055, 137 p., https://doi.org/10.3133/sir20185055.","productDescription":"Report: vii, 137 p.; Data Release","numberOfPages":"150","onlineOnly":"Y","ipdsId":"IP-066230","costCenters":[{"id":5051,"text":"FLWSC-Orlando","active":true,"usgs":true}],"links":[{"id":354255,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7QF8RS2","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Data sets for simulation of effects of surface-water and groundwater inflows and outflows on the hydrology of the Tsala Apopka Lake Basin in Citrus County, Florida"},{"id":354253,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5055/coverthb2.jpg"},{"id":354254,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5055/sir20185055.pdf","text":"Report","size":"41.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5055"}],"country":"United States","state":"Florida","county":"Citrus County","otherGeospatial":"Tsala Apopka Lake Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.81494140625,\n 28.168875180063345\n ],\n [\n -81.650390625,\n 28.168875180063345\n ],\n [\n -81.650390625,\n 29.16895060109228\n ],\n [\n -82.81494140625,\n 29.16895060109228\n ],\n [\n -82.81494140625,\n 28.168875180063345\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
The arroyo southwestern toad is a specialized and federally endangered amphibian endemic to the coastal plains and mountains of central and southern California and northwestern Baja California. It is largely unknown how long these toads live in natural systems, how their population demographics vary across occupied drainages, and how hydrology affects age structure. We used skeletochronology to estimate the ages of adult arroyo toads in seven occupied drainages with varying surface water hydrology in southern California. We processed 179 adult toads with age estimates between 1 and 6 years. Comparisons between skeletochronological ages and known ages of PIT tagged toads showed that skeletochronology likely underestimated toad age by up to 2 years, indicating they may live to 7 or 8 years, but nonetheless major patterns were evident. Arroyo toads showed sexual size dimorphism with adult females reaching a maximum size of 12 mm greater than males. Population age structure varied among the sites. Age structure at sites with seasonally predictable surface water was biased toward younger individuals, which indicated stable recruitment for these populations. Age structures at the ephemeral sites were biased toward older individuals with cohorts roughly corresponding to higher rainfall years. These populations are driven by surface water availability, a stochastic process, and thus more unstable. Based on our estimates of toad ages, climate predictions of extreme and prolonged drought events could mean that the number of consecutive dry years could surpass the maximum life span of toads making them vulnerable to extirpation, especially in ephemeral freshwater systems. Understanding the relationship between population demographics and hydrology is essential for predicting species resilience to projected changes in weather and rainfall patterns. The arroyo toad serves as a model for understanding potential responses to climatic and hydrologic changes in Mediterranean stream systems. We recommend development of adaptive management strategies to address these threats.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.4158","usgsCitation":"Fisher, R.N., Brehme, C.S., Hathaway, S.A., Hovey, T.E., Warburton, M.L., and Stokes, D.C., 2018, Longevity and population age structure of the arroyo southwestern toad (Anaxyrus californicus) with drought implications: Ecology and Evolution, v. 8, no. 12, p. 6124-6132, https://doi.org/10.1002/ece3.4158.","productDescription":"9 p.","startPage":"6124","endPage":"6132","ipdsId":"IP-095515","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":468742,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.4158","text":"Publisher Index Page"},{"id":356281,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.01239013671874,\n 32.579220642875676\n ],\n [\n -116.68853759765626,\n 32.579220642875676\n ],\n [\n -116.68853759765626,\n 34.04583232505719\n ],\n [\n -118.01239013671874,\n 34.04583232505719\n ],\n [\n -118.01239013671874,\n 32.579220642875676\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","issue":"12","noUsgsAuthors":false,"publicationDate":"2018-05-20","publicationStatus":"PW","scienceBaseUri":"5b6fc450e4b0f5d57878ea4d","contributors":{"authors":[{"text":"Fisher, Robert N. 0000-0002-2956-3240 rfisher@usgs.gov","orcid":"https://orcid.org/0000-0002-2956-3240","contributorId":1529,"corporation":false,"usgs":true,"family":"Fisher","given":"Robert","email":"rfisher@usgs.gov","middleInitial":"N.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":741871,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brehme, Cheryl S. 0000-0001-8904-3354 cbrehme@usgs.gov","orcid":"https://orcid.org/0000-0001-8904-3354","contributorId":3419,"corporation":false,"usgs":true,"family":"Brehme","given":"Cheryl","email":"cbrehme@usgs.gov","middleInitial":"S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":741872,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hathaway, Stacie A. 0000-0002-4167-8059 sahathaway@usgs.gov","orcid":"https://orcid.org/0000-0002-4167-8059","contributorId":3420,"corporation":false,"usgs":true,"family":"Hathaway","given":"Stacie","email":"sahathaway@usgs.gov","middleInitial":"A.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":741873,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hovey, Tim E.","contributorId":206822,"corporation":false,"usgs":false,"family":"Hovey","given":"Tim","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":741874,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Warburton, Manna L.","contributorId":174875,"corporation":false,"usgs":false,"family":"Warburton","given":"Manna","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":741875,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stokes, Drew C.","contributorId":33836,"corporation":false,"usgs":true,"family":"Stokes","given":"Drew","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":741876,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70196044,"text":"sim3400 - 2018 - Geologic map of the Leadville North 7.5’ quadrangle, Eagle and Lake Counties, Colorado","interactions":[],"lastModifiedDate":"2018-05-18T15:37:42","indexId":"sim3400","displayToPublicDate":"2018-05-18T16:30:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3400","title":"Geologic map of the Leadville North 7.5’ quadrangle, Eagle and Lake Counties, Colorado","docAbstract":"The Leadville North 7.5’ quadrangle lies at the northern end of the Upper Arkansas Valley, where the Continental Divide at Tennessee Pass creates a low drainage divide between the Colorado and Arkansas River watersheds. In the eastern half of the quadrangle, the Paleozoic sedimentary section dips generally 20–30 degrees east. At Tennessee Pass and Missouri Hill, the core of the Sawatch anticlinorium is mapped as displaying a tight hanging-wall syncline and foot-wall anticline within the basement-cored structure. High-angle, west-dipping, Neogene normal faults cut the eastern margin of the broad, Sawatch anticlinorium. Minor displacements along high-angle, east- and west-dipping Laramide reverse faults occurred in the core of the north-plunging anticlinorium along the western and eastern flanks of Missouri Hill. Within the western half of the quadrangle, Meso- and Paleoproterozoic metamorphic and igneous rocks are uplifted along the generally east-dipping, high-angle Sawatch fault system and are overlain by at least three generations of glacial deposits in the western part of the quadrangle. 10Be and 26Al cosmogenic nuclide ages of the youngest glacial deposits indicate a last glacial maximum age of about 21–22 kilo-annum and complete deglaciation by about 14 kilo-annum, supported by chronologic studies in adjacent drainages. No late Pleistocene tectonic activity is apparent within the quadrangle.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3400","usgsCitation":"Ruleman, C.A., Brandt, T.R., Caffee, M.W., and Goehring, B.M., 2018, Geologic map of the Leadville North 7.5’ quadrangle, Eagle and Lake Counties, Colorado: U.S. Geological Survey Scientific Investigations Map 3400, 1:24,000, https://doi.org/10.3133/sim3400.","productDescription":"Map: 50.00 x 39.94 inches; Data release; Read Me","onlineOnly":"Y","ipdsId":"IP-085050","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":353270,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3400/sim3400_hillshade.pdf","text":"Hillshaded Map","size":"65.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3400 Hillshaded Map"},{"id":353268,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3400/sim3400.pdf","text":"Map","size":"63.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3400 Map"},{"id":353269,"rank":4,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3400/sim3400_georeferenced.pdf","text":"Georeferenced Map","size":"181.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3400 Georeferenced Map"},{"id":353271,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7DR2TRG","text":"USGS data release","linkHelpText":"Data Release for Geologic Map of the Leadville North 7.5' Quadrangle, Eagle and Lake Counties, Colorado"},{"id":353612,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3400/coverthb1.jpg"},{"id":353272,"rank":6,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sim/3400/sim3400_readme.txt","text":"Read Me","size":"8.00 KB","linkFileType":{"id":2,"text":"txt"},"description":"SIM 3400 Read Me"},{"id":354341,"rank":7,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sim/3400/versionHist.txt","size":"4/00 kB","linkFileType":{"id":2,"text":"txt"},"description":"SIM 3400 Version History"}],"country":"United States","state":"Colorado","county":"Eagle County, Lake County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.375,\n 39.375\n ],\n [\n -106.25,\n 39.375\n ],\n [\n -106.25,\n 39.25\n ],\n [\n -106.375,\n 39.25\n ],\n [\n -106.375,\n 39.375\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Geosciences and Environmental Change Science Center
U.S. Geological Survey
Box 25046, Mail Stop 980
Denver, CO 80225
http://gec.cr.usgs.gov/
Specific conductance (SC), soil volumetric water content (VWC), and discharge were monitored on a subsurface agricultural drain for a 2-yr period (2007–2008) to differentiate preferential flow paths from matrix flow paths. A major observation from the 2-yr period was the fast SC decrease after relatively small rainfall events, often <5 mm. A total of 25 paired rainfall–SC events were classified, with an average preferential flow onset time (from the event start) after 1.7 h and maximum preferential flow after 2.4 h. A specific conductance end-member mixing analysis (SC-EMMA) was used to determine the volume of water that infiltrated through preferential flow pathways. The SC-EMMA was used for 20 of the 25 paired rainfall–SC events; of the 20 classified events, the maximum preferential flow ranged from 11 to 75% of the total subsurface drain flow, with a mean maximum preferential flow of 31%. Overall, SC-EMMA illustrated that a significant portion of the subsurface drain discharge can be attributed to preferential flow, mainly through macropores or other largely open preferential flow pathways. The other primary mechanism, antecedent moisture conditions shifts, could only be shown for four of the 25 classified events. Specific conductance as a tracer of preferential flow was shown to be an effective tool for distinguishing preferential flow to subsurface drains. Even during relatively dry periods, the SC had a substantial decrease shortly after a rainfall event contrary to the conventional idea that macropore flow starts only after all the smaller pores are saturated and surface ponding begins to occur.
