Freshwater flow to the Ten Thousand Islands (TTI) estuary has been altered by the construction of the Tamiami Trail and construction of features in the now defunct Southern Golden Gate Estates development. This development included four associated canals that combine into the Faka Union Canal, which discharges into the TTI estuary. The Picayune Strand Restoration Project (PSRP) was initiated in 2007 to improve freshwater delivery to the TTI estuary by removing hundreds of miles of roads, emplacing hundreds of canal plugs, removing exotic vegetation, and constructing three pump stations. Quantifying the tributary flows and salinity patterns prior to, during, and after the restoration is essential to assessing the effectiveness of upstream restoration efforts. The U.S. Geological Survey, in cooperation with U.S. Army Corps of Engineers, initiated an ongoing study in 2006 to assess flow and salinity patterns in the TTI estuary. This is the second report by the U.S. Geological Survey describing flow characteristics and salinity patterns in the TTI area as part of the PSRP. This report describes flow characteristics and salinity patterns for the monitoring stations at Faka Union River, Pumpkin River, and East River and includes an assessment of salinity data from the Faka Union Boundary and Blackwater River water-quality stations for water years 2007–19. A water year is defined as the 12-month period from October 1 for any given year to September 30 of the following year.
Annual and monthly variations in flow and salinity are often related to variations in rainfall with high and low annual flows (and below average and above average salinities) typically occurring during years with high and low annual rainfall, respectively. Monthly flows typically begin increasing in June and peak in September. Over the study period, positive trends in rainfall-adjusted monthly flow were detected at Faka Union River and East River, whereas no significant trend in flow was detected at Pumpkin River. Faka Union River is the largest contributor of freshwater to the TTI estuary, providing over 80 percent of the annual freshwater inflow to the estuary. The Faka Union Canal is expected to be the largest contributor of freshwater because until the PSRP is completed, the Faka Union Canal receives substantial drainage from multiple canals, which is not the case for Pumpkin and East Rivers. East River was the second largest contributor, followed by Pumpkin River. East River is downstream of the Fakahatchee Stand, which is a larger contributing area than the current contributing area for Pumpkin River. Monthly mean salinities were lowest at Faka Union River and East River, indicating that they received a greater amount of freshwater than the stations to the west. Negative trends in rainfall-adjusted salinity monthly means were observed at all monitoring stations during the study period. Increased trends in flow and decreased trends in salinity are attributed to increases in flow from upstream canals.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215028","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Booth, A.C., and Knight, T.M., 2021, Flow characteristics and salinity patterns in tidal rivers within the northern Ten Thousand Islands, southwest Florida, water years 2007–19: U.S. Geological Survey Scientific Investigations Report 2021–5028, 21 p., https://doi.org/10.3133/sir20215028.","productDescription":"vii, 21 p.","numberOfPages":"34","ipdsId":"IP-122818","costCenters":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":385935,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2021/5028/images"},{"id":385934,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5028/sir20215028.pdf","text":"Report","size":"4.31 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5028"},{"id":385933,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5028/coverthb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Northern Ten Thousand Islands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.67304992675781,\n 25.852426562716428\n ],\n [\n -81.47941589355469,\n 25.852426562716428\n ],\n [\n -81.47941589355469,\n 25.972243398901558\n ],\n [\n -81.67304992675781,\n 25.972243398901558\n ],\n [\n -81.67304992675781,\n 25.852426562716428\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Caribbean-Florida Water Science Center (CFWSC)
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The lower Las Vegas Wash represents the terminal surface drainage for the Las Vegas Valley in southern Nevada. In 1997, high concentrations of perchlorate were found in seeps contributing to discharge in this area and traced to an industrial byproduct from manufacturing operations in the mid-1900s at the nearby Basic Magnesium, Incorporated, plant. The discovery prompted a water-resources investigation by the Nevada Department of Environmental Protection (NDEP) to develop an understanding of the nearby groundwater flow system and the dynamics associated with surface-water flow in the Wash. In 2016, the U.S. Geological Survey was tasked with evaluating surface-water discharge in the lower Las Vegas Wash near locations where perchlorate concentrations from the groundwater system had been detected. Results of this study will assist NDEP with identifying areas of groundwater and surface-water interaction and help guide future cleanup and monitoring efforts.
Streamflow discharge is evaluated along a 4-mile section of the lower Las Vegas Wash (referred to as the Wash) and used to describe surface-water and groundwater interactions between the Wash channel and bank sediments. Continuous discharge data were collected during a 2-year period (2016–18) at 5 gaging stations along the Wash. Additionally, multiple discrete measurements between gaging stations were collected during 4 synoptic sampling events between 2016 and 2018.
A diurnal discharge pattern, controlled by upstream treated wastewater releases, provided high- and low-discharge markers that are used to compute downstream time-lags of peak and minimum flows. Computed time-lags are used to establish travel times between measurement sites, and difference in upstream and time-lagged downstream hydrographs are used to compute increases (gain) or decreases (loss) in discharge between gaging stations or between gaging stations and discrete measurements. Tributary surface-water inflows to the lower Las Vegas Wash from wastewater discharge, remediation efforts, and periodic flooding from rainfall runoff are included in computing differences in discharge. Differences between discharge data from delineated reaches are used to define locations of daily, monthly, and yearly streamflow gains from or losses to adjacent bank sediments. Construction of additional channel-stabilization weirs have occurred since the completion of this study and the associated change to streamflow dynamics may limit study results to the period analyzed; however, methods and processes described in this report can be used in future evaluations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215034","collaboration":"Prepared in cooperation with the Nevada Division of Environmental Protection","usgsCitation":"Wilson, J.W., 2021, Discharge data collection and analysis and implications for surface-water/groundwater interactions in the lower Las Vegas Wash, Clark County, Nevada, 2016–18: U.S. Geological Survey Scientific Investigations Report 2021–5034, 25 p., https://doi.org/10.3133/sir20215034.","productDescription":"Report: vi, 25 p.; Data Release","numberOfPages":"25","onlineOnly":"Y","ipdsId":"IP-091622","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":385836,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9UQCOSM","linkHelpText":"Trace of the Lower Las Vegas Wash Study Area, 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Nevada Water Science Center
U.S. Geological Survey
2730 N. Deer Run Road
Carson City, Nevada 95819
The Sac and Fox Tribe of the Mississippi in Iowa is the only federally recognized Tribe in the State of Iowa and is commonly known as the Meskwaki Nation. The Tribe owns more than 8,100 acres, referred to as the “Meskwaki Settlement.” The Meskwaki Settlement uses a well field that withdraws water from the Iowa River alluvial aquifer (IRAA) to supply drinking water to members of the Tribe. Increased severity and timing of flooding and drought conditions, coupled with water-quality concerns in the Iowa River, have prompted the Meskwaki Nation to start identifying tools to provide a better understanding of how extreme climate events (changes in streamflow, flood frequency, and magnitude and persistence of drought conditions), increasing water-supply demands, and groundwater storage depletion will affect water availability in the IRAA.
From June 2017 through September 2020, the U.S. Geological Survey, in cooperation with the Meskwaki Nation, collected continuous and discrete groundwater level data from 11 wells in a U.S. Geological Survey monitoring-well network. Groundwater level data collected at these wells were assessed with daily precipitation data and compared to changes in stream level elevations and daily groundwater withdrawals to determine how these changes affect groundwater-table elevations. Results from this study could be used to guide the development of a conceptual model for groundwater flow and a groundwater flow model for the IRAA to quantify and forecast the effect of groundwater withdrawals, Iowa River streamflow, and local precipitation on the water table in the IRAA.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211019","collaboration":"Prepared in cooperation with the Sac and Fox Tribe of the Mississippi in Iowa","usgsCitation":"Gruhn, L.R., and Haj, A.E., 2021, Effect of groundwater withdrawals, river stage, and precipitation on water-table elevations in the Iowa River alluvial aquifer near Tama, Iowa, 2017–20: U.S. Geological Survey Open-File Report 2021–1019, 11 p., https://doi.org/10.3133/ofr20211019.","productDescription":"Report: vi, 11 p.; Data Release; Dataset","numberOfPages":"22","onlineOnly":"Y","ipdsId":"IP-124518","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":385788,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1019/images"},{"id":385789,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1019/ofr20211019.XML"},{"id":385680,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1019/coverthb.jpg"},{"id":385681,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1019/ofr20211019.pdf","text":"Report","size":"2.92 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021–1019"},{"id":385682,"rank":3,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"U.S. Geological Survey National Water Information System database","linkHelpText":"— USGS water data for the Nation"},{"id":385683,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P912FO3L","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Geospatial datasets for the flood-inundation study for the Iowa River at the Meskwaki Settlement in Iowa, 2019"}],"country":"United States","state":"Iowa","county":"Tama County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-92.2996,42.2975],[-92.2992,42.2098],[-92.2989,42.1226],[-92.2991,42.0354],[-92.2977,41.9786],[-92.2994,41.95],[-92.299,41.8623],[-92.418,41.8625],[-92.5357,41.8621],[-92.6522,41.862],[-92.7674,41.8618],[-92.7671,41.9494],[-92.7662,42.0348],[-92.7672,42.1234],[-92.7687,42.2101],[-92.7697,42.2964],[-92.6531,42.2971],[-92.5353,42.2972],[-92.418,42.2976],[-92.2996,42.2975]]]},\"properties\":{\"name\":\"Tama\",\"state\":\"IA\"}}]}","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
400 South Clinton Street, Suite 269
Iowa City, IA 52240
In 2015–16, a comparison study of stream sediment collection techniques was done for a U.S. Geological Survey streamgage on the Nemadji River near South Superior, Wisconsin (U.S. Geological Survey station number 04024430) to provide an adjustment factor for comparing suspended-sediment rating curves for two historical periods 1973–86 and 2006–16. During 1973–1986, the U.S. Geological Survey used the equal-width-increment technique to collect suspended-sediment concentration data (EWI SSC). The Wisconsin Department of Natural Resources and Minnesota Pollution Control Agency collected grab samples for total suspended solids (grab TSS) concentration starting in 2006 and continuing beyond 2016. In addition to the comparison study of suspended-sediment concentrations, bedload and bed material samples were collected in 2015–16, and the modified Einstein procedure was run to further characterize total sediment loads. The 2015–16 study indicated that the EWI SSC and grab TSS concentrations were different, but not as much as expected, especially on the high end where grab TSS concentrations were sometimes higher than EWI SSC concentrations, possibly due to a combination of a high percentage of fines in suspension and higher concentrations in the center of the channel than the margins. The 2015–16 measured bedload made up a small percentage of total sediment load, and bedload and streambed particle sizes are 90 to 100 percent sand sized or smaller. The relative proportion of measured bedload to total load decreased with increased streamflow, and for streamflows greater than 1,800 cubic feet per second, the suspended load made up 98 percent of the total load. Calculated 2015–16 instantaneous total sediment loads from the modified Einstein procedure were up to 70 percent of the measured loads for flows less than 1,000 cubic feet per second and near or more than 100 percent for flows greater than 1,000 cubic feet per second. The sediment rating curve developed for the 2006–16 adjusted grab TSS data had a similar slope but a lower intercept than its 1973–86 EWI SSC counterpart, indicating that for a given streamflow, suspended-sediment concentrations were lower for 2006–16 compared to 1973–86. The negative offset equates to estimates of annual suspended-sediment loads in 2006–16 being on average 87 percent of the 1973–86 loads. Over the period 2009–16, annual suspended-sediment loads ranged from a low of about 21,000 tons per year in 2015 to a high of 167,000 tons per year in 2012 with a mean of 85,000 tons per year. However, reductions in suspended-sediment concentrations are likely obscured by large loads during years with flooding.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211003","collaboration":"Prepared in cooperation with the Wisconsin Department of Natural Resources","usgsCitation":"Fitzpatrick, F.A., 2021, Sediment characteristics of northwestern Wisconsin’s Nemadji River, 1973–2016: U.S. Geological Survey Open-File Report 2021–1003, 27 p., https://doi.org/10.3133/ofr20211003.","productDescription":"Report: viii, 27 p.; Data Release","numberOfPages":"40","onlineOnly":"Y","ipdsId":"IP-085024","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":385361,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FX0X6Y","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Selected sediment data and results from regression models, modified Einstein Procedure, and loads estimation for the Nemadji River, 1973–2016"},{"id":385360,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1003/ofr20211003.pdf","text":"Report","size":"5.16 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021–1003"},{"id":385359,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1003/coverthb.jpg"}],"country":"United States","state":"Minnesota, Wisconsin","otherGeospatial":"Nemadji River watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.55157470703125,\n 46.38672781370433\n ],\n [\n -92.01599121093749,\n 46.38672781370433\n ],\n [\n -92.01599121093749,\n 46.65697731621612\n ],\n [\n -92.55157470703125,\n 46.65697731621612\n ],\n [\n -92.55157470703125,\n 46.38672781370433\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Upper Midwest Water Science Center
U.S. Geological Survey
8505 Research Way
Middleton, WI 53562
