Wildfire area is predicted to increase with global warming. Empirical statistical models and process-based simulations agree almost universally. The key relationship for this unanimity, observed at multiple spatial and temporal scales, is between drought and fire. Predictive models often focus on ecosystems in which this relationship appears to be particularly strong, such as mesic and arid forests and shrublands with substantial biomass such as chaparral. We examine the drought–fire relationship, specifically the correlations between water-balance deficit and annual area burned, across the full gradient of deficit in the western USA, from temperate rainforest to desert. In the middle of this gradient, conditional on vegetation (fuels), correlations are strong, but outside this range the equivalence hotter and drier equals more fire either breaks down or is contingent on other factors such as previous-year climate. This suggests that the regional drought–fire dynamic will not be stationary in future climate, nor will other more complex contingencies associated with the variation in fire extent. Predictions of future wildfire area therefore need to consider not only vegetation changes, as some dynamic vegetation models now do, but also potential changes in the drought–fire dynamic that will ensue in a warming climate.
","language":"English","publisher":"Ecological Society of America","publisherLocation":"Washington, D.C.","doi":"10.1002/eap.1420","usgsCitation":"McKenzie, D., and Littell, J.S., 2017, Climate change and the eco-hydrology of fire: Will area burned increase in a warming western USA?: Ecological Applications, v. 27, no. 1, p. 26-36, https://doi.org/10.1002/eap.1420.","productDescription":"11 p.","startPage":"26","endPage":"36","ipdsId":"IP-073768","costCenters":[{"id":107,"text":"Alaska Climate Science Center","active":true,"usgs":true}],"links":[{"id":335295,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Western United 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\"}}]}","volume":"27","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-12-21","publicationStatus":"PW","scienceBaseUri":"58a2d3abe4b0c825128699e9","contributors":{"authors":[{"text":"McKenzie, Donald","contributorId":181509,"corporation":false,"usgs":false,"family":"McKenzie","given":"Donald","affiliations":[],"preferred":false,"id":668427,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Littell, Jeremy S. 0000-0002-5302-8280 jlittell@usgs.gov","orcid":"https://orcid.org/0000-0002-5302-8280","contributorId":4428,"corporation":false,"usgs":true,"family":"Littell","given":"Jeremy","email":"jlittell@usgs.gov","middleInitial":"S.","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":107,"text":"Alaska Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":668426,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70180919,"text":"tm6B35 - 2017 - Water, Energy, and Biogeochemical Model (WEBMOD), user’s manual, version 1","interactions":[],"lastModifiedDate":"2017-02-09T10:40:22","indexId":"tm6B35","displayToPublicDate":"2017-02-08T00:18:30","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"6-B35","title":"Water, Energy, and Biogeochemical Model (WEBMOD), user’s manual, version 1","docAbstract":"The Water, Energy, and Biogeochemical Model (WEBMOD) uses the framework of the U.S. Geological Survey (USGS) Modular Modeling System to simulate fluxes of water and solutes through watersheds. WEBMOD divides watersheds into model response units (MRU) where fluxes and reactions are simulated for the following eight hillslope reservoir types: canopy; snowpack; ponding on impervious surfaces; O-horizon; two reservoirs in the unsaturated zone, which represent preferential flow and matrix flow; and two reservoirs in the saturated zone, which also represent preferential flow and matrix flow. The reservoir representing ponding on impervious surfaces, currently not functional (2016), will be implemented once the model is applied to urban areas. MRUs discharge to one or more stream reservoirs that flow to the outlet of the watershed. Hydrologic fluxes in the watershed are simulated by modules derived from the USGS Precipitation Runoff Modeling System; the National Weather Service Hydro-17 snow model; and a topography-driven hydrologic model (TOPMODEL). Modifications to the standard TOPMODEL include the addition of heterogeneous vertical infiltration rates; irrigation; lateral and vertical preferential flows through the unsaturated zone; pipe flow draining the saturated zone; gains and losses to regional aquifer systems; and the option to simulate baseflow discharge by using an exponential, parabolic, or linear decrease in transmissivity. PHREEQC, an aqueous geochemical model, is incorporated to simulate chemical reactions as waters evaporate, mix, and react within the various reservoirs of the model. The reactions that can be specified for a reservoir include equilibrium reactions among water; minerals; surfaces; exchangers; and kinetic reactions such as kinetic mineral dissolution or precipitation, biologically mediated reactions, and radioactive decay. WEBMOD also simulates variations in the concentrations of the stable isotopes deuterium and oxygen-18 as a result of varying inputs, mixing, and evaporation. This manual describes the WEBMOD input and output files, along with the algorithms and procedures used to simulate the hydrology and water quality in a watershed. Examples are presented that demonstrate hydrologic processes, weathering reactions, and isotopic evolution in an alpine watershed and the effect of irrigation on water flows and salinity in an intensively farmed agricultural area.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Section B: Surface Water in Book 6: Modeling Techniques","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm6B35","issn":"2328-7055","usgsCitation":"Webb, R.M.T., and Parkhurst, D.L., 2017, Water, Energy, and Biogeochemical Model (WEBMOD), user’s manual, version 1: U.S. Geological Survey Techniques and Methods, book 6, chap. B35, 171 p., https://doi.org/10.3133/tm6B35.","productDescription":"xiv, 171 p.","numberOfPages":"190","onlineOnly":"Y","costCenters":[{"id":144,"text":"Branch of Regional Research","active":false,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":438440,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7P26W9K","text":"USGS data release","linkHelpText":"Water, Energy, and Biogeochemical Model"},{"id":334918,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/06/b35/tm6b35.pdf","text":"Report","size":"8.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"T&M 6-B35"},{"id":334917,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/06/b35/coverthb.jpg"},{"id":334980,"rank":3,"type":{"id":4,"text":"Application Site"},"url":"https://doi.org/10.5066/F7P26W9K","text":"Water, Energy, and Biogeochemical Model (WEBMOD)"}],"publicComments":"This report is Chapter 35 of Section B: Surface Water in Book 6 Modeling Techniques","contact":"Chief, National Research Program, Central Branch
U.S. Geological Survey
Box 25585, Mail Stop 418
Denver, CO 80225-0585
A cross-site analysis was conducted on seven diverse, forested watersheds in the northeastern United States to evaluate hydrological responses (evapotranspiration, soil moisture, seasonal and annual streamflow, and water stress) to projections of future climate. We used output from four atmosphere–ocean general circulation models (AOGCMs; CCSM4, HadGEM2-CC, MIROC5, and MRI-CGCM3) included in Phase 5 of the Coupled Model Intercomparison Project, coupled with two Representative Concentration Pathways (RCP 8.5 and 4.5). The coarse resolution AOGCMs outputs were statistically downscaled using an asynchronous regional regression model to provide finer resolution future climate projections as inputs to the deterministic dynamic ecosystem model PnET-BGC. Simulation results indicated that projected warmer temperatures and longer growing seasons in the northeastern United States are anticipated to increase evapotranspiration across all sites, although invoking CO2 effects on vegetation (growth enhancement and increases in water use efficiency (WUE)) diminish this response. The model showed enhanced evapotranspiration resulted in drier growing season conditions across all sites and all scenarios in the future. Spruce-fir conifer forests have a lower optimum temperature for photosynthesis, making them more susceptible to temperature stress than more tolerant hardwood species, potentially giving hardwoods a competitive advantage in the future. However, some hardwood forests are projected to experience seasonal water stress, despite anticipated increases in precipitation, due to the higher temperatures, earlier loss of snow packs, longer growing seasons, and associated water deficits. Considering future CO2effects on WUE in the model alleviated water stress across all sites. Modeled streamflow responses were highly variable, with some sites showing significant increases in annual water yield, while others showed decreases. This variability in streamflow responses poses a challenge to water resource management in the northeastern United States. Our analyses suggest that dominant vegetation type and soil type are important attributes in determining future hydrological responses to climate change.
