The only known extant population of the diamond darter (Crystallaria cincotta) exists in the lower 37 km of Elk River, WV, USA. Our understanding of diamond darter habitat use was previously limited, because few individuals have been observed during sampling with conventional gears. We quantified microhabitat use of diamond darters based on measurements of water depth, water velocity and per cent substrate composition. Using spotlights at night-time, we sampled 16 sites within the lower 133 km of Elk River and observed a total of 82 diamond darters at 10 of 11 sampling sites within the lower 37 km. Glides, located immediately upstream of riffles, were the primary habitats sampled for diamond darters, which included relatively shallow depths (<1 m), moderate-to-low water velocities (often < 0.5 m·s−1) and a smooth water surface. Microhabitat use (mean ± SE) of diamond darters was estimated for depth (0.47 ± 0.02 m), average velocity (0.27 ± 0.01 m·s−1) and bottom velocity (0.15 ± 0.01 m·s−1). Substrate used (mean ± SE) by diamond darters was predominantly sand intermixed with lesser amounts of gravel and cobble: % sand (52.1 ± 1.6), % small gravel (12.2 ± 0.78), % large gravel (14.2 ± 0.83), % cobble (19.8 ± 0.96) and % boulder (1.6 ± 0.36). Based on our microhabitat use data, conservation and management efforts for this species should consider preserving glide habitats within Elk River. Spotlighting, a successful sampling method for diamond darters, should be considered for study designs of population estimation and long-term monitoring.
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In the western United States, water diversions have caused significant declines in lake levels resulting in increased salinity, placing many aquatic species at risk (Galat and Robinson 1983, Beutel et al. 2001). Severe droughts can have similar effects on salt concentrations and aquatic communities (Swanson et al. 2003). Conversely, large inputs of water can dilute salt concentrations and contribute to community shifts (Euliss et al. 2004).","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"The Prairie Naturalist","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"South Dakota State University","usgsCitation":"Mushet, D.M., McLean, K., and Stockwell, C., 2013, Salamander colonization of Chase Lake, Stutsman County, North Dakota: The Prairie Naturalist, v. 45, p. 106-108.","productDescription":"3 p.","startPage":"106","endPage":"108","ipdsId":"IP-041798","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":287145,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Dakota","county":"Stutsman County","otherGeospatial":"Chase Lake","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -99.48,46.63 ], [ -99.48,47.33 ], [ -98.44,47.33 ], [ -98.44,46.63 ], [ -99.48,46.63 ] ] ] } } ] }","volume":"45","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53749075e4b0870f4d23cfec","contributors":{"authors":[{"text":"Mushet, David M. 0000-0002-5910-2744 dmushet@usgs.gov","orcid":"https://orcid.org/0000-0002-5910-2744","contributorId":1299,"corporation":false,"usgs":true,"family":"Mushet","given":"David","email":"dmushet@usgs.gov","middleInitial":"M.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":487891,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McLean, Kyle I.","contributorId":63316,"corporation":false,"usgs":true,"family":"McLean","given":"Kyle I.","affiliations":[],"preferred":false,"id":487893,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stockwell, Craig A.","contributorId":55257,"corporation":false,"usgs":true,"family":"Stockwell","given":"Craig A.","affiliations":[],"preferred":false,"id":487892,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70045775,"text":"sir20135037 - 2013 - Plankton communities and summertime declines in algal abundance associated with low dissolved oxygen in the Tualatin River, Oregon","interactions":[],"lastModifiedDate":"2013-05-05T16:03:22","indexId":"sir20135037","displayToPublicDate":"2013-05-05T00:00:00","publicationYear":"2013","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":"2013-5037","title":"Plankton communities and summertime declines in algal abundance associated with low dissolved oxygen in the Tualatin River, Oregon","docAbstract":"Phytoplankton populations in the Tualatin River in northwestern Oregon are an important component of the dissolved oxygen (DO) budget of the river and are critical for maintaining DO levels in summer. During the low-flow summer period, sufficient nutrients and a long residence time typically combine with ample sunshine and warm water to fuel blooms of cryptophyte algae, diatoms, green and blue-green algae in the low-gradient, slow-moving reservoir reach of the lower river. Algae in the Tualatin River generally drift with the water rather than attach to the river bottom as a result of moderate water depths, slightly elevated turbidity caused by suspended colloidal material, and dominance of silty substrates. Growth of algae occurs as if on a “conveyor belt” of streamflow, a dynamic system that is continually refreshed with inflowing water. Transit through the system can take as long as 2 weeks during the summer low-flow period. Photosynthetic production of DO during algal blooms is important in offsetting oxygen consumption at the sediment-water interface caused by the decomposition of organic matter from primarily terrestrial sources, and the absence of photosynthesis can lead to low DO concentrations that can harm aquatic life. \n\nThe periods with the lowest DO concentrations in recent years (since 2003) typically occur in August following a decline in algal abundance and activity, when DO concentrations often decrease to less than State standards for extended periods (nearly 80 days). Since 2003, algal populations have tended to be smaller and algal blooms have terminated earlier compared to conditions in the 