Recently, the miscible CO2-EOR tertiary process used in the main pay zone (MP) of suitable reservoirs has broadened to include exploitation of the underlying residual oil zone (ROZ) where a significant amount of oil may remain. The objective of this study is to identify the ROZ and to assess the remaining oil in a brownfield ROZ by using core data and conventional well logs with probabilistic and predictive methods.
Core and log data from three wells located in the East Seminole Field in Gaines County, Texas, were used to identify the MP and ROZ in the San Andres Limestone, and to predict oil saturations. The core measurements were used to calculate probabilistic in-situ oil saturations within the MP and the ROZ as a function of depth. Well logs, in combination with core data and calculated saturations, on the other hand, were used to develop two expert systems using artificial neural networks (ANN); one to identify the ROZ and MP, and the other to predict oil saturation. These systems were also supported by a classification and regression tree (CART) analysis to delineate the rules that lead to classifications of zones.
Results showed that expert systems developed and calibrated by combining core and well log data can identify MP and ROZ with a success score of more than 90%. Saturations within these zones can be predicted with a correlation coefficient of around 0.6 for testing and 0.8 for training data. The analyses showed that neutron porosity and density well log readings are the most influential ones to identify zones in this field and to predict oil saturations in the MP and ROZ. To explain the relationships of input data with the results, a rule-based system was also applied, which revealed the underlying petrophysical differences between MP and ROZ.
This new predictive approach using machine learning techniques, could potentially address the challenges that previous studies have come up against in defining the ROZ within the formation and quantifying remaining oil saturations. The method can potentially be applied to additional fields and help reliably identify the ROZ and estimate saturations for future resource evaluations.
Expanding gull (Laridae) populations throughout the world have been attributed to the availability of anthropogenic food subsidies. The influence of landfills on California Gull (Larus californicus) space use and the timing of their movements was evaluated in San Francisco Bay, California, USA. Using radio telemetry, 108 California Gulls were tracked, > 7,000 locations were recorded, and > 1 million detections were obtained at automated logger systems placed at the two main landfills and three major breeding colonies. Population home range (31-35 km2) and core use areas (2-3 km2) overlapped landfills and colonies, and expanded after breeding. California Gull attendance at landfills (1.6-19.0 km from colonies) increased throughout breeding and post-breeding, whereas attendance at colonies was low during pre-breeding (20%-40% per day), increased during breeding (60%-80% per day), and declined into and during post-breeding (< 20% per day). California Gull attendance at landfills was greatest when garbage was delivered from 06:00 hr in the morning until 18:00 hr at night. In contrast, California Gull attendance at colonies during breeding was greater at night from 20:00 hr to 05:00 hr (50%-70% per hr) than during the day from 06:00 hr to 18:00 hr (30%-40% per hr). Landfills played a predominant role in California Gull space use and the timing of their movements in this highly urbanized estuary.
","language":"English","publisher":"Waterbird Society","doi":"10.1675/063.041.0402","usgsCitation":"Ackerman, J.T., Peterson, S.H., Tsao, D., and Takekawa, J.Y., 2018, California gull (Larus californicus) space use and timing of movements in relation to landfills and breeding colonies: Waterbirds, v. 41, no. 4, p. 384-400, https://doi.org/10.1675/063.041.0402.","productDescription":"17 p.","startPage":"384","endPage":"400","ipdsId":"IP-077268","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":489098,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1675/063.041.0402","text":"Publisher Index Page"},{"id":387681,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"South San Francisco Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.21603393554688,\n 37.413800350662896\n ],\n [\n -121.92352294921874,\n 37.413800350662896\n ],\n [\n -121.92352294921874,\n 37.63000336572688\n ],\n [\n -122.21603393554688,\n 37.63000336572688\n ],\n [\n -122.21603393554688,\n 37.413800350662896\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"41","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ackerman, Joshua T. 0000-0002-3074-8322","orcid":"https://orcid.org/0000-0002-3074-8322","contributorId":202848,"corporation":false,"usgs":true,"family":"Ackerman","given":"Joshua","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":820551,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Peterson, Sarah H. 0000-0003-2773-3901 sepeterson@usgs.gov","orcid":"https://orcid.org/0000-0003-2773-3901","contributorId":167181,"corporation":false,"usgs":true,"family":"Peterson","given":"Sarah","email":"sepeterson@usgs.gov","middleInitial":"H.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":820552,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tsao, Danika C","contributorId":243314,"corporation":false,"usgs":false,"family":"Tsao","given":"Danika C","affiliations":[{"id":48682,"text":"CDWR (former USGS)","active":true,"usgs":false}],"preferred":false,"id":820553,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Takekawa, John Y. 0000-0003-0217-5907 john_takekawa@usgs.gov","orcid":"https://orcid.org/0000-0003-0217-5907","contributorId":196611,"corporation":false,"usgs":true,"family":"Takekawa","given":"John","email":"john_takekawa@usgs.gov","middleInitial":"Y.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":820554,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70201175,"text":"70201175 - 2018 - Contaminants of emerging concern in the environment: Where we have been and what does the future hold?","interactions":[],"lastModifiedDate":"2018-12-04T10:16:09","indexId":"70201175","displayToPublicDate":"2018-12-01T10:16:03","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3720,"text":"Water Resources Impact","printIssn":"1522-3175","active":true,"publicationSubtype":{"id":10}},"title":"Contaminants of emerging concern in the environment: Where we have been and what does the future hold?","docAbstract":"In 1962, Rachel Carson’s book Silent Spring alerted the nation to the dangers of manmade chemicals and indiscriminate use of pesticides. DDT was the culprit and its use threatened a variety of wildlife, including the national bird, bald eagles. In 1969, pressured by scientists and the public, the United States banned almost all uses of DDT; however, DDT was just the tip of the chemical iceberg. In 1996, Theo Colborn’s book, Our Stolen Future, again alerted the public to the dangers of chemical exposure. Endocrine-disrupting chemicals were identified as concerns because exposure to extremely small concentrations can have adverse effects on people and wildlife by interfering with chemical messaging systems, affecting things like sexual development and reproduction.
","language":"English","publisher":"American Water Resources Association","usgsCitation":"Battaglin, W., Kolpin, D., Furlong, E., Glassmeyer, S., Blackwell, B., Corsi, S., Meyer, M., and Bradley, P., 2018, Contaminants of emerging concern in the environment: Where we have been and what does the future hold?: Water Resources Impact, v. 20, no. 6, p. 8-11.","productDescription":"4 p.","startPage":"8","endPage":"11","ipdsId":"IP-101237","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":359904,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":359894,"type":{"id":15,"text":"Index Page"},"url":"https://www.awra.org/impact/"}],"volume":"20","issue":"6","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c07a063e4b0815414cee77d","contributors":{"authors":[{"text":"Battaglin, William A. 0000-0001-7287-7096","orcid":"https://orcid.org/0000-0001-7287-7096","contributorId":204638,"corporation":false,"usgs":true,"family":"Battaglin","given":"William A.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":753050,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kolpin, Dana W. 0000-0002-3529-6505","orcid":"https://orcid.org/0000-0002-3529-6505","contributorId":205652,"corporation":false,"usgs":true,"family":"Kolpin","given":"Dana W.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true},{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"preferred":true,"id":753051,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Furlong, Edward T. 0000-0002-7305-4603","orcid":"https://orcid.org/0000-0002-7305-4603","contributorId":204151,"corporation":false,"usgs":true,"family":"Furlong","given":"Edward T.","affiliations":[{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true},{"id":38175,"text":"Toxics Substances Hydrology Program","active":true,"usgs":true}],"preferred":true,"id":753052,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Glassmeyer, Susan","contributorId":184091,"corporation":false,"usgs":false,"family":"Glassmeyer","given":"Susan","affiliations":[],"preferred":false,"id":753053,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Blackwell, Brett R.","contributorId":173601,"corporation":false,"usgs":false,"family":"Blackwell","given":"Brett R.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":753054,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Corsi, Steven 0000-0003-0583-4436 srcorsi@usgs.gov","orcid":"https://orcid.org/0000-0003-0583-4436","contributorId":211035,"corporation":false,"usgs":true,"family":"Corsi","given":"Steven","email":"srcorsi@usgs.gov","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":753055,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Meyer, Michael T. 0000-0001-6006-7985","orcid":"https://orcid.org/0000-0001-6006-7985","contributorId":205665,"corporation":false,"usgs":true,"family":"Meyer","given":"Michael T.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":753056,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Bradley, Paul M. 0000-0001-7522-8606","orcid":"https://orcid.org/0000-0001-7522-8606","contributorId":205668,"corporation":false,"usgs":true,"family":"Bradley","given":"Paul M.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":753057,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70202698,"text":"70202698 - 2018 - Predicting biological conditions for small headwater streams in the Chesapeake Bay watershed","interactions":[],"lastModifiedDate":"2019-03-19T16:54:56","indexId":"70202698","displayToPublicDate":"2018-12-01T10:09:45","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1699,"text":"Freshwater Science","active":true,"publicationSubtype":{"id":10}},"title":"Predicting biological conditions for small headwater streams in the Chesapeake Bay watershed","docAbstract":"A primary goal for Chesapeake Bay watershed restoration is to improve stream health and function in 10% of stream miles by 2025. Predictive spatial modeling of stream conditions, when accurate, is one method to fill gaps in monitoring coverage and estimate baseline conditions for restoration goals. Predictive modeling can also monitor progress as additional data become available. We developed a random forests model to predict biological condition of small streams (<200 km2 in drainage) in the Chesapeake Bay watershed. Biological condition was measured with the Chesapeake Bay Basin-wide Index of Biotic Integrity (Chessie BIBI), a stream macroinvertebrate index. Our goal was to predict biological condition in all unsurveyed small streams present in a 1:24,000 scale catchment layer as a 2004–2008 baseline. We reclassified the 5-category Chessie BIBI ratings into two categories, poor and fair/good, to align with management goals of the Chesapeake Bay Program. The model included 12 geospatial predictor variables including measures on spatial location, bioregion, land cover, soil, precipitation, and number of dams in local catchments. We trained the model with a random 75% subset of Chessie BIBI data (n = 1449), and used the remaining 25% of Chessie BIBI data (n = 484) as test data. The model performed well, correctly predicting 72% of samples in training data and 73% of samples in test data, but model accuracy varied among bioregions. We performed uncertainty analyses by adding bands of either ±0.05 or ±0.10 BIBI units to the cutoff between poor and fair/good. These uncertainty analyses resulted in 14.5% (±0.05 band) and 24.8% (±0.10 band) of samples in test data being classified as in uncertain condition. For 95,877 small stream reaches in the Chesapeake Bay watershed, the model predicted 64% in fair/good condition, the ±0.05 uncertainty analyses predicted 57% in fair/good condition, and the ±0.10 uncertainty analysis predicted 50% in fair/good condition. These reported values have different implications for the number of improved stream miles required to meet the goal of improving 10%. Incorporating uncertainty provides an assessment of model strength as well as confidence in predictions. We, therefore, suggest increased reporting of uncertainty in studies that spatially predict stream conditions.