","language":"English","publisher":"Wiley","doi":"10.1111/gcb.13444","usgsCitation":"Pourmokhtarian, A., Driscoll, C.T., Campbell, J.L., Hayhoe, K., Stoner, A., Adams, M.B., Burns, D., Fernandez, I., Mitchell, M.J., and Shanley, J.B., 2017, Modeled ecohydrological responses to climate change at seven small watersheds in the northeastern United States: Global Change Biology, v. 23, no. 2, p. 840-856, https://doi.org/10.1111/gcb.13444.","productDescription":"17 p.","startPage":"840","endPage":"856","ipdsId":"IP-077080","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":352254,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"23","issue":"2","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2016-08-25","publicationStatus":"PW","scienceBaseUri":"5afee8d3e4b0da30c1bfc4ba","contributors":{"authors":[{"text":"Pourmokhtarian, Afshin","contributorId":202944,"corporation":false,"usgs":false,"family":"Pourmokhtarian","given":"Afshin","email":"","affiliations":[{"id":5082,"text":"Syracuse University","active":true,"usgs":false}],"preferred":false,"id":730243,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Driscoll, Charles T.","contributorId":167460,"corporation":false,"usgs":false,"family":"Driscoll","given":"Charles","email":"","middleInitial":"T.","affiliations":[{"id":5082,"text":"Syracuse University","active":true,"usgs":false}],"preferred":false,"id":730244,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Campbell, John L.","contributorId":178410,"corporation":false,"usgs":false,"family":"Campbell","given":"John","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":730245,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hayhoe, Katharine","contributorId":149192,"corporation":false,"usgs":false,"family":"Hayhoe","given":"Katharine","email":"","affiliations":[{"id":17667,"text":"Climate Science Center, Texas Tech University, Lubbock, Texas, United States","active":true,"usgs":false}],"preferred":false,"id":730246,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stoner, Anne M. K.","contributorId":202945,"corporation":false,"usgs":false,"family":"Stoner","given":"Anne M. K.","affiliations":[{"id":36331,"text":"Texas Tech University","active":true,"usgs":false}],"preferred":false,"id":730247,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Adams, Mary Beth","contributorId":150354,"corporation":false,"usgs":false,"family":"Adams","given":"Mary","email":"","middleInitial":"Beth","affiliations":[],"preferred":false,"id":730248,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Burns, Douglas A. 0000-0001-6516-2869","orcid":"https://orcid.org/0000-0001-6516-2869","contributorId":202943,"corporation":false,"usgs":true,"family":"Burns","given":"Douglas A.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":730242,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Fernandez, Ivan","contributorId":178215,"corporation":false,"usgs":false,"family":"Fernandez","given":"Ivan","affiliations":[],"preferred":false,"id":730249,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Mitchell, Myron J.","contributorId":73734,"corporation":false,"usgs":true,"family":"Mitchell","given":"Myron","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":730250,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Shanley, James B. 0000-0002-4234-3437 jshanley@usgs.gov","orcid":"https://orcid.org/0000-0002-4234-3437","contributorId":1953,"corporation":false,"usgs":true,"family":"Shanley","given":"James","email":"jshanley@usgs.gov","middleInitial":"B.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":730241,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70193686,"text":"70193686 - 2017 - Generation of 3-D hydrostratigraphic zones from dense airborne electromagnetic data to assess groundwater model prediction error","interactions":[],"lastModifiedDate":"2017-11-02T16:32:12","indexId":"70193686","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","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":"Generation of 3-D hydrostratigraphic zones from dense airborne electromagnetic data to assess groundwater model prediction error","docAbstract":"We present a new methodology to combine spatially dense high-resolution airborne electromagnetic (AEM) data and sparse borehole information to construct multiple plausible geological structures using a stochastic approach. The method developed allows for quantification of the performance of groundwater models built from different geological realizations of structure. Multiple structural realizations are generated using geostatistical Monte Carlo simulations that treat sparse borehole lithological observations as hard data and dense geophysically derived structural probabilities as soft data. Each structural model is used to define 3-D hydrostratigraphical zones of a groundwater model, and the hydraulic parameter values of the zones are estimated by using nonlinear regression to fit hydrological data (hydraulic head and river discharge measurements). Use of the methodology is demonstrated for a synthetic domain having structures of categorical deposits consisting of sand, silt, or clay. It is shown that using dense AEM data with the methodology can significantly improve the estimated accuracy of the sediment distribution as compared to when borehole data are used alone. It is also shown that this use of AEM data can improve the predictive capability of a calibrated groundwater model that uses the geological structures as zones. However, such structural models will always contain errors because even with dense AEM data it is not possible to perfectly resolve the structures of a groundwater system. It is shown that when using such erroneous structures in a groundwater model, they can lead to biased parameter estimates and biased model predictions, therefore impairing the model's predictive capability.
","language":"English","publisher":"AGU","doi":"10.1002/2016WR019141","usgsCitation":"Christensen, N.K., Minsley, B.J., and Christensen, S., 2017, Generation of 3-D hydrostratigraphic zones from dense airborne electromagnetic data to assess groundwater model prediction error: Water Resources Research, v. 53, no. 2, p. 1019-1038, https://doi.org/10.1002/2016WR019141.","productDescription":"20 p.","startPage":"1019","endPage":"1038","ipdsId":"IP-081403","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":488731,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://pure.au.dk/portal/en/publications/dcdb9b5e-bf3c-4826-83aa-0fb5cd606845","text":"External Repository"},{"id":348146,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"53","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59fc2ea5e4b0531197b27f85","contributors":{"authors":[{"text":"Christensen, Nikolaj K","contributorId":199736,"corporation":false,"usgs":false,"family":"Christensen","given":"Nikolaj","email":"","middleInitial":"K","affiliations":[{"id":13419,"text":"Aarhus University, Denmark","active":true,"usgs":false}],"preferred":false,"id":719889,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Minsley, Burke J. 0000-0003-1689-1306 bminsley@usgs.gov","orcid":"https://orcid.org/0000-0003-1689-1306","contributorId":697,"corporation":false,"usgs":true,"family":"Minsley","given":"Burke","email":"bminsley@usgs.gov","middleInitial":"J.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":719888,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Christensen, Steen","contributorId":199737,"corporation":false,"usgs":false,"family":"Christensen","given":"Steen","email":"","affiliations":[{"id":13419,"text":"Aarhus University, Denmark","active":true,"usgs":false}],"preferred":false,"id":719890,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70179238,"text":"sir20165179 - 2017 - Flood-inundation maps for the St. Joseph River at Elkhart, Indiana","interactions":[],"lastModifiedDate":"2017-02-02T10:11:06","indexId":"sir20165179","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-5179","title":"Flood-inundation maps for the St. Joseph River at Elkhart, Indiana","docAbstract":"Digital flood-inundation maps for a 6.6-mile reach of the St. Joseph River at Elkhart, Indiana, were created by the U.S. Geological Survey (USGS) in cooperation with the Indiana Office of Community and Rural Affairs. The flood-inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at https://water.usgs.gov/osw/flood_inundation/, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage 04101000, St. Joseph River at Elkhart, Ind. Real-time stages at this streamgage may be obtained on the Internet from the USGS National Water Information System at https://waterdata.usgs.gov/nwis or the National Weather Service (NWS) Advanced Hydrologic Prediction Service at http:/water.weather.gov/ahps/, which also forecasts flood hydrographs at this site (NWS site EKMI3).
Flood profiles were computed for the stream reach by means of a one-dimensional, step-backwater hydraulic modeling software developed by the U.S. Army Corps of Engineers. The hydraulic model was calibrated using the current stage-discharge rating at the USGS streamgage 04101000, St. Joseph River at Elkhart, Ind., and the documented high-water marks from the flood of March 1982. The hydraulic model was then used to compute six water-surface profiles for flood stages at 1-foot (ft) intervals referenced to the streamgage datum ranging from 23.0 ft (the NWS “action stage”) to 28.0 ft, which is the highest stage interval of the current USGS stage-discharge rating curve and 1 ft higher than the NWS “major flood stage.” The simulated water-surface profiles were then combined with a Geographic Information System digital elevation model (derived from light detection and ranging [lidar] data having a 0.49-ft root mean squared error and 4.9-ft horizontal resolution, resampled to a 10-ft grid) to delineate the area flooded at each stage.
The availability of these maps, along with Internet information regarding current stage from the USGS streamgage and forecasted high-flow stages from the NWS, will provide emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures, as well as for post-flood recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165179","collaboration":"Prepared in cooperation with the Indiana Office of Community and Rural Affairs","usgsCitation":"Martin, Z.W., 2017, Flood-inundation maps for the St. Joseph River at Elkhart, Indiana: U.S. Geological Survey Scientific Investigations Report 2016–5179, 10 p., https://doi.org/10.3133/sir20165179.","productDescription":"Report: vi, 10 p.; Data Release","numberOfPages":"20","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-079008","costCenters":[{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true}],"links":[{"id":333769,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7QZ2836","text":"USGS Data Release","description":"USGS Data Release","linkHelpText":"St. Joseph River at Elkhart, Indiana, Flood-Inundation HEC-RAS Model"},{"id":333734,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5179/coverthb.jpg"},{"id":333735,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5179/sir20165179.pdf","text":"Report","size":"1.35 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016–5179"}],"country":"United States","state":"Indiana","otherGeospatial":"St. Joseph River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -86.04475021362305,\n 41.67355293097283\n ],\n [\n -86.04475021362305,\n 41.69380876113261\n ],\n [\n -85.97402572631836,\n 41.69380876113261\n ],\n [\n -85.97402572631836,\n 41.67355293097283\n ],\n [\n -86.04475021362305,\n 41.67355293097283\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Indiana Water Science Center
U.S. Geological Survey
5957 Lakeside Boulevard,
Indianapolis, IN 46278–1996
The McMurdo Dry Valleys, Antarctica, are a polar desert ecosystem. The hydrologic system of the dry valleys is linked to climate with ephemeral streams that flow from glacial melt during the austral summer. Past climate variations have strongly influenced the closed-basin, chemically stratified lakes on the valley floor. Results of previous work point to important roles for both in-stream processes (e.g., mineral weathering, precipitation and dissolution of salts) and in-lake processes (e.g., mixing with paleo-seawater and calcite precipitation) in determining the geochemistry of these lakes. These processes have a significant influence on calcium (Ca) biogeochemistry in this aquatic ecosystem, and thus variations in Ca stable isotope compositions of the waters can aid in validating the importance of these processes. We have analyzed the Ca stable isotope compositions of streams and lakes in the McMurdo Dry Valleys. The results validate the important roles of weathering of aluminosilicate minerals and/or CaCO3 in the hyporheic zone of the streams, and mixing of lake surface water with paleo-seawater and precipitation of Ca-salts during cryo-concentration events to form the deep lake waters. The lakes in the McMurdo Dry Valleys evolved following different geochemical pathways, evidenced by their unique, nonsystematic Ca isotope signatures.