1990s, leading to more frequent declines in DO to levels that do not meet State standards. This study was developed to document the current abundance and species composition of phytoplankton in the Tualatin River, identify the possible causes of the general decline in algae, and evaluate hypotheses to explain why algal blooms diminish in midsummer. \n\nPlankton and water-quality sample data from 2006 to 2008 were combined with parts of a larger discrete-sample and continuous water-quality monitoring dataset and examined to identify patterns in water-quality and algal conditions since 1991, with a particular emphasis on 2003–08. Longitudinal plankton surveys were conducted in 2006–08 at six sites between river miles (RM) 24.5 and 3.4 at 2- to 3-week intervals, or 5–6 per season, and in-situ bioassay experiments were conducted in 2008 to examine the potential effects of wastewater treatment facility (WWTF) effluent and phosphorus additions on phytoplankton biomass and algal photosynthesis. Phytoplankton and zooplankton community composition, streamflow, and water-quality data were analyzed using multivariate statistical techniques to gain insights into plankton dynamics to determine what factors might be most tied to the abundance and characteristics of the phytoplankton assemblages, and identify possible causes of their declines.\n\nThe connection between low-DO events and algal declines was clearly evident, as bloom crashes were nearly always followed by periods of low DO. Algal blooms occurred each year during 2006–08, producing maximum chlorophyll-a (Chl-a) values in June or July generally in the range of 50–80 micrograms per liter (µg/L). Bloom crashes and absence of sufficient algal photosynthesis in mid- to late-summer contributed to minimum DO concentrations that were less than the State standard of 6.5 milligrams per liter (mg/L) based on the 30-day mean daily concentration, for 62–74 days each year. At times, the absolute minimum State standard (4 mg/L DO) also was not met. To learn more about why low-DO events occurred, specific algal declines during 2003–08 were scrutinized to determine their likely causal factors. From this information, a series of hypotheses were formulated and evaluated in terms of their ability to explain recent declines in algal populations in the river in late summer.\n\nMeteorological, streamflow, turbidity, water temperature, and conductance conditions in the Tualatin River during the 2006–08 summer seasons were not atypical. Natural flow comprised the majority (70–80 percent) of flow each year during spring, but then reduced to 38–40 percent during midsummer when WWTF effluent—which contributed as much as 36 percent—and flow augmentation releases comprised a greater fraction of the flow. Summer 2008 was unusual, however, in the prolonged influence from the Wapato Lake agricultural area near Gaston in the upper part of the basin. The previous winter flooding and levee breach at Wapato Lake caused a much greater area of inundation. As a result, drainage from this area continued into July, much later than normal. A subsequent algal bloom in Wapato Lake then seeded the upper Tualatin River, and this drainage had a profound effect on the downstream plankton community. A large blue-green algae bloom developed—the largest in recent memory—prompting a public health advisory for recreational contact for about two weeks.\n\nAlgal growths and surface blooms are a common feature of the Tualatin River. Most of the dominant algae have growth forms and morphologies that are well suited for planktonic life, employing spines and gas vacuoles to resist settling, forming colonies, and producing mucilage (or toxins) to resist zooplankton grazing. In 2006–08, 143 algal taxa were identified in 117 main-stem samples; diatoms and green algae were more diverse than blue-green, golden, and cryptophyte algae, although these later groups sometimes dominated the overall volumetric abundance (biovolume). The most frequently occurring taxa, occurring in 97–99 percent of samples, were flagellated cryptophytes Cryptomonas erosa and Rhodomonas minuta. Other important algal taxa included centric diatoms Stephanodiscus, Cyclotella, and Melosira species and colonial green algae Scenedesmus and Actinastrum. These taxa comprised the majority of the algal biovolume during much of the growing season. A general seasonal trend in the phytoplankton assemblages was observed, with dominance by filamentous centric diatoms Stephanodiscus and Melosira in spring and early summer, and flagellated cryptophytes and green algae, particularly Chlamydomonas sp., in late-summer; or, in 2008, dominance by blue-green algae Anabaena flos-aquae and Aphanizomenon flos-aquae during the Wapato Lake bloom event.\n\nThere were 99 zooplankton taxa identified from the Tualatin River in 2006–08, composed primarily of cladocerans, copepods, and rotifers. A seasonal increase in zooplankton abundance was observed in early summer just as or shortly after the phytoplankton population began to increase, with populations growing to 15,000−120,000 organisms per cubic meter in the lower river. Zooplankton abundance showed a predictable and distinct longitudinal downstream increase, particularly downstream of Highway 99W (RM 11.6). Although grazing rates were not measured, the data suggest that, at times, zooplankton grazing may affect algal abundance and species composition in the Tualatin River, with diatoms becoming relatively less abundant and flagellated cryptophytes and green algae relatively more abundant during periods when zooplankton densities were highest.