The Skagit River delivers about 40 percent of all fluvial sediment that enters Puget Sound, influencing flood hazards in the Skagit lowlands, critically important estuarine habitat in the delta, and some of the most diverse and productive agriculture in western Washington. A total of 175 measurements of suspended-sediment load, made routinely from 1974 to 1993, and sporadically from 2006 to 2009, were used to develop and evaluate regression models of sediment transport (also known as “sediment-rating curves”) for estimating suspended-sediment load as a function of river discharge. Using a flow-range model and 75 years of daily discharge record (acquired from 1941 to 2015), the mean annual suspended-sediment load for the Skagit River near Mount Vernon, Washington, was estimated to be 2.5 teragrams (Tg, where 1 Tg = 1 million metric tons). The seasonal model indicates that 74 percent of the total annual suspended‑sediment load is delivered to Puget Sound during the winter storm season (from October through March), but also indicates that discharge is a poor surrogate for suspended‑sediment concentration (SSC) during the summer low-flow season. Sediment-rating curves developed for different time periods revealed that the regression model slope of the SSC-discharge relation increased 66 percent between the periods of 1974–76 and 2006–09 when suspended-sediment samples were collected, implying that changes in sediment supply, channel hydraulics, and (or) basin hydrology occurred between the two time intervals. In the relatively wet water year 2007 (October 1, 2006, through September 30, 2007), an automated sampler was used to collect daily samples of suspended sediment from which an annual load of 4.5 Tg was calculated, dominated by a single large flood event that contributed 1.8 Tg, or 40 percent of the total. In comparison, the annual load calculated for water year 2007 using the preferred flow-range model was 4.8 Tg (+6.7 percent), in close agreement with the measured value.
Particle size affects sediment transport, fate and distribution across watersheds, and therefore is important for predicting how coastal environments, particularly deltas and beaches, will respond to changes in climate and sea-level. Particle-size analysis of winter storm samples indicated that about one-half of the suspended-sediment load consisted of fines (that is, silt- and clay-sized particles smaller than 0.0625 mm in diameter), and the remainder consisted of mostly fine- to medium-sized sand (0.0625–0.5 mm), whereas bedload during winter storm flows (about 1–3 percent of total sediment load) was predominantly composed of medium to coarse sand (0.25–1 mm). A continuous turbidity record from the Anacortes Water Treatment Plant (water years 1999–2013), used as a surrogate for the concentration of fines (R2 = 0.93, p = 4.2E-10, n = 17), confirms that about one-half of the mean annual suspended-sediment load is composed of fines.
The distribution of flow through the delta distributaries (that is, the channels into which the main stem splits as it approaches the delta) is dynamic, with twice as much flow through the North Fork of the Skagit River relative to the South Fork during low-flow conditions, and close to equal flows in the two channels during high-flow conditions. Turbidity, monitored at several locations in the lower river in spring 2009, was essentially uniform among sites, indicating that fines are well mixed in the lower Skagit River system (defined as the Skagit River and all its distributaries downstream of the Mount Vernon streamgage). A strong relation (R2 = 0.95, p = 3.2E-14, n = 21; linear regression) between the concentration of fines and turbidity measured at various locations in summer 2009 indicates that turbidity is an effective surrogate for the concentration of fines, independent of location in the river, under naturally well-mixed fluvial conditions. This relation is especially useful for monitoring suspended sediment in western Washington rivers that are seasonally dominated by glacier meltwater because glacial melting typically produces suspended-sediment concentrations that are not well correlated with discharge. These results provide a comprehensive set of tools to estimate sediment delivery and delta responses of interest to scientists and resource managers including decision-makers examining options for flood hazard mitigation, estuary restoration, and climate change adaptation.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165106","collaboration":"A Study by the U.S. Geological Survey Coastal Habitats in Puget Sound (CHIPS) Project","usgsCitation":"Curran, C.A., Grossman, E.E., Mastin, M.C., and Huffman, R.L., 2016, Sediment load and distribution in the lower Skagit River, Skagit County, Washington: U.S. Geological Survey Scientific Investigations Report 2016–5106, 24 p., https://dx.doi.org/10.3133/sir20165106.","productDescription":"vi, 24 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-059558","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":326607,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5106/coverthb.jpg"},{"id":326608,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5106/sir20165106.pdf","text":"Report","size":"10.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5106"}],"country":"United States","state":"Washington","county":"Skagit County","otherGeospatial":"Lower Skagit River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.541667,\n 48.466667\n ],\n [\n -122.541667,\n 48.3\n ],\n [\n -122.283333,\n 48.3\n ],\n [\n -122.283333,\n 48.466667\n ],\n [\n -122.541667,\n 48.466667\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402
http://wa.water.usgs.gov
The Upper Mississippi River Restoration (UMRR) Program’s Long Term Resource Monitoring (LTRM) element is designed to monitor and assess long term trends in the Upper Mississippi River System (UMRS). To accomplish this, standardized methods are used that allow for comparisons across pools and rivers. In recent years, other projects and other agencies have adopted the LTRM fish methodologies for use outside the UMRR. To determine how widespread the use of the Fish Component’s methods are, a twelve question survey was delivered via SurveyMonkey.com through the states comprising the American Fisheries Society (AFS) North Central Division and the Upper Mississippi River Conservation Committee. Approximately 2,000 professionals were reached with ≈11 percent participating. Results indicate that nearly all (95 percent) respondents use standardized methods in their sampling and 48 percent are familiar with the LTRM fish methodologies. Roughly one-third (35 percent) of all respondents have used the methods in the past and most (78 percent) of those have modified the methods to suit the information needs specific to their fishery. Results indicate that the LTRM methods have indeed spread outside the UMRR and are now a well-known and potentially widely used technique to sample fish communities.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","usgsCitation":"Solomon, L.E., and Casper, A.F., 2016, Documenting the use of the Long Term Resource Monitoring element’s fish monitoring methodologies throughout the Midwest: Long Term Resource Monitoring Technical Report 2016-T001, v, 15 p.","productDescription":"v, 15 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-067086","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":326397,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/mis/ltrmp2016-t001/ltrmp2016t001.pdf","text":"Report","size":"4.32 MB","linkFileType":{"id":1,"text":"pdf"},"description":"LTRM 2016-Too1"},{"id":326396,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/mis/ltrmp2016-t001/coverthb.jpg"}],"country":"United States","state":"Illinois, Iowa, Minnesota, Missouri, Wisconsin","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[-87.800477,42.49192],[-87.812461,42.232278],[-87.524844,41.691635],[-87.531646,39.347888],[-87.640435,39.166727],[-87.496537,38.778571],[-87.975511,38.232742],[-88.158207,37.664542],[-88.078046,37.532029],[-88.450127,37.411717],[-88.490068,37.067874],[-89.058036,37.188767],[-89.171881,37.068184],[-89.202607,36.601576],[-89.343753,36.630991],[-89.429311,36.481875],[-89.55264,36.577178],[-89.527029,36.341679],[-89.703511,36.243412],[-89.615128,36.113816],[-89.733095,36.000608],[-90.368718,35.995812],[-90.075934,36.281485],[-90.157136,36.484317],[-94.617919,36.499414],[-94.605734,39.122204],[-95.082714,39.516712],[-94.876344,39.806894],[-95.382957,40.027112],[-95.870481,40.71248],[-95.929889,41.415155],[-96.096186,41.547192],[-96.077543,41.777824],[-96.628741,42.757532],[-96.448134,43.104452],[-96.598396,43.495074],[-96.453049,43.500415],[-96.452948,45.268925],[-96.835451,45.586129],[-96.587093,45.816445],[-96.559271,46.058272],[-96.789572,46.639079],[-96.851293,47.589264],[-97.139497,48.153108],[-97.108655,48.691484],[-97.238387,48.982631],[-95.153711,48.998903],[-95.153314,49.384358],[-94.974286,49.367738],[-94.555835,48.716207],[-93.741843,48.517347],[-92.984963,48.623731],[-92.634931,48.542873],[-92.698824,48.494892],[-92.341207,48.23248],[-92.066269,48.359602],[-91.542512,48.053268],[-90.88548,48.245784],[-90.703702,48.096009],[-89.489226,48.014528],[-90.735927,47.624343],[-92.058888,46.809938],[-92.025789,46.710839],[-91.781928,46.697604],[-90.880358,46.957661],[-90.78804,46.844886],[-90.920813,46.637432],[-90.327548,46.550262],[-89.929158,46.29975],[-88.141001,45.930608],[-88.13364,45.823128],[-87.831442,45.714938],[-87.887828,45.358122],[-87.647454,45.345232],[-87.72796,45.207956],[-87.59188,45.094689],[-87.983065,44.72073],[-87.970702,44.530292],[-87.021088,45.296541],[-87.73063,43.893862],[-87.910172,43.236634],[-87.800477,42.49192]]],[[[-86.880572,45.331467],[-86.956192,45.351179],[-86.82177,45.427602],[-86.880572,45.331467]]]]},\"properties\":{\"name\":\"Iowa\",\"nation\":\"USA \"}}]}","contact":"Upper Midwest Environmental Science Center
2630 Fanta Reed Road
La Crosse, WI 54603
http://www.umesc.usgs.gov/
http://www.umesc.usgs.gov/ltrmp.html
Complex ecological networks appear robust to primary extinctions, possibly due to consumers’ tendency to specialize on dependable (available and persistent) resources. However, modifications to the conditions under which the network has evolved might alter resource dependability. Here, we ask whether adaptation to historical conditions can increase community robustness, and whether such robustness can protect communities from collapse when conditions change. Using artificial life simulations, we first evolved digital consumer-resource networks that we subsequently subjected to rapid environmental change. We then investigated how empirical host–parasite networks would respond to historical, random and expected extinction sequences. In both the cases, networks were far more robust to historical conditions than new ones, suggesting that new environmental challenges, as expected under global change, might collapse otherwise robust natural ecosystems.
