{"pageNumber":"557","pageRowStart":"13900","pageSize":"25","recordCount":40783,"records":[{"id":70150459,"text":"70150459 - 2015 - Reducing nitrogen export from the corn belt to the Gulf of Mexico: agricultural strategies for remediating hypoxia","interactions":[],"lastModifiedDate":"2018-02-06T12:16:11","indexId":"70150459","displayToPublicDate":"2015-02-01T00:00:00","publicationYear":"2015","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":"Reducing nitrogen export from the corn belt to the Gulf of Mexico: agricultural strategies for remediating hypoxia","docAbstract":"SPAtially Referenced Regression on Watershed models developed for the Upper Midwest were used to help evaluate the nitrogen-load reductions likely to be achieved by a variety of agricultural conservation practices in the Upper Mississippi-Ohio River Basin (UMORB) and to compare these reductions to the 45% nitrogen-load reduction proposed to remediate hypoxia in the Gulf of Mexico (GoM). Our results indicate that nitrogen-management practices (improved fertilizer management and cover crops) fall short of achieving this goal, even if adopted on all cropland in the region. The goal of a 45% decrease in loads to the GoM can only be achieved through the coupling of nitrogen-management practices with innovative nitrogen-removal practices such as tile-drainage treatment wetlands, drainage–ditch enhancements, stream-channel restoration, and floodplain reconnection. Combining nitrogen-management practices with nitrogen-removal practices can dramatically reduce nutrient export from agricultural landscapes while minimizing impacts to agricultural production. With this approach, it may be possible to meet the 45% nutrient reduction goal while converting less than 1% of cropland in the UMORB to nitrogen-removal practices. Conservationists, policy makers, and agricultural producers seeking a workable strategy to reduce nitrogen export from the Corn Belt will need to consider a combination of nitrogen-management practices at the field scale and diverse nitrogen-removal practices at the landscape scale.
","language":"English","publisher":"Wiley","doi":"10.1111/jawr.12246","usgsCitation":"McLellan, E., Robertson, D.M., Schilling, K., Tomer, M., Kostel, J., Smith, D.G., and King, K., 2015, Reducing nitrogen export from the corn belt to the Gulf of Mexico: agricultural strategies for remediating hypoxia: Journal of the American Water Resources Association, v. 51, no. 1, p. 263-289, https://doi.org/10.1111/jawr.12246.","productDescription":"27 p.","startPage":"263","endPage":"289","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-050927","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":306623,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Ohio River Basin, Upper Mississippi River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": 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,{"id":70148005,"text":"70148005 - 2015 - The cost of reproduction: differential resource specialization in female and male California sea otters","interactions":[],"lastModifiedDate":"2017-11-17T16:43:00","indexId":"70148005","displayToPublicDate":"2015-02-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2932,"text":"Oecologia","active":true,"publicationSubtype":{"id":10}},"title":"The cost of reproduction: differential resource specialization in female and male California sea otters","docAbstract":"Intraspecific variation in behavior and diet can have important consequences for population and ecosystem dynamics. Here, we examine how differences in reproductive investment and spatial ecology influence individual diet specialization in male and female southern sea otters (Enhydra lutris nereis). We hypothesize that greater reproductive constraints and smaller home ranges of females lead to more pronounced intraspecific competition and increased specialization. We integrate stable carbon (δ13C) and nitrogen (δ15N) isotope analysis of sea otter vibrissae with long-term observational studies of five subpopulations in California. We define individual diet specialization as low ratios of within-individual variation (WIC) to total population niche width (TNW). We compare isotopic and observational based metrics of WIC/TNW for males and females to data on population densities, and movement patterns using both general linear and linear mixed-effects models. Consistent with our hypothesis, increasing population density is associated with increased individual diet specialization by females but not by males. Additionally, we find the amount of coastline in a sea otter’s home range positively related with individual dietary variability, with increased range span resulting in weaker specialization for both males and females. We attribute our results to sex-based differences in movement, with females needing to specialize in their small ranges to maximize energy gain, and posit that the paradigm of individual prey specialization in sea otters with increased intraspecific competition may be a pattern driven largely by females. Our work highlights a potentially broader role of sex in the mechanistic pressures promoting and maintaining diet specialization.
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,{"id":70178680,"text":"70178680 - 2015 - Ecosystem-atmosphere exchange of CO2 in a temperate herbaceous peatland in the Sanjiang Plain of northeast China","interactions":[],"lastModifiedDate":"2016-12-05T11:18:16","indexId":"70178680","displayToPublicDate":"2015-02-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1454,"text":"Ecological Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Ecosystem-atmosphere exchange of CO2 in a temperate herbaceous peatland in the Sanjiang Plain of northeast China","docAbstract":"Northern peatlands contain a considerable share of the terrestrial carbon pool, which will be affected by future climatic variability. Using the static chamber technique, we investigated ecosystem respiration and soil respiration over two growing seasons (2012 and 2013) in a Carex lasiocarpa-dominated peatland in the Sanjiang Plain in China. We synchronously monitored the environmental factors controlling CO2 fluxes. Ecosystem respiration during these two growing seasons ranged from 33.3 to 506.7 mg CO2–C m−2 h−1. Through step-wise regression, variations in soil temperature at 10 cm depth alone explained 73.7% of the observed variance in log10(ER). The mean Q10 values ranged from 2.1 to 2.9 depending on the choice of depth where soil temperature was measured. The Q10 value at the 10 cm depth (2.9) appears to be a good representation for herbaceous peatland in the Sanjiang Plain when applying field-estimation based Q10values to current terrestrial ecosystem models due to the most optimized regression coefficient (63.2%). Soil respiration amounted to 57% of ecosystem respiration and played a major role in peatland carbon balance in our study. Emphasis on ecosystem respiration from temperate peatlands in the Sanjiang Plain will improve our basic understanding of carbon exchange between peatland ecosystem and the atmosphere.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecoleng.2014.11.035","usgsCitation":"Zhu, X., Song, C., Swarzenski, C.M., Guo, Y., Zhang, X., and Wang, J., 2015, Ecosystem-atmosphere exchange of CO2 in a temperate herbaceous peatland in the Sanjiang Plain of northeast China: Ecological Engineering, v. 75, p. 16-23, https://doi.org/10.1016/j.ecoleng.2014.11.035.","productDescription":"8 p.","startPage":"16","endPage":"23","ipdsId":"IP-056585","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":331457,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"China","otherGeospatial":"Sanjiang Plain","volume":"75","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58468aebe4b04fc80e5236cb","contributors":{"authors":[{"text":"Zhu, Xiaoyan","contributorId":177140,"corporation":false,"usgs":false,"family":"Zhu","given":"Xiaoyan","affiliations":[],"preferred":false,"id":654790,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Song, Changchun","contributorId":177141,"corporation":false,"usgs":false,"family":"Song","given":"Changchun","email":"","affiliations":[],"preferred":false,"id":654791,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Swarzenski, Christopher M. 0000-0001-9843-1471 cswarzen@usgs.gov","orcid":"https://orcid.org/0000-0001-9843-1471","contributorId":656,"corporation":false,"usgs":true,"family":"Swarzenski","given":"Christopher","email":"cswarzen@usgs.gov","middleInitial":"M.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":654789,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Guo, Yuedong","contributorId":177142,"corporation":false,"usgs":false,"family":"Guo","given":"Yuedong","email":"","affiliations":[],"preferred":false,"id":654792,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zhang, Xinhow","contributorId":177143,"corporation":false,"usgs":false,"family":"Zhang","given":"Xinhow","email":"","affiliations":[],"preferred":false,"id":654793,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wang, Jiaoyue","contributorId":177144,"corporation":false,"usgs":false,"family":"Wang","given":"Jiaoyue","email":"","affiliations":[],"preferred":false,"id":654794,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70141629,"text":"70141629 - 2015 - Flow cytometric method for measuring chromatin fragmentation in fixed sperm from yellow perch (Perca flavescens)","interactions":[],"lastModifiedDate":"2018-08-09T12:54:58","indexId":"70141629","displayToPublicDate":"2015-02-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3594,"text":"Theriogenology","active":true,"publicationSubtype":{"id":10}},"title":"Flow cytometric method for measuring chromatin fragmentation in fixed sperm from yellow perch (Perca flavescens)","docAbstract":"Declining harvests of yellow perch, Perca flavescens, in urbanized watersheds of Chesapeake Bay have prompted investigations of their reproductive fitness. The purpose of this study was to establish a flow cytometric technique for DNA analysis of fixed samples sent from the field to provide reliable gamete quality measurements. Similar to the sperm chromatin structure assay, measures were made on the susceptibility of nuclear DNA to acid-induced denaturation, but used fixed rather than live or thawed cells. Nuclei were best exposed to the acid treatment for 1 minute at 37 °C followed by the addition of cold (4 °C) propidium iodide staining solution before flow cytometry. The rationale for protocol development is presented graphically through cytograms. Field results collected in 2008 and 2009 revealed DNA fragmentation up to 14.5%. In 2008, DNA fragmentation from the more urbanized watersheds was significantly greater than from reference sites (P = 0.026) and in 2009, higher percentages of haploid testicular cells were noted from the less urbanized watersheds (P = 0.032) indicating better reproductive condition at sites with less urbanization. For both years, total and progressive live sperm motilities by computer-assisted sperm motion analysis ranged from 19.1% to 76.5%, being significantly higher at the less urbanized sites (P < 0.05). This flow cytometric method takes advantage of the propensity of fragmented DNA to be denatured under standard conditions, or 1 minute at 37 °C with 10% buffered formalin–fixed cells. The study of fixed sperm makes possible the restrospective investigation of germplasm fragmentation, spermatogenic ploidy patterns, and chromatin compaction levels from samples translocated over distance and time. The protocol provides an approach that can be modified for other species across taxa.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.theriogenology.2014.11.028","usgsCitation":"Jenkins, J.A., Draugelis-Dale, R.O., Pinkney, A.E., Iwanowicz, L., and Blazer, V., 2015, Flow cytometric method for measuring chromatin fragmentation in fixed sperm from yellow perch (Perca flavescens): Theriogenology, v. 83, no. 5, p. 920-931, https://doi.org/10.1016/j.theriogenology.2014.11.028.","productDescription":"12 p.","startPage":"920","endPage":"931","numberOfPages":"12","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-048922","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":298064,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"83","issue":"5","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54e868bce4b02d776a67c5c6","contributors":{"authors":[{"text":"Jenkins, Jill A. 0000-0002-5087-0894 jenkinsj@usgs.gov","orcid":"https://orcid.org/0000-0002-5087-0894","contributorId":2710,"corporation":false,"usgs":true,"family":"Jenkins","given":"Jill","email":"jenkinsj@usgs.gov","middleInitial":"A.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":540913,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Draugelis-Dale, Rassa O. 0000-0001-8532-3287 daler@usgs.gov","orcid":"https://orcid.org/0000-0001-8532-3287","contributorId":20422,"corporation":false,"usgs":true,"family":"Draugelis-Dale","given":"Rassa","email":"daler@usgs.gov","middleInitial":"O.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":540914,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pinkney, Alfred E.","contributorId":14253,"corporation":false,"usgs":false,"family":"Pinkney","given":"Alfred","email":"","middleInitial":"E.","affiliations":[{"id":12750,"text":"U.S. Fish and Wildlife Service, Annapolis, MD","active":true,"usgs":false}],"preferred":false,"id":540915,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Iwanowicz, Luke R. liwanowicz@usgs.gov","contributorId":139215,"corporation":false,"usgs":true,"family":"Iwanowicz","given":"Luke R.","email":"liwanowicz@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":540916,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Blazer, Vicki 0000-0001-6647-9614 vblazer@usgs.gov","orcid":"https://orcid.org/0000-0001-6647-9614","contributorId":792,"corporation":false,"usgs":true,"family":"Blazer","given":"Vicki","email":"vblazer@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":540917,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70142152,"text":"70142152 - 2015 - Time scales of porphyry Cu deposit formation: insights from titanium diffusion in quartz","interactions":[],"lastModifiedDate":"2015-03-03T11:18:21","indexId":"70142152","displayToPublicDate":"2015-02-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1472,"text":"Economic Geology","active":true,"publicationSubtype":{"id":10}},"title":"Time scales of porphyry Cu deposit formation: insights from titanium diffusion in quartz","docAbstract":"Porphyry dikes and hydrothermal veins from the porphyry Cu-Mo deposit at Butte, Montana, contain multiple generations of quartz that are distinct in scanning electron microscope-cathodoluminescence (SEM-CL) images and in Ti concentrations. A comparison of microprobe trace element profiles and maps to SEM-CL images shows that the concentration of Ti in quartz correlates positively with CL brightness but Al, K, and Fe do not. After calibrating CL brightness in relation to Ti concentration, we use the brightness gradient between different quartz generations as a proxy for Ti gradients that we model to determine time scales of quartz formation and cooling. Model results indicate that time scales of porphyry magma residence are ~1,000s of years and time scales from porphyry quartz phenocryst rim formation to porphyry dike injection and cooling are ~10s of years. Time scales for the formation and cooling of various generations of hydrothermal vein quartz range from 10s to 10,000s of years. These time scales are considerably shorter than the ~0.6 m.y. overall time frame for each porphyry-style mineralization pulse determined from isotopic studies at Butte, Montana. Simple heat conduction models provide a temporal reference point to compare chemical diffusion time scales, and we find that they support short dike and vein formation time scales. We interpret these relatively short time scales to indicate that the Butte porphyry deposit formed by short-lived episodes of hydrofracturing, dike injection, and vein formation, each with discrete thermal pulses, which repeated over the ~3 m.y. generation of the deposit.