Ecosystem-based management relies on understanding how perturbations influence ecosystem structure and function (e.g., invasive species, exploitation, abiotic changes). However, data on unimpacted systems are scarce; therefore, we often rely on impacted systems to make inferences about ‘natural states.’ Among the Laurentian Great Lakes, Lake Superior provides a unique case study to address non-native species impacts because the food web is dominated by native species. Additionally, Lake Superior is both vertically (benthic versus pelagic) and horizontally (nearshore versus offshore) structured by depth, providing an opportunity to compare the function of these sub-food webs. We developed an updated Lake Superior EcoPath model using data from the 2005/2006 lake-wide multi-agency surveys covering multiple trophic levels. We then compared trophic transfer efficiency (TTE) to previously published EcoPath models. Finally, we compared ecosystem function of the 2005/2006 ecosystem to that with non-native linkages removed and compared native versus non-native species-specific approximations of TTE and trophic flow. Lake Superior was relatively efficient (TTE = 0.14) compared to systems reported in a global review (average TTE = 0.09), and the microbial loop was highly efficient (TTE > 0.20). Non-native species represented a very small proportion (<0.01%) of total biomass and were generally more efficient and had higher trophic flow compared to native species. Our results provide valuable insight into the importance of the microbial loop and represent a baseline estimate of non-native species impacts on Lake Superior. Finally, this work is a starting point for further model development to predict future changes in the Lake Superior ecosystem.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2021.04.010","usgsCitation":"Mathias, B.G., Hrabik, T.R., Hoffman, J.C., Gorman, O., Seider, M., Sierszen, M.E., Vinson, M., Yule, D.L., and Yurista, P.M., 2021, Trophic transfer efficiency in the Lake Superior food web: Assessing the impacts of non-native species: Journal of Great Lakes Research, v. 47, no. 4, p. 1146-1158, https://doi.org/10.1016/j.jglr.2021.04.010.","productDescription":"13 p.","startPage":"1146","endPage":"1158","ipdsId":"IP-115192","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":452278,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9067395","text":"External Repository"},{"id":436366,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9W93YXH","text":"USGS data release","linkHelpText":"Compilation of Data for Parameterization of an Ecopath Model of Lake Superior at the Beginning of the 21st Century (2001-2016)"},{"id":385642,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Lake Superior","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.63671874999997,\n 46.195042108660154\n ],\n [\n -83.84765624999997,\n 46.195042108660154\n ],\n [\n -83.84765624999997,\n 49.83798245308484\n ],\n [\n -92.63671874999997,\n 49.83798245308484\n ],\n [\n -92.63671874999997,\n 46.195042108660154\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"47","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Mathias, Bryan G.","contributorId":240743,"corporation":false,"usgs":false,"family":"Mathias","given":"Bryan","email":"","middleInitial":"G.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":815547,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hrabik, Thomas R.","contributorId":35614,"corporation":false,"usgs":false,"family":"Hrabik","given":"Thomas","email":"","middleInitial":"R.","affiliations":[{"id":6915,"text":"University of Minnesota - Duluth","active":true,"usgs":false}],"preferred":false,"id":815548,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hoffman, Joel C.","contributorId":84244,"corporation":false,"usgs":false,"family":"Hoffman","given":"Joel","email":"","middleInitial":"C.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":815549,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gorman, Owen 0000-0003-0451-110X","orcid":"https://orcid.org/0000-0003-0451-110X","contributorId":216889,"corporation":false,"usgs":true,"family":"Gorman","given":"Owen","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":815550,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Seider, Michael J.","contributorId":258016,"corporation":false,"usgs":false,"family":"Seider","given":"Michael J.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":815551,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sierszen, Michael E.","contributorId":63320,"corporation":false,"usgs":false,"family":"Sierszen","given":"Michael","email":"","middleInitial":"E.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":815552,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Vinson, Mark 0000-0001-5256-9539 mvinson@usgs.gov","orcid":"https://orcid.org/0000-0001-5256-9539","contributorId":3800,"corporation":false,"usgs":true,"family":"Vinson","given":"Mark","email":"mvinson@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":815553,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Yule, Daniel L. 0000-0002-0117-5115","orcid":"https://orcid.org/0000-0002-0117-5115","contributorId":248693,"corporation":false,"usgs":true,"family":"Yule","given":"Daniel","middleInitial":"L.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":815554,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Yurista, Peder M.","contributorId":127358,"corporation":false,"usgs":false,"family":"Yurista","given":"Peder","email":"","middleInitial":"M.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":815555,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70220322,"text":"sir20215021 - 2021 - Hydraulic characterization of carbonate-rock and basin-fill aquifers near Long Canyon, Goshute Valley, northeastern Nevada","interactions":[],"lastModifiedDate":"2025-05-14T18:34:47.405035","indexId":"sir20215021","displayToPublicDate":"2021-05-07T07:51:36","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-5021","displayTitle":"Hydraulic Characterization of Carbonate-Rock and Basin-Fill Aquifers near Long Canyon, Goshute Valley, Northeastern Nevada","title":"Hydraulic characterization of carbonate-rock and basin-fill aquifers near Long Canyon, Goshute Valley, northeastern Nevada","docAbstract":"Understanding groundwater flow and pumping effects near pending mining operations requires accurate subsurface hydraulic characterization. To improve conceptual models of groundwater flow and development in the complex hydrogeologic system near Long Canyon Mine, in northwestern Goshute Valley, northeastern Nevada, the U.S. Geological Survey characterized the hydraulic properties of carbonate rocks and basin-fill aquifers using an integrated analysis of steady-state and stressed aquifer conditions informed by water chemistry and aquifer-test data. Hydraulic gradients and groundwater-age data in northern Goshute Valley indicate carbonate rocks in the Pequop Mountains just west and south of the Long Canyon Mine project area constitute a more permeable and active flow system than saturated rocks in the northern Pequop Mountains, western Toano Range, and basin fill. Permeable carbonate rocks in the northern Pequop Mountains, in part, discharge to the Johnson Springs wetland complex (JSWC), where mean groundwater ages range from 500 to 2,400 years and samples all contain a small fraction of modern waters, relative to mean ages of 8,600 to more than 22,000 years for most groundwater sampled to the north and east. Recharge to the JSWC occurs from a roughly 27-square-mile area in the upgradient Pequop Mountains to the west, composed mostly of permeable carbonate rock and fractured quartzite, and bounded by low-permeability shales and marbleized and siliclastic rocks.
Single-well aquifer-test analyses provided transmissivity estimates at pumped wells. Transmissivity estimates ranged from 7,000 to 400,000 feet squared per day (ft2/d) in carbonate rocks and from 2,000 to 80,000 ft2/d in basin fill near the Long Canyon Mine. Water-level drawdown from multiple-well aquifer testing and rise from unintentional leakage into the overlying basin-fill aquifer were estimated and distinguished from natural fluctuations in 93 pumping and monitoring sites using analytical water-level models. Leakage of disposed aquifer-test pumpage occurred south of the aquifer test area through an unlined irrigation ditch. Drawdown was detected at distances of as much as 3 miles (mi) from pumping wells at all but one carbonate-rock site, at basin-fill sites on the alluvial fan immediately downgradient from pumping wells, and in Big Spring and spring NS-05. Similar drawdowns in carbonate rocks within the drawdown detection area suggest all wells penetrate a highly transmissive zone (HTZ) that is bounded by low-permeability rocks. Drawdown was not detected in carbonate rocks to the west of Canyon fault, in any basin-fill sites on the valley floor east of the Hardy fault, or at volcanic sites to the north, indicating that these major fault structures and (or) permeability contrasts between hydrogeologic units impeded groundwater flow or obscured pumping signals. Alternatively, unintentional leakage might have obscured drawdown at basin-fill sites on the valley floor, where water-level rise was detected at nine sites over 3 mi.
Consistent hydraulic properties were estimated by simultaneously interpreting steady-state flow during predevelopment conditions and changes in groundwater levels and springflows from the 2016 carbonate-rock aquifer test with an integrated groundwater-flow model. Hydraulic properties were distributed across carbonate rocks, basin fill, volcanic rocks, and siliciclastic rocks with a hydrogeologic framework developed from geologic mapping and hydraulic testing. Estimated transmissivity distributions spanned at least three orders of magnitude in each rock unit. In the HTZ, simulated transmissivities ranged from 10,000 to 23,000,000 ft2/d, with the most transmissive areas occurring around Big Spring. Comparatively low carbonate-rock transmissivities of less than 10,000 ft2/d were estimated in the northern Pequop Mountains and poorly defined values of less than 1,000 ft2/d were estimated in the western Toano Range. Transmissivities in basin fill ranged from less than 10 to 80,000 ft2/d and were minimally constrained by the 2016 carbonate-rock aquifer test because poorly quantified leakage affected water levels more so than pumping. The most transmissive areas were informed by single-well aquifer tests along the eastern edge of the Pequop Mountains near Long Canyon Mine and could be indicative of a hydraulic connection between basin fill and more transmissive underlying carbonate rocks. Simulated transmissivities of volcanic and low-permeability rocks mostly are less than 1,000 ft2/d. The estimated hydraulic-property distributions and informed interpretation of hydraulic connections among hydrogeologic units improved the characterization and representation of groundwater flow near the Long Canyon Mine.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215021","collaboration":"Prepared in cooperation with the Nevada Division of Water Resources","usgsCitation":"Garcia, C.A., Halford, K.J., Gardner, P.M., and Smith, D.W., 2021, Hydraulic characterization of carbonate-rock and basin-fill aquifers near Long Canyon, Goshute Valley, northeastern Nevada: U.S. Geological Survey Scientific Investigations Report 2021–5021, 99 p., https://doi.org/10.3133/sir20215021.","productDescription":"Report: xii, 99 p.; 2 Data Releases","onlineOnly":"Y","ipdsId":"IP-094004","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":397361,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2021/5021/sir20215021.XML"},{"id":397360,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2021/5021/images"},{"id":385454,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9P1P7QV","text":"USGS data release","description":"USGS data release","linkHelpText":"Appendixes and supplemental data—Hydraulic characterization of carbonate-rock and basin-fill aquifers near Long Canyon, Goshute Valley, northeastern Nevada, 2011–16."},{"id":385453,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9JI8NQF","text":"USGS data release","description":"USGS data release","linkHelpText":"MODFLOW-2005 and PEST models used to simulate the 2016 carbonate-rock aquifer test and characterize hydraulic properties of carbonate-rock and basin-fill aquifers near Long Canyon, Goshute Valley, northeastern Nevada."},{"id":385451,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5021/coverthb.jpg"},{"id":385452,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5021/sir20215021.pdf","text":"Report","size":"9.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5021"}],"country":"United States","state":"Nevada","otherGeospatial":"Goshute Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.98840332031249,\n 40.55554790286311\n ],\n [\n -114.2633056640625,\n 40.55554790286311\n ],\n [\n -114.2633056640625,\n 41.693424216151314\n ],\n [\n -114.98840332031249,\n 41.693424216151314\n ],\n [\n -114.98840332031249,\n 40.55554790286311\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oregon Water Science Center
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Estuaries and coastal areas are highly vulnerable to the impacts of acidification on shellfish, coral reefs, fisheries, and the commercial and recreational industries that they support. Yet, little is known about the extent of this vulnerability and the estuary-specific drivers that contribute to acidification, such as nutrient enrichment from stormwater, agriculture and wastewater discharges, upwelling of CO2 -rich seawater, elevated atmospheric CO2 from urban and agricultural activities, benthic and marsh-driven processes, and alkalinity and carbon content of freshwater flows. Comprehensive, high resolution monitoring data are needed at varying spatial and temporal scales to provide actionable information tailored to each estuary. Because carbonate chemistry in the coastal environment can be affected by nutrient dynamics, understanding how nutrient inputs exacerbate acidification impacts is essential for the formulation of estuary-specific actions.
","language":"English","publisher":"EPA","usgsCitation":"Galavotti, H., Vasslides, J., Poach, M., Bohlen, C., Hunt, C.W., Liebman, M., Hu, X., McCutcheon, M., O’Donnell, J., Howard-Strobel, K., Vella, P., Lehrter, J., Nielsen, K., Largier, J., Ford, T., Steele, A., Yates, K.K., Johnson, Y., Brown, C., and Pacella, S.R., 2021, Measuring coastal acidification using in situ sensors in the National Estuary Program: EPA Report EPA-842-R-21001, 71 p.","productDescription":"71 p.","ipdsId":"IP-122631","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":386091,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":386090,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://www.epa.gov/sites/production/files/2021-05/documents/coastal_acidification_nep_report_508.pdf"}],"country":"United States","state":"Alabama, California, Connecticut, Delaware. 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York","contributorId":259177,"corporation":false,"usgs":false,"family":"Johnson","given":"York","email":"","affiliations":[],"preferred":false,"id":816752,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Brown, Cheryl","contributorId":259178,"corporation":false,"usgs":false,"family":"Brown","given":"Cheryl","affiliations":[],"preferred":false,"id":816753,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Pacella, Stephen R.","contributorId":259179,"corporation":false,"usgs":false,"family":"Pacella","given":"Stephen","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":816754,"contributorType":{"id":1,"text":"Authors"},"rank":20}]}} ,{"id":70220121,"text":"sir20215008 - 2021 - Time-domain electromagnetic soundings and passive-seismic measurements for delineation of saline groundwater in the Genesee Valley-fill aquifer system, western New York, 2016–17","interactions":[],"lastModifiedDate":"2021-04-30T11:49:59.712827","indexId":"sir20215008","displayToPublicDate":"2021-04-29T10:00:00","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-5008","displayTitle":"Time-Domain Electromagnetic Soundings and Passive-Seismic Measurements for Delineation of Saline Groundwater in the Genesee Valley-Fill Aquifer System, Western New York, 2016–17","title":"Time-domain electromagnetic soundings and passive-seismic measurements for delineation of saline groundwater in the Genesee Valley-fill aquifer system, western New York, 2016–17","docAbstract":"The U.S. Geological Survey, in cooperation with the New York State Department of Environmental Conservation, used noninvasive surface geophysics in the investigation of the distribution of saline groundwater in the valley-fill aquifer system of the Genesee River Valley near the former Retsof salt mine in western New York. In 1994, the Retsof salt mine, the largest of its kind in the western hemisphere, underwent a catastrophic roof collapse that resulted in groundwater inflow from the valley-fill aquifer system and bedrock fracture zones into the mine through two bedrock-rubble chimneys and the subsequent dissolution and filling of the mine with saturated brine. Since the early 2000s, except for a period of remedial pumping in 2006 to 2013, high-salinity water has migrated upward through the rubble chimneys into the basal part the aquifer system. The extent of saline-water migration within the aquifer system had not been evaluated since the end of remedial pumping when all the monitoring wells were grouted shut and abandoned. Installation of a monitoring-well network would be expensive and difficult given the thickness and heterogeneous character of valley fill. An investigation of the current extent of saline water in the aquifer system was warranted because the basal part of the aquifer is shallow to the north and it is used for water supply.