","language":"English","publisher":"Springer Nature","doi":"10.1038/ncomms12462","collaboration":"European Commission Joint Research Centre","usgsCitation":"Strona, G., and Lafferty, K.D., 2016, Environmental change makes robust ecological networks fragile: Nature Communications, v. 7, Article 12462; 7 p., https://doi.org/10.1038/ncomms12462.","productDescription":"Article 12462; 7 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-075912","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":470659,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/ncomms12462","text":"Publisher Index Page"},{"id":326482,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2016-08-11","publicationStatus":"PW","scienceBaseUri":"57b2d9a6e4b03bcb010287ba","contributors":{"authors":[{"text":"Strona, Giovanni","contributorId":62940,"corporation":false,"usgs":true,"family":"Strona","given":"Giovanni","email":"","affiliations":[],"preferred":false,"id":645454,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lafferty, Kevin D. 0000-0001-7583-4593 klafferty@usgs.gov","orcid":"https://orcid.org/0000-0001-7583-4593","contributorId":1415,"corporation":false,"usgs":true,"family":"Lafferty","given":"Kevin","email":"klafferty@usgs.gov","middleInitial":"D.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":645453,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70175749,"text":"70175749 - 2016 - Development of targeted delivery techniques for Zequanox®","interactions":[],"lastModifiedDate":"2016-08-31T10:46:47","indexId":"70175749","displayToPublicDate":"2016-08-15T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":9,"text":"Other Report"},"title":"Development of targeted delivery techniques for Zequanox®","docAbstract":"The effects of water temperature and concentration on the physical characteristics of Zequanox®, a dead-cell spray-dried powder formulation of Pseudomonas fluorescens (strain CL145A) used for controlling invasive dreissenid mussels (zebra mussel, Dreissena polymorpha, and quagga mussel, Dreissena bugensis), were investigated to determine optimal temperature-specific concentrations and delivery techniques for use during open-water subsurface Zequanox applications. Temperature-controlled laboratory tests evaluated viscosity, settling, stratification, and buoyancy of various concentrations of Zequanox suspension in water to select an optimal target viscosity for Zequanox applications. A two-step linear regression procedure was used to create a temperature-specific Zequanox prediction model from the viscosity data. The prediction model and subsurface application techniques were validated by conducting three independent outdoor pond trials at temperatures of ~9, 14, and 20°C. During these outdoor trials, subsurface applications of Zequanox at concentrations predicted by the model were performed and water samples were collected at varying depths and analyzed via spectroscopy to determine Zequanox concentration and dispersion. Although the predicted Zequanox concentrations and delivery techniques used resulted in successfully maintaining lethal Zequanox concentrations in the bottom 7.5 cm of the water column for the duration of the exposure, a revised prediction model is also provided for more accurately selecting temperature-specific Zequanox concentrations.","language":"English","publisher":"Legislative-Citizen Commission on Minnesota Resources (LCCMR)","usgsCitation":"Severson, T.J., and Luoma, J.A., 2016, Development of targeted delivery techniques for Zequanox®, 14 p.","productDescription":"14 p.","ipdsId":"IP-077367","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":328102,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":326870,"type":{"id":15,"text":"Index Page"},"url":"https://www.lccmr.leg.mn/projects/2013-index.html#201306f"}],"publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57c7ffb0e4b0f2f0cebfc231","contributors":{"authors":[{"text":"Severson, Todd J. 0000-0001-5282-3779 tseverson@usgs.gov","orcid":"https://orcid.org/0000-0001-5282-3779","contributorId":4749,"corporation":false,"usgs":true,"family":"Severson","given":"Todd","email":"tseverson@usgs.gov","middleInitial":"J.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":646302,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Luoma, James A. 0000-0003-3556-0190 jluoma@usgs.gov","orcid":"https://orcid.org/0000-0003-3556-0190","contributorId":4449,"corporation":false,"usgs":true,"family":"Luoma","given":"James","email":"jluoma@usgs.gov","middleInitial":"A.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":646303,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70176234,"text":"70176234 - 2016 - The sensitivity of WRF downscaled precipitation in Puerto Rico to cumulus parameterization and interior grid nudging","interactions":[],"lastModifiedDate":"2016-10-21T13:21:01","indexId":"70176234","displayToPublicDate":"2016-08-15T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5202,"text":"Journal of Applied Meteorology and Climatology","onlineIssn":"1558-8432","printIssn":"1558-8424","active":true,"publicationSubtype":{"id":10}},"title":"The sensitivity of WRF downscaled precipitation in Puerto Rico to cumulus parameterization and interior grid nudging","docAbstract":"The sensitivity of the Weather Research and Forecasting Model (WRF) simulated precipitation\nover Puerto Rico is evaluated using multiple combinations of cumulus parameterization (CP)\nschemes and interior grid nudging. NCEP-DOE AMIP-II reanalysis (R-2) is downscaled to 2-\n km horizontal grid spacing with both convective permitting simulations (CP active only in the 49 middle and outer domains) and CP schemes active in all domains. The results generally show\nlower simulated precipitation amounts compared to the observations, regardless of WRF\nconfiguration. However, activating the CP schemes in the inner domain improves the annual cycle, intensity, and placement of rainfall compared to the convective permitting simulations.\nFurthermore, the use of interior grid nudging techniques in the outer domains improves the\nplacement and intensity of rainfall in the inner domain. Incorporating a CP scheme at convective\npermitting scales (< 4 km) and grid nudging at non-convective permitting scales (> 4 km)\nimproves the island average correlation of precipitation by 0.05 to 0.2 and reduces the island\naverage RMSE by up to 40 mm on average over relying on the explicit microphysics at\nconvective permitting scales with grid nudging. Projected changes in summer precipitation between 2040-2042 and 1985-1987 using WRF to downscale CCSM4 ranges from a 2.6 mm\naverage increase to 81.9 mm average decrease, depending on the choice of CP scheme. The differences are only associated with differences between WRF configurations, which indicates\nthe importance of CP scheme for projected precipitation change as well as historical accuracy.","language":"English","publisher":"American Meteorology Society","doi":"10.1175/JAMC-D-16-0121.1","usgsCitation":"Wootten, A., Bowden, J., Boyles, R., and Terando, A.J., 2016, The sensitivity of WRF downscaled precipitation in Puerto Rico to cumulus parameterization and interior grid nudging: Journal of Applied Meteorology and Climatology, v. 55, p. 2263-2281, https://doi.org/10.1175/JAMC-D-16-0121.1.","productDescription":"19 p.","startPage":"2263","endPage":"2281","ipdsId":"IP-076983","costCenters":[{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true}],"links":[{"id":470662,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1175/jamc-d-16-0121.1","text":"Publisher Index 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University","active":true,"usgs":false}],"preferred":false,"id":647986,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Terando, Adam J. 0000-0002-9280-043X aterando@usgs.gov","orcid":"https://orcid.org/0000-0002-9280-043X","contributorId":173447,"corporation":false,"usgs":true,"family":"Terando","given":"Adam","email":"aterando@usgs.gov","middleInitial":"J.","affiliations":[{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":647983,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70175101,"text":"sir20165109 - 2016 - Network global navigation satellite system survey to harmonize water-surface elevation data for the Rainy River Basin","interactions":[],"lastModifiedDate":"2016-08-15T13:49:05","indexId":"sir20165109","displayToPublicDate":"2016-08-15T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-5109","title":"Network global navigation satellite system survey to harmonize water-surface elevation data for the Rainy River Basin","docAbstract":"Continuously recording water-level streamgages in Rainy Lake and Namakan Reservoir are used to regulate water levels according to rule curves established in 2000 by the International Joint Commission; however, water levels at streamgages were referenced to a variety of vertical datums, confounding efforts to model the flow of water through the system, regulate water levels during periods of high inflow, and evaluate the effectiveness of the rule curves. In October 2014, the U.S. Geological Survey, Natural Resources Canada, International Joint Commission, and National Park Service began a joint field study with the goal of obtaining precise elevations referenced to a uniform vertical datum for all reference marks used to set water levels at streamgages throughout Rainy Lake and Namakan Reservoir. This report was prepared by the U.S. Geological Survey in cooperation with Natural Resources Canada, International Joint Commission, and National Park Service.
Three field crews deployed Global Navigation Satellite System receivers statically over 16 reference marks colocated with active and discontinued water-level streamgages throughout Rainy River, Rainy Lake, Namakan Reservoir, and select tributaries of Rainy Lake and Namakan Reservoir. A Global Navigation Satellite System receiver also was deployed statically over a National Geodetic Survey cooperative base network control station for use as a quality-control reference mark. Satellite data were collected simultaneously during a 5-day period and processed independently by the U.S. Geological Survey and Natural Resources Canada to obtain accurate positioning and elevations for the 17 surveyed reference marks. Processed satellite data were used to convert published water levels to elevations above sea level referenced to the Canadian Geodetic Vertical Datum of 2013 in order to compare water-surface elevations referenced to a uniform vertical datum throughout the study area. In this report, an “offset” refers to the correction applied to published data from a particular streamgage to produce elevation data referenced to a specified vertical datum.
Offsets were applied to water-level data from surveyed streamgages to further evaluate the accuracy and utility of updated reference mark elevations presented in this report. Daily mean water levels from active streamgages surveyed in this study were converted to water-surface elevations referenced to the Canadian Geodetic Vertical Datum of 2013. Graphical comparisons of water-surface elevations for streamgages in Namakan Reservoir, Rainy Lake, and selected rivers are presented (referencing the Canadian Geodetic Vertical Datum of 2013). Offsets presented in this report can be used in the evaluation of rule curves and in flood damage curves that fully assess the benefits of one regulation approach over another. In addition, offsets may be used to calibrate hydraulic models developed for four narrows that connect lakes of Namakan Reservoir, refine digital elevation models, and support modeling studies designed to assess the effects of rule curves on aquatic vegetation, benthic invertebrates, northern pike, and walleye.
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In steep topography, the processes governing variably saturated subsurface hydrologic response and the interparticle stresses leading to shallow landslide initiation are physically linked. However, these processes are usually analyzed separately. Here, we take a combined approach, simultaneously analyzing the influence of topography on both hillslope hydrology and the effective stress fields within the hillslope itself. Clearly, runoff and saturated groundwater flow are dominated by gravity and, ultimately, by topography. Less clear is how landscape morphology influences flows in the vadose zone, where transient fluxes are usually taken to be vertical. We aim to assess and quantify the impact of topography on both saturated and unsaturated hillslope hydrology and its effects on shallow slope stability. Three real hillslope morphologies (concave, convex, and planar) are analyzed using a 3-D, physically based, distributed model coupled with a module for computation of the probability of failure, based on the infinite slope assumption. The results of the analyses, which included parameter uncertainty analysis of the results themselves, show that convex and planar slopes are more stable than concave slopes. Specifically, under the same initial, boundary, and infiltration conditions, the percentage of unstable areas ranges from 1.3% for the planar hillslope, 21% for convex, to a maximum value of 33% for the concave morphology. The results are supported by a sensitivity analysis carried out to examine the effect of initial conditions and rainfall intensity.