","language":"English","publisher":"Society of Economic Geologists","doi":"10.2113/econgeo.110.3.587","usgsCitation":"Mercer, C.N., Reed, M.H., and Mercer, C., 2015, Time scales of porphyry Cu deposit formation: insights from titanium diffusion in quartz: Economic Geology, v. 110, no. 3, p. 587-602, https://doi.org/10.2113/econgeo.110.3.587.","productDescription":"16 p.","startPage":"587","endPage":"602","numberOfPages":"16","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-053533","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":298244,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","city":"Butte","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.35992431640625,\n 46.00089681276469\n ],\n [\n -112.35992431640625,\n 46.041663258553875\n ],\n [\n -112.2996711730957,\n 46.041663258553875\n ],\n [\n -112.2996711730957,\n 46.00089681276469\n ],\n [\n -112.35992431640625,\n 46.00089681276469\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"110","issue":"3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-02-24","publicationStatus":"PW","scienceBaseUri":"54f6e949e4b02419550d30ab","contributors":{"authors":[{"text":"Mercer, Celestine N. 0000-0001-8359-4147 cmercer@usgs.gov","orcid":"https://orcid.org/0000-0001-8359-4147","contributorId":4006,"corporation":false,"usgs":true,"family":"Mercer","given":"Celestine","email":"cmercer@usgs.gov","middleInitial":"N.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":541622,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reed, Mark H.","contributorId":139519,"corporation":false,"usgs":false,"family":"Reed","given":"Mark","email":"","middleInitial":"H.","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":541623,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mercer, Cameron M.","contributorId":139520,"corporation":false,"usgs":false,"family":"Mercer","given":"Cameron M.","affiliations":[{"id":6607,"text":"Arizona State University","active":true,"usgs":false}],"preferred":false,"id":541624,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70142186,"text":"70142186 - 2015 - Temperature effects induced by climate change on the growth and consumption by salmonines in Lakes Michigan and Huron","interactions":[],"lastModifiedDate":"2015-03-03T10:47:34","indexId":"70142186","displayToPublicDate":"2015-02-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1528,"text":"Environmental Biology of Fishes","active":true,"publicationSubtype":{"id":10}},"title":"Temperature effects induced by climate change on the growth and consumption by salmonines in Lakes Michigan and Huron","docAbstract":"We used bioenergetics models to investigate temperature effects induced by climate change on the growth and consumption by Chinook salmon Oncorhynchus tshawytscha, lake trout Salvelinus namaycush, and steelhead O. mykiss in Lakes Michigan and Huron. We updated biological inputs to account for recent changes in the food webs and used temperature inputs in response to regional climate observed in the baseline period (1964–1993) and projected in the future period (2043–2070).Bioenergetics simulations were run across multiple age-classes and across all four seasons in different scenarios of prey availability. Due to the increased capacity of prey consumption, future growth and consumption by these salmonines were projected to increase substantially when prey availability was not limited. When prey consumption remained constant, future growth of these salmonines was projected to decrease in most cases but increase in some cases where the increase in metabolic cost can be compensated by the decrease in waste (egestion and excretion) loss. Consumption by these salmonines was projected to increase the most during spring and fall when prey energy densities are relatively high. Such seasonality benefits their future growth through increasing annual gross energy intake. Our results indicated that lake trout and steelhead would be better adapted to the warming climate than Chinook salmon. To maintain baseline growth into the future, an increase of 10 % in baseline prey consumption was required for Chinook salmon but considerably smaller increases, or no increases, in prey consumption were needed by lake trout and steelhead.
","language":"English","publisher":"Springer","doi":"10.1007/s10641-014-0352-6","usgsCitation":"Kao, Y., Madenjian, C.P., Bunnell, D., Lofgren, B.M., and Perroud, M., 2015, Temperature effects induced by climate change on the growth and consumption by salmonines in Lakes Michigan and Huron: Environmental Biology of Fishes, v. 98, no. 4, p. 1089-1104, https://doi.org/10.1007/s10641-014-0352-6.","productDescription":"16 p.","startPage":"1089","endPage":"1104","numberOfPages":"16","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-052575","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":298241,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Lake Huron, Lake Michigan","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.83642578125,\n 45.99696161820381\n ],\n [\n -85.6494140625,\n 46.17222297845542\n ],\n [\n -87.066650390625,\n 45.96642454131025\n ],\n [\n -88.13232421875,\n 44.59046718130883\n ],\n [\n -87.791748046875,\n 44.11914151643737\n ],\n [\n -88.04443359375,\n 43.20517581723733\n ],\n [\n -87.945556640625,\n 42.12267315117259\n ],\n [\n -87.462158203125,\n 41.48389104267175\n ],\n [\n -86.4404296875,\n 41.86956082699455\n ],\n [\n -85.946044921875,\n 42.79540065303723\n ],\n [\n -86.3525390625,\n 43.644025847699496\n ],\n [\n -85.98999023437499,\n 44.68427737181225\n ],\n [\n -85.18798828125,\n 44.78573392716592\n ],\n [\n -84.451904296875,\n 45.42158812329091\n ],\n [\n -83.56201171875,\n 45.166547157856016\n ],\n [\n -83.60595703125,\n 44.47299117260252\n ],\n [\n -84.17724609375,\n 43.79488907226601\n ],\n [\n -83.69384765625,\n 43.46089378008257\n ],\n [\n -82.9248046875,\n 43.95328204198018\n ],\n [\n -82.50732421875,\n 42.924251753870685\n ],\n [\n -81.661376953125,\n 43.27720532212024\n ],\n [\n -81.177978515625,\n 44.824708282300236\n ],\n [\n -81.968994140625,\n 45.71385093029221\n ],\n [\n -83.671875,\n 45.98932892799953\n ],\n [\n -84.627685546875,\n 46.09609080214316\n ],\n [\n -84.83642578125,\n 45.99696161820381\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"98","issue":"4","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2014-10-04","publicationStatus":"PW","scienceBaseUri":"54f6e948e4b02419550d30a9","contributors":{"authors":[{"text":"Kao, Yu-Chun","contributorId":35626,"corporation":false,"usgs":false,"family":"Kao","given":"Yu-Chun","affiliations":[{"id":6649,"text":"University of Michigan, School of Natural Resources and Environment","active":true,"usgs":false}],"preferred":false,"id":541703,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Madenjian, Charles P. 0000-0002-0326-164X cmadenjian@usgs.gov","orcid":"https://orcid.org/0000-0002-0326-164X","contributorId":2200,"corporation":false,"usgs":true,"family":"Madenjian","given":"Charles","email":"cmadenjian@usgs.gov","middleInitial":"P.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":541702,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bunnell, David B. 0000-0003-3521-7747 dbunnell@usgs.gov","orcid":"https://orcid.org/0000-0003-3521-7747","contributorId":3139,"corporation":false,"usgs":true,"family":"Bunnell","given":"David B.","email":"dbunnell@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":541704,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lofgren, Brent M.","contributorId":139534,"corporation":false,"usgs":false,"family":"Lofgren","given":"Brent","email":"","middleInitial":"M.","affiliations":[{"id":12789,"text":"NOAA Great Lakes Environmental Research Laboratory","active":true,"usgs":false}],"preferred":false,"id":541705,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Perroud, Marjorie","contributorId":139535,"corporation":false,"usgs":false,"family":"Perroud","given":"Marjorie","email":"","affiliations":[{"id":12790,"text":"Cooperative Institute for Limnology and Ecosystems Research, University of Michigan","active":true,"usgs":false}],"preferred":false,"id":541706,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70189346,"text":"70189346 - 2015 - Inter-annual and spatial variability of Hamon potential evapotranspiration model coefficients","interactions":[],"lastModifiedDate":"2017-07-11T16:16:33","indexId":"70189346","displayToPublicDate":"2015-02-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Inter-annual and spatial variability of Hamon potential evapotranspiration model coefficients","docAbstract":"Monthly calibrated values of the Hamon PET coefficient (C) are determined for 109,951 hydrologic response units (HRUs) across the conterminous United States (U.S.). The calibrated coefficient values are determined by matching calculated mean monthly Hamon PET to mean monthly free-water surface evaporation. For most locations and months the calibrated coefficients are larger than the standard value reported by Hamon. The largest changes in the coefficients were for the late winter/early spring and fall months, whereas the smallest changes were for the summer months. Comparisons of PET computed using the standard value of C and computed using calibrated values of C indicate that for most of the conterminous U.S. PET is underestimated using the standard Hamon PET coefficient, except for the southeastern U.S.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2014.12.006","usgsCitation":"McCabe, G., Hay, L.E., Bock, A., Markstrom, S., and Atkinson, R., 2015, Inter-annual and spatial variability of Hamon potential evapotranspiration model coefficients: Journal of Hydrology, v. 521, p. 389-394, https://doi.org/10.1016/j.jhydrol.2014.12.006.","productDescription":"6 p.","startPage":"389","endPage":"394","ipdsId":"IP-058189","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":343611,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"521","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5965b4b0e4b0d1f9f05b382f","contributors":{"authors":[{"text":"McCabe, Gregory J. 0000-0002-9258-2997 gmccabe@usgs.gov","orcid":"https://orcid.org/0000-0002-9258-2997","contributorId":1453,"corporation":false,"usgs":true,"family":"McCabe","given":"Gregory J.","email":"gmccabe@usgs.gov","affiliations":[{"id":218,"text":"Denver Federal Center","active":false,"usgs":true}],"preferred":false,"id":704307,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":704308,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bock, Andy 0000-0001-7222-6613 abock@usgs.gov","orcid":"https://orcid.org/0000-0001-7222-6613","contributorId":174776,"corporation":false,"usgs":true,"family":"Bock","given":"Andy","email":"abock@usgs.gov","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":false,"id":704309,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Markstrom, Steven L. 0000-0001-7630-9547 markstro@usgs.gov","orcid":"https://orcid.org/0000-0001-7630-9547","contributorId":1986,"corporation":false,"usgs":true,"family":"Markstrom","given":"Steven L.","email":"markstro@usgs.gov","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":false,"id":704310,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Atkinson, R. Dwight","contributorId":174777,"corporation":false,"usgs":false,"family":"Atkinson","given":"R. Dwight","affiliations":[{"id":27513,"text":"U.S. Environmental Protection Agency, Office of Water","active":true,"usgs":false}],"preferred":false,"id":704311,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70193029,"text":"70193029 - 2015 - Aeolian responses to climate variability during the past century on Mesquite Lake Playa, Mojave Desert","interactions":[],"lastModifiedDate":"2017-11-12T11:23:51","indexId":"70193029","displayToPublicDate":"2015-02-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1801,"text":"Geomorphology","active":true,"publicationSubtype":{"id":10}},"title":"Aeolian responses to climate variability during the past century on Mesquite Lake Playa, Mojave Desert","docAbstract":"The erosion and deposition of sediments by wind from 1901 to 2013 have created large changes in surface features of Mesquite Lake playa in the Mojave Desert. The decadal scale recurrence of sand-sheet development, migration, and merging with older dunes appears related to decadal climatic changes of drought and wetness as recorded in the precipitation history of the Mojave Desert, complemented by modeled soil-moisture index values. Historical aerial photographs, repeat land photographs, and satellite images document the presence and northward migration of a mid-20th century sand sheet that formed during a severe regional drought that coincided with a multi-decadal cool phase of the Pacific Decadal Oscillation (PDO). The sand sheet slowly eroded during the wetter conditions of the subsequent PDO warm phase (1977–1998) due to a lack of added sediment. Sand cohesion gradually increased in the sand sheet by seasonal additions of salt and clay and by re-precipitation of gypsum, which resulted in the wind-carving of yardangs in the receding sand sheet. Smaller yardangs were aerodynamically shaped from coppice dunes with salt-clay crusts, and larger yardangs were carved along the walls and floor of trough blowouts. Evidence of a 19th century cycle of sand-sheet formation and erosion is indicated by remnants of yardangs, photographed in 1901 and 1916, that were found buried in the mid-20th century sand sheet. Three years of erosion measurements on the playa, yardangs, and sand sheets document relatively rapid wind erosion. The playa has lowered 20 to 40 cm since the mid-20th century and a shallow deflation basin has developed since 1999. Annually, 5–10 cm of surface sediment was removed from yardang flanks by a combination of wind abrasion, deflation, and mass movement. The most effective erosional processes are wind stripping of thin crusts that form on the yardang surfaces after rain events and the slumping of sediment blocks from yardang flanks. These wind-eroded landforms persist several decades to a century before eroding away or being buried by younger sands. On Mesquite Lake playa the climatic history of alternating PDO phases of multi-decadal drought and wetness is recorded twice by the presence of yardangs formed nearly a century apart.