In fall 2016 and fall 2017, the U.S. Geological Survey collected time-domain electromagnetic soundings at 105 sites along 13 cross-valley transects north and south of the mine-collapse area, east of Piffard, and on the Fowlerville Moraine. The time-domain electromagnetic soundings were colocated with passive-seismic measurements to estimate the bedrock-surface elevation through use of a regression equation developed from measurements at well sites with reported bedrock depths in the study area. An integrated analysis of the time-domain electromagnetic soundings with the depth-to-bedrock estimates, well logs, and past chloride-monitoring data suggests the presence of a zone of high electrical conductivity associated with saline water in the confined lower part of the valley-fill aquifer system. This high-salinity zone delineated in the lower confined aquifer extends from the mine-collapse area northward for more than 2.5 miles (4.0 kilometers). The chloride concentration in groundwater within this high-conductivity zone may be about 20,000 milligrams per liter. Saline water flowing upward through the bedrock-rubble chimneys and mixing with northward groundwater flow in the lower confined aquifer likely is a major source of chlorides for this high-conductivity zone. The northern extent of the zone is unclear because of the presence of highly saline water zones that were delineated by time-domain electromagnetic soundings in the lower confined aquifer and uppermost bedrock and are probably associated with historic salt-solution wells in Piffard or possibly sourced from natural brine pools.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215008","collaboration":"Prepared in cooperation with the New York State Department of Environmental Conservation","usgsCitation":"Williams, J.H., Kappel, W.M., Johnson, C.D., White, E.A., Heisig, P.M., and Lane, J.W., Jr., 2021, Time-domain electromagnetic soundings and passive-seismic measurements for delineation of saline groundwater in the Genesee valley-fill aquifer system, western New York, 2016–17: U.S. Geological Survey Scientific Investigations Report 2021–5008, 25 p., https://doi.org/10.3133/sir20215008.","productDescription":"Report: vii, 25 p.; 1 Plate: 49.96 x 35.95 inches; 3 Data Releases","numberOfPages":"25","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-108173","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":385251,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5008/coverthb.jpg"},{"id":385369,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9VQOCRZ","text":"USGS data release","linkHelpText":"Time-domain electromagnetic soundings to delineate saline groundwater in the Genesee valley-fill aquifer system, New York (2016-2017)"},{"id":385368,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9J354SU","text":"USGS data release","linkHelpText":"Chloride concentrations from wells in the Genesee River Valley, Livingston County, New York"},{"id":385367,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9LI7CCR","text":"USGS data release","linkHelpText":"Horizontal-to-vertical spectral ratio and depth-to-bedrock data for saline-groundwater investigation in the Genesee valley, New York, October-November 2016 and 2017"},{"id":385366,"rank":3,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2021/5008/sir20215008_plate1.pdf","text":"Plate 1","size":"59.4 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Electrical-conductivity transects from time-domain electromagnetic soundings, top of bedrock estimated from passive-seismic measurements, and lithostratigraphic logs of selected boreholes along 13 transects in the Genesee River Valley, western New York, 2016–17"},{"id":385365,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5008/sir20215008.pdf","text":"Report","size":"3.74 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5008"}],"country":"United States","state":"New York","otherGeospatial":"Genesee Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.93701171875,\n 42.54397489736545\n ],\n [\n -77.68363952636719,\n 42.54397489736545\n ],\n [\n -77.68363952636719,\n 42.97802779741624\n ],\n [\n -77.93701171875,\n 42.97802779741624\n ],\n [\n -77.93701171875,\n 42.54397489736545\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
Shallow nearshore groundwater and estimates of groundwater seepage were collected at 21 locations along the north and south shores of Lake Spokane beginning in October 2016 and ending in October 2019. Nitrate plus nitrite concentrations in nearshore groundwater ranged from <0.04 to 7.60 milligrams of nitrogen per liter. Nearshore groundwater orthophosphate concentrations ranged from <0.004 to 0.381 milligrams of phosphorus per liter, and, overall, there were no consistent seasonal differences in nearshore groundwater nutrients during this study. Nitrate plus nitrite concentrations were highest at sites located adjacent to nearshore development and similar to concentrations in water collected from nearby drinking water wells. Similarly, samples from locations adjacent to nearshore development were statistically greater than samples collected from other locations for orthophosphate concentrations. Dissolved boron concentrations, elevated values of which are an indicator of household-detergent use, were elevated in spring and summer at some locations, indicating that residential wastewater was reaching the lake. Stable isotope ratios of nitrate (15N and 18O), which were used to identify the source nitrate in sampled groundwater, showed that most data indicated a mix of soil nitrogen and nitrogen sources from human or animal waste.
Generally, median groundwater discharge to the lake was low across all sites and seasons, with most values smaller than 1 centimeter per day (cm/d). Similar to the nutrient-concentration data, seasonal patterns in seepage flux were weak, and, where there were seasonal increases in flux, the increased groundwater discharge did not carry increased nutrients. Localized estimates of groundwater seepage flux were scaled up to the entire length of the lakeshore. The median groundwater flux of 0.34 cm/d scaled to 1.9 cubic feet per second (ft3/s) and the maximum recorded seepage flux of 17.6 cm/d was equivalent to 97 ft3/s. These estimates of groundwater inputs are orders of magnitude less than surface water inputs to the lake.
Nutrient loads were determined from the product of groundwater flow and a representative nutrient concentration. Using the median seepage flux of 1.9 ft3/s, the orthophosphate load ranged from 0.7 to 3.8 pounds of phosphorus per day based on the median and maximum orthophosphate concentrations, respectively. For nitrate plus nitrite, loads ranged from 5.8 to 76.6 pounds of nitrogen per day. Using the maximum value of seepage flux, maximum orthophosphate loads ranged from 35 to 198 pounds of phosphorus per day, and maximum nitrate plus nitrite loads ranged from 296 to 3,943 pound of nitrogen per day. Overall, groundwater nutrient loads are small compared to other sources to the lake. Continued monitoring of future nutrient loads would aid decisions by resource managers as infrastructure within the neighboring residential communities continues to age around Lake Spokane.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215023","collaboration":"Prepared in cooperation with Stevens County Conservation District and Spokane County Conservation District","usgsCitation":"Sheibley, R.W., and Foreman, J.R., 2021, Nitrogen and phosphorus loads from groundwater to Lake Spokane, Spokane, Washington, October 2016–October 2019: U.S. Geological Survey Scientific Investigations Report 2021–5023, 34 p., https://doi.org/10.3133/sir20215023.","productDescription":"Report: vii, 34 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-119397","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":397365,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2021/5023/sir20215023.XML"},{"id":385292,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P95IQ8HH","text":"USGS data release","description":"USGS data release","linkHelpText":"Water quality and seepage estimates collected at Lake Spokane, Washington, 2016–19."},{"id":385290,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5023/coverthb.jpg"},{"id":385291,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5023/sir20215023.pdf","text":"Report","size":"5.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5023"},{"id":397364,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2021/5023/images"},{"id":402988,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20215023/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2021-5023"}],"country":"United States","state":"Washington","otherGeospatial":"Lake Spokane","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.86407470703125,\n 47.76148371616669\n ],\n [\n -117.50976562499999,\n 47.76148371616669\n ],\n [\n -117.50976562499999,\n 47.91173983456231\n ],\n [\n -117.86407470703125,\n 47.91173983456231\n ],\n [\n -117.86407470703125,\n 47.76148371616669\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Washington Water Science Center
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934 Broadway, Suite 300
Tacoma, Washington 98402
The historic distribution of Mojave desert tortoises (Gopherus agassizii) was relatively continuous across the range, and the importance of tortoise habitat outside of designated tortoise conservation areas (TCAs) to recovery has long been recognized for its contributions to supporting gene flow between TCAs and to minimizing impacts and edge effects within TCAs. However, connectivity of Mojave desert tortoise populations has become a concern because of recent and proposed development of large tracts of desert tortoise habitat that cross, fragment, and surround designated conservation areas. This paper summarizes the underlying concepts and importance of connectivity for Mojave desert tortoise populations by reviewing current information on connectivity and providing information to managers for maintaining or enhancing desert tortoise population connectivity as they consider future proposals for development and management actions.
Maintaining an ecological network for the Mojave desert tortoise, with a system of core habitats (TCAs) connected by linkages, is necessary to support demographically viable populations and long-term gene flow within and between TCAs. There are four points for wildlife and land-management agencies to consider when making decisions that could affect connectivity of Mojave desert tortoise populations (for example, in updating actions in resource management plans or amendments that could help maintain or restore functional connectivity in light of the latest information):
Each TCA has unique strengths and weaknesses regarding its ability to support minimum sustainable populations based on areal extent and its ability to support population increases based on landscape connection with adjacent populations. Considering how proposed projects (inside or outside of TCAs) affect connectivity and the ability of TCAs to support at least 5,000 adult tortoises (the numerical goal for each TCA) could help managers to maintain the resilience of TCAs to population declines. The same project, in an alternative location, could have very different impacts on local and regional populations. For example, within the habitat matrix surrounding TCAs, narrowly delineated corridors may not allow for natural population dynamics if they do not accommodate overlapping home ranges along most of their widths so that tortoises reside, grow, find mates, and produce offspring that can replace older tortoises. In addition, most habitat outside TCAs may receive more surface disturbance than habitat within TCAs. Therefore, managing the entire remaining matrix of desert tortoise habitat for permeability may be better than delineating fixed corridors. These concepts apply, especially given uncertainty about long-term condition of habitat, within and outside of TCAs under a changing climate.
Ultimately, questions such as “What are the critical linkages that need to be protected?” could be better framed as “How can we manage the remaining habitat matrix in ways that sustain ecological processes and habitat suitability for special status species?” Land-management decisions made in the context of the latter question may be more conducive to maintenance of a functional ecological network.
In California, the Bureau of Land Management established 0.1–1.0 percent caps on new surface-disturbance for TCAs and mapped linkages that address the issues described in number 1 of this list.
Nevada, Utah, and Arizona currently do not have surface-disturbance limits. Limits comparable to those in the Desert Renewable Energy Conservation Plan (DRECP) would be 0.5 percent within TCAs and 1 percent within the linkages modeled by Averill-Murray and others (2013). Limits in some areas of California within the Desert Renewable Energy Conservation Plan, such as Ivanpah Valley, are more restrictive, at 0.1 percent. Continuity across the state line in Nevada could be achieved with comparable limits in the adjacent portion of Ivanpah Valley, as well as the Greater Trout Canyon Translocation Area and the Stump Springs Regional Augmentation Site. These more restrictive limits would help protect remaining habitat in the major interstate connectivity pathway through Ivanpah Valley and focal areas of population augmentation that provide additional population connectivity along the western flank of the Spring Mountains.
In a recent study that analyzed 13 years of desert tortoise monitoring data, nearly all desert tortoise observations were at sites in which 5 percent or less of the surrounding landscape within 1 kilometer was disturbed (Carter and others, 2020a). To help maintain tortoise habitability and permeability across all other non-conservation-designated tortoise habitat, all surface disturbance could be limited to less than 5-percent development per square kilometer because the 5-percent threshold for development is the point at which tortoise occupation drops precipitously (Carter and others, 2020a). However, although individual desert tortoises were observed at development levels up to 5 percent, we do not know the fitness or reproductive characteristics of these individuals. This level of development also may not allow for long-term persistence of healthy populations that are of adequate size needed for demographic or functional connectivity; therefore, a conservative interpretation suggests that, ideally, development could be lower. Lower development levels would be particularly useful in areas within the upper 5th percentile of connectivity values modeled by Gray and others (2019).
Reducing ancillary threats in places where connectivity is restricted to narrow strips of habitat, for example, narrow mountain passes or vegetated strips between solar development, could enhance the functionality of these vulnerable linkages. In such areas, maintaining multiple, redundant linkages could further enhance overall connectivity.
Minimization of mortality from roads and maximization of passage under roads. Roads pose a significant threat to the long-term persistence of local tortoise populations, and roads of high traffic volume lead to severe population declines, which ultimately fragments populations farther away from the roads. Three points (a.–c.) pertain to reducing direct mortality of tortoises on the many paved roads that cross desert tortoise habitat and to maintaining a minimal level of permeability across these roads:
Tortoise-exclusion fencing tied into culverts, underpasses, overpasses, or other passages below roads in desert tortoise habitat, would limit vehicular mortality of tortoises and provide opportunities for movement across the roads. Installation of shade structures on the habitat side of fences installed in areas with narrow population-depletion zones would limit overheating of tortoises that may pace the fence.
Passages below highways could be maintained or retrofitted to ensure safe tortoise access, for example, by filling eroded drop-offs or modifying erosion-control features such as rip-rap to make them safer and more passable for tortoises. Wildlife management agencies could work with transportation departments to develop construction standards that are consistent with hydrologic/erosion management goals, while also incorporating a design and materials consistent with tortoise survival and passage and make the standards widely available. The process would be most effective if the status of passages was regularly monitored and built into management plans.
Healthy tortoise populations along fenced highways could be supported by ensuring that land inside tortoise-exclusion fences is not so degraded that it leads to degradation of tortoise habitat outside the exclusion areas. For example, severe invasive plant infestations inside a highway exclusion could cause an increase of invasive plants outside the exclusion area and degrade habitat; therefore, invasive plants inside road rights of way could be mown or treated with herbicide to limit their spread into adjacent tortoise habitat and minimize the risk of these plants carrying wildfires into adjacent habitat.