\n\nMultivariate statistical analyses identified soluble reactive phosphorus (SRP), natural flow, flow augmentation, and WWTF effluent as important factors influencing Tualatin River phytoplankton populations, with zooplankton density (particularly rotifers and copepods), specific conductance, chloride, and water temperature also having an important influence. Although SRP was highly correlated with the plankton communities, that correlation was likely the result of high or low algal activity (uptake) as SRP concentrations were often reduced to low levels during blooms. While previous studies have already established that phosphorus, among other factors such as flow, places a theoretical cap on the size of the phytoplankton population in the river, sometimes algal declines occur when SRP concentrations are apparently sufficient. To identify alternative causal factors, additional analyses were performed without SRP to focus on other water-quality parameters, zooplankton density, and flow factors. Considering data for all 3 years and including just those samples from the lower Tualatin River not affected by the 2008 Wapato Lake drainage event, three factors (percentage of reservoir flow augmentation, total natural flow, and rotifer density) best explained variations in the phytoplankton assemblages.\n\nAnalyses focusing on the possible causes of algal declines included the above multivariate analyses, scrutiny of 10 specific instances of declines in algal populations during 2003–08 including several bloom–crash sequences, and analyses of historic routine watershed monitoring data from Clean Water Services. Six factors were hypothesized to be important in causing bloom crashes or impeding blooms from rebounding in August: (1) light limitation from cloudy weather, (2) a reduction in the plankton inocula or “seed” entering the lower river from upstream sources, (3) increased summer streamflows, (4) changes in the dominant sources of flow as the percentage of flow augmentation and WWTF discharges have increased, (5) zooplankton grazing, and (6) low concentrations of bioavailable phosphorus (<0.015 milligram per liter). All of these hypotheses are supported in some fashion by the available data and statistical analyses. Zooplankton grazing, short-term declines in photosynthesis from cloudy weather, total flow as it affects residence time, and the dominant source of flow are primary factors responsible for the low-DO events caused by declines in algae in the lower Tualatin River during late summer.\n\nCloudy weather and increased turbidity are known to inhibit algal growth in the Tualatin River, and slight increases in turbidity in recent years may be a problem. Upstream sources of algae are critical in determining the characteristics and size of downstream populations, as illustrated by the Wapato Lake bloom in 2008, but more data are needed from upstream to fully define the importance of this connection. The sources of flow, through their differential contribution of plankton inocula (quality and amount), were, at times, important factors affecting phytoplankton populations. While SRP concentrations were often most highly correlated with phytoplankton species community, the bioavailability of phosphorus is still somewhat unknown and there are several sources to consider. Preliminary bioassay tests suggested that while treated wastewater effluent may stimulate algae at 30 percent concentrations, negative effects (or decreased stimulation) on Chl-a and DO production may occur at concentrations of 50 percent. Targeted data collection and future research will be needed to further understand the importance of these factors on Tualatin River phytoplankton.\n\nWhile the data and analysis completed for this report provide insights into future research and monitoring that would be useful to continue, additional monitoring of turbidity, Chl-a, and plankton abundance and species composition in the upper part of the basin would enhance our understanding of plankton dynamics and factors affecting phytoplankton abundance in the lower river. Assessment of the key upstream sources of algal inocula via surveys of the major flow sources as well as tributaries and wetlands would provide useful information for the management of river water quality. Other studies that could prove useful for developing management strategies include targeted experiments to evaluate the bioavailability of phosphorus from a variety of sources. New research on phytoplankton–zooplankton interactions, and studies of planktivorous fish, might also provide insight about food web dynamics and potential “top-down” effects of fish predation on the plankton communities. In addition, further development of neural-network or other water-quality models would help to evaluate management strategies and provide forecasts of water-quality conditions. Finally, periodic future reassessments of the available data with the multivariate statistical tools used in this study would be helpful to assess whether and how plankton communities are changing, and to continue to shed light on the importance of factors shaping the plankton. Although certain types and sizes of algal blooms are undesirable, minimum phytoplankton populations are an important part of aquatic food webs and are needed to maintain healthy levels of DO in the river. By understanding the sources, characteristics, causal factors, and responses of the plankton communities, management strategies can be developed to improve DO conditions in the lower Tualatin River during the important summer low-flow period.