","language":"English","publisher":"AGU Publications","doi":"10.1002/2015WR017626","usgsCitation":"Giuseppe, F., Simoni, S., Godt, J.W., Lu, N., and Rigon, R., 2016, Geomorphological control on variably saturated hillslope hydrology and slope instability: Water Resources Research, v. 52, no. 6, p. 4590-4607, https://doi.org/10.1002/2015WR017626.","productDescription":"18 p.","startPage":"4590","endPage":"4607","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070797","costCenters":[{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true}],"links":[{"id":326470,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"52","issue":"6","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-18","publicationStatus":"PW","scienceBaseUri":"57aee525e4b0fc09faadbd3e","contributors":{"authors":[{"text":"Giuseppe, Formetta","contributorId":173665,"corporation":false,"usgs":false,"family":"Giuseppe","given":"Formetta","email":"","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":645393,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Simoni, Silvia","contributorId":173666,"corporation":false,"usgs":false,"family":"Simoni","given":"Silvia","email":"","affiliations":[{"id":27269,"text":"Mountain-eering Srl, Bolzano, Italy","active":true,"usgs":false}],"preferred":false,"id":645394,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Godt, Jonathan W. 0000-0002-8737-2493 jgodt@usgs.gov","orcid":"https://orcid.org/0000-0002-8737-2493","contributorId":1166,"corporation":false,"usgs":true,"family":"Godt","given":"Jonathan","email":"jgodt@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true}],"preferred":true,"id":645392,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lu, Ning","contributorId":191360,"corporation":false,"usgs":false,"family":"Lu","given":"Ning","email":"","affiliations":[{"id":12620,"text":"U.S. Army Corp. of Engineers","active":true,"usgs":false}],"preferred":false,"id":645395,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rigon, Riccardo","contributorId":152464,"corporation":false,"usgs":false,"family":"Rigon","given":"Riccardo","email":"","affiliations":[{"id":18929,"text":"Unversita di Trento","active":true,"usgs":false}],"preferred":false,"id":645396,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70175467,"text":"70175467 - 2016 - Divergent projections of future land use in the United States arising from different models and scenarios","interactions":[],"lastModifiedDate":"2017-08-29T09:36:55","indexId":"70175467","displayToPublicDate":"2016-08-12T12:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Divergent projections of future land use in the United States arising from different models and scenarios","docAbstract":"A variety of land-use and land-cover (LULC) models operating at scales from local to global have been developed in recent years, including a number of models that provide spatially explicit, multi-class LULC projections for the conterminous United States. This diversity of modeling approaches raises the question: how consistent are their projections of future land use? We compared projections from six LULC modeling applications for the United States and assessed quantitative, spatial, and conceptual inconsistencies. Each set of projections provided multiple scenarios covering a period from roughly 2000 to 2050. Given the unique spatial, thematic, and temporal characteristics of each set of projections, individual projections were aggregated to a common set of basic, generalized LULC classes (i.e., cropland, pasture, forest, range, and urban) and summarized at the county level across the conterminous United States. We found very little agreement in projected future LULC trends and patterns among the different models. Variability among scenarios for a given model was generally lower than variability among different models, in terms of both trends in the amounts of basic LULC classes and their projected spatial patterns. Even when different models assessed the same purported scenario, model projections varied substantially. Projections of agricultural trends were often far above the maximum historical amounts, raising concerns about the realism of the projections. Comparisons among models were hindered by major discrepancies in categorical definitions, and suggest a need for standardization of historical LULC data sources. To capture a broader range of uncertainties, ensemble modeling approaches are also recommended. However, the vast inconsistencies among LULC models raise questions about the theoretical and conceptual underpinnings of current modeling approaches. Given the substantial effects that land-use change can have on ecological and societal processes, there is a need for improvement in LULC theory and modeling capabilities to improve acceptance and use of regional- to national-scale LULC projections for the United States and elsewhere.
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Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Applying the collective impact approach to address non-native species: A case study of the Great Lakes Phragmites Collaborative","docAbstract":"To address the invasion of non-native Phragmites in the Great Lakes, researchers at the U.S. Geological Survey—Great Lakes Science Center partnered with the Great Lakes Commission in 2012 to establish the Great Lakes Phragmites Collaborative (GLPC). The GLPC is a regional-scale partnership established to improve collaboration among stakeholders and increase the effectiveness of non-native Phragmites management and research. Rather than forming a traditional partnership with a narrowly defined goal, the GLPC follows the principles of collective impact to engage stakeholders, guide progress, and align resources to address this complex, regional challenge. In this paper, the concept and tenets of collective impact are described, the GLPC is offered as a model for other natural resource-focused collective impact efforts, and steps for establishing collaboratives are presented. Capitalizing on the interactive collective impact approach, the GLPC is moving toward a broadly accepted common agenda around which agencies and individuals will be able to better align their actions and generate measureable progress in the regional campaign to protect healthy, diverse ecosystems from damage caused by non-native Phragmites.
","language":"English","publisher":"Kluwer Academic Publishers","doi":"10.1007/s10530-016-1142-1","usgsCitation":"Braun, H.B., Kowalski, K., and Hollins, K., 2016, Applying the collective impact approach to address non-native species: A case study of the Great Lakes Phragmites Collaborative: Biological Invasions, v. 18, no. 9, p. 2729-2738, https://doi.org/10.1007/s10530-016-1142-1.","productDescription":"10 p.","startPage":"2729","endPage":"2738","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069939","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":326447,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"18","issue":"9","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-22","publicationStatus":"PW","scienceBaseUri":"57aee524e4b0fc09faadbd36","contributors":{"authors":[{"text":"Braun, H. B.","contributorId":173652,"corporation":false,"usgs":false,"family":"Braun","given":"H.","email":"","middleInitial":"B.","affiliations":[{"id":13509,"text":"Great Lakes Commission","active":true,"usgs":false}],"preferred":false,"id":645344,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kowalski, Kurt P. 0000-0002-8424-4701 kkowalski@usgs.gov","orcid":"https://orcid.org/0000-0002-8424-4701","contributorId":3768,"corporation":false,"usgs":true,"family":"Kowalski","given":"Kurt P.","email":"kkowalski@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":645343,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hollins, K.","contributorId":173653,"corporation":false,"usgs":false,"family":"Hollins","given":"K.","email":"","affiliations":[{"id":13509,"text":"Great Lakes Commission","active":true,"usgs":false}],"preferred":false,"id":645345,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70175464,"text":"70175464 - 2016 - Evaluation of the functional roles of fungal endophytes of Phragmites australis from high saline and low saline habitats","interactions":[],"lastModifiedDate":"2016-09-16T15:47:38","indexId":"70175464","displayToPublicDate":"2016-08-12T10:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1018,"text":"Biological Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of the functional roles of fungal endophytes of Phragmites australis from high saline and low saline habitats","docAbstract":"Non-native Phragmites australis decreases biodiversity and produces dense stands in North America. We surveyed the endophyte communities in the stems, leaves and roots of collections of P. australis obtained from two sites with a low and high salt concentration to determine differences in endophyte composition and assess differences in functional roles of microbes in plants from both sites. We found differences in the abundance, richness and diversity of endophytes between the low saline collections (18 species distributed in phyla Ascomycota, Basidiomycota and Stramenopiles (Oomycota); from orders Dothideales, Pleosporales, Hypocreales, Eurotiales, Cantharellales and Pythiales; Shannon H = 2.639; Fisher alpha = 7.335) and high saline collections (15 species from phylum Ascomycota; belonging to orders Pleosporales, Hypocreales, Diaporthales, Xylariales and Dothideales; Shannon H = 2.289; Fisher alpha = 4.181). Peyronellaea glomerata, Phoma macrostoma and Alternaria tenuissima were species obtained from both sites. The high salt endophyte community showed higher resistance to zinc, mercury and salt stress compared to fungal species from the low salt site. These endophytes also showed a greater propensity for growth promotion of rice seedlings (a model species) under salt stress. The results of this study are consistent with the ‘habitat-adapted symbiosis hypothesis’ that holds that endophytic microbes may help plants adapt to extreme habitats. The capacity of P. australis to establish symbiotic relationships with diverse endophytic microbes that enhance its tolerance to abiotic stresses could be a factor that contributes to its invasiveness in saline environments. Targeting the symbiotic associates of P. australis could lead to more sustainable control of non-native P. australis.
","language":"English","publisher":"Springer","doi":"10.1007/s10530-016-1160-z","usgsCitation":"Soares, M.A., Li, H., Kowalski, K., Bergen, M., Torres, M.S., and White, J., 2016, Evaluation of the functional roles of fungal endophytes of Phragmites australis from high saline and low saline habitats: Biological Invasions, v. 18, no. 9, p. 2689-2702, https://doi.org/10.1007/s10530-016-1160-z.","productDescription":"14 p.","startPage":"2689","endPage":"2702","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069877","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":326446,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"18","issue":"9","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-09","publicationStatus":"PW","scienceBaseUri":"57aee525e4b0fc09faadbd3c","contributors":{"authors":[{"text":"Soares, Marcos Antonio","contributorId":151011,"corporation":false,"usgs":false,"family":"Soares","given":"Marcos","email":"","middleInitial":"Antonio","affiliations":[{"id":18163,"text":"Federal University of Mato Grosso","active":true,"usgs":false}],"preferred":false,"id":645347,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Li, Hai-Yan","contributorId":173654,"corporation":false,"usgs":false,"family":"Li","given":"Hai-Yan","email":"","affiliations":[{"id":18164,"text":"Kunming University of Science and Technology","active":true,"usgs":false}],"preferred":false,"id":645348,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kowalski, Kurt P. 0000-0002-8424-4701 kkowalski@usgs.gov","orcid":"https://orcid.org/0000-0002-8424-4701","contributorId":3768,"corporation":false,"usgs":true,"family":"Kowalski","given":"Kurt P.","email":"kkowalski@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":645346,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bergen, Marshall","contributorId":151013,"corporation":false,"usgs":false,"family":"Bergen","given":"Marshall","affiliations":[{"id":12727,"text":"Rutgers University","active":true,"usgs":false}],"preferred":false,"id":645349,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Torres, Monica S.","contributorId":152047,"corporation":false,"usgs":false,"family":"Torres","given":"Monica","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":645350,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"White, James F.","contributorId":152046,"corporation":false,"usgs":false,"family":"White","given":"James F.","affiliations":[],"preferred":false,"id":645351,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70164332,"text":"70164332 - 2016 - A long-term evaluation of biopsy darts and DNA to estimate cougar density","interactions":[],"lastModifiedDate":"2016-12-13T16:44:03","indexId":"70164332","displayToPublicDate":"2016-08-12T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3779,"text":"Wildlife Society Bulletin","onlineIssn":"1938-5463","printIssn":"0091-7648","active":true,"publicationSubtype":{"id":10}},"title":"A long-term evaluation of biopsy darts and DNA to estimate cougar density","docAbstract":"Accurately estimating cougar (Puma concolor) density is usually based on long-term research consisting of intensive capture and Global Positioning System collaring efforts and may cost hundreds of thousands of dollars annually. Because wildlife agency budgets rarely accommodate this approach, most infer cougar density from published literature, rely on short-term studies, or use hunter harvest data as a surrogate in their jurisdictions; all of which may limit accuracy and increase risk of management actions. In an effort to develop a more cost-effective long-term strategy, we evaluated a research approach using citizen scientists with trained hounds to tree cougars and collect tissue samples with biopsy darts. We then used the DNA to individually identify cougars and employed spatially explicit capture–recapture models to estimate cougar densities. Overall, 240 tissue samples were collected in northeastern Washington, USA, producing 166 genotypes (including recaptures and excluding dependent kittens) of 133 different cougars (8-25/yr) from 2003 to 2011. Mark–recapture analyses revealed a mean density of 2.2 cougars/100 km2 (95% CI=1.1-4.3) and stable to decreasing population trends (β=-0.048, 95% CI=-0.106–0.011) over the 9 years of study, with an average annual harvest rate of 14% (range=7-21%). The average annual cost per year for field sampling and genotyping was US$11,265 ($422.24/sample or $610.73/successfully genotyped sample). Our results demonstrated that long-term biopsy sampling using citizen scientists can increase capture success and provide reliable cougar-density information at a reasonable cost.
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2016 - Potential postwildfire debris-flow hazards—A prewildfire evaluation for the Jemez Mountains, north-central New Mexico","interactions":[],"lastModifiedDate":"2016-08-11T14:35:08","indexId":"sir20165101","displayToPublicDate":"2016-08-11T12:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-5101","title":"Potential postwildfire debris-flow hazards—A prewildfire evaluation for the Jemez Mountains, north-central New Mexico","docAbstract":"Wildfire can substantially increase the probability of debris flows, a potentially hazardous and destructive form of mass wasting, in landscapes that have otherwise been stable throughout recent history. Although the exact location, extent, and severity of wildfire or subsequent rainfall intensity and duration cannot be known, probabilities of fire and debris‑flow occurrence for given locations can be estimated with geospatial analysis and modeling. The purpose of this report is to provide information on which watersheds might constitute the most serious potential debris-flow hazards in the event of a large-scale wildfire and subsequent rainfall in the Jemez Mountains. Potential probabilities and estimated volumes of postwildfire debris flows in both the unburned and previously burned areas of the Jemez Mountains and surrounding areas were estimated using empirical debris-flow models developed by the U.S. Geological Survey in combination with fire behavior and burn probability models developed by the U.S. Forest Service.
