A Soil-Water-Balance (SWB) model for the Mississippi embayment region in Arkansas, Tennessee, Mississippi, and Louisiana was constructed and calibrated to gain insight into potential recharge patterns for the Mississippi River Valley alluvial aquifer, which has had substantial drawdown under intense pumping stress over the last several decades. An analysis of the net infiltration term from the SWB model combined with newly gathered airborne electromagnetic geophysical data on the surficial sediments in a calibrated modular three-dimensional finite-difference (MODFLOW 6) groundwater flow model of one area in the alluvial plain found that the distribution of net infiltration was significantly different from the recharge that gets to the water table through the complicated silt and clay stratigraphy of the unsaturated zone. The net infiltration of water through the rooting zone as simulated by SWB ranges from 5.7 to 12.3 inches per year in the alluvial plain part of the model domain, and is fairly evenly distributed within local areas. Recharge to the underlying aquifer is less and is much more focused in particular zones where the connectivity through the upper layers of the unsaturated zone above the water table is greater, indicating possible horizontal flow and perched water table conditions in the unsaturated zone. Runoff and net infiltration together account for 32 percent of the incoming precipitation overall and somewhat higher percentages in the alluvial plain area on an annual basis. These terms are much higher in the fall and winter than in the summer. Actual evapotranspiration accounts for between 62 and 72 percent on average of the annual precipitation but dominates all other terms in the summer months. Without irrigation, summertime net infiltration and runoff would be near zero in the crop-dominated alluvial plain area. The SWB model reproduced reported irrigation rates for corn, soybeans, rice, and cotton on an annual basis fairly well. The SWB model for the Mississippi embayment region was calibrated using more than 15,000 observations representing four parts of the calculated water budget: actual evapotranspiration, surface runoff, net infiltration, and irrigation. Using a Monte Carlo approach to determine the uncertainty in the model results stemming from the uncertainty in the model parameters used in the calibration, the uncertainty in the annual actual evapotranspiration values was around 5 percent, whereas the uncertainty in the irrigation, net infiltration, and runoff was around 20 percent.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235080","programNote":"Water Availability and Use Science Program","usgsCitation":"Nielsen, M.G., and Westenbroek, S.M., 2023, Updated estimates of water budget components for the Mississippi embayment region using a Soil-Water-Balance model, 2000–2020: U.S. Geological Survey Scientific Investigations Report 2023–5080, 58 p., https://doi.org/10.3133/sir20235080","productDescription":"Report: vii, 58 p.; Data Release; Dataset","numberOfPages":"72","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-132665","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":501044,"rank":10,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115885.htm","linkFileType":{"id":5,"text":"html"}},{"id":423679,"rank":9,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20235051","text":"SIR 2023–5051","linkHelpText":"— Automated construction of Streamflow-Routing networks for MODFLOW—Application in the Mississippi Embayment region"},{"id":423678,"rank":8,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20235100","text":"SIR 2023–5100","linkHelpText":"—Simulating groundwater flow in the Mississippi Alluvial Plain with a focus on the Mississippi Delta"},{"id":423159,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235080/full"},{"id":423153,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5080/coverthb.jpg"},{"id":423155,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5080/sir20235080.XML"},{"id":423154,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5080/sir20235080.pdf","text":"Report","size":"14.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023–5080"},{"id":423156,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5080/images/"},{"id":423158,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":423157,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P97KK17G","text":"USGS data release","linkHelpText":"Model archive and output files for net infiltration, runoff, and irrigation water use for the Mississippi Embayment Regional Aquifer System, 2000 to 2020, simulated with the Soil-Water-Balance model"}],"country":"United States","otherGeospatial":"Mississippi Embayment Region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -94.12089542031869,\n 28.886284478842654\n ],\n [\n -86.65019229531852,\n 28.886284478842654\n ],\n [\n -86.65019229531852,\n 37.89501192204163\n ],\n [\n -94.12089542031869,\n 37.89501192204163\n ],\n [\n -94.12089542031869,\n 28.886284478842654\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Upper Midwest Water Science Center
U.S. Geological Survey
1 Gifford Pinchot Drive
Madison, WI 53726
Imaging sonar was used to assess the influence of a fish guidance net, installed at the entrances to the selective water withdrawal (SWW) intake structure, in the forebay of Round Butte Dam, Oregon, on behavior, abundance, and timing of fish during the spring of 2022. The purposes of the SWW are (1) to direct surface currents in the forebay to attract and collect downriver migrating juvenile salmonid smolts (Chinook salmon [Oncorhynchus tshawytscha], sockeye salmon [O. nerka], and steelhead [O. mykiss]) from Lake Billy Chinook and (2) to enable operators of the SWW to withdraw water from surface and benthic elevations in the reservoir to manage downriver water temperatures. Part of the evaluation to determine how well the structure performs at collecting juvenile salmonids is (1) to regularly assess how fish are approaching the entrance, and (2) determine if operational flows and the installation of a guidance (lead) net near the SWW structure entrance can be optimized to increase the attraction of smolts present in the forebay of Lake Billy Chinook. The goal of this study was to provide data about the effects of the installation of a lead net on the movements and behaviors of juvenile salmonids near the entrance to the SWW to help inform decisions to improve downstream passage solutions.
Two imaging sonar units were deployed during the spring 2022 smolt out-migration period. One unit monitored fish movements near the south entrance and one unit monitored movements near the north entrance of the SWW, with the lead net between the two entrances. Both smolt and bull trout (Salvelinus confluentus)-size fish were regularly observed near the entrances, with greater abundances observed at night, corresponding with greater discharge through the SWW, as opposed to during the day when discharge was reduced. Smolt-size fish groups were primarily observed near the interior halves of each SWW entrance, and greater abundances of fish were observed at the south entrance. Increased counts of bull trout-size fish coincided with the increased abundances of smolt-size fish. Overall, the results indicate that (1) smolt-size fish were more abundant near the entrance of the SWW during periods of increased discharge, (2) bull trout-size fish were present at the SWW, and (3) a greater percentage of smolt-size fish were observed directed toward the entrances of the SWW during periods of increased discharge. The addition of the lead net may assist in orienting fish toward the entrances to the SWW.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231090","collaboration":"Prepared in cooperation with Portland General Electric","usgsCitation":"Smith, C.D., and Hatton, T.W., 2023, Influence of a guide net on the presence and behavior of fish near the selective water withdrawal structure in Lake Billy Chinook, Oregon, 2022: U.S. Geological Survey Open-File Report 2023–1090, 25 p., https://doi.org/10.3133/ofr20231090.","productDescription":"vii, 25 p.","onlineOnly":"Y","ipdsId":"IP-155570","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":423749,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231090/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2023-1090"},{"id":423751,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1090/ofr20231090.XML"},{"id":423750,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1090/Images"},{"id":423747,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1090/ofr20231090.jpg"},{"id":423748,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1090/ofr20231090.pdf","text":"Report","size":"10.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1090"},{"id":500154,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115707.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Oregon","otherGeospatial":"Lake Billy Chinook","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.64591331853623,\n 44.79048612033958\n ],\n [\n -121.64591331853623,\n 44.35814579483878\n ],\n [\n -121.03356092450966,\n 44.35814579483878\n ],\n [\n -121.03356092450966,\n 44.79048612033958\n ],\n [\n -121.64591331853623,\n 44.79048612033958\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115-5016
Monroe County is in southeastern West Virginia, encompassing an area of 474 square miles. The area consists of karst and siliciclastic aquifers of Ordovician, Silurian, Devonian, and Mississippian age and is in parts of two physiographic provinces: the Valley and Ridge Province to the east of Peters Mountain, and the Appalachian Plateau Province to the west of Peters Mountain. This study was developed in response to inquiries from the Monroe County Commission requesting assessment of the water resources of the county to better understand the quantity of the county’s groundwater resources, for both current [2023] and future demand, and to provide information to support protection and management of the county’s valuable groundwater resources.
Various products were developed for this study that provide knowledge with respect to water availability and contamination susceptibility of the karst aquifers within the county. U.S. Geological Survey (USGS) geologists conducted extensive geologic mapping in support of the project, producing (1) a countywide bedrock geologic map, (2) a countywide hydrogeologic map, and (3) a light detection and ranging (lidar)-derived countywide digital elevation model and associated sinkhole map. A significant part of this work was to map in detail the Greenbrier Group at the formation level, which prior to this study had only partially been completed. The report also includes (4) a description of the lithologic units identified as part of the geologic mapping process.
U.S. Geological Survey hydrologists completed several additional products for the hydrology part of the effort, including development of (1) a countywide potentiometric surface (water-table) map, (2) a countywide base-flow stream assessment, (3) countywide water-budget estimates, (4) well log surveys for 15 wells to better understand subsurface controls on groundwater flow within the study area, (5) two groundwater tracer tests to better refine the groundwater divide from the northern and southern parts of the karst aquifer in Monroe County; and finally, based on all available data collected for the study including the potentiometric surface map, geologic map, current [2023] and legacy fluorometric groundwater tracer tests, and base-flow stream assessments, (6) groundwater-basin delineations were reassessed for principal groundwater basins within the Greenbrier aquifer.
In Monroe County, four principal hydrogeologic settings produce large yields of water for residential, agricultural, and other uses. The most relied upon water-bearing zone with respect to current [2023] public water supply is from springs along Peters Mountain. These springs are derived from intervals of fractured sandstone and resultant alluvial deposits. Groundwater flows downslope through these permeable alluvial deposits and discharges at the contact with less permeable strata, such as the Reedsville Shale. The second most relied upon water-bearing zone in Monroe County is within the karstic Greenbrier Group aquifer, in which the basal Hillsdale Limestone overlies the less permeable Maccrady Shale. This geologic contact between the Hillsdale Limestone and Maccrady Shale is not only targeted as a source of water for agricultural supply but also is targeted as a source of water for residential supply. The third most relied upon water-bearing zone is composed of shallow perched aquifers within the Greenbrier Group. The discontinuous nature of these perched aquifers makes mapping their extent impossible, but they are related to permeable geologic strata, such as karstified limestones with solutionally enhanced permeability that overlies less permeable shale or chert bedrock. During geologic mapping of the county, several of these perched aquifers were documented in the Pickaway, Union, and Alderson Limestones. A fourth zone consists of springs from Ordovician carbonates at the base of Peters Mountain, which are influenced by sinking streams as well as upwelling along faults. In terms of water quantity, the most sustainable springs are those having deeper-sourced flows.
Public supplies are a principal source of water used for residential and commercial supply in the region, accounting for 0.49 million gallons per day (Mgal/d) of fresh-water withdrawals (0.14 Mgal/d of groundwater and 0.35 Mgal/d of surface water) for residential and commercial use and serving 6,645 individuals (49.2 percent of the population). An estimated 6,861 people, (50.8 percent of the population) primarily rely on private wells or other unregulated sources, such as springs, and withdraw 0.55 Mgal/d of groundwater for their residential use. Public water supply in the region is primarily (71.4 percent) derived from springs and augmented by stream withdrawals (backup sources mainly during low-flow periods), with the remaining portion (28.6 percent) derived from groundwater withdrawals from wells. For rural residents, however, 100 percent of their withdrawals are derived from groundwater (wells or springs).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235121","isbn":"978-1-4113-4541-6","collaboration":"Prepared in cooperation with the West Virginia Department of Environmental Protection, the West Virginia Department of Health & Human Resources, and the Monroe County Commission","usgsCitation":"Kozar, M.D., Doctor, D.H., Jones, W.K., Chien, N., Cox, C.E., Orndorff, R.C., Weary, D.J., Weaver, M.R., McAdoo, M.A., and Parker, M., 2023, Hydrogeology, karst, and groundwater availability of Monroe County, West Virginia: U.S. Geological Survey Scientific Investigations Report 2023–5121, 82 p., https://doi.org/10.3133/sir20235121.","productDescription":"Report: xii, 81 p.; 4 Appendixes, 5 Data Releases","numberOfPages":"81","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-153904","costCenters":[{"id":37280,"text":"Virginia and West Virginia Water Science Center 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Capacity Data From County Health Department Well Completion Reports"},{"id":423489,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2023/5121/sir20235121_appendix2.csv","text":"Appendix 2","size":"17.3 KB","linkFileType":{"id":7,"text":"csv"},"linkHelpText":"- Base-flow Data for 83 Sites Measured in September 2019 in Monroe County, West Virginia"},{"id":501160,"rank":18,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115685.htm","linkFileType":{"id":5,"text":"html"}},{"id":423496,"rank":14,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9TFAN5X","text":"USGS data release","linkHelpText":"Interpolated groundwater levels and altitudes for Monroe County, West Virginia, 2017–2019"},{"id":423495,"rank":13,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9KF9FD2","text":"USGS data release","linkHelpText":"Fluorescein and Rhodamine WT concentration and recovery data for select 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Virginia and West Virginia Water Science Center
U.S. Geological Survey
1730 East Parham Road
Richmond, Virginia 23228
In 2020 and 2021, the U.S. Geological Survey, Cape Cod National Seashore of the National Park Service, and Friends of Herring River cooperated to assess nutrient and suspended sediment concentrations across the ocean-estuary boundary at a dike on the Herring River on Chequessett Neck Road in Wellfleet, Massachusetts, that has restricted saltwater inputs by regulating water inflow through three culverts or sluiceways into the watershed for more than 100 years. The dike is slated to be removed, and the purpose of this project was to characterize natural variability of nutrient and suspended sediment concentration during flood tide and ebb tide conditions at the dike based on seasonal and environmental variables. This baseline can be used to assess if removal of the dike is likely to result in measurable changes in water quality.