","language":"English","publisher":"ACSESS","doi":"10.2136/vzj2017.11.0206","usgsCitation":"Smith, E.A., and Capel, P.D., 2018, Specific conductance as a tracer of preferential flow in a subsurface-drained field: Vadose Zone Journal, v. 17, no. 1, 13 p., https://doi.org/10.2136/vzj2017.11.0206.","productDescription":"13 p.","ipdsId":"IP-030091","costCenters":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"links":[{"id":468747,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2136/vzj2017.11.0206","text":"Publisher Index Page"},{"id":370106,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Iowa","county":"Hamilton County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-93.5002,42.557],[-93.4996,42.4702],[-93.4641,42.4698],[-93.4642,42.3821],[-93.4636,42.2948],[-93.4643,42.2081],[-93.5844,42.2081],[-93.7009,42.2079],[-93.8179,42.2081],[-93.9319,42.2087],[-93.9324,42.2955],[-93.9324,42.3827],[-93.9323,42.4709],[-93.9727,42.4716],[-93.972,42.5566],[-93.8563,42.557],[-93.7367,42.5568],[-93.6191,42.5565],[-93.5002,42.557]]]},\"properties\":{\"name\":\"Hamilton\",\"state\":\"IA\"}}]}","volume":"17","issue":"1","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2018-05-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Smith, Erik A. 0000-0001-8434-0798 easmith@usgs.gov","orcid":"https://orcid.org/0000-0001-8434-0798","contributorId":1405,"corporation":false,"usgs":true,"family":"Smith","given":"Erik","email":"easmith@usgs.gov","middleInitial":"A.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":709973,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Capel, Paul D. 0000-0003-1620-5185 capel@usgs.gov","orcid":"https://orcid.org/0000-0003-1620-5185","contributorId":1002,"corporation":false,"usgs":true,"family":"Capel","given":"Paul","email":"capel@usgs.gov","middleInitial":"D.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":709972,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70194694,"text":"sir20175154 - 2018 - Surface-water quality in the Lycoming Creek watershed, north-central Pennsylvania, August 1–3, 2011","interactions":[],"lastModifiedDate":"2018-05-17T16:50:52","indexId":"sir20175154","displayToPublicDate":"2018-05-17T10:30:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-5154","title":"Surface-water quality in the Lycoming Creek watershed, north-central Pennsylvania, August 1–3, 2011","docAbstract":"This report presents the methodology and results for a study of surface-water quality of the Lycoming Creek watershed in north-central Pennsylvania during August 1–3, 2011. The study was done in cooperation with the Williamsport Municipal Water Authority and the Pennsylvania Department of Environmental Protection. Samples of stream water were collected from 31 sites in an area of exploration and production of natural gas from the Marcellus Shale – 5 sites on the main stem of Lycoming Creek and 26 sites on tributary streams. The samples provide a snapshot of the base-flow water-quality conditions, which helps document the spatial variability in water-quality and could be useful for assessing future changes.
The 272-square mile Lycoming Creek watershed is located within Lycoming, Tioga, and Sullivan Counties in north-central Pennsylvania. Lycoming Creek flows 37.5 miles to its confluence with the West Branch Susquehanna River in the city of Williamsport. A well field that supplies water for Williamsport captures some water that has infiltrated the streambed of Lycoming Creek. Because the stream provides a source of water to the well field, this study focused on the stream-water quality as it relates to drinking-water standards as opposed to aquatic life.
Surface-water samples collected at 20 sites by the U.S. Geological Survey and 11 sites by the Pennsylvania Department of Environmental Protection were analyzed by each agency for a suite of constituents that included major ions, trace metals, nutrients, and radiochemicals. None of the analytical results failed to meet standards set by the U.S. Environmental Protection Agency as maximum contaminant levels for drinking water.
Results of the sampling show the substantial spatial variability in base-flow water quality within the Lycoming Creek watershed caused by the interrelated effects of physiography, geology and land use. Dissolved-solids concentrations ranged from less than the laboratory reporting level of 12 milligrams per liter (mg/L) in Wolf Run, a pristine forested watershed, to 202 mg/L in Bottle Run, a watershed with more development near Williamsport. Concentrations of the major ions ranged over at least one order of magnitude; chloride had the largest range from 0.3 to 45.4 mg/L, with nine samples exceeding the natural background level of about 5 mg/L, most likely because of the application of deicing salt to roads. Trace constituents were even more variable, with concentrations for aluminum, cobalt, and manganese ranging over almost four orders of magnitude. Samples from Red Run and Dutchman Run, watersheds that experienced past coal mining activity, had concentrations of 11 metals that were significantly greater than in samples collected from other streams. Samples from Bottle Run, the tributary of Lycoming Creek nearest to Williamsport, contained elevated levels of chloride and boron, constituents associated with urban development.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175154","collaboration":"Prepared in cooperation with the Williamsport Municipal Water Authority","usgsCitation":"Risser, D.W., and Conlon, M.D., 2018, Surface-water quality in the Lycoming Creek watershed, north-central Pennsylvania, August 1–3, 2011: U.S. Geological Survey Scientific Investigations Report 2017–5154, 77 p., https://doi.org/10.3133/sir20175154.","productDescription":"ix, 77 p.","numberOfPages":"91","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-043927","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":354219,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5154/sir20175154.pdf","text":"Report","size":"8.23 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5154"},{"id":354218,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5154/coverthb.jpg"}],"country":"United States","state":"Pennsylvania","otherGeospatial":"Lycoming Creek Watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.1667,\n 41.2\n ],\n [\n -76.6667,\n 41.2\n ],\n [\n -76.6667,\n 41.6667\n ],\n [\n -77.1667,\n 41.6667\n ],\n [\n -77.1667,\n 41.2\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Pennsylvania Water Science Center
U.S. Geological Survey
215 Limekiln Road
New Cumberland, PA. 17070
Identification and protection of water bodies used by anadromous species are critical in light of increasing threats to fish populations, yet often challenging given budgetary and logistical limitations. Noninvasive, rapid‐assessment, sampling techniques may reduce costs and effort while increasing species detection efficiencies. We used an intrinsic potential (IP) habitat model to identify high‐quality rearing habitats for Chinook Salmon Oncorhynchus tshawytscha and select sites to sample throughout the Chena River basin, Alaska, for juvenile occupancy using an environmental DNA (eDNA) approach. Water samples were collected from 75 tributary sites in 2014 and 2015. The presence of Chinook Salmon DNA in water samples was assessed using a species‐specific quantitative PCR (qPCR) assay. The IP model predicted over 900 stream kilometers in the basin to support high‐quality (IP ≥ 0.75) rearing habitat. Occupancy estimation based on eDNA samples indicated that 80% and 56% of previously unsampled sites classified as high or low IP (IP < 0.75), respectively, were occupied. The probability of detection (p) of Chinook Salmon DNA from three replicate water samples was high (p = 0.76) but varied with drainage area (km2). A power analysis indicated high power to detect proportional changes in occupancy based on parameter values estimated from eDNA occupancy models, although power curves were not symmetrical around zero, indicating greater power to detect positive than negative proportional changes in occupancy. Overall, the combination of IP habitat modeling and occupancy estimation provided a useful, rapid‐assessment method to predict and subsequently quantify the distribution of juvenile salmon in previously unsampled tributary habitats. Additionally, these methods are flexible and can be modified for application to other species and in other locations, which may contribute towards improved population monitoring and management.