Of the 4,998 subbasins modeled for this study, computed debris-flow probabilities in 671 subbasins were greater than 80 percent in response to the 100-year recurrence interval, 30-minute duration rainfall event. These subbasins ranged in size from 0.01 to 6.57 square kilometers (km2), with an average area of 0.29 km2, and were mostly steep, upstream tributaries to larger channels in the area. Modeled debris-flow volumes in 465 subbasins were greater than 10,000 cubic meters (m3), and 14 of those subbasins had modeled debris‑flow volumes greater than 100,000 m3.
The rankings of integrated relative debris-flow hazard indexes for each subbasin were generated by multiplying the individual subbasin values for debris-flow volume, debris‑flow probability, and average burn probability. The subbasins with integrated hazard index values in the top 2 percent typically are large, upland tributaries to canyons and channels primarily in the Upper Rio Grande and Rio Grande-Santa Fe watershed areas. No subbasins in this group have basin areas less than 1.0 km2. Many of these areas already had significant mass‑wasting episodes following the Las Conchas Fire in 2011. Other subbasins with integrated hazard index values in the top 2 percent are scattered throughout the Jemez River watershed area, including some subbasins in the interior of the Valles Caldera. Only a few subbasins in the top integrated hazard index group are in the Rio Chama watershed area.
This prewildfire assessment approach is valuable to resource managers because the analysis of the debris-flow threat is made before a wildfire occurs, which facilitates prewildfire management, planning, and mitigation. In north‑central New Mexico, widespread watershed restoration efforts are being done to safeguard vital watersheds against the threat of catastrophic wildfire. This study was designed to help select ideal locations for the restoration efforts that could have the best return on investment.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165101","collaboration":"Prepared in cooperation with the Buckman Direct Diversion Board, U.S. Forest Service, Albuquerque/Bernalillo County Water Utility Authority, U.S. Army Corps of Engineers, and Los Alamos County","usgsCitation":"Tillery, A.C., and Haas, J.R., 2016, Potential postwildfire debris-flow hazards—A prewildfire evaluation for the Jemez Mountains, north-central New Mexico: U.S. Geological Survey Scientific-Investigations Report 2016-5101, 27 p., https://dx.doi.org/10.3133/sir20165101.","productDescription":"Report: vi, 27 p.; Interactive Map; GIS Files","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-070303","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":326371,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5101/sir20165101.pdf","text":"Report","size":"5.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5101"},{"id":326373,"rank":4,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/sir/2016/5101/sir20165101_map100yr.html","text":"Interactive Map","linkFileType":{"id":5,"text":"html"},"description":"SIR 2016-5101 Interacative Map"},{"id":326370,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5101/coverthb.jpg"},{"id":326372,"rank":3,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sir/2016/5101/sir20165101_gis.zip","text":"GIS Files","size":"88.9 MB","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2016-5101 Spatial Data"}],"country":"United States","state":"New Mexico","otherGeospatial":"Jemez Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.4410400390625,\n 36.22876574685929\n ],\n [\n -106.42044067382812,\n 36.2354121683998\n ],\n [\n -106.35589599609375,\n 36.21214722153981\n ],\n [\n -106.32293701171874,\n 36.20771501855801\n ],\n [\n -106.26113891601562,\n 36.21436322889413\n ],\n [\n -106.21719360351562,\n 36.18333341549503\n ],\n [\n -106.19110107421875,\n 36.14341987311765\n ],\n [\n -106.15402221679688,\n 36.097938036628065\n ],\n [\n -106.14715576171875,\n 36.06464195517141\n ],\n [\n -106.1334228515625,\n 36.030221194310705\n ],\n [\n -106.11557006835938,\n 35.991340960635405\n ],\n [\n -106.12518310546875,\n 35.94910642813857\n ],\n [\n -106.14578247070312,\n 35.9357645138553\n ],\n [\n -106.14578247070312,\n 35.89795019335754\n ],\n [\n -106.15676879882812,\n 35.85455268869835\n ],\n [\n -106.17050170898438,\n 35.82560781396722\n ],\n [\n -106.18698120117188,\n 35.806676609227054\n ],\n [\n -106.20758056640625,\n 35.782170703266075\n ],\n [\n -106.22543334960938,\n 35.76991491635478\n ],\n [\n -106.25015258789062,\n 35.75765724051559\n ],\n [\n -106.25976562499999,\n 35.735365718650236\n ],\n [\n -106.29547119140625,\n 35.7097227520928\n ],\n [\n -106.31332397460938,\n 35.69299463209881\n ],\n [\n -106.36962890624999,\n 35.689648586960935\n ],\n [\n -106.40533447265625,\n 35.689648586960935\n ],\n [\n -106.44241333007812,\n 35.68295607559029\n ],\n [\n -106.52069091796875,\n 35.67514743608467\n ],\n [\n -106.578369140625,\n 35.67626300279665\n ],\n [\n -106.61544799804688,\n 35.67737855391475\n ],\n [\n -106.66351318359375,\n 35.6807251137039\n ],\n [\n -106.69921875,\n 35.68295607559029\n ],\n [\n -106.74041748046875,\n 35.69745580725804\n ],\n [\n -106.77200317382812,\n 35.71641301732958\n ],\n [\n -106.776123046875,\n 35.753199435570316\n ],\n [\n -106.7816162109375,\n 35.817813158696616\n ],\n [\n -106.79397583007812,\n 35.8723596690896\n ],\n [\n -106.79946899414062,\n 35.91129848822746\n ],\n [\n -106.79534912109375,\n 35.96244608979167\n ],\n [\n -106.79946899414062,\n 35.99800750540412\n ],\n [\n -106.80496215820312,\n 36.01133890448606\n ],\n [\n -106.81732177734375,\n 36.02799998329553\n ],\n [\n -106.8145751953125,\n 36.05020927487619\n ],\n [\n -106.8035888671875,\n 36.06908224732973\n ],\n [\n -106.79397583007812,\n 36.08795069273044\n ],\n [\n -106.75003051757812,\n 36.09127994838079\n ],\n [\n -106.68960571289062,\n 36.09904766316007\n ],\n [\n -106.68685913085938,\n 36.11901826100922\n ],\n [\n -106.68136596679686,\n 36.130110843400146\n ],\n [\n -106.67037963867188,\n 36.140092827322654\n ],\n [\n -106.644287109375,\n 36.16116173423654\n ],\n [\n -106.62094116210938,\n 36.18111652966563\n ],\n [\n -106.59210205078125,\n 36.19109202182454\n ],\n [\n -106.53579711914062,\n 36.1955251660701\n ],\n [\n -106.49734497070312,\n 36.19884985954492\n ],\n [\n -106.44515991210938,\n 36.20882309283712\n ],\n [\n -106.4410400390625,\n 36.22876574685929\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New Mexico Water Science Center
U.S. Geological Survey
5338 Montgomery Blvd. NE
Albuquerque, New Mexico 87109
http://nm.water.usgs.gov
Climate change impacts ecosystems in many ways, from effects on species to phenology to wildfire dynamics. Assessing the potential vulnerability of ecosystems to future changes in climate is an important first step in prioritizing and planning for conservation. Although assessments of climate change vulnerability commonly are done for species, fewer have been done for ecosystems. To aid regional conservation planning efforts, we assessed climate change vulnerability for ecosystems in the Southeastern United States and Caribbean.
First, we solicited input from experts to create a list of candidate ecosystems for assessment. From that list, 12 ecosystems were selected for a vulnerability assessment that was based on a synthesis of available geographic information system (GIS) data and literature related to 3 components of vulnerability—sensitivity, exposure, and adaptive capacity. This literature and data synthesis comprised “Phase I” of the assessment. Sensitivity is the degree to which the species or processes in the ecosystem are affected by climate. Exposure is the likely future change in important climate and sea level variables. Adaptive capacity is the degree to which ecosystems can adjust to changing conditions. Where available, GIS data relevant to each of these components were used. For example, we summarized observed and projected climate, protected areas existing in 2011, projected sea-level rise, and projected urbanization across each ecosystem’s distribution. These summaries were supplemented with information in the literature, and a short narrative assessment was compiled for each ecosystem. We also summarized all information into a qualitative vulnerability rating for each ecosystem.
Next, for 2 of the 12 ecosystems (East Gulf Coastal Plain Near-Coast Pine Flatwoods and Nashville Basin Limestone Glade and Woodland), the NatureServe Habitat Climate Change Vulnerability Index (HCCVI) framework was used as an alternative approach for assessing vulnerability. Use of the HCCVI approach comprised “Phase II” of the assessment. This approach uses summaries of GIS data and models to develop a series of numeric indices for components of vulnerability. We incorporated many of the data sources used in Phase I, but added the results of several other data sources, including climate envelope modeling and vegetation dynamics modeling. The results of Phase II were high and low numeric vulnerability ratings for mid-century and the end of century for each ecosystem. The high and low ratings represented the potential range of vulnerability scores owing to uncertainties in future climate conditions and ecosystem effects.
Of the 12 ecosystems assessed in the first approach, five were rated as having high vulnerability (Caribbean Coastal Mangrove, Caribbean Montane Wet Elfin Forest, East Gulf Coastal Plain Southern Loess Bluff Forest, Edwards Plateau Limestone Shrubland, and Nashville Basin Limestone Glade and Woodland). Six ecosystems had medium vulnerability, and one ecosystem had low vulnerability. For the two ecosystems assessed with both approaches, vulnerability ratings generally agreed. The assessment concluded by comparing the two approaches, identifying critical research needs, and making suggestions for future ecosystem vulnerability assessments in the Southeast and beyond. Research needs include reducing uncertainty in the degree of climate exposure likely in the future, as well as acquiring more information on how climate might affect biotic interactions and hydrologic processes. Ideally, a comprehensive vulnerability assessment would include both the narrative summaries that resulted from the synthesis in Phase I, as well as a numeric index that incorporates uncertainty as in Phase II.
