Surface-water-quality data in the Rapid Creek Basin in South Dakota were compiled to assess basic trends in the water quality of Rapid Creek. Spatial and temporal patterns in water quality were described for major ions, sediment, total suspended solids, nutrients, field measurements, bacteria, and select metals for the period of 1970–2020, and a water-quality trend analysis was completed for sites with enough data for selected constituents.
Major ions and total suspended solids had higher median concentrations in the lower basin (downstream from the city of Rapid City) relative to the upper and middle basins. Nutrient concentrations were generally low, and increased concentrations were only detected at the sites downstream from the City of Rapid City Water Reclamation Facility. Fecal indicator bacteria (Escherichia coli and fecal coliform) concentrations were highest downstream from the main urbanized area of Rapid City.
Water-quality trends were analyzed for total dissolved solids, specific conductance, calcium, magnesium, total suspended solids, total phosphorus, dissolved phosphorus, and total Kjeldahl nitrogen for the period of 1979–2019. Concentrations for major ions and total dissolved solids typically changed by less than 15 percent. Total dissolved solids concentrations upstream from Rapid City were generally decreasing, whereas concentrations downstream were generally increasing. The flow-averaged geometric mean concentration of total dissolved solids at three sites upstream from Rapid City decreased overall by 3–5 percent, and concentrations at two sites downstream from Rapid City increased by at least 7 percent between 1979 and 2019. Trends in specific conductance in the Rapid Creek Basin were mixed with alternating increasing and decreasing trends at many of the sites between 1979 and 2014. Total suspended solids concentrations were observed to be decreasing at two sites analyzed for trends. Concentrations in total phosphorus were observed to be decreasing at every site analyzed for trends between 1989 and 2014. Significant downward trends in total Kjeldahl nitrogen were observed at two sites in the lower Rapid Creek Basin for the trend period of 1999–2019. The decreases in total suspended solids and nutrient concentrations in the Rapid Creek Basin could be related to several processes such as the implementation of a stormwater management plan in Rapid City, improvements to the water reclamation facility downstream from Rapid City, and residual climatic effects.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225086","collaboration":"Prepared in cooperation with the City of Rapid City","usgsCitation":"Tatge, W.S., Hoogestraat, G.K., and Nustad, R.A., 2022, Water-quality data and trends in the Rapid Creek Basin, South Dakota, 1970–2020: U.S. Geological Survey Scientific Investigations Report 2022–5086, 67 p., https://doi.org/10.3133/sir20225086.","productDescription":"Report: viii, 67 p.; Data Release; Dataset","numberOfPages":"80","onlineOnly":"Y","ipdsId":"IP-133856","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":405392,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20225086/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":405347,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5086/sir20225086.XML"},{"id":405350,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":405346,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5086/sir20225086.pdf","text":"Report","size":"21.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022–5086"},{"id":405345,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5086/coverthb.jpg"},{"id":405349,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9D8BSXR","text":"USGS data release","linkHelpText":"Model scripts and water-quality data for trends in the Rapid Creek Basin, South Dakota, 1970–2020"},{"id":405348,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5086/images"}],"country":"United States","state":"South Dakota","otherGeospatial":"Rapid Creek Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.0185546875,\n 43.84443209873525\n ],\n [\n -102.64251708984374,\n 43.84443209873525\n ],\n [\n -102.64251708984374,\n 44.213709909702054\n ],\n [\n -104.0185546875,\n 44.213709909702054\n ],\n [\n -104.0185546875,\n 43.84443209873525\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Dakota Water Science Center
U.S. Geological Survey
821 East Interstate Avenue, Bismarck, ND 58503
1608 Mountain View Road, Rapid City, SD 57702
The glacial geology and hydrogeology of valley-fill aquifers and their surrounding uplands are described within a 112-square-mile area in southern Otsego and northwestern Delaware Counties, New York, centered around the City of Oneonta. The major valleys include those of the Susquehanna River, Otego Creek, Charlotte Creek, and Schenevus Creek. A variety of data were analyzed to provide a broad picture of the glacial deposits, hydrogeologic framework, aquifer occurrence, and water-resource potential in the area. Both valley-fill and bedrock aquifers are used for water supply within the study area. The valley-fill aquifers consist of coarse-grained stratified drift, are mostly limited to the larger valleys, and have well yields that typically are much greater than those obtained from the bedrock aquifers. The bedrock aquifers generally have lower well yields, are the sole source of groundwater in upland areas, and are tapped in valley areas where sediments are very silty or are absent.
Through and non-through valleys and their orientations relative to ice flow have resulted in a variety of deglacial environments and deposits, some of which depart from glacial stratigraphy typically observed elsewhere in central New York. In comparison to through valleys with low in-valley divides, the regional thinning of ice over the high bedrock divides of the non-through valleys resulted in the earlier and more widespread stagnation of glacial ice, development of dead-ice sinks, and earlier diversion of meltwater from ice north of the divides. As the main through valley in the study area, the Susquehanna River valley is characterized by multiple inferred ice-margin positions with associated outwash deposition or ice-contact deposits. Throughout the study area, valleys orientated parallel or subparallel to the ice flow facilitated the development of long ice tongues; valleys oriented perpendicular to the ice flow led to little ice-tongue development, but they did facilitate the deposition of the extensive kame moraines that now occupy several-mile-long valley reaches. Lacustrine sediments were deposited in proglacial lakes. These sediments underlie most valleys that were oriented parallel and subparallel to ice flow, but they are largely absent in the Charlotte Creek valley, which was oriented perpendicular to the ice flow and now contains an extensive kame moraine. Beneath these lacustrine deposits, sand and gravel were deposited as subaqueous fans, eskers, and the distal parts of delta (kame) terraces, each with variable silt content.
The presence of coarse-grained stratified deposits, their saturated thicknesses, and their recharge potential are the primary controls on aquifer locations in the study area. The most widespread aquifers in the study area consist of sand and gravel and are confined mostly beneath lacustrine deposits. Confined aquifer yields are enhanced by hydraulic connections with unconfined ice-contact deposits along the valley walls, especially where tributary streams cross these deposits and provide additional recharge through streambed infiltration. The Susquehanna River and other large valley creeks provide a potentially large source of recharge to aquifers where groundwater withdrawals from nearby production wells induce infiltration of river water into aquifers. Unconfined aquifers are present where ice-contact deposits extend below the valley floor and are sufficiently saturated. Most surficial outwash deposits in the study area are thinly saturated; thus their water-resource potential is likely to be limited.
The upland areas contain very little stratified drift; therefore, characterization was limited to delineating areas of thick till and thin, or absent, till. Recharge of bedrock aquifers is greatest in areas overlain by thin till or where bedrock is exposed at land surface.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225069","collaboration":"Prepared in cooperation with the New York State Department of Environmental Conservation","usgsCitation":"Heisig, P.M., and Fleisher, P.J., 2022, Glacial geology and hydrogeology of valley-fill aquifers in the Oneonta area, Otsego and Delaware Counties, New York: U.S. Geological Survey Scientific Investigations Report 2022–5069, 35 p., 1 pl., https://doi.org/10.3133/sir20225069.","productDescription":"Report: vii, 35 p.; 1 Plate: 36.00 × 40.00 inches; 1 Figure: 25.00 × 17.00 inches ; Data Releases","numberOfPages":"35","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-118408","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":405214,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9RCQS14","text":"USGS data release","linkHelpText":"Geospatial datasets of the glacial geology and hydrogeology of valley-fill aquifers in the Oneonta area, Otsego and Delaware Counties, New York"},{"id":405211,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20225069/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2022-5069"},{"id":405199,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5069/coverthb.jpg"},{"id":405219,"rank":10,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2022/5069/sir20225069_plate01.pdf","text":"Plate 1","size":"177 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Map of glacial geology and hydrogeology of valley-fill aquifers in the Oneonta area, Otsego and Delaware Counties, New York [layered pdf; to toggle layers, download the file (right-click and select \"Save link as...\") and open it with Adobe Acrobat Reader]"},{"id":405210,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5069/sir20225069.pdf","text":"Report","size":"12.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5069"},{"id":405212,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5069/sir20225069.XML"},{"id":405213,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5069/images/"},{"id":405218,"rank":9,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/sir/2022/5069/sir20225069_fig04a.pdf","text":"Figure 4A","size":"423 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Primary longitudinal hydrogeologic section A.1–A.1′ and secondary longitudinal hydrogeologic section A.2–A.2′ along the Susquehanna River valley, Otsego County, New York"},{"id":405216,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HGQUJL","text":"USGS data release","linkHelpText":"Horizontal-to-vertical spectral ratio (HVSR) soundings in Broome, Chenango, Franklin, Orange, Rensselaer, and Saratoga Counties, New York, and Susquehanna County, Pennsylvania 2010–2019"},{"id":405215,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P92NSO7T","text":"USGS data release","linkHelpText":"Horizontal-to-vertical spectral ratio soundings and depth-to-bedrock data for valley-fill aquifers in the Oneonta area, Otsego and Delaware Counties, New York, 2016–2018"}],"country":"United States","state":"New York","county":"Delaware County, Otsego County","otherGeospatial":"Oneonta area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.1667,\n 42.4167\n ],\n [\n -74.9167,\n 42.4167\n ],\n [\n -74.9167,\n 42.5833\n ],\n [\n -75.1667,\n 42.5833\n ],\n [\n -75.1667,\n 42.4167\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 12180–8349
The Scituate Reservoir is the primary source of drinking water for more than 60 percent of the population of Rhode Island. From October 1, 1982, to September 30, 2019, water years (WYs) 1983–2019 (a water year is the period between October 1 and September 30 and is designated by the year in which it ends), the Providence Water Supply Board maintained a fixed-frequency sampling program at 37 stations to monitor water quality in tributaries to the Scituate Reservoir. The U.S. Geological Survey (USGS), in cooperation with the Providence Water Supply Board, has measured streamflow at selected streamgages in the Scituate Reservoir drainage area since WY 1994, monitored water quality at selected stations since WY 2009, and conducted targeted base-flow and stormflow sampling at five stations in WYs 2016–19. Daily loads and yields of constituents (chloride, nitrite, nitrate, total coliform bacteria, Escherichia coli, and orthophosphate) were determined for sampled days during WYs 2013–19, and trends were examined for the entire period of record, predominantly WYs 1983–2019. USGS water-quality data were used to determine annual loads and yields of chloride and sodium for WYs 2013–19 at 14 stations, and nutrients and suspended sediment for WYs 2016–19 at 5 stations.
Tributaries in the Scituate Reservoir drainage area for WYs 2013–19 were slightly acidic (pH values less than 7.0 standard units) and often below the recommended pH range of 6.5 to 8.5 standard units, as described by the U.S. Environmental Protection Agency (EPA) in the secondary drinking-water regulations. Most measurements of water color in the tributaries were greater than the EPA secondary drinking-water regulation of 15 platinum-cobalt units. Chloride concentrations in Providence Water Supply Board samples rarely exceeded the EPA secondary drinking-water regulation for chloride (250 milligrams per liter); however, chloride concentrations estimated from continuous measurements of specific conductance exceeded the EPA criterion continuous concentration recommended for freshwater (230 milligrams per liter) for short periods ranging from 10 minutes to 26 hours at two streamgages.
Positive trends in pH, color, alkalinity, and chloride at more than half of the monitoring stations were identified for WYs 1983–2019. Fewer than half of the stations had significant trends in turbidity values, and significant trends varied in direction (positive or negative trends). Trend tests were not performed on total coliform bacteria, Escherichia coli, and nitrate concentrations because of analytical method changes that coincide with abrupt shifts in the magnitude and distribution of concentration data.