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135037","collaboration":"Prepared in cooperation with Clean Water Services","usgsCitation":"Carpenter, K., and Rounds, S.A., 2013, Plankton communities and summertime declines in algal abundance associated with low dissolved oxygen in the Tualatin River, Oregon: U.S. Geological Survey Scientific Investigations Report 2013-5037, x, 78 p.; Appendixes A-C; Table 10, https://doi.org/10.3133/sir20135037.","productDescription":"x, 78 p.; Appendixes A-C; Table 10","additionalOnlineFiles":"Y","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":271825,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135037.jpg"},{"id":271821,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2013/5037/appendixes/sir20135037_appendixA.xlsx"},{"id":271822,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2013/5037/appendixes/sir20135037_appendixB.xlsx"},{"id":271823,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2013/5037/appendixes/sir20135037_appendixC.xlsx"},{"id":271824,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2013/5037/appendixes/sir20135037_table10.pdf"},{"id":271819,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5037/"},{"id":271820,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5037/pdf/sir20135037.pdf"}],"country":"United States","state":"Oregon","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.6,42.0 ], [ -124.6,46.3 ], [ -116.5,46.3 ], [ -116.5,42.0 ], [ -124.6,42.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5187716ce4b078fc9c244b63","contributors":{"authors":[{"text":"Carpenter, Kurt D. kdcar@usgs.gov","contributorId":1372,"corporation":false,"usgs":true,"family":"Carpenter","given":"Kurt D.","email":"kdcar@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":false,"id":478342,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rounds, Stewart A. 0000-0002-8540-2206 sarounds@usgs.gov","orcid":"https://orcid.org/0000-0002-8540-2206","contributorId":905,"corporation":false,"usgs":true,"family":"Rounds","given":"Stewart","email":"sarounds@usgs.gov","middleInitial":"A.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":478341,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70045773,"text":"ds745 - 2013 - Classifications for Coastal Wetlands Planning, Protection and Restoration Act (CWPPRA) site-specific projects: 2010","interactions":[],"lastModifiedDate":"2013-05-05T16:05:08","indexId":"ds745","displayToPublicDate":"2013-05-05T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"745","title":"Classifications for Coastal Wetlands Planning, Protection and Restoration Act (CWPPRA) site-specific projects: 2010","docAbstract":"The Coastal Wetlands Planning, Protection and Restoration Act (CWPPRA) funds over 100 wetland restoration projects across Louisiana. Integral to the success of CWPPRA is its long-term monitoring program, which enables State and Federal agencies to determine the effectiveness of each restoration effort. One component of this monitoring program is the classification of high-resolution, color-infrared aerial photography at the U.S. Geological Survey’s National Wetlands Research Center in Lafayette, Louisiana.\n\nColor-infrared aerial photography (9- by 9-inch) is obtained before project construction and several times after construction. Each frame is scanned on a photogrametric scanner that produces a high-resolution image in Tagged Image File Format (TIFF). By using image-processing software, these TIFF files are then orthorectified and mosaicked to produce a seamless image of a project area and its associated reference area (a control site near the project that has common environmental features, such as marsh type, soil types, and water salinities.) The project and reference areas are then classified according to pixel value into two distinct classes, land and water. After initial land and water ratios have been established by using photography obtained before and after project construction, subsequent comparisons can be made over time to determine land-water change.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds745","collaboration":"Prepared in cooperation with Coastal Protection and Restoration Authority of Louisiana, U.S. Army Corps of Engineers, U.S. Environmental Protection Agency, U.S. Fish and Wildlife Service, Natural Resources Conservation Service, and National Oceanic and Atmospheric Administration","usgsCitation":"Jones, W.R., and Garber, A., 2013, Classifications for Coastal Wetlands Planning, Protection and Restoration Act (CWPPRA) site-specific projects: 2010: U.S. Geological Survey Data Series 745, Pamphlet: iv, 8 p.; 2010 CWPPRA Maps: 10 Sheets: 58 x 47 inches; Data and Metadata Files, https://doi.org/10.3133/ds745.","productDescription":"Pamphlet: iv, 8 p.; 2010 CWPPRA Maps: 10 Sheets: 58 x 47 inches; Data and Metadata Files","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2010-01-01","temporalEnd":"2010-12-31","ipdsId":"IP-037884","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"links":[{"id":271818,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds745.gif"},{"id":271805,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/745/"},{"id":271806,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/745/DS745.pdf"},{"id":271807,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/745/Maps_online%20only/cs27_2010l_Black%20Bayou%20Hydrologic%20Restoration_letter.pdf"},{"id":271808,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/745/Maps_online%20only/cs27_2010l_Black%20Bayou%20Hydrologic%20Restoration_poster.pdf"},{"id":271809,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/745/Maps_online%20only/cs27_2010l_Black%20Bayou%20Hydrologic%20Restoration_mosaic_ltr.pdf"},{"id":271810,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/745/Maps_online%20only/cs30_2005_2010l_GIWW-Perry%20Ridge%20West%20Bank%20Stabilization_poster.pdf"},{"id":271811,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/745/Maps_online%20only/cs30_2005_2010l_GIWW-Perry%20Ridge%20West%20Bank%20Stabilization_tabloid.pdf"},{"id":271812,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/745/Maps_online%20only/cs30_2010_GIWW-Perry%20Ridge%20West%20Bank%20Stabilization_mosaic_letter.pdf"},{"id":271813,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/745/Maps_online%20only/cs30_2010l_GIWW-Perry%20Ridge%20West%20Bank%20Stabilization_letter.pdf"},{"id":271814,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/745/Maps_online%20only/tv18_2010_Four%20Mile%20Canal%20Terracing%20and%20Sediment%20Trapping_letter.pdf"},{"id":271815,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/745/Maps_online%20only/tv18_2010_Four%20Mile%20Canal%20Terracing%20and%20Sediment%20Trapping_poster.pdf"},{"id":271816,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/745/Maps_online%20only/po06_2010lpr_Fritchie%20Marsh%20Restoration_letter.pdf"},{"id":271817,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/ds/745/downloads2010/"}],"country":"United