Data from the current [2023] study were aggregated with previously published data from November 2015 through September 2018 to provide a long-term record. Samples for the current [2023] study were collected from flood and following ebb tides approximately twice per month from June 2020 through December 2021 at fixed time intervals after the beginning of the tides. Samples were analyzed for nitrate plus nitrite, ammonium, total dissolved nitrogen, total nitrogen, orthophosphate, total dissolved phosphorus, total phosphorus, silica, dissolved organic carbon, and suspended sediment. Constituent concentrations generally were lower using fixed time sampling than in previous studies that used flow-weighted composite sampling, except for nitrate plus nitrite and orthophosphate. Concentrations of nitrate plus nitrite, ammonium, total nitrogen, total dissolved nitrogen, silica, and dissolved organic nitrogen generally were higher on the ebb tide than on the flood tide. By contrast, concentrations of orthophosphate, total phosphorus, and total dissolved phosphorus were generally similar between flood and ebb tides.
Most nutrient concentrations except silica and ammonium varied seasonally on flood and ebb tides. Phosphorus species, total nitrogen, and dissolved organic carbon concentrations generally peaked in mid- to late summer and were lowest in winter. For nitrate, the reverse was true. Nutrient concentrations generally were higher on the ebb tide than on the flood tide except for total dissolved phosphorus and total phosphorus where differences between flood and ebb tide depended on season. Constituent concentrations were similar between spring, neap, and midamplitude tides on both the flood and ebb tides.
Nitrate, ammonium, total nitrogen, and silica concentrations were positively correlated with precipitation and runoff. Orthophosphate, total dissolved phosphorus, total phosphorus, and dissolved organic carbon were positively correlated with surface air temperature, downwelling shortwave radiation, and ocean water temperature. Nitrate, ammonium, and silica concentration were negatively correlated with surface air temperature and ocean water temperature. Orthophosphate and total dissolved phosphorus were negatively correlated with runoff. Nitrate plus nitrite, ammonium, and silica concentrations were negatively correlated with downwelling shortwave radiation.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235120","collaboration":"Prepared in cooperation with the National Park Service and the Friends of Herring River","usgsCitation":"Huntington, T.G., 2023, Assessment of prerestoration water quality in the Herring River to support adaptive management at the Cape Cod National Seashore: U.S. Geological Survey Scientific Investigations Report 2023–5120, 51 p., https://doi.org/10.3133/sir20235120.","productDescription":"Report: viii, 51 p.; Data Release; 2 Appendixes","numberOfPages":"51","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-143243","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":501158,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115686.htm","linkFileType":{"id":5,"text":"html"}},{"id":423334,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ZU5YHW","text":"USGS data release","linkHelpText":"Data supporting analysis of relations between nutrient concentrations in the Herring River on the ebb tide, near Wellfleet, Massachusetts, and environmental conditions, 2015–2022"},{"id":423333,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2023/5120/sir20235120_appendix3.pdf","text":"Appendix 3","size":"96.1 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Alert and Preliminary Guidance for Addressing Nitrogen Contamination of Pall Versapor GWV High-Capacity Capsule Filters"},{"id":423332,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2023/5120/sir20235120_appendix2.pdf","text":"Appendix 2","size":"19.3 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Field Methods—Interim Announcement for Change in Capsule-Filter Type, Supplier, and Instructions for Use"},{"id":423331,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5120/images/"},{"id":423330,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5120/sir20235120.XML"},{"id":423329,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235120/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2023-5120"},{"id":423328,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5120/sir20235120.pdf","text":"Report","size":"6.34 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5120"},{"id":423327,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5120/coverthb.jpg"}],"country":"United States","state":"Massachusetts","otherGeospatial":"Herring River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -70.07530273023929,\n 41.972935131526725\n ],\n [\n -70.07530273023929,\n 41.92351733741285\n ],\n [\n -70.00976667801922,\n 41.92351733741285\n ],\n [\n -70.00976667801922,\n 41.972935131526725\n ],\n [\n -70.07530273023929,\n 41.972935131526725\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
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A 21-layer three-dimensional transient groundwater-flow model of the New Jersey Coastal Plain was developed and calibrated by the U.S. Geological Survey (USGS) in cooperation with the New Jersey Department of Environmental Protection to simulate groundwater-flow conditions during 1980–2013, incorporating average annual groundwater withdrawals and average annual groundwater recharge. This model is the third version of the New Jersey Coastal Plain regional groundwater-flow model that was initially developed as part of the USGS Regional Aquifer System Analysis (RASA) program. The model simulates groundwater flow in 11 aquifers and 10 intervening confining units of the New Jersey Coastal Plain to provide a regional overview of groundwater conditions. Averaged groundwater withdrawal data for 1980 to 2013 were used in the model. The 11 aquifers in New Jersey are, from shallowest to deepest, the Holly Beach water-bearing zone and the confined Cohansey aquifer in Cape May County; the Rio Grande water-bearing zone; the Atlantic City 800-foot sand; the Piney Point, Vincentown, and Wenonah-Mount Laurel aquifers; the Englishtown aquifer system; and the upper, middle, and lower aquifers of the Potomac-Raritan-Magothy (PRM) aquifer system.
The model was developed with the MODFLOW–2005 numerical code and the UCODE parameter estimation technique and calibrated using water-level and base-flow observations. A total of 3,453 water-level observations from 392 wells in New Jersey and 48 wells in Delaware from 1983 to 2013 were used in model calibration, which includes historical water-level trends for 29 wells in New Jersey during 1980–2013 presented in time-series hydrographs. In addition, derived observations also were included by calculating the vertical gradient at 33 pairs of nested observation wells in New Jersey, for a total of 210 observations. Changes in water levels over time were calculated for 134 wells in New Jersey and four wells in Delaware where water levels had varied substantially (approximately 10 ft) over the 30-year span of synoptic water-level measurements, for a total of 767 observations. A total of 1,485 base-flow observations in 47 surface-water basins in New Jersey from 1980 to 2013 were used in model calibration.
Updates to the groundwater-flow model include the conversion to a fully three-dimensional model from the previous quasi-three-dimensional model. The new model will allow for potential future uses such as particle tracking or simulation of variable-density groundwater flow that could not be accomplished with earlier versions of the model. Spatially and temporally variable recharge estimated by using a soil-water balance model resulted in a spatially and temporally finer discretization. The Rio Grande water-bearing zone was added to the model as an aquifer layer to refine estimates of simulated flow in Atlantic and Cape May Counties, New Jersey. Hydrogeologic parameters were updated to include the confining units in New Jersey and corresponding hydrogeologic units in Delaware and eastern Maryland.
The simulated water levels for the New Jersey Coastal Plain aquifers were compared to water-level measurements made during 1980–2013. The average residual for 4,243 water-level observations for New Jersey (simulated water levels minus measured water levels) is 1.5 feet. The simulated water-level contours for the confined aquifers for 2013 were compared to potentiometric surfaces produced from water levels measured during 2013. Simulated water levels generally matched the 2013 potentiometric surfaces of the confined aquifers in the areas of large withdrawals. Hydrographs of wells in the confined Coastal Plain aquifers of New Jersey show that simulated water levels generally match the magnitude and seasonal variation of the observed water levels. Hydrographs of base flow for the 47 streamgaging stations in New Jersey indicate that most of the simulated and estimated data match reasonably well.
Groundwater withdrawals are an important resource for water supply, agricultural, industrial, and commercial needs in the New Jersey Coastal Plain. Groundwater withdrawals from the New Jersey Coastal Plain aquifers have resulted in persistent, regionally extensive cones of depression in the Englishtown aquifer system and Wenonah-Mount Laurel aquifer in Ocean and Monmouth Counties; Wenonah-Mount Laurel and upper, middle, and lower PRM aquifers in Camden County; and Atlantic City 800-foot sand in Atlantic County. Because hydrologic stresses and water-management needs change with time, periodic updates to the groundwater-flow model are required to provide current information about hydrologic conditions in the New Jersey Coastal Plain and to maintain its usefulness as a tool to manage water resources and develop water-resource strategies. The current updates will support the continued application of this model as a tool for evaluating the regional effects of changes in groundwater withdrawals and of current and potential future water-management strategies on groundwater levels in the New Jersey Coastal Plain.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235066","collaboration":"Prepared in cooperation with the New Jersey Department of Environmental Protection","usgsCitation":"Gordon, A.D., and Carleton, G.B., 2023, Updates to the regional groundwater-flow model of the New Jersey Coastal Plain, 1980–2013: U.S. Geological Survey Scientific Investigations Report 2023–5066, 116 p., https://doi.org/10.3133/sir20235066","productDescription":"Report: xii, 116 p.; Data Release","numberOfPages":"116","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-127396","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":500947,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115639.htm","linkFileType":{"id":5,"text":"html"}},{"id":422695,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5066/images/"},{"id":422693,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235066/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2023-5066"},{"id":422696,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9W6RXFC","text":"USGS data release","linkHelpText":"MODFLOW-2005 model used to simulate the regional groundwater flow system in the updated New Jersey Coastal Plain model, 1980-2013"},{"id":422694,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5066/sir20235066.XML"},{"id":422692,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5066/sir20235066.pdf","text":"Report","size":"25.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5066"},{"id":422691,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5066/coverthb.jpg"}],"country":"United States","otherGeospatial":"New Jersey Coastal Plain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -74.49018324613056,\n 41.03712838002892\n ],\n [\n -75.25922621488034,\n 41.417217443631785\n ],\n [\n -77.41254652738019,\n 39.17183412365296\n ],\n [\n -75.22626723050551,\n 37.8132834585617\n ],\n [\n -72.98505629300531,\n 40.4043207917766\n ],\n [\n -74.49018324613056,\n 41.03712838002892\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, New Jersey Water Science Center
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During 2020–22, the U.S. Geological Survey, in cooperation with the Edwards Aquifer Authority, revised a previous publication that described the geologic framework and hydrostratigraphy of the Edwards and Trinity aquifers within northern Bexar and Comal Counties, Texas. This report presents the refined maps and descriptions of geologic framework and hydrostratigraphy of the Edwards and Trinity aquifers within northern Bexar and Comal Counties that resulted from additional field data. Two informal geologic units and their corresponding informal hydrostratigraphic unit (HSU) names are introduced in this report; these informal units were identified during geologic mapping work done in counties adjoining the study area. Hydrostratigraphically, the rocks exposed in the study area represent a section of the upper confining unit to the Edwards aquifer, the Edwards aquifer, the upper zone of the Trinity aquifer, the middle zone of the Trinity aquifer, and the lower confining unit to the middle zone of the Trinity aquifer. The Washita, Eagle Ford, Austin, and Taylor Groups are generally considered to be the upper confining unit to the Edwards aquifer. The Edwards aquifer was subdivided into nine informally named HSUs (from top to bottom) as follows: I, II, III, IV, V, VI, VII, Seco Pass, and VIII. The upper zone of the Trinity aquifer was subdivided into five informal HSUs and two subunits (from top to bottom) as follows: cavernous, Camp Bullis, upper evaporite, fossiliferous (subunits: upper and lower), and lower evaporite. The middle zone of the Trinity aquifer was subdivided into nine named HSUs (from top to bottom) as follows: Bulverde, Little Blanco, Twin Sisters, Doeppenschmidt, Herff Falls (where present), Rust, Honey Creek, Hensell, and Cow Creek. The middle zone of the Trinity aquifer is underlain by the confining Hammett HSU. Groundwater recharge and flow paths in the study area are influenced not only by the hydrostratigraphic characteristics of the individual HSUs but also by faults and fractures.