","language":"English","publisher":"Wiley","doi":"10.1002/nafm.10014","usgsCitation":"Matter, A., Falke, J.A., Lopez, J.A., and Savereide, J.W., 2018, A rapid assessment method to estimate the distribution of juvenile Chinook Salmon in tributary habitats using eDNA and occupancy estimation: North American Journal of Fisheries Management, v. 38, no. 1, p. 223-236, https://doi.org/10.1002/nafm.10014.","productDescription":"14 p.","startPage":"223","endPage":"236","ipdsId":"IP-082148","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":354275,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Chena River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -152.34741210937497,\n 62.935234870604695\n ],\n [\n -143.2177734375,\n 62.935234870604695\n ],\n [\n -143.2177734375,\n 66.08491099733617\n ],\n [\n -152.34741210937497,\n 66.08491099733617\n ],\n [\n -152.34741210937497,\n 62.935234870604695\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"38","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-12-11","publicationStatus":"PW","scienceBaseUri":"5afee6b9e4b0da30c1bfbd66","contributors":{"authors":[{"text":"Matter, A.","contributorId":68879,"corporation":false,"usgs":true,"family":"Matter","given":"A.","email":"","affiliations":[],"preferred":false,"id":735707,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Falke, Jeffrey A. 0000-0002-6670-8250 jfalke@usgs.gov","orcid":"https://orcid.org/0000-0002-6670-8250","contributorId":5195,"corporation":false,"usgs":true,"family":"Falke","given":"Jeffrey","email":"jfalke@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":735390,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lopez, J. Andres","contributorId":14306,"corporation":false,"usgs":true,"family":"Lopez","given":"J.","email":"","middleInitial":"Andres","affiliations":[],"preferred":false,"id":735708,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Savereide, James W.","contributorId":204591,"corporation":false,"usgs":false,"family":"Savereide","given":"James","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":735709,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70197121,"text":"70197121 - 2018 - Three-dimensional geophysical mapping of shallow water saturated altered rocks at Mount Baker, Washington: Implications for slope stability","interactions":[],"lastModifiedDate":"2018-05-17T16:37:43","indexId":"70197121","displayToPublicDate":"2018-05-17T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Three-dimensional geophysical mapping of shallow water saturated altered rocks at Mount Baker, Washington: Implications for slope stability","docAbstract":"Water-saturated hydrothermal alteration reduces the strength of volcanic edifices, increasing the potential for catastrophic sector collapses that can lead to far traveled and destructive debris flows. Intense hydrothermal alteration significantly lowers the resistivity and magnetization of volcanic rock and therefore hydrothermally altered rocks can be identified with helicopter electromagnetic and magnetic measurements. Geophysical models constrained by rock properties and geologic mapping show that intensely altered rock is restricted to two small (500 m diameter), >150 m thick regions around Sherman Crater and Dorr Fumarole Field at Mount Baker, Washington. This distribution of alteration contrasts with much thicker and widespread alteration encompassing the summits of Mounts Adams and Rainier prior to the 5600 year old Osceola collapse, which is most likely due to extreme erosion and the limited duration of summit magmatism at Mount Baker. In addition, the models suggest that the upper ~300 m of rock contains water which could help to lubricate potential debris flows. Slope stability modeling incorporating the geophysically modeled distribution of alteration and water indicates that the most likely and largest (~0.1 km3) collapses are from the east side of Sherman Crater. Alteration at Dorr Fumarole Field raises the collapse hazard there, but not significantly because of its lower slope angles. Geochemistry and analogs from other volcanoes suggest a model for the edifice hydrothermal system.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2018.04.013","usgsCitation":"Finn, C., Deszcz-Pan, M., Ball, J.L., Bloss, B.J., and Minsley, B.J., 2018, Three-dimensional geophysical mapping of shallow water saturated altered rocks at Mount Baker, Washington: Implications for slope stability: Journal of Volcanology and Geothermal Research, v. 357, p. 261-275, https://doi.org/10.1016/j.jvolgeores.2018.04.013.","productDescription":"15 p.","startPage":"261","endPage":"275","ipdsId":"IP-092862","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":354291,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Mount Baker","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.8667,\n 48.8\n ],\n [\n -121.7667,\n 48.8\n ],\n [\n -121.7667,\n 48.75\n ],\n [\n -121.8667,\n 48.75\n ],\n [\n -121.8667,\n 48.8\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"357","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6b4e4b0da30c1bfbd4c","contributors":{"authors":[{"text":"Finn, Carol A. 0000-0002-6178-0405","orcid":"https://orcid.org/0000-0002-6178-0405","contributorId":205010,"corporation":false,"usgs":true,"family":"Finn","given":"Carol A.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":false,"id":735738,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Deszcz-Pan, Maria 0000-0002-6298-5314","orcid":"https://orcid.org/0000-0002-6298-5314","contributorId":201859,"corporation":false,"usgs":true,"family":"Deszcz-Pan","given":"Maria","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":false,"id":735739,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ball, Jessica L. 0000-0002-7837-8180 jlball@usgs.gov","orcid":"https://orcid.org/0000-0002-7837-8180","contributorId":205012,"corporation":false,"usgs":true,"family":"Ball","given":"Jessica","email":"jlball@usgs.gov","middleInitial":"L.","affiliations":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":735742,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bloss, Benjamin J. 0000-0002-1678-8571","orcid":"https://orcid.org/0000-0002-1678-8571","contributorId":205011,"corporation":false,"usgs":true,"family":"Bloss","given":"Benjamin","email":"","middleInitial":"J.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":false,"id":735741,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Minsley, Burke J. 0000-0003-1689-1306 bminsley@usgs.gov","orcid":"https://orcid.org/0000-0003-1689-1306","contributorId":697,"corporation":false,"usgs":true,"family":"Minsley","given":"Burke","email":"bminsley@usgs.gov","middleInitial":"J.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":735740,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70197007,"text":"70197007 - 2018 - Generalist feeding strategies in Arctic freshwater fish: A mechanism for dealing with extreme environments","interactions":[],"lastModifiedDate":"2018-06-12T14:04:32","indexId":"70197007","displayToPublicDate":"2018-05-17T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1471,"text":"Ecology of Freshwater Fish","active":true,"publicationSubtype":{"id":10}},"title":"Generalist feeding strategies in Arctic freshwater fish: A mechanism for dealing with extreme environments","docAbstract":"Generalist feeding strategies are favoured in stressful or variable environments where flexibility in ecological traits is beneficial. Species that feed across multiple habitat types and trophic levels may impart stability on food webs through the use of readily available, alternative energy pools. In lakes, generalist fish species may take advantage of spatially and temporally variable prey by consuming both benthic and pelagic prey to meet their energy demands. Using stomach content and stable isotope analyses, we examined the feeding habits of fish species in Alaska's Arctic Coastal Plain (ACP) lakes to determine the prevalence of generalist feeding strategies as a mechanism for persistence in extreme environments (e.g. low productivity, extreme cold and short growing season). Generalist and flexible feeding strategies were evident in five common fish species. Fish fed on benthic and pelagic (or nektonic) prey and across trophic levels. Three species were clearly omnivorous, feeding on fish and their shared invertebrate prey. Dietary differences based on stomach content analysis often exceeded 70%, and overlap in dietary niches based on shared isotopic space varied from zero to 40%. Metrics of community‐wide trophic structure varied with the number and identity of species involved and on the dietary overlap and niche size of individual fishes. Accumulation of energy from shared carbon sources by Arctic fishes creates redundancy in food webs, increasing likely resistance to perturbations or stochastic events. Therefore, the generalist and omnivorous feeding strategies employed by ACP fish may maintain energy flow and food web stability in extreme environments.