States","state":"Louisiana","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -94.0,28.9 ], [ -94.0,33.0 ], [ -88.8,33.0 ], [ -88.8,28.9 ], [ -94.0,28.9 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51877151e4b078fc9c244b4f","contributors":{"authors":[{"text":"Jones, William R. 0000-0002-5493-4138 jonesb@usgs.gov","orcid":"https://orcid.org/0000-0002-5493-4138","contributorId":463,"corporation":false,"usgs":true,"family":"Jones","given":"William","email":"jonesb@usgs.gov","middleInitial":"R.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":478339,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Garber, Adrienne 0000-0003-1139-8256 garbera@usgs.gov","orcid":"https://orcid.org/0000-0003-1139-8256","contributorId":464,"corporation":false,"usgs":true,"family":"Garber","given":"Adrienne","email":"garbera@usgs.gov","affiliations":[],"preferred":true,"id":478340,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70045768,"text":"70045768 - 2013 - Floral ecology and insect visitation in riparian Tamarix sp. (saltcedar)","interactions":[],"lastModifiedDate":"2013-05-05T16:11:37","indexId":"70045768","displayToPublicDate":"2013-05-05T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2183,"text":"Journal of Arid Environments","active":true,"publicationSubtype":{"id":10}},"title":"Floral ecology and insect visitation in riparian Tamarix sp. (saltcedar)","docAbstract":"Climate change projections for semiarid and arid North America include reductions in stream discharge that could adversely affect riparian plant species dependent on stream-derived ground water. In order to better understand this potential impact, we used a space-for-time substitution to test the hypotheses that increasing depth-to-groundwater (DGW) is inversely related to Tamarix sp. (saltcedar) flower abundance (F) and nectar production per flower (N). We also assessed whether DGW affected the richness or abundance of insects visiting flowers. We examined Tamarix floral attributes and insect visitation patterns during 2010 and 2011 at three locations along a deep DWG gradient (3.2–4.1 m) on a floodplain terrace adjacent to Las Vegas Wash, an effluent-dominated Mojave Desert stream. Flower abundance and insect visitation patterns differed between years, but no effect from DGW on either F or N was detected. An eruption of a novel non-native herbivore, the splendid tamarisk weevil (Coniatus splendidulus), likely reduced flower production in 2011.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Arid Environments","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.jaridenv.2013.03.009","usgsCitation":"Andersen, D., and Nelson, S.M., 2013, Floral ecology and insect visitation in riparian Tamarix sp. (saltcedar): Journal of Arid Environments, v. 94, p. 1-5-112, https://doi.org/10.1016/j.jaridenv.2013.03.009.","productDescription":"8 p.","startPage":"1-5","endPage":"112","ipdsId":"IP-045358","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":271826,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.jaridenv.2013.03.009"},{"id":271827,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"94","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5187716ae4b078fc9c244b53","contributors":{"authors":[{"text":"Andersen, D.C.","contributorId":19119,"corporation":false,"usgs":true,"family":"Andersen","given":"D.C.","email":"","affiliations":[],"preferred":false,"id":478322,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nelson, S. M.","contributorId":81853,"corporation":false,"usgs":false,"family":"Nelson","given":"S.","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":478323,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70043044,"text":"70043044 - 2013 - Use of general purpose graphics processing units with MODFLOW","interactions":[],"lastModifiedDate":"2013-05-29T13:46:18","indexId":"70043044","displayToPublicDate":"2013-05-05T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1861,"text":"Ground Water","active":true,"publicationSubtype":{"id":10}},"title":"Use of general purpose graphics processing units with MODFLOW","docAbstract":"To evaluate the use of general-purpose graphics processing units (GPGPUs) to improve the performance of MODFLOW, an unstructured preconditioned conjugate gradient (UPCG) solver has been developed. The UPCG solver uses a compressed sparse row storage scheme and includes Jacobi, zero fill-in incomplete, and modified-incomplete lower-upper (LU) factorization, and generalized least-squares polynomial preconditioners. The UPCG solver also includes options for sequential and parallel solution on the central processing unit (CPU) using OpenMP. For simulations utilizing the GPGPU, all basic linear algebra operations are performed on the GPGPU; memory copies between the central processing unit CPU and GPCPU occur prior to the first iteration of the UPCG solver and after satisfying head and flow criteria or exceeding a maximum number of iterations. The efficiency of the UPCG solver for GPGPU and CPU solutions is benchmarked using simulations of a synthetic, heterogeneous unconfined aquifer with tens of thousands to millions of active grid cells. Testing indicates GPGPU speedups on the order of 2 to 8, relative to the standard MODFLOW preconditioned conjugate gradient (PCG) solver, can be achieved when (1) memory copies between the CPU and GPGPU are optimized, (2) the percentage of time performing memory copies between the CPU and GPGPU is small relative to the calculation time, (3) high-performance GPGPU cards are utilized, and (4) CPU-GPGPU combinations are used to execute sequential operations that are difficult to parallelize. Furthermore, UPCG solver testing indicates GPGPU speedups exceed parallel CPU speedups achieved using OpenMP on multicore CPUs for preconditioners that can be easily parallelized.