Adaptation of management based on new information. Future research will continue to build upon and refine models related to desert tortoise population connectivity and develop new ones. New models could consider landscape levels of development and be constructed such that they share common foundations to support future synthesis efforts. If model development was undertaken in partnership with entities that are responsible for management of desert tortoise habitat, it would facilitate incorporation of current and future modeling results into their land management decisions. There are specific topics that may be clarified with further evaluation:
The effects of climate change on desert tortoise habitat, distribution, and population connectivity;
The effects of large-scale fires, especially within repeatedly burned habitat, on desert tortoise distribution and population connectivity;
The ability of solar energy facilities or similar developments to support tortoise movement and presence by leaving washes intact; leaving native vegetation intact whenever possible, or if not possible, mowing the site, allowing vegetation to re-sprout, and managing weeds; and allowing tortoises to occupy the sites; and
The design and frequency of underpasses necessary to maintain functional demographic and genetic connectivity across linear features, like highways.
Wildlife Program
Prepared in cooperation with the U.S. Fish and Wildlife Service
","usgsCitation":"Averill-Murray, R.C., Esque, T.C., Allison, L.J., Bassett, S., Carter, S.K., Dutcher, K.E., Hromada, S.J., Nussear, K.E., and Shoemaker, K., 2021, Connectivity of Mojave Desert tortoise populations—Management implications for maintaining a viable recovery network: U.S. Geological Survey Open-File Report 2021–1033, 23 p., https://doi.org/10.3133/ofr20211033.","productDescription":"vi, 23 p.","numberOfPages":"23","onlineOnly":"Y","ipdsId":"IP-125269","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":385161,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1033/covrthb.jpg"},{"id":385162,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1033/ofr20211033.pdf","text":"Report","size":"11 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":385163,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1033/images"},{"id":385164,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1033/ofr20211033.xml"}],"country":"United States","state":"Arizona, California, Nevada","otherGeospatial":"Mojave Desert","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.71923828124999,\n 33.669496972795535\n ],\n [\n -113.8623046875,\n 33.578014746143985\n ],\n [\n -112.69775390625,\n 33.50475906922609\n ],\n [\n -111.51123046875,\n 33.284619968887675\n ],\n [\n -111.73095703125,\n 34.10725639663118\n ],\n [\n -111.9287109375,\n 35.51434313431818\n ],\n [\n -113.00537109375,\n 36.24427318493909\n ],\n [\n -114.3896484375,\n 36.73888412439431\n ],\n [\n -115.86181640625001,\n 37.07271048132943\n ],\n [\n -117.42187500000001,\n 37.68382032669382\n ],\n [\n -118.27880859375001,\n 37.579412513438385\n ],\n [\n -117.7734375,\n 35.97800618085566\n ],\n [\n -117.72949218749999,\n 35.44277092585766\n ],\n [\n -118.76220703125001,\n 34.75966612466248\n ],\n [\n -117.99316406249999,\n 34.488447837809304\n ],\n [\n -116.74072265625,\n 34.288991865037524\n ],\n [\n -114.71923828124999,\n 33.669496972795535\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
Cheney Reservoir, in south-central Kansas, is the primary water supply for the city of Wichita, Kansas. The North Fork Ninnescah River is the largest tributary to Cheney Reservoir and contributes about 70 percent of the inflow. The U.S. Geological Survey, in cooperation with the City of Wichita, has been continuously monitoring water quality (including water temperature, specific conductance, pH, dissolved oxygen, and turbidity) on the North Fork Ninnescah River upstream from Cheney Reservoir (U.S. Geological Survey site 07144780) since November 1998. Continued data collection would be beneficial to update and describe changing water-quality conditions in the drainage basin and in the reservoir over time.
Regression models were developed to describe relations between discretely measured constituent concentrations and continuously measured physical properties. The models updated in this report include total suspended solids (TSS), suspended-sediment concentration (SSC), nitrate plus nitrite, nitrate, orthophosphate (OP), total phosphorus (TP), and total organic carbon (TOC).
Daily computed concentrations for TSS, TP, and nitrate plus nitrite during 1999–2019 were compared with Cheney Reservoir Task Force (CRTF) goals for base-flow and runoff conditions. CRTF goals for base-flow concentrations were exceeded more frequently (70 to 99.9 percent of the time) than runoff goals (0 to 11 percent of the time). Except for 2012, annual mean TSS concentrations exceeded the base-flow goal every year. Nitrate plus nitrite and TP annual mean concentrations exceeded the base-flow goals every year. TSS and nitrate plus nitrite annual mean concentrations during runoff conditions never exceeded the CRTF runoff goal. TP annual mean concentrations during runoff conditions only exceeded the CRTF runoff goal during 2002.
Sedimentation is progressively reducing the storage capacity of Cheney Reservoir. During 1999–2019, 55 percent of the computed suspended-sediment load was transported during the top 1 percent of loading days (76 days); 22 percent of the total load was transported in the top 10 loading days, indicating that substantial parts of suspended-sediment loads continue to be delivered during disproportionately small periods in Cheney Reservoir. Successful sediment management efforts necessitate reduction techniques that account for these large load events.
Flow-normalized concentrations and fluxes were computed during 1999 through 2019 using Weighted Regressions on Time, Discharge, and Season (WRTDS) statistical models and WRTDS bootstrap tests. Flow-normalized concentrations of TSS, SSC, OP, TP, and TOC had upward trend probabilities; conversely, nitrate plus nitrite had a downward trend. Flow-normalized fluxes for OP, TP, and TOC had an upward trend. No discernible patterns were identified for flow-normalized flux of TSS or suspended sediment. Nitrate plus nitrite flow-normalized flux indicated a downward trend.
Flow-normalized concentrations for TSS were less than the CRTF long-term goal of 100 milligrams per liter (mg/L), but the upward trend indicated the long-term goal may be exceeded if no changes are made. Flow-normalized TP concentrations exceeded the CRTF long-term goal (0.1 mg/L) and were assigned a very likely upward trend. Flow-normalized nitrate plus nitrite concentrations exceeded the CRTF long-term goal of 1.2 mg/L during the beginning of the study period, then were less than the CRTF goal for the remainder of the study; however, during 2010–19 flow-normalized concentrations increased by 6 percent.
Linking water-quality changes to causal factors requires consistent monitoring before, during, and after changes; this presents challenges related to length and frequency of data collection and available concomitant land-use and conservation practice data. As such, attribution of water-quality trends to land-use changes or conservation practices was not possible for this study because of a lack of land-use and conservation practice data. Additionally, because precipitation frequency and intensity are projected to continue to increase in the Great Plains region, accounting for extreme episodic events may be an important consideration in future sediment and nutrient load reduction plans.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215006","collaboration":"Prepared in cooperation with the City of Wichita","usgsCitation":"Kramer, A.R., Klager, B.J., Stone, M.L., and Eslick-Huff, P.J., 2021, Regression relations and long-term water-quality constituent concentrations, loads, yields, and trends in the North Fork Ninnescah River, south-central Kansas, 1999–2019: U.S. Geological Survey Scientific Investigations Report 2021–5006, 51 p., https://doi.org/10.3133/sir20215006.","productDescription":"Report: ix, 51 p.; Appendixes: 24; Dataset","numberOfPages":"66","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-118868","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":384937,"rank":3,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"U.S. Geological Survey National Water Information System database","description":"USGS Dataset","linkHelpText":"— USGS water data for the Nation"},{"id":384935,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5006/coverthb.jpg"},{"id":384936,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5006/sir20215006.pdf","text":"Report","size":"3.80 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5006"},{"id":384938,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5006/downloads/","text":"Appendixes 1–24","description":"SIR 2021–5006 Appendixes 1–24"}],"country":"United States","state":"Kansas","otherGeospatial":"North Fork Ninnescah River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -98.7176513671875,\n 37.60987994374712\n ],\n [\n -97.3663330078125,\n 37.60987994374712\n ],\n [\n -97.3663330078125,\n 38.238180119798635\n ],\n [\n -98.7176513671875,\n 38.238180119798635\n ],\n [\n -98.7176513671875,\n 37.60987994374712\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Kansas Water Science Center
1217 Biltmore Drive
Lawrence, KS 66049
The U.S. Geological Survey, in cooperation with the U.S. Fish and Wildlife Service (FWS), began a study in 2019 to complete the compilation and quality assurance of water-resource threats and needs data for the 117 National Wildlife Refuges (NWRs) in the FWS Legacy Mountain-Prairie Region (LMPR) and to characterize the water-resource threats and needs of each refuge and of the LMPR itself. The LMPR encompasses the states of Colorado, Kansas, Montana, Nebraska, North Dakota, South Dakota, Utah, and Wyoming. This report includes the compilation and quality assurance of current (April 2020) water-resource threats and needs data for the refuges in the LMPR and a statistical, graphical, and spatial characterization, including the ranking and prioritization of threat types, threat causes, and needs by the number of occurrences in the LMPR as a whole and by refuges, states, and select U.S. Environmental Protection Agency Level III Ecoregions.
A total of 540 unique threat occurrences were identified for 109 refuges in the LMPR. No threats were identified for eight refuges. About 43 percent of the threat occurrences, for 59 refuges, had a high-severity threat rating. Of the 10 most common threat types, 8 were also among the most common high-severity threat types. Water-resource threats had 72 different causes. About 83 percent of the overall common causes for threats and for high-severity threats were the same. The most common threat types overall and the most common high-severity threat types were compromised water management capability, habitat shifting/alteration, and altered flow regimes. The 20 water-resource threat types for Long Lake NWR were the most for refuges in the LMPR. Other refuges with the greatest number of threat types included Marais des Cygnes NWR (18) and Arapaho and Lee Metcalf NWRs (16 each). About 54 percent of refuges with threats had high-severity threats. Arapaho and Quivira NWRs each had 10 high-severity threat types, the maximum number of high-severity threat types for LMPR refuges.
A total of 637 unique need occurrences were identified for 114 refuges. No needs were reported for three refuges. The most common need type, a Water Resource Inventory and Assessment, was reported for 78 refuges. Two of the most common need types, repair and replace water management infrastructure and water supply/quantity monitoring, were the most common high-priority need types. Bear River Migratory Bird Refuge had the most (39) unique water-resource need types for refuges in the LMPR. Other refuges with the greatest number of need types were Baca (38), Alamosa (36), and Monte Vista (36) NWRs. The most high-priority need types for a refuge was 23, at Monte Vista NWR. Alamosa (22), Baca (22), and Lake Andes (19) NWRs were also among the top 4 refuges with the greatest number of high-priority need types.
An overall ranking scheme was developed to identify refuges that have the highest-ranking priority for conservation efforts to fulfill refuges’ statutory purposes. The count of occurrences of high-severity threats and high-priority needs were summed to determine the overall ranking value for a refuge. The 10 refuges with the highest overall ranking values, in order of ranking from higher to lower, were Alamosa, Baca, and Monte Vista NWRs (tied for highest); Lake Andes NWR, Ouray and Quivira NWRs, Bear River Migratory Bird Refuge and Flint Hills NWR, Cokeville Meadows NWR, and Arapaho NWR.
About 33 percent of overall threat occurrences were reported as under the control of the FWS to mitigate, as were 37 percent of all threat occurrences with a high-severity rating. The most common overall threat types and high-severity threat types under FWS control were compromised water management capability; habitat shifting/alteration; altered flow regimes; loss/alteration of wetland habitat; and legal challenges or fines for non-compliance with water policy, law, or regulation. A total of 68 percent of overall need occurrences and 67 percent of all high-priority need occurrences were under the control of the FWS. The most common overall need types and high-priority needs types under control were repair or replace water management infrastructure, water supply/quantity monitoring, water quality baseline monitoring, and protect habitat from invasive species. A Water Resource Inventory and Assessment was also a common overall need under FWS control, as was the high-priority need of water level monitoring.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/ofr20211007","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Bauch, N.J., Kohn, M.S., and Caruso, B.S., 2021, Characterization of water-resource threats and needs for U.S. Fish and Wildlife Service National Wildlife Refuges in the Legacy Mountain-Prairie Region, 2020: U.S. Geological Survey Open-File Report 2021–1007, 46 p., https://doi.org/10.3133/ofr20211007.","productDescription":"viii, 46 p.","onlineOnly":"Y","ipdsId":"IP-119415","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":384940,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1007/coverthb.jpg"},{"id":384941,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1007/ofr20211007.pdf","text":"Report","size":"9.45 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1007"}],"country":"United States","state":"Colorado, Kansas, Montana, Nebraska, North Dakota, South Dakota, Utah, Wyoming","otherGeospatial":"Legacy Mountain Prairie Region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.0283203125,\n 36.96744946416934\n ],\n [\n -94.63623046875,\n 37.00255267215955\n ],\n [\n -94.63623046875,\n 39.095962936305476\n ],\n [\n -95.00976562499999,\n 39.62261494094297\n ],\n [\n -94.81201171875,\n 39.85915479295669\n ],\n [\n -95.64697265625,\n 40.51379915504413\n ],\n [\n -96.1083984375,\n 41.60722821271717\n ],\n [\n -96.6357421875,\n 42.66628070564928\n ],\n [\n -96.50390625,\n 43.48481212891603\n ],\n [\n -96.416015625,\n 45.36758436884978\n ],\n [\n -96.85546875,\n 45.61403741135093\n ],\n [\n -96.52587890625,\n 45.9511496866914\n ],\n [\n -96.85546875,\n 46.81509864599243\n ],\n [\n -96.85546875,\n 47.62097541515849\n ],\n [\n -97.20703125,\n 48.1367666796927\n ],\n [\n -97.20703125,\n 48.99463598353405\n ],\n [\n -116.01562499999999,\n 49.03786794532644\n ],\n [\n -116.08154296875001,\n 48.004625021133904\n ],\n [\n -115.4443359375,\n 47.27922900257082\n ],\n [\n -114.36767578124999,\n 46.51351558059737\n ],\n [\n -114.521484375,\n 45.66012730272194\n ],\n [\n -114.14794921875,\n 45.521743896993634\n ],\n [\n -113.99414062499999,\n 45.61403741135093\n ],\n [\n -113.48876953125,\n 44.94924926661153\n ],\n [\n -112.69775390625,\n 44.38669150215206\n ],\n [\n -111.26953125,\n 44.69989765840318\n ],\n [\n -111.11572265625,\n 44.574817404670306\n ],\n [\n -111.0498046875,\n 41.983994270935625\n ],\n [\n -114.01611328125,\n 42.00032514831621\n ],\n [\n -114.06005859375,\n 36.94989178681327\n ],\n [\n -109.0283203125,\n 36.96744946416934\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Colorado Water Science Center
U.S. Geological Survey
Box 25046, MS 415
Denver, CO 80225
Emergent late Pliocene and Pleistocene shoreline deposits, morphologically identifiable Pleistocene shoreline units, and seaward-facing scarps characterize the easternmost Atlantic Coastal Plain (ACP) of the United States of America. In some areas of the ACP, these deposits, units, and scarps have been studied in detail. Within these areas, temporal and spatial data are sufficient for time-depositional frameworks for shoreline-evolution to have been developed and published. For other areas, such as the southeastern Atlantic Coastal Plain (SEACP), available data are conflicting and (or) insufficient to develop such a framework, or to make shoreline correlations. Differential epeirogenic uplift and shoreline deformation, resulting from mantle-flow and climate-induced isostatic adjustments, complicate regional shoreline correlations. In the SEACP, the topographically prominent Orangeburg Scarp (hereafter, the Scarp) rises tens of meters in elevation from southeastern Georgia to southeastern North Carolina. The degree to which the Scarp and shoreline units seaward of the Scarp are deformed continues to be debated, but there is general agreement that the lower Savannah River area (LSRA) of Georgia and South Carolina is the least deformed area of the SEACP.