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\"}}]}","contact":"Director, South Atlantic Water Science Center
U.S. Geological Survey
3916 Sunset Ridge Rd
Raleigh, N.C. 27607
http://nc.water.usgs.gov/
Water from the Little Arkansas River is used as source water for artificial recharge of the Equus Beds aquifer, one of the primary water-supply sources for the city of Wichita, Kansas. The U.S. Geological Survey has operated two continuous real-time water-quality monitoring stations since 1995 on the Little Arkansas River in Kansas. Regression models were developed to establish relations between discretely sampled constituent concentrations and continuously measured physical properties to compute concentrations of those constituents of interest. Site-specific regression models were originally published in 2000 for the near Halstead and near Sedgwick U.S. Geological Survey streamgaging stations and the site-specific regression models were then updated in 2003. This report updates those regression models using discrete and continuous data collected during May 1998 through August 2014. In addition to the constituents listed in the 2003 update, new regression models were developed for total organic carbon. The real-time computations of water-quality concentrations and loads are available at http://nrtwq.usgs.gov. The water-quality information in this report is important to the city of Wichita because water-quality information allows for real-time quantification and characterization of chemicals of concern (including chloride), in addition to nutrients, sediment, bacteria, and atrazine transported in the Little Arkansas River. The water-quality information in this report aids in the decision making for water treatment before artificial recharge.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161057","collaboration":"Prepared in cooperation with the city of Wichita, Kansas","usgsCitation":"Rasmussen, P.P., Eslick, P.J., and Ziegler, A.C., 2016, Relations between continuous real-time physical properties and discrete water-quality constituents in the Little Arkansas River, south-central Kansas, 1998-2014: U.S. Geological Survey Open-File Report 2016–1057, 20 p., https://dx.doi.org/10.3133/ofr20161057.","productDescription":"Report: ii, 16 p.; Appendixes 1-2","numberOfPages":"21","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-073013","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":326275,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1057/ofr20161057.pdf","text":"Report","size":"783 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016–1057"},{"id":326274,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1057/coverthb.jpg"},{"id":326280,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2016/1057/ofr20161057_appendix2.pdf","text":"Appendix 2","size":"2.90 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016–1057 Appendix 2"},{"id":326276,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2016/1057/ofr20161057_appendix1.pdf","text":"Appendix 1","size":"2.65 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016–1057 Appendix 1"}],"country":"United States","state":"Kansas","otherGeospatial":"Little Arkansas River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -98.2,\n 37.75\n ],\n [\n -98.2,\n 38.6\n ],\n [\n -97.25,\n 38.6\n ],\n [\n -97.25,\n 37.75\n ],\n [\n -98.2,\n 37.75\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Kansas Water Science Center
U.S. Geological Survey
4821 Quail Crest Place
Lawrence, KS 66049
Dissolved-selenium loading analyses of data collected at 18 water-quality sites in the lower Gunnison River Basin in Colorado were completed through water year (WY) 2014. A WY is defined as October 1–September 30. Selenium is a trace element that bioaccumulates in aquatic food chains and can cause reproductive failure, deformities, and other harmful effects. This report presents information on the dissolved-selenium loads at 18 sites in the lower Gunnison River Basin for WYs 2011–2014. Annual dissolved-selenium loads were calculated at 5 sites with continuous U.S. Geological Survey (USGS) streamflow gages, whereas instantaneous dissolved-selenium loads were calculated for the remaining 13 sites using water-quality samples that had been collected periodically during WYs 2011–2014. Annual dissolved-selenium loads for WY 2014 ranged from 336 pounds (lb) at Uncompahgre River at Colona to 13,300 lb at Gunnison River near Grand Junction (Whitewater). Most sites in the basin had a median instantaneous dissolved-selenium load of less than 20.0 lb per day. In general, dissolved-selenium loads at Gunnison River main-stem sites showed an increase from upstream to downstream.
The State of Colorado water-quality standard for dissolved selenium of 4.6 micrograms per liter (µg/L) was compared to the 85th percentiles for dissolved selenium at selected water-quality sites. Annual 85th percentiles for dissolved selenium were calculated for the five core USGS sites having streamflow gages using estimated dissolved-selenium concentrations from linear regression models. These annual 85th percentiles in WY 2014 ranged from 0.97 µg/L at Uncompahgre River at Colona to 16.7 µg/L at Uncompahgre River at Delta. Uncompahgre River at Delta and Whitewater were the only core sites where water samples exceeded the State of Colorado water-quality standard for dissolved selenium of 4.6 µg/L.
Instantaneous 85th percentiles for dissolved selenium were calculated for sites with sufficient data using water-quality samples collected during WYs 2011–2014. The instantaneous 85th percentiles for samples for WY 2014 ranged from 1.1 µg/L at Uncompahgre River at Colona to 125 µg/L at Loutzenhizer Arroyo at North River Road.
A trend analysis was completed for Whitewater to determine if dissolved-selenium loads are increasing or decreasing. The trend analysis indicates a decrease of 8,000 lb from WY 1986 to WY 2014, a 34.8 percent reduction during the time period, and an additional 6.2 percent reduction from a reported 28.6 percent reduction during WYs 1986–2008. The trend analysis for WY 1992 to WY 2014 indicates a decrease of 5,800 lb per year, or 27.9 percent.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161129","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Henneberg, M.F., 2016, 2014 annual summary of the lower Gunnison River Basin Selenium Management Program water-quality monitoring, Colorado: U.S. Geological Survey Open-File Report 2016–1129, 25 p., https://dx.doi.org/10.3133/ofr20161129. ","productDescription":"iv, 26 p.","numberOfPages":"30","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-076878","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":326308,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1129/ofr20161129.pdf","text":"Report","size":"3.15 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1129"},{"id":326307,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1129/coverthb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Lower Gunnison River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.39935302734375,\n 39.095962936305504\n ],\n [\n -108.270263671875,\n 39.059716474034666\n ],\n [\n -108.160400390625,\n 39.03838632847038\n ],\n [\n -107.99011230468749,\n 39.06824672852526\n ],\n [\n -107.874755859375,\n 39.095962936305504\n ],\n [\n -107.786865234375,\n 39.089567854849314\n ],\n [\n -107.70172119140624,\n 39.0533181067413\n ],\n [\n -107.6055908203125,\n 38.976492485539424\n ],\n [\n -107.6055908203125,\n 38.805470223177466\n ],\n [\n -107.70721435546875,\n 38.62116234642254\n ],\n [\n -107.808837890625,\n 38.43207668538204\n ],\n [\n -107.841796875,\n 38.28131307922969\n ],\n [\n -107.81982421874999,\n 38.048091067457236\n ],\n [\n -107.81982421874999,\n 37.95286091815649\n ],\n [\n -107.92144775390625,\n 37.91820111976663\n ],\n [\n -108.0120849609375,\n 37.91603433975963\n ],\n [\n -108.15216064453125,\n 37.94203148678865\n ],\n [\n -108.26202392578125,\n 38.07404145941957\n ],\n [\n -108.44329833984374,\n 38.47939467327645\n ],\n [\n -108.5723876953125,\n 38.70908932739828\n ],\n [\n -108.6053466796875,\n 38.83542884007303\n ],\n [\n -108.58612060546875,\n 39.04691915968503\n ],\n [\n -108.49822998046875,\n 39.104488809440475\n ],\n [\n -108.39935302734375,\n 39.095962936305504\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,Colorado Water Science Center
U.S. Geological Survey
Box 25046, MS 415
Denver, CO 80225-0046
Knowledge of the factors affecting the vigor of desert riparian trees is important for their conservation and management. I used multiple regression to assess effects of streamflow and climate (12–14 years of data) or climate alone (up to 60 years of data) on radial growth of clonal narrowleaf cottonwood (Populus angustifolia), a foundation species in the arid, Closed Basin portion of the San Luis Valley, Colorado. I collected increment cores from trees (14–90 cm DBH) at four sites along each of Sand and Deadman creeks (total N = 85), including both perennial and ephemeral reaches. Analyses on trees <110 m from the stream channel explained 33–64% of the variation in standardized growth index (SGI) over the period having discharge measurements. Only 3 of 7 models included a streamflow variable; inclusion of prior-year conditions was common. Models for trees farther from the channel or over a deep water table explained 23–71% of SGI variability, and 4 of 5 contained a streamflow variable. Analyses using solely climate variables over longer time periods explained 17–85% of SGI variability, and 10 of 12 included a variable indexing summer precipitation. Three large, abrupt shifts in recent decades from wet to dry conditions (indexed by a seasonal Palmer Drought Severity Index) coincided with dramatically reduced radial growth. Each shift was presumably associated with branch dieback that produced a legacy effect apparent in many SGI series: uncharacteristically low SGI in the year following the shift. My results suggest trees in locations distant from the active channel rely on the regional shallow unconfined aquifer, summer rainfall, or both to meet water demands. The landscape-level differences in the water supplies sustaining these trees imply variable effects from shifts in winter-versus monsoon-related precipitation, and from climate change versus streamflow or groundwater management.
","language":"English","publisher":"Academic Press","publisherLocation":"London","doi":"10.1016/j.jaridenv.2016.07.005","usgsCitation":"Andersen, D., 2016, Climate, streamflow, and legacy effects on growth of riparian Populus angustifolia in the arid San Luis Valley, Colorado: Journal of Arid Environments, v. 134, p. 104-121, https://doi.org/10.1016/j.jaridenv.2016.07.005.","startPage":"104","endPage":"121","numberOfPages":"18","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071295","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":470671,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jaridenv.2016.07.005","text":"Publisher Index Page"},{"id":326343,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Luis Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.84983825683594,\n 37.62075814551956\n ],\n [\n -105.84983825683594,\n 38.03078569382294\n ],\n [\n -105.47561645507812,\n 38.03078569382294\n ],\n [\n -105.47561645507812,\n 37.62075814551956\n ],\n [\n -105.84983825683594,\n 37.62075814551956\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"134","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57ac4227e4b0d183567452ec","chorus":{"doi":"10.1016/j.jaridenv.2016.07.005","url":"http://dx.doi.org/10.1016/j.jaridenv.2016.07.005","publisher":"Elsevier BV","authors":"Andersen Douglas C.","journalName":"Journal of Arid Environments","publicationDate":"11/2016"},"contributors":{"authors":[{"text":"Andersen, Douglas doug_andersen@usgs.gov","contributorId":152661,"corporation":false,"usgs":true,"family":"Andersen","given":"Douglas","email":"doug_andersen@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":645133,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70175410,"text":"70175410 - 2016 - Three-dimensional electrical resistivity model of the hydrothermal system in Long Valley Caldera, California, from magnetotellurics","interactions":[],"lastModifiedDate":"2016-08-26T11:15:54","indexId":"70175410","displayToPublicDate":"2016-08-10T10:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Three-dimensional electrical resistivity model of the hydrothermal system in Long Valley Caldera, California, from magnetotellurics","docAbstract":"Though shallow flow of hydrothermal fluids in Long Valley Caldera, California, has been well studied, neither the hydrothermal source reservoir nor heat source has been well characterized. Here a grid of magnetotelluric data were collected around the Long Valley volcanic system and modeled in 3-D. The preferred electrical resistivity model suggests that the source reservoir is a narrow east-west elongated body 4 km below the west moat. The heat source could be a zone of 2–5% partial melt 8 km below Deer Mountain. Additionally, a collection of hypersaline fluids, not connected to the shallow hydrothermal system, is found 3 km below the medial graben, which could originate from a zone of 5–10% partial melt 8 km below the south moat. Below Mammoth Mountain is a 3 km thick isolated body containing fluids and gases originating from an 8 km deep zone of 5–10% basaltic partial melt.