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.geomorph.2014.10.024","usgsCitation":"Whitney, J.W., Breit, G.N., Buckingham, S., Reynolds, R.L., Bogle, R., Luo, L., Goldstein, H.L., and Vogel, J.M., 2015, Aeolian responses to climate variability during the past century on Mesquite Lake Playa, Mojave Desert: Geomorphology, v. 230, p. 13-25, https://doi.org/10.1016/j.geomorph.2014.10.024.","productDescription":"13 p.","startPage":"13","endPage":"25","ipdsId":"IP-028706","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":348620,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Mesquite Lake, Mojave Desert","volume":"230","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a096bb1e4b09af898c9414b","contributors":{"authors":[{"text":"Whitney, John W. 0000-0003-3824-3692 jwhitney@usgs.gov","orcid":"https://orcid.org/0000-0003-3824-3692","contributorId":804,"corporation":false,"usgs":true,"family":"Whitney","given":"John","email":"jwhitney@usgs.gov","middleInitial":"W.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":721690,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Breit, George N. 0000-0003-2188-6798 gbreit@usgs.gov","orcid":"https://orcid.org/0000-0003-2188-6798","contributorId":1480,"corporation":false,"usgs":true,"family":"Breit","given":"George","email":"gbreit@usgs.gov","middleInitial":"N.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":721691,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buckingham, S.E.","contributorId":9454,"corporation":false,"usgs":true,"family":"Buckingham","given":"S.E.","email":"","affiliations":[],"preferred":false,"id":721692,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Reynolds, Richard L. 0000-0002-4572-2942 rreynolds@usgs.gov","orcid":"https://orcid.org/0000-0002-4572-2942","contributorId":147880,"corporation":false,"usgs":true,"family":"Reynolds","given":"Richard","email":"rreynolds@usgs.gov","middleInitial":"L.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":271,"text":"Federal Center","active":false,"usgs":true}],"preferred":true,"id":721693,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bogle, Rian C. 0000-0002-0389-4367 rbogle@usgs.gov","orcid":"https://orcid.org/0000-0002-0389-4367","contributorId":179318,"corporation":false,"usgs":true,"family":"Bogle","given":"Rian C.","email":"rbogle@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":false,"id":721694,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Luo, Lifeng","contributorId":176993,"corporation":false,"usgs":false,"family":"Luo","given":"Lifeng","email":"","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":721695,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Goldstein, Harland L. 0000-0002-6092-8818 hgoldstein@usgs.gov","orcid":"https://orcid.org/0000-0002-6092-8818","contributorId":147881,"corporation":false,"usgs":true,"family":"Goldstein","given":"Harland","email":"hgoldstein@usgs.gov","middleInitial":"L.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":false,"id":721696,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Vogel, John M. 0000-0002-8226-1188 jvogel@usgs.gov","orcid":"https://orcid.org/0000-0002-8226-1188","contributorId":3167,"corporation":false,"usgs":true,"family":"Vogel","given":"John","email":"jvogel@usgs.gov","middleInitial":"M.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":721697,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70193748,"text":"70193748 - 2015 - Development of a new semi-analytical model for cross-borehole flow experiments in fractured media","interactions":[],"lastModifiedDate":"2018-08-09T12:48:52","indexId":"70193748","displayToPublicDate":"2015-02-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":664,"text":"Advances in Water Resources","active":true,"publicationSubtype":{"id":10}},"title":"Development of a new semi-analytical model for cross-borehole flow experiments in fractured media","docAbstract":"Analysis of borehole flow logs is a valuable technique for identifying the presence of fractures in the subsurface and estimating properties such as fracture connectivity, transmissivity and storativity. However, such estimation requires the development of analytical and/or numerical modeling tools that are well adapted to the complexity of the problem. In this paper, we present a new semi-analytical formulation for cross-borehole flow in fractured media that links transient vertical-flow velocities measured in one or a series of observation wells during hydraulic forcing to the transmissivity and storativity of the fractures intersected by these wells. In comparison with existing models, our approach presents major improvements in terms of computational expense and potential adaptation to a variety of fracture and experimental configurations. After derivation of the formulation, we demonstrate its application in the context of sensitivity analysis for a relatively simple two-fracture synthetic problem, as well as for field-data analysis to investigate fracture connectivity and estimate fracture hydraulic properties. These applications provide important insights regarding (i) the strong sensitivity of fracture property estimates to the overall connectivity of the system; and (ii) the non-uniqueness of the corresponding inverse problem for realistic fracture configurations.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.advwatres.2014.12.002","usgsCitation":"Roubinet, D., Irving, J., and Day-Lewis, F.D., 2015, Development of a new semi-analytical model for cross-borehole flow experiments in fractured media: Advances in Water Resources, v. 76, p. 97-108, https://doi.org/10.1016/j.advwatres.2014.12.002.","productDescription":"12 p.","startPage":"97","endPage":"108","ipdsId":"IP-061584","costCenters":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":472304,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://serval.unil.ch/notice/serval:BIB_547C366CAA45","text":"External Repository"},{"id":349128,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"76","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60febde4b06e28e9c25341","contributors":{"authors":[{"text":"Roubinet, Delphine","contributorId":199840,"corporation":false,"usgs":false,"family":"Roubinet","given":"Delphine","email":"","affiliations":[],"preferred":false,"id":720181,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Irving, James","contributorId":199841,"corporation":false,"usgs":false,"family":"Irving","given":"James","email":"","affiliations":[],"preferred":false,"id":720182,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Day-Lewis, Frederick D. 0000-0003-3526-886X daylewis@usgs.gov","orcid":"https://orcid.org/0000-0003-3526-886X","contributorId":1672,"corporation":false,"usgs":true,"family":"Day-Lewis","given":"Frederick","email":"daylewis@usgs.gov","middleInitial":"D.","affiliations":[{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":720180,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70193751,"text":"70193751 - 2015 - Anomalous solute transport in saturated porous media: Relating transport model parameters to electrical and nuclear magnetic resonance properties","interactions":[],"lastModifiedDate":"2018-09-04T15:50:44","indexId":"70193751","displayToPublicDate":"2015-02-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Anomalous solute transport in saturated porous media: Relating transport model parameters to electrical and nuclear magnetic resonance properties","docAbstract":"The advection-dispersion equation (ADE) fails to describe commonly observed non-Fickian solute transport in saturated porous media, necessitating the use of other models such as the dual-domain mass-transfer (DDMT) model. DDMT model parameters are commonly calibrated via curve fitting, providing little insight into the relation between effective parameters and physical properties of the medium. There is a clear need for material characterization techniques that can provide insight into the geometry and connectedness of pore spaces related to transport model parameters. Here, we consider proton nuclear magnetic resonance (NMR), direct-current (DC) resistivity, and complex conductivity (CC) measurements for this purpose, and assess these methods using glass beads as a control and two different samples of the zeolite clinoptilolite, a material that demonstrates non-Fickian transport due to intragranular porosity. We estimate DDMT parameters via calibration of a transport model to column-scale solute tracer tests, and compare NMR, DC resistivity, CC results, which reveal that grain size alone does not control transport properties and measured geophysical parameters; rather, volume and arrangement of the pore space play important roles. NMR cannot provide estimates of more-mobile and less-mobile pore volumes in the absence of tracer tests because these estimates depend critically on the selection of a material-dependent and flow-dependent cutoff time. Increased electrical connectedness from DC resistivity measurements are associated with greater mobile pore space determined from transport model calibration. CC was hypothesized to be related to length scales of mass transfer, but the CC response is unrelated to DDMT.
","language":"English","publisher":"AGU","doi":"10.1002/2014WR015284","usgsCitation":"Swanson, R., Binley, A., Keating, K., France, S., Osterman, G., Day-Lewis, F.D., and Singha, K., 2015, Anomalous solute transport in saturated porous media: Relating transport model parameters to electrical and nuclear magnetic resonance properties: Water Resources Research, v. 51, no. 2, p. 1264-1283, https://doi.org/10.1002/2014WR015284.","productDescription":"20 p.","startPage":"1264","endPage":"1283","ipdsId":"IP-057728","costCenters":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":472303,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2014wr015284","text":"Publisher Index Page"},{"id":349126,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"51","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2015-02-27","publicationStatus":"PW","scienceBaseUri":"5a60febde4b06e28e9c2533f","contributors":{"authors":[{"text":"Swanson, Ryan D","contributorId":199846,"corporation":false,"usgs":false,"family":"Swanson","given":"Ryan D","affiliations":[],"preferred":false,"id":720193,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Binley, Andrew 0000-0002-0938-9070","orcid":"https://orcid.org/0000-0002-0938-9070","contributorId":192556,"corporation":false,"usgs":false,"family":"Binley","given":"Andrew","email":"","affiliations":[],"preferred":false,"id":720194,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Keating, Kristina","contributorId":199847,"corporation":false,"usgs":false,"family":"Keating","given":"Kristina","email":"","affiliations":[],"preferred":false,"id":720195,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"France, Samantha","contributorId":199848,"corporation":false,"usgs":false,"family":"France","given":"Samantha","email":"","affiliations":[],"preferred":false,"id":720196,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Osterman, Gordon","contributorId":199849,"corporation":false,"usgs":false,"family":"Osterman","given":"Gordon","email":"","affiliations":[],"preferred":false,"id":720197,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Day-Lewis, Frederick D. 0000-0003-3526-886X daylewis@usgs.gov","orcid":"https://orcid.org/0000-0003-3526-886X","contributorId":1672,"corporation":false,"usgs":true,"family":"Day-Lewis","given":"Frederick","email":"daylewis@usgs.gov","middleInitial":"D.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true}],"preferred":true,"id":720192,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Singha, Kamini 0000-0002-0605-3774","orcid":"https://orcid.org/0000-0002-0605-3774","contributorId":191366,"corporation":false,"usgs":false,"family":"Singha","given":"Kamini","email":"","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":720198,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70187032,"text":"70187032 - 2015 - DigitalCrust – a 4D data system of material properties for transforming research on crustal fluid flow","interactions":[],"lastModifiedDate":"2018-08-10T16:52:31","indexId":"70187032","displayToPublicDate":"2015-02-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1765,"text":"Geofluids","active":true,"publicationSubtype":{"id":10}},"title":"DigitalCrust – a 4D data system of material properties for transforming research on crustal fluid flow","docAbstract":"Fluid circulation in the Earth's crust plays an essential role in surface, near surface, and deep crustal processes. Flow pathways are driven by hydraulic gradients but controlled by material permeability, which varies over many orders of magnitude and changes over time. Although millions of measurements of crustal properties have been made, including geophysical imaging and borehole tests, this vast amount of data and information has not been integrated into a comprehensive knowledge system. A community data infrastructure is needed to improve data access, enable large-scale synthetic analyses, and support representations of the subsurface in Earth system models. Here, we describe the motivation, vision, challenges, and an action plan for a community-governed, four-dimensional data system of the Earth's crustal structure, composition, and material properties from the surface down to the brittle–ductile transition. Such a system must not only be sufficiently flexible to support inquiries in many different domains of Earth science, but it must also be focused on characterizing the physical crustal properties of permeability and porosity, which have not yet been synthesized at a large scale. The DigitalCrust is envisioned as an interactive virtual exploration laboratory where models can be calibrated with empirical data and alternative hypotheses can be tested at a range of spatial scales. It must also support a community process for compiling and harmonizing models into regional syntheses of crustal properties. Sustained peer review from multiple disciplines will allow constant refinement in the ability of the system to inform science questions and societal challenges and to function as a dynamic library of our knowledge of Earth's crust.