This paper synthesizes published and previously unpublished numerical age and stratigraphic data for emergent Pliocene and younger shoreline deposits in the LSRA in Georgia. Age data are applied to these shoreline deposits as they are delineated (map units) on the 1976 geologic map of Georgia by Lawton and others. Age assignments are based on stratigraphic position, fossil content, soil and weathering diagnostic properties, and numerical ages as determined by meteoric Beryllium‑10 paleosol residence time (10BePRT), optically stimulated luminescence (OSL), uranium disequilibrium series (U-series), amino acid racemization (AAR), and radiocarbon (14C) analyses. These data provide a preliminary Pliocene-Pleistocene geochronology for the Orangeburg Scarp and shoreline deposits seaward of the Scarp in the LSRA of Georgia. Minimum ages and age ranges indicate the following:
Director, Florence Bascom Geoscience Center
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 21092
Precipitation events in urban areas often result in stormwater runoff containing a diverse array of chemical contaminants. Although many traditional contaminants, such as nutrients, heavy metals, and polycyclic aromatic hydrocarbons have been studied extensively, only recently has evidence emerged showing that trace organic compounds (TrOCs), including pharmaceuticals, personal care products and pesticides are frequently found in stormwater runoff. As there is little existing information about the sources of TrOCs in urban stormwater or their removal efficacy across a range of stormwater treatment options, we conducted a study to address these knowledge gaps and to characterize the potential contribution of TrOCs to groundwater resources from stormwater infiltration practices, based on several synoptic measurements. The current study allowed us to enhance an existing effort to assess TrOC presence and toxicity in stormwater runoff and treatment pond outflow by addressing questions related to TrOC sources to stormwater and TrOC transport to groundwaters.
Analysis of eDNA confirms multiple sources of TrOCs to stormwater including human sewage, dog waste, and feces from waterfowl. It is likely that the presence of some TrOCs detected in stormwater are the result of direct, untreated sewage inputs to stormwater from either human (i.e., leaking sewer infrastructure) or pet waste (washed from sidewalks into storm drains). The seasonal detection of avian eDNA is noteworthy as it highlights seasonality and patterns of migration patterns as contributing factors to stormwater contamination. In contrast to human and pet waste, which likely enters stormwater ponds via the stormwater conveyance system, avian feces may enter ponds either through stormwater runoff or through direct inputs by waterfowl stopping-over temporarily at stormwater ponds. Stormwater ponds had little effect in reducing TrOCs as determined by comparative inflow and outflow analysis. Our results also indicate that overall few TrOCs were present in receiving groundwater adjacent to underground infiltration basins, compared to inflow. However, some contaminants were present at relatively high concentrations compared to stormwater flowing into the basins. This is particularly true for pesticides and their degradants. Fewer TrOCs were detected in interstitial water collected near stormwater ponds compared to inflow and outflow. The presence and concentrations of TrOCs in outflow from ponds was generally similar to or higher than what was observed in inflow.
The data collected as part of this study can be used to guide future research or monitoring in an effort to better understand TrOC fate and transport in the environment via stormwater BMPs. Specifically, more work is needed to track parcels of water as they flow through BMPs to better quantify transport and degradation of TrOCs, monitor flow into and out of ponds for mass balance calculations, and conduct tracer tests to better quantify the amount of water that monitoring wells are intercepting from underground infiltration basins.
These results have been shared in multiple presentations and in meetings with high school teachers to develop age-appropriate curriculum to highlight the role of individuals in reducing and preventing stormwater contamination. The ongoing pandemic hindered some of these efforts (cancelled conferences; suspended MN Water Roundtable meetings; pre-occupation with teachers moving materials online), however, as dissemination activities become more common in the near future, we will continue to educate stakeholders and educators about the root causes and effects of urban stormwater contamination.
","language":"English","publisher":"University of Minnesota","usgsCitation":"Schoenfuss, H.L., Kiesling, R.L., Elliott, S.M., and Kohno, S., 2021, Identifying sources of contaminants in urban stormwater and evaluation of their removal efficacy across a continuum of urban best management practices: Final Report, 46 p.","productDescription":"46 p.","ipdsId":"IP-127948","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":387866,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":387830,"type":{"id":15,"text":"Index Page"},"url":"https://www.wrc.umn.edu/sites/wrc.umn.edu/files/identifying_sources_of_contaminants_scsu_usgs_final_report_march_2021.pdf"}],"country":"United States","state":"Minnesota","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.44970703125,\n 44.95265089681472\n ],\n [\n -93.01162719726562,\n 44.95265089681472\n ],\n [\n -93.01162719726562,\n 45.22364447346731\n ],\n [\n -93.44970703125,\n 45.22364447346731\n ],\n [\n -93.44970703125,\n 44.95265089681472\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Schoenfuss, Heiko L.","contributorId":76409,"corporation":false,"usgs":false,"family":"Schoenfuss","given":"Heiko","email":"","middleInitial":"L.","affiliations":[{"id":13317,"text":"Saint Cloud State University","active":true,"usgs":false}],"preferred":false,"id":821064,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kiesling, Richard L. 0000-0002-3017-1826 kiesling@usgs.gov","orcid":"https://orcid.org/0000-0002-3017-1826","contributorId":1837,"corporation":false,"usgs":true,"family":"Kiesling","given":"Richard","email":"kiesling@usgs.gov","middleInitial":"L.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":821065,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Elliott, Sarah M. 0000-0002-1414-3024 selliott@usgs.gov","orcid":"https://orcid.org/0000-0002-1414-3024","contributorId":1472,"corporation":false,"usgs":true,"family":"Elliott","given":"Sarah","email":"selliott@usgs.gov","middleInitial":"M.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":821009,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kohno, Satomi","contributorId":264174,"corporation":false,"usgs":false,"family":"Kohno","given":"Satomi","email":"","affiliations":[],"preferred":false,"id":821066,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70219172,"text":"ds1136 - 2021 - Groundwater-quality and select quality-control data from the National Water-Quality Assessment Project, January 2017 through December 2019","interactions":[],"lastModifiedDate":"2021-03-30T11:57:07.918866","indexId":"ds1136","displayToPublicDate":"2021-03-29T17:42:50","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"1136","displayTitle":"Groundwater-Quality and Select Quality-Control Data from the National Water-Quality Assessment Project, January 2017 through December 2019","title":"Groundwater-quality and select quality-control data from the National Water-Quality Assessment Project, January 2017 through December 2019","docAbstract":"Groundwater-quality environmental data were collected from 983 wells as part of the National Water-Quality Assessment Project of the U.S. Geological Survey National Water Quality Program and are included in this report. The data were collected from six types of well networks: principal aquifer study networks, which are used to assess the quality of groundwater used for public water supply; land-use study networks, which are used to assess land-use effects on shallow groundwater quality; major aquifer study networks, which are used to assess the quality of groundwater used for domestic supply; enhanced trends networks, which are used to evaluate the time scales during which groundwater quality changes; vertical flow-path study networks, which are used to evaluate changes in groundwater quality from shallow to deeper depths; and modeling support studies, which are used to provide data to support groundwater modeling. Groundwater samples were analyzed for many water-quality indicators and constituents, including major ions, nutrients, trace elements, volatile organic compounds, pesticides, radionuclides, microbiological indicators, and some constituents of special interest (arsenic speciation, hexavalent chromium [chromium (VI)], and perchlorate). These groundwater-quality data, along with data from quality-control samples, are tabulated in this report and in an associated data release. Data for microbiological indicators for samples collected in 2016 are included in the companion data release.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1136","collaboration":"National Water-Quality Assessment Project","usgsCitation":"Kingsbury, J.A., Bexfield, L.M., Arnold, T., Musgrove, M., Erickson, M.L., Degnan, J.R., Tesoriero, A.J., Lindsey, B.D., and Belitz, K., 2021, Groundwater-quality and select quality-control data from the National Water-Quality Assessment Project, January 2017 through December 2019: U.S. Geological Survey Data Series 1136, 97 p., https://doi.org/10.3133/ds1136.","productDescription":"Report: x, 97 p.; 2 Appendixes; Data Release; Dataset","numberOfPages":"112","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-118835","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true},{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":583,"text":"Texas Water Science 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U.S. Geological Survey
640 Grassmere Park Drive
Nashville, TN 37211
The U.S. Geological Survey, Cape Cod National Seashore of the National Park Service, and Friends of Herring River cooperated from 2015 to 2017 to assess nutrient concentrations and fluxes across the ocean-estuary boundary at a dike on the Herring River in Wellfleet, Massachusetts. The purpose of this assessment was to characterize environmental conditions prior to a future removal of the dike, which has restricted saltwater inputs into the Herring River watershed for more than 100 years. Water temperature, dissolved oxygen, pH, and specific conductance were monitored continuously, and flow-weighted composite samples were collected approximately twice per month at the ocean-estuary boundary. Bidirectional discharge was computed for the U.S. Geological Survey Herring River at Chequessett Neck Road at Wellfleet, Massachusetts, streamgage (011058798) by using a stage-area rating and index-velocity ratings developed with acoustic Doppler current profile measurements made upstream and downstream from the dike. LOADEST regression modeling software was used to estimate nutrient fluxes (loads) from composite, paired nutrient concentration and discharge data in conjunction with continuous discharge data. Temperature, dissolved oxygen, pH, and specific conductance were also monitored continuously on two tributaries to the Herring River, Pole Dike Creek and Bound Brook, from late-May 2016 to mid-June 2017. Composite or discrete water samples were collected from the tributaries approximately twice per month in most months from late-May 2016 to mid-June 2017 and analyzed for total nitrogen, total phosphorus, and dissolved organic carbon.
Flow-weighted concentrations of ammonium, nitrate, and total nitrogen on the Herring River at the dike on the ebb tide generally varied between 0.01 and 0.1, 0.003 and 0.03, and 0.3 and 0.7 milligram per liter as nitrogen, respectively. Flow-weighted concentrations of orthophosphate, total dissolved phosphorus, and total phosphorus generally varied between 0.002 and 0.02, 0.003 and 0.06, and 0.03 and 0.1 milligram per liter as phosphorus, respectively, on the ebb tide. Flow-weighted concentrations of silicate and dissolved organic carbon on the ebb tide generally varied between 0.08 and 3.0 milligrams per liter of silica (silicon dioxide), and 1.7 and 5.6 milligrams per liter of carbon, respectively. Ebb tide concentrations of nitrate were highest in winter and lowest in summer. By contrast, ebb tide concentrations of phosphorus species were highest in late summer and early fall and lowest in winter. Silica and dissolved organic carbon did not exhibit systematic variation in seasonal concentrations. There was uncertainty in estimates of nutrient fluxes, but the LOADEST-estimated fluxes indicated that annual (and in almost all cases seasonal) exports (ebb tides) exceeded inputs (flood tides). Ebb tide concentrations of ammonium, nitrate, total nitrogen, and silica were positively correlated with antecedent cumulative 7-day precipitation.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205120","collaboration":"Prepared in cooperation with the National Park Service and Friends of Herring River","usgsCitation":"Huntington, T.G., Spaetzel, A.B., Colman, J.A., Kroeger, K.D., and Bradley, R.T., 2021, Assessment of water quality and discharge in the Herring River, Wellfleet, Massachusetts, November 2015 to September 2017: U.S. Geological Survey Scientific Investigations Report 2020–5120, 59 p., https://doi.org/10.3133/sir20205120.","productDescription":"Report: x, 59 p.; Data Release","numberOfPages":"59","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-106718","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":384601,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5120/coverthb.jpg"},{"id":384603,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9BKW4BX","text":"USGS data release","linkHelpText":"Tidal daily discharge and quality assurance data supporting an assessment of water quality and discharge in the Herring River, Wellfleet, Massachusetts, November 2015–September 2017"},{"id":384602,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5120/sir20205120.pdf","text":"Report","size":"3.78 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5120"}],"country":"United States","state":"Massachusetts","city":"Wellfleet","otherGeospatial":"Herring River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -70.07801055908203,\n 41.93318868195924\n ],\n [\n -69.99870300292969,\n 41.93318868195924\n ],\n [\n -69.99870300292969,\n 41.98833256890643\n ],\n [\n -70.07801055908203,\n 41.98833256890643\n ],\n [\n -70.07801055908203,\n 41.93318868195924\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
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The Navajo (N) aquifer is the primary source of groundwater in the 5,400-square-mile Black Mesa area in northeastern Arizona. Availability of water is an important issue in the Black Mesa area because of continued water requirements for industrial and municipal use by a growing population and because of its arid climate. Precipitation in the area typically ranges from less than 6 to more than 16 inches per year depending on location.