","language":"English","publisher":"University of Chicago Press","doi":"10.1086/700701","usgsCitation":"Maloney, K.O., Smith, Z.M., Buchanan, C., Nagel, A., and Young, J.A., 2018, Predicting biological conditions for small headwater streams in the Chesapeake Bay watershed: Freshwater Science, v. 4, no. 37, p. 795-809, https://doi.org/10.1086/700701.","productDescription":"15 p.","startPage":"795","endPage":"809","ipdsId":"IP-094122","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":460801,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1086/700701","text":"Publisher Index Page"},{"id":362172,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Chesapeake Bay watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n 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M.","contributorId":214279,"corporation":false,"usgs":false,"family":"Smith","given":"Zachary","email":"","middleInitial":"M.","affiliations":[{"id":39005,"text":"ICPRB","active":true,"usgs":false}],"preferred":false,"id":759530,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buchanan, Claire","contributorId":214280,"corporation":false,"usgs":false,"family":"Buchanan","given":"Claire","affiliations":[{"id":39005,"text":"ICPRB","active":true,"usgs":false}],"preferred":false,"id":759531,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nagel, Andrea","contributorId":214281,"corporation":false,"usgs":false,"family":"Nagel","given":"Andrea","email":"","affiliations":[{"id":39005,"text":"ICPRB","active":true,"usgs":false}],"preferred":false,"id":759532,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Young, John A. 0000-0002-4500-3673 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management addresses uncertainty about the processes influencing resource dynamics, as well as the elements of decision making itself. The use of management to reduce both kinds of uncertainty is known as double-loop learning. Though much work has been done on the theory and procedures to address structural uncertainty, there has been less progress in developing an explicit approach for institutional learning about decision elements. Our objective is to describe evidence-based learning about the decision elements, as a complement to the formal “learning by doing” framework for reducing structural uncertainties. Adaptive management is described as a multi-phase approach to management and learning, with a set-up phase of identifying stakeholders, objectives, and other decision elements; an iterative phase that uses these elements in an ongoing cycle of technical learning about system structure and management impacts; and an institutional learning phase involving the periodic reconsideration of the decision elements. We describe a framework for institutional learning that is complementary to that of technical learning, including uncertainty metrics, propagation of change, and mechanisms and consequences of change over time. Operational issues include ways to recognize when the decision elements should be revisited, which elements should be adjusted, and how alternatives can be identified and incorporated based on experience and management performance. We discuss the application of this framework in decision making for renewable natural resources. As important as it is to learn about the processes driving resource dynamics, learning about the elements of the decision architecture is equally, if not more, important.","language":"English","publisher":"Springer","doi":"10.1007/s00267-018-1107-5","usgsCitation":"Williams, B.K., and Brown, E., 2018, Double loop learning in adaptive management: the need, the challenge, and the opportunity: Environmental Management, v. 62, no. 6, p. 995-1006, https://doi.org/10.1007/s00267-018-1107-5.","productDescription":"12 p.","startPage":"995","endPage":"1006","ipdsId":"IP-098525","costCenters":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"links":[{"id":468223,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s00267-018-1107-5","text":"Publisher Index Page"},{"id":362580,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"62","issue":"6","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-09-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Williams, Byron K. 0000-0001-7644-1396","orcid":"https://orcid.org/0000-0001-7644-1396","contributorId":86616,"corporation":false,"usgs":true,"family":"Williams","given":"Byron","email":"","middleInitial":"K.","affiliations":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"preferred":false,"id":760257,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brown, Ellie 0000-0001-7798-830X ebrown@usgs.gov","orcid":"https://orcid.org/0000-0001-7798-830X","contributorId":200491,"corporation":false,"usgs":true,"family":"Brown","given":"Ellie","email":"ebrown@usgs.gov","affiliations":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"preferred":false,"id":760256,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70265695,"text":"70265695 - 2018 - A full annual-cycle conservation strategy for Sprague’s Pipit, Chestnut-collared and McCown’s Longspurs, and Baird’s Sparrow","interactions":[],"lastModifiedDate":"2025-04-14T14:14:09.437801","indexId":"70265695","displayToPublicDate":"2018-12-01T09:02:27","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"title":"A full annual-cycle conservation strategy for Sprague’s Pipit, Chestnut-collared and McCown’s Longspurs, and Baird’s Sparrow","docAbstract":"Sprague’s Pipit (Anthus spragueii), Chestnut-collared Longspur (Calcarius ornatus), McCown’s Longspur (Rhynchophanes mccownii), and Baird’s Sparrow (Centronyx bairdii) [hereafter, “the Species”] are North American grassland-obligate songbirds whose populations have experienced significant annual population declines and are the focus of increasing conservation concern. The purpose of this strategy is to summarize current knowledge of the Species and identify priority research, monitoring and conservation actions required to improve their population status.
Grasslands are among the most threatened ecosystems in the world with historic losses of 61-70% converted to other land uses, primarily cropland agriculture. Losses continue, with current conversion in the northern Great Plains occurring several times faster than grasslands can be protected. The Partners in Flight North American Landbird Conservation Plan (PIF NALCP) estimates current global populations of 900,000, 3,000,000, 600,000, and 2,000,000 for Sprague’s Pipit, Chestnut-collared Longspur, McCown’s Longspur, and Baird’s Sparrow, respectively. Over the period of 1967-2015, these populations have declined at -3.1, -4.2, -5.9 and -2.2% annually for estimated total losses of 78, 87, 94 and 65%, respectively.
Habitat associations of breeding birds, especially at the local scale, represent the majority of the existing scientific literature on the Species’ biology. Landscape-scale associations are more poorly understood, and few studies have linked habitat, at any scale, to population vital rates. Increasing effort is focused on nonbreeding season and very little is known about migration. Current knowledge identifies three primary threats: 1) loss of native grasslands, 2) degradation and fragmentation of remaining native grasslands, and 3) disturbance inconsistent with needs of the Species. Top priorities for future research include: identification of population limiting factors, links between breeding habitat and demographics, identification of migratory habitat requirements, and identification of conditions promoting winter survival.
Implementation strategies must focus on the protection, restoration, and enhancement (i.e., management) of grassland communities. Most imperative is the protection of remaining native grasslands from conversion to other uses. Actions supporting grass-based agriculture on privately-owned, native grasslands are paramount. These include incentive-based tools to support livestock grazing that benefits both priority birds and healthy ranching communities, which in turn prevent the conversion of native grasslands to cropland. Where cropland conversion has already taken place, conservation partners should work to continue and improve programs such as the Conservation Reserve Program (CRP) to restore and maintain permanent native cover.
This strategy adopts the PIF NALCP objective, which is to reduce the rate of the Species’ decline in the first 10 years, then stabilize and ultimately increase the 2016 population by 5-15% over the subsequent 20 years. Ongoing monitoring programs such as the Breeding Bird Survey, Integrated Monitoring of Bird Conservation Regions, and eBird are critical for informing broadscale demographic and geographic trends for the Species. However, to achieve PIF NALCP goals, there is additional need for monitoring that links habitat conservation accomplishments to population performance within a strategic habitat conservation framework.
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database model","interactions":[],"lastModifiedDate":"2025-02-12T15:07:57.436066","indexId":"70263478","displayToPublicDate":"2018-12-01T09:00:20","publicationYear":"2018","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"A proposed seismic velocity profile database model","docAbstract":"We describe the data model that we intend to use in a publicly available site profile database under development for the United States. The initial implementation of the database contains data from California. Currently, our prototype data model consists of JavaScript Object Notation (JSON) format files for storing metadata and data. For a site to be included in the database, the minimum metadata requirements are geodetic coordinates and elevation values, and the minimum data requirement is a shear-wave velocity profile. The JSON files are structured in a hierarchal manner to store metadata and data using a nested structure consisting of location, velocity profiles, dispersion curve data (for surface-wave methods), geotechnical data, and horizontal-to-vertical spectral ratios. The database schema at the current stage of the project, and as we continue to develop the data model we will consider including other relevant data, as well as evaluate other file formats to increase the efficiency of data storage and querying. In the current data model, location information includes site geodetic values (latitude, longitude, and elevation) and various site descriptors related to surface geology, geomorphic terrain category, slope gradient at various resolutions, and a geotechnical site category. Velocity data include the geophysical method(s) used to obtain the shear-wave velocity profile, type of data recorded, modeled primary- and shear-wave velocity as a function of depth, modeled profile maximum depth, and the calculated VS30 value. In the case of surface-wave based data, dispersion curve data can be recorded in data structure as phase velocity versus either wavelength or frequency. Geotechnical data includes boring logs penetration resistance, cone penetration test sounding logs, and laboratory index test results. Horizontal-to-vertical spectral ratio plots are given as a function of frequency.
","conferenceTitle":"11th United States National Conference on Earthquake Engineering","conferenceDate":"June 25-29, 2018","conferenceLocation":"Los Angeles, CA","language":"English","publisher":"Earthquake Engineering Research Institute","usgsCitation":"Sadiq, S., Ilkan, O., Ahdi, S.K., Bozorgina, Y., Hashash, Y., Kwak, D., Park, D., Yong, A., and Stewart, J., 2018, A proposed seismic velocity profile database model, 11th United States National Conference on Earthquake Engineering, Los Angeles, CA, June 25-29, 2018, 9 p.","productDescription":"9 p.","ipdsId":"IP-092618","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":481974,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Sadiq, Shamsher","contributorId":350844,"corporation":false,"usgs":false,"family":"Sadiq","given":"Shamsher","affiliations":[{"id":83848,"text":"Dept. 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Eng., Hanyang Univ.; email: dpark@hanyang.ac.kr","active":true,"usgs":false}],"preferred":false,"id":927118,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Yong, Alan 0000-0003-1807-5847","orcid":"https://orcid.org/0000-0003-1807-5847","contributorId":204730,"corporation":false,"usgs":true,"family":"Yong","given":"Alan","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927119,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Stewart, Jonathan P.","contributorId":350854,"corporation":false,"usgs":false,"family":"Stewart","given":"Jonathan P.","affiliations":[{"id":83855,"text":"University of California, Los Angeles, U.S.A.","active":true,"usgs":false}],"preferred":false,"id":927120,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70227784,"text":"70227784 - 2018 - Comparing growth and body condition of indoor-reared, outdoor-reared, and direct-released juvenile Mojave desert tortoises","interactions":[],"lastModifiedDate":"2022-01-31T14:46:36.019542","indexId":"70227784","displayToPublicDate":"2018-12-01T08:40:57","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1894,"text":"Herpetological Conservation and Biology","onlineIssn":"2151-0733","printIssn":"1931-7603","active":true,"publicationSubtype":{"id":10}},"title":"Comparing growth and body condition of indoor-reared, outdoor-reared, and direct-released juvenile Mojave desert tortoises","docAbstract":"Desert tortoise populations have declined, and head-starting hatchlings in captivity until they are larger and older — and presumably more likely to survive — is one strategy being evaluated for species recovery. Previous studies have reared hatchlings in outdoor, predator-proof pens for 5–9 years before release, in efforts to produce hatchlings in excess of 100–110 mm midline carapace length that are believed to be predation-resistant. We began a comparative study to evaluate indoor-rearing to shorten this rearing period by facilitating faster initial growth. We assigned 70 neonates from the 2015 hatching season to three treatment groups: 1) indoor-reared (n = 30), 2) outdoor-reared (n = 20), and 3) direct-release (n = 20). Direct-release hatchlings were released shortly after hatching in September 2015 and monitored 1–2x per week with radio telemetry. We head-started the indoor- and outdoor-reared treatment groups for 7 mo before releasing them in April 2016. Indoor-reared tortoises were fed 5x per week (Sep–Mar). Outdoor-reared tortoises had access to native forage and were given supplemental water and food once per week while active before winter dormancy. Indoor-reared tortoises grew >16x faster than direct-release tortoises and >8x faster than outdoor-reared tortoises. However, indoor-reared tortoises weighed less and had softer shells than comparatively sized older (3–4 year-old) tortoises raised outdoors. Increasing the duration of the indoor-rearing period or incorporating a combination of both indoor and later outdoor husbandry may increase shell hardness among head-starts, while retaining the growth-promoting effect of indoor rearing and shortening overall captivity duration.