","language":"English","publisher":"Wiley","doi":"10.1111/gfl.12114","usgsCitation":"Fan, Y., Richard, S., Bristol, R.S., Peters, S., Ingebritsen, S.E., Moosdorf, N., Packman, A.I., Gleeson, T., Zazlavsky, I., Peckham, S., Murdoch, L., Cardiff, M., Tarboton, D., Jones, N., Hooper, R., Arrigo, J., Gochis, D., and Olson, J., 2015, DigitalCrust – a 4D data system of material properties for transforming research on crustal fluid flow: Geofluids, v. 15, no. 1-2, p. 372-379, https://doi.org/10.1111/gfl.12114.","productDescription":"8 p.","startPage":"372","endPage":"379","ipdsId":"IP-053923","costCenters":[{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true},{"id":37226,"text":"Core Science Analytics, Synthesis, and Libraries","active":true,"usgs":true}],"links":[{"id":340008,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"15","issue":"1-2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2014-10-07","publicationStatus":"PW","scienceBaseUri":"58f877bae4b0b7ea54521c24","contributors":{"authors":[{"text":"Fan, Yin","contributorId":191145,"corporation":false,"usgs":false,"family":"Fan","given":"Yin","email":"","affiliations":[],"preferred":false,"id":691999,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Richard, Steve","contributorId":191146,"corporation":false,"usgs":false,"family":"Richard","given":"Steve","email":"","affiliations":[],"preferred":false,"id":692000,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bristol, R. Sky 0000-0003-1682-4031 sbristol@usgs.gov","orcid":"https://orcid.org/0000-0003-1682-4031","contributorId":191144,"corporation":false,"usgs":true,"family":"Bristol","given":"R.","email":"sbristol@usgs.gov","middleInitial":"Sky","affiliations":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":false,"id":691998,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Peters, Shanan","contributorId":191147,"corporation":false,"usgs":false,"family":"Peters","given":"Shanan","email":"","affiliations":[],"preferred":false,"id":692001,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ingebritsen, Steven E. 0000-0001-6917-9369 seingebr@usgs.gov","orcid":"https://orcid.org/0000-0001-6917-9369","contributorId":818,"corporation":false,"usgs":true,"family":"Ingebritsen","given":"Steven","email":"seingebr@usgs.gov","middleInitial":"E.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":692003,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Moosdorf, Nils","contributorId":191149,"corporation":false,"usgs":false,"family":"Moosdorf","given":"Nils","email":"","affiliations":[],"preferred":false,"id":692006,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Packman, Aaron I.","contributorId":124517,"corporation":false,"usgs":false,"family":"Packman","given":"Aaron","email":"","middleInitial":"I.","affiliations":[{"id":5041,"text":"Department of Civil and Environmental Engineering, Northwestern University, Evanston, Illinois, USA","active":true,"usgs":false}],"preferred":false,"id":692007,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Gleeson, Tom","contributorId":42694,"corporation":false,"usgs":false,"family":"Gleeson","given":"Tom","affiliations":[{"id":6646,"text":"McGill University","active":true,"usgs":false}],"preferred":false,"id":692008,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Zazlavsky, Ilya","contributorId":191148,"corporation":false,"usgs":false,"family":"Zazlavsky","given":"Ilya","email":"","affiliations":[],"preferred":false,"id":692002,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Peckham, Scott","contributorId":191150,"corporation":false,"usgs":false,"family":"Peckham","given":"Scott","affiliations":[],"preferred":false,"id":692009,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Murdoch, Larry","contributorId":191151,"corporation":false,"usgs":false,"family":"Murdoch","given":"Larry","email":"","affiliations":[],"preferred":false,"id":692010,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Cardiff, Michael","contributorId":191152,"corporation":false,"usgs":false,"family":"Cardiff","given":"Michael","email":"","affiliations":[],"preferred":false,"id":692011,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Tarboton, David","contributorId":152467,"corporation":false,"usgs":false,"family":"Tarboton","given":"David","email":"","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":692012,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Jones, Norm","contributorId":152459,"corporation":false,"usgs":false,"family":"Jones","given":"Norm","email":"","affiliations":[{"id":6681,"text":"Brigham Young University","active":true,"usgs":false}],"preferred":false,"id":692013,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Hooper, Richard","contributorId":191153,"corporation":false,"usgs":false,"family":"Hooper","given":"Richard","affiliations":[],"preferred":false,"id":692014,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Arrigo, Jennifer","contributorId":191154,"corporation":false,"usgs":false,"family":"Arrigo","given":"Jennifer","affiliations":[],"preferred":false,"id":692015,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Gochis, David","contributorId":152455,"corporation":false,"usgs":false,"family":"Gochis","given":"David","email":"","affiliations":[{"id":6648,"text":"National Center for Atmospheric Research","active":true,"usgs":false}],"preferred":false,"id":692016,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Olson, John","contributorId":191155,"corporation":false,"usgs":false,"family":"Olson","given":"John","affiliations":[],"preferred":false,"id":692017,"contributorType":{"id":1,"text":"Authors"},"rank":18}]}}
,{"id":70126403,"text":"sir20145173 - 2015 - Geochemical conditions and the occurrence of selected trace elements in groundwater basins used for public drinking-water supply, Desert and Basin and Range hydrogeologic provinces, 2006-11: California GAMA Priority Basin Project","interactions":[],"lastModifiedDate":"2015-01-30T16:23:46","indexId":"sir20145173","displayToPublicDate":"2015-01-30T17:15:00","publicationYear":"2015","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":"2014-5173","title":"Geochemical conditions and the occurrence of selected trace elements in groundwater basins used for public drinking-water supply, Desert and Basin and Range hydrogeologic provinces, 2006-11: California GAMA Priority Basin Project","docAbstract":"The geochemical conditions, occurrence of selected trace elements, and processes controlling the occurrence of selected trace elements in groundwater were investigated in groundwater basins of the Desert and Basin and Range (DBR) hydrogeologic provinces in southeastern California as part of the Priority Basin Project (PBP) of the Groundwater Ambient Monitoring and Assessment (GAMA) Program. The GAMA PBP is designed to provide an assessment of the quality of untreated (raw) groundwater in the aquifer systems that are used for public drinking-water supply. The GAMA PBP is being conducted by the California State Water Resources Control Board in collaboration with the U.S. Geological Survey and the Lawrence Livermore National Laboratory.
\nThe DBR hydrogeologic provinces consist of 141 defined groundwater basins separated by mountain ranges, faults, and other features. This report presents analyses of data collected from nine study areas within the DBR hydrogeologic provinces: Antelope Valley, Borrego Valley, the Central Desert area, Coachella Valley, Colorado River, Indian Wells Valley, Low-Use Basins of the Mojave and Sonoran Deserts, the Mojave, and Owens Valley. Collectively, these nine study areas are referred to as the DBR study unit. The study unit covers approximately 7,000 square miles and includes the 63 groundwater basins in the DBR hydrogeologic provinces in which groundwater is used for public drinking-water supply. The vast majority of the 223 wells sampled for this study were long-screened production wells used primarily for public supply.
\nUncorrected carbon-14 (14C) groundwater ages for samples collected in the DBR study unit ranged from less than (<) 100 to 33,700 years before present (BP). Sixty-six percent of sample ages were greater than (>) 100 years BP, and 40 percent were >3,800 years BP. Samples collected from wells located adjacent to mountain-front recharge areas or major surface-water features generally had younger groundwater ages than did samples collected from wells located away from mountain fronts or towards the distal ends of basin groundwater flow paths. Most groundwater sampled in the DBR study unit had alkaline pH: 89 percent of sample pH values ranged from 7.1 to 9.8, with 37 percent greater than or equal to (≥) 7.9. Groundwater age was significantly correlated (positively) with pH, likely because silicate weathering is a primary control on groundwater pH and is a slow process. The oxidation-reduction (redox) condition of the groundwater sampled in the DBR study unit was predominantly oxic (71 percent), except in the Colorado River study area where organic-rich fluvial aquifers provide the electron donors necessary to support iron-reducing (anoxic-Fe) redox processes. The cation type of 78 percent of the samples was either sodium- or mixed-type, and the anion type of 83 percent of the samples was either bicarbonate- or mixed-type. Sodium-type groundwaters generally were older and more alkaline than calcium-type groundwaters, consistent with the change in water chemistry expected from cation exchange between groundwater and aquifer sediments over long periods of time. Because of the correlation with young groundwater, calcium-type groundwater was predominantly from wells located adjacent to mountain-front recharge areas.
\nArsenic (As), boron (B), fluoride (F), molybdenum (Mo), strontium (Sr), uranium (U), and vanadium (V) were selected for assessment in this study because they occurred at concentrations greater than California Department of Public Health or U.S. Environmental Protection Agency regulatory or non-regulatory drinking-water-quality benchmarks in more than 2 percent of the 223 samples collected in the DBR study unit. As and F were detected most commonly (18 and 13 percent, respectively) at concentrations above associated water-quality benchmarks and Sr and V least frequently (both at 3 percent). Given that 14C groundwater ages are predominantly >100 years BP, land use in the study unit is primarily undeveloped, and chemicals derived from anthropogenic sources, such as volatile organic compounds, were infrequently detected, high concentrations of these trace elements in groundwater were most likely the result of natural factors and not anthropogenic factors.
\nAs, F, Mo, and V concentrations showed significant positive correlations to groundwater age and to pH. This relation is partly due to the sources of trace elements likely being the weathering of primary minerals, such as silicate minerals, which is a slow process that takes place over hundreds to thousands of years. This relation also reflects the positive correlation between groundwater age and pH. Geochemical modeling predicted that the dominant species of As, Mo, and V in solution were oxyanions (HAsO42–, MoO42–, and H2VO4–), which are likely to be mobile in alkaline groundwater because mineral surfaces composing aquifer matrices have a predominantly negative surface charge under alkaline conditions. F also exists predominantly as a negatively charged ion (F–). At pH values >7.5, saturation indices generated by the geochemical modeling program PHREEQC indicated that F solubility may be somewhat limited by the precipitation of the mineral fluorapatite [Ca5(PO4)3F]. Speciation modeling of As in anoxic-Fe groundwater (iron-reducing conditions) showed that samples were supersaturated with orpiment (As2S3), indicating that mineral precipitation may be responsible for low As concentrations observed in reducing groundwater.
\nIn contrast, U concentrations showed significant negative correlations to groundwater age and to pH. Higher U concentrations generally occurred in samples for which geochemical modeling indicated that the uncharged ternary complex Ca2UO2(CO3)3 was the dominant aqueous U species. This uncharged complex is not attracted to the charged surfaces of minerals and thus increases U solubility. Formation of Ca2UO2(CO3)3 was greater in younger groundwaters because calcium and uranium concentrations generally were lower in older groundwaters, likely due to cation-exchange processes and precipitation of the mineral calcite as groundwater pH increased. Co-precipitation of U with the calcite (CaCO3) may remove U from the aqueous phase. Saturation indices indicated that the anoxic-Fe groundwaters from the Colorado River study area were supersaturated with the mineral uraninite (UO2), suggesting that UO2 precipitation may be responsible for the low concentrations of U observed in these samples.
\nConcentrations of strontium, which exists primarily in a cationic form (Sr2+), were not significantly correlated with either groundwater age or pH. Strontium concentrations showed a strong positive correlation with total dissolved solids (TDS). Dissolved constituents, such as Sr, that interact with mineral surfaces through outer-sphere complexation become increasingly soluble with increasing TDS concentrations of groundwater. Boron concentrations also showed a significant positive correlation with TDS, indicating the B may interact to a large degree with mineral surfaces through outer-sphere complexation.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145173","collaboration":"Prepared in cooperation with the California State Water Resources Control Board","usgsCitation":"Wright, M., Fram, M.S., and Belitz, K., 2015, Geochemical conditions and the occurrence of selected trace elements in groundwater basins used for public drinking-water supply, Desert and Basin and Range hydrogeologic provinces, 2006-11: California GAMA Priority Basin Project: U.S. Geological Survey Scientific Investigations Report 2014-5173, viii, 48 p., https://doi.org/10.3133/sir20145173.","productDescription":"viii, 48 p.","numberOfPages":"60","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2006-01-01","temporalEnd":"2011-12-31","ipdsId":"IP-037705","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":297661,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145173.jpg"},{"id":297659,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5173/"},{"id":297660,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5173/pdf/sir2014-5173.pdf","size":"6.7 MB","linkFileType":{"id":1,"text":"pdf"}}],"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 -120.39916992187499,\n 34.43409789359469\n ],\n [\n -117.103271484375,\n 32.52828936482526\n ],\n [\n -114.444580078125,\n 32.704111144407406\n ],\n [\n -114.114990234375,\n 34.32529192442733\n ],\n [\n -114.67529296874999,\n 35.06597313798418\n ],\n [\n -117.39990234375,\n 37.081475648860525\n ],\n [\n -120.39916992187499,\n 34.43409789359469\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2a7de4b08de9379b30a2","contributors":{"authors":[{"text":"Wright, Michael T. 0000-0003-0653-6466","orcid":"https://orcid.org/0000-0003-0653-6466","contributorId":116545,"corporation":false,"usgs":false,"family":"Wright","given":"Michael T.","affiliations":[],"preferred":false,"id":539646,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fram, Miranda S. 0000-0002-6337-059X mfram@usgs.gov","orcid":"https://orcid.org/0000-0002-6337-059X","contributorId":1156,"corporation":false,"usgs":true,"family":"Fram","given":"Miranda","email":"mfram@usgs.gov","middleInitial":"S.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":539647,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Belitz, Kenneth 0000-0003-4481-2345 kbelitz@usgs.gov","orcid":"https://orcid.org/0000-0003-4481-2345","contributorId":442,"corporation":false,"usgs":true,"family":"Belitz","given":"Kenneth","email":"kbelitz@usgs.gov","affiliations":[{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"preferred":true,"id":539648,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70137521,"text":"sir20155005 - 2015 - Data Collection and Simulation of Ecological Habitat and Recreational Habitat in the Shenandoah River, Virginia","interactions":[],"lastModifiedDate":"2016-03-21T15:08:10","indexId":"sir20155005","displayToPublicDate":"2015-01-30T14:30:00","publicationYear":"2015","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":"2015-5005","title":"Data Collection and Simulation of Ecological Habitat and Recreational Habitat in the Shenandoah River, Virginia","docAbstract":"This report presents updates to methods, describes additional data collected, documents modeling results, and discusses implications from an updated habitat-flow model that can be used to predict ecological habitat for fish and recreational habitat for canoeing on the main stem Shenandoah River in Virginia. Given a 76-percent increase in population predictions for 2040 over 1995 records, increased water-withdrawal scenarios were evaluated to determine the effects on habitat and recreation in the Shenandoah River. Projected water demands for 2040 vary by watershed: the North Fork Shenandoah River shows a 55.9-percent increase, the South Fork Shenandoah River shows a 46.5-percent increase, and the main stem Shenandoah River shows a 52-percent increase; most localities are projected to approach the total permitted surface-water and groundwater withdrawals values by 2040, and a few localities are projected to exceed these values.