Director, Oklahoma-Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, TX 78754–4501
The 2012 Little Bear Fire caused substantial vegetation loss in the Eagle Creek Basin of south-central New Mexico. This loss was expected to alter the localized hydrologic response to precipitation by creating conditions that amplify surface runoff, which might alter the geomorphology of North Fork Eagle Creek, a major tributary to Eagle Creek. To monitor short-term geomorphic change, annual geomorphic surveys of North Fork Eagle Creek were conducted from 2017 to 2021. The surveys measured 14 cross sections, stream gradients, woody debris accumulations, and pools found within the study reach. During the 2017–21 study period, the study reach experienced multiple high-flow events that resulted from both monsoonal rainfall and snowmelt runoff. Comparisons of the cross-section and channel profile data for the repeat geomorphic surveys indicate localized erosion and deposition occurred as a result of the high-flow events but overall study reach geomorphology shower little change through the study period. Additionally, the number of woody debris accumulations and pools increased during the study period. Evidence from the 5-year geomorphic survey indicates that the North Fork Eagle Creek’s geomorphology did not change substantially during the study period. Wildfire severity and frequency within mountainous regions of the Southwest are projected to increase and their effect on fluvial systems remains uncertain; however, continued geomorphic studies can provide informative insight on watershed post-wildfire resiliency and recovery by establishing baselines that can be used in the event of a future severe wildfire within the Eagle Creek Basin.
Director, New Mexico Water Science Center
U.S. Geological Survey
6700 Edith Blvd. NE
Albuquerque, NM 87113
We rarely consider light limitation in ecosystem productivity, yet light limitation is a major constraint on river autotrophy. Because the light that reaches benthic autotrophs must first pass through terrestrial vegetation and an overlying water column that can be loaded with sediments or colored organic material, there is strong selection for river autotrophs to have high light use efficiencies (LUEs), that is, the efficiency at which light energy is converted to biomass. In contrast to prior studies that have estimated river LUE on single days, we calculated continuous LUE over more than 6 full years for 64 free-flowing rivers across the United States. This dataset represents the largest compilation of continuous estimates of daily rates of gross primary productivity (GPP) and daily light inputs from which we calculated daily estimates of LUE. Early estimates of LUE in rivers found that clearwater springs with stable flows could achieve LUEs of 4%, much higher than LUEs reported for terrestrial plants. We found that 53% of the rivers in our dataset have LUEs that exceed 4% on at least one day of their time series. Because of the high variability in daily LUE, measurements taken on any given day may misrepresent a river ecosystem's annual LUE. Though most rivers share a high potential, the mean annual LUE of all rivers in our dataset is much lower, only 0.5%. We found that rivers with more variable flow regimes had lower annual LUEs, which indicates that LUE is constrained by hydrologic disturbances that remove, bury, or shade autotrophic biomass. Comparisons of LUE across ecosystems allow us to reframe our view of rivers, by recognizing the high efficiency with which they convert light to biomass compared with lentic, marine, and terrestrial ecosystems.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.4659","usgsCitation":"Thellman, A., Savoy, P., and Bernhardt, E., 2023, High potential but low achievement: Frequent disturbance constrains the light use efficiency of river ecosystems: Ecosphere, v. 14, no. 10, e4659, 9 p., https://doi.org/10.1002/ecs2.4659.","productDescription":"e4659, 9 p.","ipdsId":"IP-151660","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":492879,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.4659","text":"Publisher Index Page"},{"id":492731,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"conterminous United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"geometry\": {\n \"type\": \"MultiPolygon\",\n 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0000-0002-6075-837X","orcid":"https://orcid.org/0000-0002-6075-837X","contributorId":300288,"corporation":false,"usgs":true,"family":"Savoy","given":"Philip","email":"","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":943677,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bernhardt, Emily S.","contributorId":92143,"corporation":false,"usgs":false,"family":"Bernhardt","given":"Emily S.","affiliations":[{"id":27331,"text":"Duke University, Durham, NC","active":true,"usgs":false}],"preferred":false,"id":943678,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70249500,"text":"ofr20231002 - 2023 - The enigmatic Rattlesnake Knoll, Spring Valley, east-central Nevada—A geophysical perspective","interactions":[],"lastModifiedDate":"2026-02-10T21:24:41.808706","indexId":"ofr20231002","displayToPublicDate":"2023-10-11T11:03:42","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-1002","displayTitle":"The Enigmatic Rattlesnake Knoll, Spring Valley, East-Central Nevada—A Geophysical Perspective","title":"The enigmatic Rattlesnake Knoll, Spring Valley, east-central Nevada—A geophysical perspective","docAbstract":"Rattlesnake Knoll is a small, 30-meter-high mound of igneous breccia in the center of Spring Valley, east-central Nevada. In the past, researchers have disagreed as to whether the unusual-looking outcrop is intrusive or volcanic. The breccia possesses a normal magnetic polarity, but this is not apparent in aeromagnetic survey data. These data instead show that the knoll lies within a small aeromagnetic low that partially overlaps the extent of a small gravity high. The small gravity anomaly associated with the knoll, combined with an initial, limited ground magnetic survey taken at the knoll, indicates that the knoll rocks extend northward in the subsurface. A second, more extensive ground magnetic traverse was also done north of the knoll. Taking into consideration these new survey data and preexisting data, a two and one-half dimensional modeling program based on Webring (1985) was used to produce a geophysical model that accounts for gravity and magnetic properties, satisfies available geologic information, and conforms to current estimates of basin thickness. This model and the field observations support the interpretation that the knoll consists of gently west-dipping beds of Tertiary volcanic flow breccia, mudflow breccia, and conglomerate.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231002","usgsCitation":"Mankinen, E.A., Rowley, P.D., and McKee, E.H., 2023, The enigmatic Rattlesnake Knoll, Spring Valley, east-central Nevada—A geophysical perspective: U.S. Geological Survey Open-File Report 2023–1002, 13 p., https://doi.org/10.3133/ofr20231002.","productDescription":"Report: vi, 13 p.; Data Release","numberOfPages":"13","onlineOnly":"Y","ipdsId":"IP-133281","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":435149,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WL97XY","text":"USGS data release","linkHelpText":"Ground magnetic data, Spring Valley, White Pine County, Nevada"},{"id":421859,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1002/covrthb_.jpg"},{"id":421860,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1002/ofr20231002.pdf","text":"Report","size":"2 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":499729,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115506.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Nevada","otherGeospatial":"Spring Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -114.36,\n 39.06\n ],\n [\n -114.36,\n 39.00\n ],\n [\n -114.24,\n 39.00\n ],\n [\n -114.24,\n 39.06\n ],\n [\n -114.36,\n 39.06\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Geology, Minerals, Energy, & Geophysics Science Center
U.S. Geological Survey
Building 19, 350 N. Akron Rd.
P.O. Box 158
Moffett Field, CA 94035
The segment of the Upper Missouri River between Fort Peck Dam and the headwaters of Lake Sakakawea is home to a population of the endangered Scaphirhynchus albus (pallid sturgeon). Lack of population growth (recruitment failure) has been attributed to inadequate dispersal distance of larvae between spawning locations and the headwaters of Lake Sakakawea, where conventional wisdom holds that anoxic water-quality conditions are lethal to larval sturgeon. River-management objectives to recover pallid sturgeon in this segment therefore focus on increasing available drift distance, decreasing drift rate, increasing larval development rate, or a combination of these objectives. Understanding of channel morphological conditions along this about 400-kilometer segment may provide insight into upstream spawning habitat potential (where sturgeon likely spawn) and into geomorphic factors that may contribute to flow complexity, hence drift rate. This report documents a continuous geomorphic classification of the Fort Peck segment of the Upper Missouri River using remotely sensed datasets to provide contextual information about spatial variations potentially affecting pallid sturgeon reproductive ecology.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235109","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers, Missouri River Recovery Program","usgsCitation":"Jacobson, R.B., Elliott, C.M., and Bulliner, E., 2023, Geomorphic classification framework for assessing reproductive ecology of Scaphirhynchus albus (pallid sturgeon), Fort Peck segment, Upper Missouri River, Montana and North Dakota: U.S. Geological Survey Scientific Investigations Report 2023–5109, 15 p., https://doi.org/10.3133/sir20235109.","productDescription":"Report: vi, 15 p.; Data Release","numberOfPages":"26","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-155746","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":421828,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P92HVKT3","text":"USGS data release","linkHelpText":"Geomorphic variables for classification of the Upper Missouri River, Montana and North Dakota"},{"id":421829,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235109/full","linkFileType":{"id":5,"text":"html"}},{"id":421827,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5109/images/"},{"id":421824,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5109/coverthb.jpg"},{"id":421825,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5109/sir20235109.pdf","text":"Report","size":"5.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023–5109"},{"id":421826,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5109/sir20235109.XML","linkFileType":{"id":8,"text":"xml"}}],"country":"United States","state":"Montana, North Dakota","otherGeospatial":"Fort Peck segment, Upper Missouri River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -103.31605153925373,\n 48.4037537878354\n ],\n [\n -106.52859788507773,\n 48.4037537878354\n ],\n [\n -106.60549394122786,\n 47.047516337061694\n ],\n [\n -103.30750753301488,\n 47.08228719733623\n ],\n [\n -103.31605153925373,\n 48.4037537878354\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Columbia Environmental Research Center
U.S. Geological Survey
4200 New Haven Road
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Anadromous fish returning to the lower American River are restricted to 36 kilometers of free-flowing river between Nimbus Dam and American River’s confluence with the Sacramento River, California. Salmon in the American River provide an important freshwater recreational fishery. However, annual salmon production in the American River in recent years has been low relative to the mid-1990s (Surface Water Resources, Inc., 2001). To investigate the low production of fall-run Chinook salmon (Oncorhynchus tshawytscha), the Bureau of Reclamation requested that the U.S. Geological Survey apply the Stream Salmonid Simulator (S3) model to the population of fall-run Chinook salmon on the American River.
The American River was chosen among seven candidate Sacramento Basin rivers for S3 application. The American River was selected because of its management and public interest, recently low anadromous fish production, and rich time series of key demographic data needed for S3 application. Data that were not available, however, were empirical estimates on juvenile salmon habitat suitability in the American River. Therefore, a large component of applying S3 to the American River was devoted to the estimation of juvenile salmon habitat suitability and capacity. This entailed snorkeling the lower American River for 3 weeks in March 2021 during the early out-migration period for juvenile Chinook salmon. These efforts were fruitful and showed that the typically small fish (<55 millimeters) in the American River preferred much shallower depths than predicted by habitat suitability criteria derived from the literature for this population. Having empirical estimates on juvenile salmon in the American River provided a solid foundation from which to simulate the population using the S3 model.
The S3 model is a spatially explicit population model that runs on a daily time step to simulate redd superimposition, egg maturation, fry emergence and the subsequent growth, survival, and emigration of juvenile Chinook salmon from the river. The key features of this model relevant to this report include (1) a temperature-dependent bioenergetics model driving daily growth rates; (2) density-dependent dynamics that are influenced by the effect of flow on suitable habitat area; and (3) within-year habitat, river flow, and water temperature effects specific to spawning, egg incubation, and fry, parr, and smolt life stages. We used estimates of spawning escapement and geo-referenced redd locations to quantify the spatial and temporal distribution of female spawners for brood years 2014–19. These estimates of female spawners initiate the simulation of each year’s juvenile salmon emergence and emigration over a spatial domain extending from Nimbus Dam to the river’s confluence with the Sacramento River.
Using weekly estimates of juvenile salmon abundance and size (fork length) that passed the Watt Avenue fish trap (river kilometer 14.7), we calibrated the S3 model by estimating three key demographic parameters for each year, y: (1) Sy, the average daily survival probability, (2) M0y, the intercept for density-dependence in movement, representing the average daily probability of remaining in a habitat at zero abundance, and (3) Cy, the average daily proportion of maximum consumption. These parameters were obtained by minimizing the Mallow’s distance (Lupu and others, 2017) between distributions of weekly abundances and sizes of fish at the traps and weekly simulated abundances and sizes (by S3). Investigation of model fit showed excellent agreement between simulated annual abundances and the abundance of fish passing the fish trap. However, when we compared weekly abundances at the fish trap, S3 under-predicted peaks and over-predicted troughs in the time series of weekly abundances at the fish trap. Thus, some unknown within-year effects have yet to be identified and incorporated in the S3 model. Identifying these important effects and incorporating them in the S3 model would help explain the lack of fit between estimated and simulated weekly abundances.