","language":"English","publisher":"AGU Publications","doi":"10.1002/2016GL071169","usgsCitation":"Lyons, W.B., Bullen, T.D., and Welch, K.A., 2017, Ca isotopic geochemistry of an Antarctic aquatic system: Geophysical Research Letters, v. 44, no. 2, p. 882-891, https://doi.org/10.1002/2016GL071169.","productDescription":"10 p.","startPage":"882","endPage":"891","ipdsId":"IP-082104","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":470087,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2016gl071169","text":"Publisher Index Page"},{"id":348277,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Antarctica, McMurdo Dry Valleys","volume":"44","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-01-16","publicationStatus":"PW","scienceBaseUri":"5a07e93ee4b09af898c8cc09","contributors":{"authors":[{"text":"Lyons, W. Berry","contributorId":193456,"corporation":false,"usgs":false,"family":"Lyons","given":"W.","email":"","middleInitial":"Berry","affiliations":[],"preferred":false,"id":714524,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bullen, Thomas D. 0000-0003-2281-1691 tdbullen@usgs.gov","orcid":"https://orcid.org/0000-0003-2281-1691","contributorId":1969,"corporation":false,"usgs":true,"family":"Bullen","given":"Thomas","email":"tdbullen@usgs.gov","middleInitial":"D.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":714523,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Welch, Kathleen A.","contributorId":197891,"corporation":false,"usgs":false,"family":"Welch","given":"Kathleen","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":714525,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70189348,"text":"70189348 - 2017 - Variability of runoff-based drought conditions in the conterminous United States","interactions":[],"lastModifiedDate":"2017-08-29T09:35:36","indexId":"70189348","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2032,"text":"International Journal of Climatology","active":true,"publicationSubtype":{"id":10}},"title":"Variability of runoff-based drought conditions in the conterminous United States","docAbstract":"In this study, a monthly water-balance model is used to simulate monthly runoff for 2109 hydrologic units (HUs) in the conterminous United States (CONUS) for water-years 1901 through 2014. The monthly runoff time series for each HU were smoothed with a 3-month moving average, and then the 3-month moving-average runoff values were converted to percentiles. For each HU, a drought was considered to occur when the HU runoff percentile dropped to the 20th percentile or lower. A drought was considered to end when the HU runoff percentile exceeded the 20th percentile. After identifying drought events for each HU, the frequency and length of drought events were examined. Results indicated that (1) the longest mean drought lengths occur in the eastern CONUS and parts of the Rocky Mountain region and the northwestern CONUS, (2) the frequency of drought is highest in the southwestern and central CONUS, and lowest in the eastern CONUS, the Rocky Mountain region, and the northwestern CONUS, (3) droughts have occurred during all months of the year and there does not appear to be a seasonal pattern to drought occurrence, (4) the variability of precipitation appears to have been the principal climatic factor determining drought, and (5) for most of the CONUS, drought frequency appears to have decreased during the 1901 through 2014 period.
","language":"English","publisher":"Royal Meteorological Society","doi":"10.1002/joc.4756","usgsCitation":"McCabe, G., Wolock, D.M., and Austin, S.H., 2017, Variability of runoff-based drought conditions in the conterminous United States: International Journal of Climatology, v. 37, no. 2, p. 1014-1021, https://doi.org/10.1002/joc.4756.","productDescription":"8 p.","startPage":"1014","endPage":"1021","ipdsId":"IP-073812","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":343608,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}\n","volume":"37","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-06","publicationStatus":"PW","scienceBaseUri":"5965b227e4b0d1f9f05b37dd","contributors":{"authors":[{"text":"McCabe, Gregory J. 0000-0002-9258-2997 gmccabe@usgs.gov","orcid":"https://orcid.org/0000-0002-9258-2997","contributorId":167116,"corporation":false,"usgs":true,"family":"McCabe","given":"Gregory J.","email":"gmccabe@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":false,"id":704314,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wolock, David M. 0000-0002-6209-938X dwolock@usgs.gov","orcid":"https://orcid.org/0000-0002-6209-938X","contributorId":540,"corporation":false,"usgs":true,"family":"Wolock","given":"David","email":"dwolock@usgs.gov","middleInitial":"M.","affiliations":[{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":704315,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Austin, Samuel H. 0000-0001-5626-023X saustin@usgs.gov","orcid":"https://orcid.org/0000-0001-5626-023X","contributorId":153,"corporation":false,"usgs":true,"family":"Austin","given":"Samuel","email":"saustin@usgs.gov","middleInitial":"H.","affiliations":[{"id":37280,"text":"Virginia and West Virginia Water Science Center ","active":true,"usgs":true}],"preferred":true,"id":704316,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70186420,"text":"70186420 - 2017 - Expanding the role of reactive transport models in critical zone processes","interactions":[],"lastModifiedDate":"2017-04-05T10:00:40","indexId":"70186420","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1431,"text":"Earth-Science Reviews","active":true,"publicationSubtype":{"id":10}},"title":"Expanding the role of reactive transport models in critical zone processes","docAbstract":"Models test our understanding of processes and can reach beyond the spatial and temporal scales of measurements. Multi-component Reactive Transport Models (RTMs), initially developed more than three decades ago, have been used extensively to explore the interactions of geothermal, hydrologic, geochemical, and geobiological processes in subsurface systems. Driven by extensive data sets now available from intensive measurement efforts, there is a pressing need to couple RTMs with other community models to explore non-linear interactions among the atmosphere, hydrosphere, biosphere, and geosphere. Here we briefly review the history of RTM development, summarize the current state of RTM approaches, and identify new research directions, opportunities, and infrastructure needs to broaden the use of RTMs. In particular, we envision the expanded use of RTMs in advancing process understanding in the Critical Zone, the veneer of the Earth that extends from the top of vegetation to the bottom of groundwater. We argue that, although parsimonious models are essential at larger scales, process-based models offer tools to explore the highly nonlinear coupling that characterizes natural systems. We present seven testable hypotheses that emphasize the unique capabilities of process-based RTMs for (1) elucidating chemical weathering and its physical and biogeochemical drivers; (2) understanding the interactions among roots, micro-organisms, carbon, water, and minerals in the rhizosphere; (3) assessing the effects of heterogeneity across spatial and temporal scales; and (4) integrating the vast quantity of novel data, including “omics” data (genomics, transcriptomics, proteomics, metabolomics), elemental concentration and speciation data, and isotope data into our understanding of complex earth surface systems. With strong support from data-driven sciences, we are now in an exciting era where integration of RTM framework into other community models will facilitate process understanding across disciplines and across scales.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.earscirev.2016.09.001","usgsCitation":"Li, L., Maher, K., Navarre-Sitchler, A., Druhan, J., Meile, C., Lawrence, C., Moore, J., Perdrial, J., Sullivan, P., Thompson, A., Jin, L., Bolton, E.W., Brantley, S.L., Dietrich, W., Mayer, K.U., Steefel, C., Valocchi, A.J., Zachara, J.M., Kocar, B.D., McIntosh, J., Tutolo, B.M., Kumar, M., Sonnenthal, E., Bao, C., and Beisman, J., 2017, Expanding the role of reactive transport models in critical zone processes: Earth-Science Reviews, v. 165, p. 280-301, https://doi.org/10.1016/j.earscirev.2016.09.001.","productDescription":"22 p.","startPage":"280","endPage":"301","ipdsId":"IP-070272","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":461771,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://escholarship.org/uc/item/81f302jz","text":"Publisher Index Page"},{"id":339191,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"165","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58e60272e4b09da6799ac681","contributors":{"authors":[{"text":"Li, Li","contributorId":190439,"corporation":false,"usgs":false,"family":"Li","given":"Li","affiliations":[],"preferred":false,"id":688432,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Maher, Kate","contributorId":190440,"corporation":false,"usgs":false,"family":"Maher","given":"Kate","email":"","affiliations":[],"preferred":false,"id":688433,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Navarre-Sitchler, Alexis","contributorId":190441,"corporation":false,"usgs":false,"family":"Navarre-Sitchler","given":"Alexis","email":"","affiliations":[],"preferred":false,"id":688434,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Druhan, Jennifer","contributorId":190442,"corporation":false,"usgs":false,"family":"Druhan","given":"Jennifer","affiliations":[],"preferred":false,"id":688435,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Meile, Christof","contributorId":190443,"corporation":false,"usgs":false,"family":"Meile","given":"Christof","email":"","affiliations":[],"preferred":false,"id":688436,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lawrence, Corey 0000-0002-2179-2436 clawrence@usgs.gov","orcid":"https://orcid.org/0000-0002-2179-2436","contributorId":190438,"corporation":false,"usgs":true,"family":"Lawrence","given":"Corey","email":"clawrence@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":688431,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Moore, Joel","contributorId":190444,"corporation":false,"usgs":false,"family":"Moore","given":"Joel","email":"","affiliations":[],"preferred":false,"id":688437,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Perdrial, Julia","contributorId":190445,"corporation":false,"usgs":false,"family":"Perdrial","given":"Julia","affiliations":[],"preferred":false,"id":688438,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Sullivan, Pamela","contributorId":190446,"corporation":false,"usgs":false,"family":"Sullivan","given":"Pamela","affiliations":[],"preferred":false,"id":688439,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Thompson, Aaron","contributorId":190447,"corporation":false,"usgs":false,"family":"Thompson","given":"Aaron","affiliations":[],"preferred":false,"id":688440,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Jin, Lixin","contributorId":190448,"corporation":false,"usgs":false,"family":"Jin","given":"Lixin","email":"","affiliations":[],"preferred":false,"id":688441,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Bolton, Edward W.","contributorId":190449,"corporation":false,"usgs":false,"family":"Bolton","given":"Edward","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":688442,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Brantley, Susan L. 0000-0003-4320-2342","orcid":"https://orcid.org/0000-0003-4320-2342","contributorId":184201,"corporation":false,"usgs":false,"family":"Brantley","given":"Susan","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":688443,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Dietrich, William E.","contributorId":115128,"corporation":false,"usgs":true,"family":"Dietrich","given":"William E.","affiliations":[],"preferred":false,"id":688444,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Mayer, K. 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Concentrations, loadings and yields of E. coli and microbial source tracking (MST) markers, were characterized during base flow and storm events in five subbasins within Independence, as well as sources entering and leaving the city through the river. The E. coli water quality threshold was exceeded in 29% of base-flow and 89% of storm-event samples. The total contribution of E. coli and MST markers from tributaries within Independence to the Little Blue River, regardless of streamflow, did not significantly increase the median concentrations leaving the city. Daily loads and yields of E. coli and MST markers were used to rank the subbasins according to their contribution of each constituent to the river. The ranking methodology used in this study may prove useful in prioritizing remediation in the different subbasins.