\nThe habitat model used for this study evaluates the suitability of ecological habitat, represented by fish, and recreational habitat, represented by canoeing, based on depth, velocity, and substrate conditions, which are weighted for the physical habitat types (riffles, runs, or pools) present within a stretch of river. Weighted usable-habitat area in the Lockes Mill reach was maximized for adult smallmouth bass and sub-adult smallmouth bass (Micropterus dolomieu) and river chub (Nocomis micropogon) when streamflows were equal to median flow (900 cubic feet per second) for summer months. Ecological maximum weighted usable-habitat areas for smaller fish, such as spotfin or satinfin shiner (Cyprinella spp.), margined madtom (Noturus insignis), and juvenile redbreast sunfish (Lepomis auritus) occurred with 10th percentile flows (482 cubic feet per second) and lower. Recreational weighted usable-habitat areas for canoeing were maximized when streamflows were above the 75th percentile (1,410 cubic feet per second). During historic droughts, streamflows were less than the 10th percentile, and adult smallmouth bass and sub-adult smallmouth bass habitat was below normal for the majority of days during at least 2 months of the summer. When streamflows were less than the lowest 7-day average in a 10-year period, or 7Q10 flow (357 cubic feet per second), margined madtom, river chub, and sub-adult redbreast sunfish habitat areas were below normal as well. Streamflows that limit most fish species habit availability range from 300 to 500 cubic feet per second. For the drought years simulated, flows that were equal to or less than the 10th percentile for summer months did not provide adequate depth for canoe passage through riffle habitats. A modeling limitation for higher flows than those studied during development of the habitat-suitability criteria is that modeled habitat availability will decrease as flows increase.
\nTime-series analyses were used to investigate changes in habitat availability with increased water withdrawals of 10, 20, and almost 50 percent (48.6 percent) up to the 2040 amounts projected by local water supply plans. Adult and sub-adult smallmouth bass frequently had habitat availability outside the normal range for habitat conditions during drought years, yet 10- or 20-percent increases in withdrawals did not contribute to a large reduction in habitat. When withdrawals were increased by 50 percent, there was an additional decrease in habitat. During 2002 drought scenarios, reduced habitat availability for sub-adult redbreast sunfish or river chub was only slightly evident with 50-percent increased withdrawal scenarios. Recreational habitat represented by canoeing decreased lower than normal during the 2002 drought. For a recent normal year, like 2012, increased water-withdrawal scenarios did not affect habitat availability for fish such as adult and sub-adult smallmouth bass, sub-adult redbreast sunfish, or river chub. Canoeing habitat availability was within the normal range most of 2012, and increased water-withdrawal scenarios showed almost no affect. For both ecological fish habitat and recreational canoeing habitat, the antecedent conditions (habitat within normal range of habitat or below normal) appear to govern whether additional water withdrawals will affect habitat availability. As human populations and water demands increase, many of the ecological or recreational stresses may be lessened by managing the timing of water withdrawals from the system.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155005","collaboration":"Prepared in cooperation with Clarke County and Warren County, Virginia","usgsCitation":"Krstolic, J.L., 2015, Data Collection and Simulation of Ecological Habitat and Recreational Habitat in the Shenandoah River, Virginia: U.S. Geological Survey Scientific Investigations Report 2015-5005, v, 30 p., https://doi.org/10.3133/sir20155005.","productDescription":"v, 30 p.","numberOfPages":"40","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-054536","costCenters":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"links":[{"id":297646,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20155005.jpg"},{"id":297644,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2015/5005/"},{"id":297645,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5005/pdf/sir2015-5005.pdf","text":"Report","size":"1.83 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"projection":"Universal Transverse Mercator projection, Zone 17N","datum":"North American Datum of 1983","country":"United States","state":"Virginia","otherGeospatial":"Shenandoah River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.97649383544922,\n 39.091699613104595\n ],\n [\n -77.97649383544922,\n 39.10695312754686\n ],\n [\n -77.9190731048584,\n 39.10695312754686\n ],\n [\n -77.9190731048584,\n 39.091699613104595\n ],\n [\n -77.97649383544922,\n 39.091699613104595\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2a63e4b08de9379b3032","contributors":{"authors":[{"text":"Krstolic, Jennifer L. 0000-0003-2253-9886 jkrstoli@usgs.gov","orcid":"https://orcid.org/0000-0003-2253-9886","contributorId":3677,"corporation":false,"usgs":true,"family":"Krstolic","given":"Jennifer","email":"jkrstoli@usgs.gov","middleInitial":"L.","affiliations":[{"id":37759,"text":"VA/WV Water Science Center","active":true,"usgs":true},{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":537861,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70137255,"text":"sir20155002 - 2015 - Chemical constituents in groundwater from multiple zones in the eastern Snake River Plain aquifer, Idaho National Laboratory, Idaho, 2009-13","interactions":[],"lastModifiedDate":"2015-01-30T09:00:40","indexId":"sir20155002","displayToPublicDate":"2015-01-30T10:00:00","publicationYear":"2015","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":"2015-5002","title":"Chemical constituents in groundwater from multiple zones in the eastern Snake River Plain aquifer, Idaho National Laboratory, Idaho, 2009-13","docAbstract":"From 2009 to 2013, the U.S. Geological Survey’s (USGS) Idaho National Laboratory (INL) Project office, in cooperation with the U.S. Department of Energy, collected water-quality samples from multiple water-bearing zones in the eastern Snake River Plain aquifer. Water samples were collected from 11 monitoring wells completed in about 250–750 feet of the upper part of the aquifer, and samples were analyzed for selected major ions, trace elements, nutrients, radiochemical constituents, and stable isotopes. Each well was equipped with a multilevel monitoring system containing four to seven sampling ports that were each isolated by permanent packer systems. The sampling ports were installed in aquifer zones that were highly transmissive and that represented the water chemistry of the top three to five model layers of a steady-state and transient groundwater‑flow model. The groundwater-flow model and water chemistry are being used to better define movement of wastewater constituents in the aquifer.
\nThe water-chemistry composition of all sampled zones for the five new multilevel wells is calcium plus magnesium bicarbonate. One of the zones in well USGS 131A has a slightly different chemistry from the rest of the zones and wells and the difference is attributed to more wastewater influence from the Idaho Nuclear Technology and Engineering Center. One well, USGS 135, was not influenced by wastewater disposal and consisted of mostly older water in all of its zones.
\nTritium concentrations in relation to basaltic flow units indicate the presence of wastewater influence in multiple basalt flow groups; however, tritium is most abundant in the South Late Matuyama flow group in the southern boundary wells. The concentrations of wastewater constituents in deep zones in wells Middle 2051, USGS 132, USGS 105, and USGS 103 support the concept of groundwater flow deepening in the southwestern corner of the INL, as indicated by the INL groundwater-flow model.
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,{"id":70129825,"text":"fs20143110 - 2015 - The 3D Elevation Program: summary for New Hampshire","interactions":[],"lastModifiedDate":"2016-08-10T15:30:33","indexId":"fs20143110","displayToPublicDate":"2015-01-30T09:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-3110","title":"The 3D Elevation Program: summary for New Hampshire","docAbstract":"Elevation data are essential to a broad range of applications important to New Hampshire, including flood mitigation, land development, agriculture, transportation planning and design, infrastructure asset inventory and management, and many others. For the State of New Hampshire, elevation data are critical for many business uses such as flood risk management, natural resources conservation, forest resources management, agriculture and precision farming, infrastructure and construction management, and geologic resource assessment and hazard mitigation. Today, high-density light detection and ranging (lidar) data are the primary sources for deriving elevation models and other datasets. Federal, State, Tribal, and local agencies work in partnership to (1) replace data that are older and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of State and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data.
\nThe National Enhanced Elevation Assessment evaluated multiple elevation data acquisition options to determine the optimal data quality and data replacement cycle relative to cost to meet the identified requirements of the user community. The evaluation demonstrated that lidar acquisition at quality level 2 for the conterminous United States and quality level 5 interferometric synthetic aperture radar (ifsar) data for Alaska with a 6- to 10-year acquisition cycle provided the highest benefit/cost ratios. The 3D Elevation Program (3DEP) initiative selected an 8-year acquisition cycle for the respective quality levels. 3DEP, managed by the U.S. Geological Survey, the Office of Management and Budget Circular A–16 lead agency for terrestrial elevation data, responds to the growing need for high-quality topographic data and a wide range of other 3D representations of the Nation’s natural and constructed features.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20143110","usgsCitation":"Carswell, W., 2015, The 3D Elevation Program: summary for New Hampshire (Version 1.0: Originally posted January 30, 2015; Version 1.1: June 29, 2015): U.S. Geological Survey Fact Sheet 2014-3110, 2 p., https://doi.org/10.3133/fs20143110.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-059925","costCenters":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"links":[{"id":297634,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20143110.jpg"},{"id":297633,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2014/3110/pdf/fs2014-3110.pdf","text":"Report","size":"318 KB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":297632,"rank":1,"type":{"id":15,"text":"Index 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Jr. carswell@usgs.gov","contributorId":1787,"corporation":false,"usgs":true,"family":"Carswell","given":"William J.","suffix":"Jr.","email":"carswell@usgs.gov","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":false,"id":519924,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70147192,"text":"70147192 - 2015 - Mapping the distribution of malaria: current approaches and future directions","interactions":[],"lastModifiedDate":"2015-12-14T16:00:01","indexId":"70147192","displayToPublicDate":"2015-01-30T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Mapping the distribution of malaria: current approaches and future directions","docAbstract":"Mapping the distribution of malaria has received substantial attention because the disease is a major source of illness and mortality in humans, especially in developing countries. It also has a defined temporal and spatial distribution. The distribution of malaria is most influenced by its mosquito vector, which is sensitive to extrinsic environmental factors such as rainfall and temperature. Temperature also affects the development rate of the malaria parasite in the mosquito. Here, we review the range of approaches used to model the distribution of malaria, from spatially explicit to implicit, mechanistic to correlative. Although current methods have significantly improved our understanding of the factors influencing malaria transmission, significant gaps remain, particularly in incorporating nonlinear responses to temperature and temperature variability. We highlight new methods to tackle these gaps and to integrate new data with models.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Analyzing and modeling spatial and temporal dynamics of infectious diseases","language":"English","publisher":"Wiley","doi":"10.1002/9781118630013.ch10","usgsCitation":"Johnson, L., Lafferty, K.D., McNally, A., Mordecai, E., Paaijmans, K.P., Pawar, S., and Ryan, S.J., 2015, Mapping the distribution of malaria: current approaches and future directions, chap. of Analyzing and modeling spatial and temporal dynamics of infectious diseases, p. 189-209, https://doi.org/10.1002/9781118630013.ch10.","productDescription":"21 p.","startPage":"189","endPage":"209","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-054101","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":498956,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/9781118630013.ch10","text":"Publisher Index Page"},{"id":312272,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"edition":"1","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2015-01-30","publicationStatus":"PW","scienceBaseUri":"566ff653e4b09cfe53ca79ae","contributors":{"editors":[{"text":"Chen, Dongmei","contributorId":150562,"corporation":false,"usgs":false,"family":"Chen","given":"Dongmei","email":"","affiliations":[],"preferred":false,"id":582138,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Moulin, Bernard","contributorId":150563,"corporation":false,"usgs":false,"family":"Moulin","given":"Bernard","email":"","affiliations":[],"preferred":false,"id":582139,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Wu, Jianhong","contributorId":92413,"corporation":false,"usgs":false,"family":"Wu","given":"Jianhong","email":"","affiliations":[],"preferred":false,"id":582140,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Johnson, Leah R.","contributorId":83382,"corporation":false,"usgs":true,"family":"Johnson","given":"Leah R.","affiliations":[],"preferred":false,"id":545715,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lafferty, Kevin D. 0000-0001-7583-4593 klafferty@usgs.gov","orcid":"https://orcid.org/0000-0001-7583-4593","contributorId":1415,"corporation":false,"usgs":true,"family":"Lafferty","given":"Kevin","email":"klafferty@usgs.gov","middleInitial":"D.