We estimated parameters for 6 years that included a wide range of female spawner abundances (3,057–10,753) and water year types (Critical–Wet). We contrast our estimated parameters to the corresponding number of female spawners and the water year type for the Sacramento Valley. By happenstance, years having higher annual spawner abundances concurred with Critical to Dry water year types. Estimates of survival trended lower with higher spawner abundances and Critical to Dry conditions. In contrast, the extremely wet water year of 2017 had the lowest M0y, suggesting less density-dependence in fish movement, and the lowest Cy, suggesting lower average consumption in this year. When this high-flow year was excluded, a trend towards higher probabilities of fish remaining in a habitat at low abundance and lower proportions of maximum consumption was apparent from Critical to Wet conditions, but only 5 years of data were included. Except for 2017, daily proportions of maximum consumption were relatively high (Cy > 0.83), suggesting that fish were feeding at reasonably high proportions relative to the expected maximum consumption as defined by the “Wisconsin” bioenergetics model (Stewart and Ibarra, 1991).
Survival estimates from fry emergence to outmigration at the Sacramento River confluence were generally low when integrated over time. The highest daily survival probability was Sy = 0.93 in 2019, or 50 percent total mortality after 10 days. In contrast, our lowest daily survival probability was Sy = 0.74 in 2015, or 95 percent total mortality after 10 days. Consequently, even our highest estimated daily survival probability might be considered low. This is especially true given that Sy was estimated over a relatively short distance (<14.7 kilometers) from emergence to the Watt Avenue fish trap. Several factors, including our assumed and relatively high daily egg survival rate of 0.9975, could influence juvenile survival estimates. For example, an egg survival rate of 0.9975 results in 3-percent total mortality after 10 days. Egg mortality estimates used in S3 calibration were approximated from egg survivorship studies in the Yakima River, Washington (Johnson and others, 2012), and remains one of the greater uncertainties in S3 when estimating survival across life stages. By including bona fide estimates of egg survival in S3 simulations, the validity of the S3’s current daily egg survival rate could be assessed specifically for the American River. Tagging studies also could provide S3 with direct estimates of juvenile survival and movement; survival during egg incubation then could be estimated indirectly via model fitting.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231060","collaboration":"Prepared in cooperation with U.S. Bureau of Reclamation","usgsCitation":"Plumb, J.M., Perry, R.W., Hatton, T.W., Smith, C.D., and Hannon, J.M., 2023, Application of the Stream Salmonid Simulator (S3) model to assess fall Chinook salmon (Oncorhynchus tshawytscha) production in the American River, California: U.S. Geological Survey Open-File Report 2023–1060, 35 p., https://doi.org/10.3133/ofr20231060.","productDescription":"ix, 35 p.","onlineOnly":"Y","ipdsId":"IP-141661","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":421858,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1060/ofr20231060.XML"},{"id":421857,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1060/images"},{"id":421856,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231060/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2023-1060"},{"id":421855,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1060/ofr20231060.pdf","text":"Report","size":"5.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1060"},{"id":421854,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1060/coverthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"American River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.5064051133351,\n 38.727216763718815\n ],\n [\n -121.5064051133351,\n 38.523370433079805\n ],\n [\n -121.11639046489739,\n 38.523370433079805\n ],\n [\n -121.11639046489739,\n 38.727216763718815\n ],\n [\n -121.5064051133351,\n 38.727216763718815\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115-5016
Between 9 August and 1 September, 2022, the Mesophotic and Deep Benthic (MDBC) Habitat Assessment and Evaluation (HAE) and Mapping, Ground-truthing, and Predictive Habitat Modeling (MGM) projects implemented remotely operated vehicle (ROV) dives, multibeam surveys, and conductivity, temperature, depth (CTD) operations at deep-sea sites in the northern Gulf of Mexico. The primary sites selected are a region of known deep-sea coral habitats, including Deepwater Horizon (DWH) injured and reference sites at depths of 1,100–2,000 m.
The cruise includes objectives from MGM and HAE projects. Habitat characterization and analysis of biological samples collected with ROV Odysseus maintain long-term data flows and fill critical data gaps on the biology and ecology at impacted and reference sites, assess potential ongoing impacts from threats, refine predictive habitat models, help target locations for direct restoration and protection, and determine a baseline for health and condition. Multibeam echosounder data can help document the broadscale abundance and distribution of MDBC, characterize benthic habitats, and provide information that can help guide future ROV surveys.
","language":"English","publisher":"National Oceanic and Atmospheric Administration","doi":"10.25923/nwxc-ab95","usgsCitation":"Clark, R., and Demopoulos, A., 2023, Cruise Report for NOAA Ship Nancy Foster Cruise NF-22-06: DWH MDBC Cruise Report CR-23-03, 33 p., https://doi.org/10.25923/nwxc-ab95.","productDescription":"33 p.","ipdsId":"IP-153687","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":422038,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Gulf of Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -87.5,\n 30\n ],\n [\n -91.5,\n 30\n ],\n [\n -91.5,\n 27\n ],\n [\n -87.5,\n 27\n ],\n [\n -87.5,\n 30\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Clark, Randy","contributorId":218497,"corporation":false,"usgs":false,"family":"Clark","given":"Randy","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":886574,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Demopoulos, Amanda 0000-0003-2096-4694","orcid":"https://orcid.org/0000-0003-2096-4694","contributorId":222183,"corporation":false,"usgs":true,"family":"Demopoulos","given":"Amanda","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":886575,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70248980,"text":"sir20235096 - 2023 - Groundwater-flow model of the Treasure Valley, southwestern Idaho, 1986–2015","interactions":[],"lastModifiedDate":"2026-03-12T21:20:19.984383","indexId":"sir20235096","displayToPublicDate":"2023-09-28T11:19:49","publicationYear":"2023","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":"2023-5096","displayTitle":"Groundwater-Flow Model of the Treasure Valley, Southwestern Idaho, 1986–2015","title":"Groundwater-flow model of the Treasure Valley, southwestern Idaho, 1986–2015","docAbstract":"Most of the population of the Treasure Valley and the surrounding area of southwestern Idaho and easternmost Oregon depends on groundwater for domestic supply, either from domestic or municipal-supply wells. Current and projected rapid population growth in the area has caused concern about the long-term sustainability of the groundwater resource. In 2016, the U.S. Geological Survey, in cooperation with the Idaho Water Resource Board and the Idaho Department of Water Resources, began a project to construct a numerical groundwater-flow model of the westernmost portion of the western Snake River Plain aquifer system, called the Treasure Valley.
The development of the model was guided by several objectives, including:
The model was constructed with a spatial scale and level of detail that aimed to meet these objectives while balancing the sometimes-competing goals of fast runtimes, numerical stability, usability, and parsimony.
The Treasure Valley Groundwater Flow Model (TVGWFM) is a three-dimensional finite-difference numerical model constructed using MODFLOW 6 (Langevin and others, 2017, Documentation for the MODFLOW 6 Groundwater Flow Model: U.S. Geological Survey Techniques and Methods, book 6, chap. A55, 197 p., https://doi.org/10.3133/tm6A55). The model covers the westernmost portion of the western Snake River Plain and is discretized into a regular grid of 64 by 65 cells with a side length of 1 mile and 6 layers of varying depth and active area. A historical model period was developed consisting of 360 month-long stress periods for 1986–2015. The model builds upon previous modeling efforts by adding a transient period, incorporating new head and discharge observations to constrain parameters, incorporating information from the hydrogeologic framework model (HFM) of Bartolino (2019, Hydrogeologic framework of the Treasure Valley and surrounding area, Idaho and Oregon: U.S. Geological Survey Scientific Investigations Report 2019–5138, https://doi.org/10.3133/sir20195138) and incorporating refined estimates of evapotranspiration and irrigation classification of lands in the study area.
The TVGWFM includes all significant components of recharge to and discharge from the aquifer. Inflows include canal seepage, irrigation and precipitation recharge, mountain-front recharge, rivers and stream seepage, and seepage from Lake Lowell. Outflows include discharge to agricultural drainage ditches, discharge to rivers and streams, pumping, and discharge to Lake Lowell. Each recharge or discharge component is represented separately using individual MODFLOW 6 packages.
Parameter values were derived with a combination of trial-and-error steps and automated parameter estimation using PEST software (Doherty, J.E., 2005, PEST, model-independent parameter estimation–User manual: Watermark Numerical Computing, https://pesthomepage.org/documentation). Parameter estimates were constrained with several types of observation data, including water levels, water level changes, vertical water level differences, drain discharges, change in drain discharges, river seepage, seepage from Lake Lowell, and change in seepage from Lake Lowell. Material properties from the hydrogeologic framework were also used to assign the minimum and maximum values of some parameters.
A final parameter realization was reached that minimized residuals between the observed and modelled values for the various observation groups. Mean residuals for the observation groups were 15.4 feet (ft) for water levels, 0.2 ft for water level changes, 19.4 ft for vertical water level differences, −3.9 cubic feet per second (ft3/s) for drain discharges, 0.0 ft3/s for changes in drain discharge, 45.0 ft3/s for river seepage, −40.1 ft3/s for Lake Lowell seepage, and 126.3 ft3/s for changes in Lake Lowell seepage. The quality of the model’s fit to observations varied spatially, with notable areas of under- or over-simulation of water levels present to the northwest and southwest of Lake Lowell, in the foothills along the eastern model boundary, and near the City of Eagle. Trends were observed in the residuals of many of the observation groups, indicating that the model is missing or not fully reproducing some phenomena that are observed in the system.
The TVGWFM can be used as a tool for water resource planning, for understanding the interactions of groundwater and surface water at a basin scale, and for facilitating conjunctive management, but may lack the precision needed for water rights administration at a local scale. Additional sources of uncertainty or limitations of the model are noted. The quantity and spatial distribution of canal seepage and infiltration of irrigation water recharge, the largest sources of recharge to the system, are unknown and approximated indirectly. There is poor understanding of how canal seepage and incidental recharge change as land is converted from agricultural (irrigated) to suburban (semi-irrigated). These uncertainties will affect any scenarios that investigate changes to land use or irrigation practices. Finally, the model has relatively high water-level residuals around and to the southwest of Lake Lowell and should not be used to estimate water level effects in that region.