","language":"English","publisher":"Water Environment Federation","doi":"10.2175/106143016X14798353399412","collaboration":"City of Independence, Missouri Water Pollution Control Station","usgsCitation":"Bushon, R.N., Brady, A.M., Christensen, E.D., and Stelzer, E.A., 2017, Multi-year microbial source tracking study characterizing fecal contamination in an urban watershed: Water Environment Research, v. 89, no. 2, p. 127-143, https://doi.org/10.2175/106143016X14798353399412.","productDescription":"17 p.","startPage":"127","endPage":"143","ipdsId":"IP-069132","costCenters":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"links":[{"id":342249,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Missouri","city":"Independence","otherGeospatial":"Little Blue River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": 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Range","interactions":[],"lastModifiedDate":"2017-02-20T11:34:12","indexId":"70182184","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1007,"text":"Biogeochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Critical zone properties control the fate of nitrogen during experimental rainfall in montane forests of the Colorado Front Range","docAbstract":"Several decades of research in alpine ecosystems have demonstrated links among the critical zone, hydrologic response, and the fate of elevated atmospheric nitrogen (N) deposition. Less research has occurred in mid-elevation forests, which may be important for retaining atmospheric N deposition. To explore the fate of N in the montane zone, we conducted plot-scale experimental rainfall events across a north–south transect within a catchment of the Boulder Creek Critical Zone Observatory. Rainfall events mimicked relatively common storms (20–50% annual exceedance probability) and were labeled with 15N-nitrate (
This report describes an R package called smwrGraphs, which consists of a collection of graphing functions for hydrologic data within R, a programming language and software environment for statistical computing. The functions in the package have been developed by the U.S. Geological Survey to create high-quality graphs for publication or presentation of hydrologic data that meet U.S. Geological Survey graphics guidelines.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161188","usgsCitation":"Lorenz, D.L., and Diekoff, A.L., 2017, smwrGraphs—An R package for graphing hydrologic data, version 1.1.2: U.S. Geological Survey Open-File Report 2016–1188, 17 p., https://doi.org/10.3133/ofr20161188. [Supersedes USGS Open-File Report 2015–1202.]","productDescription":"Report: iii, 17 p.; Appendixes: 1–9","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-054442","costCenters":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"links":[{"id":334283,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1188/ofr20161188.pdf","text":"Report","size":"0.97 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016–1188"},{"id":334282,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1188/coverthb.jpg"},{"id":334284,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2016/1188/downloads","text":"Appendixes 1–9","size":"3.20 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016–1188 Appendixes 1–9","linkHelpText":"Director, Minnesota Water Science Center
U.S. Geological Survey
2280 Woodale Drive
Mounds View, Minnesota 55112
Forecasts of flows entering and leaving the Chain of Lakes reservoir on the Fox River in northeastern Illinois are critical information to water-resource managers who determine the optimal operation of the dam at McHenry, Illinois, to help minimize damages to property and loss of life because of flooding on the Fox River. In 2014, the U.S. Geological Survey; the Illinois Department of Natural Resources, Office of Water Resources; and National Weather Service, North Central River Forecast Center began a cooperative study to develop a system to enable engineers and planners to simulate and communicate flows and to prepare proactively for precipitation events in near real time in the upper Fox River watershed. The purpose of this report is to document the development and evaluation of the Chain of Lakes reservoir model developed in this study.
The reservoir model for the Chain of Lakes was developed using the Hydrologic Engineering Center–Reservoir System Simulation program. Because of the complex relation between the dam headwater and reservoir pool elevations, the reservoir model uses a linear regression model that relates dam headwater elevation to reservoir pool elevation. The linear regression model was developed using 17 U.S. Geological Survey streamflow measurements, along with the gage height in the reservoir pool and the gage height at the dam headwater. The Nash-Sutcliffe model efficiency coefficients for all three linear regression model variables ranged from 0.90 to 0.98.
The reservoir model performance was evaluated by graphically comparing simulated and observed reservoir pool elevation time series during nine periods of high pool elevation. In addition, the peak elevations during these time periods were graphically compared to the closest-in-time observed pool elevation peak. The mean difference in the simulated and observed peak elevations was -0.03 feet, with a standard deviation of 0.19 feet. The Nash-Sutcliffe coefficient for peak prediction was calculated as 0.94. Evaluation of the model based on accuracy of peak prediction and the ability to simulate an elevation time series showed the performance of the model was satisfactory.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165155","collaboration":"Prepared in cooperation with the llinois Department of Natural Resources and the National Weather Service","usgsCitation":"Domanski, M.M., 2017, Development and evaluation of a reservoir model for the Chain of Lakes in Illinois: U.S. Geological Survey Scientific Investigations Report 2016–5155, 21 p., https://doi.org/10.3133/sir20165155.","productDescription":"viii, 21 p.","numberOfPages":"34","onlineOnly":"Y","ipdsId":"IP-074336","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":334088,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5155/coverthb.jpg"},{"id":334089,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5155/sir20165155.pdf","text":"Report","size":"5.08 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5155"}],"country":"United States","state":"Illinois","otherGeospatial":"Chain of Lakes, Fox River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.27857971191406,\n 42.293564192170095\n ],\n [\n -88.27857971191406,\n 42.49488409061174\n ],\n [\n -88.10142517089844,\n 42.49488409061174\n ],\n [\n -88.10142517089844,\n 42.293564192170095\n ],\n [\n -88.27857971191406,\n 42.293564192170095\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Illinois Water Science Center
U.S. Geological Survey
405 N. Goodwin
Urbana, IL 61801
http://il.water.usgs.gov/
The U.S. Geological Survey completed hydrologic and hydraulic analyses of Cromwell Brook and the Sieur de Monts tributary in Acadia National Park, Maine, to better understand causes of flooding in complex hydrologic and hydraulic environments, like those in the Great Meadow wetland and Sieur de Monts Spring area. Regional regression equations were used to compute peak flows with from 2 to 100-year recurrence intervals at seven locations. Light detection and ranging data were adjusted for bias caused by dense vegetation in the Great Meadow wetland; and then combined with local ground surveys used to define the underwater topography and hydraulic structures in the study area. Hydraulic modeling was used to evaluate flood response in the study area to a variety of hydrologic and hydraulic scenarios.
Hydraulic modeling indicates that enlarging the culvert at Park Loop Road could help mitigate flooding near the Sieur de Monts Nature Center that is caused by streamflows with large recurrence intervals; however, hydraulic modeling also indicates that the Park Loop Road culvert does not aggravate flooding near the Nature Center caused by the more frequent high intensity rainstorms. That flooding is likely associated with overland flow resulting from (1) quick runoff from the steep Dorr Mountain hitting the lower gradient Great Meadow wetland area and (2) poor drainage aggravated by beaver dams holding water in the wetland.