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ground Water","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1111/gwat.12004","usgsCitation":"Hughes, J.D., and White, J., 2013, Use of general purpose graphics processing units with MODFLOW: Ground Water, 14 p., https://doi.org/10.1111/gwat.12004.","productDescription":"14 p.","ipdsId":"IP-039567","costCenters":[{"id":285,"text":"Florida Water Science Center","active":false,"usgs":true}],"links":[{"id":272968,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":272967,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/gwat.12004"}],"country":"United States","noUsgsAuthors":false,"publicationDate":"2013-01-02","publicationStatus":"PW","scienceBaseUri":"51a7236ce4b09db86f875d37","contributors":{"authors":[{"text":"Hughes, Joseph D. 0000-0003-1311-2354 jdhughes@usgs.gov","orcid":"https://orcid.org/0000-0003-1311-2354","contributorId":2492,"corporation":false,"usgs":true,"family":"Hughes","given":"Joseph","email":"jdhughes@usgs.gov","middleInitial":"D.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":472830,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"White, Jeremy T. jwhite@usgs.gov","contributorId":3930,"corporation":false,"usgs":true,"family":"White","given":"Jeremy T.","email":"jwhite@usgs.gov","affiliations":[{"id":270,"text":"FLWSC-Tampa","active":true,"usgs":true}],"preferred":false,"id":472831,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70045769,"text":"sir20135084 - 2013 - Groundwater conditions in Georgia, 2010–2011","interactions":[],"lastModifiedDate":"2017-01-17T20:46:02","indexId":"sir20135084","displayToPublicDate":"2013-05-03T00:00:00","publicationYear":"2013","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":"2013-5084","title":"Groundwater conditions in Georgia, 2010–2011","docAbstract":"The U.S. Geological Survey collects groundwater data and conducts studies to monitor hydrologic conditions, better define groundwater resources, and address problems related to water supply, water use, and water quality. In Georgia, water levels were monitored continuously at 186 wells during calendar year 2010 and at 181 wells during calendar year 2011. Because of missing data or short periods of record (less than 3 years) for several of these wells, a total of 168 wells are discussed in this report. These wells include 17 in the surficial aquifer system, 19 in the Brunswick aquifer system and equivalent sediments, 70 in the Upper Floridan aquifer, 16 in the Lower Floridan aquifer and underlying units, 10 in the Claiborne aquifer, 1 in the Gordon aquifer, 11 in the Clayton aquifer, 14 in the Cretaceous aquifer system, 2 in Paleozoic-rock aquifers, and 8 in crystalline-rock aquifers. Data from the well network indicate that water levels generally declined during the 2010 through 2011 calendar-year period, with water levels declining in 158 wells and rising in 10. Water levels declined over the period of record at 106 wells, increased at 56 wells, and remained relatively constant at 6 wells. In addition to continuous water-level data, periodic water-level measurements were collected and used to construct potentiometric-surface maps for the Upper Floridan aquifer in Camden, Charlton, and Ware Counties, Georgia, and adjacent counties in Florida during May–June 2010, and in the following areas in Georgia: the Brunswick area during August 2010 and August 2011, in the Albany–Dougherty County area during November 2010 and November 2011, and in the Augusta–Richmond County area during October 2010 and August 2011. In general, water levels in these areas were lower during 2011 than during 2010; however, the configuration of the potentiometric surfaces in each of the areas showed little change. Groundwater quality in the Floridan aquifer system is monitored in the Albany, Savannah, and Brunswick areas of Georgia. In the Albany area, nitrate as nitrogen concentrations in the Upper Floridan aquifer during 2011 generally decreased from 2010; however, concentrations in two wells remained above the U.S. Environmental Protection Agency (USEPA) 10-milligrams-per-liter (mg/L) drinking-water standard. In the Savannah area, specific conductance and chloride concentrations were measured in water samples from discrete depths in two wells completed in the Upper Floridan aquifer. Data from the two wells indicate that chloride concentrations in the Upper Floridan aquifer showed little change during calendar years 2010 through 2011 and remained below the 250 mg/L USEPA secondary drinking-water standard. During calendar years 2010 through 2011, chloride concentrations in the Lower Floridan aquifer increased slightly at Tybee Island and Skidaway Island, remaining above the drinking-water standard. In the Brunswick area, maps showing the chloride concentration of water in the Upper Floridan aquifer constructed using data collected from 32 wells during August 2010 and from 30 wells during August 2011 indicate that chloride concentrations remained above the USEPA secondary drinking-water standard in an approximately 2-square-mile area. During calendar years 2010 through 2011, chloride concentrations generally decreased in over 70 percent of the wells sampled during 2011, with a maximum decrease of 200 mg/L in a well located in the north-central part of the Brunswick area.