The median of daily loads and yields of chloride, nitrite, nitrate, orthophosphate, and bacteria determined for each Providence Water Supply Board sample in WYs 2013–19 varied across the 37 monitoring stations, but yields were generally greater at stations in the Moswansicut and Regulating Reservoir subbasins. Average daily yields of chloride and sodium estimated from continuous records of specific-conductance and streamflow data at 14 stations ranged from 42 to 310 kilograms per square mile per day and 28 to 180 kilograms per square mile per day, respectively. The mean annual yields of total phosphorus, total nitrogen, and suspended sediment determined for five stations ranged from 16 to 78 kilograms per square mile, from 370 to 2,100 kilograms per square mile, and from 5,000 to 13,000 kilograms per square mile, respectively. More than half of the nutrient and suspended sediment loads occurred during stormflow.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225043","collaboration":"Prepared in cooperation with the Providence Water Supply Board","usgsCitation":"Spaetzel, A.B., and Smith, K.P., 2022, Water-quality conditions and constituent loads, water years 2013–19, and water-quality trends, water years 1983–2019, in the Scituate Reservoir drainage area, Rhode Island: U.S. Geological Survey Scientific Investigations Report 2022–5043, 102 p., https://doi.org/10.3133/sir20225043.","productDescription":"Report: xiv, 102 p.; Data Release","numberOfPages":"102","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-128796","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":405187,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5043/coverthb.jpg"},{"id":405188,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5043/sir20225043.pdf","text":"Report","size":"10.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5043"},{"id":405190,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P98XCK0R","text":"USGS data release","linkHelpText":"Water-quality, streamflow, and quality-control data supporting estimation of nutrient and sediment loads in the Scituate Reservoir drainage area, Rhode Island, water years 2016–19"},{"id":405191,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5043/sir20225043.XML"},{"id":405192,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5043/images/"}],"country":"United States","state":"Rhode Island","otherGeospatial":"Scituate Reservoir drainage area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -71.79840087890625,\n 41.724180549563606\n ],\n [\n -71.52786254882812,\n 41.724180549563606\n ],\n [\n -71.52786254882812,\n 41.96459591213679\n ],\n [\n -71.79840087890625,\n 41.96459591213679\n ],\n [\n -71.79840087890625,\n 41.724180549563606\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
The greater Houston area of Texas includes approximately 11,000 square miles and encompasses all or part of 11 counties (Harris, Galveston, Fort Bend, Montgomery, Brazoria, Chambers, Grimes, Liberty, San Jacinto, Walker, and Waller). From the early 1900s until the mid-1970s, groundwater withdrawn from the three primary aquifers that compose the Gulf Coast aquifer system—the Chicot, Evangeline, and Jasper aquifers—had been the primary source of water for the greater Houston area. The withdrawal of groundwater was unregulated prior to 1975, resulting in land-surface subsidence caused by large water-level declines in the greater Houston area.
This report, prepared by the U.S. Geological Survey in cooperation with the Harris-Galveston Subsidence District, City of Houston, Fort Bend Subsidence District, Lone Star Groundwater Conservation District, and Brazoria County Groundwater Conservation District, describes updates to the ways in which water-level altitudes and water-level changes in the greater Houston area are presented relative to previous U.S. Geological Survey reports. The first update involves presenting water-level altitudes and water-level changes as a combined (undifferentiated) representation of the Chicot and Evangeline aquifers. The second update concerns the methods used to depict water-level altitudes and water-level changes in the greater Houston area in interpretive reports, with geostatistical interpolation methods replacing manual contouring methods.
The Chicot and Evangeline aquifers have historically been described as distinct hydrogeologic units for the purpose of water-level mapping. A confining unit does not separate these two aquifers in the study area, and water-level data from colocated wells screened in these aquifers indicate that there is likely a substantial degree of hydrogeologic connection. From a groundwater-flow perspective, these two aquifer units predominantly function as a single unit. Hence, the decision was made to combine the Chicot and Evangeline aquifers into a single, undifferentiated hydrogeologic unit for the purposes of assessing water-level altitudes and water-level changes over time. The 2020 water-level altitudes for the Chicot, Evangeline, and Jasper aquifers were re-created in this report from computer algorithms of the contoured datasets as gridded surfaces to demonstrate the similarity of results from geostatistical interpolation methods to those from manual contouring methods.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225064","collaboration":"Prepared in cooperation with the Harris-Galveston Subsidence District, City of Houston, Fort Bend Subsidence District, Lone Star Groundwater Conservation District, and Brazoria County Groundwater Conservation District","usgsCitation":"Ramage, J.K., Braun, C.L., and Ellis, J.H., 2022, Treatment of the Chicot and Evangeline aquifers as a single hydrogeologic unit and use of geostatistical interpolation methods to develop gridded surfaces of water-level altitudes and water-level changes in the Chicot and Evangeline aquifers (undifferentiated) and Jasper aquifer, greater Houston area, Texas, 2021: U.S. Geological Survey Scientific Investigations Report 2022–5064, 51 p., https://doi.org/10.3133/sir20225064.","productDescription":"Report: vi, 51 p.; Data Release; Dataset","numberOfPages":"62","onlineOnly":"Y","ipdsId":"IP-134432","costCenters":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":404777,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":404775,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5064/images"},{"id":404774,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5064/sir20225064.XML"},{"id":404821,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20225065","text":"Scientific Investigations Report 2022–5065","linkHelpText":"—Status of water-level altitudes and long-term water-level changes in the Chicot and Evangeline (undifferentiated) and Jasper aquifers, greater Houston area, Texas, 2021"},{"id":404776,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9R6CX2T","text":"USGS data release","linkHelpText":"Depth to groundwater measured from wells completed in the Chicot and Evangeline (undifferentiated) and Jasper aquifers, greater Houston area, Texas, 2021"},{"id":404771,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5064/coverthb.jpg"},{"id":404772,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5064/sir20225064.pdf","text":"Report","size":"23.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022–5064"}],"country":"United States","state":"Texas","otherGeospatial":"Greater Houston area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.185302734375,\n 28.82061274169944\n ],\n [\n -94.757080078125,\n 28.82061274169944\n ],\n [\n -94.757080078125,\n 30.590637026892917\n ],\n [\n -96.185302734375,\n 30.590637026892917\n ],\n [\n -96.185302734375,\n 28.82061274169944\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oklahoma-Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, TX 78754–4501
As marine ecosystems respond to climate change and other stressors, it is necessary to evaluate current and past hybridization events to gain insight on the outcomes and drivers of such events. Ancestral introgression within the gadids has been suggested to allow cod to inhabit a variety of habitats. Little attention has been given to contemporary hybridization, especially within cold-water-adapted cod (Boreogadus saida Lepechin, 1774 and Arctogadus glacialis Peters, 1872). We used whole-genome, restriction-site associated, and mitochondrial sequence data to explore the degree and direction of hybridization between these species where previous hybridization had not been reported. Although nearly identical morphologically at certain life stages, we detected very distinct nuclear and mitochondrial lineages. We detected one potential hybrid with a Arctogadus mitochondrial haplotype and Boreogadus nuclear genotype, but no early generational hybrids. The presence of a late generation hybrid suggests that at least some hybrids survive to maturity and reproduce. However, a historical introgression event could not be excluded. Contemporary gene flow appears asymmetrical from Arctogadus into Boreogadus, which may be due to overlap in timing of spawning, environmental heterogeneity, or differences in population size. This study provides important baseline information for the degree of potential hybridization between these species within Alaska marine environments.
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/as-2021-0030","usgsCitation":"Wilson, R.E., Sonsthagen, S.A., Lavretsky, P., Majewski, A., Arnason, E., Halldorsdottir, K., Einarsson, A., Wedemeyr, K., and Talbot, S.L., 2022, Low levels of hybridization between sympatric cold-water-adapted Arctic cod and Polar cod in the Beaufort Sea confirm genetic distinctiveness: Arctic Science, v. 8, no. 4, p. 1082-1093, https://doi.org/10.1139/as-2021-0030.","productDescription":"12 p.","startPage":"1082","endPage":"1093","ipdsId":"IP-130423","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":446914,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1139/as-2021-0030","text":"Publisher Index Page"},{"id":433449,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Beaufort Sea, Chukchi Sea","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -174.72007918044827,\n 75.06986491260304\n ],\n [\n -174.76506022895288,\n 69.14800723197729\n ],\n [\n -166.15259714556063,\n 69.52600683358969\n ],\n [\n -156.95456159243057,\n 71.39604084905038\n ],\n [\n -136.81825817727585,\n 69.54036567664357\n ],\n [\n -129.58194373827234,\n 70.33510131179872\n ],\n [\n -126.37318701117965,\n 74.99060622515827\n ],\n [\n -174.72007918044827,\n 75.06986491260304\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"8","issue":"4","noUsgsAuthors":false,"publicationDate":"2022-02-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Wilson, Robert E.","contributorId":293234,"corporation":false,"usgs":false,"family":"Wilson","given":"Robert","email":"","middleInitial":"E.","affiliations":[{"id":63255,"text":"Nebraska State Museum","active":true,"usgs":false}],"preferred":false,"id":908846,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sonsthagen, Sarah A. 0000-0001-6215-5874 ssonsthagen@usgs.gov","orcid":"https://orcid.org/0000-0001-6215-5874","contributorId":3711,"corporation":false,"usgs":true,"family":"Sonsthagen","given":"Sarah","email":"ssonsthagen@usgs.gov","middleInitial":"A.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":908847,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lavretsky, P.","contributorId":341733,"corporation":false,"usgs":false,"family":"Lavretsky","given":"P.","affiliations":[{"id":36422,"text":"University of Texas","active":true,"usgs":false}],"preferred":false,"id":908848,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Majewski, A.","contributorId":341734,"corporation":false,"usgs":false,"family":"Majewski","given":"A.","email":"","affiliations":[{"id":13677,"text":"Fisheries and Oceans Canada","active":true,"usgs":false}],"preferred":false,"id":908849,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Arnason, E.","contributorId":341736,"corporation":false,"usgs":false,"family":"Arnason","given":"E.","email":"","affiliations":[{"id":36649,"text":"University of Iceland","active":true,"usgs":false}],"preferred":false,"id":908850,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Halldorsdottir, K.","contributorId":341738,"corporation":false,"usgs":false,"family":"Halldorsdottir","given":"K.","email":"","affiliations":[{"id":36649,"text":"University of Iceland","active":true,"usgs":false}],"preferred":false,"id":908851,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Einarsson, A.W.","contributorId":341742,"corporation":false,"usgs":false,"family":"Einarsson","given":"A.W.","email":"","affiliations":[{"id":36649,"text":"University of Iceland","active":true,"usgs":false}],"preferred":false,"id":908852,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wedemeyr, K.","contributorId":341745,"corporation":false,"usgs":false,"family":"Wedemeyr","given":"K.","email":"","affiliations":[{"id":20318,"text":"Bureau of Ocean Energy Management","active":true,"usgs":false}],"preferred":false,"id":908853,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Talbot, Sandra L. 0000-0002-3312-7214 stalbot@usgs.gov","orcid":"https://orcid.org/0000-0002-3312-7214","contributorId":140512,"corporation":false,"usgs":true,"family":"Talbot","given":"Sandra","email":"stalbot@usgs.gov","middleInitial":"L.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":908854,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70237270,"text":"70237270 - 2022 - Floodplains and climate change","interactions":[],"lastModifiedDate":"2022-10-06T15:00:23.931708","indexId":"70237270","displayToPublicDate":"2022-08-01T11:35:37","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"seriesTitle":{"id":12617,"text":"IEP Technical Report","active":true,"publicationSubtype":{"id":2}},"seriesNumber":"99","chapter":"4","title":"Floodplains and climate change","docAbstract":"Floodplains are landscape features that are periodically inundated by water from adjacent rivers (Opperman et al. 2010). Ecologically, functional floodplains are characterized by three primary elements: connectivity, flow regime, and spatial scale. Water quantity flowing over floodplains can vary greatly. Based on a flood’s effects on the floodplain, three flood categories have been defined: floodplain-activation floods, floodplain-maintenance floods, and floodplainresetting floods (Box 1). Several physical parameters determine the types of ecosystems on floodplains and the species they will support; these include temperature, water depth, water velocity, and hydrologic connectivity (Opperman et al. 2010). Natural ecosystems commonly found on floodplains include annual vegetation, forests, seasonal wetlands, and permanent ponds or wetlands (Whipple et al. 2012). Floodplains provide many valuable ecosystem services: attenuation of flood flows which reduces flood risk, filtration of surface water, recreation, fisheries, agriculture, biodiversity, food availability, and groundwater recharge, which contributes to more-sustained and cooler dry-season flows (Opperman et al. 2010).
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Box 1
Floodplain-activation flood
A small magnitude flood that occurs relatively frequently and produces characteristic ecological benefits such as food-web productivity and habitat creation for native fish spawning and rearing.