Rapid geomorphic assessment data collected in June 2015 and again in April 2016 indicate that Cromwell Brook has evidence of aggradation, degradation, and channel widening throughout the drainage basin. Two of five reference cross sections developed for this report also indicate channel aggradation.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165159","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Lombard, P.J., 2017, Hydrologic and hydraulic analyses of Great Meadow wetland, Acadia National Park, Maine: U.S. Geological Survey Scientific Investigations Report 2016–5159, 39 p., https://doi.org/10.3133/sir20165159.","productDescription":"viii, 39 p.","numberOfPages":"52","onlineOnly":"Y","ipdsId":"IP-077064","costCenters":[{"id":371,"text":"Maine Water Science Center","active":true,"usgs":true}],"links":[{"id":333754,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5159/sir20165159.pdf","text":"Report","size":"7.66 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5159"},{"id":333753,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5159/coverthb.jpg"}],"country":"United States","state":"Maine","otherGeospatial":"Acadia National Park, Mount Desert Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -68.43795776367188,\n 44.22158376545796\n ],\n [\n -68.43795776367188,\n 44.44554600843547\n ],\n [\n -68.16329956054688,\n 44.44554600843547\n ],\n [\n -68.16329956054688,\n 44.22158376545796\n ],\n [\n -68.43795776367188,\n 44.22158376545796\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
196 Whitten Road
Augusta, ME 04330
Or visit our Web site at:
http://newengland.water.usgs.gov
This research highlights development and application of an integrated hydrologic model (GSFLOW) to a semiarid, snow-dominated watershed in the Great Basin to evaluate Pinyon-Juniper (PJ) and temperature controls on mountain meadow shallow groundwater. The work used Google Earth Engine Landsat satellite and gridded climate archives for model evaluation. Model simulations across three decades indicated that the watershed operates on a threshold response to precipitation (P) >400 mm/y to produce a positive yield (P-ET; 9%) resulting in stream discharge and a rebound in meadow groundwater levels during these wetter years. Observed and simulated meadow groundwater response to large P correlates with above average predicted soil moisture and with a normalized difference vegetation index threshold value >0.3. A return to assumed pre-expansion PJ conditions or an increase in temperature to mid-21st century shifts yielded by only ±1% during the multi-decade simulation period; but changes of approximately ±4% occurred during wet years. Changes in annual yield were largely dampened by the spatial and temporal redistribution of evapotranspiration across the watershed: Yet the influence of this redistribution and vegetation structural controls on snowmelt altered recharge to control water table depth in the meadow. Even a small-scale removal of PJ (0.5 km2) proximal to the meadow will promote a stable, shallow groundwater system resilient to droughts, while modest increases in temperature will produce a meadow susceptible to declining water levels and a community structure likely to move toward dry and degraded conditions.
","language":"English","publisher":"Wiley","doi":"10.1002/eco.1792","usgsCitation":"Carroll, R.W., Huntington, J., Snyder, K.A., Niswonger, R.G., Morton, C., and Stringham, T.K., 2017, Evaluating mountain meadow groundwater response to Pinyon-Juniper and temperature in a great basin watershed: Ecohydrology, v. 10, no. 1, p. 1-18, https://doi.org/10.1002/eco.1792.","productDescription":"e1792; 18 p.","startPage":"1","endPage":"18","ipdsId":"IP-072881","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":461779,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/eco.1792","text":"Publisher Index Page"},{"id":334058,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","otherGeospatial":"Great Basin","volume":"10","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-11-14","publicationStatus":"PW","scienceBaseUri":"588b1976e4b0ad67323f97dc","contributors":{"authors":[{"text":"Carroll, Rosemary W.H.","contributorId":39928,"corporation":false,"usgs":true,"family":"Carroll","given":"Rosemary","email":"","middleInitial":"W.H.","affiliations":[],"preferred":false,"id":660972,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Huntington, Justin L.","contributorId":31279,"corporation":false,"usgs":true,"family":"Huntington","given":"Justin L.","affiliations":[],"preferred":false,"id":660973,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Snyder, Keirith A.","contributorId":178786,"corporation":false,"usgs":false,"family":"Snyder","given":"Keirith","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":660974,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Niswonger, Richard G. 0000-0001-6397-2403 rniswon@usgs.gov","orcid":"https://orcid.org/0000-0001-6397-2403","contributorId":152462,"corporation":false,"usgs":true,"family":"Niswonger","given":"Richard","email":"rniswon@usgs.gov","middleInitial":"G.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":false,"id":660975,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Morton, Charles","contributorId":178787,"corporation":false,"usgs":false,"family":"Morton","given":"Charles","affiliations":[],"preferred":false,"id":660976,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stringham, Tamzen K.","contributorId":178788,"corporation":false,"usgs":false,"family":"Stringham","given":"Tamzen","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":660977,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70180266,"text":"70180266 - 2017 - Nutrient processes at the stream-lake interface for a channelized versus unmodified stream mouth","interactions":[],"lastModifiedDate":"2025-05-14T18:36:52.488165","indexId":"70180266","displayToPublicDate":"2017-01-26T00:00:00","publicationYear":"2017","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":"Nutrient processes at the stream-lake interface for a channelized versus unmodified stream mouth","docAbstract":"Inorganic forms of nitrogen and phosphorous impact freshwater lakes by stimulating primary production and affecting water quality and ecosystem health. Communities around the world are motivated to sustain and restore freshwater resources and are interested in processes controlling nutrient inputs. We studied the environment where streams flow into lakes, referred to as the stream-lake interface (SLI), for a channelized and unmodified stream outlet. Channelization is done to protect infrastructure or recreational beach areas. We collected hydraulic and nutrient data for surface water and shallow groundwater in two SLIs to develop conceptual models that describe characteristics that are representative of these hydrologic features. Water, heat, and solute transport models were used to evaluate hydrologic conceptualizations and estimate mean residence times of water in the sediment. A nutrient mass balance model is developed to estimate net rates of adsorption and desorption, mineralization, and nitrification along subsurface flow paths. Results indicate that SLIs are dynamic sources of nutrients to lakes and that the common practice of channelizing the stream at the SLI decreases nutrient concentrations in pore water discharging along the lakeshore. This is in contrast to the unmodified SLI that forms a barrier beach that disconnects the stream from the lake and results in higher nutrient concentrations in pore water discharging to the lake. These results are significant because nutrient delivery through pore water seepage at the lakebed from the natural SLI contributes to nearshore algal communities and produces elevated concentrations of inorganic nutrients in the benthic zone where attached algae grow.
","language":"English","publisher":"AGU Publications","doi":"10.1002/2016WR019538","usgsCitation":"Niswonger, R.G., Naranjo, R.C., Smith, D., Constantz, J., Allander, K.K., Rosenberry, D.O., Neilson, B., Rosen, M.R., and Stonestrom, D.A., 2017, Nutrient processes at the stream-lake interface for a channelized versus unmodified stream mouth: Water Resources Research, v. 53, no. 1, p. 237-256, https://doi.org/10.1002/2016WR019538.","productDescription":"20 p.","startPage":"237","endPage":"256","ipdsId":"IP-077507","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":334057,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.er.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"53","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-01-11","publicationStatus":"PW","scienceBaseUri":"588b1976e4b0ad67323f97da","contributors":{"authors":[{"text":"Niswonger, Richard G. 0000-0001-6397-2403 rniswon@usgs.gov","orcid":"https://orcid.org/0000-0001-6397-2403","contributorId":152462,"corporation":false,"usgs":true,"family":"Niswonger","given":"Richard","email":"rniswon@usgs.gov","middleInitial":"G.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":false,"id":661003,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Naranjo, Ramon C. 0000-0003-4469-6831 rnaranjo@usgs.gov","orcid":"https://orcid.org/0000-0003-4469-6831","contributorId":3391,"corporation":false,"usgs":true,"family":"Naranjo","given":"Ramon","email":"rnaranjo@usgs.gov","middleInitial":"C.","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":661004,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, David 0000-0002-9543-800X","orcid":"https://orcid.org/0000-0002-9543-800X","contributorId":169280,"corporation":false,"usgs":true,"family":"Smith","given":"David","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":661005,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Constantz, James E. 0000-0002-4062-2096 jconstan@usgs.gov","orcid":"https://orcid.org/0000-0002-4062-2096","contributorId":1962,"corporation":false,"usgs":true,"family":"Constantz","given":"James E.","email":"jconstan@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":661006,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Allander, Kip K. 0000-0002-3317-298X kalland@usgs.gov","orcid":"https://orcid.org/0000-0002-3317-298X","contributorId":2290,"corporation":false,"usgs":true,"family":"Allander","given":"Kip","email":"kalland@usgs.gov","middleInitial":"K.","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":661007,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rosenberry, Donald O. 0000-0003-0681-5641 rosenber@usgs.gov","orcid":"https://orcid.org/0000-0003-0681-5641","contributorId":1312,"corporation":false,"usgs":true,"family":"Rosenberry","given":"Donald","email":"rosenber@usgs.gov","middleInitial":"O.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":661008,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Neilson, Bethany","contributorId":178798,"corporation":false,"usgs":false,"family":"Neilson","given":"Bethany","affiliations":[],"preferred":false,"id":661009,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Rosen, Michael R. 0000-0003-3991-0522 mrosen@usgs.gov","orcid":"https://orcid.org/0000-0003-3991-0522","contributorId":495,"corporation":false,"usgs":true,"family":"Rosen","given":"Michael","email":"mrosen@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":661010,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Stonestrom, David A. 0000-0001-7883-3385 dastones@usgs.gov","orcid":"https://orcid.org/0000-0001-7883-3385","contributorId":2280,"corporation":false,"usgs":true,"family":"Stonestrom","given":"David","email":"dastones@usgs.gov","middleInitial":"A.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":661011,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70180205,"text":"70180205 - 2017 - A carbon balance model for the great dismal swamp ecosystem","interactions":[],"lastModifiedDate":"2017-02-08T10:30:06","indexId":"70180205","displayToPublicDate":"2017-01-25T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1183,"text":"Carbon Balance and Management","active":true,"publicationSubtype":{"id":10}},"title":"A carbon balance model for the great dismal swamp ecosystem","docAbstract":"Carbon storage potential has become an important consideration for land management and planning in the United States. The ability to assess ecosystem carbon balance can help land managers understand the benefits and tradeoffs between different management strategies. This paper demonstrates an application of the Land Use and Carbon Scenario Simulator (LUCAS) model developed for local-scale land management at the Great Dismal Swamp National Wildlife Refuge. We estimate the net ecosystem carbon balance by considering past ecosystem disturbances resulting from storm damage, fire, and land management actions including hydrologic inundation, vegetation clearing, and replanting.