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135084","usgsCitation":"Peck, M., Gordon, D., and Painter, J.A., 2013, Groundwater conditions in Georgia, 2010–2011: U.S. Geological Survey Scientific Investigations Report 2013-5084, iv, 65 p., https://doi.org/10.3133/sir20135084.","productDescription":"iv, 65 p.","numberOfPages":"71","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":271798,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135084.gif"},{"id":271796,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5084/"},{"id":271797,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5084/pdf/sir2013-5084.pdf"}],"country":"United States","state":"Georgia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.640625,\n 43.34116005412307\n ],\n [\n -76.640625,\n 44.85586880735725\n ],\n [\n -72.97119140625,\n 44.85586880735725\n ],\n [\n -72.97119140625,\n 43.34116005412307\n ],\n [\n -76.640625,\n 43.34116005412307\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.562255859375,\n 33.96158628979907\n ],\n [\n -82.430419921875,\n 33.87041555094183\n ],\n [\n -82.210693359375,\n 33.779147331286474\n ],\n [\n -82.1337890625,\n 33.660353121928814\n ],\n [\n -82.210693359375,\n 33.62376800118811\n ],\n [\n -82.056884765625,\n 33.55055114384406\n ],\n [\n -81.925048828125,\n 33.44977658311846\n ],\n [\n -81.93603515625,\n 33.358061612778876\n ],\n [\n -81.84814453125,\n 33.293803558346596\n ],\n [\n -81.7822265625,\n 33.211116472416855\n ],\n [\n -81.705322265625,\n 33.17434155100208\n ],\n [\n -81.6064453125,\n 33.100745405144245\n ],\n [\n -81.54052734375,\n 33.04550781490999\n ],\n [\n -81.463623046875,\n 32.90726224488304\n ],\n [\n -81.441650390625,\n 32.80574473290688\n ],\n [\n -81.4306640625,\n 32.69486597787505\n ],\n [\n -81.34277343749999,\n 32.61161640317033\n ],\n [\n -81.298828125,\n 32.54681317351514\n ],\n [\n -81.1669921875,\n 32.43561304116276\n ],\n [\n -81.903076171875,\n 32.03602003973755\n ],\n [\n -83.1884765625,\n 31.82156451492074\n ],\n [\n -83.265380859375,\n 33.00866349457558\n ],\n [\n -82.96875,\n 33.50475906922609\n ],\n [\n -82.781982421875,\n 34.15272698011818\n ],\n [\n -82.6611328125,\n 34.125447565116126\n ],\n [\n -82.584228515625,\n 34.016241889667015\n ],\n [\n -82.562255859375,\n 33.96158628979907\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5184ce60e4b04d6ec94d6299","contributors":{"authors":[{"text":"Peck, Michael F. mfpeck@usgs.gov","contributorId":1467,"corporation":false,"usgs":true,"family":"Peck","given":"Michael F.","email":"mfpeck@usgs.gov","affiliations":[],"preferred":false,"id":478325,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gordon, Debbie W. 0000-0002-5195-6657","orcid":"https://orcid.org/0000-0002-5195-6657","contributorId":79591,"corporation":false,"usgs":true,"family":"Gordon","given":"Debbie W.","affiliations":[],"preferred":false,"id":478326,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Painter, Jaime A. 0000-0001-8883-9158 jpainter@usgs.gov","orcid":"https://orcid.org/0000-0001-8883-9158","contributorId":1466,"corporation":false,"usgs":true,"family":"Painter","given":"Jaime","email":"jpainter@usgs.gov","middleInitial":"A.","affiliations":[{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":478324,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70045765,"text":"tm6A45 - 2013 - MODFLOW–USG version 1: An unstructured grid version of MODFLOW for simulating groundwater flow and tightly coupled processes using a control volume finite-difference formulation","interactions":[],"lastModifiedDate":"2013-05-03T09:00:59","indexId":"tm6A45","displayToPublicDate":"2013-05-03T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"6-A45","title":"MODFLOW–USG version 1: An unstructured grid version of MODFLOW for simulating groundwater flow and tightly coupled processes using a control volume finite-difference formulation","docAbstract":"A new version of MODFLOW, called MODFLOW–USG (for UnStructured Grid), was developed to support a wide variety of structured and unstructured grid types, including nested grids and grids based on prismatic triangles, rectangles, hexagons, and other cell shapes. Flexibility in grid design can be used to focus resolution along rivers and around wells, for example, or to subdiscretize individual layers to better represent hydrostratigraphic units. MODFLOW–USG is based on an underlying control volume finite difference (CVFD) formulation in which a cell can be connected to an arbitrary number of adjacent cells. To improve accuracy of the CVFD formulation for irregular grid-cell geometries or nested grids, a generalized Ghost Node Correction (GNC) Package was developed, which uses interpolated heads in the flow calculation between adjacent connected cells. MODFLOW–USG includes a Groundwater Flow (GWF) Process, based on the GWF Process in MODFLOW–2005, as well as a new Connected Linear Network (CLN) Process to simulate the effects of multi-node wells, karst conduits, and tile drains, for example. The CLN Process is tightly coupled with the GWF Process in that the equations from both processes are formulated into one matrix equation and solved simultaneously. This robustness results from using an unstructured grid with unstructured matrix storage and solution schemes. MODFLOW–USG also contains an optional Newton-Raphson formulation, based on the formulation in MODFLOW–NWT, for improving solution convergence and avoiding problems with the drying and rewetting of cells. Because the existing MODFLOW solvers were developed for structured and symmetric matrices, they were replaced with a new Sparse Matrix Solver (SMS) Package developed specifically for MODFLOW–USG. The SMS Package provides several methods for resolving nonlinearities and multiple symmetric and asymmetric linear solution schemes to solve the matrix arising from the flow equations and the Newton-Raphson formulation, respectively.