Floodplain-maintenance flood
A higher magnitude flood that, in addition to providing ecological benefits, results in geomorphic changes including bank erosion and deposition on the floodplain.
Floodplain-resetting flood
A very high-magnitude flood that occurs rarely and results in extensive geomorphic changes, such as the scouring of floodplain surfaces and changes in channel location due to avulsion.
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","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Synthesis of data and studies related to the effect of climate change on the ecosystems and biota of the Upper San Francisco Estuary Year 2022","largerWorkSubtype":{"id":2,"text":"State or Local Government Series"},"language":"English","publisher":"Interagency Ecological Program","usgsCitation":"Keeley, A., Khanna, S., Kwan, N., Matthias, B.G., Pien, C., and Wulff, M.L., 2022, Floodplains and climate change: IEP Technical Report 99, 51 p.","productDescription":"51 p.","startPage":"188","endPage":"238","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":408038,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":407971,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://iep.ca.gov/Publications/Library","linkFileType":{"id":5,"text":"html"}}],"country":"United 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(in preparation for the journal Hydrological Processes) and is a summary of the USGS preliminary findings to date.
This report documents the changes in green foliage density (greenness) as measured by satellite vegetation index (VI) data and corresponding evapotranspiration (ET) in the riparian corridor of the Colorado River delta associated with the Minutes 319 and 323 environmental water deliveries using time-series data from 2013 through 2018. The report focuses on what happened only within the riparian corridor’s seven reaches since the 2014 flows, and despite being a continuation of measuring greenness and ET after the 2017 end of Minute 319, this study continued the tracking of these two variables, greenness and ET, in these original riparian corridor focal areas. Two spatial scales are used here: (1) Landsat satellite imagery at 30 m pixels and (2) the EOS-1 satellite sensor the Moderate Resolution Imaging Spectrometer (MODIS) with a resolution of 250 m pixels. The focal period includes 2013 (prepulse flow) and the years 2014-2018, with a focus on imagery collected from the Summer growing seasons 2014 through 2018 (one-year, pre-pulse and several post-pulse years, respectively).
This report re-creates the 2013-2017 Landsat-based results from Jarchow et al. (2017a, b) by using the same region of interest (ROI). The report now provides revised and re-created results using all new imagery acquisition and processing techniques, as well as extraction code, created by the Vegetation Index and Phenology (VIP) Lab of the Biosystems Engineering Department of the University of Arizona (UofA). In 2018, methods employed by the VIP lab (and not ArcGIS) were used. ArcGIS was only used in the newly processed data to display the final difference maps. The entire spatial tile data from NASA was downloaded and processed at the VIP Lab using satellite imagery at two resolutions: 250 m MODIS and 30 m Landsat using three sensors, Landsat 5, Landsat 7 ETM+ and Landsat 8 Operational Land Imager (OLI), with added scenes for each year based on new clear atmosphere requirements. The VIP lab clipped the river boundary and seven riparian reaches from the previously existing ROI used in Jarchow et al. (2017 a, b) for the analyses done under Minute 319. The NASA image datasets for this riparian corridor ROI in seven reaches were re-processed to produce additional vegetation index (VI) information for years 2013 to 2018 for this report. At the same time, the report acquired and processed imagery from 2000- 2018 (data outside the scope of this report and data not shown here). The additional VIs (NDVI, scaled NDVI, EVI, EVI2) were analyzed so that new assessments of greenness and ET could be produced from the imagery datasets following methods in Nagler et al. (2013). These VI choices were based on previous performance comparisons between biophysical ground-based data and radiometric satellite-based data collected from this riparian ecosystem (Nagler et al., 2001) as well as performance related to ET estimation (Nagler et al., 2005a, b) and current advancements in VIs such as EVI2.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Minute 323: Colorado River limitrophe and delta environmental flows monitoring interim report for 2018","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"International Boundary and Water Commission United States and Mexico","usgsCitation":"Nagler, P.L., Barreto-Munoz, A., Jarchow, C., and Didan, K., 2022, Section 5: Remote sensing of vegetation in the riparian corridor of the Colorado River’s delta 2013-2018, 10 p.","productDescription":"10 p.","startPage":"39","endPage":"48","ipdsId":"IP-114755","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":407594,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico, United States","otherGeospatial":"Colorado River Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.17517089843749,\n 31.587894464070395\n ],\n [\n -114.3621826171875,\n 31.587894464070395\n ],\n [\n -114.3621826171875,\n 32.99484290420988\n ],\n [\n -115.17517089843749,\n 32.99484290420988\n ],\n [\n -115.17517089843749,\n 31.587894464070395\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Nagler, Pamela L. 0000-0003-0674-103X pnagler@usgs.gov","orcid":"https://orcid.org/0000-0003-0674-103X","contributorId":1398,"corporation":false,"usgs":true,"family":"Nagler","given":"Pamela","email":"pnagler@usgs.gov","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":853313,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barreto-Munoz, Armando","contributorId":131000,"corporation":false,"usgs":false,"family":"Barreto-Munoz","given":"Armando","email":"","affiliations":[{"id":7204,"text":"University of Arizona, Electrical and Computer Engineering","active":true,"usgs":false}],"preferred":false,"id":853314,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jarchow, Christopher J. 0000-0002-0424-4104","orcid":"https://orcid.org/0000-0002-0424-4104","contributorId":211737,"corporation":false,"usgs":false,"family":"Jarchow","given":"Christopher J.","affiliations":[{"id":38314,"text":"USGS Southwest Biological Science Center, Flagstaff, AZ","active":true,"usgs":false}],"preferred":false,"id":853315,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Didan, Kamel","contributorId":292780,"corporation":false,"usgs":false,"family":"Didan","given":"Kamel","affiliations":[{"id":62999,"text":"Biosystems Engineering, University of Arizona, Tucson, AZ, 85721 USA","active":true,"usgs":false}],"preferred":false,"id":853316,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70232598,"text":"ofr20221030 - 2022 - Mapping structural control through analysis of land-surface deformation for the Rialto-Colton groundwater subbasin, San Bernardino County, California, 1992–2010","interactions":[],"lastModifiedDate":"2026-03-27T20:06:42.204886","indexId":"ofr20221030","displayToPublicDate":"2022-07-29T10:58:41","publicationYear":"2022","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":"2022-1030","displayTitle":"Mapping Structural Control Through Analysis of Land-Surface Deformation for the Rialto-Colton Groundwater Subbasin, San Bernardino County, California, 1992–2010","title":"Mapping structural control through analysis of land-surface deformation for the Rialto-Colton groundwater subbasin, San Bernardino County, California, 1992–2010","docAbstract":"The locations of many faults in and near the Rialto-Colton groundwater subbasin are not precisely known because the spatial density of existing lithologic and hydrologic data used to infer the locations of faults can be sparse. The U.S. Geological Survey, in cooperation with the San Bernardino Valley Municipal Water District, analyzed structural control of groundwater flow in and near the Rialto-Colton groundwater subbasin using Interferometric Synthetic Aperture Radar (InSAR) methods. Faults commonly are barriers to groundwater flow, and the high spatial resolution of InSAR imagery can be used to infer the locations of buried faults where groundwater pumping occurs. InSAR results have revealed three areas in and near the Rialto-Colton groundwater subbasin where buried faults are interpreted as groundwater-flow barriers: the northwestern area about 3 miles northwest of the City of Rialto, the San Jacinto fault area west of the City of San Bernardino, and the southeastern area about 2 miles southeast of the City of Colton. The InSAR results were combined with knowledge gained from previous studies to better define the location and extent of faults acting as groundwater-flow barriers. New data about faults acting as groundwater-flow barriers can be incorporated into future conceptual and hydrologic models of the Rialto-Colton groundwater subbasin and provide water managers information to help effectively manage groundwater resources.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221030","collaboration":"Prepared in cooperation with the San Bernardino Valley Municipal Water District","programNote":"Water Availability and Use Science Program","usgsCitation":"Brandt, J.T., 2022, Mapping structural control through analysis of land-surface deformation for the Rialto-Colton groundwater subbasin, San Bernardino County, California, 1992–2010: U.S. Geological Survey Open-File Report 2022–1030, 11 p., https://doi.org/10.3133/ofr20221030.","productDescription":"Report: vi, 11 p.; Data Release","numberOfPages":"11","onlineOnly":"Y","ipdsId":"IP-084965","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":501769,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113347.htm","linkFileType":{"id":5,"text":"html"}},{"id":403230,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1030/images"},{"id":403228,"rank":1,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1030/ofr20221030.xml"},{"id":403229,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1030/ofr20221030.pdf","text":"Report","size":"3 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":403232,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7P55KJN","text":"Data release","description":"U.S. Geological Survey, 2014, Web interface: U.S. Geological Survey National Water Information System web page, accessed June 11, 2014, at https://doi.org/10.5066/F7P55KJN.","linkHelpText":"Web interface: U.S. Geological Survey National Water Information System web page"},{"id":404520,"rank":5,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1030/covrthb.jpg"},{"id":404546,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221030/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1030"}],"country":"United States","state":"California","county":"San Bernardino County","otherGeospatial":"Rialto-Colton groundwater subbasin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.51319885253905,\n 34.01851844336969\n ],\n [\n -117.2138214111328,\n 34.01851844336969\n ],\n [\n -117.2138214111328,\n 34.19362958613085\n ],\n [\n -117.51319885253905,\n 34.19362958613085\n ],\n [\n -117.51319885253905,\n 34.01851844336969\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
California Water Science Center
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6000 J Street, Placer Hall
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Municipal water supply for Albuquerque, New Mexico, is provided, in part, through diversion of surface water from the Rio Grande by way of the San Juan-Chama Drinking Water Project diversion structure. Changes in surface-water quality along the Rio Grande and its tributaries upstream from the San Juan-Chama Drinking Water Project diversion structure are not well characterized. This study describes the methods and results of an analysis of surface-water-quality trends for selected constituents in the Rio Grande upstream from Albuquerque. Trends were evaluated for differing time periods ranging from 2004 to 2019 by using the Seasonal Kendall Tau (SKT) test and the Weighted Regressions on Time, Discharge, and Season (WRTDS) model.
Water-quality data at three long-term sites were used for the trend analyses in this study, with the Cochiti and Alameda sites along the Rio Grande and the Jemez Canyon Dam site along the Jemez River, a tributary of the Rio Grande. The proximity of the Cochiti and Jemez Canyon Dam sites to dams is a drawback to the analysis because it is difficult to differentiate between the influence of dam management and the influence of streamflow on water-quality trends. The data used also did not fully meet desired levels of seasonal sampling density and had shorter periods of record than typically used for trend analysis, and this should be considered in the interpretation of these results.
Study results indicate that concentrations, and thereby fluxes, are influenced by changes in streamflow at the Alameda site. Most trends from the WRTDS results, obtained by using flow-normalization, were downward for constituents at the Alameda site. Most constituents that were analyzed for trends by using SKT did not have a significant trend at any of the sites included in this study, indicating either that the water quality in the Middle Rio Grande Basin has been stable during the study period or that not enough samples were collected during different seasons to characterize the range of concentration variability with streamflow. The SKT test results indicate upward trends in concentrations of the following constituents: aluminum and antimony at the Alameda site, nitrate and nitrate plus nitrite at the Cochiti site, and potassium and antimony during the spring season at Jemez Canyon Dam. The SKT test results indicate a downward trend in cobalt at the Cochiti site that is subject to bias in the cobalt concentrations. SKT test results also indicate small, downward trends in Kjeldahl nitrogen at the Alameda and Cochiti sites.