","language":"English","publisher":"Herpetological Conservation and Biology","usgsCitation":"Daly, J.A., Buhlman, K.A., Todd, B.D., Moore, C.T., Peaden, J., and Tuberville, T.D., 2018, Comparing growth and body condition of indoor-reared, outdoor-reared, and direct-released juvenile Mojave desert tortoises: Herpetological Conservation and Biology, v. 13, no. 3, p. 622-633.","productDescription":"12 p.","startPage":"622","endPage":"633","ipdsId":"IP-092840","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":395131,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":395130,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.herpconbio.org/contents_vol13_issue3.html"}],"country":"United States","state":"California","county":"San Bernardino County","otherGeospatial":"Mojave National Preserve","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.8895263671875,\n 35.04798673426734\n ],\n [\n -115.34545898437499,\n 35.576916524038616\n ],\n [\n -116.0870361328125,\n 35.55010533588552\n ],\n [\n -116.378173828125,\n 35.15584570226544\n ],\n [\n -116.44958496093749,\n 34.84536693184101\n ],\n [\n -116.0211181640625,\n 34.58799745550482\n ],\n [\n -115.58166503906251,\n 34.538237527295756\n ],\n [\n -114.9444580078125,\n 34.66935854524543\n ],\n [\n -114.840087890625,\n 34.84987503195418\n ],\n [\n -114.8895263671875,\n 35.04798673426734\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"13","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Daly, J. A.","contributorId":272613,"corporation":false,"usgs":false,"family":"Daly","given":"J.","email":"","middleInitial":"A.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":832233,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Buhlman, K. A.","contributorId":272614,"corporation":false,"usgs":false,"family":"Buhlman","given":"K.","email":"","middleInitial":"A.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":832234,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Todd, B. D.","contributorId":272615,"corporation":false,"usgs":false,"family":"Todd","given":"B.","email":"","middleInitial":"D.","affiliations":[{"id":36629,"text":"University of California","active":true,"usgs":false}],"preferred":false,"id":832235,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Moore, Clinton T. 0000-0002-6053-2880 cmoore@usgs.gov","orcid":"https://orcid.org/0000-0002-6053-2880","contributorId":3643,"corporation":false,"usgs":true,"family":"Moore","given":"Clinton","email":"cmoore@usgs.gov","middleInitial":"T.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":832236,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Peaden, J. M.","contributorId":272616,"corporation":false,"usgs":false,"family":"Peaden","given":"J. M.","affiliations":[{"id":36629,"text":"University of California","active":true,"usgs":false}],"preferred":false,"id":832237,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Tuberville, T. D.","contributorId":272617,"corporation":false,"usgs":false,"family":"Tuberville","given":"T.","email":"","middleInitial":"D.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":832238,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70259538,"text":"70259538 - 2018 - A geophysical characterization of the structural framework of the Camas Prairie Geothermal System, southcentral Idaho","interactions":[],"lastModifiedDate":"2024-10-11T13:49:16.719504","indexId":"70259538","displayToPublicDate":"2018-12-01T08:38:45","publicationYear":"2018","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"A geophysical characterization of the structural framework of the Camas Prairie Geothermal System, southcentral Idaho","docAbstract":"Play Fairway Analysis methods, utilizing existing geologic, thermal, geochemical, and geophysical data were employed in an initial assessment of geothermal resources in the Snake River Plain. These efforts identified the Camas Prairie in southcentral Idaho as a region with elevated resource potential. Subsequent efforts included structural and geophysical data collection to identify the most favorable structural settings for exploiting resources in the valley. The present work involved high-resolution gravity, magnetic, magnetotellurics (MT), field mapping, and seismic surveys to further characterize the system and target sites for exploration drilling around Barron’s Hot Springs (BHS) in the southwest part of the valley.
Geophysical mapping and modeling reveal that the BHS coincides with a complex intersection of two major fault systems: a prominent NW-trending system that includes the Pothole fault, and EW-trending basin-bounding faults that control NS-extension. This complex zone includes a dense network of EW-oriented faults and a right stepover in the Pothole fault which, given the dominant dextral-normal to normal slip inferred for this fault, would promote extension in the immediate vicinity of the BHS.
Surface faulting in this region indicate Pleistocene or younger slip, and seismic imaging documents offsets of shallow strata that suggest ongoing activity on these structures. MT modeling results show that this zone also coincides with a prominent conductive anomaly, characteristic of the presence of hydrothermal alteration or hydrothermal fluids. These results point to the importance of these structures in maintaining current and long-lived shallow hydrothermal activity around the BHS.
The detailed structural mapping and conceptual framework developed from this study provide critical constraints for siting a drill hole aimed at documenting reservoir characteristics and informing potential future development of these geothermal resources.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Geothermal's role in today's energy market","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Geothermal Resource Council","usgsCitation":"Glen, J.M., Liberty, L., Peacock, J., Gasperikova, E., Earney, T.E., Schermerhorn, W.D., Siler, D.L., Shervais, J., and Dobson, P., 2018, A geophysical characterization of the structural framework of the Camas Prairie Geothermal System, southcentral Idaho, in Geothermal's role in today's energy market, v. 42, p. 466-481.","productDescription":"16 p.","startPage":"466","endPage":"481","ipdsId":"IP-098962","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":462814,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.geothermal-library.org/index.php?mode=pubs&action=view&record=1033924"},{"id":462825,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Camas Prairie study area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -115.5,\n 43.5\n ],\n [\n -115.5,\n 43.1667\n ],\n [\n -114.5,\n 43.1667\n ],\n [\n -114.5,\n 43.5\n ],\n [\n -115.5,\n 43.5\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"42","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Glen, Jonathan M.G. 0000-0002-3502-3355 jglen@usgs.gov","orcid":"https://orcid.org/0000-0002-3502-3355","contributorId":176530,"corporation":false,"usgs":true,"family":"Glen","given":"Jonathan","email":"jglen@usgs.gov","middleInitial":"M.G.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":915655,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Liberty, Lee","contributorId":345105,"corporation":false,"usgs":false,"family":"Liberty","given":"Lee","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":915656,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Peacock, Jared R. 0000-0002-0439-0224","orcid":"https://orcid.org/0000-0002-0439-0224","contributorId":210082,"corporation":false,"usgs":true,"family":"Peacock","given":"Jared R.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":915657,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gasperikova, Erika 0000-0003-1553-4569","orcid":"https://orcid.org/0000-0003-1553-4569","contributorId":345107,"corporation":false,"usgs":false,"family":"Gasperikova","given":"Erika","email":"","affiliations":[{"id":38900,"text":"Lawrence Berkeley National Laboratory","active":true,"usgs":false}],"preferred":false,"id":915658,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Earney, Tait E. 0000-0002-1504-0457","orcid":"https://orcid.org/0000-0002-1504-0457","contributorId":210080,"corporation":false,"usgs":true,"family":"Earney","given":"Tait","email":"","middleInitial":"E.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":915659,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schermerhorn, William D. 0000-0002-0167-378X","orcid":"https://orcid.org/0000-0002-0167-378X","contributorId":210081,"corporation":false,"usgs":true,"family":"Schermerhorn","given":"William","email":"","middleInitial":"D.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":915660,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Siler, Drew L. 0000-0001-7540-8244","orcid":"https://orcid.org/0000-0001-7540-8244","contributorId":203341,"corporation":false,"usgs":true,"family":"Siler","given":"Drew","email":"","middleInitial":"L.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":915661,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Shervais, John 0000-0003-4370-7500","orcid":"https://orcid.org/0000-0003-4370-7500","contributorId":345109,"corporation":false,"usgs":false,"family":"Shervais","given":"John","email":"","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":915662,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Dobson, Patrick","contributorId":345111,"corporation":false,"usgs":false,"family":"Dobson","given":"Patrick","affiliations":[{"id":38900,"text":"Lawrence Berkeley National Laboratory","active":true,"usgs":false}],"preferred":false,"id":915663,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70259533,"text":"70259533 - 2018 - Geothermal potential of the Umatilla Indian Reservation, Oregon: Evidence from detailed geophysical investigations","interactions":[],"lastModifiedDate":"2024-10-11T13:36:56.07466","indexId":"70259533","displayToPublicDate":"2018-12-01T08:18:40","publicationYear":"2018","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Geothermal potential of the Umatilla Indian Reservation, Oregon: Evidence from detailed geophysical investigations","docAbstract":"Recent geologic and geophysical investigations were undertaken in northeastern Oregon to better assess earthquake hazards in the region and determine relative favorability for geothermal energy development on lands of the Confederated Tribes of the Umatilla Indian Reservation (CTUIR). This work was funded in part by a Bureau of Indian Affairs grant awarded to the CTUIR to identify areas most suitable for further exploration of geothermal resources. Results from this work were utilized as inputs to a geothermal favorability modeling process that led to the identification of target sites for further geothermal investigation. Beyond the geothermal aspect of this project, the region is of great tectonic significance as it marks the intersection of two major physiographic and geophysical features, the Klamath-Blue Mountain lineament (KBL) and Olympic-Wallowa lineament (OWL), inferred to represent major basement boundaries. The Thorn Hollow and Hite faults, which appear to be major linkages between the KBL and OWL, run through the study area.\nNew aeromagnetic, gravity and magnetotelluric (MT) surveying, along with fault analyses, were conducted as part of this effort. Detailed geophysical exploration resulted in the collection of 1,380 new gravity stations, 34,524-line kilometers of aeromagnetic data (covering 12,524 km2) and measurements from 36 MT stations. Two-dimensional (2D) forward-modeling was executed along several profiles using gravity and aeromagnetic data, combined with existing geologic mapping and rock property constraints measured from hand samples and outcrops. These models are used to define lithologic contacts in the subsurface in the absence of well logs or borehole data to determine possible geothermal fluid reservoirs, as well as identify major structures that may act as conduits for the upward migration of geothermal fluids.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Geothermal's role in today's energy market","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Geothermal Resources Council","usgsCitation":"Ritzinger, B., Glen, J.M., Peacock, J., Blakely, R.J., Mills, P., Staisch, L.M., Bennett, S.E., and Sherrod, B.L., 2018, Geothermal potential of the Umatilla Indian Reservation, Oregon: Evidence from detailed geophysical investigations, in Geothermal's role in today's energy market, v. 42, p. 925-942.","productDescription":"18 p.","startPage":"925","endPage":"942","ipdsId":"IP-098936","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":462823,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.geothermal-library.org/index.php?mode=pubs&action=view&record=1033960"},{"id":462824,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Umatilla Indian Reservation","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -118.74244913340956,\n 45.79556361851067\n ],\n [\n -118.7698549962068,\n 45.454060713964566\n ],\n [\n -118.2292120664795,\n 45.454060713964566\n ],\n [\n -118.25910937134924,\n 45.80945769607672\n ],\n [\n -118.74244913340956,\n 45.79556361851067\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"42","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ritzinger, Brent 0000-0002-5379-1390 britzinger@usgs.gov","orcid":"https://orcid.org/0000-0002-5379-1390","contributorId":216213,"corporation":false,"usgs":true,"family":"Ritzinger","given":"Brent","email":"britzinger@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":915635,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Glen, Jonathan M.G. 0000-0002-3502-3355 jglen@usgs.gov","orcid":"https://orcid.org/0000-0002-3502-3355","contributorId":176530,"corporation":false,"usgs":true,"family":"Glen","given":"Jonathan","email":"jglen@usgs.gov","middleInitial":"M.G.","affiliations":[{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":915636,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Peacock, Jared R. 0000-0002-0439-0224","orcid":"https://orcid.org/0000-0002-0439-0224","contributorId":210082,"corporation":false,"usgs":true,"family":"Peacock","given":"Jared R.