The model was built with multiple, broadly expressed objectives and did not optimize performance for specific uses. However, the model and the tools included in an associated data release provide ample flexibility to improve the model for future uses. Adjustments and improvements could be made by refining the model in an area of interest, collecting additional calibration data, applying more rigorous boundary conditions, or re-estimating model parameters to optimize model performance for a specific model forecast.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235096","collaboration":"Prepared in cooperation with the Idaho Water Resource Board and the Idaho Department of Water Resources","usgsCitation":"Hundt, S.A., and Bartolino, J.R., 2023, Groundwater-flow model of the Treasure Valley, southwestern Idaho, 1986–2015: U.S. Geological Survey Scientific Investigations Report 2023–5096, 107 p., https://doi.org/10.3133/sir20235096.","productDescription":"Report: xii, 107 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-127901","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":501062,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115439.htm","linkFileType":{"id":5,"text":"html"}},{"id":421318,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5096/sir20235096.pdf","text":"Report","size":"30.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5096"},{"id":421321,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5096/images"},{"id":421317,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5096/coverthb.jpg"},{"id":421320,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9U6OOPH","text":"USGS data release","description":"USGS data release","linkHelpText":"Data and archive for a groundwater flow model of the Treasure Valley aquifer system, southwestern Idaho"},{"id":421322,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5096/sir20235096.XML"}],"country":"United States","state":"Idaho","otherGeospatial":"Treasure Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.26392993194762,\n 44.27650517719664\n ],\n [\n -117.26392993194762,\n 42.71456173603502\n ],\n [\n -115.50611743194747,\n 42.71456173603502\n ],\n [\n -115.50611743194747,\n 44.27650517719664\n ],\n [\n -117.26392993194762,\n 44.27650517719664\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Idaho Water Science Center
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Boise, Idaho 83702-4520
The U.S. Geological Survey and the Idaho Department of Water Resources measured groundwater levels during spring 2022 and autumn 2022 to create detailed potentiometric-surface maps for the alluvial aquifer in the Big Lost River Valley in south-central Idaho. Wells were assigned to shallow, intermediate, and deep water-bearing units based on well depth, groundwater potentiometric-surface altitude, and hydrogeologic unit. Potentiometric-surface contours were created for each of the three water-bearing units for spring 2022 and autumn 2022. Groundwater flow generally follows topography down valley to the south. The groundwater-level data also were used to calculate changes in groundwater levels from spring to autumn 2022 and from historical measurement events in 1968 and 1991 to 2022. Groundwater levels declined at most wells from spring 1968 to spring 2022 and from spring 1991 to spring 2022. Although groundwater-level changes are sensitive to interannual wet and dry periods, long-term groundwater-level declines suggest that recharge and down-valley groundwater flows are insufficient to fully recover groundwater-level declines from pumping in some parts of the alluvial aquifer in the Big Lost River Valley.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3509","collaboration":"Prepared in cooperation with the Idaho Department of Water Resources","usgsCitation":"Ducar, S.D., and Zinsser, L.M., 2023, Groundwater potentiometric-surface altitude in 2022 and groundwater-level changes between 1968, 1991, and 2022, in the alluvial aquifer in the Big Lost River Valley, south-central Idaho: U.S. Geological Survey Scientific Investigations Map 3509, 1 sheet, scale 1:150,000, 11-p. pamphlet, https://doi.org/10.3133/sim3509.","productDescription":"Pamphlet: viii, 11 p.; Map: 22.51 × 30.00 inches","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-140355","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":500438,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115436.htm","linkFileType":{"id":5,"text":"html"}},{"id":421346,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93NQAP9","text":"USGS data release","description":"USGS data release","linkHelpText":"Groundwater potentiometric-surface contours and well numbers used to map groundwater potentiometric-surface altitude in 2022 and groundwater-level changes between 1968, 1991, and 2022 in the alluvial aquifer in the Big Lost River Valley, south-central Idaho"},{"id":421275,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sim/3509/sim3509_pamphlet.XML"},{"id":421274,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sim/3509/images"},{"id":421270,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3509/coverthb.jpg"},{"id":421271,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3509/sim3509.pdf","text":"Sheet","size":"2.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3509"},{"id":421272,"rank":3,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/sim/3509/sim3509_pamphlet.pdf","text":"Pamphlet","size":"3.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3509 Pamphlet"},{"id":421273,"rank":4,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sim3509/full","text":"Pamphlet","linkFileType":{"id":5,"text":"html"},"description":"SIM 3509 Pamphlet"}],"country":"United States","state":"Idaho","otherGeospatial":"Big Lost River Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -114.0,\n 44.15\n ],\n [\n -114,\n 43.30\n ],\n [\n -113.15,\n 43.3\n ],\n [\n -113.15,\n 44.15\n ],\n [\n -114,\n 44.15\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Idaho Water Science Center
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Boise, Idaho 83702-4520
The Equus Beds aquifer and Cheney Reservoir are primary sources for the city of Wichita’s current (2023) water supply. The Equus Beds aquifer storage and recovery (ASR) project was developed by the city of Wichita in the early 1990s to meet future water demands using the Little Arkansas River as an artificial aquifer recharge water source during above-base-flow conditions. Little Arkansas River water is removed from the river at an ASR Facility intake structure, treated using National Primary Drinking Water Regulations as a guideline, and is infiltrated into the Equus Beds aquifer through recharge basins or injected into the aquifer through recharge wells for later use. The U.S. Geological Survey, in cooperation with the city of Wichita, completed this study to quantify and characterize Little Arkansas River water-quality data. Data in this report can be used to evaluate changing conditions, provide science-based information for decision making, and help meet regulatory requirements.
Continuous (hourly) physicochemical properties were measured, and discrete water-quality samples were collected from three Little Arkansas River sites located along the easternmost extent of the Equus Beds aquifer during 1995 through 2021 over a range of streamflow conditions. The Little Arkansas River at Highway 50 near Halstead, Kansas, streamgage (U.S. Geological Survey station 07143672; hereafter referred to as the “Highway 50 site”) is located upstream from the other two sites, and the Little Arkansas River near Sedgwick, Kans., streamgage (U.S. Geological Survey station 07144100; hereafter referred to as the “Sedgwick site”) is located downstream from the other two sites; these two sites bracket most of the easternmost part of the Equus Beds aquifer. The Little Arkansas River upstream of ASR Facility near Sedgwick, Kans., streamgage (U.S. Geological Survey station 375350097262800; hereafter referred to as the “Upstream ASR site”) is located between the Highway 50 and Sedgwick sites, about 14.7 river miles (mi) downstream from the Highway 50 site, about 1.7 river mi upstream from the Sedgwick site, and immediately upstream from the ASR Facility intake structure. Surrogate models for water-quality constituents of interest (including bromide, dissolved organic carbon, 2-chloro-4-isopropylamino-6-amino-s-triazine [deethylatrazine], atrazine, and metolachlor) were updated or developed using continuously measured and concomitant discrete data. These surrogate models, along with previously developed regression models, were used to compute concentrations (at the Highway 50, Sedgwick, and Upstream ASR sites) and loads (at the Highway 50 and Sedgwick sites) during the study period. Federal criteria were used to evaluate water quality. Where applicable, water-quality data were compared to Federal national drinking-water regulations. Flow-normalized water-quality constituent trends were evaluated using Weighted Regressions on Time, Discharge, and Season (WRTDS) statistical models and water-quality trends were described using WRTDS bootstrap tests.
Continuously computed primary ion concentrations were generally larger at the Highway 50 site compared to the Sedgwick site. During the study period, the Federal secondary maximum contaminant level (SMCL) for dissolved solids was exceeded 57 percent of the time at the Highway 50 site and 38 percent of the time at the Sedgwick site. Computed bromide concentrations were larger at the Highway 50 site and exceeded the city of Wichita treatment threshold about 70, 21, and 19 percent of the time at the Highway 50, Sedgwick, and Upstream ASR sites, respectively. Chloride concentrations exceeded the Federal SMCL about 16 percent of the time at the Highway 50 site and did not exceed the SMCL at the Sedgwick site. Continuous arsenic concentrations exceeded the Federal Maximum Contaminant Level (MCL) 9 to 15 percent of the time at the Sedgwick and Highway 50 sites, respectively, during the study. Atrazine concentrations exceeded the Federal MCL 10 percent of the time at the Highway 50 and Sedgwick sites and 14 percent of the time at the Upstream ASR site during the study; computed glyphosate concentrations at the Sedgwick site never exceeded the MCL during the study.
Little Arkansas River flow-normalized primary ion concentrations during 1995 through 2021 generally had downward trends and decreases were generally larger at the Highway 50 site compared to the Sedgwick site. Dissolved solids and chloride concentrations decreased at the Highway 50 and Sedgwick sites. Bromide had no trend at the Highway 50 site and a downward trend at the Sedgwick site. Nitrate plus nitrite and total phosphorus concentrations had upward trends at the Highway 50 site but downward trends at the Sedgwick site, whereas total organic carbon had upward trends at both sites. Nitrate plus nitrite, total nitrogen, total phosphorus, and total organic carbon fluxes had upward trends at the Highway 50 and Sedgwick sites. Suspended-sediment concentrations had an upward trend at the Highway 50 site and had no trend at the Sedgwick site. Arsenic concentrations had downward trends at the Highway 50 and Sedgwick sites.
About one-quarter to one-half of the Little Arkansas River loads, including nutrients and sediment, were transported during 1 percent of the time during the study. Because streamflows are highly sensitive to climatic variation and an increase of extreme precipitation events in the Great Plains is expected, similar disproportionately large pollutant loading events may increase into the future. Continuous measurement of physicochemical properties in near-real time allowed characterization of Little Arkansas River surface water during conditions and time scales that would not have been possible otherwise and served as a complement to discrete water-quality sampling. Continuation of this water-quality monitoring will provide data to characterize changing conditions in the Little Arkansas River and possibly identify new and changing trends. Information in this report allows the city of Wichita to make informed municipal water-supply decisions using past and present water-quality conditions and trends in the watershed.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235102","collaboration":"Prepared in cooperation with the city of Wichita, Kansas","usgsCitation":"Stone, M.L., and Klager, B.J., 2023, Long-term water-quality constituent trends in the Little Arkansas River, south-central Kansas, 1995–2021: U.S. Geological Survey Scientific Investigations Report 2023–5102, 103 p., https://doi.org/10.3133/sir20235102.","productDescription":"Report: ix, 103 p.; 1 Figure; 9 Tables; 5 Appendixes; Dataset","numberOfPages":"118","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-146544","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":421187,"rank":26,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2023/5102/sir20235102_appendix10.zip","text":"Appendix 10","size":"46 MB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Weighted Regressions on Time, Discharge, 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Sedgwick, Kansas"},{"id":421175,"rank":22,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2023/5102/sir20235102_appendix4.zip","text":"Appendix 4","size":"1.1 MB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Surrogate Regression Model Archive Summaries for the Little Arkansas River at Highway 50 near Halstead, Kansas"},{"id":421185,"rank":19,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2023/5102/sir20235102_table8.3.csv","text":"Table 8.3","size":"9 KB","linkFileType":{"id":7,"text":"csv"},"linkHelpText":"- Weighted Regressions on Time, Discharge, and Season estimated mean, flow-normalized, and generalized mean fluxes for sediment, indicator bacteria, and trace elements at the Little Arkansas River at Highway 50 near Halstead, Kansas, and Little Arkansas River near Sedgwick, Kans., 1995–2021"},{"id":421184,"rank":18,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2023/5102/sir20235102_table8.2.csv","text":"Table 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Highway 50 near Halstead, Kansas; Little Arkansas River near Sedgwick, Kans.; and Little Arkansas River upstream of ASR Facility near Sedgwick, Kans., 2004–19"},{"id":421170,"rank":7,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/sir/2023/5102/sir20235102_fig1.1.PDF","text":"Figure 1.1","size":"2.7 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Relations between turbidity sensors, 2004–19. A, YSI 6026 (YSI6026) and YSI 6136 (YSI6136) at the Little Arkansas River at Highway 50 near Halstead, Kansas"},{"id":421190,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":421169,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5102/images/"},{"id":421168,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5102/sir20235102.XML","linkFileType":{"id":8,"text":"xml"}},{"id":501150,"rank":27,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115440.htm","linkFileType":{"id":5,"text":"html"}},{"id":421182,"rank":16,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2023/5102/sir20235102_tables8.1-8.3.xlsx","text":"Tables 8.1–8.3","size":"112 KB","linkFileType":{"id":3,"text":"xlsx"}},{"id":421167,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5102/sir20235102.pdf","text":"Report","size":"5.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023–5102"},{"id":421188,"rank":20,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2023/5102/sir20235102_table11.1.xlsx","text":"Table 11.1","size":"51 KB","linkFileType":{"id":3,"text":"xlsx"},"linkHelpText":"- Weighted Regressions on Time, Discharge, and Season estimated yearly water-quality constituent loads at the Little Arkansas River at Highway 50 near Halstead, Kansas and near Sedgwick, Kans., 1998–2021"},{"id":421166,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5102/coverthb.jpg"},{"id":421189,"rank":21,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2023/5102/sir20235102_table11.1.csv","text":"Table 11.1","size":"14 KB","linkFileType":{"id":7,"text":"csv"}},{"id":421201,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235102/full","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Kansas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -98.1667,\n 38.6\n ],\n [\n -98.1667,\n 37.5\n ],\n [\n -97.25,\n 37.5\n ],\n [\n -97.25,\n 38.6\n ],\n [\n -98.1667,\n 38.6\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Kansas Water Science Center
U.S. Geological Survey
1217 Biltmore Drive
Lawrence, KS 66049
The soil and groundwater at the Central Chemical facility, Hagerstown, Maryland, are contaminated due to the blending and production of pesticides and fertilizers during much of the 20th century. Remedial investigations focus on two operable units (OU) consisting of the surface soils and waste disposal lagoon (OU-1) and the groundwater (OU-2). The contaminants of concern (COC) for groundwater include 41 compounds categorized within the subgroups of volatile organic compounds (VOCs), semi-volatile organic compounds (SVOCs), pesticides, and metals. The purpose of this report is to provide a conceptual site model of the hydrogeology and groundwater contaminant transport at and near the Central Chemical facility. The conceptual model was developed through review, synthesis, and interpretation of the results of hydrogeologic, soil, and other environmental investigations conducted at and in the vicinity of the facility in recent decades and is intended to support plans for environmental remediation of the groundwater in OU-2.