The U.S. Geological Survey water-monitoring program in the Black Mesa area began in 1971 and provides information about the long-term effects of groundwater withdrawals from the N aquifer for industrial and municipal uses. This report presents results of data collected as part of the monitoring program in the Black Mesa area from November 2016 to December 2018. The monitoring program includes measurements of (1) groundwater withdrawals (pumping), (2) groundwater levels, (3) spring discharge, (4) surface-water discharge, and (5) groundwater and surface-water chemistry.
In calendar year 2017, total groundwater withdrawals were 3,710 acre-feet (acre-ft), industrial withdrawals were 1,110 acre-ft, and municipal withdrawals were 2,600 acre-ft. In calendar year 2018, total groundwater withdrawals were 3,670 acre-ft, industrial withdrawals were 1,170 acre-ft, and municipal withdrawals were 2,500 acre-ft. Total withdrawals during 2017 and 2018 were about 49 percent less than total withdrawals in 2005 because of Peabody Western Coal Company’s discontinued use of water to transport coal in a coal slurry pipeline.
From the prestress period (prior to 1965) to 2018, measured water levels available for comparison in wells completed in the unconfined areas of the N aquifer within the Black Mesa area declined in 8 of 14 wells, the changes ranged from +12.1 feet to −39.4 feet, and the median change was -0.6 feet. Water levels also declined in 15 of 18 wells measured in the confined area of the aquifer. The median change for the confined area of the aquifer was −40.2 feet (ft), with changes ranging from +14.2 ft to −189.0 ft. From the prestress period to 2018, the median water-level change for all 32 wells in both the confined and unconfined areas was −9.4 ft.
Spring flow was measured at four springs in 2017 and 2018. Flow fluctuated during the period of record for Burro Spring and Pasture Canyon Spring, but a decreasing trend was statistically significant (p<0.05) at Moenkopi School Spring and Unnamed Spring near Dennehotso. Discharge at Burro Spring has remained relatively constant since it was first measured in the 1980s and discharge at Pasture Canyon Spring has fluctuated for the period of record.
Continuous records of surface-water discharge in the Black Mesa area were collected from streamflow-gaging stations at the following sites: Moenkopi Wash at Moenkopi 09401260 (1976 to 2018), Dinnebito Wash near Sand Springs 09401110 (1993 to 2018), Polacca Wash near Second Mesa 09400568 (1994 to 2018), and Pasture Canyon Springs 09401265 (2004 to 2018). Median winter flows (November through February) of each water year were used as an index of the amount of groundwater discharge at the above-named sites. For the period of record, the median winter flows have generally remained constant at Dinnebito Wash and Polacca Wash, whereas a decreasing trend was indicated at Moenkopi Wash and Pasture Canyon Springs.
In 2017 and 2018, water samples collected from two wells, four springs, and three streams in the Black Mesa area were analyzed for selected chemical constituents. The results from wells and springs were compared with previous analyses from the same wells and springs. At the Peabody 2 well, a significant (p<0.05) decreasing trend in dissolved solids over time was found, while concentrations of dissolved solids have not varied significantly (p>0.05) at the Kykotsmovi PM2 well. Dissolved solids, chloride, and sulfate concentrations increased at Moenkopi School Spring during the more than 30 years of record at that site. Concentrations of dissolved solids, chloride, and sulfate at Pasture Canyon Spring have not varied significantly (p>0.05) since the early 1980s, and there is no increasing or decreasing trend in those data. Concentrations of dissolved solids, chloride, and sulfate at Burro Spring and Unnamed Spring near Dennehotso have varied for the period of record, but there is no statistical trend in the data. Baseflow water chemistry samples were collected from Moenkopi, Dinnebito, and Polacca washes in 2017. Samples from all three washes had total-dissolved solids concentrations higher than is typically found in the N aquifer water.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211124","collaboration":"Prepared in cooperation with the Navajo Nation and Peabody Western Coal Company","usgsCitation":"Mason, J.P., 2021, Groundwater, surface-water, and water-chemistry data, Black Mesa area, northeastern Arizona—2016–2018: U.S. Geological Survey Open-File Report 2021–1124, 50 p., https://doi.org/10.3133/ofr20211124.","productDescription":"vii, 50 p.","numberOfPages":"50","onlineOnly":"Y","ipdsId":"IP-110021","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":384543,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20181193","text":"Open-File Report 2018-1193","linkHelpText":"- Groundwater, Surface-Water, and Water-Chemistry Data, Black Mesa Area, Northeastern Arizona—2015–2016"},{"id":384455,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1124/ofr20211124.pdf","text":"Report","size":"8 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":384454,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1124/covrthb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Black Mesa area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.76391601562499,\n 35.32633026307483\n ],\n [\n -109.171142578125,\n 35.32633026307483\n ],\n [\n -109.171142578125,\n 36.99377838872517\n ],\n [\n -111.76391601562499,\n 36.99377838872517\n ],\n [\n -111.76391601562499,\n 35.32633026307483\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Arizona Water Science Center
U.S. Geological Survey
520 N. Park Avenue
Tucson, AZ 85719
Data collection, along with hydraulic and fluvial egg transport modeling, was completed along a 70.9-mile reach of the Ohio River between Markland Locks and Dam and McAlpine Locks and Dam in Kentucky and Indiana. Water-quality data collected in this reach included surface measurements and vertical profiles of water temperature, specific conductance, pH, dissolved oxygen, turbidity, relative chlorophyll, and relative phycocyanin. Data were collected during two surveys: October 27–November 4, 2016, and June 26–29, 2017. Streamflow and velocity data were collected simultaneously with the water-quality data at cross sections and along longitudinal lines (corresponding to the water-quality surface measurements) and at selected stationary locations (corresponding to the water-quality vertical profiles). The data were collected to understand variability of flow and water-quality conditions relative to simulated reaches of the Ohio River and to aid in identifying parts of the reach that may provide conditions favorable to spawning and recruitment habitat for Hypophthalmichthys nobilis (bighead carp).
A copy of an existing step-backwater model of Ohio River flows was obtained from the National Weather Service and used to simulate hydraulic conditions for four different streamflows. Streamflows were selected to represent typical conditions ranging from a high-streamflow event to a seasonal dry-weather event, with two streamflows between these extremes for this reach of the Ohio River. Outputs from the hydraulic model, a range of five water temperatures observed in water-quality data, and four potential spawning locations were used as input to the Fluvial Egg Drift Simulator to simulate the extents and quantile positions of developing bighead carp, from egg hatching to the gas bladder inflation stage, under each scenario. A total of 80 simulations were run.
Results from the Fluvial Egg Drift Simulator scenarios (which include only the hydraulic influences on survival that result from settling, irrespective of mortality from other physical or biological factors such as excess turbulence, fertilization failure, predation, or starvation) indicate that most eggs will hatch, about half will die, and a quarter of the surviving larvae will reach the gas bladder inflation stage within the model reach. The overall mean percentage of embryos surviving to the gas bladder inflation stage was 13.1 percent. Individual simulations have embryo survival percentages as high as 49.1 percent. The highest embryo survival percentages occurred for eggs spawned at a streamflow of 38,100 cubic feet per second and water temperatures of 24 to 30 degrees Celsius. Conversely, embryo survival percentages were lowest for the lowest and highest streamflows regardless of water temperature or spawn location. Under low water temperature and high-streamflow conditions, some of the eggs did not hatch nor did the larvae reach the gas bladder inflation stage until passing beyond the downstream model domain. Although the final quantile positions of the eggs and larvae beyond the downstream model domain are unknown, the outcomes still provide useful information about conditions favorable to spawning and recruitment habitat for bighead carp in the Ohio River.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215005","collaboration":"Biological Threats and Invasive Species Research Program","usgsCitation":"Ostheimer, C.J., Boldt, J.A., and Buszka, P.M., 2021, Supporting data and simulation of hypothetical bighead carp egg and larvae development and transport in the Ohio River between Markland Locks and Dam and McAlpine Locks and Dam, Kentucky and Indiana, by use of the Fluvial Egg Drift Simulator: U.S. Geological Survey Scientific Investigations Report 2021–5005, 30 p., https://doi.org/10.3133/sir20215005.","productDescription":"Report: v, 30 p.; 2 Data Releases","numberOfPages":"38","onlineOnly":"Y","ipdsId":"IP-116266","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":384390,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5005/coverthb.jpg"},{"id":384391,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5005/sir20215005.pdf","text":"Report","size":"10.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5005"},{"id":384392,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9MQHEPU","text":"USGS data release","linkHelpText":"Velocity and water-quality surveys in the Ohio River between Markland Locks and Dam and McAlpine Locks and Dam, Kentucky and Indiana, October 27–November 4, 2016, and June 26–29, 2017"},{"id":384393,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9JHLGZL","text":"USGS data release","linkHelpText":"Geospatial data and models for the simulation of hypothetical bighead carp egg and larvae development and transport in the Ohio River between Markland Locks and Dam and McAlpine Locks and Dam, Kentucky and Indiana, by use of the Fluvial Egg Drift Simulator"}],"country":"United States","state":"Indiana, Kentucky","otherGeospatial":"Ohio River, Markland Locks and Dam, McAlpine Locks and Dam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -85.660400390625,\n 38.40194908237822\n ],\n [\n -84.935302734375,\n 38.40194908237822\n ],\n [\n -84.935302734375,\n 38.85682013474361\n ],\n [\n -85.660400390625,\n 38.85682013474361\n ],\n [\n -85.660400390625,\n 38.40194908237822\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Ohio-Kentucky-Indiana Water Science Center
U.S. Geological Survey
6460 Busch Blvd., Suite 100
Columbus, OH 43229–1737
Crex Meadows Wildlife Area (Crex) is a 30,000-acre property in Burnett County, Wisconsin. Crex is managed by the Wisconsin Department of Natural Resources (WDNR) with the goal of providing public recreation opportunities while also protecting the quality of native ecological communities and species on the property. The WDNR’s management strategy includes controlling water levels at flowages in Crex using a system of dikes, water control structures, ditches, and a diversion pump. For the past several decades there has been concern among nearby landowners that the water manage-ment strategy at Crex may be contributing to groundwater flooding in adjacent, privately held properties. This issue has been particularly contentious during periods when regional groundwater elevations are already high. This study was conducted in response to those concerns. For the study, a network of 12 monitoring wells was installed in and to the west of Crex. Groundwater elevations were recorded in the wells before, during, and after water-level changes in the western Crex flowages to assess if groundwater elevations to the west of Crex are detectably affected by the flowage water levels.
This study successfully collected groundwater elevations in 11 study wells during a 3-month period in 2019 when water elevations in the Dike 6 flowage and Erickson flowage were lowered and then raised. The data logger at a 12th location failed and no data were recorded. The groundwater elevation trends in these study wells were compared with groundwater elevation trends at a regional U.S. Geological Survey well to provide information for determining if changing the flowage elevations had a noticeable response in the study wells west of Crex Meadows. This analysis was done by (1) evaluating study well groundwater elevation trends compared to the regional well, (2) using a scatter plot of study well and regional well data during raising and lowering periods,
(3) assessing horizontal hydraulic gradient data during the study period, and (4) assessing the cumulative departure from the mean groundwater elevation for each well.