","language":"English","publisher":"American Geophysical Union","publisherLocation":"Washington, D.C.","doi":"10.1002/2016GL069263","usgsCitation":"Peacock, J.R., Mangan, M.T., McPhee, D., and Wannamaker, P.E., 2016, Three-dimensional electrical resistivity model of the hydrothermal system in Long Valley Caldera, California, from magnetotellurics: Geophysical Research Letters, v. 43, no. 15, p. 7953-7962, https://doi.org/10.1002/2016GL069263.","productDescription":"10 p.","startPage":"7953","endPage":"7962","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-074195","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":499825,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doaj.org/article/8141104d95554d10b45eedd01006b332","text":"External Repository"},{"id":326333,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Long Valley Caldera","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.083333,\n 37.791667\n ],\n [\n -119.083333,\n 37.55\n ],\n [\n -118.666667,\n 37.55\n ],\n [\n -118.666667,\n 37.791667\n ],\n [\n -119.083333,\n 37.791667\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"43","issue":"15","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-08-08","publicationStatus":"PW","scienceBaseUri":"57ac4227e4b0d183567452f0","contributors":{"authors":[{"text":"Peacock, Jared R. 0000-0002-0439-0224 jpeacock@usgs.gov","orcid":"https://orcid.org/0000-0002-0439-0224","contributorId":4996,"corporation":false,"usgs":true,"family":"Peacock","given":"Jared","email":"jpeacock@usgs.gov","middleInitial":"R.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":645107,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mangan, Margaret T. 0000-0002-5273-8053 mmangan@usgs.gov","orcid":"https://orcid.org/0000-0002-5273-8053","contributorId":3343,"corporation":false,"usgs":true,"family":"Mangan","given":"Margaret","email":"mmangan@usgs.gov","middleInitial":"T.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":645108,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McPhee, Darcy 0000-0002-5177-3068 dmcphee@usgs.gov","orcid":"https://orcid.org/0000-0002-5177-3068","contributorId":2621,"corporation":false,"usgs":true,"family":"McPhee","given":"Darcy","email":"dmcphee@usgs.gov","affiliations":[{"id":412,"text":"National Cooperative Geologic Mapping Program","active":false,"usgs":true}],"preferred":true,"id":645109,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wannamaker, Phil E.","contributorId":173574,"corporation":false,"usgs":false,"family":"Wannamaker","given":"Phil","email":"","middleInitial":"E.","affiliations":[{"id":7079,"text":"Energy and Geoscience Institute, University of Utah","active":true,"usgs":false}],"preferred":false,"id":645110,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70173831,"text":"sir20165072 - 2016 - Evaluation of effects of groundwater withdrawals at the proposed Allen combined-cycle combustion turbine plant, Shelby County, Tennessee","interactions":[],"lastModifiedDate":"2016-08-10T13:43:31","indexId":"sir20165072","displayToPublicDate":"2016-08-10T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-5072","title":"Evaluation of effects of groundwater withdrawals at the proposed Allen combined-cycle combustion turbine plant, Shelby County, Tennessee","docAbstract":"The Mississippi Embayment Regional Aquifer Study groundwater-flow model was used to simulate the potential effects of future groundwater withdrawals at the proposed Allen combined-cycle combustion turbine plant in Shelby County, Tennessee. The scenario used in the simulation consisted of a 30-year average withdrawal period followed by a 30-day maximum withdrawal period. Effects of withdrawals at the Allen plant site on the Mississippi embayment aquifer system were evaluated by comparing the difference in simulated water levels in the aquifers at the end of the 30-year average withdrawal period and at the end of the scenario to a base case without the Allen combined-cycle combustion turbine plant withdrawals. Simulated potentiometric surface declines in the Memphis aquifer at the Allen plant site were about 7 feet at the end of the 30-year average withdrawal period and 11 feet at the end of the scenario. The affected area of the Memphis aquifer at the Allen plant site as delineated by the 4-foot potentiometric surface-decline contour was 2,590 acres at the end of the 30-year average withdrawal period and 11,380 acres at the end of the scenario. Simulated declines in the underlying Fort Pillow aquifer and overlying shallow aquifer were both less than 1 foot at the end of the 30-year average withdrawal period and the end of the scenario.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165072","collaboration":"Prepared in cooperation with the Tennessee Valley Authority","usgsCitation":"Haugh, C.J., 2016, Evaluation of effects of groundwater withdrawals at the proposed Allen combined-cycle combustion turbine plant, Shelby County, Tennessee: U.S. Geological Survey Scientific Investigations Report 2016–5072, 8 p., https://dx.doi.org/10.3133/sir20165072.","productDescription":"iv, 8 p.","startPage":"1","endPage":"8","numberOfPages":"16","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-072773","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":326304,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5072/coverthb.jpg"},{"id":326305,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5072/sir20165072.pdf","text":"Report","size":"668 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016–5072"}],"country":"United States","state":"Arkansas, Mississippi, Tennessee","county":"Shelby County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.5,\n 35.375\n ],\n [\n -90.5,\n 34.75\n ],\n [\n -89.75,\n 34.75\n ],\n [\n -89.75,\n 35.375\n ],\n [\n -90.5,\n 35.375\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Chief, Lower Mississippi-Gulf Water Science Center—Tennessee
U.S. Geological Survey
640 Grassmere Park, Suite 100,
Nashville, TN 37211
The U.S. Geological Survey, in cooperation with the Puerto Rico Electric Power Authority, completed hydrologic and hydraulic analyses to assess the potential hazard to human life and property associated with the hypothetical failure of the Lago El Guineo Dam. The Lago El Guineo Dam is within the headwaters of the Río Grande de Manatí and impounds a drainage area of about 4.25 square kilometers.
The hydrologic assessment was designed to determine the outflow hydrographs and peak discharges for Lago El Guineo and other subbasins in the Río Grande de Manatí hydrographic basin for three extreme rainfall events: (1) a 6-hour probable maximum precipitation event, (2) a 24-hour probable maximum precipitation event, and (3) a 24-hour, 100-year recurrence rainfall event. The hydraulic study simulated a dam failure of Lago El Guineo Dam using flood hydrographs generated from the hydrologic study. The simulated dam failure generated a hydrograph that was routed downstream from Lago El Guineo Dam through the lower reaches of the Río Toro Negro and the Río Grande de Manatí to determine water-surface profiles developed from the event-based hydrologic scenarios and “sunny day” conditions. The Hydrologic Engineering Center’s Hydrologic Modeling System (HEC–HMS) and Hydrologic Engineering Center’s River Analysis System (HEC–RAS) computer programs, developed by the U.S. Army Corps of Engineers, were used for the hydrologic and hydraulic modeling, respectively. The flow routing in the hydraulic analyses was completed using the unsteady flow module available in the HEC–RAS model.
Above the Lago El Guineo Dam, the simulated inflow peak discharges from HEC–HMS resulted in about 550 and 414 cubic meters per second for the 6- and 24-hour probable maximum precipitation events, respectively. The 24-hour, 100-year recurrence storm simulation resulted in a peak discharge of about 216 cubic meters per second. For the hydrologic analysis, no dam failure conditions are considered within the model. The results of the hydrologic simulations indicated that for all hydrologic conditions scenarios, the Lago El Guineo Dam would not experience overtopping. For the dam breach hydraulic analysis, failure by piping was the selected hypothetical failure mode for the Lago El Guineo Dam.
Results from the simulated dam failure of the Lago El Guineo Dam using the HEC–RAS model for the 6- and 24-hour probable maximum precipitation events indicated peak discharges below the dam of 1,342.43 and 1,434.69 cubic meters per second, respectively. Dam failure during the 24-hour, 100-year recurrence rainfall event resulted in a peak discharge directly downstream from Lago El Guineo Dam of 1,183.12 cubic meters per second. Dam failure during sunny-day conditions (no precipitation) produced a peak discharge at Lago El Guineo Dam of 1,015.31 cubic meters per second assuming the initial water-surface elevation was at the morning-glory spillway invert elevation.
The results of the hydraulic analysis indicate that the flood would extend to many inhabited areas along the stream banks from the Lago El Guineo Dam to the mouth of the Río Grande as a result of the simulated failure of the Lago El Guineo Dam. Low-lying regions in the vicinity of Ciales, Manatí, and Barceloneta, Puerto Rico, are among the regions that would be most affected by failure of the Lago El Guineo Dam. Effects of the flood control (levee) structure constructed in 2000 to provide protection to the low-lying populated areas of Barceloneta, Puerto Rico, were considered in the hydraulic analysis of dam failure. The results indicate that overtopping can be expected in the aforementioned levee during 6- and 24-hour probable maximum precipitation events. The levee was not overtopped during dam failure scenarios under the 24-hour, 100-year recurrence rainfall event or sunny-day conditions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165070","collaboration":"Prepared in cooperation with the Puerto Rico Electric Power Authority","usgsCitation":"Gómez-Fragoso, Julieta, and Torres-Sierra, Heriberto, 2016, Dam failure analysis for the Lago El Guineo Dam, Orocovis, Puerto Rico: U.S. Geological Survey Scientific Investigations Report 2016–5070, 49 p., 4 pls., https://dx.doi.org/10.3133/sir20165070.","productDescription":"Report: vi, 49 p.; 4 Plates: 29 x 35 inches; 2 Data Releases","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-062802","costCenters":[{"id":156,"text":"Caribbean Water Science Center","active":true,"usgs":true}],"links":[{"id":438575,"rank":9,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F72V2D7Q","text":"USGS data release","linkHelpText":"Dam Failure Analysis for the Lago de Guineo dam, Orocovis, Puerto Rico"},{"id":326029,"rank":4,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2016/5070/sir20165070_plate02.pdf","text":"Plate 2 - Flood-Inundation Map of the Predicted 24-Hour Probable Maximum Precipitation Event, Northern Part of Rio Grande de Manati Basin","size":"101 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5070"},{"id":326026,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5070/coverthb.jpg"},{"id":326028,"rank":3,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2016/5070/sir20165070_plate01.pdf","text":"Plate 1 - Flood-Inundation Map of the Predicted 6-Hour Probable Maximum Precipitation Event, Northern Part of Rio Grande de Manati Basin","size":"101 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5070"},{"id":326027,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5070/sir20165070.pdf","text":"Report","size":"14 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5070"},{"id":326030,"rank":5,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2016/5070/sir20165070_plate03.pdf","text":"Plate 3 - Flood-Inundation Map of the Predicted 100-Year Recurrence, 24-Hour Precipitation Event, Northern Part of Rio Grande de Manati Basin","size":"101 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5070"},{"id":326031,"rank":6,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2016/5070/sir20165070_plate04.pdf","text":"Plate 4 - Flood-Inundation Map During Sunny Day Conditions, Northern Part of Rio Grande de Manati Basin ","size":"101 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5070"},{"id":326032,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F72V2D7Q","text":"USGS data release - Spatial Data for Dam failure analysis for the Lago El Guineo Dam, Orocovis, Puerto Rico","description":"SIR 2016-5070"},{"id":326195,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F72J690R","text":"USGS data release - HEC-HMS and HEC-RAS models used to analyze dam failure for the Lago El Guineo Dam, Orocovis, Puerto Rico","description":"SIR 2016-5070"}],"country":"Puerto Rico","city":"Orocovis","otherGeospatial":"Lago El Guineo Dam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -66.583333,\n 18.49\n ],\n [\n -66.583333,\n 18.291667\n ],\n [\n -66.394444,\n 18.291667\n ],\n [\n -66.394444,\n 18.49\n ],\n [\n -66.583333,\n 18.49\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559
813-498-5000
http://pr.water.usgs.gov/
Drift-foraging models offer a mechanistic description of how fish feed in flowing water and the application of drift-foraging bioenergetics models to answer both applied and theoretical questions in aquatic ecology is growing. These models typically include nonlinear descriptions of ecological processes and as a result may be sensitive to how model inputs are summarized because of a mathematical property of nonlinear equations known as Jensen’s inequality. In particular, we show that the way in which continuous size distributions of invertebrate prey are represented within foraging models can lead to biases within the modeling process. We begin by illustrating how different equations common to drift-foraging models are sensitive to invertebrate inputs. We then use two case studies to show how different representations of invertebrate prey can influence predictions of energy intake and lifetime growth. Greater emphasis should be placed on accurate characterizations of invertebrate drift, acknowledging that inferences from drift-foraging models may be influenced by how invertebrate prey are represented.