","language":"English","publisher":"Wiley","doi":"10.1111/eff.12391","usgsCitation":"Laske, S.M., Rosenberger, A.E., Wipfli, M.S., and Zimmerman, C.E., 2018, Generalist feeding strategies in Arctic freshwater fish: A mechanism for dealing with extreme environments: Ecology of Freshwater Fish, v. 27, no. 3, p. 767-784, https://doi.org/10.1111/eff.12391.","productDescription":"18 p.","startPage":"767","endPage":"784","ipdsId":"IP-088949","costCenters":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"links":[{"id":437892,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7TQ60CH","text":"USGS data release","linkHelpText":"Fish Species Composition and Diet Information in Lakes of the Arctic Coastal Plain, Alaska, 2011-2013"},{"id":354274,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"27","issue":"3","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-08","publicationStatus":"PW","scienceBaseUri":"5afee6b9e4b0da30c1bfbd6a","contributors":{"authors":[{"text":"Laske, Sarah M. 0000-0002-6096-0420 slaske@usgs.gov","orcid":"https://orcid.org/0000-0002-6096-0420","contributorId":204872,"corporation":false,"usgs":true,"family":"Laske","given":"Sarah","email":"slaske@usgs.gov","middleInitial":"M.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":735291,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rosenberger, Amanda E. 0000-0002-5520-8349 arosenberger@usgs.gov","orcid":"https://orcid.org/0000-0002-5520-8349","contributorId":5581,"corporation":false,"usgs":true,"family":"Rosenberger","given":"Amanda","email":"arosenberger@usgs.gov","middleInitial":"E.","affiliations":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":735292,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wipfli, Mark S. 0000-0002-4856-6068 mwipfli@usgs.gov","orcid":"https://orcid.org/0000-0002-4856-6068","contributorId":1425,"corporation":false,"usgs":true,"family":"Wipfli","given":"Mark","email":"mwipfli@usgs.gov","middleInitial":"S.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":735293,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zimmerman, Christian E. 0000-0002-3646-0688 czimmerman@usgs.gov","orcid":"https://orcid.org/0000-0002-3646-0688","contributorId":410,"corporation":false,"usgs":true,"family":"Zimmerman","given":"Christian","email":"czimmerman@usgs.gov","middleInitial":"E.","affiliations":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":735290,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70196934,"text":"70196934 - 2018 - Integrating real-time subsurface hydrologic monitoring with empirical rainfall thresholds to improve landslide early warning","interactions":[],"lastModifiedDate":"2018-09-10T11:32:27","indexId":"70196934","displayToPublicDate":"2018-05-17T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2604,"text":"Landslides","active":true,"publicationSubtype":{"id":10}},"title":"Integrating real-time subsurface hydrologic monitoring with empirical rainfall thresholds to improve landslide early warning","docAbstract":"Early warning for rainfall-induced shallow landsliding can help reduce fatalities and economic losses. Although these commonly occurring landslides are typically triggered by subsurface hydrological processes, most early warning criteria rely exclusively on empirical rainfall thresholds and other indirect proxies for subsurface wetness. We explore the utility of explicitly accounting for antecedent wetness by integrating real-time subsurface hydrologic measurements into landslide early warning criteria. Our efforts build on previous progress with rainfall thresholds, monitoring, and numerical modeling along the landslide-prone railway corridor between Everett and Seattle, Washington, USA. We propose a modification to a previously established recent versus antecedent (RA) cumulative rainfall thresholds by replacing the antecedent 15-day rainfall component with an average saturation observed over the same timeframe. We calculate this antecedent saturation with real-time telemetered measurements from five volumetric water content probes installed in the shallow subsurface within a steep vegetated hillslope. Our hybrid rainfall versus saturation (RS) threshold still relies on the same recent 3-day rainfall component as the existing RA thresholds, to facilitate ready integration with quantitative precipitation forecasts. During the 2015–2017 monitoring period, this RS hybrid approach has an increase of true positives and a decrease of false positives and false negatives relative to the previous RA rainfall-only thresholds. We also demonstrate that alternative hybrid threshold formats could be even more accurate, which suggests that further development and testing during future landslide seasons is needed. The positive results confirm that accounting for antecedent wetness conditions with direct subsurface hydrologic measurements can improve thresholds for alert systems and early warning of rainfall-induced shallow landsliding.
","language":"English","publisher":"Springer","doi":"10.1007/s10346-018-0995-z","usgsCitation":"Mirus, B.B., Becker, R.E., Baum, R.L., and Smith, J.B., 2018, Integrating real-time subsurface hydrologic monitoring with empirical rainfall thresholds to improve landslide early warning: Landslides, v. 15, no. 10, p. 1909-1919, https://doi.org/10.1007/s10346-018-0995-z.","productDescription":"11 p.","startPage":"1909","endPage":"1919","ipdsId":"IP-093501","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":354283,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"15","issue":"10","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-05-15","publicationStatus":"PW","scienceBaseUri":"5afee6bae4b0da30c1bfbd6e","contributors":{"authors":[{"text":"Mirus, Benjamin B. 0000-0001-5550-014X bbmirus@usgs.gov","orcid":"https://orcid.org/0000-0001-5550-014X","contributorId":4064,"corporation":false,"usgs":true,"family":"Mirus","given":"Benjamin","email":"bbmirus@usgs.gov","middleInitial":"B.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":5061,"text":"National Cooperative Geologic Mapping and Landslide Hazards","active":true,"usgs":true},{"id":5077,"text":"Northwest Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":735057,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Becker, Rachel E. 0000-0002-2546-1706","orcid":"https://orcid.org/0000-0002-2546-1706","contributorId":204809,"corporation":false,"usgs":false,"family":"Becker","given":"Rachel","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":735058,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Baum, Rex L. 0000-0001-5337-1970 baum@usgs.gov","orcid":"https://orcid.org/0000-0001-5337-1970","contributorId":1288,"corporation":false,"usgs":true,"family":"Baum","given":"Rex","email":"baum@usgs.gov","middleInitial":"L.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":735059,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, Joel B. 0000-0001-7219-7875 jbsmith@usgs.gov","orcid":"https://orcid.org/0000-0001-7219-7875","contributorId":4925,"corporation":false,"usgs":true,"family":"Smith","given":"Joel","email":"jbsmith@usgs.gov","middleInitial":"B.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":735060,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70197092,"text":"70197092 - 2018 - Spatial variability of sediment transport processes over intratidal and subtidal timescales within a fringing coral reef system","interactions":[],"lastModifiedDate":"2021-03-18T17:13:34.860263","indexId":"70197092","displayToPublicDate":"2018-05-17T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2318,"text":"Journal of Geophysical Research F: Earth Surface","active":true,"publicationSubtype":{"id":10}},"title":"Spatial variability of sediment transport processes over intratidal and subtidal timescales within a fringing coral reef system","docAbstract":"Sediment produced on fringing coral reefs that is transported along the bed or in suspension affects ecological reef communities as well as the morphological development of the reef, lagoon, and adjacent shoreline. This study quantified the physical process contribution and relative importance of sea‐swell waves, infragravity waves, and mean currents to the spatial and temporal variability of sediment in suspension. Estimates of bed shear stresses demonstrate that sea‐swell waves are the key driver of the suspended sediment concentration (SSC) variability spatially (reef flat, lagoon, and channels) but cannot fully describe the SSC variability alone. The comparatively small but statistically significant contribution to the bed shear stress by infragravity waves and currents, along with the spatial availability of sediment of a suitable size and volume, is also important. Although intratidal variability in SSC occurs in the different reef zones, the majority of the variability occurs over longer slowly varying (subtidal) timescales, which is related to the arrival of large swell waves at a reef location. The predominant flow pathway, which can transport suspended sediment, consists of cross‐reef flow across the reef flat that diverges in the lagoon and returns offshore through channels. This pathway is primarily due to subtidal variations in wave‐driven flows but can also be driven alongshore by wind stresses when the incident waves are small. Higher frequency (intratidal) current variability also occurs due to both tidal flows and variations in the water depth that influence wave transmission across the reef and wave‐driven currents.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2017JF004468","usgsCitation":"Pomeroy, A., Lowe, R.J., Ghisalberti, M., Winter, G., Storlazzi, C., and Cuttler, M.V., 2018, Spatial variability of sediment transport processes over intratidal and subtidal timescales within a fringing coral reef system: Journal of Geophysical Research F: Earth Surface, v. 123, no. 5, p. 1013-1034, https://doi.org/10.1002/2017JF004468.","productDescription":"22 p.","startPage":"1013","endPage":"1034","ipdsId":"IP-090065","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":460919,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/2017jf004468","text":"External Repository"},{"id":354266,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Australia","state":"Western Australia","otherGeospatial":"Ningaloo Reef, Tantabiddi","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 113.785400390625,\n -21.999081858361517\n ],\n [\n 114.02984619140625,\n -21.999081858361517\n ],\n [\n 114.02984619140625,\n -21.71995560384493\n ],\n [\n 113.785400390625,\n -21.71995560384493\n ],\n [\n 113.785400390625,\n -21.999081858361517\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"123","issue":"5","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-05-17","publicationStatus":"PW","scienceBaseUri":"5afee6b8e4b0da30c1bfbd5e","contributors":{"authors":[{"text":"Pomeroy, Andrew","contributorId":182033,"corporation":false,"usgs":false,"family":"Pomeroy","given":"Andrew","affiliations":[],"preferred":false,"id":735673,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lowe, Ryan J.","contributorId":152265,"corporation":false,"usgs":false,"family":"Lowe","given":"Ryan","email":"","middleInitial":"J.