We modeled the annual ecosystem carbon stock and flow rates for the 30-year historic time period of 1985–2015, using age-structured forest growth curves and known data for disturbance events and management activities. The 30-year total net ecosystem production was estimated to be a net sink of 0.97 Tg C. When a hurricane and six historic fire events were considered in the simulation, the Great Dismal Swamp became a net source of 0.89 Tg C. The cumulative above and below-ground carbon loss estimated from the South One and Lateral West fire events totaled 1.70 Tg C, while management activities removed an additional 0.01 Tg C. The carbon loss in below-ground biomass alone totaled 1.38 Tg C, with the balance (0.31 Tg C) coming from above-ground biomass and detritus.
Natural disturbances substantially impact net ecosystem carbon balance in the Great Dismal Swamp. Through alternative management actions such as re-wetting, below-ground biomass loss may have been avoided, resulting in the added carbon storage capacity of 1.38 Tg. Based on two model assumptions used to simulate the peat system, (a burn scar totaling 70 cm in depth, and the soil carbon accumulation rate of 0.36 t C/ha−1/year−1 for Atlantic white cedar), the total soil carbon loss from the South One and Lateral West fires would take approximately 1740 years to re-amass. Due to the impractical time horizon this presents for land managers, this particular loss is considered permanent. Going forward, the baseline carbon stock and flow parameters presented here will be used as reference conditions to model future scenarios of land management and disturbance.
Within Voyageurs National Park in Minnesota, lake levels are controlled by a series of dams to support a variety of uses. Previous research indicates a link between these artificially maintained water levels, referred to as rule curves, and mercury concentrations in fish owing to the drying and rewetting of wetlands and other nearshore areas, which may release methylmercury into the water when inundated. The U.S. Geological Survey, National Park Service, and University of Wisconsin-La Crosse cooperated in a study to assess the importance of lake-level fluctuation and other factors affecting mercury concentrations in Perca flavescens (yellow perch) in the lakes of Voyageurs National Park. For this study, mercury body burdens were determined for young-of-the-year yellow perch collected from the large lakes within Voyageurs National Park during 2013–15. These mercury body burdens were compared to lake levels and water-quality constituents from the same period.
Field properties and profiles of lake water quality indicated that Sand Point, Little Vermilion, and Crane Lakes were anoxic at times near the lake bottom sediments, where sulfate-reducing bacteria may convert mercury to methylmercury. The median dissolved sulfate concentration was highest in Crane Lake, the median total organic carbon concentration was highest in Sand Point Lake, and the median total phosphorus concentration was highest in Kabetogama Lake, all of which is consistent with previous research. All lakes had median chlorophyll a concentrations of 3.6 micrograms per liter or less with the exception of Kabetogama Lake, where the median concentrations were 4.3 micrograms per liter for the midlake sites and 7.1 micrograms per liter and 9.0 micrograms per liter for the nearshore sites.
Mercury concentrations in sampled fish varied widely between years and among lakes, from 14.7 nanograms per gram in fish samples from Kabetogama Lake in 2015 to 178 nanograms per gram in fish samples from Crane Lake in 2014. Data from this study can be combined with ongoing hydrologic modeling studies to evaluate trends in the mercury body burden of fish and different water-level management scenarios prescribed by the 2000 Rule Curves and the 1970 Rule Curves.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165175","collaboration":"Prepared in cooperation with the National Park Service and the University of Wisconsin-La Crosse","usgsCitation":"Christensen, V.G., Larson, J.H., Maki, R.P., Sandheinrich, M.B., Brigham, M.E., Kissane, Claire, and LeDuc, J.F., 2017, Lake levels and water quality in comparison to fish mercury body burdens, Voyageurs National Park, Minnesota, 2013–15: U.S. Geological Survey Scientific Investigations Report 2016–5175, 17 p., https://doi.org/10.3133/sir20165175.","productDescription":"iv, 17 p.","numberOfPages":"26","onlineOnly":"Y","ipdsId":"IP-079622","costCenters":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"links":[{"id":333068,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5175/coverthb.jpg"},{"id":333069,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5175/sir20165175.pdf","text":"Report","size":"2.35 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Sir 2016–5175"}],"country":"United States","state":"Minnesota","otherGeospatial":"Voyageurs National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.13934326171875,\n 48.25942712329832\n ],\n [\n -93.13934326171875,\n 48.647427805533546\n ],\n [\n -92.39227294921875,\n 48.647427805533546\n ],\n [\n -92.39227294921875,\n 48.25942712329832\n ],\n [\n -93.13934326171875,\n 48.25942712329832\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Minnesota Water Science Center
U.S. Geological Survey
2280 Woodale Drive
Mounds View, MN 55112
We collected soil-hydraulic property data from the literature for wildfire-affected soils, ash, and unburned soils. These data were used to calculate metrics and timescales of hydrologic response related to infiltration and surface runoff generation. Sorptivity (S) and wetting front potential (Ψf) were significantly different (lower) in burned soils compared with unburned soils, whereas field-saturated hydraulic conductivity (Kfs) was not significantly different. The magnitude and duration of the influence of capillarity during infiltration was greatly reduced in burned soils, causing faster ponding times in response to rainfall. Ash had large values of S and Kfs but moderate values of Ψf, compared with unburned and burned soils, indicating ash has long ponding times in response to rainfall. The ratio of S2/Kfs was nearly constant (~100 mm) for unburned soils but more variable in burned soils, suggesting that unburned soils have a balance between gravity and capillarity contributions to infiltration that may depend on soil organic matter, whereas in burned soils the gravity contribution to infiltration is greater. Changes in S and Kfs in burned soils act synergistically to reduce infiltration and accelerate and amplify surface runoff generation. Synthesis of these findings identifies three key areas for future research. First, short timescales of capillary influences on infiltration indicate the need for better measurements of infiltration at times less than 1 min to accurately characterize S in burned soils. Second, using parameter values, such as Ψf, from unburned areas could produce substantial errors in hydrologic modeling when used without adjustment for wildfire effects, causing parameter compensation and resulting underestimation of Kfs. Third, more thorough measurement campaigns that capture soil-structural changes, organic matter impacts, quantitative water repellency trends, and soil-water content along with soil-hydraulic properties could drive the development of better techniques for numerically simulating infiltration in burned areas.
","language":"English","publisher":"Wiley","doi":"10.1002/hyp.10998","usgsCitation":"Ebel, B.A., and Moody, J.A., 2017, Synthesis of soil-hydraulic properties and infiltration timescales in wildfire-affected soils: Hydrological Processes, v. 31, no. 2, p. 324-340, https://doi.org/10.1002/hyp.10998.","productDescription":"17 p.","startPage":"324","endPage":"340","ipdsId":"IP-078817","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":333232,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"31","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-11-10","publicationStatus":"PW","scienceBaseUri":"587f3bdbe4b0d96de2564535","contributors":{"authors":[{"text":"Ebel, Brian A. 0000-0002-5413-3963 bebel@usgs.gov","orcid":"https://orcid.org/0000-0002-5413-3963","contributorId":2557,"corporation":false,"usgs":true,"family":"Ebel","given":"Brian","email":"bebel@usgs.gov","middleInitial":"A.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":658484,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moody, John A. 0000-0003-2609-364X jamoody@usgs.gov","orcid":"https://orcid.org/0000-0003-2609-364X","contributorId":771,"corporation":false,"usgs":true,"family":"Moody","given":"John","email":"jamoody@usgs.gov","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":658485,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70178590,"text":"ofr20161198 - 2017 - Peak streamflow on selected streams in Arkansas, December 2015","interactions":[],"lastModifiedDate":"2017-01-11T15:13:09","indexId":"ofr20161198","displayToPublicDate":"2017-01-11T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-1198","title":"Peak streamflow on selected streams in Arkansas, December 2015","docAbstract":"Heavy rainfall during December 2015 resulted in flooding across parts of Arkansas; rainfall amounts were as high as 12 inches over a period from December 27, 2015, to December 29, 2015. Although precipitation accumulations were highest in northwestern Arkansas, significant flooding occurred in other parts of the State. Flood damage occurred in several counties as water levels rose in streams, and disaster declarations were declared in 32 of the 75 counties in Arkansas.