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":545714,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McNally, Amy","contributorId":53225,"corporation":false,"usgs":true,"family":"McNally","given":"Amy","affiliations":[],"preferred":false,"id":545716,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mordecai, Erin A.","contributorId":9113,"corporation":false,"usgs":true,"family":"Mordecai","given":"Erin A.","affiliations":[],"preferred":false,"id":545717,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Paaijmans, Krijn P.","contributorId":62459,"corporation":false,"usgs":true,"family":"Paaijmans","given":"Krijn","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":545718,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pawar, Samraat","contributorId":22622,"corporation":false,"usgs":true,"family":"Pawar","given":"Samraat","email":"","affiliations":[],"preferred":false,"id":545719,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ryan, Sadie J.","contributorId":102738,"corporation":false,"usgs":true,"family":"Ryan","given":"Sadie","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":545720,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70169070,"text":"70169070 - 2015 - Avian Influenza spread and transmission dynamics","interactions":[],"lastModifiedDate":"2017-07-19T15:43:32","indexId":"70169070","displayToPublicDate":"2015-01-30T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Avian Influenza spread and transmission dynamics","docAbstract":"The spread of highly pathogenic avian influenza (HPAI) viruses of type A of subtype H5N1 has been a serious threat to global public health. Understanding the roles of various (migratory, wild, poultry) bird species in the transmission of these viruses is critical for designing and implementing effective control and intervention measures. Developing appropriate models and mathematical techniques to understand these roles and to evaluate the effectiveness of mitigation strategies have been a challenge. Recent development of the global health surveillance (especially satellite tracking and GIS techniques) and the mathematical theory of dynamical systems combined have gradually shown the promise of some cutting-edge methodologies and techniques in mathematical biology to meet this challenge.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Analyzing and modeling spatial and temporal dynamics of infectious diseases","language":"English","publisher":"Wiley","doi":"10.1002/9781118630013.ch7","usgsCitation":"Bourouiba, L., Gourley, S.A., Liu, R., Takekawa, J.Y., and Wu, J., 2015, Avian Influenza spread and transmission dynamics, chap. of Analyzing and modeling spatial and temporal dynamics of infectious diseases, p. 137-162, https://doi.org/10.1002/9781118630013.ch7.","productDescription":"26 p.","startPage":"137","endPage":"162","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056959","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":319583,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2015-01-30","publicationStatus":"PW","scienceBaseUri":"56fba733e4b0a6037df1a083","contributors":{"editors":[{"text":"Chen, Dongmei","contributorId":150562,"corporation":false,"usgs":false,"family":"Chen","given":"Dongmei","email":"","affiliations":[],"preferred":false,"id":625550,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Moulin, Bernard","contributorId":150563,"corporation":false,"usgs":false,"family":"Moulin","given":"Bernard","email":"","affiliations":[],"preferred":false,"id":625551,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Wu, Jianhong","contributorId":92413,"corporation":false,"usgs":false,"family":"Wu","given":"Jianhong","email":"","affiliations":[],"preferred":false,"id":625552,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Bourouiba, Lydia","contributorId":167584,"corporation":false,"usgs":false,"family":"Bourouiba","given":"Lydia","email":"","affiliations":[{"id":24763,"text":"Civil & Environmental Engineering, MIT, MA, USA","active":true,"usgs":false}],"preferred":false,"id":622767,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gourley, Stephen A.","contributorId":60487,"corporation":false,"usgs":true,"family":"Gourley","given":"Stephen","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":622768,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Liu, Rongsong","contributorId":43480,"corporation":false,"usgs":false,"family":"Liu","given":"Rongsong","email":"","affiliations":[],"preferred":false,"id":622769,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Takekawa, John Y. 0000-0003-0217-5907 john_takekawa@usgs.gov","orcid":"https://orcid.org/0000-0003-0217-5907","contributorId":176168,"corporation":false,"usgs":true,"family":"Takekawa","given":"John","email":"john_takekawa@usgs.gov","middleInitial":"Y.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":622766,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wu, Jianhong","contributorId":92413,"corporation":false,"usgs":false,"family":"Wu","given":"Jianhong","email":"","affiliations":[],"preferred":false,"id":622770,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70140273,"text":"70140273 - 2015 - Structural equation modeling: Building and evaluating causal models","interactions":[],"lastModifiedDate":"2022-12-06T23:58:27.684537","indexId":"70140273","displayToPublicDate":"2015-01-29T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"8","title":"Structural equation modeling: Building and evaluating causal models","docAbstract":"Scientists frequently wish to study hypotheses about causal relationships, rather than just statistical associations. This chapter addresses the question of how scientists might approach this ambitious task. Here we describe structural equation modeling (SEM), a general modeling framework for the study of causal hypotheses. Our goals are to (a) concisely describe the methodology, (b) illustrate its utility for investigating ecological systems, and (c) provide guidance for its application. Throughout our presentation, we rely on a study of the effects of human activities on wetland ecosystems to make our description of methodology more tangible. We begin by presenting the fundamental principles of SEM, including both its distinguishing characteristics and the requirements for modeling hypotheses about causal networks. We then illustrate SEM procedures and offer guidelines for conducting SEM analyses. Our focus in this presentation is on basic modeling objectives and core techniques. Pointers to additional modeling options are also given.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Ecological statistics: contemporary theory and application","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Oxford University Press","publisherLocation":"Oxford, UK","usgsCitation":"Grace, J.B., Scheiner, S.M., and Schoolmaster, D.R., 2015, Structural equation modeling: Building and evaluating causal models, chap. 8 of Ecological statistics: contemporary theory and application, p. 168-199.","productDescription":"32 p.","startPage":"168","endPage":"199","numberOfPages":"32","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057226","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"links":[{"id":298333,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54faddbce4b02419550db6e4","contributors":{"authors":[{"text":"Grace, James B. 0000-0001-6374-4726 gracej@usgs.gov","orcid":"https://orcid.org/0000-0001-6374-4726","contributorId":884,"corporation":false,"usgs":true,"family":"Grace","given":"James","email":"gracej@usgs.gov","middleInitial":"B.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":539926,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Scheiner, Samuel M.","contributorId":139066,"corporation":false,"usgs":false,"family":"Scheiner","given":"Samuel","email":"","middleInitial":"M.","affiliations":[{"id":12642,"text":"National Science Foundation","active":true,"usgs":false}],"preferred":false,"id":539927,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schoolmaster, Donald R. Jr. 0000-0003-0910-4458 schoolmasterd@usgs.gov","orcid":"https://orcid.org/0000-0003-0910-4458","contributorId":4746,"corporation":false,"usgs":true,"family":"Schoolmaster","given":"Donald","suffix":"Jr.","email":"schoolmasterd@usgs.gov","middleInitial":"R.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":539928,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70139461,"text":"70139461 - 2015 - The effect of pressurized magma chamber growth on melt migration and pre-caldera vent locations through time at Mount Mazama, Crater Lake, Oregon","interactions":[],"lastModifiedDate":"2018-10-24T09:08:08","indexId":"70139461","displayToPublicDate":"2015-01-28T10:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1427,"text":"Earth and Planetary Science Letters","active":true,"publicationSubtype":{"id":10}},"title":"The effect of pressurized magma chamber growth on melt migration and pre-caldera vent locations through time at Mount Mazama, Crater Lake, Oregon","docAbstract":"The pattern of eruptions at long-lived volcanic centers provides a window into the co-evolution of crustal magma transport, tectonic stresses, and unsteady magma generation at depth. Mount Mazama in the Oregon Cascades has seen variable activity over the last 400 ky, including the 50 km3 climactic eruption at ca. 7.7 ka that produced Crater Lake caldera. The physical mechanisms responsible for the assembly of silicic magma reservoirs that are the precursors to caldera-forming eruptions are poorly understood. Here we argue that the spatial and temporal distribution of geographically clustered volcanic vents near Mazama reflects the development of a centralized magma chamber that fed the climactic eruption. Time-averaged eruption rates at Mount Mazama imply an order of magnitude increase in deep magma influx prior to the caldera-forming event, suggesting that unsteady mantle melting triggered a chamber growth episode that culminated in caldera formation. We model magma chamber–dike interactions over ∼50 ky preceding the climactic eruption to fit the observed distribution of surface eruptive vents in space and time, as well as petrologically estimated deep influx rates. Best fitting models predict an expanding zone of dike capture caused by a growing, oblate spheroidal magma chamber with 10–30 MPa of overpressure. This growing zone of chamber influence causes closest approaching regional mafic vent locations as well as more compositionally evolved Mazama eruptions to migrate away from the climactic eruptive center, returning as observed to the center after the chamber drains during the caldera-forming eruption.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.epsl.2014.12.001","usgsCitation":"Karlstrom, L., Wright, H.M., and Bacon, C.R., 2015, The effect of pressurized magma chamber growth on melt migration and pre-caldera vent locations through time at Mount Mazama, Crater Lake, Oregon: Earth and Planetary Science Letters, v. 412, p. 209-219, https://doi.org/10.1016/j.epsl.2014.12.001.","productDescription":"11 p.","startPage":"209","endPage":"219","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-053451","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":297594,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Cascades, Crater Lake, Mount Mazama","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.33276367187499,\n 42.754071181010865\n ],\n [\n -122.33276367187499,\n 43.069891000631294\n ],\n [\n -121.82052612304688,\n 43.069891000631294\n ],\n [\n -121.82052612304688,\n 42.754071181010865\n ],\n [\n -122.33276367187499,\n 42.754071181010865\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"412","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2abfe4b08de9379b31cc","contributors":{"authors":[{"text":"Karlstrom, Leif","contributorId":23048,"corporation":false,"usgs":false,"family":"Karlstrom","given":"Leif","affiliations":[],"preferred":false,"id":539417,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wright, Heather M. 0000-0001-9013-507X hwright@usgs.gov","orcid":"https://orcid.org/0000-0001-9013-507X","contributorId":3949,"corporation":false,"usgs":true,"family":"Wright","given":"Heather","email":"hwright@usgs.gov","middleInitial":"M.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":539416,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bacon, Charles R. 0000-0002-2165-5618 cbacon@usgs.gov","orcid":"https://orcid.org/0000-0002-2165-5618","contributorId":2909,"corporation":false,"usgs":true,"family":"Bacon","given":"Charles","email":"cbacon@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":539418,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70133413,"text":"fs20143115 - 2015 - The 3D Elevation Program: summary for Utah","interactions":[],"lastModifiedDate":"2016-08-17T15:07:01","indexId":"fs20143115","displayToPublicDate":"2015-01-27T12:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-3115","title":"The 3D Elevation Program: summary for Utah","docAbstract":"Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the State of Utah, elevation data are critical for infrastructure and construction management, natural resources conservation, geologic resource assessment and hazard mitigation, flood risk management, agriculture and precision farming, and other business uses. Today, high-density light detection and ranging (lidar) data are the primary sources for deriving elevation models and other datasets. Federal, State, Tribal, and local agencies work in partnership to (1) replace data that are older and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of State and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data.
\nThe National Enhanced Elevation Assessment evaluated multiple elevation data acquisition options to determine the optimal data quality and data replacement cycle relative to cost to meet the identified requirements of the user community. The evaluation demonstrated that lidar acquisition at quality level 2 for the conterminous United States and quality level 5 interferometric synthetic aperture radar (ifsar) data for Alaska with a 6- to 10-year acquisition cycle provided the highest benefit/cost ratios. The 3D Elevation Program (3DEP) initiative selected an 8-year acquisition cycle for the respective quality levels. 3DEP, managed by the U.S. Geological Survey, the Office of Management and Budget Circular A–16 lead agency for terrestrial elevation data, responds to the growing need for high-quality topographic data and a wide range of other 3D representations of the Nation’s natural and constructed features.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20143115","usgsCitation":"Carswell, W., 2015, The 3D Elevation Program: summary for Utah (Version 1.0: Originally posted January 27, 2015; Version 1.1: June 29, 2015): U.S. Geological Survey Fact Sheet 2014-3115, 2 p., https://doi.org/10.3133/fs20143115.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-059632","costCenters":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"links":[{"id":297588,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20143115.jpg"},{"id":297586,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2014/3115/"},{"id":297587,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2014/3115/pdf/fs2014-3115.pdf","text":"Report","size":"282 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,{"id":70138827,"text":"sir20145226 - 2015 - Hydrologic record extension of water-level data in the Everglades Depth Estimation Network (EDEN), 1991-99","interactions":[],"lastModifiedDate":"2017-01-18T13:16:53","indexId":"sir20145226","displayToPublicDate":"2015-01-27T09:15:00","publicationYear":"2015","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":"2014-5226","title":"Hydrologic record extension of water-level data in the Everglades Depth Estimation Network (EDEN), 1991-99","docAbstract":"The real-time Everglades Depth Estimation Network (EDEN) has been established to support a variety of scientific and water management purposes. The expansiveness of the Everglades, limited number of gaging stations, and extreme sensitivity of the ecosystem to small changes in water depth have created a need for accurate water-level and water-depth maps. The EDEN water-surface elevation model uses data from approximately 240 gages in the Everglades to create daily continuous interpolations of the water-surface elevation and water depth for the freshwater portion of the Everglades from 2000 to the present (2014). These maps provide hydrologic data previously unavailable for assessing biological and ecological studies.