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":915637,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Blakely, Richard J. 0000-0003-1701-5236 blakely@usgs.gov","orcid":"https://orcid.org/0000-0003-1701-5236","contributorId":1540,"corporation":false,"usgs":true,"family":"Blakely","given":"Richard","email":"blakely@usgs.gov","middleInitial":"J.","affiliations":[{"id":662,"text":"Western Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":915638,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mills, Patrick","contributorId":345096,"corporation":false,"usgs":false,"family":"Mills","given":"Patrick","email":"","affiliations":[{"id":13345,"text":"Confederated Tribes of the Umatilla Indian Reservation","active":true,"usgs":false}],"preferred":false,"id":915639,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Staisch, Lydia M. 0000-0002-1414-5994 lstaisch@usgs.gov","orcid":"https://orcid.org/0000-0002-1414-5994","contributorId":167068,"corporation":false,"usgs":true,"family":"Staisch","given":"Lydia","email":"lstaisch@usgs.gov","middleInitial":"M.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":915640,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bennett, Scott E.K. 0000-0002-9772-4122 sekbennett@usgs.gov","orcid":"https://orcid.org/0000-0002-9772-4122","contributorId":5340,"corporation":false,"usgs":true,"family":"Bennett","given":"Scott","email":"sekbennett@usgs.gov","middleInitial":"E.K.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":915641,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sherrod, Brian L. 0000-0002-4492-8631 bsherrod@usgs.gov","orcid":"https://orcid.org/0000-0002-4492-8631","contributorId":2834,"corporation":false,"usgs":true,"family":"Sherrod","given":"Brian","email":"bsherrod@usgs.gov","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":915642,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70203226,"text":"70203226 - 2018 - Effects of rearing environment on behavior of captive-reared whooping cranes","interactions":[],"lastModifiedDate":"2019-05-01T08:27:15","indexId":"70203226","displayToPublicDate":"2018-12-01T08:15:46","publicationYear":"2018","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Effects of rearing environment on behavior of captive-reared whooping cranes","docAbstract":"Whooping cranes (Grus americana) are 1 of the most endangered bird species in North America. In 1999 the Whooping Crane Eastern Partnership was formed to establish a migratory population of whooping cranes in eastern North America. These efforts have been extremely successful in terms of adult survival but reproductive success post-release has been low. One hypothesis developed to explain such low reproductive success is that captive-rearing techniques fail to prepare the birds to be effective parents. Captive-reared whooping cranes at the U.S. Geological Survey, Patuxent Wildlife Research Center, Laurel, Maryland, are either reared by humans in crane costumes or by surrogate conspecific adults. We hypothesized that the 2 captive-rearing techniques differentially shaped chick behavior. To test this, we measured chick behavior daily as well as when chicks were placed in novel environments. Twice per day, every day, 5-minute focal observations were conducted on each chick. When they were introduced to a novel environment, 10-minute focal observations were conducted within 1 hour of introduction. The 2 groups differed significantly: costume-reared chicks were, on average, more stationary than parent-reared birds. These data suggest that future research should be done to determine whether or not rearing technique could have longterm effects on post-release behavior and reproductive success
","largerWorkType":{"id":24,"text":"Conference Paper"},"largerWorkTitle":"Proceedings of the fourteenth North American Crane Workshop","largerWorkSubtype":{"id":19,"text":"Conference Paper"},"conferenceTitle":"North American Crane Workshop","conferenceDate":"January 11-15, 2017","conferenceLocation":"Chattanooga, Tennessee ","language":"English","publisher":"North American Crane Working Group","usgsCitation":"Sadowski, C.L., Olsen, G.H., and McPhee, M.E., 2018, Effects of rearing environment on behavior of captive-reared whooping cranes, in Proceedings of the fourteenth North American Crane Workshop, Chattanooga, Tennessee , January 11-15, 2017, p. 56-66.","productDescription":"11 p.","startPage":"56","endPage":"66","ipdsId":"IP-101609","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":363421,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":363351,"type":{"id":15,"text":"Index Page"},"url":"https://digitalcommons.unl.edu/nacwgproc/353/"}],"publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Sadowski, Christy L.","contributorId":215180,"corporation":false,"usgs":false,"family":"Sadowski","given":"Christy","email":"","middleInitial":"L.","affiliations":[{"id":39193,"text":"University of Wisconsin - Oshkosh","active":true,"usgs":false}],"preferred":false,"id":761784,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Olsen, Glenn H. 0000-0002-7188-6203 golsen@usgs.gov","orcid":"https://orcid.org/0000-0002-7188-6203","contributorId":40918,"corporation":false,"usgs":true,"family":"Olsen","given":"Glenn","email":"golsen@usgs.gov","middleInitial":"H.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":761783,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McPhee, M. Elsbeth","contributorId":215181,"corporation":false,"usgs":false,"family":"McPhee","given":"M.","email":"","middleInitial":"Elsbeth","affiliations":[{"id":39193,"text":"University of Wisconsin - Oshkosh","active":true,"usgs":false}],"preferred":false,"id":761785,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70199070,"text":"sir20185116 - 2018 - Estimating metal concentrations with regression analysis and water-quality surrogates at nine sites on the Animas and San Juan Rivers, Colorado, New Mexico, and Utah","interactions":[],"lastModifiedDate":"2018-12-03T14:33:08","indexId":"sir20185116","displayToPublicDate":"2018-11-30T17:15:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-5116","title":"Estimating metal concentrations with regression analysis and water-quality surrogates at nine sites on the Animas and San Juan Rivers, Colorado, New Mexico, and Utah","docAbstract":"The purpose of this report is to evaluate the use of site-specific regression models to estimate metal concentrations at nine U.S. Geological Survey streamflow-gaging stations on the Animas and San Juan Rivers in Colorado, New Mexico, and Utah. Downstream users could use these regression models to determine if metal concentrations are elevated and pose a risk to water supplies, agriculture, and recreation. Multiple linear-regression models were developed by relating metal concentrations in discrete water-quality samples to continuously monitored streamflow and surrogate parameters (specific conductance, pH, turbidity, and water temperature) collected at the U.S. Geological Survey stations. Models were developed for dissolved and total concentrations of aluminum, arsenic, cadmium, copper, iron, lead, manganese, and zinc using water-quality samples collected from 2005 to 2017 by several Federal, State, Tribal, and local agencies using different collection methods and analytical laboratories. Model performance varied but, in general, models for dissolved metals did not perform as well as those for total metals. Dissolved metals generally were correlated to specific conductance or streamflow and total metals generally were better correlated with turbidity.
Explanatory variables in the models reflected hydrologic and geochemical processes within the basin. A larger number of regression models were statistically significant for the most upstream sites, where metal concentrations were elevated by drainage from abandoned mines and mineralized bedrock. Models generally did not perform as well at downstream sites, especially for dissolved metals, which occurred at lower concentrations than at the upstream sites. In the lower reaches of the rivers, the input of more alkaline water from tributaries and groundwater reduced metal solubility and diluted metal concentrations. The number and distribution of samples in the calibration datasets also may have been a factor in model development. At some sites on the San Juan River, calibration datasets were more limited and did not represent the full range of observed hydrologic and water-quality conditions, especially during storm events in summer and fall. Recommendations for model use are given based on estimates of model precision, biases, and adequacy of the calibration datasets in terms of the number of samples and representativeness of the observed range of streamflow and water-quality conditions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185116","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Mast, M.A., 2018, Estimating metal concentrations with regression analysis and water-quality surrogates at nine sites on the Animas and San Juan Rivers, Colorado, New Mexico, and Utah: U.S. Geological Survey Scientific Investigations Report 2018–5116, 68 p., https://doi.org/10.3133/sir20185116.","productDescription":"Report: vii, 68 p.; Data release","onlineOnly":"Y","ipdsId":"IP-095270","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":359772,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5116/ofr20185116.pdf","text":"Report","size":"77.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5116"},{"id":359771,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5116/coverthb.jpg"},{"id":359773,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9THSFE0","text":"USGS data release","linkHelpText":"Calibration datasets and model archive summaries for regression models developed to estimate metal concentrations at nine sites on the Animas and San Juan Rivers, Colorado, New Mexico, and Utah"}],"country":"United States","state":"Colorado, New Mexico, Utah","otherGeospatial":"Animas River, San Juan River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110,\n 36.5\n ],\n [\n -107.5,\n 36.5\n ],\n [\n -107.5,\n 38\n ],\n [\n -110,\n 38\n ],\n [\n -110,\n 36.5\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
The explosive growth of geospatial data has stimulated the development of many standards aimed at decreasing data heterogeneity and enhancing data use. Well-established design methods for geospatial data standards typically involve the creation of two schemas for data structure, designated here as logical and physical, but this can lead to conceptual inconsistencies and modelling inefficiencies. In this paper we describe a design method that overcomes these issues by incorporating an additional schema – the conceptual schema – and demonstrate its application to the design of GroundWaterML2 (GWML2), a new international standard for groundwater data. Results include not only a new data standard, robustly constructed and tested, but also an enhanced method for geospatial data standard design.
","language":"English","publisher":"Springer","doi":"10.1186/s40965-018-0058-3","usgsCitation":"Brodaric, B., Boisvert, E., Dahlhaus, P., Grellet, S., Kmoch, A., Letourneau, F., Lucido, J., Simons, B., and Wagner, B., 2018, The conceptual schema in geospatial data standard design with application to GroundWaterML2: Open Geospatial Data, Software and Standards, v. 3, p. 1-15, https://doi.org/10.1186/s40965-018-0058-3.","productDescription":"15 p.","startPage":"1","endPage":"15","ipdsId":"IP-104677","costCenters":[{"id":39013,"text":"WMA - Project Management Office","active":true,"usgs":true}],"links":[{"id":468224,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s40965-018-0058-3","text":"Publisher Index Page"},{"id":362256,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-11-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Brodaric, Boyan","contributorId":214353,"corporation":false,"usgs":false,"family":"Brodaric","given":"Boyan","email":"","affiliations":[{"id":13092,"text":"Geological Survey of Canada","active":true,"usgs":false}],"preferred":false,"id":759704,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boisvert, Eric","contributorId":167613,"corporation":false,"usgs":false,"family":"Boisvert","given":"Eric","email":"","affiliations":[{"id":24780,"text":"Geological Survey of Canada, Quebec, QC, Canada","active":true,"usgs":false}],"preferred":false,"id":759705,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dahlhaus, Peter","contributorId":214354,"corporation":false,"usgs":false,"family":"Dahlhaus","given":"Peter","email":"","affiliations":[{"id":39014,"text":"Federation University Australia","active":true,"usgs":false}],"preferred":false,"id":759706,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Grellet, Sylvain","contributorId":214355,"corporation":false,"usgs":false,"family":"Grellet","given":"Sylvain","email":"","affiliations":[{"id":39015,"text":"Bureau de Recherche Géologiques et Minières (BRGM)","active":true,"usgs":false}],"preferred":false,"id":759707,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kmoch, Alexander","contributorId":214356,"corporation":false,"usgs":false,"family":"Kmoch","given":"Alexander","email":"","affiliations":[{"id":39016,"text":"University of Salzburg (Z_GIS)","active":true,"usgs":false}],"preferred":false,"id":759708,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Letourneau, Francois","contributorId":214357,"corporation":false,"usgs":false,"family":"Letourneau","given":"Francois","email":"","affiliations":[{"id":13092,"text":"Geological Survey of Canada","active":true,"usgs":false}],"preferred":false,"id":759709,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lucido, Jessica 0000-0003-2249-4796 