Concentrations of water-quality constituents were also compared to Federal and State water-quality standards to provide context and relevance to the results. No concentrations were above the national primary or secondary drinking water standards at the Alameda and Cochiti sites, but the Jemez Canyon Dam site did have concentrations above the U.S. Environmental Protection Agency primary drinking water standard for arsenic and above the national secondary drinking water standards for dissolved solids and aluminum. The Alameda and Cochiti sites are on reaches of the Rio Grande that are listed as impaired for gross alpha particles and the Alameda site is on a reach of the Rio Grande that is listed as impaired for Escherichia coli, but there were no consistent changes in concentrations of these constituents at the impaired locations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225062","collaboration":"Prepared in cooperation with the Albuquerque Bernalillo County Water Utility Authority","usgsCitation":"Flickinger, A.K., and Shephard, Z.M., 2022, Water-quality trends in surface waters of the Jemez River and Middle Rio Grande Basin from Cochiti to Albuquerque, New Mexico, 2004–19: U.S. Geological Survey Scientific Investigations Report 2022–5062, 33 p., https://doi.org/10.3133/sir20225062.","productDescription":"Report: vi, 33 p.; 4 Appendixes; Dataset","numberOfPages":"44","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-125261","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":404243,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5062/coverthb.jpg"},{"id":404250,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":404245,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5062/sir20225062.pdf","text":"Report","size":"4.76 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022–5062"},{"id":404246,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2022/5062/sir20225062_appendixes.xlsx","text":"Appendixes 1–4","size":"59.7 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2022–5062, appendixes 1–4"},{"id":404248,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2022/5062/sir20225062_appendixes.zip","text":"Appendixes 1–4","size":"17.0 kB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2022–5062, appendixes 1–4"},{"id":404251,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5062/sir20225062.XML"},{"id":404252,"rank":7,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5062/images"}],"country":"United States","state":"New Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.24829101562499,\n 33.8430453147447\n ],\n [\n -105.16113281249999,\n 33.8430453147447\n ],\n [\n -105.16113281249999,\n 36.589068371399115\n ],\n [\n -108.24829101562499,\n 36.589068371399115\n ],\n [\n -108.24829101562499,\n 33.8430453147447\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New Mexico Water Science Center
U.S. Geological Survey
6700 Edith Blvd. NE
Albuquerque, NM 87113
Louisiana holds a unique historical, economic, and cultural position in the national consciousness. Its off-shore oil operations help fuel the U.S. economy. The Port of South Louisiana is the busiest in the United States by cargo volume; the nearby Port of New Orleans is the sixth busiest. The former French and Spanish colony served as a key connection to the Caribbean long before U.S. independence, and Louisiana’s multinational effects soon melded into a Creole culture that had an outsized effect on America.
That heritage remains a powerful draw for the tourism industry in Louisiana. Gulf Coast breezes carry the aromas of tropical flowers, sweet beignets, and savory crawfish through the 13 colorful blocks of New Orleans’ French Quarter. Interwoven with the sounds of jazz, rock, country music, and zydeco, the city’s charms delight more than 18 million visitors each year.
The proximity of the Gulf Coast and the city’s elevation, however—just 6.5 feet above sea level—also offer an ominous warning of the ever-present threat of climate change and natural disaster. Hurricane Katrina battered New Orleans in 2005, an incident tied to more than 1,800 deaths that marks one of the most notorious U.S. weather-related tragedies in the 21st century. Environmental changes have amplified threats from tropical storms. Through more frequent and powerful storms, sea level rise threatens low-lying areas such as Lake Charles and creates unpredictable weather patterns that threaten the cities and agricultural operations to the north.
Landsat data offer rich information that can aid in early warning, disaster response, and the monitoring of recovery from natural disasters. Its historic, unparalleled 50-year archive of repeat Earth observations also serves to guide resiliency plans and feeds modeling that can help States like Louisiana prepare for coming coastal and inland change. Here are just a few examples of how Landsat has been used to study and understand Louisiana.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20223059","usgsCitation":"U.S. Geological Survey, 2022, Louisiana and Landsat (ver. 1.1, March 2025): U.S. Geological Survey Fact Sheet 2022–3059, 2 p., https://doi.org/10.3133/fs20223059.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-143119","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":483279,"rank":6,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/fs/2022/3059/versionHist.txt","size":"1 KB","linkFileType":{"id":2,"text":"txt"}},{"id":406526,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/fs20223059/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":404497,"rank":4,"type":{"id":34,"text":"Image 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"nation\":\"USA \"}}]}","edition":"Version 1.0: July 20, 2022; Version 1.1: March 19, 2025","contact":"Program Coordinator, National Land Imaging Program
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
The northern and central parts of the Tug Hill glacial aquifer consist of a 29-mile-long, crescent-shaped, mixture of glaciofluvial, glaciolacustrine, and recent alluvial deposits of predominantly sand and gravel on the western side of the Tug Hill Plateau in Jefferson and Oswego Counties in north-central New York. Approximately 11,400 people are supplied by groundwater that is withdrawn from municipal and nonmunicipal wells in the northern and central parts of the aquifer. In addition, many farms, several industries, and a large New York State fish hatchery also rely on the water from the aquifer.
In the early 2000s, anticipated developmental pressures from potential new industries (including a proposed water-bottling plant in the central part of the Tug Hill glacial aquifer) and expansion of the Fort Drum military base north of Watertown (with the projected increase in population extending into the northern part of the aquifer) prompted the Tug Hill Commission, local municipal officials, and representatives from the New York State Department of Environmental Conservation to initiate a geohydrologic study with the U.S. Geological Survey. The information from this study is intended to help the state, counties, and local communities make sound policy decisions about their use of this large groundwater resource.
The northern part of the Tug Hill glacial aquifer is a combination of glaciofluvial outwash and alluvial sand and gravel in the Sandy Creek Valley northeast of Adams, New York, and mostly glaciolacustrine beach and deltaic sand or sand and gravel north and south of the village of Adams. The southern and eastern areas of the central part of the aquifer are composed mostly of glaciofluvial sediments such as kames, kame moraines, and kame terraces, whereas most of the western areas of the central part are composed mostly of glaciolacustrine sediments such as deltaic sand and beach sand and gravel.
The northern and central parts of the aquifer are unconfined. Recharge to the northern and central parts of the aquifer is from three main sources: (1) precipitation that falls directly onto the aquifer; (2) unchannelized runoff (overland flow) and groundwater from till and bedrock in the Tug Hill Plateau that seeps into the eastern side of the aquifer; and (3) streams that drain the Tug Hill Plateau and flow across and lose water to the aquifer. Groundwater discharges to springs, seeps, headwaters of streams, and wetlands in the middle area of the central part of the aquifer and along the entire western boundary of the northern and central parts of the aquifer; pumping wells; artificial ditches; and deeply incised streams in the northern and central parts of the aquifer. The groundwater discharge to such streams is critical in supporting the salmonid fishery in the central part of the aquifer.
Groundwater levels were measured on July 17, 2014, at 22 wells throughout the northern and central parts of the aquifer. Water-table contours were drawn on the basis of the measured July 2014 water levels, historical water-level data, and surface-water levels where surface water in the channels was expected to be hydraulically connected to the groundwater system. The water table generally slopes from east to west throughout the northern and central parts of the aquifer; this slope also indicates that the direction of groundwater flow is generally from east to west.
Water-quality samples were collected from 23 stream sites during base-flow conditions, and groundwater-quality and other types of environmental samples were collected from 20 wells in the northern and central parts of the Tug Hill glacial aquifer. The results of the sampling indicate that surface water and groundwater are generally of good quality.
Comparison of the median concentration values of major ions in groundwater samples indicated that hardness in the northern part of the aquifer was about twice as great, and concentrations of calcium and sodium were more than three times as great, as in the central part of the aquifer. As was the case with surface water, the much greater median concentrations in groundwater of calcium, hardness, and alkalinity in the northern part of the aquifer are due to the dissolution of limestone that underlies most of that area and to the high-carbonate content of the clasts in the sand and gravel. There was little to no difference among the median values for bromide, fluoride, silica, and iron in the two parts of the aquifer. Concentrations of most other major ions were slightly greater in the northern part than in the central part of the Tug Hill glacial aquifer, except for magnesium, whose concentration was greater in the central part. Median concentrations of nutrients were generally greatest in surface water and groundwater in the northern part of the aquifer.
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New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 12180–8349
Water samples collected from 27 rivers and streams in Massachusetts were analyzed to characterize the presence and concentrations of per- and polyfluoroalkyl substances (collectively known as PFAS) in surface waters across the Commonwealth. Sampling sites were selected in urban rivers where PFAS were expected to be present, such as those that receive treated municipal wastewater, and in rural rivers that were not known to be affected by municipal wastewater. The samples were collected three times in 2020 from 64 sites, and were analyzed for 24 PFAS, 18 of which are included in the U.S. Environmental Protection Agency’s Method 537.1.
Samples were collected when the instantaneous flow of the rivers and streams were at base-flow condition to minimize PFAS input or dilution from stormwater runoff and overland flow. The analyses detected PFAS in samples from all 27 rivers and streams. The number of PFAS detected in each sample ranged from 2 to 16. Concentrations of individual PFAS ranged from no detectable concentrations (less than 1.74 nanograms per liter) to 109 nanograms per liter. Samples from sites associated with wastewater treatment facilities in urban areas had a larger number and variety of PFAS present, and at higher concentrations, than in samples from the more rural rivers. This report includes a summary of the chemical data and physical properties of both environmental and quality-control samples, and a description of procedures for the collection and processing of the samples.
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\"}}]}","edition":"Version 1.0: July 20, 2022; Version 1.1: February 17, 2023; Version 2.0: October 2, 2023","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
Concentrations of suspended sediment were measured in discrete samples and turbidity was continuously monitored at four U.S. Geological Survey streamgages in western Washington State, including one gage on the Sauk River; two gages on the Suiattle River, a tributary to the Sauk River; and one gage on Downey Creek, a tributary to the Suiattle River. The Suiattle River is a sediment-rich stream with headwaters on Glacier Peak, a glaciated volcano in the northern Cascade Range.
Contributions of suspended sediment to the Suiattle River from unglaciated tributaries, represented by Downey Creek, were compared to the contributions from Glacier Peak in the upper Suiattle River watershed. During summer 2017, a period for which complete records of discharge and sediment data were available for all three streamgages in the Suiattle River Basin, the suspended-sediment load from Downey Creek (drainage area [DA] 93 square kilometers [km2]) was 1,400 metric tons, which is equivalent to a sediment yield of about 15 metric tons per km2. During the same period, the suspended-sediment load from the upper Suiattle River (DA 176 km2) was 142,000 metric tons, or a sediment yield of about 800 metric tons per km2; and the suspended-sediment load from the lower Suiattle River (DA 733 km2) was 230,000 metric tons, or a sediment yield of about 300 metric tons per km2. The Downey Creek Basin accounts for 13 percent of the drainage area of the Suiattle River watershed but contributed only 0.6 percent of the suspended-sediment load over the summer of 2017 and water year 2017 (October 1, 2016–September 30, 2017). In contrast, the upper Suiattle River Basin, which accounts for 24 percent of the entire Suiattle River watershed, contributed 62 percent of the suspended-sediment load during the summer of 2017.