Given the severity of the December 2015 flooding, the U.S. Geological Survey (USGS), in cooperation with the Federal Emergency Management Agency (FEMA), conducted a study to document the meteorological and hydrological conditions prior to and during the flood; compiled flood-peak gage heights, streamflows, and flood probabilities at USGS streamflow-gaging stations; and estimated streamflows and flood probabilities at selected ungaged locations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161198","usgsCitation":"Breaker, B.K., 2017, Peak streamflow on selected streams in Arkansas, December 2015: U.S. Geological Survey Open-File Report 2016–1198, 7 p., https://doi.org/10.3133/ofr20161198.","productDescription":"7 p.","onlineOnly":"Y","ipdsId":"IP-079418","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":332997,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1198/coverthb2.jpg"},{"id":332995,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1198/ofr20161198.pdf","text":"Report","size":"622 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016–1198"}],"country":"United 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\"}}]}","contact":"Director, Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
401 Hardin Road
Little Rock, AR 72211
This 1:24,000-scale geologic map includes new geologic mapping as well as compilation and revision of previous geologic maps in the area. Field investigations were carried out during 2009–2011 that included mapping and investigations of the geology and hydrology of the Chickasaw National Recreation Area, Oklahoma, west of the map area.
The Fittstown quadrangle is in Pontotoc and Johnston Counties in south-central Oklahoma, which is in the northeastern part of the Arbuckle Mountains. The Arbuckle Mountains are composed of a thick sequence of Paleozoic sedimentary rocks that overlie Lower Cambrian and Precambrian igneous rocks; these latter rocks are not exposed in the quadrangle. From Middle to Late Pennsylvanian time, the Arbuckle Mountains region was folded, faulted, and uplifted. Periods of erosion followed these Pennsylvanian mountain-building events, beveling this region and ultimately developing the current subtle topography that includes hills and incised uplands. The southern and northwestern parts of the Fittstown quadrangle are directly underlain by Lower Ordovician dolomite of the Arbuckle Group that has eroded to form an extensive, stream-incised upland containing the broad, gently southeast-plunging, Pennsylvanian-age Hunton anticline. The northeastern part of the map area is underlain by Middle Ordovician to Pennsylvanian limestone, shale, and sandstone units that predominantly dip northeast and form the northeastern limb of the Hunton anticline; this limb is cut by steeply dipping, northwest-southeast striking faults of the Franks fault zone. This limb and the Franks fault zone define the southwestern margin of the Franks graben, which is underlain by Pennsylvanian rocks in the northeast part of the map area.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3371","usgsCitation":"Lidke, D.J., and Blome, C.D., 2017, Geologic map of the Fittstown 7.5′ quadrangle, Pontotoc and Johnston Counties, Oklahoma: U.S. Geological Survey Scientific Investigations Map 3371, 14 p., 1 sheet, scale 1:24,000, https://doi.org/10.3133/sim3371.","productDescription":"Pamphlet: iv, 14 p.; 1 Sheet: 34.09 x 34.35 inches; Read Me; Spatial Data","numberOfPages":"22","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-073124","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":438453,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F77P8WJN","text":"USGS data release","linkHelpText":"Geologic map of the Fittstown 7 1/2' quadrangle, Pontotoc and Johnston Counties, Oklahoma"},{"id":332521,"rank":4,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3371/sim3371__map.pdf","text":"Map","size":"31.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3371 Map"},{"id":332522,"rank":5,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3371/sim3371__map_geo.pdf","text":"Georeferenced Map","size":"187 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3371 Georeferenced Map"},{"id":332520,"rank":3,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sim/3371/sim3371_ReadMe_v2.txt","text":"Read Me","size":"8.0 kB","linkFileType":{"id":2,"text":"txt"},"description":"SIM 3371 Read Me"},{"id":332523,"rank":6,"type":{"id":23,"text":"Spatial Data"},"url":"https://doi.org/10.5066/F77P8WJN","text":"Data Release","description":"SIM 3371 Data Release"},{"id":332519,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3371/sim3371_pamphlet.pdf","text":"Pamphlet","size":"3.19 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3371 Pamphlet"},{"id":332518,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3371/coverthb_map2.jpg"}],"country":"United States","state":"Oklahoma","county":"Johnson County. Pontotoc County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.75,\n 34.625\n ],\n [\n -96.75,\n 34.5\n ],\n [\n -96.625,\n 34.5\n ],\n [\n -96.625,\n 34.625\n ],\n [\n -96.75,\n 34.625\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Center Director, USGS Geosciences and Environmental Change Science Center
Box 25046, Mail Stop 980
Denver, CO 80225
Comprehensive sampling of peat, underlying lakebed sediments, and coexisting waters of a naturally uraniferous montane wetland are combined with hydrologic measurements to define the important controls on uranium (U) supply and uptake. The major source of U to the wetland is groundwater flowing through locally fractured and faulted granite gneiss of Proterozoic age. Dissolved U concentrations in four springs and one seep ranged from 20 to 83 ppb (μg/l). Maximum U concentrations are ∼300 ppm (mg/kg) in lakebed sediments and >3000 ppm in peat. Uranium in lakebed sediments is primarily stratabound in the more organic-rich layers, but samples of similar organic content display variable U concentrations. Post-depositional modifications include variable additions of U delivered by groundwater. Uranium distribution in peat is heterogeneous and primarily controlled by proximity to groundwater-fed springs and seeps that act as local point sources of U, and by proximity to groundwater directed along the peat/lakebeds contact. Uranium is initially sorbed on various organic components of peat as oxidized U(VI) present in groundwater. Selective extractions indicate that the majority of sorbed U remains as the oxidized species despite reducing conditions that should favor formation of U(IV). Possible explanations are kinetic hindrances related to strong complex formation between uranyl and humic substances, inhibition of anaerobic bacterial activity by low supply of dissolved iron and sulfate, and by cold temperatures.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeochem.2017.01.001","usgsCitation":"Schumann, R.R., Zielinski, R.A., Otton, J.K., Pantea, M.P., and Orem, W.H., 2017, Uranium delivery and uptake in a montane wetland, north-central Colorado, USA: Applied Geochemistry, v. 78, no. 3, p. 363-379, https://doi.org/10.1016/j.apgeochem.2017.01.001.","productDescription":"17 p.","startPage":"363","endPage":"379","ipdsId":"IP-074221","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":470147,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.apgeochem.2017.01.001","text":"Publisher Index Page"},{"id":335164,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":335496,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F70Z71DQ","text":"Stratigraphic, geochemical, and hydrologic data for the Boston Peak wetland, Larimer County, CO, USA"}],"country":"United States","state":"Colorado","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -107.5341796875,\n 38.805470223177466\n ],\n [\n -107.5341796875,\n 41.0130657870063\n ],\n [\n -103.4912109375,\n 41.0130657870063\n ],\n [\n -103.4912109375,\n 38.805470223177466\n ],\n [\n -107.5341796875,\n 38.805470223177466\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"78","issue":"3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"589ffedfe4b099f50d3e0434","contributors":{"authors":[{"text":"Schumann, R. Randall 0000-0001-8158-6960 rschumann@usgs.gov","orcid":"https://orcid.org/0000-0001-8158-6960","contributorId":1569,"corporation":false,"usgs":true,"family":"Schumann","given":"R.","email":"rschumann@usgs.gov","middleInitial":"Randall","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":663365,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zielinski, Robert A. 0000-0002-4047-5129 rzielinski@usgs.gov","orcid":"https://orcid.org/0000-0002-4047-5129","contributorId":1593,"corporation":false,"usgs":true,"family":"Zielinski","given":"Robert","email":"rzielinski@usgs.gov","middleInitial":"A.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":663366,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Otton, James K. jkotton@usgs.gov","contributorId":1170,"corporation":false,"usgs":true,"family":"Otton","given":"James","email":"jkotton@usgs.gov","middleInitial":"K.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":663367,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pantea, Michael P. mpantea@usgs.gov","contributorId":1549,"corporation":false,"usgs":true,"family":"Pantea","given":"Michael","email":"mpantea@usgs.gov","middleInitial":"P.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":663368,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Orem, William H. 0000-0003-4990-0539 borem@usgs.gov","orcid":"https://orcid.org/0000-0003-4990-0539","contributorId":577,"corporation":false,"usgs":true,"family":"Orem","given":"William","email":"borem@usgs.gov","middleInitial":"H.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":663369,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70179438,"text":"70179438 - 2017 - Spatial and temporal patterns of dissolved organic matter quantity and quality in the Mississippi River Basin, 1997–2013","interactions":[],"lastModifiedDate":"2017-02-15T15:39:56","indexId":"70179438","displayToPublicDate":"2017-01-03T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Spatial and temporal patterns of dissolved organic matter quantity and quality in the Mississippi River Basin, 1997–2013","docAbstract":"Recent studies have found insignificant or decreasing trends in time-series dissolved organic carbon (DOC) datasets, questioning the assumption that long-term DOC concentrations in surface waters are increasing in response to anthropogenic forcing, including climate change, land use, and atmospheric acid deposition. We used the weighted regressions on time, discharge, and season (WRTDS) model to estimate annual flow-normalized concentrations and fluxes to determine if changes in DOC quantity and quality signal anthropogenic forcing at 10 locations in the Mississippi River Basin. Despite increases in agriculture and urban development throughout the basin, net increases in DOC concentration and flux were significant at only 3 of 10 sites from 1997 to 2013 and ranged between −3.5% to +18% and −0.1 to 19%, respectively. Positive shifts in DOC quality, characterized by increasing specific ultraviolet absorbance at 254 nm, ranged between +8% and +45%, but only occurred at one of the sites with significant DOC quantity increases. Basinwide reductions in atmospheric sulfate deposition did not result in large increases in DOC either, likely because of the high buffering capacity of the soil. Hydroclimatic factors including annual discharge, precipitation, and temperature did not significantly change during the 17-year timespan of this study, which contrasts with results from previous studies showing significant increases in precipitation and discharge over a century time scale. Our study also contrasts with those from smaller catchments, which have shown stronger DOC responses to climate, land use, and acidic deposition. This temporal and spatial analysis indicated that there was a potential change in DOC sources in the Mississippi River Basin between 1997 and 2013. However, the overall magnitude of DOC trends was not large, and the pattern in quantity and quality increases for the 10 study sites was not consistent throughout the basin.