jlucido@usgs.gov","orcid":"https://orcid.org/0000-0003-2249-4796","contributorId":214352,"corporation":false,"usgs":true,"family":"Lucido","given":"Jessica","email":"jlucido@usgs.gov","affiliations":[{"id":39013,"text":"WMA - Project Management Office","active":true,"usgs":true}],"preferred":true,"id":759703,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Simons, Bruce","contributorId":214358,"corporation":false,"usgs":false,"family":"Simons","given":"Bruce","email":"","affiliations":[{"id":39017,"text":"CSIRO Land and Water","active":true,"usgs":false}],"preferred":false,"id":759710,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Wagner, Bernhard","contributorId":214359,"corporation":false,"usgs":false,"family":"Wagner","given":"Bernhard","email":"","affiliations":[{"id":39018,"text":"Geological Survey of Bavaria","active":true,"usgs":false}],"preferred":false,"id":759711,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70200505,"text":"ofr20181170 - 2018 - Assessing the impact of open-ocean and back-barrier shoreline change on Dauphin Island, Alabama, at multiple time scales over the last 75 years","interactions":[],"lastModifiedDate":"2025-05-13T16:19:30.858259","indexId":"ofr20181170","displayToPublicDate":"2018-11-30T15:30:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-1170","displayTitle":"Assessing the Impact of Open-Ocean and Back-Barrier Shoreline Change on Dauphin Island, Alabama, at Multiple Time Scales Over the Last 75 Years","title":"Assessing the impact of open-ocean and back-barrier shoreline change on Dauphin Island, Alabama, at multiple time scales over the last 75 years","docAbstract":"Dauphin Island and Little Dauphin Island, collectively, make up a geomorphically complex barrier island system located along Alabama’s southern coast, separating Mississippi Sound from the Gulf of Mexico and Mobile Bay. The barrier island system provides numerous economical (tourism, fisheries) and natural (habitat for migratory birds, natural protection of inland and coastal areas from storms) benefits to the State of Alabama. The complex geomorphology of Dauphin Island is partly a response to temporal variations in the direction and magnitude of sediment transport along and across the barrier island system. In this report, we present open-ocean and back-barrier shoreline change rates at different time scales to evaluate the island’s dominant behavior (expansion or widening and contraction or narrowing) over the last 75 years. The spatial and temporal variability of barrier island width provides baseline and historical context for potential restoration alternatives being considered as part of the Alabama Barrier Island Restoration Feasibility Study. Open-ocean shorelines have eroded continuously over the last 75 years, with rates ranging from 1.5 to 4 meters per year. Back-barrier shorelines are less uniform than open-ocean shorelines, but are, on average, also eroding over the same period. Periods of back-barrier progradation are observed but generally occur during discrete, large altering events like hurricanes that overwash or breach narrow sections of the barrier island. Because both shorelines are eroding, the width of the island has decreased during the last 75 years. The section to the west of a breach that opened during Hurricanes Ivan and Katrina (known as Katrina Cut) exhibits a steady, rapid decrease in width while the section to the east of the breach has gone through periods of expansion and contraction and has only recently begun slowly narrowing. Although the recent trends indicate declining widths, the back-barrier progradation rates in this area were the highest compared to other time periods, which abated extreme narrowing caused by increased open-ocean shoreline erosion. These data and the interpreted results indicate that both short-term (annual) and long-term (decadal) cross-barrier sediment exchange is a key component of sustaining barrier island width. Therefore, any mechanisms that influence this exchange, whether from natural processes (overwash, breaching, or inlet dynamics) or human activities (development, post-storm recovery, restoration), should be considered when evaluating the long-term sustainability of barrier island systems.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181170","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers, Mobile District","usgsCitation":"Smith, C.G., Long, J.W., Henderson, R.E., and Nelson, P.R., 2018, Assessing the impact of open-ocean and back-barrier shoreline change on Dauphin Island, Alabama, at multiple time scales over the last 75 years: U.S. Geological Survey Open-File Report 2018–1170, 20 p., https://doi.org/10.3133/ofr20181170.","productDescription":"vii, 20 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-092796","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":359767,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1170/ofr20181170.pdf","text":"Report","size":"949 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1170"},{"id":359766,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1170/coverthb.jpg"}],"country":"United States","state":"Alabama","otherGeospatial":"Dauphin Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.3626937866211,\n 30.1667\n ],\n [\n -88.03447723388672,\n 30.1667\n ],\n [\n -88.03447723388672,\n 30.3333\n ],\n [\n -88.3626937866211,\n 30.3333\n ],\n [\n -88.3626937866211,\n 30.1667\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
600 4th Street South
St. Petersburg, FL 33701
Landscape carbon (C) flux estimates are necessary for assessing the ability of terrestrial ecosystems to buffer further increases in anthropogenic carbon dioxide (CO2) emissions. Advances in remote sensing have allowed for coarse-scale estimates of gross primary productivity (GPP) (e.g., MODIS 17), yet efforts to assess spatial patterns in respiration lag behind those of GPP. Here, we demonstrate a method to predict growing season soil respiration at a regional scale in a forested ecosystem. We related field measurements (n=144) of growing season soil respiration across subalpine forests in the Southern Rocky Mountains ecoregion to a suite of biophysical predictors with a Random Forest model (30 m pixel size). We found that Landsat Enhanced Vegetation Index (EVI), growing season AI, temperature, precipitation, elevation, and slope aspect explained spatiotemporal variability in soil respiration. Our model had a psuedo-r2 of 0.45 and root mean squared error (RMSE) of roughly one-quarter of the mean value of respiration. Predicted growing season soil respiration across the region was remarkably consistent across 2004, 2005 and 2006 (150-d averages of 542.8, 544.3, and 536.5 g C m-2, respectively). Yet, we observed substantial variability in spatial patterns of soil respiration predictions that varied between years, suggesting that our method is sensitive to changes in respiration drivers. We compared our estimates to MODIS GPP and nocturnal net ecosystem exchange (NEE) derived from eddy covariance towers as a proxy for ecosystem respiration. Averaged across the predictive region, mean predicted growing season soil respiration was 73% of MODIS GPP, while predicted soil respiration was generally within 20% of nocturnal NEE from eddy covariance towers. This study demonstrated that geospatial and remotely-sensed datasets can be used in a statistical modeling framework to estimate soil respiration at landscape scales.
","language":"English","publisher":"AGU","doi":"10.1029/2018JG004613","usgsCitation":"Berryman, E.M., Vanderhoof, M.K., Bradford, J.B., Hawbaker, T., Henne, P., Burns, S.P., Frank, J.M., Birdsey, R.A., and Ryan, M.G., 2018, Estimating soil respiration in a subalpine landscape using point, terrain, climate and greenness data: Journal of Geophysical Research G: Biogeosciences, v. 123, no. 10, p. 3231-3249, https://doi.org/10.1029/2018JG004613.","productDescription":"19 p.","startPage":"3231","endPage":"3249","ipdsId":"IP-097679","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":437667,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P99TRHPB","text":"USGS data release","linkHelpText":"Data release for estimating soil respiration in a subalpine landscape using point, terrain, climate and greenness data"},{"id":360845,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108,\n 39\n ],\n [\n -104,\n 39\n ],\n [\n -104,\n 41.5\n ],\n [\n -108,\n 41.5\n ],\n [\n -108,\n 39\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"123","issue":"10","noUsgsAuthors":false,"publicationDate":"2018-10-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Berryman, Erin Michele 0000-0001-8699-2474 eberryman@usgs.gov","orcid":"https://orcid.org/0000-0001-8699-2474","contributorId":5765,"corporation":false,"usgs":true,"family":"Berryman","given":"Erin","email":"eberryman@usgs.gov","middleInitial":"Michele","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":755441,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vanderhoof, Melanie K. 0000-0002-0101-5533 mvanderhoof@usgs.gov","orcid":"https://orcid.org/0000-0002-0101-5533","contributorId":168395,"corporation":false,"usgs":true,"family":"Vanderhoof","given":"Melanie","email":"mvanderhoof@usgs.gov","middleInitial":"K.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":755442,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bradford, John B. 0000-0001-9257-6303 jbradford@usgs.gov","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":611,"corporation":false,"usgs":true,"family":"Bradford","given":"John","email":"jbradford@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":755443,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hawbaker, Todd 0000-0003-0930-9154 tjhawbaker@usgs.gov","orcid":"https://orcid.org/0000-0003-0930-9154","contributorId":568,"corporation":false,"usgs":true,"family":"Hawbaker","given":"Todd","email":"tjhawbaker@usgs.gov","affiliations":[{"id":547,"text":"Rocky Mountain Geographic Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":755444,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Henne, Paul D. 0000-0003-1211-5545 phenne@usgs.gov","orcid":"https://orcid.org/0000-0003-1211-5545","contributorId":169166,"corporation":false,"usgs":true,"family":"Henne","given":"Paul D.","email":"phenne@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":755445,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Burns, Sean P.","contributorId":98921,"corporation":false,"usgs":true,"family":"Burns","given":"Sean","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":755446,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Frank, John M.","contributorId":11969,"corporation":false,"usgs":true,"family":"Frank","given":"John","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":755447,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Birdsey, Richard A.","contributorId":17751,"corporation":false,"usgs":true,"family":"Birdsey","given":"Richard","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":755448,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Ryan, Michael G.","contributorId":202371,"corporation":false,"usgs":false,"family":"Ryan","given":"Michael","email":"","middleInitial":"G.","affiliations":[{"id":33176,"text":"Rocky Mountain Research Station, USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":755449,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70201136,"text":"70201136 - 2018 - Sewage loading and microbial risk in urban waters of the Great Lakes","interactions":[],"lastModifiedDate":"2018-11-30T15:08:37","indexId":"70201136","displayToPublicDate":"2018-11-30T15:07:27","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3888,"text":"Elementa: Science of the Anthropocene","active":true,"publicationSubtype":{"id":10}},"title":"Sewage loading and microbial risk in urban waters of the Great Lakes","docAbstract":"Despite modern sewer system infrastructure, the release of sewage from deteriorating pipes and sewer overflows is a major water pollution problem in US cities, particularly in coastal watersheds that are highly developed with large human populations. We quantified fecal pollution sources and loads entering Lake Michigan from a large watershed of mixed land use using host-associated indicators. Wastewater treatment plant influent had stable concentrations of human Bacteroides and human Lachnospiraceae with geometric mean concentrations of 2.77 × 107 and 5.94 × 107 copy number (by quantitative PCR) per 100 ml, respectively. Human-associated indicator levels were four orders of magnitude higher than norovirus concentrations, suggesting that these human-associated bacteria could be sensitive indicators of pathogen risk. Norovirus concentrations in these same samples were used in calculations for quantitative microbial risk assessment. Assuming a typical recreational exposure to untreated sewage in water, concentrations of 7,800 copy number of human Bacteroides per 100 mL or 14,000 copy number of human Lachnospiraceae per 100 mL corresponded to an illness risk of 0.03. These levels were exceeded in estuarine waters during storm events with greater than 5 cm of rainfall. Following overflows from combined sewer systems (which must accommodate both sewage and stormwater), concentrations were 10-fold higher than under rainfall conditions. Automated high frequency sampling allowed for loads of human-associated markers to be determined, which could then be related back to equivalent volumes of untreated sewage that were released. Evidence of sewage contamination decreased as ruminant-associated indicators increased approximately one day post-storm, demonstrating the delayed impact of upstream agricultural sources on the estuary. These results demonstrate that urban areas are a diffuse source of sewage contamination to urban waters and that storm-driven release of sewage, particularly when sewage overflows occur, creates a serious though transient human health risk.