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":735674,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ghisalberti, Marco","contributorId":182034,"corporation":false,"usgs":false,"family":"Ghisalberti","given":"Marco","email":"","affiliations":[],"preferred":false,"id":735675,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Winter, Gundula","contributorId":204988,"corporation":false,"usgs":false,"family":"Winter","given":"Gundula","email":"","affiliations":[],"preferred":false,"id":735676,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Storlazzi, Curt D. 0000-0001-8057-4490 cstorlazzi@usgs.gov","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":2333,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt D.","email":"cstorlazzi@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":735677,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cuttler, Michael V. W.","contributorId":177844,"corporation":false,"usgs":false,"family":"Cuttler","given":"Michael","email":"","middleInitial":"V. W.","affiliations":[],"preferred":false,"id":735678,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70196959,"text":"70196959 - 2018 - A method to quantify and value floodplain sediment and nutrient retention ecosystem services","interactions":[],"lastModifiedDate":"2025-01-22T15:43:21.583619","indexId":"70196959","displayToPublicDate":"2018-05-17T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2258,"text":"Journal of Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"A method to quantify and value floodplain sediment and nutrient retention ecosystem services","docAbstract":"Floodplains provide critical ecosystem services to local and downstream communities by retaining floodwaters, sediments, and nutrients. The dynamic nature of floodplains is such that these areas can both accumulate sediment and nutrients through deposition, and export material downstream through erosion. Therefore, estimating floodplain sediment and nutrient retention should consider the net flux of both depositional and erosive processes. An ecosystem services framework was used to quantify and value the sediment and nutrient ecosystem service provided by floodplains in the Difficult Run watershed, a small (151 km2) suburban watershed located in the Piedmont of Virginia (USA). A sediment balance was developed for Difficult Run and two nested watersheds. The balance included upland sediment delivery to streams, stream bank flux, floodplain flux, and stream load. Upland sediment delivery was estimated using geospatial datasets and a modified Revised Universal Soil Loss Equation. Predictive models were developed to extrapolate field measurements of the flux of sediment, sediment-bound nitrogen (N), and sediment-bound phosphorus (P) from stream banks and floodplains to 3232 delineated stream segments in the study area. A replacement cost approach was used to estimate the economic value of the sediment and nutrient retention ecosystem service based on estimated net stream bank and floodplain flux of sediment-bound N for all streams in the study area. Results indicated the net fluvial fluxes of sediment, sediment-bound N, and sediment-bound P were −10,439 Mg yr−1 (net export), 57,300 kg-N yr−1(net trapping), and 98 kg-P yr−1(net trapping), respectively. For sediment, floodplain retention was offset by substantial losses from stream bank erosion, particularly in headwater catchments, resulting in a net export of sediment. Nutrient retention in the floodplain exceeded that lost through stream bank erosion resulting in net retention of nutrients (TN and TP). Using a conservative cost estimate of \\$12.69 (USD) per kilogram of nitrogen, derived from wastewater treatment costs, the estimated annual value for sediment and nutrient retention on Difficult Run floodplains was \\$727,226 ± 194,220 USD/yr. Values and differences in floodplain nitrogen retention among stream reaches can be used to target areas for floodplain conservation and stream restoration. The methods presented are scalable and transferable to other areas if appropriate datasets are available for validation.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jenvman.2018.05.013","usgsCitation":"Hopkins, K.G., Noe, G.E., Franco, F., Pindilli, E., Gordon, S.E., Metes, M.J., Claggett, P.R., Gellis, A.C., Hupp, C.R., and Hogan, D.M., 2018, A method to quantify and value floodplain sediment and nutrient retention ecosystem services: Journal of Environmental Management, v. 220, p. 65-76, https://doi.org/10.1016/j.jenvman.2018.05.013.","productDescription":"12 p.","startPage":"65","endPage":"76","ipdsId":"IP-092758","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":354277,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.4167,\n 38.85\n ],\n [\n -77.2167,\n 38.85\n ],\n [\n -77.2167,\n 39\n ],\n [\n -77.4167,\n 39\n ],\n [\n -77.4167,\n 38.85\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"220","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6b9e4b0da30c1bfbd6c","contributors":{"authors":[{"text":"Hopkins, Kristina G. 0000-0003-1699-9384 khopkins@usgs.gov","orcid":"https://orcid.org/0000-0003-1699-9384","contributorId":195604,"corporation":false,"usgs":true,"family":"Hopkins","given":"Kristina","email":"khopkins@usgs.gov","middleInitial":"G.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":735132,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Noe, Gregory E. 0000-0002-6661-2646 gnoe@usgs.gov","orcid":"https://orcid.org/0000-0002-6661-2646","contributorId":139100,"corporation":false,"usgs":true,"family":"Noe","given":"Gregory","email":"gnoe@usgs.gov","middleInitial":"E.","affiliations":[{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":735133,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Franco, Fabiano 0000-0002-4849-3057","orcid":"https://orcid.org/0000-0002-4849-3057","contributorId":204834,"corporation":false,"usgs":true,"family":"Franco","given":"Fabiano","email":"","affiliations":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"preferred":true,"id":735134,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pindilli, Emily 0000-0002-5101-1266 epindilli@usgs.gov","orcid":"https://orcid.org/0000-0002-5101-1266","contributorId":140262,"corporation":false,"usgs":true,"family":"Pindilli","given":"Emily","email":"epindilli@usgs.gov","affiliations":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"preferred":true,"id":735135,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gordon, Stephanie E. 0000-0002-6292-2612 sgordon@usgs.gov","orcid":"https://orcid.org/0000-0002-6292-2612","contributorId":200931,"corporation":false,"usgs":true,"family":"Gordon","given":"Stephanie","email":"sgordon@usgs.gov","middleInitial":"E.","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":735136,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Metes, Marina J. 0000-0002-6797-9837","orcid":"https://orcid.org/0000-0002-6797-9837","contributorId":204835,"corporation":false,"usgs":true,"family":"Metes","given":"Marina","middleInitial":"J.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":735137,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Claggett, Peter R. 0000-0002-5335-2857 pclaggett@usgs.gov","orcid":"https://orcid.org/0000-0002-5335-2857","contributorId":176287,"corporation":false,"usgs":true,"family":"Claggett","given":"Peter","email":"pclaggett@usgs.gov","middleInitial":"R.","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":735138,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Gellis, Allen C. 0000-0002-3449-2889 agellis@usgs.gov","orcid":"https://orcid.org/0000-0002-3449-2889","contributorId":197684,"corporation":false,"usgs":true,"family":"Gellis","given":"Allen","email":"agellis@usgs.gov","middleInitial":"C.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":735139,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hupp, Cliff R. 0000-0003-1853-9197 crhupp@usgs.gov","orcid":"https://orcid.org/0000-0003-1853-9197","contributorId":2344,"corporation":false,"usgs":true,"family":"Hupp","given":"Cliff","email":"crhupp@usgs.gov","middleInitial":"R.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":735140,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Hogan, Dianna M. 0000-0003-1492-4514 dhogan@usgs.gov","orcid":"https://orcid.org/0000-0003-1492-4514","contributorId":131137,"corporation":false,"usgs":true,"family":"Hogan","given":"Dianna","email":"dhogan@usgs.gov","middleInitial":"M.","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":5064,"text":"Southeast Regional Director's Office","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":735141,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70197110,"text":"70197110 - 2018 - Precision and relative effectiveness of a purse seine for sampling age-0 river herring in lakes","interactions":[],"lastModifiedDate":"2018-07-03T11:17:31","indexId":"70197110","displayToPublicDate":"2018-05-17T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Precision and relative effectiveness of a purse seine for sampling age-0 river herring in lakes","docAbstract":"Stock assessments for anadromous river herring, collectively Alewife Alosa pseudoharengus and Blueback Herring A. aestivalis, lack adequate demographic information, particularly with respect to early life stages. Although sampling adult river herring is increasingly common throughout their range, currently no standardized, field‐based, analytical methods exist for estimating juvenile abundance in freshwater lakes. The objective of this research was to evaluate the relative effectiveness and sampling precision of a purse seine for estimating densities of age‐0 river herring in freshwater lakes. We used a purse seine to sample age‐0 river herring in June–September 2015 and June–July 2016 in 16 coastal freshwater lakes in the northeastern USA. Sampling effort varied from two seine hauls to more than 50 seine hauls per lake. Catch rates were highest in June and July, and sampling precision was maximized in July. Sampling at night (versus day) in open water (versus littoral areas) was most effective for capturing newly hatched larvae and juveniles up to ca. 100 mm TL. Bootstrap simulation results indicated that sampling precision of CPUE estimates increased with sampling effort, and there was a clear threshold beyond which increased effort resulted in negligible increases in precision. The effort required to produce precise CPUE estimates, as determined by the CV, was dependent on lake size; river herring densities could be estimated with up to 10 purse‐seine hauls (one‐two nights) in a small lake (<50 ha) and 15–20 hauls (two‐three nights) in a large lake (>50 ha). Fish collection techniques using a purse seine as described in this paper are likely to be effective for estimating recruit abundance of river herring in freshwater lakes across their range.