","language":"English","publisher":"Wiley","doi":"10.1002/hyp.11072","usgsCitation":"Stackpoole, S.M., Stets, E., Clow, D.W., Burns, D.A., Aiken, G.R., Aulenbach, B.T., Creed, I., Hirsch, R.M., Laudon, H., Pellerin, B., and Striegl, R.G., 2017, Spatial and temporal patterns of dissolved organic matter quantity and quality in the Mississippi River Basin, 1997–2013: Hydrological Processes, v. 31, no. 4, p. 902-915, https://doi.org/10.1002/hyp.11072.","productDescription":"14 p.","startPage":"902","endPage":"915","ipdsId":"IP-066770","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":470153,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/hyp.11072","text":"Publisher Index Page"},{"id":332738,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"31","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-12-11","publicationStatus":"PW","scienceBaseUri":"586cc68ee4b0f5ce109fa93d","contributors":{"authors":[{"text":"Stackpoole, Sarah M. 0000-0002-5876-4922 sstackpoole@usgs.gov","orcid":"https://orcid.org/0000-0002-5876-4922","contributorId":3784,"corporation":false,"usgs":true,"family":"Stackpoole","given":"Sarah","email":"sstackpoole@usgs.gov","middleInitial":"M.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":657186,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stets, Edward G. estets@usgs.gov","contributorId":174182,"corporation":false,"usgs":true,"family":"Stets","given":"Edward G.","email":"estets@usgs.gov","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":false,"id":657187,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Clow, David W. 0000-0001-6183-4824 dwclow@usgs.gov","orcid":"https://orcid.org/0000-0001-6183-4824","contributorId":1671,"corporation":false,"usgs":true,"family":"Clow","given":"David","email":"dwclow@usgs.gov","middleInitial":"W.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":657188,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Burns, Douglas A. 0000-0001-6516-2869 daburns@usgs.gov","orcid":"https://orcid.org/0000-0001-6516-2869","contributorId":1237,"corporation":false,"usgs":true,"family":"Burns","given":"Douglas","email":"daburns@usgs.gov","middleInitial":"A.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":657189,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Aiken, George R. 0000-0001-8454-0984 graiken@usgs.gov","orcid":"https://orcid.org/0000-0001-8454-0984","contributorId":1322,"corporation":false,"usgs":true,"family":"Aiken","given":"George","email":"graiken@usgs.gov","middleInitial":"R.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":657281,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Aulenbach, Brent T. 0000-0003-2863-1288 btaulenb@usgs.gov","orcid":"https://orcid.org/0000-0003-2863-1288","contributorId":3057,"corporation":false,"usgs":true,"family":"Aulenbach","given":"Brent","email":"btaulenb@usgs.gov","middleInitial":"T.","affiliations":[{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":657190,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Creed, Irena F.","contributorId":81209,"corporation":false,"usgs":false,"family":"Creed","given":"Irena F.","affiliations":[{"id":27655,"text":"Department of Biology, University of Western Ontario, London, ON Canada","active":true,"usgs":false}],"preferred":false,"id":657191,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hirsch, Robert M. 0000-0002-4534-075X rhirsch@usgs.gov","orcid":"https://orcid.org/0000-0002-4534-075X","contributorId":2005,"corporation":false,"usgs":true,"family":"Hirsch","given":"Robert","email":"rhirsch@usgs.gov","middleInitial":"M.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":657192,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Laudon, Hjalmar","contributorId":46812,"corporation":false,"usgs":true,"family":"Laudon","given":"Hjalmar","affiliations":[],"preferred":false,"id":657193,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Pellerin, Brian A. 0000-0003-3712-7884 bpeller@usgs.gov","orcid":"https://orcid.org/0000-0003-3712-7884","contributorId":147077,"corporation":false,"usgs":true,"family":"Pellerin","given":"Brian","email":"bpeller@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true}],"preferred":true,"id":657194,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Striegl, Robert G. 0000-0002-8251-4659 rstriegl@usgs.gov","orcid":"https://orcid.org/0000-0002-8251-4659","contributorId":1630,"corporation":false,"usgs":true,"family":"Striegl","given":"Robert","email":"rstriegl@usgs.gov","middleInitial":"G.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":false,"id":657195,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70190248,"text":"70190248 - 2017 - Geology and vertebrate paleontology of Tule Springs Fossil Beds National Monument, Nevada, USA","interactions":[],"lastModifiedDate":"2019-02-04T08:40:43","indexId":"70190248","displayToPublicDate":"2017-01-01T08:34:12","publicationYear":"2017","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Geology and vertebrate paleontology of Tule Springs Fossil Beds National Monument, Nevada, USA","docAbstract":"Tule Springs Fossil Beds National Monument (TUSK) preserves 22,650 acres of the upper Las Vegas Wash in the northern Las Vegas Valley, Nevada, USA. TUSK is home to extensive and stratigraphically complex groundwater discharge (GWD) deposits, called the Las Vegas Formation, which represent springs and desert wetlands that covered much of the valley during the late Quaternary. The GWD deposits record hydrologic changes that occurred here in a dynamic and temporally congruent response to abrupt climatic oscillations over the last ~300 ka (thousands of years). The deposits also entomb the Tule Springs Local Fauna (TSLF), one of the most significant late Pleistocene (Rancholabrean) vertebrate assemblages in the American Southwest. The TSLF is both prolific and diverse, and includes a large mammal assemblage dominated by Mammuthus columbi and Camelops hesternus. Two and possibly three distinct species of Equus, two species of Bison, Panthera atrox, Smilodon fatalis, Canis dirus, Megalonyx jeffersonii, and Nothrotheriops shastensis are also present, and newly recognized faunal components include micromammals, amphibians, snakes, and birds. Invertebrates, plant macrofossils, and pollen also occur in the deposits and provide important and complementary paleoenvironmental information. This field compendium highlights some of the classic stratigraphic sequences of the Las Vegas Formation within TUSK, emphasizes the significant hydrologic changes that occurred in the area during the recent geologic past, and examines the subsequent and repeated effect of rapid climate change on the local desert wetland ecosystem.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Field excursions in Southern California: Field guides to the 2016 Geological Society of American cordilleran section meeting","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Geological Society of America ","doi":"10.1130/2017.0045(01)","isbn":"9780813756455","usgsCitation":"Springer, K.B., Pigati, J., and Eric Scott, 2017, Geology and vertebrate paleontology of Tule Springs Fossil Beds National Monument, Nevada, USA, chap. of Field excursions in Southern California: Field guides to the 2016 Geological Society of American cordilleran section meeting, v. 45, p. 1-30, https://doi.org/10.1130/2017.0045(01).","productDescription":"30 p.","startPage":"1","endPage":"30","ipdsId":"IP-077008","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":360946,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada ","otherGeospatial":"Tule Springs Fossil Beds National Monument ","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.42167663574217,\n 36.25313319699069\n ],\n [\n -115.02891540527344,\n 36.25313319699069\n ],\n [\n -115.02891540527344,\n 36.4223874864237\n ],\n [\n -115.42167663574217,\n 36.4223874864237\n ],\n [\n -115.42167663574217,\n 36.25313319699069\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"45","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Springer, Kathleen B. 0000-0002-2404-0264 kspringer@usgs.gov","orcid":"https://orcid.org/0000-0002-2404-0264","contributorId":149826,"corporation":false,"usgs":true,"family":"Springer","given":"Kathleen","email":"kspringer@usgs.gov","middleInitial":"B.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":708147,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pigati, Jeffrey S. 0000-0001-5843-6219 jpigati@usgs.gov","orcid":"https://orcid.org/0000-0001-5843-6219","contributorId":149825,"corporation":false,"usgs":true,"family":"Pigati","given":"Jeffrey S.","email":"jpigati@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":false,"id":708148,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Eric Scott","contributorId":195776,"corporation":false,"usgs":false,"family":"Eric Scott","affiliations":[],"preferred":false,"id":708149,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ]}