The extent and nature of the groundwater contaminant plume associated with the bedrock was characterized for OU-2 of the site. Lithologic and structural comparisons between shallow soil, weathered rock, and epikarst and deeper competent but bedded, dipping, fractured, and karstic limestones illustrate two connected flow systems—a surficial flow system consisting of the unconsolidated overburden and epikarst and a structurally dominant bedrock flow system below the epikarst. Uncertainties exist regarding the nature and transport of contaminants within the epikarst system particularly within voids and perched epikarst water tables. Karst dissolution features are observed within the site including sinkholes and dissolution voids within wells at the site. Of interest, one well in the northern part of the study area (MW-J-71) appears to have a dissolution void connected to an offsite well (OW-2-115) farther to the north. This connection is supported by groundwater level data and elevated concentrations of total suspended solids (TSS) and chlorobenzene in both wells. The high level of TSS supports the possibility of offsite transport of particle-bound contaminants within the conduit system. Episodically elevated concentrations of COC from different groups also were observed within select wells in the epikarst near the waste disposal lagoon (particularly MW-A-51). The variability observed between different COC within the same well may be the result of additional contaminated source materials unrelated to the disposal lagoon. Storage and episodic transport of contaminated material within the epikarst system has the potential to hinder remediation efforts if not considered in the remedial action.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225011","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Needham, T.P., Fiore, A.R., Ator, S.W., Raffensperger, J.P., Smith, M.B., Bellmyer, N.M., Dugan, C.M., and Morel, C.J., 2023, Geology, hydrology, and groundwater contamination in the vicinity of Central Chemical facility, Hagerstown, Maryland: U.S. Geological Survey Scientific Investigations Report 2022–5011, 62 p., https://doi.org/10.3133/sir20225011.","productDescription":"ix, 62 p.","numberOfPages":"62","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-127106","costCenters":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":500691,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115410.htm","linkFileType":{"id":5,"text":"html"}},{"id":420978,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5011/images/"},{"id":420977,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5011/sir20225011.XML"},{"id":420976,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20225011/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2022-5011"},{"id":420975,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5011/sir20225011.pdf","text":"Report","size":"13.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5011"},{"id":420974,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5011/coverthb.jpg"}],"country":"United States","state":"Maryland","city":"Hagerstown","otherGeospatial":"Central Chemical Facility","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -77.7208,\n 39.6542\n ],\n [\n -77.7208,\n 39.6597\n ],\n [\n -77.726,\n 39.6597\n ],\n [\n -77.726,\n 39.6542\n ],\n [\n -77.7208,\n 39.6542\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Maryland-Delaware-D.C. Water Science Center
U.S. Geological Survey
5522 Research Park Drive
Catonsville, MD 21228
The Federal Clean Water Act stipulates that States adopt water-quality standards to protect and enhance the quality of water in those States and to protect water quality through the creation of planning documents and discharge permits. Critical low-flow values, including the 4-day, 3-year low-flow frequency (4Q3) and harmonic mean streamflows, are necessary for developing those planning documents and permits. The U.S. Geological Survey computed the 4Q3 and adjusted harmonic mean streamflows using data from 96 streamgages on perennial streams, and regression equations were developed for the estimation of these parameters at ungaged, perennial streams in the State of New Mexico using weighted least-squares regression and readily accessed basin and climatic characteristics. Six equations were developed for the 4Q3 statistic, and five equations were developed for the adjusted harmonic mean statistic. Separate equations were developed for sites located in basins with mean elevations equal to or greater than 8,000 feet above the National Geodetic Vertical Datum of 1929 (except where noted as the North American Vertical Datum of 1988), as well as for sites on streams that are tributary to the San Juan River. Pseudo R-squared values ranged from 0.53 to 0.87 (4Q3) and adjusted R-squared values ranged from 0.69 to 0.89 (adjusted harmonic mean). For sites in basins with mean elevations of less than 8,000 feet above the National Geodetic Vertical Datum of 1929 (except where noted as the North American Vertical Datum of 1988), equations were developed based on contributing drainage area size. Drainage area, mean basin elevation, basinwide mean annual precipitation, and mean basin slope were found to have relations to the 4Q3; drainage area, mean basin elevation, basinwide mean annual precipitation, mean basin slope, and mean basinwide precipitation for the winter period, defined as the months of October through April, were found to have relations to the adjusted harmonic mean. Comparison to previous 4Q3 regression equations using fit statistics indicate an overall improvement in performance.
Director, New Mexico Water Science Center
U.S. Geological Survey
6700 Edith Blvd. NE
Albuquerque, NM 87113
The Stochastic Empirical Loading and Dilution Model (SELDM) was designed to help quantify the risk of adverse effects of runoff on receiving waters, the potential need for mitigation measures, and the potential effectiveness of such management measures for reducing these risks. SELDM is calibrated using representative hydrological and water-quality input statistics. This report by the U.S. Geological Survey, in cooperation with the Federal Highway Administration and the Connecticut, Massachusetts, and Rhode Island Departments of Transportation, documents approaches for assessing flows, concentrations, and loads of highway- and urban-runoff and receiving-stream stormwater in southern New England with SELDM. In this report, the term “urban runoff” is used to identify stormwater flows from developed areas with impervious fractions ranging from 10 to 100 percent without regard to the U.S. Census Bureau designation for any given location. There are more than 48,000 delineated road-stream crossings in southern New England, but because there are relatively few precipitation, streamflow, and water-quality monitoring sites in this area, methods were needed to simulate conditions at unmonitored sites. This report documents simulation methods, methods for interpreting stochastic model results, sensitivity analyses to identify the most critical variables of concern, and examples demonstrating how simulation results can be used to inform scientific decision-making processes. Results of 7,511 SELDM simulations were used to do the sensitivity analyses and provide information decisionmakers can use to address runoff-quality issues in southern New England and other areas of the Nation.
The sensitivity analyses indicate the relatively strong effect of input variables on variations in output results. These analyses indicate that highway and urban runoff quality and upstream water-quality statistics that vary considerably from site to site have the greatest effect on simulated results. Further data are needed to improve available water-quality statistics, and because the number of monitored sites will never approach the number of sites of interest for water-quality management, research is needed to identify methods to select statistics for unmonitored sites and quantify the uncertainties in the selection process. Hydrologically, prestorm streamflows with and without zero flows are the most sensitive and therefore the most important hydrologic variables to quantify. Results of analyses also are sensitive to statistics used for simulating structural best management practices.
Although the focus of the report is on data, statistics, simulation methods, and methods to interpret stochastic simulations, the examples in this report provide results that can be used to inform scientific decision-making processes. The results of 441 simulations that provide regional and site-specific highway and urban runoff yields across southern New England can be used for total maximum daily load analyses. The example stormwater load analysis done for 16 tributaries of the Narragansett Bay demonstrates that highway nitrogen loads are a small fraction of stormwater loads (about 3.6 percent), and a much smaller fraction of all nitrogen loads to the bay, primarily because highways have a small footprint on the land. Examples evaluating the potential effectiveness of end-of-pipe treatment indicate that offsite treatment is warranted in developed areas, and land conservation may be an effective mitigation strategy. The results of these analyses are consistent with conclusions from other simulation and monitoring studies.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235087","collaboration":"Prepared in cooperation with the Federal Highway Administration and the Connecticut, Massachusetts, and Rhode Island Departments of Transportation","usgsCitation":"Granato, G.E., Spaetzel, A.B., and Jeznach, L.C., 2023, Approaches for assessing flows, concentrations, and loads of highway and urban runoff and receiving-stream stormwater in southern New England with the Stochastic Empirical Loading and Dilution Model (SELDM): U.S. Geological Survey Scientific Investigations Report 2023–5087, 152 p., https://doi.org/10.3133/sir20235087.","productDescription":"Report: xii, 152 p.; Software Release; 4 Data Releases","numberOfPages":"152","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-133112","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":501050,"rank":12,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115402.htm","linkFileType":{"id":5,"text":"html"}},{"id":420555,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9K0Y7XR","text":"USGS data release","linkHelpText":"Model archive for analysis of the effects of impervious cover on receiving-water quality with the Stochastic Empirical Loading Dilution Model (SELDM)"},{"id":420556,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9CZNIH5","text":"USGS data release","linkHelpText":"Model archive for analysis of flows, concentrations, and loads of highway and urban runoff and receiving-stream stormwater in southern New England with the Stochastic Empirical Loading and Dilution Model (SELDM)"},{"id":420554,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9B02EUZ","text":"USGS data release","linkHelpText":"Model archive for analysis of long-term annual yields of highway and urban runoff in selected areas of California with the Stochastic Empirical Loading Dilution Model (SELDM)"},{"id":420557,"rank":9,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9VK1MCG","text":"USGS data release","linkHelpText":"Basin characteristics and point locations of road crossings in Connecticut, Massachusetts, and Rhode Island for highway-runoff mitigation analyses using the Stochastic Empirical Loading and Dilution Model"},{"id":420548,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5087/coverthb.jpg"},{"id":420549,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5087/sir20235087.pdf","text":"Report","size":"8.64 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5087"},{"id":420552,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5087/images/"},{"id":420887,"rank":11,"type":{"id":35,"text":"Software Release"},"url":"https://doi.org/10.5066/P9PYG7T5","text":"USGS software release","linkHelpText":"- Stochastic Empirical Loading and Dilution Model (SELDM) software archive"},{"id":420551,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5087/sir20235087.XML"},{"id":420553,"rank":10,"type":{"id":35,"text":"Software Release"},"url":"https://doi.org/10.5066/P9XBPIOB","text":"USGS software release","linkHelpText":"- Best management practices statistical estimator (BMPSE) version 1.2.0"},{"id":420550,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235087/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2023-5087"}],"country":"United States","state":"Connecticut, Massachusetts, New Hampshire, Rhode Island, Vermont","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -73.28249194123347,\n 42.97558594616143\n ],\n [\n -73.81823969745555,\n 41.00628384122689\n ],\n [\n -69.72117184187273,\n 40.9949482400483\n ],\n [\n -69.72117184187273,\n 42.97558594616143\n ],\n [\n -73.28249194123347,\n 42.97558594616143\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
North America is a global center for native freshwater mussel (order Unionida, hereinafter “mussels”) diversity, with more than 350 species. Mussels are among the most imperiled fauna on the planet. Reasons for both local and widespread declines in mussels are mostly unknown, although the threats may include habitat loss and fragmentation, diseases, environmental contaminants, altered flow regimes, migration barriers to larval hosts, non-native species, and climate change.
Over the past three decades, research on mussels has been substantial. Nevertheless, current conservation and management efforts are limited by significant information gaps. For example, the effects of emerging stressors on mussels are largely unknown and identifying when habitats are rehabilitated and suitable for reestablishment of mussels remains challenging. Additionally, historical and current information on the distribution, taxonomy, and life histories are often unreliable or lacking altogether, and more reliable information is needed for many species.
We identified focal research themes, goals, and objectives where research on mussels is needed based on information gaps identified through conversations with resource partners across local, regional, and national organizations. Research on biodiversity seeks to enhance the diversity of mussel species and populations to support healthy aquatic ecosystems. Research on emerging stressors seeks to improve the understanding of how mussel species, populations, and communities respond to emerging stressors, including environmental contaminants and climate change. Research on conservation seeks to enhance the recovery of species and populations and to identify data gaps limiting the conservation of mussels and their habitats. Mussels are in urgent need of proactive conservation because they are an integral part of our natural heritage, enhance biodiversity, and provide vital ecological services that support freshwater ecosystems.