","language":"English","publisher":"Wiley","doi":"10.1002/nafm.10065","usgsCitation":"Devine, M.T., Roy, A.H., Whiteley, A.R., Gahagan, B.I., Armstrong, M., and Jordaan, A., 2018, Precision and relative effectiveness of a purse seine for sampling age-0 river herring in lakes: North American Journal of Fisheries Management, v. 38, no. 3, p. 650-662, https://doi.org/10.1002/nafm.10065.","productDescription":"13 p.","startPage":"650","endPage":"662","ipdsId":"IP-093443","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":354252,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"38","issue":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-22","publicationStatus":"PW","scienceBaseUri":"5afee6b6e4b0da30c1bfbd54","contributors":{"authors":[{"text":"Devine, Matthew T.","contributorId":204986,"corporation":false,"usgs":false,"family":"Devine","given":"Matthew","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":735650,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":735621,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Whiteley, Andrew R.","contributorId":52072,"corporation":false,"usgs":false,"family":"Whiteley","given":"Andrew","email":"","middleInitial":"R.","affiliations":[{"id":6932,"text":"University of Massachusetts, Amherst","active":true,"usgs":false}],"preferred":false,"id":735651,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gahagan, Benjamin I.","contributorId":200168,"corporation":false,"usgs":false,"family":"Gahagan","given":"Benjamin","email":"","middleInitial":"I.","affiliations":[],"preferred":false,"id":735652,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Armstrong, Michael P.","contributorId":200170,"corporation":false,"usgs":false,"family":"Armstrong","given":"Michael P.","affiliations":[],"preferred":false,"id":735653,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jordaan, Adrian","contributorId":197449,"corporation":false,"usgs":false,"family":"Jordaan","given":"Adrian","affiliations":[],"preferred":false,"id":735654,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70197077,"text":"70197077 - 2018 - Imidacloprid sorption and transport in cropland, grass buffer and riparian buffer soils","interactions":[],"lastModifiedDate":"2018-05-17T09:48:09","indexId":"70197077","displayToPublicDate":"2018-05-16T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3674,"text":"Vadose Zone Journal","active":true,"publicationSubtype":{"id":10}},"title":"Imidacloprid sorption and transport in cropland, grass buffer and riparian buffer soils","docAbstract":"An understanding of neonicotinoid sorption and transport in soil is critical for determining and mitigating environmental risk associated with the most widely used class of insecticides. The objective of this study was to evaluate mobility and transport of the neonicotinoid imidacloprid (ICD) in soils collected from cropland, grass vegetative buffer strip (VBS), and riparian VBS soils. Soils were collected at six randomly chosen sites within grids that encompassed all three land uses. Single-point equilibrium batch sorption experiments were conducted using radio-labeled (14C) ICD to determine solid–solution partition coefficients (Kd). Column experiments were conducted using soils collected from the three vegetation treatments at one site by packing soil into glass columns. Water flow was characterized by applying Br− as a nonreactive tracer. A single pulse of 14C-ICD was then applied, and ICD leaching was monitored for up to 45 d. Bromide and ICD breakthrough curves for each column were simulated using CXTFIT and HYDRUS-1D models. Sorption results indicated that ICD sorbs more strongly to riparian VBS (Kd = 22.6 L kg−1) than crop (Kd = 11.3 L kg−1) soils. Soil organic C was the strongest predictor of ICD sorption (p < 0.0001). The column transport study found mean peak concentrations of ICD at 5.83, 10.84, and 23.8 pore volumes for crop, grass VBS, and riparian VBS soils, respectively. HYDRUS-1D results indicated that the two-site, one-rate linear reversible model best described results of the breakthrough curves, indicating the complexity of ICD sorption and demonstrating its mobility in soil. Greater sorption and longer retention by the grass and riparian VBS soils than the cropland soil suggests that VBS may be a viable means to mitigate ICD loss from agroecosystems, thereby preventing ICD transport into surface water, groundwater, or drinking water resources.
","language":"English","publisher":"Soil Science Society of America","doi":"10.2136/vzj2017.07.0139","usgsCitation":"Satkowski, L.E., Goyne, K.W., Anderson, S., Lerch, R.N., Allen, C.R., and Snow, D.D., 2018, Imidacloprid sorption and transport in cropland, grass buffer and riparian buffer soils: Vadose Zone Journal, v. 17, no. 1, p. 1-12, https://doi.org/10.2136/vzj2017.07.0139.","productDescription":"12 p.","startPage":"1","endPage":"12","ipdsId":"IP-087113","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":468760,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2136/vzj2017.07.0139","text":"Publisher Index Page"},{"id":354233,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"17","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-04-12","publicationStatus":"PW","scienceBaseUri":"5afee6bbe4b0da30c1bfbd80","contributors":{"authors":[{"text":"Satkowski, Laura E.","contributorId":204930,"corporation":false,"usgs":false,"family":"Satkowski","given":"Laura","email":"","middleInitial":"E.","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":735491,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Goyne, Keith W.","contributorId":204931,"corporation":false,"usgs":false,"family":"Goyne","given":"Keith","email":"","middleInitial":"W.","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":735492,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anderson, Stephen H.","contributorId":204932,"corporation":false,"usgs":false,"family":"Anderson","given":"Stephen H.","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":735493,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lerch, Robert N.","contributorId":204933,"corporation":false,"usgs":false,"family":"Lerch","given":"Robert","email":"","middleInitial":"N.","affiliations":[{"id":37009,"text":"USDA Agricultural Research Service","active":true,"usgs":false}],"preferred":false,"id":735494,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Allen, Craig R. 0000-0001-8655-8272 allencr@usgs.gov","orcid":"https://orcid.org/0000-0001-8655-8272","contributorId":1979,"corporation":false,"usgs":true,"family":"Allen","given":"Craig","email":"allencr@usgs.gov","middleInitial":"R.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":735490,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Snow, Daniel D.","contributorId":204934,"corporation":false,"usgs":false,"family":"Snow","given":"Daniel","email":"","middleInitial":"D.","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":735495,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70197089,"text":"70197089 - 2018 - Effects of turbidity, sediment, and polyacrylamide on native freshwater mussels","interactions":[],"lastModifiedDate":"2018-06-04T15:59:11","indexId":"70197089","displayToPublicDate":"2018-05-16T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Effects of turbidity, sediment, and polyacrylamide on native freshwater mussels","docAbstract":"Turbidity is a ubiquitous pollutant adversely affecting water quality and aquatic life in waterways globally. Anionic polyacrylamide (PAM) is widely used as an effective chemical flocculent to reduce suspended sediment (SS) and turbidity. However, no information exists on the toxicity of PAM‐flocculated sediments to imperiled, but ecologically important, freshwater mussels (Unionidae). Thus, we conducted acute (96 h) and chronic (24 day) laboratory tests with juvenile fatmucket (Lampsilis siliquoidea) and three exposure conditions (nonflocculated settled sediment, SS, and PAM‐flocculated settled sediment) over a range of turbidity levels (50, 250, 1,250, and 3,500 nephelometric turbidity units). Survival and sublethal endpoints of protein oxidation, adenosine triphosphate (ATP) production, and protein concentration were used as measures of toxicity. We found no effect of turbidity levels or exposure condition on mussel survival in acute or chronic tests. However, we found significant reductions in protein concentration, ATP production, and oxidized proteins in mussels acutely exposed to the SS condition, which required water movement to maintain sediment in suspension, indicating responses that are symptoms of physiological stress. Our results suggest anionic PAM applied to reduce SS may minimize adverse effects of short‐term turbidity exposure on juvenile freshwater mussels without eliciting additional lethal or sublethal toxicity.