Overall, regional groundwater elevations had a down-ward trend before and during the flowage lowering period and then had an upward trend during the flowage raising period. This pattern was observed in the regional well and in all the study wells adjacent to and several miles from the flowages. The similarity in patterns indicates that precipitation and regional groundwater flow conditions were the dominant drivers of the system during the study period. The scatter plot and cumulative departure from the mean analysis showed that in addition to regional trends, wells 1, 6, and 7 were likely affected by the changes in the flowage water levels. Overall, at least on the timescale of this study, water management at Crex likely did not have detectable effects on wells outside the Crex property. Wells installed on the Crex property including the wells in the lakebeds of the flowages (wells 1 and 7) and possibly well 6 east of the flowages showed what seems to be minor affects due to water management at Crex.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205149","collaboration":"Prepared in cooperation with the Wisconsin Department of Natural Resources","usgsCitation":"Haserodt, M.J., and Fienen, M.N., 2020, Assessment of groundwater trends near Crex Meadows, Wisconsin: U.S. Geological Survey Scientific Investigations Report 2020–5149, 32 p., https://doi.org/10.3133/sir20205149.","productDescription":"vi, 36 p.","numberOfPages":"46","onlineOnly":"Y","ipdsId":"IP-117629","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":385958,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2020/5149/versionHist.txt","text":"Version History","size":"1.69 kB","linkFileType":{"id":2,"text":"txt"},"description":"SIR 2020–5149 Version History"},{"id":385957,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5149/sir20205149.pdf","text":"Report","size":"13.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5149"},{"id":384275,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5149/coverthb3.jpg"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Crex Meadows","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.51930236816406,\n 45.81540082150529\n ],\n [\n -92.51861572265625,\n 45.829756159282766\n ],\n [\n -92.51861572265625,\n 45.84506443975059\n ],\n [\n -92.52616882324219,\n 45.84506443975059\n ],\n [\n -92.52754211425781,\n 45.87853662114514\n ],\n [\n -92.55226135253906,\n 45.882360730184025\n ],\n [\n -92.55088806152344,\n 45.90768880475299\n ],\n [\n -92.60856628417967,\n 45.90386643939614\n ],\n [\n -92.67105102539061,\n 45.897654534346906\n ],\n [\n -92.68272399902344,\n 45.88618457602257\n ],\n [\n -92.68135070800781,\n 45.867062714815475\n ],\n [\n -92.69096374511719,\n 45.817315080406246\n ],\n [\n -92.691650390625,\n 45.80008438131991\n ],\n [\n -92.68753051757812,\n 45.79338211440398\n ],\n [\n -92.64770507812499,\n 45.79338211440398\n ],\n [\n -92.61543273925781,\n 45.813965084145295\n ],\n [\n -92.57972717285156,\n 45.817315080406246\n ],\n [\n -92.57492065429688,\n 45.82688538784564\n ],\n [\n -92.54539489746094,\n 45.82640691154487\n ],\n [\n -92.54539489746094,\n 45.81109349837976\n ],\n [\n -92.51930236816406,\n 45.81540082150529\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: March 15, 2021; Version 1.1: May 26, 2021","contact":"Director, Upper Midwest Water Science Center
U.S. Geological Survey
8505 Research Way
Middleton, WI 53562
The Osage Nation of northeastern Oklahoma, conterminous with Osage County, covers about 2,900 square miles. The area is primarily rural with 62 percent of the land being native prairie grass, and much of the area is used for cattle ranching and extraction of petroleum and natural gas. Protection of water rights are important to the Osage Nation because of its reliance on cattle ranching and the potential for impairment of water quality by petroleum extraction. Additionally, the potential for future population increases, demands for water from neighboring areas such as the Tulsa metropolitan area, and expansion of petroleum and natural-gas extraction on water resources of this area further the need for the Osage Nation to better understand its water availability. Therefore, the U.S. Geological Survey, in cooperation with the Osage Nation, completed a hydrologic investigation to assess the status and availability of surface-water and groundwater resources in the Osage Nation.
A transient integrated hydrologic-flow model was constructed using the U.S. Geological Survey fully integrated hydrologic-flow model called the MODFLOW One-Water Hydrologic Model. The integrated hydrologic-flow model, called the Osage Nation Integrated Hydrologic Model (ONIHM), was constructed and uses an orthogonal grid of 276 rows and 289 columns, and each grid cell measures 1,312.34 feet (ft; 400 meters) per side, with eight variably thick vertical layers that represented the alluvial and bedrock aquifers within the study area, including the alluvial aquifer, the Vamoosa-Ada aquifer, and the minor Pennsylvanian bedrock aquifers, and the confining units. Landscape and groundwater-flow processes were simulated for two periods: (1) the 1950–2014 period from January 1950 through September 2014 and (2) the forecast period from October 2014 through December 2099. The 1950–2014 period ONIHM simulated past conditions using measured or estimated inputs, and the forecast-period ONIHM simulated three separate potential forecast conditions under constant dry, average, or wet climate conditions using calibrated input values from the 1950–2014 period ONIHM.
The 1950–2014 period ONIHM was calibrated by linking the Parameter Estimation software (PEST) with the MODFLOW One-Water Hydrologic Model. PEST uses statistical parameter estimation techniques to identify the best set of parameter values to minimize the difference between measured or estimated calibration targets and their simulated equivalent values (residuals). Tikhonov regularization and singular-value decomposition-assist features of PEST were used during the calibration process. The 1950–2014 period ONIHM was calibrated to 713 measured groundwater levels at 195 wells; 95,636 estimated monthly mean groundwater levels at 124 wells; 5,307 measured streamflows at 13 streamgages; and 8,679 simulated mean monthly streamflows at 10 streamgages extracted from a surface-water model by adjusting 231 parameters. The estimated groundwater-level observations and streamflows were included as observations to improve the spatial and temporal density of observation targets during calibration. The best set of parameter values obtained during the calibration process of the 1950–2014 model was then used as the input parameter values for the forecast model simulations. A comparison of the calibration targets to their corresponding simulated values indicated that the model adequately reproduced streamflows and groundwater levels for some streamgages and wells and underestimated streamflows and groundwater levels at other locations. Measured and simulated streamflows correlated adequately with a coefficient of determination of 0.938, as did water levels with a coefficient of determination of 0.795. The 1950–2014 period ONIHM underestimated certain groundwater levels and streamflows, but generally measured or estimated calibration targets correlated well with simulated equivalents, which indicated that the model can adequately simulate the response of the hydrologic system to stresses in the 1950–2014 and forecast periods.
In the 1950–2014 period ONIHM, the calibrated mean horizontal hydraulic conductivity for layer 1 alluvial aquifer was 30.7 feet per day, and the seven lower layers had a calibrated mean horizontal hydraulic conductivity of less than 3.3 feet per day. The mean calibrated groundwater-level residual was 16.6 ft, and the mean calibrated streamflow residual of the Arkansas River at Ralston, Oklahoma, streamgage (U.S. Geological Survey station 07152500) was within 6 percent (373 cubic feet per second) of mean measured streamflow for the 1950–2014 period ONIHM.
The ONIHM simulated landscape fluxes of precipitation; groundwater applied by irrigation wells; evapotranspiration from precipitation, groundwater, and irrigation; runoff from precipitation; and deep percolation from precipitation. The largest loss of water from the landscape was evapotranspiration from precipitation with a calibrated mean annual outflow of 32 inches (in.): mean annual precipitation was about 36 in. Calibrated mean annual runoff and deep percolation (recharge to the water table) rates were 4.7 inches per year (in/yr) and 0.70 in/yr, respectively, for the 1950–2014 period ONIHM.
The calibrated 1950–2014 period ONIHM groundwater fluxes included net farm net recharge (calculated as the difference between the inflow of recharge to the water table and the outflow of evapotranspiration from the water table such that negative values indicate that evapotranspiration from the water table was greater than deep percolation [recharge to the water table] and vice versa). Net farm net recharge was the largest flux from the groundwater system with a mean annual net outflow of 153.4 cubic feet per second. Stream leakage was the largest flux to the groundwater system with a mean annual net inflow of 152.5 cubic feet per second, indicating that, on average, the groundwater/surface-water interaction was a “losing” system where stream water leaked into the subsurface and recharged the water table. Simulated monthly trends demonstrated that net stream leakage was the largest inflow to the groundwater-flow system for 10 of the 12 months; for the other 2 months (January and March), farm net recharge (January) and net storage (March) were the largest inflow to the groundwater-flow system.
A saline groundwater interface map was created for the study and compared to the water levels from the final stress period of the 1950–2014 model to identify the presence of fresh/marginal groundwater throughout the study area. Fresh/marginal groundwater was characterized as groundwater with less than 1,500 milligrams per liter of total dissolved solids. Fresh/marginal groundwater thickness ranged from 0 to 438.2 ft within the study area. The thickest regions of fresh/marginal groundwater were in the eastern part of the study area near Sand Creek, Bird Creek, and Hominy Creek and in the Arkansas River alluvial aquifer in the region downstream from the Arkansas River at Ralston, Okla.
Like the 1950–2014 model, forecast model results for the landscape indicated that transpiration from precipitation was the largest flux out of the landscape for all three forecasts, constituting 77, 73, and 58 percent of precipitation for the dry, average, and wet forecasts, respectively. The dry and average forecast landscape fluxes demonstrated similar trends and magnitudes, whereas the wet forecast landscape fluxes indicated the largest changes compared to the average forecast fluxes. Most notably, runoff increased from a mean of 1.1 and 1.6 in/yr for the dry and average forecasts, respectively, to 10 in/yr for the wet forecast. Similar changes occurred for the other wet forecast landscape fluxes.
The calibrated 1950–2014 period ONIHM simulated three forecasts to assess the effects of potential climatic changes on the hydrologic system from October 2014 to December 2099. The three forecasts simulated theoretical dry, average, and wet conditions using precipitation and potential evapotranspiration datasets from selected years in the calibrated 1950–2014 period ONIHM. Annual precipitation amounts were 26.89, 35.47, and 50.73 in. for the dry, average, and wet forecasts, respectively. Groundwater-flow component forecast results indicated that stream leakage is always a net inflow to the groundwater-flow system for dry, average, and wet conditions, meaning the study area stream network is always predominantly a “losing” regime where stream water infiltrates into the underlying aquifer. Storage was only a net outflow from the groundwater-flow system and indicated a replenishment to groundwater storage that resulted in an increase in groundwater levels only during the wet forecast. Further, these gains in groundwater storage for the wet forecast occurred only during February through June.
Mean fresh/marginal groundwater saturated thicknesses were 125 and 126 ft for the dry and average forecast conditions, respectively, and wet forecast average thickness was 145 ft and ranged from 0 to 443 ft. The spatial extents of fresh/marginal groundwater at the end of the dry, average, and wet forecast model periods (December 2099) did not change substantially from the end of the 1950–2014 model period (September 2014).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205141","collaboration":"Prepared in cooperation with the Osage Nation","usgsCitation":"Traylor, J.P., Mashburn, S.L., Hanson, R.T., and Peterson, S.M., 2021, Assessment of water availability in the Osage Nation using an integrated hydrologic-flow model: U.S. Geological Survey Scientific Investigations Report 2020–5141, 96 p., https://doi.org/10.3133/sir20205141.","productDescription":"Report: xiii, 96 p.; 2 Interactive Figures; Data Release; Dataset","numberOfPages":"114","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-102662","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":384320,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5141/coverthb.jpg"},{"id":384321,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5141/sir20205141.pdf","text":"Report","size":"9.57 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5141"},{"id":384322,"rank":3,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/sir/2020/5141/sir20205141_figure8.pdf","text":"Figure 8 (layered)","size":"626 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5141 Figure 8","linkHelpText":"— Supergroups for the Osage Nation Integrated Hydrologic Model (note: some supergroups are hidden; in order to see a given supergroup, the reader may need to turn off layers for the overlying supergroups)."},{"id":384324,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91OKQ2C","text":"USGS data release","description":"USGS data release","linkHelpText":"MODFLOW-One Water Hydrologic Model integrated hydrologic-flow model used to evaluate water availability in the Osage Nation"},{"id":384323,"rank":4,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/sir/2020/5141/sir20205141_figure14.pdf","text":"Figure 14 (layered)","size":"711 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5141 Figure 14","linkHelpText":"— Simulated groundwater-level altitude contours for the final stress period of the calibrated Osage Nation Integrated Hydrologic Model (September 30, 2014), dry forecast (December 31, 2099), average forecast (December 31, 2099), and wet forecast (December 31, 2099). This figure is a layered PDF."},{"id":384325,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"U.S. Geological Survey National Water Information System database","linkHelpText":"— USGS water data for the Nation"}],"country":"United States","state":"Kansas, Oklahoma","otherGeospatial":"Osage Nation","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -95.99578857421875,\n 36.13565654678543\n ],\n [\n -95.99853515625,\n 37.00035919622158\n ],\n [\n -95.97930908203125,\n 37.081475648860525\n ],\n [\n -96.29241943359375,\n 37.13623498442895\n ],\n [\n -96.48193359375,\n 36.96306042436515\n ],\n [\n -96.9873046875,\n 36.94989178681327\n ],\n [\n -97.12188720703125,\n 36.6992553955527\n ],\n [\n -97.14385986328125,\n 36.36822190085111\n ],\n [\n -96.6412353515625,\n 36.213255233061844\n ],\n [\n -96.26220703125,\n 36.11125252076156\n ],\n [\n -95.99578857421875,\n 36.13565654678543\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Nebraska Water Science Center
U.S. Geological Survey
5231 South 19th Street
Lincoln, NE 68512
Regional flood frequency analysis (RFFA) methods are essential tools to assess flood hazard and plan interventions for its mitigation. They are used to estimate flood quantiles when the at‐site record of streamflow data is not available or limited. One commonly used RFFA method is the index flood method (IFM), which assumes that peak floods satisfy the simple scaling hypothesis.
In this work we present an integrated approach to assess the spatial scaling behavior of floods in the United Kingdom (UK) for 540 catchments, where the IFM is currently used operationally. This assessment employs product moments, probability weighted moments, and quantile analysis, and is applied to two different types of “hydrologically homogeneous” UK regions: geographical regions as defined in the Flood Studies Report (NERC, 1975) and pooling‐groups as defined in the updated Flood Estimation Handbook (FEH; Institute of Hydrology, 1999). To understand which variables play a significant role in the flood‐peak generating mechanism, the assessment approach considers scaling not only of drainage area alone but also of other hydro‐geomorphological variables. Results provided by the different methodologies consistently showed that only part (ranging from 30% to 70%) of the peak flow variability is explained by drainage area alone; this fraction increases (up to 80%–95%) when multiple regression is used. Supported by the peak flow spatial scaling assessment, we compared the proposed approach for peak flow quantile estimation with the current FEH method in ungauged catchments. The quantile regression method based on the pooling‐group outperforms the current FEH‐ungauged method, providing a 14% relative improvement in root mean square error over the entire country.