Given the short period for which data were collected, it cannot be known with certainty whether the above values are representative of long-term means. The relatively minor contribution of suspended sediment from Downey Creek, however, is consistent with the expectation that the upper Suiattle River, which drains Glacier Peak, is the dominant contemporary source of suspended sediment to the Sauk River. During summer 2016, the suspended-sediment load in the upper Siuattle River (180,000 metric tons) was more than double the estimated load in the lower Sauk River (80,000 metric tons), even though the upper Suiattle River represents only 10 percent of the total contributing area to the lower Sauk River Basin. This ratio of relative contribution is interpreted as an indication of transient storage of sediment along the Suiattle and Sauk Rivers between the two streamgaging stations. In the glaciated upper Suiattle River Basin, sediment is transported by annual glacial-melt processes in spring and summer months, deposited during the summer base-flow period, and then remobilized by fall and winter floods for delivery to the lower Sauk River.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221056","collaboration":"Prepared in cooperation with the Sauk-Suiattle Indian Tribe","usgsCitation":"Jaeger, K.L., Anderson, S.W., Senter, C.A., Curran, C.A., and Morris, S., 2022, Relative contributions of suspended sediment between the upper Suiattle River Basin and a non-glacial tributary, Washington, May 2016–September 2017: U.S. Geological Survey Open-File Report 2022–1056, 18 p., https://doi.org/10.3133/ofr20221056.","productDescription":"v, 18 p.","onlineOnly":"Y","ipdsId":"IP-132545","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":403971,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1056/ofr20221056.pdf","text":"Report","size":"8.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1056"},{"id":403970,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1056/coverthb.jpg"},{"id":501781,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113307.htm","linkFileType":{"id":5,"text":"html"}},{"id":403972,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/ofr20221056/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1056"},{"id":404178,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9W74K0K","text":"USGS data release","description":"USGS data release","linkHelpText":"Suspended sediment and water temperature data in the Suiattle River and the Downey Creek Tributary, Washington for select time periods over 2013 - 2017 (ver. 2.0, October 2021)"},{"id":403974,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1056/ofr20221056.XML"},{"id":403973,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1056/images"}],"country":"United States","state":"Washington","otherGeospatial":"Upper Suiattle River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.4,\n 48.0\n ],\n [\n -121.0,\n 48.0\n ],\n [\n -121.0,\n 48.4\n ],\n [\n -121.4,\n 48.4\n ],\n [\n -121.4,\n 48.0\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Washington Water Science Center
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Tacoma, Washington 98402
The Old Erie Canal has undergone sedimentation and aquatic growth that have restricted flow and diminished the aesthetic quality of the canal during the nearly 200 years since its construction. During 2018–2019, the U.S. Geological Survey (USGS) in cooperation with the Madison County Planning Department and the New York State Canal Corporation conducted a study of the Old Erie Canal between the Town of DeWitt, New York, and its junction with the current Erie Canal of the New York State Canal System near Rome, N.Y. The study comprised bathymetric, velocity, and water-quality surveys and documentation of the canal infrastructure. The USGS established benchmarks and staff gages along the 30.8 miles of the canal study area to reference the water-surface level in the canal to the North American Vertical Datum of 1988 (NAVD 88). Bathymetric survey results indicated that during the time of the survey, the canal depths ranged from 1.26 feet (ft) to 7.33 ft between the Butternut and Durhamville aqueducts (with a mean depth of 3.52 ft). Shallow depths are located throughout the canal, but the section north of the Durhamville aqueduct was the shallowest, with depths ranging from 0.68 ft to 2.44 ft (and a mean depth of 1.36 ft). The reach-averaged water velocity was 0.28 feet per second. The system generally flows west to east from the Butternut aqueduct to the entrance to the Erie Canal.
Water-quality data (dissolved oxygen, water temperature, specific conductance, pH, and turbidity) were collected concurrently with the bathymetric survey (spring 2018) to characterize changes in water quality along the length of the canal. Specific-conductance values measured upstream from the hamlet of Kirkville, Manlius, N.Y. may reflect road salts being flushed into the canal through the Butternut and Limestone feeder system (designed to divert water from nearby creeks to supply water for the Old Erie Canal) from recent stormwater runoff. Increases in pH in the downstream direction are possibly caused by increasing amounts of aquatic vegetation. During the time of the survey, turbidity was highest near inflows from the canal feeder system and tributary inputs which were elevated by stormwater runoff that transported sediment into the canal.
The canal infrastructure was documented to provide a baseline assessment. The feeder system, designed to bring water into the canal, does not deliver flow when the creeks supplying water to those feeders are at base flow, but does bring water into the system when flows in the feeder creeks are elevated. A recent report provides an example of repair work completed on the Chittenango feeder to improve flow through the feeder into the canal (Welch and Madison County Planning Department, 1996). Two non-regulated tributaries, Meadow Brook and Pools Brook, consistently delivered flow to the canal. Outfalls where canal water discharges into nearby creeks were sealed in the Butternut and Limestone aqueducts. Outfalls in the Chittenango, Cowaselon, and Durhamville aqueducts were found with flashboards installed at an elevation that allows water to be discharged from the canal. These structures are designed to accept additional flashboards to raise the canal water surface with the potential to convey flow farther down the system. The general condition of the channel was open and navigable between Butternut aqueduct and Chittenago aqueduct. On the segment of the canal east of the Chittenango aqueduct, an increasing number of downed trees and tangled wads of vegetation affected flow and made navigation by boat difficult to the Durhamville aqueduct. North of the Durhamville aqueduct, numerous downed trees and an increased density of aquatic vegetation limited navigation by boat and reduced the flow rate.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211125","usgsCitation":"Wernly, J.F., 2022, Characterization of the bathymetry, hydrodynamics, water quality, infrastructure, and channel condition of the Old Erie Canal from DeWitt to its junction with the current Erie Canal in Verona, near Rome, New York, 2018–19: U.S. Geological Survey Open-File Report 2021–1125, 75 p., https://doi.org/10.3133/ofr20211125.","productDescription":"Report: viii, 75 p.; Data Release","numberOfPages":"75","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-118164","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":402850,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1125/ofr20211125.XML"},{"id":402848,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1125/ofr20211125.pdf","text":"Report","size":"94.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1125"},{"id":402847,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1125/coverthb.jpg"},{"id":402849,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9QRL294","text":"USGS data release","linkHelpText":"Geospatial dataset of the characterization of the bathymetry, hydrodynamics, water quality, infrastructure, and channel condition of the Old Erie Canal from DeWitt to Rome, New York 2018–2019"},{"id":402851,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1125/images/"},{"id":403542,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/ofr20211125/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2021-1125"},{"id":501536,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113265.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"New York","otherGeospatial":"Old Erie Canal","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.13250732421875,\n 42.974511174899156\n ],\n [\n -76.11328125,\n 42.968984647488014\n ],\n [\n -75.9375,\n 42.96044267380142\n ],\n [\n -75.74798583984375,\n 42.96446257387128\n ],\n [\n -75.57769775390625,\n 43.002638523957906\n ],\n [\n -75.41839599609375,\n 43.1270477646888\n ],\n [\n -75.35522460937499,\n 43.207177786666655\n ],\n [\n -75.42388916015625,\n 43.271206115959785\n ],\n [\n -75.52001953125,\n 43.25920592943639\n ],\n [\n -75.65460205078125,\n 43.23920036180898\n ],\n [\n -75.92926025390625,\n 43.219188223481325\n ],\n [\n -76.09405517578125,\n 43.13105676219153\n ],\n [\n -76.18194580078124,\n 43.07891929985966\n ],\n [\n -76.18743896484375,\n 43.022721607058344\n ],\n [\n -76.13250732421875,\n 42.974511174899156\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 12180–8349
Anthropogenic activities, including groundwater withdrawals, return flow from irrigated agriculture, and treated wastewater-effluent disposal have the potential to affect groundwater quality in the Lucerne Valley groundwater basin, located in the southwest Mojave Desert. Questions regarding the current state and potential future of groundwater quality in this basin were addressed by (1) considering groundwater data from and findings of historical water-quality studies, (2) evaluating recent (1990–2021) U.S. Geological Survey water-quality and geochemical-tracer data, and (3) assessing groundwater-quality results from samples collected in 2021 to better understand the transport of applied treated wastewater effluent in the subsurface and associated effects of this practice on water quality. As observed by previous studies, differences in groundwater quality existed among the upper, middle, and lower aquifers of the Lucerne Valley groundwater basin, with the lower aquifer characterized by high dissolved-solid content relative to the middle and upper aquifers. Stable and radioisotope tracers indicate that most of the groundwater sampled in the basin was recharged during cooler, wetter climate conditions than those of the present day (2022). Analyses of the 2021 samples collected to examine the subsurface transport of applied treated wastewater effluent were not conclusive but indicate that water from applied treated wastewater effluent is currently (2022) limited to the upper aquifer and likely to remain so given the extensive confining unit below the upper aquifer.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221063","collaboration":"Prepared in cooperation with the Mojave Water Agency","usgsCitation":"Fackrell, J.K., 2022, Groundwater quality of the Lucerne Valley groundwater basin, California: U.S. Geological Survey Open-File Report 2022-1063, 19 p., https://doi.org/10.3133/ofr20221063.","productDescription":"viii, 19 p.","numberOfPages":"19","onlineOnly":"Y","ipdsId":"IP-137528","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":501818,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113259.htm","linkFileType":{"id":5,"text":"html"}},{"id":403158,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1063/ofr20221063.pdf","text":"Report","size":"3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Open-File Report 2022–1063"},{"id":403163,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20225048","text":"Scientific Investigations Report 2022-5048","description":"Stamos, C.L., Larsen, J.D., Powell, R.E., Matti, J.C., and Martin, P., 2022, Hydrogeology and simulation of groundwater flow in the Lucerne Valley groundwater basin, California: U.S. Geological Survey Scientific Investigations Report 2022-5048, 120 p., https://doi.org/10.3133/sir20225048.","linkHelpText":"- Hydrogeology and Simulation of Groundwater Flow in the Lucerne Valley Groundwater Basin, California"},{"id":403159,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1063/ofr20221063.xml"},{"id":403160,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1063/images"},{"id":403157,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1063/covrthb.jpg"},{"id":403185,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221063/full","text":"Report","description":"Open-File Report 2022-1063"}],"country":"United States","state":"California","otherGeospatial":"Lucerne Valley Groundwater Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.666667,\n 34.266667\n ],\n [\n -117.083333,\n 34.266667\n ],\n [\n -117.083333,\n 34.666667\n ],\n [\n -116.666667,\n 34.666667\n ],\n [\n -116.666667,\n 34.266667\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
There have been over 507 million cases of COVID-19, the disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), resulting in 6 million deaths globally. Wastewater surveillance has emerged as a valuable tool in understanding SARS-CoV-2 burden in communities. The National Wastewater Surveillance System (NWSS) partnered with the United States Geological Survey (USGS) to implement a high-frequency sampling program. This report describes basic surveillance and sampling statistics as well as a comparison of SARS-CoV-2 trends between high-frequency sampling 3–5 times per week, referred to as USGS samples, and routine sampling 1–2 times per week, referred to as NWSS samples. USGS samples provided a more nuanced impression of the changes in wastewater trends, which could be important in emergency response situations. Despite the rapid implementation time frame, USGS samples had similar data quality and testing turnaround times as NWSS samples. Ensuring there is a reliable sample collection and testing plan before an emergency arises will aid in the rapid implementation of a high-frequency sampling approach. High-frequency sampling requires a constant flow of information and supplies throughout sample collection, testing, analysis, and data sharing. High-frequency sampling may be a useful approach for increased resolution of disease trends in emergency response.
The Lucerne Valley is in the southwestern part of the Mojave Desert and is about 75 miles northeast of Los Angeles, California. The Lucerne Valley groundwater basin encompasses about 230 square miles and is separated from the Upper Mojave Valley groundwater basin by splays of the Helendale Fault. Since its settlement, groundwater has been the primary source of water for agricultural, industrial, municipal, and domestic uses. Groundwater withdrawal from pumping has exceeded the amount of water recharged to the basin, causing groundwater declines of more than 100 feet between 1917 and 2016 in the center of the basin. The continued withdrawal has resulted in an increase in pumping costs, reduced well efficiency, and land subsidence near Lucerne Lake. Although the volume of pumping has declined in recent years, there is concern that new agricultural growth and limits on imported water will continue to strain the sustainability of the groundwater system.
To address these concerns, the U.S. Geological Survey entered into a cooperative agreement with the Mojave Water Agency to develop a better understanding of the Lucerne Valley hydrogeologic system and provide tools to help evaluate and manage the effects of future development in the Lucerne Valley. The objectives of this study were to (1) improve the understanding of the aquifer system, (2) improve the understanding of subsidence in the basin, and (3) incorporate the understanding into a groundwater-flow model that can be used to help manage the groundwater resources in the Lucerne Valley. The model developed for this study covers the period of 1942–2016 and can help evaluate various proposed water-management scenarios during different climatic and hydrologic conditions.