","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.12639","usgsCitation":"Buczek, S.B., Cope, W., McLaughlin, R.A., and Kwak, T.J., 2018, Effects of turbidity, sediment, and polyacrylamide on native freshwater mussels: Journal of the American Water Resources Association, v. 54, no. 3, p. 631-643, https://doi.org/10.1111/1752-1688.12639.","productDescription":"13 p.","startPage":"631","endPage":"643","ipdsId":"IP-091273","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":354223,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"54","issue":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-10","publicationStatus":"PW","scienceBaseUri":"5afee6bae4b0da30c1bfbd70","contributors":{"authors":[{"text":"Buczek, Sean B.","contributorId":200188,"corporation":false,"usgs":false,"family":"Buczek","given":"Sean","email":"","middleInitial":"B.","affiliations":[{"id":33914,"text":"North Carolina State University, Raleigh","active":true,"usgs":false}],"preferred":false,"id":735535,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cope, W. Gregory","contributorId":70353,"corporation":false,"usgs":true,"family":"Cope","given":"W. Gregory","affiliations":[],"preferred":false,"id":735536,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McLaughlin, Richard A.","contributorId":200189,"corporation":false,"usgs":false,"family":"McLaughlin","given":"Richard","email":"","middleInitial":"A.","affiliations":[{"id":33914,"text":"North Carolina State University, Raleigh","active":true,"usgs":false}],"preferred":false,"id":735537,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kwak, Thomas J. 0000-0002-0616-137X tkwak@usgs.gov","orcid":"https://orcid.org/0000-0002-0616-137X","contributorId":834,"corporation":false,"usgs":true,"family":"Kwak","given":"Thomas","email":"tkwak@usgs.gov","middleInitial":"J.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":735530,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70190581,"text":"sir20175100 - 2018 - Preliminary synthesis and assessment of environmental flows in the middle Verde River watershed, Arizona","interactions":[],"lastModifiedDate":"2019-05-15T09:24:27","indexId":"sir20175100","displayToPublicDate":"2018-05-15T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-5100","title":"Preliminary synthesis and assessment of environmental flows in the middle Verde River watershed, Arizona","docAbstract":"A 3-year study was undertaken to evaluate the suitability of the available modeling tools for characterizing environmental flows in the middle Verde River watershed of central Arizona, describe riparian vegetation throughout the watershed, and estimate sediment mobilization in the river. Existing data on fish and macroinvertebrates were analyzed in relation to basin characteristics, flow regimes, and microhabitat, and a pilot study was conducted that sampled fish and macroinvertebrates and the microhabitats in which they were found. The sampling for the pilot study took place at five different locations in the middle Verde River watershed. This report presents the results of this 3-year study.
The Northern Arizona Groundwater Flow Model (NARGFM) was found to be capable of predicting long-term changes caused by alteration of regional recharge (such as may result from climate variability) and groundwater pumping in gaining, losing, and dry reaches of the major streams in the middle Verde River watershed. Over the period 1910 to 2006, the model simulated an increase in dry reaches, a small increase in reaches losing discharge to the groundwater aquifer, and a concurrent decrease in reaches gaining discharge from groundwater. Although evaluations of the suitability of using the NARGFM and Basin Characteristic Model to characterize various streamflow intervals showed that smallerscale basin monthly runoff could be estimated adequately at locations of interest, monthly stream-flow estimates were found unsatisfactory for determining environmental flows.
Orthoimagery and Moderate Resolution Imaging Spectroradiometer data were used to quantify stream and riparian vegetation properties related to biotic habitat. The relative abundance of riparian vegetation varied along the main channel of the Verde River. As would be expected, more upland plant species and fewer lowland species were found in the upper-middle section compared to the lower-middle section, and vice-versa. Vegetation changes within the upper-middle and lower-middle reaches are related to differences in climate and hydrology. In general, the riparian vegetation of the middle Verde River watershed is that of a healthy ecosystem’s mixed age, mixed patch structure, likely a result of the mostly unaltered disturbance regime.
The frequency of in-river hydrogeomorphic features (pool, riffle, run) varied along the middle Verde River channel. There was a greater abundance of riffle habitat in the upper-middle reach; the lower-middle reach included more pool habitat. The Oak Creek tributary was more homogenous in geomorphic stream habitat composition than West Clear Creek, where runs dominated the upper reaches and pools dominated many of the lower reaches.
On the basis of the period of record and discharges recorded at 15-minute intervals, five flows were found to reach the gravel-transport threshold. Sediment mobilization computed with flows averaged over daily time steps yielded just three flows that reached the gravel-transport threshold, and monthly averaged flows yielded none. In the middle Verde River watershed, 15-minute data should be used when possible to evaluate sediment transport in the river system.
Data from more than 300 fish surveys conducted from 1992 to 2011 were analyzed using two schemes, one that divided the river into five reaches based on basin characteristics, and a second that divided the river into five reaches based on degree of flow alteration (specifically, diversions). Fish community metrics and assemblage data were used to analyze patterns of species composition and abundance in the two approaches. Overall, native and non-native species were regularly interacting and probably competing for similar resources. Fish abundances were also analyzed in response to floods and other flow metrics. Although the data are limited, native fish abundances increased more rapidly than non-native fish abundances in response to large floods. The basin-characteristic reach analysis showed native fish in greater abundance in the upper-middle reaches of the Verde River watershed and generally decreasing with downstream distance. The median relative abundance of native fish decreased by 50 percent from reach 1 to reach 5. Using the reach scheme based on degree of flow alteration, nondiverted reaches were found to have a greater abundance of native fish than diverted reaches. In heavily diverted reaches, non-native species outnumbered native species.
Fish metrics and stream-flow metrics for the 30, 90, and 365-day periods before collection were computed and the results analyzed statistically. Only abundance of all fish species was associated with the 30-day flow metrics. The 90-day flow metrics were generally positively associated with fish metrics, whereas the 365-day flow metrics had more negative correlations. In particular, significant relations were found between fish metrics and the magnitude and frequency of high flows, including maximum monthly flow, median annual number of high-flow events, and median annual maximum streamflow. Native sucker (Catostomidae) populations tended to decrease in periods of extended base flow, and fish in the non-native sunfish family (Centrarchidae) decreased in periods of flashy, high magnitude flows.
A pilot study surveyed fish at five locations in the upper part of the middle Verde River watershed as a means to measure microhabitat availability and quantify native and non-native fish use of that available microhabitat. Results indicated that native and non-native species exhibit some clear differences in microhabitat use. Although at least some native and non-native fish were found in each velocity, depth, and substrate category, preferential microhabitat use was common. On a percentage basis, non-native species had a strong preference for slow-moving and deeper water with silt and sand substrate, with a secondary preference for faster moving and very shallow water and a coarse gravel substrate. Native species showed a general preference for somewhat faster, moderate depth water over coarse gravel and had no clear secondary preference.