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Section A: Ground Water in Book 6 Modeling Techniques ","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm6A45","collaboration":"Groundwater Resources Program Prepared in collaboration with AMEC; This report is Chapter 45 of Section A: Ground Water in Book 6: Modeling Techniques","usgsCitation":"Panday, S., Langevin, C.D., Niswonger, R., Ibaraki, M., and Hughes, J.D., 2013, MODFLOW–USG version 1: An unstructured grid version of MODFLOW for simulating groundwater flow and tightly coupled processes using a control volume finite-difference formulation: U.S. Geological Survey Techniques and Methods 6-A45, Report: vii, 68 p.; Available Software, https://doi.org/10.3133/tm6A45.","productDescription":"Report: vii, 68 p.; Available Software","numberOfPages":"78","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":494,"text":"Office of Groundwater","active":false,"usgs":true}],"links":[{"id":271788,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/tm6A45.gif"},{"id":271786,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/tm/06/a45/pdf/tm6-A45.pdf"},{"id":271787,"type":{"id":7,"text":"Companion Files"},"url":"https://water.usgs.gov/ogw/mfusg/"}],"country":"United States","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5184ce62e4b04d6ec94d62a1","contributors":{"authors":[{"text":"Panday, Sorab","contributorId":100513,"corporation":false,"usgs":true,"family":"Panday","given":"Sorab","affiliations":[],"preferred":false,"id":478318,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Langevin, Christian D. 0000-0001-5610-9759 langevin@usgs.gov","orcid":"https://orcid.org/0000-0001-5610-9759","contributorId":1030,"corporation":false,"usgs":true,"family":"Langevin","given":"Christian","email":"langevin@usgs.gov","middleInitial":"D.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":478314,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Niswonger, Richard G.","contributorId":45402,"corporation":false,"usgs":true,"family":"Niswonger","given":"Richard G.","affiliations":[],"preferred":false,"id":478316,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ibaraki, Motomu","contributorId":81235,"corporation":false,"usgs":true,"family":"Ibaraki","given":"Motomu","email":"","affiliations":[],"preferred":false,"id":478317,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hughes, Joseph D. 0000-0003-1311-2354 jdhughes@usgs.gov","orcid":"https://orcid.org/0000-0003-1311-2354","contributorId":2492,"corporation":false,"usgs":true,"family":"Hughes","given":"Joseph","email":"jdhughes@usgs.gov","middleInitial":"D.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":478315,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70045682,"text":"70045682 - 2013 - Detecting drawdowns masked by environmental stresses with water-level models","interactions":[],"lastModifiedDate":"2015-10-26T13:48:22","indexId":"70045682","displayToPublicDate":"2013-05-02T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1861,"text":"Ground Water","active":true,"publicationSubtype":{"id":10}},"title":"Detecting drawdowns masked by environmental stresses with water-level models","docAbstract":"Detecting and quantifying small drawdown at observation wells distant from the pumping well greatly expands the characterized aquifer volume. However, this detection is often obscured by water level fluctuations such as barometric and tidal effects. A reliable analytical approach for distinguishing drawdown from nonpumping water-level fluctuations is presented and tested here. Drawdown is distinguished by analytically simulating all pumping and nonpumping water-level stresses simultaneously during the period of record. Pumping signals are generated with Theis models, where the pumping schedule is translated into water-level change with the Theis solution. This approach closely matched drawdowns simulated with a complex three-dimensional, hypothetical model and reasonably estimated drawdowns from an aquifer test conducted in a complex hydrogeologic system. Pumping-induced changes generated with a numerical model and analytical Theis model agreed (RMS as low as 0.007 m) in cases where pumping signals traveled more than 1 km across confining units and fault structures. Maximum drawdowns of about 0.05 m were analytically estimated from field investigations where environmental fluctuations approached 0.2 m during the analysis period.
","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ground Water","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1111/gwat.12042","usgsCitation":"Garcia, C., Halford, K.J., and Fenelon, J., 2013, Detecting drawdowns masked by environmental stresses with water-level models: Ground Water, v. 51, no. 3, p. 322-332, https://doi.org/10.1111/gwat.12042.","productDescription":"11 p.","startPage":"322","endPage":"332","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-033308","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":473844,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/gwat.12042","text":"Publisher Index Page"},{"id":271727,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":271726,"rank":2,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/gwat.12042"}],"volume":"51","issue":"3","noUsgsAuthors":false,"publicationDate":"2013-03-07","publicationStatus":"PW","scienceBaseUri":"51837ce4e4b0a21483941a41","contributors":{"authors":[{"text":"Garcia, C.A.","contributorId":90128,"corporation":false,"usgs":true,"family":"Garcia","given":"C.A.","affiliations":[],"preferred":false,"id":478044,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Halford, K. J. 0000-0002-7322-1846","orcid":"https://orcid.org/0000-0002-7322-1846","contributorId":61077,"corporation":false,"usgs":true,"family":"Halford","given":"K.","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":478043,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fenelon, J.M.","contributorId":100430,"corporation":false,"usgs":true,"family":"Fenelon","given":"J.M.","email":"","affiliations":[],"preferred":false,"id":478045,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ]}