The aquifer system consists of a shallow aquifer, a confining unit, and middle and lower aquifers. These layered water-bearing units were identified based on geologic units of the mostly unconsolidated sediments and hydrologic properties. These alluvial deposits consist of clay, silt, sand, and gravel; some places also contain clay and silty clay lacustrine deposits. Several faults act, at least in part, as barriers to groundwater flow on the eastern, southern, and western edges of the basin. Present-day natural recharge is primarily from the infiltration of runoff from the San Bernardino Mountains to the south; however, stable and radioactive isotopes show that groundwater from the middle of the Lucerne Valley was older than about 10,000 years and probably was recharged as infiltration from streams draining the mountains in the Mojave Desert to the north, which probably does not occur under present-day climatic conditions. The annual average natural recharge for 1942–2016, estimated by a Basin Characterization Model, was about 635 acre-feet per year; the average amount of treated wastewater effluent transferred to the Lucerne Valley for artificial recharge annually ranged from about 1,500 to 4,000 acre-feet per year during 1980–2016. Pumpage estimates for 1942–2016 ranged from about 3,000 acre-feet in 1942 to about 18,300 acre-feet in 1984. The total cumulative amount of groundwater removed from the basin by pumping between 1942 and 2016 was estimated to be about 700,000 acre-feet, which was about 10 times greater than the cumulative amount of recharge to the entire Lucerne Valley groundwater basin. Before groundwater development, the direction of groundwater flow was from the southern part of the basin northward to discharge areas near Lucerne Lake, where it discharged through springs along the Helendale Fault and by evapotranspiration. Since the early 1900s, groundwater-level declines have mostly eliminated the areas where natural discharge occurred and exceeded 100 feet in the middle of the basin between the early 1950s and mid-1990s, and as much as 25 feet near the margins from about the mid-1950s to 2000s. A decrease in the rate of pumping after the mid-1990s lessened the hydraulic stress on the middle and lower aquifers and enabled hydraulic heads in the middle of the basin to recover slightly as groundwater near the margins of the basin moved toward the pumping depression. Although trends in groundwater levels in the center of the basin have reversed since the mid-1990s, levels at the basin margins continue to decline as the movement of groundwater from the margins fills the pumping depression and gradually flattens the groundwater table throughout the basin.
The long-term extraction of groundwater and associated dewatering of the fine-grained sediments present within the aquifer system has resulted in aquifer compaction and consequently land subsidence, primarily near Lucerne Lake. Analysis of interferometric synthetic aperture radar data shows that almost 11 inches of land subsidence has occurred south of Lucerne Lake between April 1992 and November 2009; less subsidence occurred elsewhere in the basin during this period. This differential land subsidence has caused fissures and cracks in the ground surface, which have buckled the pavement and undercut roads in several locations.
The Lucerne Valley Hydrologic Model was developed using the finite-difference groundwater modeling software One Water Hydrologic Model to represent the hydrologic conditions and stresses during 1942–2016. The model has a uniform grid of approximately 92 acres per cell (2,000 feet by 2,000 feet) and has four layers representing the water-bearing units. The results from the calibrated model simulations indicated that groundwater pumpage exceeded recharge, resulting in an estimated net cumulative depletion of groundwater storage (discharge minus recharge) of about 465,000 acre-feet from 1942 to 2016. The model simulated as much as 7.5 feet (90 inches; 2,286 millimeters) of aquifer compaction, which indicates the extensive fine-grained deposits and measured subsidence near Lucerne Lake.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225048","collaboration":"Prepared in cooperation with the Mojave Water Agency","usgsCitation":"Stamos, C.L., Larsen, J.D., Powell, R.E., Matti, J.C., and Martin, P., 2022, Hydrogeology and simulation of groundwater flow in the Lucerne Valley groundwater basin, California: U.S. Geological Survey Scientific Investigations Report 2022-5048, 120 p., https://doi.org/10.3133/sir20225048.","productDescription":"Report: xi, 120 p.; Appendix; Data Release","numberOfPages":"120","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-095487","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":403187,"rank":8,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20221063","text":"Open-File Report 2022-1063","description":"Fackrell, J.K., 2022, Groundwater quality of the Lucerne Valley groundwater basin, California: U.S. Geological Survey Open-File Report 2022-1063, 19 p., https://doi.org/10.3133/ofr20221063.","linkHelpText":"- Groundwater Quality of the Lucerne Valley Groundwater Basin, California"},{"id":402644,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P94W41EL","text":"MODFLOW-OWHM model used to simulate groundwater flow and evaluate storage in the Lucerne Valley Groundwater Basin, California","description":"Larsen, J.D., 2022, MODFLOW-OWHM model used to simulate groundwater flow and evaluate storage in the Lucerne Valley Groundwater Basin, California: U.S. Geological Survey data release, https://doi.org/10.5066/P94W41EL."},{"id":402643,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2022/5048/sir20225048_appendix1.txt","text":"Appendix 1","size":"27 KB","linkFileType":{"id":2,"text":"txt"},"linkHelpText":"- Sites with groundwater-level data available on the U. S. Geological Survey National Water Inventory System Web service (NWISWeb) from 1911-2016 within the Lucerne Valley, California"},{"id":402641,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5048/sir20225048.xml"},{"id":402640,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5048/sir20225048.pdf","text":"Report","size":"20 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5048"},{"id":402639,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5048/covrthb.jpg"},{"id":402695,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20225048/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2022-5048"},{"id":402642,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5048/images"}],"country":"United States","state":"California","otherGeospatial":"Lucerne Valley Groundwater Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.666667,\n 34.266667\n ],\n [\n -117.083333,\n 34.266667\n ],\n [\n -117.083333,\n 34.666667\n ],\n [\n -116.666667,\n 34.666667\n ],\n [\n -116.666667,\n 34.266667\n ]\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 hydrogeology on and near Cannon Air Force Base (AFB) in eastern New Mexico was assessed to gain a better understanding of preferential groundwater flow paths through paleochannels. In and near the study area, paleochannels incised the top surface of the Dockum Group (Chinle Formation) and were subsequently filled in with electrically resistive coarse-grained sediments of the overlying Ogallala Formation, resulting in a preferential groundwater flow path in the form of a paleochannel network. A better understanding of the spatial characteristics of this preferential groundwater flow path is needed to support ongoing efforts to remediate groundwater contamination at Cannon AFB. Therefore, the U.S. Geological Survey, in cooperation with the U.S. Air Force Civil Engineer Center, used surface geophysical resistivity methods and data compiled from previous studies to better understand the spatial distribution and characteristics of the paleochannel network incised into the top of the Dockum Group.
Previous studies have shown these paleochannels incised into the top of the Dockum Group with increasing resolution, but limited borehole data on and near Cannon AFB continued to make accurately mapping the top of Dockum Group challenging. For this study, surface geophysical resistivity measurements in the form of time-domain electromagnetic soundings made by the U.S. Geological Survey were used in conjunction with data previously published by Architecture, Engineering, Construction, Operations, and Management and borehole data compiled from the New Mexico Water Rights Reporting System database to prepare an updated map of the top of the Dockum Group that includes the location and characteristics of paleochannels incised into the top of the Dockum Group (Chinle Formation). A total of 149 borehole picks (determinations of the tops and bases of geologic units and their hydrogeologic-unit equivalents) were obtained from previous studies, along with 72 additional borehole picks from the New Mexico Water Rights Reporting System database and 43 picks from newly collected time-domain electromagnetic soundings. The data were gridded and contoured using Oasis Montaj v. 9.8.1.
The updated map of the top of Dockum Group has many areas of uncertainty greater than 20 feet, because there are not enough data for the gridding process to reliably determine a value. However, this interpretation of the altitude of the top of the Dockum Group represents a substantial improvement in data resolution compared to previous studies.
Two methodologies were used to evaluate paleochannels incised in the top of the Dockum Group across the study area: (1) trend-removal grid analysis and (2) analysis with Esri’s ArcMap Hydrology toolset. These two paleochannel analysis techniques show groundwater flow direction as well as areas having the deepest saturated thickness. Hydrologically, these techniques show where aquifer storage is highest (in the deepest parts of the paleochannel network), as well as the spatial distribution of preferential groundwater flow paths (the paleochannels). The analyses indicate a large paleochannel trending to the southeast, with smaller channels feeding in from the west. Areas where groundwater management could be more beneficial are indicated by locations where these flow lines intersect the deeper parts of the paleochannel.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225050","collaboration":"Prepared in cooperation with the Air Force Civil Engineer Center","usgsCitation":"Payne, J.D., Teeple, A.P., McDowell, J., Wallace, D., and Hancock, W.A., 2022, Mapping the altitude of the top of the Dockum Group and paleochannel analysis using surface geophysical methods on and near Cannon Air Force Base in Curry County, New Mexico, 2020: U.S. Geological Survey Scientific Investigations Report 2022–5050, 21 p., https://doi.org/10.3133/sir20225050.","productDescription":"Report: iv, 21 p.; 2 Data Releases; Dataset","numberOfPages":"30","onlineOnly":"Y","ipdsId":"IP-125577","costCenters":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":402462,"rank":8,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20225050/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":402441,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5050/images"},{"id":402444,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://www.sciencebase.gov/catalog/item/543e6b86e4b0fd76af69cf4c","text":"USGS data release","linkHelpText":"1 meter digital elevation models (DEMs)—USGS National Map 3DEP downloadable data collection"},{"id":402443,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9P6KWR5","text":"USGS data release","linkHelpText":"Surface geophysical data used for mapping the top of the Dockum Group on Cannon Air Force Base in Curry County, New Mexico, 2020"},{"id":402442,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://nmwrrs.ose.state.nm.us/nmwrrs/wellSurfaceDiversion.html","text":"New Mexico Office of the State Engineer online database","linkHelpText":"—New Mexico Water Rights Reporting System"},{"id":402438,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5050/coverthb.jpg"},{"id":402439,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5050/sir20225050.pdf","text":"Report","size":"1.44 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022–5050"},{"id":402440,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5050/sir20225050.XML"}],"country":"United States","state":"New Mexico","county":"Curry County","otherGeospatial":"Cannon Air Force Base","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -103.375,\n 34.333\n ],\n [\n -103.25,\n 34.333\n ],\n [\n -103.25,\n 34.458333\n ],\n [\n -103.375,\n 34.458333\n ],\n [\n -103.375,\n 34.333\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oklahoma-Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, TX 78754-4501
The U.S. Geological Survey, in cooperation with the Montana Department of Transportation, installed cameras and large-scale particle image velocimetry (LSPIV) recording equipment at four sites where the U.S. Geological Survey and Montana Department of Transportation are monitoring bridge scour using other methods. Determination of stream velocities is an important component of hydraulic engineering, river ecology, and fluvial geomorphology. LSPIV is an emerging technique that can be used to estimate stream surface velocities and streamflow using video cameras. Video from the camera is referenced to known locations on streambanks, and postprocessed using computer software that calculates water surface velocity and flow direction between video frames.
The goal of the study was to determine if LSPIV can increase the accuracy of current bridge scour prediction methods using video recordings from 2019 to 2021. Scour around piers is one of the primary failure mechanisms for bridges and poses threats to public safety and interstate commerce. LSPIV installations can capture the flow velocities and directions near bridge piers where other measurement methods might fail or be too dangerous. Additional benefits to the LSPIV technique were continuous data collection throughout the hydrologic cycle and enhanced safety of the methods for estimating velocity magnitude and direction during flood events. Limitations of the LSPIV technique included the angle of the camera to incoming flow; video recordings that were not usable because of ice cover, night, or high winds; and vegetation along the streambank that interfered with water flow analysis. Future applications of the LSPIV technique may continue to improve the processing of the video and reduce limitations for this process.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20223040","usgsCitation":"Armstrong, D.W., Holnbeck, S.R., and Chase, K.J., 2022, Evaluating the use of video cameras to estimate bridge scour potential at four bridges in southwestern Montana: U.S. Geological Survey Fact Sheet 2022–3040, 2 p., https://doi.org/10.3133/fs20223040.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","ipdsId":"IP-137820","costCenters":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"links":[{"id":402153,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2022/3040/coverthb.jpg"},{"id":402154,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2022/3040/fs20223040.pdf","text":"Report","size":"1.83 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2022-3040"},{"id":402155,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2022/3040/fs20223040.XML"},{"id":402156,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2022/3040/images"},{"id":402157,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/fs20223040/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":501493,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113199.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Montana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.5,\n 45\n ],\n [\n -110.5,\n 45\n ],\n [\n -110.5,\n 46\n ],\n [\n -112.5,\n 46\n ],\n [\n -112.5,\n 45\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Wyoming-Montana Water Science Center
U.S. Geological Survey
3162 Bozeman Avenue
Helena, MT 59601
Ratings are used for a variety of reasons in water-resources investigations. The simplest rating relates discharge to the stage of the river. From a pure hydrodynamics perspective, all rivers and streams have some form of hysteresis in the relation between stage and discharge because of unsteady flow as a flood wave passes. Simple ratings are unable to represent hysteresis in a stage/discharge relation. A dynamic rating method is capable of capturing hysteresis owing to the variable energy slope caused by unsteady momentum and pressure.