","language":"English","publisher":"University of California Press","doi":"10.1525/elementa.301","usgsCitation":"McLellan, S.L., Sauer, E.P., Corsi, S., Bootsma, M.J., Boehm, A.B., Spencer, S.K., and Borchardt, M.A., 2018, Sewage loading and microbial risk in urban waters of the Great Lakes: Elementa: Science of the Anthropocene, v. 6, p. 1-15, https://doi.org/10.1525/elementa.301.","productDescription":"Article 46; 15 p.","startPage":"1","endPage":"15","ipdsId":"IP-096539","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":468225,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1525/elementa.301","text":"Publisher Index Page"},{"id":359858,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Milwaukee River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.5,\n 42.9\n ],\n [\n -87.835693359375,\n 42.9\n ],\n [\n -87.835693359375,\n 43.7\n ],\n [\n -88.5,\n 43.7\n ],\n [\n -88.5,\n 42.9\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"6","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2018-06-20","publicationStatus":"PW","scienceBaseUri":"5c025a68e4b0815414cc782c","contributors":{"authors":[{"text":"McLellan, Sandra L. 0000-0003-3283-1151","orcid":"https://orcid.org/0000-0003-3283-1151","contributorId":210968,"corporation":false,"usgs":false,"family":"McLellan","given":"Sandra","email":"","middleInitial":"L.","affiliations":[{"id":7200,"text":"University of Wisconsin-Milwaukee","active":true,"usgs":false}],"preferred":false,"id":752869,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sauer, Elizabeth P.","contributorId":210969,"corporation":false,"usgs":false,"family":"Sauer","given":"Elizabeth","email":"","middleInitial":"P.","affiliations":[{"id":7200,"text":"University of Wisconsin-Milwaukee","active":true,"usgs":false}],"preferred":false,"id":752870,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Corsi, Steven R. 0000-0003-0583-5536 srcorsi@usgs.gov","orcid":"https://orcid.org/0000-0003-0583-5536","contributorId":172002,"corporation":false,"usgs":true,"family":"Corsi","given":"Steven R.","email":"srcorsi@usgs.gov","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":752868,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bootsma, Melinda J.","contributorId":210970,"corporation":false,"usgs":false,"family":"Bootsma","given":"Melinda","email":"","middleInitial":"J.","affiliations":[{"id":7200,"text":"University of Wisconsin-Milwaukee","active":true,"usgs":false}],"preferred":false,"id":752871,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Boehm, Alexandria B. 0000-0002-8162-5090","orcid":"https://orcid.org/0000-0002-8162-5090","contributorId":210971,"corporation":false,"usgs":false,"family":"Boehm","given":"Alexandria","email":"","middleInitial":"B.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":752872,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Spencer, Susan K.","contributorId":210972,"corporation":false,"usgs":false,"family":"Spencer","given":"Susan","email":"","middleInitial":"K.","affiliations":[{"id":38162,"text":"United States Department of Agriculture Agricultural Research Service","active":true,"usgs":false}],"preferred":false,"id":752873,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Borchardt, Mark A. 0000-0002-6471-2627","orcid":"https://orcid.org/0000-0002-6471-2627","contributorId":210973,"corporation":false,"usgs":false,"family":"Borchardt","given":"Mark","email":"","middleInitial":"A.","affiliations":[{"id":38162,"text":"United States Department of Agriculture Agricultural Research Service","active":true,"usgs":false}],"preferred":false,"id":752874,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70201417,"text":"70201417 - 2018 - Serpentinite‐rich gouge in a creeping segment of the Bartlett Springs Fault, northern California: Comparison with SAFOD and implications for seismic hazard","interactions":[],"lastModifiedDate":"2019-01-28T08:31:21","indexId":"70201417","displayToPublicDate":"2018-11-30T15:03:32","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3524,"text":"Tectonics","active":true,"publicationSubtype":{"id":10}},"title":"Serpentinite‐rich gouge in a creeping segment of the Bartlett Springs Fault, northern California: Comparison with SAFOD and implications for seismic hazard","docAbstract":"An exposure of a creeping segment of the Bartlett Springs Fault (BSF), part of the San Andreas Fault system in northern California, is a ~1.5‐m‐wide zone of serpentinite‐bearing fault gouge cutting through Late Pleistocene fluvial deposits. The fault gouge consists of porphyroclasts of antigorite serpentinite, talc, chlorite, and tremolite‐actinolite, along with some Franciscan metamorphic rocks, in a matrix of the same materials. The Mg‐mineral assemblage is stable at temperatures above 250–300 °C. The BSF gouge is interpreted to have been tectonically incorporated into the fault from depths near the base of the seismogenic zone and to have risen buoyantly to the surface where it is now undergoing right‐lateral displacement. The ultramafic‐rich composition, frictional properties, and inferred mode of emplacement of the BSF serpentinitic gouge correspond to those of the creeping traces of the San Andreas Fault identified in the SAFOD (San Andreas Fault Observatory at Depth) drill hole. This suggests a common origin for creep at both locations. A tectonic model for the source of the ultramafic‐rich materials in the BSF is proposed that potentially could explain the distribution of creep throughout the northernmost San Andreas Fault system.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2018TC005307","usgsCitation":"Moore, D.E., McLaughlin, R., and Lienkaemper, J.J., 2018, Serpentinite‐rich gouge in a creeping segment of the Bartlett Springs Fault, northern California: Comparison with SAFOD and implications for seismic hazard: Tectonics, v. 37, no. 12, p. 4515-4534, https://doi.org/10.1029/2018TC005307.","productDescription":"20 p.","startPage":"4515","endPage":"4534","ipdsId":"IP-092866","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":468226,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2018tc005307","text":"Publisher Index Page"},{"id":437668,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9OUFFKS","text":"USGS data release","linkHelpText":"Data for "Serpentinite-rich Gouge in a Creeping Segment of the Bartlett Springs Fault, Northern California: Comparison with SAFOD and Implications for Seismic Hazard""},{"id":360255,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","volume":"37","issue":"12","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-12-11","publicationStatus":"PW","scienceBaseUri":"5c137dd4e4b006c4f851488c","contributors":{"authors":[{"text":"Moore, Diane E. 0000-0002-8641-1075 dmoore@usgs.gov","orcid":"https://orcid.org/0000-0002-8641-1075","contributorId":2704,"corporation":false,"usgs":true,"family":"Moore","given":"Diane","email":"dmoore@usgs.gov","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":754093,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McLaughlin, Robert J. 0000-0002-4390-2288","orcid":"https://orcid.org/0000-0002-4390-2288","contributorId":211450,"corporation":false,"usgs":true,"family":"McLaughlin","given":"Robert J.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":754094,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lienkaemper, James J. 0000-0002-7578-7042 jlienk@usgs.gov","orcid":"https://orcid.org/0000-0002-7578-7042","contributorId":1941,"corporation":false,"usgs":true,"family":"Lienkaemper","given":"James","email":"jlienk@usgs.gov","middleInitial":"J.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":754095,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70201132,"text":"70201132 - 2018 - Characteristic earthquake magnitude frequency distributions on faults calculated from consensus data in California","interactions":[],"lastModifiedDate":"2019-01-28T08:41:29","indexId":"70201132","displayToPublicDate":"2018-11-30T14:54:52","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2314,"text":"Journal of Geophysical Research B: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Characteristic earthquake magnitude frequency distributions on faults calculated from consensus data in California","docAbstract":"An estimate of the expected earthquake rate at all possible magnitudes is needed for seismic hazard forecasts. Regional earthquake magnitude frequency distributions obey a negative exponential law (Gutenberg‐Richter), but it's unclear if individual faults do. We add three new methods to calculate long‐term California earthquake rupture rates to the existing Uniform California Earthquake Rupture Forecast (UCERF3) efforts to assess method and parameter dependence on magnitude frequency results for individual faults. All solutions show strongly characteristic magnitude‐frequency distributions on the San Andreas and other faults, with higher rates of large earthquakes than would be expected from a Gutenberg‐Richter distribution. This is a necessary outcome that results from fitting high fault slip rates under the overall statewide earthquake rate budget. We find that input data choices can affect the nucleation magnitude‐frequency distribution shape for the San Andreas fault; solutions are closer to a Gutenberg‐Richter distribution if the maximum magnitude allowed for earthquakes that occur away from mapped faults (background events) is raised above the consensus threshold of M=7.6, if the moment rate for background events is reduced, or if the overall maximum magnitude is reduced from M=8.5. We also find that participation magnitude‐frequency distribution shapes can be strongly affected by slip‐rate discontinuities along faults that may be artifacts related to segment boundaries.
","language":"English","publisher":"AGU","doi":"10.1029/2018JB016539","usgsCitation":"Parsons, T.E., Geist, E.L., Console, R., and Carluccio, R., 2018, Characteristic earthquake magnitude frequency distributions on faults calculated from consensus data in California: Journal of Geophysical Research B: Solid Earth, v. 123, no. 12, p. 10,761-10,784, https://doi.org/10.1029/2018JB016539.","productDescription":"24 p.","startPage":"10,761","endPage":"10,784","ipdsId":"IP-102834","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":460803,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2018jb016539","text":"Publisher Index Page"},{"id":359855,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","volume":"123","issue":"12","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-12-15","publicationStatus":"PW","scienceBaseUri":"5c025a69e4b0815414cc782e","contributors":{"authors":[{"text":"Parsons, Thomas E. 0000-0002-0582-4338 tparsons@usgs.gov","orcid":"https://orcid.org/0000-0002-0582-4338","contributorId":2314,"corporation":false,"usgs":true,"family":"Parsons","given":"Thomas","email":"tparsons@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":752848,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Geist, Eric L. 0000-0003-0611-1150 egeist@usgs.gov","orcid":"https://orcid.org/0000-0003-0611-1150","contributorId":1956,"corporation":false,"usgs":true,"family":"Geist","given":"Eric","email":"egeist@usgs.gov","middleInitial":"L.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":752849,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Console, Rodolfo","contributorId":172718,"corporation":false,"usgs":false,"family":"Console","given":"Rodolfo","email":"","affiliations":[{"id":27089,"text":"Center of Integrated Geomorphology for the Mediterranean Area, Potenza, Italy","active":true,"usgs":false}],"preferred":false,"id":752850,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Carluccio, Roberto","contributorId":187465,"corporation":false,"usgs":false,"family":"Carluccio","given":"Roberto","email":"","affiliations":[],"preferred":false,"id":752851,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70202549,"text":"70202549 - 2018 - A video surveillance system to monitor breeding colonies of common terns (Sterna Hirundo)","interactions":[],"lastModifiedDate":"2019-03-08T15:03:15","indexId":"70202549","displayToPublicDate":"2018-11-30T14:52:35","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2498,"text":"Journal of Visualized Experiments","active":true,"publicationSubtype":{"id":10}},"displayTitle":"A video surveillance system to monitor breeding colonies of common terns (Sterna Hirundo)","title":"A video surveillance system to monitor breeding colonies of common terns (Sterna Hirundo)","docAbstract":"Many waterbird populations have faced declines over the last century, including the common tern (Sterna hirundo), a waterbird species with a widespread breeding distribution, that has been recently listed as endangered in some habitats of its range. Waterbird monitoring programs exist to track populations through time; however, some of the more intensive approaches require entering colonies and can be disruptive to nesting populations. This paper describes a protocol that utilizes a minimally invasive surveillance system to continuously monitor common tern nesting behavior in typical ground-nesting colonies. The video monitoring system utilizes wireless cameras focused on individual nests as well as over the colony as a whole, and allows for observation without entering the colony. The video system is powered with several 12 V car batteries that are continuously recharged using solar panels. Footage is recorded using a digital video recorder (DVR) connected to a hard drive, which can be replaced when full. The DVR may be placed outside of the colony to reduce disturbance. In this study, 3,624 h of footage recorded over 63 days in weather conditions ranging from 12.8 °C to 35.0 °C produced 3,006 h (83%) of usable behavioral data. The types of data retrieved from the recorded video can vary; we used it to detect external disturbances and measure nesting behavior during incubation. Although the protocol detailed here was designed for ground-nesting waterbirds, the principal system could easily be modified to accommodate alternative scenarios, such as colonial arboreal nesting species, making it widely applicable to a variety of research needs.