","language":"English","publisher":"Kluwer Academic Publishers","doi":"10.1007/s10641-016-0507-8","usgsCitation":"Dodrill, M.J., and Yackulic, C.B., 2016, Nonlinear relationships can lead to bias in biomass calculations and drift-foraging models when using summaries of invertebrate drift data: Environmental Biology of Fishes, v. 99, no. 8, p. 659-670, https://doi.org/10.1007/s10641-016-0507-8.","productDescription":"12 p.","startPage":"659","endPage":"670","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070151","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":326332,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"99","issue":"8","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-08-09","publicationStatus":"PW","scienceBaseUri":"57ac50dbe4b0d1835674b25c","chorus":{"doi":"10.1007/s10641-016-0507-8","url":"http://dx.doi.org/10.1007/s10641-016-0507-8","publisher":"Springer Nature","authors":"Dodrill Michael J., Yackulic Charles B.","journalName":"Environmental Biology of Fishes","publicationDate":"8/9/2016","auditedOn":"2/15/2017","publiclyAccessibleDate":"8/9/2016"},"contributors":{"authors":[{"text":"Dodrill, Michael J. 0000-0002-7038-7170 mdodrill@usgs.gov","orcid":"https://orcid.org/0000-0002-7038-7170","contributorId":5468,"corporation":false,"usgs":true,"family":"Dodrill","given":"Michael","email":"mdodrill@usgs.gov","middleInitial":"J.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":645105,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yackulic, Charles B. 0000-0001-9661-0724 cyackulic@usgs.gov","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":4662,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","email":"cyackulic@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":645106,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70175390,"text":"70175390 - 2016 - Pruning high-value Douglas-fir can reduce dwarf mistletoe severity and increase longevity in central Oregon","interactions":[],"lastModifiedDate":"2016-08-09T10:12:53","indexId":"70175390","displayToPublicDate":"2016-08-08T17:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1687,"text":"Forest Ecology and Management","active":true,"publicationSubtype":{"id":10}},"title":"Pruning high-value Douglas-fir can reduce dwarf mistletoe severity and increase longevity in central Oregon","docAbstract":"Mid- to very large-sized Douglas-fir (Pseudotsuga menzieseii var. menziesii) that were lightly- to moderately-infected by dwarf mistletoe (Arceuthobium douglasii) were analyzed over a 14-year period to evaluate whether mechanical pruning could eradicate mistletoe (or at least delay the onset of severe infection) without significantly affecting tree vitality and by inference, longevity. Immediate and longterm pruning effects on mistletoe infection severity were assessed by comparing pruned trees (n = 173) to unpruned trees (n = 55) with respect to: (1) percentage of trees with no visible infections 14 years post-pruning, (2) Broom Volume Rating (BVR), and (3) rate of BVR increase 14 years postpruning. Vitality/longevity (compared with unpruned trees) was assessed using six indicators: (1) tree survival, (2) the development of severe infections, (3) the development of dead tops, (4) tree-ring width indices, (5) Normalized Difference Vegetation Index (NDVI) from high-resolution multi-spectral imagery, and (6) live-crown ratio (LCR) and increment. Twenty-four percent of the pruned trees remained free of mistletoe 14 years post-pruning. Pruning is most likely to successfully eradicate mistletoe in lightly infected trees (BVR 1 or 2) without infected neighbors. Pruning significantly decreased mean BVR in the pruned versus the unpruned trees. However, the subsequent average rate of intensification (1.3–1.5 BVR per decade) was not affected, implying that a single pruning provides ~14 years respite in the progression of infection levels. Post-pruning infection intensification was slower on dominant and co-dominants than on intermediate or suppressed trees. The success of mistletoe eradication via pruning and need for follow-up pruning should be evaluated no sooner than 14 years after pruning to allow for the development of detectable brooms. Based on six indicators, foliage from witches brooms contribute little to long-term tree vitality since removal appears to have little effect on resources available for tree growth and maintenance. In the severely pruned trees, tree-ring width was reduced for several years post-pruning, but then compensated with larger ring width in later years. Both NDVI and LCR increment were significantly higher for the pruned trees than the control trees, while the development of severe infections and/or dead tops was significantly (5X and 3X) higher for the controls. If possible, multiple indicators of tree vitality should be evaluated. Pruning can be worthwhile even if all the mistletoe is not removed, because mistletoe intensification is delayed. The impact of removing the brooms seems to be minimal, and post-pruning crowns had greater NDVI values.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.foreco.2016.07.014","usgsCitation":"Maffei, H.M., Filip, G.M., Gruelke, N.E., Oblinger, B.W., Margolis, E.Q., and Chadwick, K.L., 2016, Pruning high-value Douglas-fir can reduce dwarf mistletoe severity and increase longevity in central Oregon: Forest Ecology and Management, v. 379, p. 11-19, https://doi.org/10.1016/j.foreco.2016.07.014.","productDescription":"9 p.","startPage":"11","endPage":"19","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-075721","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":470674,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.foreco.2016.07.014","text":"Publisher Index Page"},{"id":326281,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","volume":"379","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57a99f25e4b05e859bdf485b","contributors":{"authors":[{"text":"Maffei, Helen M","contributorId":173539,"corporation":false,"usgs":false,"family":"Maffei","given":"Helen","email":"","middleInitial":"M","affiliations":[{"id":6684,"text":"USDA Forest Service, Southern Research Station, Aiken, SC","active":true,"usgs":false}],"preferred":false,"id":645024,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Filip, Gregory M","contributorId":173540,"corporation":false,"usgs":false,"family":"Filip","given":"Gregory","email":"","middleInitial":"M","affiliations":[{"id":27245,"text":"USDA Forest Service, Pacific Northwest Regional Office","active":true,"usgs":false}],"preferred":false,"id":645025,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gruelke, Nancy E","contributorId":173541,"corporation":false,"usgs":false,"family":"Gruelke","given":"Nancy","email":"","middleInitial":"E","affiliations":[{"id":27246,"text":"USDA Forest Service, Western Wildlands Environmental Threat Assessment Center","active":true,"usgs":false}],"preferred":false,"id":645026,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Oblinger, Brent W","contributorId":173542,"corporation":false,"usgs":false,"family":"Oblinger","given":"Brent","email":"","middleInitial":"W","affiliations":[{"id":6684,"text":"USDA Forest Service, Southern Research Station, Aiken, SC","active":true,"usgs":false}],"preferred":false,"id":645027,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Margolis, Ellis Q. 0000-0002-0595-9005 emargolis@usgs.gov","orcid":"https://orcid.org/0000-0002-0595-9005","contributorId":173538,"corporation":false,"usgs":true,"family":"Margolis","given":"Ellis","email":"emargolis@usgs.gov","middleInitial":"Q.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":645023,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Chadwick, Kristen L","contributorId":173543,"corporation":false,"usgs":false,"family":"Chadwick","given":"Kristen","email":"","middleInitial":"L","affiliations":[{"id":6684,"text":"USDA Forest Service, Southern Research Station, Aiken, SC","active":true,"usgs":false}],"preferred":false,"id":645028,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70175391,"text":"70175391 - 2016 - Historical dominance of low-severity fire in dry and wet mixed-conifer forest habitats of the endangered terrestrial Jemez Mountains salamander (Plethodon neomexicanus)","interactions":[],"lastModifiedDate":"2016-08-08T16:15:04","indexId":"70175391","displayToPublicDate":"2016-08-08T17:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1687,"text":"Forest Ecology and Management","active":true,"publicationSubtype":{"id":10}},"title":"Historical dominance of low-severity fire in dry and wet mixed-conifer forest habitats of the endangered terrestrial Jemez Mountains salamander (Plethodon neomexicanus)","docAbstract":"Anthropogenic alteration of ecosystem processes confounds forest management and conservation of rare, declining species. Restoration of forest structure and fire hazard reduction are central goals of forest management policy in the western United States, but restoration priorities and treatments have become increasingly contentious. Numerous studies have documented changes in fire regimes, forest stand structure and species composition following a century of fire exclusion in dry, frequent-fire forests of the western U.S. (e.g., ponderosa pine and dry mixed-conifer). In contrast, wet mixed-conifer forests are thought to have historically burned infrequently with mixed- or high-severity fire—resulting in reduced impacts from fire exclusion and low restoration need—but data are limited. In this study we quantified the current forest habitat of the federally endangered, terrestrial Jemez Mountains salamander (Plethodon neomexicanus) and compared it to dendroecological reconstructions of historical habitat (e.g., stand structure and composition), and fire regime parameters along a gradient from upper ponderosa pine to wet mixed-conifer forests. We found that current fire-free intervals in Jemez Mountains salamander habitat (116–165 years) are significantly longer than historical intervals, even in wet mixed-conifer forests. Historical mean fire intervals ranged from 10 to 42 years along the forest gradient. Low-severity fires were historically dominant across all forest types (92 of 102 fires). Although some mixed- or highseverity fire historically occurred at 67% of the plots over the last four centuries, complete mortality within 1.0 ha plots was rare, and asynchronous within and among sites. Climate was an important driver of temporal variability in fire severity, such that mixed- and high-severity fires were associated with more extreme drought than low-severity fires. Tree density in dry conifer forests historically ranged from open (90 trees/ha) to moderately dense (400 trees/ha), but has doubled on average since fire exclusion. Infill of fire-sensitive tree species has contributed to the conversion of historically dry mixedconifer to wet mixed-conifer forest. We conclude that low-severity fire, which has been absent for over a century, was a critical ecosystem process across the forest gradient in Jemez Mountains salamander habitat, and thus is an important element of ecosystem restoration, resilience, and rare species recovery.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.foreco.2016.05.011","usgsCitation":"Margolis, E.Q., and Malevich, S.B., 2016, Historical dominance of low-severity fire in dry and wet mixed-conifer forest habitats of the endangered terrestrial Jemez Mountains salamander (Plethodon neomexicanus): Forest Ecology and Management, v. 375, p. 12-26, https://doi.org/10.1016/j.foreco.2016.05.011.","productDescription":"15 p.","startPage":"12","endPage":"26","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071390","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":326279,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"375","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57a99f25e4b05e859bdf4857","contributors":{"authors":[{"text":"Margolis, Ellis Q. 0000-0002-0595-9005 emargolis@usgs.gov","orcid":"https://orcid.org/0000-0002-0595-9005","contributorId":173538,"corporation":false,"usgs":true,"family":"Margolis","given":"Ellis","email":"emargolis@usgs.gov","middleInitial":"Q.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":645029,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Malevich, Steven B.","contributorId":173544,"corporation":false,"usgs":false,"family":"Malevich","given":"Steven","email":"","middleInitial":"B.","affiliations":[{"id":6624,"text":"University of Arizona, Laboratory of Tree-Ring Research","active":true,"usgs":false}],"preferred":false,"id":645030,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70168517,"text":"70168517 - 2016 - Model simulations of flood and debris flow timing in steep catchments after wildfire","interactions":[],"lastModifiedDate":"2016-09-28T16:11:59","indexId":"70168517","displayToPublicDate":"2016-08-08T14:45:00","publicationYear":"2016","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":"Model simulations of flood and debris flow timing in steep catchments after wildfire","docAbstract":"Debris flows are a typical hazard on steep slopes after wildfire, but unlike debris flows that mobilize from landslides, most post-wildfire debris flows are generated from water runoff. The majority of existing debris-flow modeling has focused on landslide-triggered debris flows. In this study we explore the potential for using process-based rainfall-runoff models to simulate the timing of water flow and runoff-generated debris flows in recently burned areas. Two different spatially distributed hydrologic models with differing levels of complexity were used: the full shallow water equations and the kinematic wave approximation. Model parameter values were calibrated in two different watersheds, spanning two orders of magnitude in drainage area. These watersheds were affected by the 2009 Station Fire in the San Gabriel Mountains, CA, USA. Input data for the numerical models were constrained by time series of soil moisture, flow stage, and rainfall collected at field sites, as well as high-resolution lidar-derived digital elevation models. The calibrated parameters were used to model a third watershed in the burn area, and the results show a good match with observed timing of flow peaks. The calibrated roughness parameter (Manning's $n$) was generally higher when using the kinematic wave approximation relative to the shallow water equations, and decreased with increasing spatial scale. The calibrated effective watershed hydraulic conductivity was low for both models, even for storms occurring several months after the fire, suggesting that wildfire-induced changes to soil-water infiltration were retained throughout that time. Overall the two model simulations were quite similar suggesting that a kinematic wave model, which is simpler and more computationally efficient, is a suitable approach for predicting flood and debris flow timing in steep, burned watersheds.