A dynamic rating method developed to compute discharge from stage for compact channel geometry, referred to as DYNMOD, previously has been developed through a simplification of the one-dimensional Saint-Venant equations. A dynamic rating method, which accommodates compound and compact channel geometry, referred to as DYNPOUND, has been developed through a similar simplification as a part of this study. The DYNMOD and DYNPOUND methods were implemented in the Python programming language. Discharge time series computed with the dynamic rating method implementations were then compared to simulated discharge time series and discrete discharge measurements made at U.S. Geological Survey streamgage sites.
Four sets of stage and discharge time series were created using one-dimensional unsteady simulation software with compound channel geometry to compare the results of both dynamic rating methods to results from the full one-dimensional shallow water equations. Discharge time series were computed from stage time series using DYNMOD and DYNPOUND. DYNPOUND outperformed DYNMOD in all four scenarios. The minimum and maximum mean squared logarithmic error (MSLE) for the DYNMOD results were 2.75×10−2 and 3.40×10−2, respectively. The minimum and maximum MSLE for the DYNPOUND results were 2.51×10−7 and 1.91×10−4, respectively.
The dynamic rating methods were calibrated for six U.S. Geological Survey streamgage sites using observed discharge data collected at the sites. The calibration objective for each site was to minimize the MSLE of the discharge computed with the rating method with respect to observed discharge. For each site, the calibration included all field measurements within a selected water year. The DYNMOD method failed to compute discharge for the full calibration time series for three sites. A method fails to compute when the implementation returns a nonfinite value at a time step. Because the values computed for following time steps are dependent on the previous time step, a nonfinite value results in nonfinite values that follow. For the three sites for which DYNMOD computed the complete discharge time series, the minimum MSLE for calibration was 2.19×10−3 and the maximum was 9.77×10−3. The MSLE of the DYNPOUND computed discharge calibration time series for the six sites ranged from 3.70×10−3 to 1.25. For each site, an event-based time period was selected to compare the discharge time series computed with the dynamic rating methods to discrete discharge field measurements made at the streamgage sites. The DYNMOD-computed discharge time series for the three sites had an MSLE range of 2.76×10−3 to 3.14×10−2. The range of MSLE for the six DYNPOUND sites was 3.64×10−3 to 7.23×10−2. Although the DYNMOD method outperforms the DYNPOUND method when calibrated streamgage sites are under consideration, the DYNMOD method failed to compute a discharge time series at three of the six sites. The DYNPOUND method, therefore, was more robust than the DYNMOD method. Improvements to the implementation of the DYNPOUND method may improve the accuracy of the method.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221031","programNote":"Groundwater and Streamflow Information Program","usgsCitation":"Domanski, M., Holmes, R.R., Jr., and Heal, E.N., 2022, Dynamic rating method for computing discharge from time-series stage data: U.S. Geological Survey Open-File Report 2022–1031, 48 p., https://doi.org/10.3133/ofr20221031.","productDescription":"Report: vii, 48 p.; 2 Data Releases; Dataset","numberOfPages":"60","onlineOnly":"Y","ipdsId":"IP-128037","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":501770,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113161.htm","linkFileType":{"id":5,"text":"html"}},{"id":400457,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":400459,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9YUV9DG","text":"USGS data release","linkHelpText":"Dynamic stage to discharge rating model archive"},{"id":400458,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P955QRPQ","text":"USGS data release","linkHelpText":"Dynamic rating method for computing discharge from time series stage data—Site datasets"},{"id":400454,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1031/ofr20221031.XML"},{"id":400455,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1031/images"},{"id":400453,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1031/ofr20221031.pdf","text":"Report","size":"2.85 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1031"},{"id":400452,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1031/coverthb.jpg"}],"contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
405 North Goodwin
Urbana, IL 61801
The Willamette River, Oregon, is home to two salmonid species listed as threatened under the Endangered Species Act, Upper WIllamette River spring Chinook salmon (Oncorhynchus tshawytscha) and Upper Willamette River winter steelhead (O. mykiss). Streamflow in the Willamette River is regulated by upstream dams, 13 of which are operated by the U.S. Army Corps of Engineers (USACE) as part of the Willamette Valley Project. In 2008, these dams were determined to have a deleterious effect on Endangered Species Act-listed salmonids, resulting in USACE taking actions to mitigate those effects. Mitigation actions included setting seasonal streamflow targets at various locations along the river to improve survival and migration of juvenile salmonids. Although these targets were established with the best available information at the time, recent data and models have advanced understanding of Willamette River bathymetric, hydraulic, and thermal conditions, allowing for a more robust analysis of the effect of streamflow on downstream habitat. This study integrates those recent advances to build high-resolution models of usable habitat for juvenile Chinook salmon and steelhead to assess variation in spatial and seasonal patterns of habitat availability. Specifically, this study develops detailed maps of habitat availability for juvenile Chinook salmon and steelhead for two size classes (fry and pre-smolt). Habitat availability is modeled in a three-step process whereby (1) two-dimensional hydraulic models are paired with literature-supplied data on habitat preferences to create spatially explicit maps of rearing habitats for a wide range of streamflows; (2) reach-specific relations between streamflow and habitat area are developed and paired with streamgage records to create habitat time series for 2011, 2015, and 2016, which reflect “cool and wet,” “hot and dry,” and “warm but average precipitation” conditions, respectively; (3) temperature models are coupled with literature-based thermal thresholds to determine time periods and locations along the river corridor when rearing habitat has optimal, harmful, or lethal temperature conditions; (4) finally, habitat availability is summarized at several spatial scales to characterize longitudinal and seasonal patterns.
Findings show that modeled area of rearing habitat for Chinook salmon and steelhead responds non-uniformly to streamflow, where habitat in some reaches of the Willamette River consistently increase with additional streamflow, while in other reaches, habitat area decreases when streamflows increase from low to moderate flows. Modeled differences in flow-habitat relations are primarily explained by local geomorphology in each reach and resulting hydraulic conditions that arise with different streamflows. These are most pronounced when comparing laterally active, multi-channel reaches upstream from Corvallis with downstream reaches that are laterally stable with single-channel planforms. The reaches upstream from Corvallis generally have more habitat available per unit stream distance than downstream reaches, but all reaches display greatest amounts of habitat at the highest streamflows. Finally, results show that warm water temperature in summer greatly decreases the utility of habitat available to the focal species, particularly downstream from Corvallis. Together, these findings serve to inform flow management by characterizing spatial and seasonal patterns of habitat availability for juvenile spring Chinook salmon and winter steelhead and provide a quantitative assessment of the effects of streamflow on rearing habitat.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225034","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"White, J.S., Peterson, J.T., Stratton Garvin, L.E., Kock, T.J., and Wallick, J.R., 2022, Assessment of habitat availability for juvenile Chinook salmon (Oncorhynchus tshawytscha) and steelhead (O. mykiss) in the Willamette River, Oregon: U.S. Geological Survey Scientific Investigations Report 2022–5034, 44 p., https://doi.org/10.3133/sir20225034.","productDescription":"viii, 44 p.","onlineOnly":"Y","ipdsId":"IP-130018","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":401758,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5034/coverthb.jpg"},{"id":401759,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5034/sir20225034.pdf","text":"Report","size":"13.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5034"}],"country":"United States","state":"Oregon","otherGeospatial":"Willamette River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.40942382812501,\n 44.05995928349327\n ],\n [\n -122.2943115234375,\n 44.05995928349327\n ],\n [\n -122.2943115234375,\n 45.66780526567164\n ],\n [\n -123.40942382812501,\n 45.66780526567164\n ],\n [\n -123.40942382812501,\n 44.05995928349327\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201
Mechanistic river models capable of simulating hydrodynamics and stream temperature are valuable tools for investigating thermal conditions and their relation to streamflow in river basins where upstream water storage and management decisions have an important influence on river reaches with threatened fish populations. In the Willamette River Basin in northwestern Oregon, a two-dimensional, hydrodynamic water-quality model (CE‑QUAL‑W2) has been used to investigate the downstream effects of dam operations and other anthropogenic influences on stream temperature. By simulating the managed releases of water and various temperatures from the large Willamette Valley Project dams upstream of the modeling domain, these models can be used to investigate riverine temperature conditions and their relation to streamflow to determine where and when conditions are most challenging for threatened fish populations and how dam operations and flow management can affect and optimize thermal conditions in the river.
The original models were initially developed to simulate conditions in spring–autumn of 2001 and 2002. This report documents (1) the upgrade of the river models to CE‑QUAL‑W2 version 4.2 and (2) the update of those models to simulate conditions that occurred from March through October of 2011, 2015, and 2016. These years were selected to represent a range of climatic and hydrologic conditions in the Willamette River Basin, including a “cool, wet” year (2011), a “hot, dry” year (2015), and a “normal” year (2016). Six submodels comprise the modeling system updated in this report; each submodel can be run independently or run with the others as a system. These models include the Coast Fork and Middle Fork Willamette River submodel, which includes the Coast Fork and Middle Fork Willamette Rivers, the Row River, and Fall Creek; the McKenzie River submodel, which includes the South Fork McKenzie River downstream of Cougar Dam and the McKenzie River from its confluence with the South Fork McKenzie River to its mouth; the South Santiam River submodel, which comprises the South Santiam River from Foster Dam to the Santiam River; the North Santiam and Santiam River submodel, which includes the Santiam River and the North Santiam River downstream of Big Cliff Dam; the Upper Willamette River submodel, which includes the Willamette River from Eugene to Salem; and the Middle Willamette River submodel, which includes the Willamette River from Salem to Willamette Falls near Oregon City.
The models included in this report were originally developed, calibrated, and documented by other researchers. As part of the model updates described here, some model parameters were adjusted to improve stability and decrease runtime. Boundary conditions including meteorological, hydrologic, and thermal parameters were developed and updated for model years 2011, 2015, and 2016. In many cases, the data sources used to drive the 2001 and 2002 models were no longer available, which required the use of new data sources, the determination of a proxy record, or the development of appropriate estimation techniques. Goodness-of-fit statistics for the updated models show a good model fit, with the models simulating subdaily water temperatures at most comparable locations with a mean absolute error of generally less than 1 °C and often nearing 0.5 °C, depending on the individual submodel, and a reasonably low bias. The subdaily mean error for the South Santiam River submodel produced the highest bias of any of the submodels. Goodness-of-fit statistics indicate that the results may be biased cool (ranging from -0.43 °C in 2016 to -0.80 °C in 2011 for subdaily results), but the only water temperature data available for comparison on the South Santiam River is itself estimated, and those estimates are known to be too high in summer. Depending on future modeling needs, that submodel may warrant further refinement, along with additional data collection to properly define and minimize any model bias.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221017","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers, Portland District","usgsCitation":"Stratton Garvin, L.E., Rounds, S.A., and Buccola, N.L., 2022, Updates to models of streamflow and water temperature for 2011, 2015, and 2016 in rivers of the Willamette River Basin, Oregon: U.S. Geological Survey Open-File Report 2022–1017, 73 p., https://doi.org/10.3133/ofr20221017.","productDescription":"Report: x, 73 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-119723","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":401872,"rank":8,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1017/ofr20221017.XML"},{"id":401871,"rank":7,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1017/images"},{"id":401815,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20225035","text":"SIR 2022-5035 —","linkHelpText":"The thermal landscape of the Willamette River—Patterns and controls on stream temperature and implications for flow management and cold-water salmonids"},{"id":401814,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20225034","text":"SIR 2022-5034 —","linkHelpText":"Assessment of habitat availability for juvenile Chinook salmon (Oncorhynchus tshawytscha) and steelhead (O. mykiss) in the Willamette River, Oregon"},{"id":501762,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113157.htm","linkFileType":{"id":5,"text":"html"}},{"id":401754,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1017/coverthb.jpg"},{"id":401755,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1017/ofr20221017.pdf","text":"Report","size":"10.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1017"},{"id":401756,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P908DXKH","text":"USGS data release","description":"USGS data release","linkHelpText":"CE-QUAL-W2 models for the Willamette River and major tributaries below U.S. Army Corps of Engineers dams—2011, 2015, and 2016"},{"id":401813,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20225006","text":"SIR 2022-5006 —","linkHelpText":"Tracking heat in the Willamette River system, Oregon"}],"country":"United States","state":"Oregon","otherGeospatial":"Willamette River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.134765625,\n 42.779275360241904\n ],\n [\n -120.673828125,\n 42.779275360241904\n ],\n [\n -120.673828125,\n 45.9511496866914\n ],\n [\n -123.134765625,\n 45.9511496866914\n ],\n [\n -123.134765625,\n 42.779275360241904\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201
Groundwater levels have declined since the 1940s in the Wailuku area of central Maui, Hawai‘i, on the eastern flank of West Maui volcano, mainly in response to increased groundwater withdrawals. Available data since the 1980s also indicate a thinning of the freshwater lens and an increase in chloride concentrations of pumped water from production wells. These trends, combined with projected increases in demand for groundwater in central Maui, have led to concerns over groundwater availability and have highlighted a need to improve general understanding of the hydrologic effects of proposed groundwater withdrawals in the Waihe‘e, ‘Īao, and Waikapū areas of central Maui.