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Processing and regression methods described by Robertson and others (2018) were used with discrete and continuous data collected during water years 2011 and 2018 to update regression models for estimating instantaneous flux with the same form of equations as published by Robertson and others (2018). Monthly and water year average fluxes for all but two of the 23 gage sites were estimated using a weighted combination of results from surrogate models (which have streamflow, turbidity, and seasonal indicators as explanatory variables) and unit-value (UV)-flow models which have only UV streamflow and seasonal indicators as explanatory variables. Two of the gage sites had extensive periods of missing turbidity records, so average flux estimates for those stations were based solely on results from UV-flow models.
For most sites, estimated loads of total phosphorus were computed and summed for water years 2014–2018. The cumulative loads were used to compute yields and flow-weighted mean concentrations for water years 2014–2018. The estimated cumulative total phosphorus loads for water years 2014–2018 ranged from 112 to 11,500 metric tons. The Maumee River site (U.S. Geological Survey gage number 04193500) had the largest estimated cumulative load for water years 2014–2018 and the third largest estimated flow-weighted mean concentration. In fact, the estimated cumulative load at the Maumee River site was more than three times larger than the second largest estimated cumulative load.
Estimated average annual total phosphorus yields and flow-weighted mean concentrations for water years 2014–2018 ranged from 0.016 metric tons per square kilometer to 0.771 metric tons per square kilometer and 0.033 milligram per liter to 0.466 milligram per liter, respectively. The Cattaraugus Creek gage site (U.S. Geological Survey gage number 04213500) had the highest estimated average annual total phosphorus yield and flow-weighted mean concentration. The average annual total phosphorus yield at the Cattaraugus Creek gage site was almost twice as large as the second largest estimated yield.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201145","collaboration":"Prepared in cooperation with the Great Lakes Restoration Initiative","usgsCitation":"Koltun, G.F., 2021, Estimated total phosphorus loads for selected sites on Great Lakes tributaries, water years 2014–2018: U.S. Geological Survey Open-File Report 2020–1145, 13 p., https://doi.org/10.3133/ofr20201145.","productDescription":"Report: v, 13 p.; 2 Appendixes; Data Release","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-122090","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":383717,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2020/1145//ofr20201145_appendix_2.csv","text":"Appendix 2","size":"64.8 kB","linkFileType":{"id":7,"text":"csv"},"description":"OFR 2020–1145 Appendix 2","linkHelpText":"— Estimated monthly total phosphorus loads at selected U.S. Geological Survey gage sites on Great Lakes tributaries"},{"id":383712,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1145/coverthb.jpg"},{"id":383713,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1145/ofr20201145.pdf","text":"Report","size":"1.69 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020–1145"},{"id":383714,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2020/1145/ofr20201145_appendix_1.xlsx","text":"Appendix 1","size":"16.4 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2020–1145 Appendix 1","linkHelpText":"— Estimated annual total phosphorus loads and flow-weighted mean concentrations at selected U.S. Geological Survey gage sites on Great Lakes tributaries"},{"id":383715,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2020/1145/ofr20201145_appendix_1.csv","text":"Appendix 1","size":"8.45 kB","linkFileType":{"id":7,"text":"csv"},"description":"OFR 2020–1145 Appendix 1","linkHelpText":"— Estimated annual total phosphorus loads and flow-weighted mean concentrations at selected U.S. Geological Survey gage sites on Great Lakes tributaries"},{"id":383716,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2020/1145/ofr20201145_appendix_2.xlsx","text":"Appendix 2","size":"66.0 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2020–1145 Appendix 2","linkHelpText":"— Estimated monthly total phosphorus loads at selected U.S. Geological Survey gage sites on Great Lakes tributaries"},{"id":383718,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WEW32M","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Model archive—Estimated total phosphorus loads for selected sites on Great Lakes tributaries, water years 2014–2018"}],"country":"United States","state":"Illinois, Indiana, Michigan, 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The U.S. Geological Survey assists the Federal Emergency Management Agency in its mission to identify flood hazards and zones for risk premiums for communities nationwide, by creating flood insurance rate maps through updating hydraulic models that use river geometry data. The data collected consist of elevations of river channels, banks, and structures, such as bridges, dams, and weirs that can affect flow. To account for the model complexity of river structure hydraulics and the fidelity between river channel and structure geometry, two distinct standards for collecting geometry data are presented, both using global navigation satellite system real-time network surveying. This method is adapted from U.S. Geological Survey manuals and is foundational in hydraulic surveying for flood insurance rate maps.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201146","collaboration":"Prepared in cooperation with the Federal Emergency Management Agency","usgsCitation":"Taylor, N.J., and Simeone, C.E., 2021, Practical field survey operations for flood insurance rate maps: U.S. Geological Survey Open-File Report 2020–1146, 8 p., https://doi.org/10.3133/ofr20201146.","productDescription":"iv, 8 p.","numberOfPages":"8","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-114316","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":383741,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/tm11D1","text":"Techniques and Methods 11-D1","linkHelpText":"- Methods of practice and guidelines for using survey-grade global navigation satellite systems (GNSS) to establish vertical datum in the United States Geological Survey"},{"id":383723,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1146/coverthb.jpg"},{"id":383724,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1146/ofr20201146.pdf","text":"Report","size":"662 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1146"},{"id":383725,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/tm11D3","text":"Techniques and Methods 11-D3","linkHelpText":"- Procedures and Best Practices for Trigonometric Leveling in the U.S. Geological Survey"}],"contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
Steady-state numerical groundwater-flow models were constructed for the islands of Kaua‘i, O‘ahu, and Maui to enable quantification of the hydrologic consequences of withdrawals and other stresses that can place limits on groundwater availability. The volcanic aquifers of Hawai‘i supply nearly all drinking water for the islands’ residents, freshwater for diverse industries, and natural discharge to springs, streams, and nearshore areas that support ecosystems, cultural practices, aesthetics, and recreation. Increases in groundwater withdrawal and changes in climate can cause water-table depression, saltwater rise, and reduction of natural groundwater discharge—all of which can limit fresh groundwater availability. The numerical models described in this report are designed to quantify these consequences. Separate models were created for each island using MODFLOW-2005 with the Seawater Intrusion package, which allows simulation of freshwater and saltwater in ocean-island aquifers. Calibration resulted in models that generally replicate observed water-level, stream base-flow, and spring-flow data, and simulate groundwater-flow directions and fresh groundwater thicknesses that are consistent with conceptual models. The calibrated models use hydraulic properties that are consistent with the ranges reported in previous studies. The models show that the relative distribution of fresh groundwater discharge to the ocean, streams, and springs and withdrawals for human use differ substantially among the three islands studied here. These differences indicate that consequences that limit the availability of fresh groundwater for human use are likely to differ among the three islands.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205126","usgsCitation":"Izuka, S.K., Rotzoll, K., and Nishikawa, T., 2021, Volcanic Aquifers of Hawai‘i—Construction and calibration of numerical models for assessing groundwater availability on Kaua‘i, O‘ahu, and Maui: U.S. Geological Survey Scientific Investigations Report 2020-5126, 63 p., https://doi.org/10.3133/sir20205126.","productDescription":"Report: viii, 63 p.; Data Release","numberOfPages":"63","ipdsId":"IP-071367","costCenters":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"links":[{"id":383611,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5126/covrthb.jpg"},{"id":383612,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5126/sir20205126.pdf","text":"Report","size":"53 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":383613,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9K4DK2P","linkHelpText":"MODFLOW-2005 and SWI2 models for assessing groundwater availability in volcanic aquifers on Kaua‘i, O‘ahu, and Maui, Hawai‘i"},{"id":416444,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20155164","text":"Scientific Investigations Report 2015-5164","description":"Izuka, S.K., Engott, J.A., Rotzoll, Kolja, Bassiouni, Maoya, Johnson, A.G., Miller, L.D., and Mair, Alan, 2018, Volcanic aquifers of Hawai‘i—Hydrogeology, water budgets, and conceptual models (ver. 2.0, March 2018): U.S. Geological Survey Scientific Investigations Report 2015-5164, 158 p., https://doi.org/10.3133/sir20155164.","linkHelpText":"- Volcanic Aquifers of Hawai‘i—Hydrogeology, Water budgets, and Conceptual Models"},{"id":416445,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/pp1876","text":"Professional Paper 1876","description":"Izuka, S.K., and Rotzoll, K., 2023, Volcanic aquifers of Hawaiʻi—Contributions to assessing groundwater availability on Kauaʻi, Oʻahu, and Maui: U.S. Geological Survey Professional Paper 1876, 100 p., https://doi.org/10.3133/pp1876.","linkHelpText":"- Volcanic Aquifers of Hawai‘i—Contributions to Assessing Groundwater Availability on Kaua‘i, O‘ahu, and Maui"},{"id":417944,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/fs20233010","text":"Fact Sheet 2023-3010","description":"Izuka, S.K., and Rotzoll, K., 2023, Availability of groundwater from the volcanic aquifers of the Hawaiian Islands: U.S. Geological Survey Fact Sheet 2023-3010, 4 p., https://doi.org/10.3133/fs20233010.","linkHelpText":"- Availability of Groundwater from the Volcanic Aquifers of the Hawaiian Islands"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kaua'i, Maui, O'ahu","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -156.73095703125,\n 20.57365332356332\n ],\n [\n -155.90423583984375,\n 20.57365332356332\n ],\n [\n -155.90423583984375,\n 21.04861794324536\n ],\n [\n -156.73095703125,\n 21.04861794324536\n ],\n [\n -156.73095703125,\n 20.57365332356332\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -158.33221435546875,\n 21.235622362422877\n ],\n [\n -157.62359619140625,\n 21.235622362422877\n ],\n [\n -157.62359619140625,\n 21.72505868324388\n ],\n [\n -158.33221435546875,\n 21.72505868324388\n ],\n [\n -158.33221435546875,\n 21.235622362422877\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -159.85931396484375,\n 21.830906665069758\n ],\n [\n -159.22622680664062,\n 21.830906665069758\n ],\n [\n -159.22622680664062,\n 22.264951388846296\n ],\n [\n -159.85931396484375,\n 22.264951388846296\n ],\n [\n -159.85931396484375,\n 21.830906665069758\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Pacific Islands Water Science Center
U.S. Geological Survey
Inouye Regional Center
1845 Wasp Blvd., B176
Honolulu, HI 96818
High-resolution topographic and bathymetric mapping can assist in the analysis of river habitat. The National Park Service has been planning to relocate a boat ramp along the St. Croix River in Minnesota, across the river from the town of Osceola, Wisconsin, to improve visitor safety, improve operations for commercial use, enhance the overall visitor experience, and eliminate deferred maintenance at the landing. This landing grants access to the St. Croix River, which is a part of the National Park Service St. Croix National Scenic Riverway. Hydrographic and topographic surveys were needed to determine where the new location should be. The objective for these surveys was to provide baseline information in order to assess the direct effects of the landing relocation on physical habitat in areas adjacent to Osceola, Wisconsin. The study area for these surveys was about 18.5 hectares and located directly off the existing landing. Although the existing boat launch is referred to as the Osceola landing, it is located on the Minnesota side of the river and is the busiest National Park Service landing on the St. Croix River (National Park Service St. Croix National Scenic Riverway, 2020). This report documents methods and results of aquatic benthic mapping in a small area of the St. Croix River.
The hydroacoustic and topographic surveys were collected from October 16–17, 2019. The hydrographic surveys consisted of multibeam and sidescan sound navigation and ranging (sonars). The topographic shoreline survey consisted of light detection and ranging (lidar) captured by boat adjacent to riverbanks. Additionally, an acoustic Doppler current profiler was used to measure flow velocities. The water level was higher than normal, and therefore had faster flow during the hydroacoustic surveys. Multibeam, lidar, and sidescan surveys occurred the first day, and the velocity mapping and ground truthing was conducted the second day. Multibeam and lidar provided derivative datasets that included bathymetry and a topobathy with a spatial resolution of 1 foot. From these data, additional data could be measured including slope and terrain ruggedness. Sidescan (acoustic reflectance measures) provided imagery that was used to help with interpretation of the river bottom.
Outcomes from these combined datasets were substrate and bedform maps. Much of the area was covered in sand ripples or small dunes. A small area running adjacent to the deeper valley or cut down the river consisted of harder substrates, such as cobble and gravel. Large woody debris piles were found throughout the study area. Multiple stationary moving-bed tests were completed, and no corrections were recommended for the conditions occurring during survey. Mussel presence was noted in some of the underwater videos. The physical parameters of depth, flow, bedforms, and substrate derived from the datasets provided baseline measures for a benthic habitat map. Further analysis of benthic habitat might be possible with additional biological and chemical data.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201149","collaboration":"Prepared in cooperation with the National Park Service, the St. Croix National Scenic Riverway, and the Denver Service Center","usgsCitation":"Hanson, J.L., and Strange, J.M., 2021, Hydrographic and benthic mapping—St. Croix National Scenic Riverway—Osceola landing: U.S. Geological Survey Open-File Report 2020–1149, 26 p., https://doi.org/10.3133/ofr20201149.","productDescription":"Report: vi, 26 p.; Data Release","numberOfPages":"36","onlineOnly":"Y","ipdsId":"IP-118301","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":383330,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1149/coverthb3.jpg"},{"id":383331,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1149/ofr20201149.pdf","text":"Report","size":"37.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020–1149"},{"id":383332,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9O0QH8B","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Saint Croix National Scenic Riverway (SACN)—Osceola boat landing 2019 benthic and bathymetry data"}],"country":"United States","state":"Wisconsin","county":"Osceola","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.72460937499999,\n 45.3111146177239\n ],\n [\n -92.69577026367185,\n 45.3111146177239\n ],\n [\n -92.69577026367185,\n 45.33187500352944\n ],\n [\n -92.72460937499999,\n 45.33187500352944\n ],\n [\n -92.72460937499999,\n 45.3111146177239\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Upper Midwest Environmental Sciences Center
U.S. Geological Survey
2630 Fanta Reed Road
La Crosse, WI 54603