\nEcologists working in the Everglades expressed a need to the EDEN project team for daily EDEN water-level surfaces from 1990 to 1999. The additional 10 years of surfaces will provide ecologists and resource managers with two decades (1991–2011) of surfaces to analyze hydrologic dynamics. Before 2000, many of the EDEN gages used to generate water surfaces were not in operation. These datasets were extended to provide estimations of hydrologic time-series histories. The general approach to the record extension (hindcasts) was to (1) create a database of available data from 1990 to the present; (2) use dynamic cluster analysis to group stations with similar hydrologic behaviors for subareas of the Everglades with a large number of stations; (3) use results from the cluster analysis to select candidate explanatory variables; (4) develop linear regression or artificial neural network models to extend water-level records; and (5) evaluate record extensions by using model performance statistics and comparison of water-surface maps for similar hydrologic conditions for the hindcasted period (1991–99) and measured period (2000–11).
\nTo hindcast and fill data records, 214 empirical models were developed—189 are linear regression models and 25 are artificial neural network models. The coefficient of determination (R2) for 163 of the models is greater than 0.80 and the median percent model error (root mean square error divided by the range of the measured data) is 5 percent. To evaluate the performance of the hindcast models as a group, contour maps of modeled water-level surfaces at 2-centimeter (cm) intervals were generated using the hindcasted data. The 2-cm contour maps were examined for selected days to verify that water surfaces from the EDEN model are consistent with the input data. The biweekly 2-cm contour maps did show a higher number of issues during days in 1990 as compared to days after 1990. May 1990 had the lowest water levels in the Everglades of the 21-year dataset used for the hindcasting study. To hindcast these record low conditions in 1990, many of the hindcast models would require large extrapolations beyond the range of the predictive quality of the models. For these reasons, it was decided to limit the hindcasted data to the period January 1, 1991, to December 31, 1999. Overall, the hindcasted and gap-filled data are assumed to provide reasonable estimates of station-specific water-level data for an extended historical period to inform research and natural resource management in the Everglades.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145226","usgsCitation":"Conrads, P., Petkewich, M.D., O’Reilly, A.M., and Telis, P.A., 2015, Hydrologic record extension of water-level data in the Everglades Depth Estimation Network (EDEN), 1991-99: U.S. Geological Survey Scientific Investigations Report 2014-5226, Report: vi, 27 p.; 2 Tables; 2 Appendixes, https://doi.org/10.3133/sir20145226.","productDescription":"Report: vi, 27 p.; 2 Tables; 2 Appendixes","numberOfPages":"38","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"1991-01-01","temporalEnd":"1999-12-31","ipdsId":"IP-059254","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":297562,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145226.jpg"},{"id":297559,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5226/"},{"id":297560,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5226/pdf/sir2014-5226.pdf","size":"2.93 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":297561,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2014/5226/downloads/sir2014-5226.xlsx","text":"Table 1 and 3, Appendixes 1-2","size":"149 kB","linkFileType":{"id":3,"text":"xlsx"}}],"projection":"Universal Transverse Mercator projection","country":"United States","state":"Florida","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.93328857421875,\n 25.063209244186485\n ],\n [\n -81.93328857421875,\n 26.649913524725044\n ],\n [\n -79.98596191406249,\n 26.649913524725044\n ],\n [\n -79.98596191406249,\n 25.063209244186485\n ],\n [\n -81.93328857421875,\n 25.063209244186485\n ]\n ]\n ]\n }\n }\n ]\n}","publicComments":"Prepared as part of the U.S. Geological Survey Greater Everglades Priority Ecosystem Science","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2a87e4b08de9379b30d1","contributors":{"authors":[{"text":"Conrads, Paul 0000-0003-0408-4208 pconrads@usgs.gov","orcid":"https://orcid.org/0000-0003-0408-4208","contributorId":764,"corporation":false,"usgs":true,"family":"Conrads","given":"Paul","email":"pconrads@usgs.gov","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true}],"preferred":false,"id":539310,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Petkewich, Matthew D. 0000-0002-5749-6356 mdpetkew@usgs.gov","orcid":"https://orcid.org/0000-0002-5749-6356","contributorId":982,"corporation":false,"usgs":true,"family":"Petkewich","given":"Matthew","email":"mdpetkew@usgs.gov","middleInitial":"D.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true}],"preferred":true,"id":539311,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"O’Reilly, Andrew M. 0000-0003-3220-1248 aoreilly@usgs.gov","orcid":"https://orcid.org/0000-0003-3220-1248","contributorId":2184,"corporation":false,"usgs":true,"family":"O’Reilly","given":"Andrew","email":"aoreilly@usgs.gov","middleInitial":"M.","affiliations":[{"id":5051,"text":"FLWSC-Orlando","active":true,"usgs":true}],"preferred":true,"id":539312,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Telis, Pamela A. patelis@usgs.gov","contributorId":1461,"corporation":false,"usgs":true,"family":"Telis","given":"Pamela","email":"patelis@usgs.gov","middleInitial":"A.","affiliations":[{"id":269,"text":"FLWSC-Ft. Lauderdale","active":true,"usgs":true}],"preferred":false,"id":539313,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70138808,"text":"ds914 - 2015 - Bathymetry of the Wilderness breach at Fire Island, New York, June 2013","interactions":[],"lastModifiedDate":"2016-02-08T12:36:53","indexId":"ds914","displayToPublicDate":"2015-01-26T16:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"914","title":"Bathymetry of the Wilderness breach at Fire Island, New York, June 2013","docAbstract":"The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center in St. Petersburg, Florida, collaborated with the U.S. Army Corps of Engineers Field Research Facility in Duck, North Carolina, to collect shallow water bathymetric data of the Wilderness breach on Fire Island, New York, in June 2013. The breach formed in October 2012 during Hurricane Sandy, and the USGS is involved in a post-Sandy effort to map, monitor, and model the morphologic evolution of the breach as part of Hurricane Sandy Supplemental Project GS2-2B: Linking Coastal Vulnerability and Process, Fire Island. This publication includes a bathymetric dataset of the breach and the adjacent nearshore on the ocean side of the island. The objective of the data collection and analysis is to map the bathymetry of the primary breach channel, ebb shoal, and nearshore bar system.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds914","usgsCitation":"Brownell, A.T., Hapke, C.J., Spore, N., and McNinch, J., 2015, Bathymetry of the Wilderness breach at Fire Island, New York, June 2013: U.S. Geological Survey Data Series 914, HTML Document, https://doi.org/10.3133/ds914.","productDescription":"HTML Document","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-059527","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":297555,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds914.jpg"},{"id":297554,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0914/ds914_abstract.html","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"Report"}],"country":"United States","state":"New York","otherGeospatial":"Fire Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.3502197265625,\n 40.588928169693745\n ],\n [\n -73.3502197265625,\n 40.81796653313175\n ],\n [\n -72.66357421875,\n 40.81796653313175\n ],\n [\n -72.66357421875,\n 40.588928169693745\n ],\n [\n -73.3502197265625,\n 40.588928169693745\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2a58e4b08de9379b2ffa","contributors":{"authors":[{"text":"Brownell, Andrew T. abrownell@usgs.gov","contributorId":5801,"corporation":false,"usgs":true,"family":"Brownell","given":"Andrew","email":"abrownell@usgs.gov","middleInitial":"T.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":538902,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hapke, Cheryl J. 0000-0002-2753-4075 chapke@usgs.gov","orcid":"https://orcid.org/0000-0002-2753-4075","contributorId":2981,"corporation":false,"usgs":true,"family":"Hapke","given":"Cheryl","email":"chapke@usgs.gov","middleInitial":"J.","affiliations":[{"id":6676,"text":"USGS (retired)","active":true,"usgs":false}],"preferred":true,"id":538904,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Spore, Nicholas J.","contributorId":138833,"corporation":false,"usgs":false,"family":"Spore","given":"Nicholas J.","affiliations":[{"id":12537,"text":"USACE","active":true,"usgs":false}],"preferred":false,"id":538903,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McNinch, Jesse E.","contributorId":93804,"corporation":false,"usgs":true,"family":"McNinch","given":"Jesse E.","affiliations":[],"preferred":false,"id":538905,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70134733,"text":"sir20145202 - 2015 - Flood-inundation maps for Indian Creek and Tomahawk Creek, Johnson County, Kansas, 2014","interactions":[],"lastModifiedDate":"2016-06-14T11:12:39","indexId":"sir20145202","displayToPublicDate":"2015-01-26T16:00:00","publicationYear":"2015","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":"2014-5202","title":"Flood-inundation maps for Indian Creek and Tomahawk Creek, Johnson County, Kansas, 2014","docAbstract":"Digital flood-inundation maps for a 6.4-mile upper reach of Indian Creek from College Boulevard to the confluence with Tomahawk Creek, a 3.9-mile reach of Tomahawk Creek from 127th Street to the confluence with Indian Creek, and a 1.9-mile lower reach of Indian Creek from the confluence with Tomahawk Creek to just beyond the Kansas/Missouri border at State Line Road in Johnson County, Kansas, were created by the U.S. Geological Survey in cooperation with the city of Overland Park, Kansas. The flood-inundation maps, which can be accessed through the U.S. Geological Survey Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation/, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the U.S. Geological Survey streamgages on Indian Creek at Overland Park, Kansas; Indian Creek at State Line Road, Leawood, Kansas; and Tomahawk Creek near Overland Park, Kansas. Near real time stages at these streamgages may be obtained on the Web from the U.S. Geological Survey National Water Information System at http://waterdata.usgs.gov/nwis or the National Weather Service Advanced Hydrologic Prediction Service at http://water.weather.gov/ahps/, which also forecasts flood hydrographs at these sites.
Flood profiles were computed for the stream reaches by means of a one-dimensional step-backwater model. The model was calibrated for each reach by using the most current stage-discharge relations at the streamgages. The hydraulic models were then used to determine 15 water-surface profiles for Indian Creek at Overland Park, Kansas; 17 water-surface profiles for Indian Creek at State Line Road, Leawood, Kansas; and 14 water-surface profiles for Tomahawk Creek near Overland Park, Kansas, for flood stages at 1-foot intervals referenced to the streamgage datum and ranging from bankfull to the next interval above the 0.2-percent annual exceedance probability flood level (500-year recurrence interval). The simulated water-surface profiles were then combined in a geographic information system with a digital elevation model derived from light detection and ranging data (having a 0.429-foot vertical and 0.228-foot horizontal accuracy) to delineate the area flooded at each water level.