A numerical groundwater model was constructed to simulate the flow and salinity of groundwater in central Maui. The model simulates the effects of changes in groundwater withdrawals and recharge on water levels, freshwater-lens thicknesses, and chloride concentrations of pumped water from production wells. The model incorporates updated water-budget estimates of groundwater recharge from infiltration and direct recharge, seepage in stream channels, and inflow from inland areas. Mean annual groundwater recharge from infiltration and direct recharge was estimated using a daily water-budget model and the most current data, including the distributions of monthly rainfall and potential evapotranspiration, for the study area for nine historical periods from 1926 through 2012: 1926–69, 1970–79, 1980–84, 1985–89, 1990–94, 1995–99, 2000–04, 2005–09, and 2010–12. The water-budget model also estimated groundwater recharge based on one hypothetical scenario that used 1980–2010 rainfall and 2017 land cover. For the nine historical periods, estimated recharge from infiltration and direct recharge within the area of the groundwater model ranged from 30.4 million gallons per day (Mgal/d) during 2010–12 to 98.7 Mgal/d during 1926–69. Variability in recharge during these periods mainly reflects changes in rainfall and irrigation over time. Between 2010 and 2014, streamflow restoration in previously diverted streams resulted in an estimated increase in recharge from seepage in stream channels of about 12.5 Mgal/d. Average groundwater inflow of about 39.6 Mgal/d from inland, dike-intruded areas to the main area of interest was estimated from an existing island-wide numerical groundwater-flow model, which is at a larger scale and incorporates a greater number of simplifying assumptions.
The numerical groundwater model developed for this study was calibrated to 1926–2012 transient water levels, vertical salinity profiles, and chloride concentrations of water pumped by production wells in the study area. The model was then used to evaluate one future recharge and six selected withdrawal scenarios, developed in consultation with the Maui Department of Water Supply, in terms of long-term changes in water level and 50-percent ocean-water salinity surface. The groundwater model was also used to simulate the future salinity of water withdrawn by existing and proposed production wells. The simulations were run to steady-state conditions, providing an estimate of the long-term effects of changes in withdrawal and recharge on the groundwater resource. Results of the simulated future withdrawal scenarios indicate that, relative to 2017–18 rates, the scenarios’ long-term effect of increased withdrawals ultimately leads to lower water levels and a higher 50-percent ocean-water salinity surface indicating a thinning of the freshwater lens. Results also indicate that the increased withdrawals produce some groundwater with chloride concentration below 250 milligrams per liter and some groundwater with higher chloride concentration. The amount of drawdown near production wells and the quality of water withdrawn from production wells is dependent on the rate and spatial distribution of the withdrawals.
The model was also used to evaluate how groundwater availability may be affected for a drier recharge scenario based on a published study of future climate. Model results of the future recharge scenario indicate that the rate of groundwater recharge is a controlling factor for (1) water levels, (2) the 50-percent ocean-water salinity surface, and (3) the quality of water withdrawn from production wells in the Wailuku area. Coupled with reduced groundwater recharge (with all other factors remaining equal), the modeled future withdrawals in the scenario would tend to cause lower water levels, a higher 50-percent ocean-water salinity surface, and increased salinity of water withdrawn from production wells.
The three-dimensional numerical groundwater model developed for this study utilizes the latest available hydrologic and geologic information and is a useful tool for understanding the long-term hydrologic effects of additional groundwater withdrawals in central Maui. The model has several limitations, including its non-uniqueness and inability to account for local-scale heterogeneities. Short-term effects of changes in recharge and withdrawals—and optimization of pumping rates to meet increased demand for water with acceptable salinity—are possible conditions for future simulation analyses.
Director,
Pacific Islands Water Science Center
U.S. Geological Survey
Inouye Regional Center
1845 Wasp Blvd., B176
Honolulu, HI 96818
This report describes the findings of a U.S. Geological Survey study, completed in cooperation with the Bureau of Land Management, focused on better understanding the present-day (1975–2019) hydrogeology and groundwater quality of the San Agustin Basin in west-central New Mexico to support sustainable groundwater resource management. The basin hosts a relatively undeveloped basin-fill and alluvium aquifer system and is topographically divided into east and west subbasins by the McClure Hills. Groundwater chemistry and groundwater elevation data were compiled, collected, and interpreted in the context of groundwater flow and quality. The analyses presented in this report consider groundwater chemistry data collected within the last decade (2010–19) and groundwater elevation data collected from 1975 through 2019 to provide insight into present-day conditions. Groundwater elevations show that groundwater typically moves from the highlands to the lowlands, with a prominent east to west regional trend. Groundwater elevations were lowest in the southwestern portion of the west subbasin, where estimated flow directions suggest underflow through the local highlands into the northern East Fork Gila River watershed, which is further supported by historical groundwater elevation data from the northern East Fork Gila River watershed. Gradual groundwater elevation gradients (about 2 feet per mile) near the east and west subbasin divide suggest that groundwater slowly flows from the east subbasin to the west subbasin.
Quantitative analyses of groundwater chemistry data show that groundwater in both subbasins has similar chemical characteristics. A systematic east to west groundwater evolution in water chemistry was not observed despite evidenced subbasin connectivity. The absence of this pattern suggests that groundwater mixing is regionally prevalent, sediment reactivity is low and variable, and (or) recharge conditions are comparable in both subbasins. Groundwater chemistry was generally independent of aquifer type, suggesting that the aquifers are hydrologically well connected. Corrected carbon-14 groundwater age estimates in the basin ranged from 232 to 13,916 years before present with a median of 5,409 years. A wide range of groundwater ages is therefore present in the basin, with waters commonly being thousands of years old, thereby supporting generally slow regional groundwater movement. A component of relatively young groundwater, for which estimated ages could not be accurately computed, is also present in the basin, and it may commonly mix with older waters. The spatial distribution of categorical and quantitative groundwater ages indicates that most recharge likely occurs in the highlands through mountain-block recharge and as focused recharge within arroyos, although evidence of modern (1953 and after) groundwater was minimal at sampled sites.
Median annual gradients (groundwater elevation change over time) indicate that most groundwater elevations in the lowlands changed little (−0.2 to 0.2 foot per year) from 1975 through 2019. Groundwater elevations in the highlands varied more annually, which is likely due to recharge from precipitation events. These more variable groundwater elevations in the highlands compared with the lowlands, along with groundwater ages, provide further evidence that most groundwater recharge takes place in the highlands, with minimal recharge in the lowlands. Median groundwater elevation change for all sites was −0.05 foot per year. Temporal consistency of lowland groundwater elevations suggests that regional groundwater dynamics have been more or less stable through time under current climate and development conditions, although median annual gradients indicate that groundwater elevations may have slightly declined on average between 1975 and 2019.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225029","collaboration":"Prepared in cooperation with Bureau of Land Management and in collaboration with New Mexico Bureau of Geology and Mineral Resources","usgsCitation":"Pepin, J.D., Travis, R.E., Blake, J.M., Rinehart, A., and Koning, D., 2022, Hydrogeology and groundwater quality in the San Agustin Basin, New Mexico, 1975–2019: U.S. Geological Survey Scientific Investigations Report 2022–5029, 61 p., 4 app., https://doi.org/10.3133/sir20225029.","productDescription":"Report: x, 61 p.; 6 Tables; Dataset","numberOfPages":"76","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-120066","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":401145,"rank":11,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":401143,"rank":10,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2022/5029/sir20225029_table3.1.csv","text":"Table 3.1","size":"29.5 kB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2022-5029 Table 3.1"},{"id":401142,"rank":9,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2022/5029/sir20225029_table3.1.xlsx","text":"Table 3.1","size":"55.2 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2022-5029 Table 3.1"},{"id":401141,"rank":8,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2022/5029/sir20225029_table2.1.csv","text":"Table 2.1","size":"14.3 kB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2022-5029 Table 2.1"},{"id":401138,"rank":5,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2022/5029/sir20225029_table1.1.xlsx","text":"Table 1.1","size":"116 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2022-5029 Table 1.1"},{"id":401137,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5029/images"},{"id":401140,"rank":7,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2022/5029/sir20225029_table2.1.xlsx","text":"Table 2.1","size":"27.6 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2022-5029 Table 2.1"},{"id":401136,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5029/sir20225029.XML"},{"id":401139,"rank":6,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2022/5029/sir20225029_table1.1.csv","text":"Table 1.1","size":"146 kB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2022-5029 Table 1.1"},{"id":401135,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5029/sir20225029.pdf","text":"Report","size":"8.37 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5029"},{"id":401134,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5029/coverthb.jpg"}],"country":"United States","state":"New Mexico","otherGeospatial":"San Agustin Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.666,\n 34.5\n ],\n [\n -107.333,\n 34.5\n ],\n [\n -107.333,\n 33.333\n ],\n [\n -108.666,\n 33.333\n ],\n [\n -108.666,\n 34.5\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New Mexico Water Science Center
U.S. Geological Survey
6700 Edith Blvd. NE
Albuquerque, NM 87113
An airborne electromagnetic survey west of the Poso Creek oil field, located in the southeastern San Joaquin Valley, California, was flown in October 2016 to improve understanding of the hydrogeologic setting and the distribution of groundwater salinity in the area. The airborne electromagnetic data were used to develop resistivity models of the subsurface, where the mean depth of investigation is about 300 meters below the land surface and thus characterizes parts of the Kern River Formation and overlying sediments. Resistivity models along with water table elevation, historical total dissolved solids measurements of water samples from wells, well lithologic records, borehole geophysical logs, and mapped surface geology were used to develop an understanding of local hydrogeologic controls on resistivity. Interpretation of these data indicate the resistivity structure primarily reflects the general lithologic character and geologic structure of the study area, with more subtle influences from variations in saturation and salinity.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/dr1155","collaboration":"Prepared in cooperation with the California State Water Resources Control Board","usgsCitation":"Zamudio, K.D., Ball, L.B., and Stephens, M.J., 2022, Airborne electromagnetic survey results near the Poso Creek oil field, San Joaquin Valley, California, fall 2016: U.S. Geological Survey Data Report 1155, 55 p., https://doi.org/10.3133/dr1155.","productDescription":"Report: vii, 59 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-131476","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":501206,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113076.htm","linkFileType":{"id":5,"text":"html"}},{"id":400702,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/dr/1155/dr1155.xml"},{"id":400701,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/dr/1155/images"},{"id":400662,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/dr/1155/coverthb.jpg"},{"id":400663,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/dr/1155/dr1155.pdf","text":"Report","size":"14.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DR 1155"},{"id":400664,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9H9AVZY","text":"USGS data release","linkHelpText":"Airborne electromagnetic and magnetic survey data, southeastern San Joaquin Valley near Cawelo, California, 2016"}],"country":"United States","state":"California","otherGeospatial":"Poso Creek Oil Field, 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 -119.2,\n 35.4667\n ],\n [\n -119.0667,\n 35.4667\n ],\n [\n -119.0667,\n 35.5833\n ],\n [\n -119.2,\n 35.5833\n ],\n [\n -119.2,\n 35.4667\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Geology, Geophysics, and Geochemistry Science Center
U.S. Geological Survey
Box 25046, Mail Stop 973
Denver, CO 80225