The U.S. Geological Survey (USGS) has been, and continues to be, a leader in mussel research. Although the USGS is well suited to address the broad-scale multidisciplinary research needed to conserve mussels, the USGS has had substantial loss of scientists with mussel expertise over the past 20 years. However, the breadth of the USGS expertise on mussels can be leveraged internally across other USGS mission and program areas and externally across research partners. Given the breadth and scope of the issues facing mussels across the United States, the research themes outlined in this science vision can only be accomplished through extensive collaborations between the USGS and the full spectrum of natural resource partners, including other Federal and State agencies, Tribal organizations, universities, industries, and nongovernmental organizations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1511","isbn":"978-1-4113-4537-9","programNote":"Ecosystems Mission Area—Species Management Research Program","usgsCitation":"Newton, T.J., Johnson, N.A., and Hu, D.H., 2023, U.S. Geological Survey science vision for native freshwater mussel research in the United States: U.S. Geological Survey Circular 1511, 15 p., https://doi.org/10.3133/cir1511.","productDescription":"vi, 15 p.","numberOfPages":"15","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-147504","costCenters":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"links":[{"id":420318,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/circ/1511/cir1511.XML"},{"id":420317,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/circ/1511/images/"},{"id":420316,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/cir1511/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"CIR 1511"},{"id":420329,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1511/cir1511.pdf","text":"Report","size":"29.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"CIR 1511"},{"id":420328,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/circ/1511/coverthb.jpg"}],"contact":"Program Coordinator, Species Management Research Program
Ecosystems Mission Area
U.S. Geological Survey
12201 Sunrise Valley Drive, Mail Stop 415
Reston, VA 20192
We used multi-component seismic data (including two-dimensional images of compressional-wave velocity [vP], shear-wave velocity [vS], the ratio of compressional-wave velocity to shear-wave velocity [vP/vS ratio], Poisson’s ratio [μ], and seismic reflections) along a transect across northeastern Edwards Air Force Base to investigate the upper few hundred meters of the subsurface. The shallow subsurface there is characterized by unconsolidated sediments (vP of less than 2,500 meters per second [m/s]; vS of less than 1,500 m/s) in the upper 40 meters (m), underlain by weathered granitic basement rock (vP of 2,500–4,000 m/s; vS of 1,500–2,700 m/s) to about 100 m depth and unweathered granitic basement rock (vP of 4,000–6,000 m/s; vS of 2,700–4,000 m/s). The depth to basement rock varies laterally along the transect by as many as tens of meters. The top of groundwater, as indicated by both the 1,500-m/s vP contour and measurements in five wells along the transect, is located 8–30 m below the surface. In places, the top of groundwater is vertically offset over short lateral distances, likely the result of fault barriers. Faults mapped at the surface along the northeastern part of the transect correlate with multiple seismic indicators of faulting at the same locations. These same indicators show evidence for faulting in several other places along the transect beneath the alluvium. A major zone of faulting is apparent near the center of the seismic profile and is characterized by offsets in the top of groundwater; diffractions on the reflection image; a near-vertical zone of low vS; a corresponding near-vertical, shallow-depth zone of high vP relative to adjacent rocks (indicating high saturation); a near-vertical zone of high vP/vS ratios; and a near-vertical zone of high Poisson’s ratios (also indicating saturation). Many of these anomalies extend at least 400 m deep, reaching into granitic basement rock and indicating that the fault zone is water-saturated to those depths. There is likely vertical flow of contaminants along these fault zones, which are apparently barriers to the lateral flow of groundwater. The major central fault zone marks a boundary beyond which contaminant flow is apparently impeded. Along the southwestern part of the transect, there are also areas with similar indicators of faulting, but these appear to be smaller fault zones.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231018","collaboration":"Prepared in cooperation with the U.S. Air Force","usgsCitation":"Catchings, R.D., Goldman, M.R., Chan, J.H., Sickler, R.R., and Criley, C.J., 2023, Seismic images and subsurface structures of northeastern Edwards Air Force Base, Kern County, California: U.S. Geological Survey Open-File Report 2023–1018, 29 p., https://doi.org/10.3133/ofr20231018.","productDescription":"Report: vii, 29 p.,; Data Release; 8 Figures","numberOfPages":"29","onlineOnly":"Y","ipdsId":"IP-139215","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":499769,"rank":12,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115219.htm","linkFileType":{"id":5,"text":"html"}},{"id":420028,"rank":11,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ZAM79S","text":"Data release for a 2020 high-resolution seismic survey across northeastern Edwards Air Force Base, Kern County, California","description":"Goldman, M.R., Catchings, R.D., Chan, J.H., Criley, C.J., and Sickler, R.R., 2021, Data release for a 2020 high-resolution seismic survey across northeastern Edwards Air Force Base, Kern County, California: U.S. Geological Survey data release, https://doi.org/10.5066/P9ZAM79S."},{"id":420027,"rank":10,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/of/2023/1018/ofr20231018_figure14.pdf","text":"Figure 14","size":"2 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Two-dimensional Poisson’s ratio model along the Edwards seismic profile (Edwards Air Force Base, California), annotated with interpretative faults shown in figure 11."},{"id":420024,"rank":8,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/of/2023/1018/ofr20231018_figure08def.pdf","text":"Figure 8D, E, F","size":"11 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Unmigrated reflection image of the upper 400 meters (depth) along the Edwards seismic profile, Edwards Air Force Base, California."},{"id":420025,"rank":7,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/of/2023/1018/ofr20231018_figure08abc.pdf","text":"Figure 8A, B, C","size":"7 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Unmigrated reflection image of the upper 400 meters (depth) along the Edwards seismic profile, Edwards Air Force Base, California."},{"id":420023,"rank":6,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/of/2023/1018/ofr20231018_figure07a.pdf","text":"Figure 7A","size":"1.5 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Two-dimensional Poisson’s ratio model along the Edwards seismic profile (Edwards Air Force Base, California), derived from the tomographic compressional-wave velocity model and the multichannel analysis of surface waves shear-wave velocity model."},{"id":420022,"rank":5,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/of/2023/1018/ofr20231018_figure06a.pdf","text":"Figure 6A","size":"1.5 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Two-dimensional model of the ratio of compressional-wave velocity to shear-wave velocity along the Edwards seismic profile (Edwards Air Force Base, California), derived from the tomographic compressional-wave velocity model and the multichannel analysis of surface waves shear-wave velocity model."},{"id":420021,"rank":4,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/of/2023/1018/ofr20231018_figure05.pdf","text":"Figure 5","size":"1.5 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Two-dimensional shear-wave velocity model along the Edwards seismic profile (Edwards Air Force Base, California) developed from Rayleigh surface waves and the multichannel analysis of surface waves modeling technique."},{"id":420019,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1018/ofr20231018.pdf","text":"Report","size":"20 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":420018,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1018/covrthb.jpg"},{"id":420020,"rank":3,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/of/2023/1018/ofr20231018_figure04a.pdf","text":"Figure 4A","size":"1.5 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Two-dimensional compressional-wave velocity tomography model along the Edwards seismic profile (Edwards Air Force Base, California), generated using a subset of the seismic data with short offset distances between the shots and the receivers."},{"id":420026,"rank":9,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/of/2023/1018/ofr20231018_figure13.pdf","text":"Figure 13","size":"2 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Two-dimensional model of the ratio of compressional-wave velocity to shear-wave velocity along the Edwards seismic profile (Edwards Air Force Base, California), annotated with interpretive faults shown in figure 11"}],"country":"United States","state":"California","county":"Kern County","otherGeospatial":"Edwards Air Force Base","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -118.13696891699124,\n 35.05523690329453\n ],\n [\n -118.13696891699124,\n 34.719740760796995\n ],\n [\n -117.59793378058632,\n 34.719740760796995\n ],\n [\n -117.59793378058632,\n 35.05523690329453\n ],\n [\n -118.13696891699124,\n 35.05523690329453\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Earthquake Science Center
U.S. Geological Survey
350 N. Akron Road
Moffett Field, CA 94035
The Souris River Basin is an international basin in southeast Saskatchewan, north-central North Dakota, and southwest Manitoba. Sustained exceedances of water-quality objectives for total phosphorus, sodium, sulfate, total dissolved solids, and total iron have been reported since the late 1990s at the two binational sites on the Souris River (Souris River near Sherwood, North Dakota [U.S. Geological Survey station 05114000] and Souris River near Westhope, N. Dak. [U.S. Geological Survey station 05124000]). To understand conditions at the binational sites, it is important to understand water-quality changes on a basin-wide scale. Because streamflow is highly variable in the basin and changes in streamflow affect water-quality conditions, it is particularly important to use a trend-analysis method that accounts for changes in streamflow. Trends in water-quality concentrations can be affected by human-induced changes on the landscape or natural changes in land-runoff interactions that are driven by climate patterns and reflected by changes in streamflow (commonly referred to as “hydroclimatic variability”). In the primarily agricultural Souris River Basin, human-induced changes that are likely to affect trends are widespread changes in agricultural management such as fertilizer application, tilling practices, and crop types, as well as dam emplacement and artificial drainage. Around 1970, there was a long-term natural (hydroclimatic) change in the basin in which a significant transition from a dry climate state to a wet climate state resulted in higher streamflow in the basin. To assist the International Souris River Board in assessing current water-quality conditions in the Souris River Basin and exceedances of water-quality objectives at the binational sites, the U.S. Geological Survey, in cooperation with the International Joint Commission, completed a comprehensive analysis for selected ions, nutrients, and trace metals for many sites in the basin that included descriptive water-quality statistics, trend analysis using a trend method that considers interannual hydroclimatic variability, and an assessment of exceedances of the water-quality objectives for the binational sites.
Water-quality and streamflow or reservoir inflow or outflow data were compiled for 34 sites (30 stream sites and four reservoir sites) and 23 constituents with established water-quality objectives from 1970 to 2020 in the Souris River Basin and were used for descriptive statistics and water-quality trend analysis. Median total dissolved solids, sulfate, and sodium concentrations were low in the headwaters of the Souris River and some of the highest median concentrations were measured in the upper basin. At main-stem Souris River sites, all median sodium concentrations were greater than the binational water-quality objective. Median total phosphorus concentrations in the Souris River Basin were highest in the headwaters of the Souris River and all sites had median concentrations greater than the water-quality objective. Median total iron concentrations were highly variable across the basin, and for most main-stem sites, median concentrations were greater than or equal to the water-quality objective.
During the recent period (2009–19), the annual flow-averaged concentrations of total dissolved solids and sulfate increased for nearly all stream sites with most sites having mildly significant or significant increases. One-half of the sites had an annual flow-averaged geometric mean concentration greater than the total dissolved solids water-quality objective, and four sites had sulfate increases greater than 100 milligrams per liter. Trends in annual flow-averaged concentrations of sodium and chloride generally were small and nonsignificant. Most sites had concentrations greater than the sodium water-quality objective, whereas all sites had concentrations much less than the chloride water-quality objective. Annual flow-averaged geometric mean concentration of total phosphorus decreased for nearly all sites across the Souris River Basin, but all sites had concentrations greater than the total phosphorus water-quality objective for the entire period. Small and nonsignificant changes in annual flow-averaged geometric mean concentration of total iron were detected at all sites but the binational site at Sherwood, N. Dak., and by 2019 all sites had concentrations greater than the total iron water-quality objective. For the reservoir sites, during 2000–15, mostly significant increases for total dissolved solids, sulfate, and sodium were detected, whereas changes in total phosphorus and total iron were mixed.
During the historical period (1976–2019), large and consistent increases in total dissolved solids and sulfate have occurred since the late 1980s, with the largest increases and the most sites with mildly significant or significant increases generally occurring during the middle period (1988–2005). Large and significant or mildly significant increases in sodium concentrations occurred at eight of 10 sites in the middle period (1988–2005), and by the late period (2005–19) changes were small and nonsignificant. Similar to other basins in the region, such as the Red River of the North and Heart River, large and overall consistent increases since the late 1980s in total dissolved solids and sulfate in the Souris River Basin suggest that long-term natural (hydroclimatic) processes are large contributors to increases in the concentration of salts in streams and reservoirs associated with the onset of wetter conditions. The concurrent increases in sulfate and sodium concentrations at all sites during the middle period (1988–2005) suggest that sodium-sulfate evaporite dissolution may be a factor contributing to increases.
Total phosphorus concentrations oscillated between increasing and decreasing during the historical period, with concentrations increasing during the first trend period (1976–88) and decreasing in the fourth trend period (2009–19) to the lowest flow-averaged geometric mean concentration by 2019 for most sites. During the historical period, changes in total iron concentrations were mostly nonsignificant and generally small, and variability in total iron concentrations likely affected the ability to detect statistically significant changes in concentration.