","language":"English","publisher":"AGU Publications","doi":"10.1002/2015WR018176","usgsCitation":"Rengers, F.K., McGuire, L., Kean, J.W., Staley, D.M., and Hobley, D., 2016, Model simulations of flood and debris flow timing in steep catchments after wildfire: Water Resources Research, v. 52, no. 8, p. 6041-6061, https://doi.org/10.1002/2015WR018176.","productDescription":"21 p.","startPage":"6041","endPage":"6061","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-073271","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":470675,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015wr018176","text":"Publisher Index Page"},{"id":326243,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"52","issue":"8","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-08-11","publicationStatus":"PW","scienceBaseUri":"57a99f25e4b05e859bdf4859","contributors":{"authors":[{"text":"Rengers, Francis K. 0000-0002-1825-0943 frengers@usgs.gov","orcid":"https://orcid.org/0000-0002-1825-0943","contributorId":150422,"corporation":false,"usgs":true,"family":"Rengers","given":"Francis","email":"frengers@usgs.gov","middleInitial":"K.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":620765,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McGuire, Luke lmcguire@usgs.gov","contributorId":167018,"corporation":false,"usgs":true,"family":"McGuire","given":"Luke","email":"lmcguire@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":620766,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kean, Jason W. 0000-0003-3089-0369 jwkean@usgs.gov","orcid":"https://orcid.org/0000-0003-3089-0369","contributorId":1654,"corporation":false,"usgs":true,"family":"Kean","given":"Jason","email":"jwkean@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":620767,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Staley, Dennis M. 0000-0002-2239-3402 dstaley@usgs.gov","orcid":"https://orcid.org/0000-0002-2239-3402","contributorId":4134,"corporation":false,"usgs":true,"family":"Staley","given":"Dennis","email":"dstaley@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":620768,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hobley, D.E.J","contributorId":167019,"corporation":false,"usgs":false,"family":"Hobley","given":"D.E.J","email":"","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":620769,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70175379,"text":"70175379 - 2016 - Highstand shelf fans: The role of buoyancy reversal in the deposition of a new type of shelf sand body","interactions":[],"lastModifiedDate":"2016-11-03T16:25:43","indexId":"70175379","displayToPublicDate":"2016-08-08T14:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1786,"text":"Geological Society of America Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"Highstand shelf fans: The role of buoyancy reversal in the deposition of a new type of shelf sand body","docAbstract":"Although sea-level highstands are typically associated with sediment-starved continental shelves, high sea level does not hinder major river floods. Turbidity currents generated by plunging of sediment-laden rivers at the fluvial-marine interface, known as hyperpycnal flows, allow for cross-shelf transport of suspended sand beyond the coastline. Hyperpycnal flows in southern California have deposited six subaqueous fans on the shelf of the northern Santa Barbara Channel in the Holocene. Using eight cores and nine grab samples, we describe the deposits, age, and stratigraphic architecture of two fans in the Santa Barbara Channel. Fan lobes have up to 3 m of relief and are composed of multiple hyperpycnite beds ∼5 cm to 40 cm thick. Deposit architecture and geometry suggest the hyperpycnal flows became positively buoyant and lifted off the seabed, resulting in well-sorted, structureless, elongate sand lobes. Contrary to conventional sequence stratigraphic models, the presence of these features on the continental shelf suggests that active-margin shelves may locally develop high-quality reservoir sand bodies during sea-level highstands, and that such shelves need not be solely the site of sediment bypass. These deposits may provide a Quaternary analogue to many well-sorted sand bodies in the rock record that are interpreted as turbidites but lack typical Bouma-type features.
","language":"English","publisher":"Geological of Society of America","doi":"10.1130/B31438.1","usgsCitation":"Steel, E., Simms, A.R., Warrick, J.A., and Yokoyama, Y., 2016, Highstand shelf fans: The role of buoyancy reversal in the deposition of a new type of shelf sand body: Geological Society of America Bulletin, v. 128, no. 11-12, p. 1717-1724, https://doi.org/10.1130/B31438.1.","productDescription":"8 p.","startPage":"1717","endPage":"1724","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-074404","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":326233,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"128","issue":"11-12","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-25","publicationStatus":"PW","scienceBaseUri":"57a99f25e4b05e859bdf4855","contributors":{"authors":[{"text":"Steel, Elisabeth","contributorId":47692,"corporation":false,"usgs":true,"family":"Steel","given":"Elisabeth","email":"","affiliations":[],"preferred":false,"id":644988,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Simms, Alexander R.","contributorId":52887,"corporation":false,"usgs":true,"family":"Simms","given":"Alexander","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":644989,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Warrick, Jonathan A. 0000-0002-0205-3814 jwarrick@usgs.gov","orcid":"https://orcid.org/0000-0002-0205-3814","contributorId":167736,"corporation":false,"usgs":true,"family":"Warrick","given":"Jonathan","email":"jwarrick@usgs.gov","middleInitial":"A.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":644987,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Yokoyama, Yusuke","contributorId":173528,"corporation":false,"usgs":false,"family":"Yokoyama","given":"Yusuke","email":"","affiliations":[{"id":7267,"text":"University of Tokyo","active":true,"usgs":false}],"preferred":false,"id":644990,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70174909,"text":"ofr20161120 - 2016 - A satellite model of Southwestern Willow Flycatcher (Empidonax traillii extimus) breeding habitat and a simulation of potential effects of tamarisk leaf beetles (Diorhabda spp.), southwestern United States","interactions":[],"lastModifiedDate":"2016-08-09T09:18:11","indexId":"ofr20161120","displayToPublicDate":"2016-08-08T13:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-1120","title":"A satellite model of Southwestern Willow Flycatcher (Empidonax traillii extimus) breeding habitat and a simulation of potential effects of tamarisk leaf beetles (Diorhabda spp.), southwestern United States","docAbstract":"The study described in this report represents the first time that a satellite model has been used to identify potential Southwestern Willow Flycatcher (Empidonax traillii extimus) (hereinafter referred to as “flycatcher”) breeding habitat rangewide for 2013–15. Fifty-seven Landsat scenes were required to map the entire range of the flycatcher, encompassing parts of six States and more than 1 billion 30-meter pixels. Predicted flycatcher habitat was summarized in a hierarchical fashion from largest to smallest: regionwide, State, U.S. Fish and Wildlife Service (FWS) management unit, 7.5-minute quadrangle, and critical-habitat reach. The term “predicted habitat” is used throughout this report to distinguish areas the satellite model predicts as suitable flycatcher habitat from what may actually exist on the ground. A rangewide accuracy assessment was done with 758 territories collected in 2014, and change detection was done with yearly habitat maps to identify how and where habitat changed over time. Additionally, effects of tamarisk leaf beetles (Diorhabda spp.) on flycatcher habitat were summarized for the lower Virgin River from 2010 to 2015, and simulations of how tamarisk leaf beetles may affect flycatcher habitat in the lower Colorado and upper Gila Rivers were done for 2015. Model results indicated that the largest areas of predicted flycatcher habitat at elevations below 1,524 meters were in New Mexico and Arizona, areas followed in descending order by California, Texas, Nevada, Utah, and Colorado. By FWS management unit, the largest area of flycatcher habitat during all 3 years were the Middle Rio Grande (New Mexico), followed by the Upper Gila (Arizona and New Mexico) and Middle Gila/San Pedro (Arizona) management units. The area of predicted flycatcher habitat varied considerably in 7.5-minute quadrangles, ranging from 0 to1,398 hectares (ha). Averaged across 3 years, the top three producing quadrangles were Paraje Well (New Mexico), San Marcial (New Mexico), and San Carlos Reservoir (Arizona). The top three FWS critical-habitat reaches in 2015 were Rio Grande-middle (9,544 ha), San Pedro River (1,779 ha), and Gila River-mid San Carlos (1,356 ha); this ranking did not change in 2013 or 2014. Change detection among years showed a large shift in predicted flycatcher habitat influenced by drought patterns, with California habitat decreasing and New Mexico habitat increasing. An accuracy assessment indicated that 88 percent of territories were correctly classified at a 40 percent probability threshold, with an exponential relationship between territory densities and five probability classes. A spatially explicit analysis indicated that beetles decreased predicted flycatcher habitat 94.2 percent from 2010 to 2015 along the lower Virgin River, with only 5.8 percent persisting. In contrast, beetle simulations indicated that 64.1 percent of habitat will persist along the lower Colorado River and 45 percent will persist along the upper Gila River. This project shows that the satellite model adequately predicts flycatcher habitat rangewide, but it lacks the ability to predict which patches will be occupied in a given year. The next logical step is the development of an occupancy model that ties the habitat predictions of the satellite model to patch occupancy so managers can better allocate their resources for survey and restoration activities. Finally, the methods presented in this report seem well suited for automated mapping applications and cloud-based resources.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161120","usgsCitation":"Hatten, J.R., 2016, A satellite model of Southwestern Willow Flycatcher (Empidonax traillii extimus) breeding habitat and a simulation of potential effects of tamarisk leaf beetles (Diorhabda spp.), Southwestern United States: U.S. Geological Survey Open-File Report 2016–1120, 88 p., https://dx.doi.org/10.3133/ofr20161120.","productDescription":"vi, 88 p.","numberOfPages":"98","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-074418","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":326223,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1120/coverthb.jpg"},{"id":326224,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1120/ofr20161120.pdf","text":"Report","size":"13.6 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U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115
http://wfrc.usgs.gov/