The availability of these maps, along with Web information regarding current stage from the U.S. Geological Survey streamgages and forecasted high-flow stages from the National Weather Service, will provide emergency management personnel and residents with information that is critical for flood response activities such as evacuations, road closures, and postflood recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145202","collaboration":"Prepared in cooperation with the City of Overland Park, Kansas","usgsCitation":"Peters, A.J., and Studley, S.E., 2014, Flood-inundation maps for Indian Creek and Tomahawk Creek, Johnson County, Kansas, 2014 (ver. 1.1, January 2016): U.S. Geological Survey Scientific Investigations Report 2014–5202, 11 p., https://dx.doi.org/10.3133/sir20145202.","productDescription":"vi, 11 p.","numberOfPages":"22","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-056342","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":323570,"rank":4,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2014/5202/downloads/","text":"Downloads Directory","linkHelpText":"Contains: geospatial database. Refer to the Metadata file for more information."},{"id":323571,"rank":5,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sir/2014/5202/downloads/metadata.docx"},{"id":297546,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2014/5202/pdf/coverthb.jpg"},{"id":297545,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5202/pdf/sir20145202.pdf","text":"Report","size":"10.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":297536,"rank":3,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5202/"},{"id":314701,"rank":6,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2014/5202/versionhist.txt","size":"1 kb","linkFileType":{"id":2,"text":"txt"},"description":"SIR 2014-5202 version history"}],"country":"United States","state":"Kansas","county":"Johnson County","otherGeospatial":"Indian Creek, Tomahawk Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -102.1728515625,\n 40.01078714046552\n ],\n [\n -94.833984375,\n 39.9434364619742\n ],\n [\n -94.833984375,\n 37.020098201368114\n ],\n [\n -102.0849609375,\n 37.020098201368114\n ],\n [\n -102.1728515625,\n 40.01078714046552\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: Originally posted January 26, 2015; Version 1.1: January 25, 2016","contact":"Director, USGS Kansas Water Science Center
4821 Quail Crest Place
Lawrence, KS 66049
\nhttp://ks.water.usgs.gov
","tableOfContents":"\n- Acknowledgments
\n- Abstract
\n- Introduction
\n- Creation of Flood-Inundation-Map Library
\n- Summary
\n- References Cited
\n
","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2016-01-25","noUsgsAuthors":false,"publicationDate":"2016-01-25","publicationStatus":"PW","scienceBaseUri":"54dd2a78e4b08de9379b3089","contributors":{"authors":[{"text":"Peters, Arin J. ajpeters@usgs.gov","contributorId":5862,"corporation":false,"usgs":true,"family":"Peters","given":"Arin","email":"ajpeters@usgs.gov","middleInitial":"J.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":539268,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Studley, Seth E. sstudley@usgs.gov","contributorId":5916,"corporation":false,"usgs":true,"family":"Studley","given":"Seth","email":"sstudley@usgs.gov","middleInitial":"E.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":539267,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70123438,"text":"70123438 - 2015 - Landscape-level terrestrial methane flux observed from a very tall tower","interactions":[],"lastModifiedDate":"2015-01-28T08:44:48","indexId":"70123438","displayToPublicDate":"2015-01-26T15:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":681,"text":"Agricultural and Forest Meteorology","active":true,"publicationSubtype":{"id":10}},"title":"Landscape-level terrestrial methane flux observed from a very tall tower","docAbstract":"Simulating the magnitude and variability of terrestrial methane sources and sinks poses a challenge to ecosystem models because the biophysical and biogeochemical processes that lead to methane emissions from terrestrial and freshwater ecosystems are, by their nature, episodic and spatially disjunct. As a consequence, model predictions of regional methane emissions based on field campaigns from short eddy covariance towers or static chambers have large uncertainties, because measurements focused on a particular known source of methane emission will be biased compared to regional estimates with regards to magnitude, spatial scale, or frequency of these emissions. Given the relatively large importance of predicting future terrestrial methane fluxes for constraining future atmospheric methane growth rates, a clear need exists to reduce spatiotemporal uncertainties. In 2010, an Ameriflux tower (US-PFa) near Park Falls, WI, USA, was instrumented with closed-path methane flux measurements at 122 m above ground in a mixed wetland–upland landscape representative of the Great Lakes region. Two years of flux observations revealed an average annual methane (CH4) efflux of 785 ± 75 mg C![\"single](\"http://cdn.els-cdn.com/sd/entities/sbnd\")
CH4 m−2 yr−1, compared to a mean CO2 sink of −80 g CCO2 m−2 yr−1, a ratio of 1% in magnitude on a mole basis. Interannual variability in methane flux was 30% of the mean flux and driven by suppression of methane emissions during dry conditions in late summer 2012. Though relatively small, the magnitude of the methane source from the very tall tower measurements was mostly within the range previously measured using static chambers at nearby wetlands, but larger than a simple scaling of those fluxes to the tower footprint. Seasonal patterns in methane fluxes were similar to those simulated in the Dynamic Land Ecosystem Model (DLEM), but magnitude depends on model parameterization and input data, especially regarding wetland extent. The model was unable to simulate short-term (sub-weekly) variability. Temperature was found to be a stronger driver of regional CH4flux than moisture availability or net ecosystem production at the daily to monthly scale. Taken together, these results emphasize the multi-timescale dependence of drivers of regional methane flux and the importance of long, continuous time series for their characterization.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.agrformet.2014.10.017","usgsCitation":"Desai, A.R., Xu, K., Tian, H., Weishampel, P., Thom, J., Baumann, D.D., Andrews, A.E., Cook, B.D., King, J.Y., and Kolka, R., 2015, Landscape-level terrestrial methane flux observed from a very tall tower: Agricultural and Forest Meteorology, v. 201, p. 61-75, https://doi.org/10.1016/j.agrformet.2014.10.017.","productDescription":"15 p.","startPage":"61","endPage":"75","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057381","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":297533,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","city":"Park Falls","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.5048828125,\n 46.800059446787316\n ],\n [\n -87.4951171875,\n 46.6795944656402\n ],\n [\n -87.451171875,\n 42.42345651793833\n ],\n [\n -92.6806640625,\n 42.779275360241904\n ],\n [\n -92.5048828125,\n 46.800059446787316\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"201","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2a8ee4b08de9379b30f2","contributors":{"authors":[{"text":"Desai, Ankur R. 0000-0002-5226-6041","orcid":"https://orcid.org/0000-0002-5226-6041","contributorId":20622,"corporation":false,"usgs":false,"family":"Desai","given":"Ankur","email":"","middleInitial":"R.","affiliations":[{"id":7122,"text":"University of Wisconsin","active":true,"usgs":false}],"preferred":false,"id":519367,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Xu, Ke","contributorId":115559,"corporation":false,"usgs":false,"family":"Xu","given":"Ke","email":"","affiliations":[{"id":7122,"text":"University of Wisconsin","active":true,"usgs":false}],"preferred":false,"id":519368,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tian, Hanqin","contributorId":117981,"corporation":false,"usgs":true,"family":"Tian","given":"Hanqin","email":"","affiliations":[],"preferred":false,"id":519372,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Weishampel, Peter","contributorId":116746,"corporation":false,"usgs":true,"family":"Weishampel","given":"Peter","email":"","affiliations":[],"preferred":false,"id":519370,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thom, Jonthan","contributorId":118322,"corporation":false,"usgs":true,"family":"Thom","given":"Jonthan","email":"","affiliations":[],"preferred":false,"id":519373,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Baumann, Daniel D. dbaumann@usgs.gov","contributorId":5950,"corporation":false,"usgs":true,"family":"Baumann","given":"Daniel","email":"dbaumann@usgs.gov","middleInitial":"D.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":false,"id":519366,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Andrews, Arlyn E.","contributorId":117698,"corporation":false,"usgs":false,"family":"Andrews","given":"Arlyn","email":"","middleInitial":"E.","affiliations":[{"id":12448,"text":"U.S. National Oceanic and Atmospheric Administration","active":true,"usgs":false}],"preferred":false,"id":519371,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Cook, Bruce D.","contributorId":118323,"corporation":false,"usgs":false,"family":"Cook","given":"Bruce","email":"","middleInitial":"D.","affiliations":[{"id":7049,"text":"NASA Goddard Space Flight Center","active":true,"usgs":false}],"preferred":false,"id":519374,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"King, Jennifer Y.","contributorId":120697,"corporation":false,"usgs":false,"family":"King","given":"Jennifer","email":"","middleInitial":"Y.","affiliations":[{"id":6710,"text":"University of California, Santa Barbara, CA","active":true,"usgs":false}],"preferred":false,"id":519375,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Kolka, Randall","contributorId":115924,"corporation":false,"usgs":false,"family":"Kolka","given":"Randall","affiliations":[],"preferred":false,"id":519369,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70139233,"text":"sir20145186 - 2015 - A model for evaluating stream temperature response to climate change in Wisconsin","interactions":[],"lastModifiedDate":"2015-01-26T15:19:51","indexId":"sir20145186","displayToPublicDate":"2015-01-26T15:00:00","publicationYear":"2015","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":"2014-5186","title":"A model for evaluating stream temperature response to climate change in Wisconsin","docAbstract":"Expected climatic changes in air temperature and precipitation patterns across the State of Wisconsin may alter future stream temperature and flow regimes. As a consequence of flow and temperature changes, the composition and distribution of fish species assemblages are expected to change. In an effort to gain a better understanding of how climatic changes may affect stream temperature, an approach was developed to predict and project daily summertime stream temperature under current and future climate conditions for 94,341 stream kilometers across Wisconsin. The approach uses a combination of static landscape characteristics and dynamic time-series climatic variables as input for an Artificial Neural Network (ANN) Model integrated with a Soil-Water-Balance (SWB) Model. Future climate scenarios are based on output from downscaled General Circulation Models (GCMs). The SWB model provided a means to estimate the temporal variability in groundwater recharge and provided a mechanism to evaluate the effect of changing air temperature and precipitation on groundwater recharge and soil moisture. The Integrated Soil-Water-Balance and Artificial Neural Network version 1 (SWB-ANNv1) Model was used to simulate daily summertime stream temperature under current (1990–2008) climate and explained 76 percent of the variation in the daily mean based on validation at 67 independent sites. Results were summarized as July mean water temperature, and individual stream segments were classified by thermal class (cold, cold transition, warm transition, and warm) for comparison of current (1990–2008) with future climate conditions.
\nIntegrating the SWB Model with the ANN Model provided a mechanism by which downscaled global or regional climate model results could be used to estimate the potential effects of climate change on future stream temperature on a daily time step. To address future climate scenarios, statistically downscaled air temperature and precipitation projections from 10 GCMs and 2 time periods were used with the SWB-ANNv1 Model to project future stream temperature. Projections of future stream temperatures at mid- (2046–65) and late- (2081–2100) 21st century showed the July mean water temperature increasing for all stream segments with about 80 percent of stream kilometers increasing by 1 to 2 degrees Celsius (°C) by mid-century and about 99 percent increasing by 1 to 3 °C by late-century. Projected changes in stream temperatures also affected changes in thermal classes with a loss in the total amount of cold-water, cold-transition, and warm-transition thermal habitat and a gain in warm-water and very warm thermal habitat for both mid- and late-21st century time periods. The greatest losses occurred for cold-water streams and the greatest gains for warm-water streams, with a contraction of cold-water streams in the Driftless Area of western and southern Wisconsin and an expansion of warm-water streams across northern Wisconsin. Results of this study suggest that such changes will affect the composition of fish assemblages, with a loss of suitable habitat for cold-water fishes and gain in suitable habitat for warm-water fishes. In the end, these projected changes in thermal habitat attributable to climate may result in a net loss of fisheries, because many warm-water species may be unable to colonize habitats formerly occupied by cold-water species because of other habitat limitations (e.g., stream size, gradient). Although projected stream temperatures may vary greatly, depending on the emissions scenario and models used, the results presented in this report represent one possibility. The relative change in stream temperature can provide useful information for planning for potential climate impacts to aquatic ecosystems. Model results can be used to help identify vulnerabilities of streams to climate change, guide stream surveys and thermal classifications, prioritize the allocation of scarce financial resources, identify approaches to climate adaptation to best protect and enhance resiliency in stream thermal habitat, and provide information to make quantitative assessments of statewide stream resources.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145186","collaboration":"Prepared in cooperation with the Wisconsin Department of Natural Resources","usgsCitation":"Stewart, J.S., Westenbroek, S.M., Mitro, M.G., Lyons, J.D., Kammel, L.E., and Buchwald, C.A., 2015, A model for evaluating stream temperature response to climate change in Wisconsin: U.S. Geological Survey Scientific Investigations Report 2014-5186, Report: ix, 64 p.; Appendices 1-2, https://doi.org/10.3133/sir20145186.","productDescription":"Report: ix, 64 p.; Appendices 1-2","numberOfPages":"78","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-057452","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":297551,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145186.jpg"},{"id":297547,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5186/"},{"id":297548,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5186/pdf/sir2014-5186.pdf","text":"Report","size":"208 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":297549,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5186/appendix/appendix1_stream_temp_sites.xlsx","text":"Appendix 1","size":"69 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"Appendix 1","linkHelpText":"Stream Identification Information"},{"id":297550,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5186/appendix/appendix2_climate_stations.xlsx","text":"Appendix 2","size":"20 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"Appendix 2","linkHelpText":"Climate Station Information"}],"country":"United States","state":"Wisconsin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.878173828125,\n 42.47209690919285\n ],\n [\n -93.878173828125,\n 47.10752278534248\n ],\n [\n -86.6162109375,\n 47.10752278534248\n ],\n [\n -86.6162109375,\n 42.47209690919285\n ],\n [\n -93.878173828125,\n 42.47209690919285\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2a4ce4b08de9379b2fca","contributors":{"authors":[{"text":"Stewart, Jana S. 0000-0002-8121-1373 jsstewar@usgs.gov","orcid":"https://orcid.org/0000-0002-8121-1373","contributorId":539,"corporation":false,"usgs":true,"family":"Stewart","given":"Jana","email":"jsstewar@usgs.gov","middleInitial":"S.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":539286,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Westenbroek, Stephen M. 0000-0002-6284-8643 smwesten@usgs.gov","orcid":"https://orcid.org/0000-0002-6284-8643","contributorId":2210,"corporation":false,"usgs":true,"family":"Westenbroek","given":"Stephen","email":"smwesten@usgs.gov","middleInitial":"M.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":539287,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mitro, Matthew G.","contributorId":25090,"corporation":false,"usgs":true,"family":"Mitro","given":"Matthew","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":539288,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lyons, John D.","contributorId":55364,"corporation":false,"usgs":false,"family":"Lyons","given":"John","email":"","middleInitial":"D.","affiliations":[{"id":6913,"text":"Wisconsin Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":539289,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kammel, Leah E. lkammel@usgs.gov","contributorId":4778,"corporation":false,"usgs":true,"family":"Kammel","given":"Leah","email":"lkammel@usgs.gov","middleInitial":"E.","affiliations":[],"preferred":true,"id":539290,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Buchwald, Cheryl A. 0000-0001-8968-5023 cabuchwa@usgs.gov","orcid":"https://orcid.org/0000-0001-8968-5023","contributorId":1943,"corporation":false,"usgs":true,"family":"Buchwald","given":"Cheryl","email":"cabuchwa@usgs.gov","middleInitial":"A.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":539291,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
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