The probability of exceeding the water-quality objective for total dissolved solids, sulfate, and sodium increased between 1976 and 2019 for the binational sites, especially for sulfate, which more than doubled for Souris River near Sherwood, N. Dak. and increased more than seven times for Souris River near Westhope, N. Dak. Total phosphorus and total iron concentrations for the binational sites were likely to exceed the water-quality objective for most of the year, but seasonal patterns of total phosphorus and total iron concentrations were different between the sites, suggesting that different factors may affect concentrations at different times of the year. For sodium, total phosphorus, and total iron, exceedance of the water-quality objective most of the time is not unexpected given that the flow-averaged geometric mean concentration for these three constituents for most sites across the basin are greater than the water-quality objective for most of the period. If natural processes are affecting total dissolved solids and sulfate concentrations, concentrations would be expected to vary with time, and as a result, extended periods of concentrations greater or less than the water-quality objective are likely to occur depending upon climatic conditions.
A better understanding of the state of water quality across the Souris River Basin is beneficial to understanding and interpreting water-quality conditions at the two Souris River binational sites. The most consistent spatial and temporal change observed for this study was large and consistent increases in sulfate and total dissolved solids among tributary and main-stem sites since the late 1980s. For sulfate and total dissolved solids, wetter climatic conditions combined with naturally occurring and abundant sources of sulfate likely contributed to sustained exceedances of water-quality objectives in recent decades, and extended periods of concentrations greater than or less than the water-quality objective are likely to occur depending on climatic conditions. For sodium, total iron, and total phosphorus, sustained exceedances of the current water-quality objective likely will continue because most sites across the basin had flow-averaged geometric mean concentrations greater than the water-quality objective; and during the 43-year period of analysis, regardless of climatic conditions, exceedances were consistently greater than the water-quality objective. Further investigation into the factors causing increasing sulfate concentrations and a better understanding of reservoir dynamics would enhance the understanding of changes in water-quality conditions in the Souris River Basin.
The basin-wide approach of this report provided an improved understanding of water-quality conditions in the Souris River Basin, and results can be used to inform the current water-quality objectives, inform potential changes to water management in the basin, and serve as a starting point for tracking future progress. Gaps in understanding of water-quality conditions can be closed through continued monitoring and further investigation into causes behind changes in water-quality conditions identified in this report.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235084","collaboration":"Prepared in cooperation with the International Joint Commission","usgsCitation":"Nustad, R.A., and Tatge, W.S., 2023, Comprehensive water-quality trend analysis for selected sites and constituents in the International Souris River Basin, Saskatchewan and Manitoba, Canada, and North Dakota, United States, 1970–2020: U.S. Geological Survey Scientific Investigations Report 2023–5084, 83 p., https://doi.org/10.3133/sir20235084.","productDescription":"Report: viii, 83 p.; 4 Linked Tables; Data Release; Dataset","numberOfPages":"98","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-142196","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":419898,"rank":5,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2023/5084/sir20235084_tables1.1-1.4.xlsx","text":"Appendix tables 1.1–1.4","size":"79.1 kB","linkFileType":{"id":3,"text":"xlsx"}},{"id":419895,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5084/sir20235084.pdf","text":"Report","size":"20.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023–5084"},{"id":419896,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5084/sir20235084.XML"},{"id":419899,"rank":6,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2023/5084/sir20235084_tables1.1-1.4.zip","text":"Appendix tables 1.1–1.4","size":"14 kB","linkFileType":{"id":7,"text":"csv"}},{"id":419897,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5084/images"},{"id":419894,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5084/coverthb.jpg"},{"id":419900,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9TZAQ75","text":"USGS data release","linkHelpText":"Data and scripts used in water-quality trend analysis in the International Souris River Basin, Saskatchewan and Manitoba, Canada, and North Dakota, United States, 1970–2020"},{"id":501048,"rank":10,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115217.htm","linkFileType":{"id":5,"text":"html"}},{"id":419901,"rank":8,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":419970,"rank":9,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235084/full","text":"Report","linkFileType":{"id":5,"text":"html"}}],"country":"Canada, United States","state":"Manitoba, North Dakota, Saskatchewan","otherGeospatial":"International Souris River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -105,\n 50.5\n ],\n [\n -105,\n 47.5\n ],\n [\n -99,\n 47.5\n ],\n [\n -99,\n 50.5\n ],\n [\n -105,\n 50.5\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Dakota Water Science Center
U.S. Geological Survey
821 East Interstate Avenue, Bismarck, ND 58503
1608 Mountain View Road, Rapid City, SD 57702
Digital flood-inundation maps for a 3.4-mile reach of Fourmile Creek at Silver Grove, Kentucky, were created by the U.S. Geological Survey (USGS) in cooperation with the City of Silver Grove and the U.S. Army Corps of Engineers Louisville District. Because the City of Silver Grove is subject to flooding from Fourmile Creek and the Ohio River (backwater flooding up Fourmile Creek), a set of flood-inundation maps was created, including maps for each flooding source considered independently and for possible scenarios involving flooding from both sources combined. The flood-inundation maps depict estimates of the areal extent and depth of flooding corresponding to a range of gage heights (gage height is commonly referred to as “stage,” or the water-surface elevation at a streamgage) at the USGS streamgage on Fourmile Creek at Grays Crossing at Silver Grove, Ky. (station number 03238785), and the USGS streamgage on Fourmile Creek at Highway 8 at Silver Grove, Ky. (station number 03238798). Near-real-time stages at these streamgages can be obtained from the USGS National Water Information System at https://waterdata.usgs.gov/. The USGS streamgage on the Ohio River at Cincinnati, Ohio (station number 03255000), is also important in this study because the National Weather Service (NWS) Advanced Hydrologic Prediction Service (AHPS; https://water.weather.gov/ahps/) forecasts flood hydrographs for this site (NWS AHPS site CCNO1). The peak-stage information forecast by the NWS AHPS can be used in conjunction with the maps developed in this study to show predicted areas of flood inundation.
Flood profiles were computed for the Fourmile Creek study reach by means of a one-dimensional, step-backwater hydraulic model (HEC-RAS) developed by the U.S. Army Corps of Engineers. The hydraulic model was calibrated by using the current stage-discharge relation (USGS rating number 1.1) at USGS streamgage 03238785, Fourmile Creek at Grays Crossing at Silver Grove, Ky. The model was then used to compute water-surface profiles for 83 combinations of flood stages on the Ohio River and Fourmile Creek ranging from approximately base flow to greater than a 2-percent annual exceedance probability flood in the model reach. An additional 50 water-surface profiles were computed for backwater-only flooding (from the Ohio River) for flood elevations (referenced to the North American Vertical Datum of 1988 [NAVD 88]) at 1-foot intervals referenced to USGS streamgage 03238798, Fourmile Creek at Highway 8 at Silver Grove, Ky.; these elevations ranged from approximately normal pool (460 ft, NAVD 88) to approximately a 0.2-percent annual exceedance probability flood (509 ft, NAVD 88) on the Ohio River. The computed water-surface profile information was then combined with a digital elevation model derived from light detection and ranging (lidar) data to delineate the approximate flooded areas.
The digital flood-inundation maps are available through the USGS Flood Inundation Mapper application (https://fim.wim.usgs.gov/fim/), which presents map libraries and provides detailed information on flood extent and depths for selected sites. The flood-inundation maps developed in this study, in conjunction with the real-time stage data from the USGS streamgages on Fourmile Creek at Silver Grove, Ky., and forecasted stream stages from the NWS AHPS, are intended to provide information that can help inform the public about potential flooding and provide emergency management personnel with a tool to efficiently manage emergency flood operations, such as evacuations and road closures, and assist in postflood recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235068","collaboration":"Prepared in cooperation with the City of Silver Grove and the U.S. Army Corps of Engineers Louisville District","usgsCitation":"Boldt, J.A., 2023, Flood-inundation maps for Fourmile Creek at Silver Grove, Kentucky: U.S. Geological Survey Scientific Investigations Report 2023–5068, 22 p., https://doi.org/10.3133/sir20235068.","productDescription":"Report: vii, 22 p.; Data Release","numberOfPages":"22","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-130251","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":500949,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115179.htm","linkFileType":{"id":5,"text":"html"}},{"id":418995,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9VJSH7D","text":"USGS data release","linkHelpText":"Geospatial datasets and model for the flood-inundation study of Fourmile Creek at Silver Grove, Kentucky"},{"id":418994,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5068/sir20235068.XML"},{"id":418993,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5068/images/"},{"id":418992,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235068/full","text":"Report","description":"SIR 2023-5068"},{"id":418991,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5068/sir20235068.pdf","text":"Report","size":"5.38 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5068"},{"id":418990,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5068/coverthb.jpg"}],"country":"United States","state":"Kentucky","city":"Silver Grove","otherGeospatial":"Fourmile Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -84.5333,\n 39.1333\n ],\n [\n -84.5333,\n 39.0167\n ],\n [\n -84.3583,\n 39.0167\n ],\n [\n -84.3583,\n 39.1333\n ],\n [\n -84.5333,\n 39.1333\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Ohio-Kentucky-Indiana Water Science Center
U.S. Geological Survey
5957 Lakeside Blvd.
Indianapolis, IN 46278-1996
Water withdrawn from rivers and streams accounts for approximately 80 percent of the public water supply in West Virginia. Localized and (or) seasonal droughts may threaten future water availability in the state, particularly in rural communities located in the headwaters of unregulated watersheds. Monthly water withdrawal data obtained from the West Virginia Department of Environmental Protection’s Large Quantity User program’s regulatory database was used to calculate all-time, seasonal, and monthly 75th quantile withdrawal rates for 109 public water system (PWS) intakes withdrawing from surface waters in West Virginia. A drought-vulnerability assessment value was calculated by comparing PWS withdrawal rates to the 1-day, 10-year hydrologically based streamflow statistic (1Q10) for 71 of the 109 PWS in locations with valid streamflow statistics. Withdrawal rates were evaluated against thresholds representing different levels of drought-related impacts from the West Virginia interagency drought plan and ecological-flow literature. The drought-vulnerability assessment found 33 of 71 PWS have 75th quantile withdrawal rates greater than 100 percent of 1Q10 streamflow. Forty-five of 71 PWS have 75th quantile withdrawal rates more than 10 percent of 1Q10 streamflow, suggesting some level of ecological impairment during severe drought. Additionally, a publicly available, near real-time drought-awareness web tool was created to compare the estimated withdrawal rate for 109 PWS to forecast streamflows from the National Water Model to support decision-making for emergency and water managers.
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Virginia\",\"nation\":\"USA \"}}]}","contact":"Director, Virginia and West Virginia Water Science Center
U.S. Geological Survey
1730 East Parham Road
Richmond, VA 23228
During 1989–92, an extensive rehabilitation project was completed in and around Delavan Lake, Wisconsin, to improve the lake’s water quality. However, in 2016, the lake was listed by the Wisconsin Department of Natural Resources as impaired for excessive algal growth (high chlorophyll a concentrations), and high phosphorus input was listed as its likely cause. In addition, the recent (2017–21) mean summer water clarity (as measured with a Secchi disk) was shallower than the goal set by the community (3.0 meters). Based primarily on flow and water-quality data collected in Jackson Creek, which is the main tributary of the lake, the mean annual phosphorus loading to the lake during water years (WYs) 2017–21 was 6,570 kilograms per year (kg/yr), and 306 kg/yr came from uncontrollable sources (atmospheric deposition and groundwater). Phosphorus loading during these years was about 48 percent higher than the long-term mean loading from WY 1984 to WY 2021. Based on results from Canfield-Bachmann phosphorus models, Carlson trophic state index relations, and the Jones and Bachmann chlorophyll a relation, external phosphorus loading would need to be decreased from 6,570 to 5,270 kg/yr (a 21-percent reduction in the potentially controllable external phosphorus load from the base period of WYs 2017–21) for chlorophyll a concentrations greater than 20 micrograms per liter to be detected no more than 5.0 percent of the time (the Wisconsin Department of Natural Resources criterion for chlorophyll a impairment for the lake). Based on Carlson trophic state index relations, external loading would need to be decreased from 6,570 to 4,380 kg/yr (a 35-percent reduction in the potentially controllable external phosphorus load) for summer mean Secchi depths to increase to 3.0 meters. Therefore, for Delavan Lake to reach the water-quality criteria for impairment and the goals for all three water-quality constituents, a 35-percent reduction in the potentially controllable phosphorus load is needed, which equates to a reduction in total phosphorus loading from 6,570 to 4,380 kg/yr. A 35-percent reduction in phosphorus loading to improve the water quality of Delavan Lake is less than the 49-percent reduction in phosphorus loading required for the area near Delavan Lake to improve the water quality of the Rock River and its tributaries indicated in the Rock River total maximum daily load.
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U.S. Geological Survey
1 Gifford Pinchot Drive
Madison, WI 53726