","language":"English","doi":"10.3791/57928","usgsCitation":"Wall, J., Marban, P., Brinker, D., Sullivan, J., Zimnik, M., Murrow, J., McGowan, P.C., Callahan, C.R., and Prosser, D.J., 2018, A video surveillance system to monitor breeding colonies of common terns (Sterna Hirundo): Journal of Visualized Experiments, v. 137, e57928, https://doi.org/10.3791/57928.","productDescription":"e57928","ipdsId":"IP-093212","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":468227,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.3791/57928","text":"External Repository"},{"id":361902,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"137","noUsgsAuthors":false,"publicationDate":"2018-07-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Wall, J.L.","contributorId":214070,"corporation":false,"usgs":false,"family":"Wall","given":"J.L.","email":"","affiliations":[],"preferred":false,"id":759063,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Marban, Paul 0000-0002-4910-6565 pmarban@usgs.gov","orcid":"https://orcid.org/0000-0002-4910-6565","contributorId":196581,"corporation":false,"usgs":true,"family":"Marban","given":"Paul","email":"pmarban@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":759064,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brinker, D.F.","contributorId":10523,"corporation":false,"usgs":true,"family":"Brinker","given":"D.F.","email":"","affiliations":[],"preferred":false,"id":759065,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sullivan, J.D.","contributorId":214071,"corporation":false,"usgs":false,"family":"Sullivan","given":"J.D.","email":"","affiliations":[],"preferred":false,"id":759066,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zimnik, M.","contributorId":214072,"corporation":false,"usgs":false,"family":"Zimnik","given":"M.","affiliations":[],"preferred":false,"id":759067,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Murrow, J.L.","contributorId":101490,"corporation":false,"usgs":true,"family":"Murrow","given":"J.L.","affiliations":[],"preferred":false,"id":759068,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McGowan, P. C.","contributorId":67191,"corporation":false,"usgs":false,"family":"McGowan","given":"P.","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":759069,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Callahan, Carl R.","contributorId":205289,"corporation":false,"usgs":false,"family":"Callahan","given":"Carl","email":"","middleInitial":"R.","affiliations":[{"id":37073,"text":"USFWS, Annapolis MD","active":true,"usgs":false}],"preferred":false,"id":759070,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Prosser, Diann J. 0000-0002-5251-1799 dprosser@usgs.gov","orcid":"https://orcid.org/0000-0002-5251-1799","contributorId":2389,"corporation":false,"usgs":true,"family":"Prosser","given":"Diann","email":"dprosser@usgs.gov","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":759071,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70204264,"text":"70204264 - 2018 - Tidal Wetlands and Estuaries ","interactions":[],"lastModifiedDate":"2019-07-16T14:27:37","indexId":"70204264","displayToPublicDate":"2018-11-30T14:25:59","publicationYear":"2018","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"chapter":"15","title":"Tidal Wetlands and Estuaries ","docAbstract":"1. The top 1 m of tidal wetland soils and estuarine sediments of North America contains 1,886 ± 1046 teragrams of carbon (Tg C). [High confidence, Very likely]
2. Soil carbon accumulation rate (i.e., sediment burial) in North American tidal wetlands is currently 9 ± 5 Tg C per year and estuarine carbon burial is 5 ± 3 Tg C per year. [High confidence, Likely]
3. The lateral flux of carbon from tidal wetlands to estuaries is 16 ± 10 Tg C per year for North America. [Low confidence, Likely]
4. In North America, tidal wetlands remove 27 ± 13 Tg C per year from the atmosphere, estuaries outgas 10 ± 10 Tg C per year to the atmosphere, and the net uptake by the combined wetland-estuary system is 17 ± 16 Tg C per year. [Low confidence, Likely]
5. Research and modeling needs are greatest for understanding responses to accelerated sea level rise, mapping tidal wetland and estuarine extent and quantification of CO2 and CH4 exchange with the atmosphere, especially in large, under-sampled, and rapidly changing regions. [High confidence, Likely]
Note: Confidence levels are provided as appropriate for quantitative, but not qualitative, Key Findings and statements.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Second state of the carbon cycle report (SOCCR2): A sustained assessment report","largerWorkSubtype":{"id":1,"text":"Federal Government Series"},"language":"English","doi":"10.7930/SOCCR2.2018.Ch15","usgsCitation":"Windham-Myers, L., Cai, W.J., Alin, S., Andersson, A., Crosswell, J., Dunton, K., Hernandez-Ayon, J.M., Herrmann, M., Hinson, A.L., Charles Hopkinson, Howard, J., Xinping Hu, Knox, S.H., Kroeger, K., David Lagomasino, Megonigal, P., Najjar, R., Paulsen, M., Dorothy Peteet, Pidgeon, E., Karina Schafer, Elizabeth Watson, Wang, Z.A., and Maria Tzortziou, 2018, Tidal Wetlands and Estuaries , chap. 15 of Second state of the carbon cycle report (SOCCR2): A sustained assessment report, p. 596-648, https://doi.org/10.7930/SOCCR2.2018.Ch15.","productDescription":"53 p.","startPage":"596","endPage":"648","ipdsId":"IP-098391","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":365625,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, Mexico, United States","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"editors":[{"text":"Howard, Jennifer","contributorId":149225,"corporation":false,"usgs":false,"family":"Howard","given":"Jennifer","email":"","affiliations":[{"id":17683,"text":"AAAS Science & Technology Policy Fellow/NOAA","active":true,"usgs":false}],"preferred":false,"id":766252,"contributorType":{"id":2,"text":"Editors"},"rank":18},{"text":"Pidgeon, Emily","contributorId":217016,"corporation":false,"usgs":false,"family":"Pidgeon","given":"Emily","email":"","affiliations":[{"id":16938,"text":"Conservation International","active":true,"usgs":false}],"preferred":false,"id":766253,"contributorType":{"id":2,"text":"Editors"},"rank":19}],"authors":[{"text":"Windham-Myers, Lisamarie","contributorId":216999,"corporation":false,"usgs":true,"family":"Windham-Myers","given":"Lisamarie","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":766231,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cai, Wei Jun","contributorId":217000,"corporation":false,"usgs":false,"family":"Cai","given":"Wei","email":"","middleInitial":"Jun","affiliations":[{"id":39556,"text":"U. 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Texas, Austin","active":true,"usgs":false}],"preferred":false,"id":766236,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hernandez-Ayon, Jose Martin","contributorId":217005,"corporation":false,"usgs":false,"family":"Hernandez-Ayon","given":"Jose","email":"","middleInitial":"Martin","affiliations":[{"id":39560,"text":"Autonomous University of Baja California","active":true,"usgs":false}],"preferred":false,"id":766237,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Herrmann, Maria","contributorId":217006,"corporation":false,"usgs":false,"family":"Herrmann","given":"Maria","email":"","affiliations":[{"id":6738,"text":"The Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":766238,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hinson, Audra 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Schafer","contributorId":217017,"corporation":false,"usgs":false,"family":"Karina Schafer","affiliations":[{"id":12642,"text":"National Science Foundation","active":true,"usgs":false}],"preferred":false,"id":766248,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Wang, Zhaohui Aleck","contributorId":217019,"corporation":false,"usgs":false,"family":"Wang","given":"Zhaohui","email":"","middleInitial":"Aleck","affiliations":[{"id":36711,"text":"Woods Hole Oceanographic Institution","active":true,"usgs":false}],"preferred":false,"id":766250,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Maria Tzortziou","contributorId":217018,"corporation":false,"usgs":false,"family":"Maria Tzortziou","affiliations":[{"id":39562,"text":"City University of New York","active":true,"usgs":false}],"preferred":false,"id":766249,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Elizabeth Watson","contributorId":217020,"corporation":false,"usgs":false,"family":"Elizabeth Watson","affiliations":[{"id":39563,"text":"Drexel University","active":true,"usgs":false}],"preferred":false,"id":766251,"contributorType":{"id":1,"text":"Authors"},"rank":24}]}} ,{"id":70201167,"text":"70201167 - 2018 - GSFLOW-GRASS v1.0.0: GIS-enabled hydrologic modeling of coupled groundwater–surface-water systems","interactions":[],"lastModifiedDate":"2018-12-04T10:32:16","indexId":"70201167","displayToPublicDate":"2018-11-30T10:32:11","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1818,"text":"Geoscientific Model Development","active":true,"publicationSubtype":{"id":10}},"title":"GSFLOW-GRASS v1.0.0: GIS-enabled hydrologic modeling of coupled groundwater–surface-water systems","docAbstract":"The importance of water moving between the atmosphere and aquifers has led to efforts to develop and maintain coupled models of surface water and groundwater. However, developing inputs to these models is usually time-consuming and requires extensive knowledge of software engineering, often prohibiting their use by many researchers and water managers, thus reducing these models' potential to promote science-driven decision-making in an era of global change and increasing water resource stress. In response to this need, we have developed GSFLOW–GRASS, a bundled set of open-source tools that develops inputs for, executes, and graphically displays the results of GSFLOW, the U.S. Geological Survey's coupled groundwater and surface-water flow model. In order to create a robust tool that can be widely implemented over diverse hydro(geo)logic settings, we built a series of GRASS GIS extensions that automatically discretizes a topological surface-water flow network that is linked with an underlying gridded groundwater domain. As inputs, GSFLOW–GRASS requires at a minimum a digital elevation model, a precipitation and temperature record, and estimates of channel parameters and hydraulic conductivity. We demonstrate the broad applicability of the toolbox by successfully testing it in environments with varying degrees of drainage integration, landscape relief, and grid resolution, as well as the presence of irregular coastal boundaries. These examples also show how GSFLOW–GRASS can be implemented to examine the role of groundwater–surface-water interactions in a diverse range of water resource and land management applications.
","language":"English","publisher":"European Geosciences Union","doi":"10.5194/gmd-11-4755-2018","usgsCitation":"Ng, G., Wickert, A.D., Somers, L.D., Saberi, L., Cronkite-Ratcliff, C., Niswonger, R.G., and McKenzie, J.M., 2018, GSFLOW-GRASS v1.0.0: GIS-enabled hydrologic modeling of coupled groundwater–surface-water systems: Geoscientific Model Development, v. 11, p. 4755-4777, https://doi.org/10.5194/gmd-11-4755-2018.","productDescription":"23 p.","startPage":"4755","endPage":"4777","ipdsId":"IP-094852","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":468228,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/gmd-11-4755-2018","text":"Publisher Index Page"},{"id":359917,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-11-30","publicationStatus":"PW","scienceBaseUri":"5c07a063e4b0815414cee77f","contributors":{"authors":[{"text":"Ng, G.-H. Crystal","contributorId":197792,"corporation":false,"usgs":false,"family":"Ng","given":"G.-H. Crystal","affiliations":[],"preferred":false,"id":753014,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wickert, Andrew D.","contributorId":211022,"corporation":false,"usgs":false,"family":"Wickert","given":"Andrew","email":"","middleInitial":"D.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":753015,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Somers, Lauren D.","contributorId":211023,"corporation":false,"usgs":false,"family":"Somers","given":"Lauren","email":"","middleInitial":"D.","affiliations":[{"id":6646,"text":"McGill University","active":true,"usgs":false}],"preferred":false,"id":753016,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Saberi, Leila","contributorId":211024,"corporation":false,"usgs":false,"family":"Saberi","given":"Leila","email":"","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":753017,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cronkite-Ratcliff, Collin 0000-0001-5485-3832 ccronkite-ratcliff@usgs.gov","orcid":"https://orcid.org/0000-0001-5485-3832","contributorId":203951,"corporation":false,"usgs":true,"family":"Cronkite-Ratcliff","given":"Collin","email":"ccronkite-ratcliff@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":753013,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Niswonger, Richard G. 0000-0001-6397-2403 rniswon@usgs.gov","orcid":"https://orcid.org/0000-0001-6397-2403","contributorId":197892,"corporation":false,"usgs":true,"family":"Niswonger","given":"Richard","email":"rniswon@usgs.gov","middleInitial":"G.","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":753018,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McKenzie, Jeffrey M.","contributorId":176299,"corporation":false,"usgs":false,"family":"McKenzie","given":"Jeffrey","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":753019,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70223328,"text":"70223328 - 2018 - Propagation of endangered moapa dace","interactions":[],"lastModifiedDate":"2021-08-24T12:11:17.560164","indexId":"70223328","displayToPublicDate":"2018-11-29T17:29:05","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1337,"text":"Copeia","active":true,"publicationSubtype":{"id":10}},"title":"Propagation of endangered moapa dace","docAbstract":"We report successful captive spawning and rearing of the highly endangered Moapa Dace, Moapa coriacea (approximately 650 individual fish in existence at time of this study). We simulated conditions under which this stream-dwelling southern Nevada cyprinid and similar species spawned and reared in the wild by varying temperature, photoperiod, flow, and substrate in 14 different spawning and rearing treatments in a propagation facility. Successful spawning occurred in artificial streams with the following characteristics: water flow directed both across the bottom gravel substrate into a cobble bed and across the upper water column; 12–14 fish/stream (0.016–0.026 fish/L depending on water level); static water temperature of 30–32°C; photoperiod of 12 h light and 12 h dark; gradual replacement of water from their natal stream with on-site well water; a combination of pelleted, frozen and live food; and minimal disturbance of fish. Nevada Department of Wildlife now uses these techniques successfully to produce fish in a culture setting. Identification of the effective combination of factors to trigger spawning in exceptionally rare fishes can be difficult and time consuming, and limiting factors can be subtle. Sufficient numbers of available test fish, close study and replication of wild spawning conditions, careful documentation, and patience to identify subtle limiting factors are often required to effectively rear and spawn fishes not previously propagated.