Macroinvertebrate-variables index period, high-flow year, and collection location (upper-middle Verde River, lowermiddle Verde River, or Verde River tributaries) were found to be important explanatory variables in differentiating among community metrics. Overall richness (number of unique taxa), Shannon’s diversity index, and the percent of the most dominant taxa were all highly correlated, but their response to each macroinvertebrate variable was different. The percentage of mayfly (order Ephemeroptera) taxa was significantly higher in Oak Creek and the upper-middle and lower-middle Verde River reaches, locations which have higher flows and more urbanization than other reaches. When community metrics were related to hydrologic metrics, caddisfly (order Trichoptera) populations appeared to increase and mayfly populations to decrease in response to less flashy and more stable streamflows. Conversely, caddisfly populations appeared to decrease and mayfly populations to increase in response to greater flow variability.
Six locations along the Verde River were sampled for macroinvertebrates as part of a pilot study associated with this report—(1) below Granite Creek, (2) near Campbell Ranch, (3) at the U.S. Geological Survey Paulden gage, (4) at the Perkinsville Bridge, (5) at the USGS Clarkdale gage, and (6) near the Reitz Ranch property. A nonmetric multidimensional scaling ordination of macroinvertebrate assemblages showed that the Verde River below Granite Creek site was different from the five other sites and that the Perkinsville Bridge and near Reitz Ranch samples had similar community structure. The near Campbell Ranch and Paulden gage locations had similar microhabitat characteristics, with the exception of riparian cover, yet the assemblage structure was very different. The different community composition at Verde River below Granite Creek was likely due to it having the smallest substrate sizes, lowest velocities, shallowest depths, and most riparian cover of the six sites.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175100","collaboration":"Prepared in cooperation with The Nature Conservancy and Salt River Project","usgsCitation":"Paretti, N.V., Brasher, A.M.D., Pearlstein, S.L., Skow, D.M., Gungle, Bruce, and Garner, B.D., 2018, Preliminary synthesis and assessment of environmental flows in the middle Verde River watershed, Arizona: U.S. Geological Survey Scientific Investigations Report 2017–5100, 104 p., https://doi.org/10.3133/sir20175100.","productDescription":"Report: xii; 104 p.; 3 Tables","numberOfPages":"120","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-084364","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":354141,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5100/sir20175100_table14.csv","text":"Table 14","size":"5 KB","linkFileType":{"id":7,"text":"csv"},"description":"Scientific Investigation Report 2017-5100 Table 12"},{"id":354142,"rank":5,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5100/sir20175100_tables12_14.xlsx","text":"Table 12 and 14","size":"25 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"Scientific Investigation Report 2017-5100 Table 12 and 14 Excel file"},{"id":354139,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5100/sir20175100.pdf","text":"Report","size":"17 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Scientific Investigation Report 2017-5100"},{"id":354138,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5100/coverthb.jpg"},{"id":354140,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5100/sir20175100_table12.csv","text":"Table 12","size":"5 KB","linkFileType":{"id":7,"text":"csv"},"description":"Scientific Investigation Report 2017-5100 Table 12"}],"country":"United States","state":"Arizona","otherGeospatial":"Verde River Watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.5,\n 34.5\n ],\n [\n -112.5,\n 34.5\n ],\n [\n -112.5,\n 35.5\n ],\n [\n -111.5,\n 35.5\n ],\n [\n -111.5,\n 34.5\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Arizona Water Science Center
U.S. Geological Survey
520 N. Park Avenue
Tucson, AZ 85719
Reconstructions of paleo-seawater chemistry are largely inferred from biogenic records of epicontinental seas. Recent studies provide considerable evidence for large-scale spatial and temporal variability in the environmental dynamics of these semi-restricted seas that leads to the decoupling of epicontinental isotopic records from those of the open ocean. We present conodont apatite δ18OPO4 and 87Sr/86Sr records spanning 24 Myr of the late Mississippian through Pennsylvanian derived from the U–Pb calibrated cyclothemic succession of the Donets Basin, eastern Ukraine. On a 2 to 6 Myr-scale, systematic fluctuations in bioapatite δ18OPO4 and 87Sr/86Sr broadly follow major shifts in the Donets onlap–offlap history and inferred regional climate, but are distinct from contemporaneous more open-water δ18OPO4 and global seawater Sr isotope trends.
A −1 to −6‰ offset in Donets δ18OPO4 values from those of more open-water conodonts and greater temporal variability in δ18OPO4 and 87Sr/86Sr records are interpreted to primarily record climatically driven changes in local environmental processes in the Donets sea. Systematic isotopic shifts associated with Myr-scale sea-level fluctuations, however, indicate an extrabasinal driver. We propose a mechanistic link to glacioeustasy through a teleconnection between high-latitude ice changes and atmospheric pCO2 and regional monsoonal circulation in the Donets region. Inferred large-magnitude changes in Donets seawater salinity and temperature, not archived in the more open-water or global contemporaneous records, indicate a modification of the global climate signal in the epicontinental sea through amplification or dampening of the climate signal by local and regional environmental processes. This finding of global climate change filtered through local processes has implications for the use of conodont δ18OPO4 and 87Sr/86Sr values as proxies of paleo-seawater composition, mean temperature, and glacioeustasy.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.epsl.2018.03.051","usgsCitation":"Montanez, I.P., Osleger, D.J., Chen, J., Wortham, B.E., Stamm, R.G., Nemyrovska, T.I., Griffin, J.M., Poletaev, V.I., and Wardlaw, B.R., 2018, Carboniferous climate teleconnections archived in coupled bioapatite δ18OPO4 and 87Sr/86Sr records from the epicontinental Donets Basin, Ukraine: Earth and Planetary Science Letters, v. 492, p. 89-101, https://doi.org/10.1016/j.epsl.2018.03.051.","productDescription":"13 p.","startPage":"89","endPage":"101","ipdsId":"IP-090058","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":468762,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.epsl.2018.03.051","text":"Publisher Index Page"},{"id":354190,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Ukraine","otherGeospatial":"Donets Basin","volume":"492","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6bbe4b0da30c1bfbd82","contributors":{"authors":[{"text":"Montanez, Isabel P.","contributorId":204886,"corporation":false,"usgs":false,"family":"Montanez","given":"Isabel","email":"","middleInitial":"P.","affiliations":[{"id":37004,"text":"Department of Earth and Planetary Sciences, University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":735365,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Osleger, Dillon J.","contributorId":204887,"corporation":false,"usgs":false,"family":"Osleger","given":"Dillon","email":"","middleInitial":"J.","affiliations":[{"id":37004,"text":"Department of Earth and Planetary Sciences, University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":735366,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chen, J.-H.","contributorId":203812,"corporation":false,"usgs":false,"family":"Chen","given":"J.-H.","email":"","affiliations":[{"id":36211,"text":"GFDL/NOAA","active":true,"usgs":false}],"preferred":false,"id":735367,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wortham, Barbara E.","contributorId":204904,"corporation":false,"usgs":false,"family":"Wortham","given":"Barbara","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":735419,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stamm, Robert G. 0000-0001-9141-5364","orcid":"https://orcid.org/0000-0001-9141-5364","contributorId":204885,"corporation":false,"usgs":true,"family":"Stamm","given":"Robert","email":"","middleInitial":"G.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":false,"id":735364,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nemyrovska, Tamara I.","contributorId":204888,"corporation":false,"usgs":false,"family":"Nemyrovska","given":"Tamara","email":"","middleInitial":"I.","affiliations":[{"id":37005,"text":"Department of Paleontology and Stratigraphy, Institute of Geological Science, Ukrainian Academy of Sciences, Kiev, Ukraine","active":true,"usgs":false}],"preferred":false,"id":735368,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Griffin, Julie M.","contributorId":204889,"corporation":false,"usgs":false,"family":"Griffin","given":"Julie","email":"","middleInitial":"M.","affiliations":[{"id":37004,"text":"Department of Earth and Planetary Sciences, University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":735369,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Poletaev, Vladislav I.","contributorId":204890,"corporation":false,"usgs":false,"family":"Poletaev","given":"Vladislav","email":"","middleInitial":"I.","affiliations":[{"id":37005,"text":"Department of Paleontology and Stratigraphy, Institute of Geological Science, Ukrainian Academy of Sciences, Kiev, Ukraine","active":true,"usgs":false}],"preferred":false,"id":735370,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Wardlaw, Bruce R. bwardlaw@usgs.gov","contributorId":266,"corporation":false,"usgs":true,"family":"Wardlaw","given":"Bruce","email":"bwardlaw@usgs.gov","middleInitial":"R.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":735371,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ]}