","language":"English","publisher":"BioOne","doi":"10.1643/OT-18-036","usgsCitation":"Ruggirello, J., Bonar, S.A., Feuerbacher, O.G., Simons, L.H., and Powers, C., 2018, Propagation of endangered moapa dace: Copeia, v. 106, no. 4, p. 652-662, https://doi.org/10.1643/OT-18-036.","productDescription":"11 p.","startPage":"652","endPage":"662","ipdsId":"IP-102179","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":388394,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","otherGeospatial":"southeast Nevada","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.433349609375,\n 36.19109202182454\n ],\n [\n -114.114990234375,\n 36.19109202182454\n ],\n [\n -114.114990234375,\n 37.02886944696474\n ],\n [\n -115.433349609375,\n 37.02886944696474\n ],\n [\n -115.433349609375,\n 36.19109202182454\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"106","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ruggirello, Jack E.","contributorId":264620,"corporation":false,"usgs":false,"family":"Ruggirello","given":"Jack E.","affiliations":[{"id":40855,"text":"UA","active":true,"usgs":false}],"preferred":false,"id":821765,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bonar, Scott A. 0000-0003-3532-4067 sbonar@usgs.gov","orcid":"https://orcid.org/0000-0003-3532-4067","contributorId":3712,"corporation":false,"usgs":true,"family":"Bonar","given":"Scott","email":"sbonar@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":821763,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Feuerbacher, Olin G.","contributorId":264619,"corporation":false,"usgs":false,"family":"Feuerbacher","given":"Olin","email":"","middleInitial":"G.","affiliations":[{"id":40855,"text":"UA","active":true,"usgs":false}],"preferred":false,"id":821764,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Simons, Lee H.","contributorId":264621,"corporation":false,"usgs":false,"family":"Simons","given":"Lee","email":"","middleInitial":"H.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":821766,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Powers, Chelsea","contributorId":264622,"corporation":false,"usgs":false,"family":"Powers","given":"Chelsea","email":"","affiliations":[{"id":40855,"text":"UA","active":true,"usgs":false}],"preferred":false,"id":821767,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70200652,"text":"sir20185144 - 2018 - Land subsidence along the California Aqueduct in west-central San Joaquin Valley, California, 2003–10","interactions":[],"lastModifiedDate":"2018-11-30T13:15:16","indexId":"sir20185144","displayToPublicDate":"2018-11-29T14:00:39","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-5144","displayTitle":"Land Subsidence Along the California Aqueduct in West-Central San Joaquin Valley, California, 2003–10","title":"Land subsidence along the California Aqueduct in west-central San Joaquin Valley, California, 2003–10","docAbstract":"Extensive groundwater withdrawal from the unconsolidated deposits in the San Joaquin Valley caused widespread aquifer-system compaction and resultant land subsidence from 1926 to 1970—locally exceeding 8.5 meters. The importation of surface water beginning in the early 1950s through the Delta-Mendota Canal and in the early 1970s through the California Aqueduct resulted in decreased groundwater pumping, recovery of water levels, and a reduced rate of compaction in some areas of the San Joaquin Valley. However, drought conditions during 1976–77, 1987–92, and drought conditions and operational reductions in surface-water deliveries during 2007–10 decreased surface-water availability, causing pumping to increase, water levels to decline, and renewed compaction. Land subsidence from this compaction has reduced freeboard and flow capacity of the California Aqueduct, Delta-Mendota Canal, and other canals that deliver irrigation water and transport floodwater.
The U.S. Geological Survey, in cooperation with the California Department of Water Resources, assessed more recent land subsidence near a 145-kilometer reach of the California Aqueduct in the west-central part of the San Joaquin Valley as part of an effort to minimize future subsidence-related damages to the California Aqueduct. The location, magnitude, and stress regime of land-surface deformation during 2003–10 were determined by using data and analyses associated with extensometers, Global Positioning System surveys, Interferometric Synthetic Aperture Radar, spirit-leveling surveys, and groundwater wells. Comparison of continuous Global Positioning System, shallow-extensometer, and groundwater-level data indicated that most of the compaction in this area took place beneath the Corcoran Clay, the primary regional confining unit. The integration of measurements strengthens confidence in individual measurement methods and provides the information at spatial and temporal scales that water managers need to design and implement groundwater sustainability plans in compliance with California’s Sustainable Groundwater Management Act.
Measurements of land-surface deformation during 2003–10 indicated that the parts of the California Aqueduct closest to the Coast Ranges in the west-central part of the San Joaquin Valley were fairly stable or minimally subsiding on an annual basis; some areas show seasonal periods of subsidence and uplift that resulted in little or no longer-term elevation loss. Many groundwater levels in these areas did not reach historical lows during 2003–10, indicating that deformation nearest the Coast Ranges was likely primarily elastic.
Land-surface deformation measurements indicated that some parts of the California Aqueduct that traverse farther from the Coast Ranges toward the valley center subsided. Some parts of the California Aqueduct subsided locally, but generally the California Aqueduct is within part of a 12,000-square-kilometer area affected by 25 millimeters or more of subsidence during 2008–10, with maxima in Madera County, south of the town of El Nido near the San Joaquin River and the Eastside Bypass (540 millimeters), and in Tulare County, west of the town of Pixley (345 millimeters). Interferometric Synthetic Aperture Radar-derived subsidence maps for various periods during 2003–10 show that the area of maximum active subsidence (that is, the largest rates of subsidence) shifted from its historical (1926–70) location southwest of the town of Mendota to these areas nearer the valley center. Calculations indicated that the subsidence rate doubled in 2008 in parts of the study area. Water levels declined during 2007–10 in many shallow and deep wells in the most rapidly subsiding areas, where water levels in many deep wells reached their historical lows, indicating that subsidence measured during this period was largely inelastic.
Continued groundwater-level and land-subsidence monitoring in the San Joaquin Valley is important because (1) operational- and drought-related reductions in surface-water deliveries since 1976 have resulted in increased groundwater pumping and associated water-level declines and land subsidence, (2) land use and associated pumping continue to change throughout the valley, and (3) subsidence management is stipulated in the Sustainable Groundwater Management Act. The availability of surface water remains uncertain; even during record-setting precipitation years, such as 2010–11, water deliveries fell short of requests and groundwater pumping was required to meet the irrigation demand. In some areas, the infrastructure is not available to supply surface water, and groundwater is the only source of water. Because of the expected continued demand for water and the limitations and uncertainty of surface-water supplies, groundwater pumping and associated land subsidence remains a concern. Spatially detailed information on land subsidence is needed to minimize future subsidence-related damages to the California Aqueduct and other infrastructure in the San Joaquin Valley, as well as alterations to natural resources such as stream gradients, water depths, and water temperatures. The integration of data on land-surface elevation, subsurface deformation, and water levels—particularly continuous measurements—enables the analysis of aquifer-system response to groundwater pumping, which in turn, enables estimation of the preconsolidation head and calculation of aquifer-system storage properties. This information can be used to improve numerical model simulations of groundwater flow and aquifer-system compaction and allow for consideration of land subsidence in the evaluation of water resource management alternatives and compliance with the Sustainable Groundwater Management Act.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185144","collaboration":"Prepared in cooperation with the California Department of Water Resources","usgsCitation":"Sneed, M., Brandt, J.T., and Solt, M., 2018, Land subsidence along the California Aqueduct in west-central San Joaquin Valley, California, 2003–10: U.S. Geological Survey Scientific Investigations Report 2018–5144, 67 p., https://doi.org/10.3133/sir20185144. ","productDescription":"x, 67 p.","onlineOnly":"Y","ipdsId":"IP-044802","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":437670,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9NC9LLL","text":"USGS data release","linkHelpText":"Interferometric Synthetic Aperture Radar-Derived Subsidence Contours for the West-Central San Joaquin Valley, California, 2008-10"},{"id":359739,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5144/sir20185144.pdf","text":"Report","size":"16 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Scientfic Investigations Report 2018-5144"},{"id":359738,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5144/coverthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Joaquin Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.5,\n 35.75\n ],\n [\n -119.5,\n 35.75\n ],\n [\n -119.5,\n 37.5\n ],\n [\n -121.5,\n 37.5\n ],\n [\n -121.5,\n 35.75]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
The U.S. Geological Survey monitors groundwater-storage change and land-surface elevation change caused by groundwater withdrawal in Tucson Basin and Avra Valley—the two most populated alluvial basins within the Tucson Active Management Area. The Tucson Active Management Area is one of five active management areas in Arizona established by the 1980 Groundwater Management Act and governed by the Arizona Department of Water Resources. Gravity and land-surface elevation change were monitored every 1 to 3 years at wells and benchmarks in Tucson Basin and Avra Valley from 2003 to 2016. Monitoring resulted in estimates of land-surface elevation change and groundwater-storage change. Interferometric synthetic aperture radar (InSAR) interferograms showing land-surface elevation change were constructed for the Tucson metropolitan area from (1) May 2003 to July 2006, (2) July 2006 to June 2008, (3) June 2008 to April 2011, (4) April 2011 to November 2014, and (5) November 2014 to March 2016. For the Tucson metropolitan area, maximum subsidence of about 2 inches occurred during May 2003 to July 2006. From July 2006 to June 2008, maximum subsidence of approximately 0.8 inches occurred in two regions in the Tucson metropolitan area. From June 2008 to April 2011, about 0.8 inches of subsidence also occurred in two regions. Additionally, for the period April 2011 to November 2014, a maximum of about 0.9 inches of subsidence occurred in the same two regions of Tucson Basin. For the entire monitoring period from May 2003 to March 2016, maximum subsidence of as much as 5.3 inches occurred in the Tucson metropolitan area south of Irvington Road between south 12th Avenue and south Park Avenue, and as much as 4 inches in central Tucson south of Broadway between Country Club Road and Craycroft Road. The InSAR data indicated that there was no significant land-surface deformation from 2003 to 2016 in Avra Valley, and no change in either basin from 2014 to 2016.
The volume of stored groundwater in the monitored part of Tucson Basin showed net zero change from spring 2003 to summer 2006. From summer 2006 to summer 2008 the volume of stored groundwater in the monitored part of Tucson Basin increased approximately 50,000 acre-feet; however, overdraft conditions resumed from summer 2008 to spring 2011, resulting in decreased storage of approximately 178,000 acre-feet. From spring 2011 to fall 2014, the volume of stored groundwater in Tucson Basin decreased about 200,000 acre-feet, following a period of lower than average rainfall in 2012 and 2013. The volume of stored groundwater in the monitored part of Tucson Basin increased approximately 167,000 acre-feet from fall 2014 to spring 2016.
Groundwater storage in Avra Valley increased during the entire monitoring period from spring 2003 to spring 2016, largely as a result of managed recharge of Central Arizona Project water in the monitored region. From 2003 to 2016, artificial recharge in Avra Valley totaled approximately 1,788,000 acre-feet, and in Tucson Basin artificial recharge for the entire period was about 636,790 acre-feet. Artificial recharge exceeded pumping in Avra Valley for each time interval. Pumping in Tucson Basin exceeded artificial recharge for every period except 2014 to 2016. Overall, long-term water-level declines have stabilized or reversed since 2000 at most areas in Tucson Basin and Avra Valley.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185154","collaboration":"Prepared in cooperation with the Arizona Department of Water Resources, Pima County, Tucson Water, the Town of Oro Valley, the Town of Marana, and the Metropolitan Domestic Water Improvement District","usgsCitation":"Carruth, R.L., Kahler, L.M., and Conway, B.D., 2018, Groundwater-storage change and land-surface elevation change in Tucson Basin and Avra Valley, south-central Arizona—2003–2016: U.S. Geological Survey Scientific Investigations Report 2018–5154, 34 p., https://doi.org/10.3133/sir20185154.","productDescription":"vii, 34 p.","numberOfPages":"46","onlineOnly":"Y","ipdsId":"IP-019853","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":359796,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5154/coverthb.jpg"},{"id":359797,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5154/sir20185154.pdf","text":"Report","size":"26 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5154"}],"country":"United States","state":"Arizona","otherGeospatial":"Avra Valley, Tucson Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.5936279296875,\n 31.33311153820117\n ],\n [\n -110.44281005859375,\n 31.33311153820117\n ],\n [\n -110.44281005859375,\n 32.90726224488304\n ],\n [\n -111.5936279296875,\n 32.90726224488304\n ],\n [\n -111.5936279296875,\n 31.33311153820117\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
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