The U.S. Geological Survey, in cooperation with the Upper Gunnison River Water Conservancy District, studied historical streamflow in a reach of the East River, Colorado, to gain a preliminary understanding of return flow dynamics. Return flow is agricultural irrigation water that is not consumed by evapotranspiration and instead reaches streams by surface and subsurface flow paths. The study reach had a contributing area of 50 square miles and contained 5.23 square miles of pastures irrigated with water diverted from the East River and its tributaries. By comparing upstream inflows to downstream outflows, the net water balance of the study reach from 1994 to 2023 was assessed.
Two general hydrologic conditions for the study reach were identified. One hydrologic condition was characterized by a net loss or consumption of water, termed here as general deficit. This general deficit condition extended about 16 years, from 1997 to 2012. During general deficit years, there was usually a notable net loss of streamflow from April through July, and a small net gain, possibly related to return flows, occurred in August about 75 days after the minimums for losses. The second hydrologic condition was characterized by a net gain of water, termed here as general surplus. This second condition extended about 10 years, from 2014 to 2023. During general surplus years, two separate transitions from net loss to net gain commonly occurred during June through August. Losses during general surplus years were smaller than losses during general deficit years, the respective gains were larger, and times between losses and gains were about 18 and 22 days.
Differences between the two hydrologic conditions could reflect interactions among irrigation water, available capacity to store additional shallow groundwater, and streamflow. However, deciphering the causes for the shifts between the two general hydrologic conditions was beyond the scope of this report.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/ofr20241075","collaboration":"Prepared in cooperation with Upper Gunnison River Water Conservancy District","usgsCitation":"Bern, C.R., and Gidley, R.G., 2024, Agricultural return flow dynamics on a reach of the East River, Colorado, as assessed by mass balance: U.S. Geological Survey Open-File Report 2024–1075, 10 p., https://doi.org/10.3133/ofr20241075.","productDescription":"Report: iv, 10 p.; Database","onlineOnly":"Y","ipdsId":"IP-170543","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":494235,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118077.htm","linkFileType":{"id":5,"text":"html"}},{"id":465116,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20241075/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2024-1075"},{"id":465073,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2024/1075/ofr20241075.xml"},{"id":465072,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2024/1075/images"},{"id":464952,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2024/1075/ofr20241075.pdf","text":"Report","size":"1.73 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2024-1075"},{"id":464954,"rank":3,"type":{"id":9,"text":"Database"},"url":"http://doi.org/10.5066/F7P55KJN","text":"USGS water data for the Nation","linkHelpText":"U.S. Geological Survey National Water Information System database, accessed June 15, 2024"},{"id":464951,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2024/1075/coverthb.jpg"}],"country":"United states","state":"Colorado","otherGeospatial":"East River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -106.966667,\n 38.8333\n ],\n [\n -106.966667,\n 38.6333\n ],\n [\n -106.766667,\n 38.6333\n ],\n [\n -106.766667,\n 38.8333\n ],\n [\n -106.966667,\n 38.8333\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Colorado Water Science Center
U.S. Geological Survey
Box 25046, Mail Stop 415
Denver, CO 80225
This report addresses system characterization of the Earth Surface Mineral Dust Source Investigation (EMIT) sensor, an imaging spectrometer developed by the National Aeronautics and Space Administration. This report is part of a series of system characterization reports produced and delivered by the U.S. Geological Survey Earth Resources Observation and Science Cal/Val Center of Excellence. These reports present and detail the methodology and procedures for characterization; present technical and operational information about the specific sensing system being evaluated; and provide a summary of test measurements, data retention practices, data analysis results, and conclusions.
The Earth Resources Observation and Science Cal/Val Center of Excellence system characterization team completed data analyses to characterize the geometric (interior and exterior) and radiometric performances. Results of these analyses indicate that the EMIT sensor has a band-to-band geometric performance in the range of −0.355 to 0.210 pixel with a few exceptions of shortwave infrared channels. Geometric offset relative to the Landsat 8 Operational Land Imager ranged from −15.966 meters (−0.266 pixel) to 43.844 meters (0.731 pixel). Offset of a radiometric comparison ranged from −0.016 to 0.025, and slope of a radiometric comparison ranged from 0.837 to 0.985. EMIT agreed with Radiometric Calibration Network measurements within 5 percent across most of the spectral channels.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211030R","usgsCitation":"Shrestha, M., Sampath, A., Kim, M., and Park, S., 2024, System characterization report on the Earth Surface Mineral Dust Source Investigation (EMIT) sensor, chap. R of Ramaseri Chandra, S.N., comp., System characterization of Earth observation sensors: U.S. Geological Survey Open-File Report 2021–1030, 27 p., https://doi.org/10.3133/ofr20211030R.","productDescription":"vi, 27 p.","numberOfPages":"38","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-167707","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":464759,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20211030R/full"},{"id":464758,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1030/r/images/"},{"id":464755,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1030/r/coverthb.jpg"},{"id":464756,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1030/r/ofr20211030r.pdf","text":"Report","size":"6.35 MB","description":"OFR 2021–1030–R"},{"id":464757,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1030/r/ofr20211030r.XML"}],"contact":"Director, Earth Resources Observation and Science Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD 57198
Conducting detailed investigations of large landslides is difficult, especially in the subsurface, largely due to environmental factors such as steep slopes, difficult access, and numerous objective hazards. These factors have made it challenging to accurately estimate the depth to the failure surface of the Barry Arm landslide, a large (roughly 108 cubic meters), deep-seated bedrock landslide in Prince William Sound, Alaska, recognized in 2019. The landslide has exhibited accelerated movement in recent years and poses a potential tsunamigenic hazard if rapid failure occurs. Failure surface depth, equivalent to landslide thickness, is a necessary metric for landslide-volume calculations and associated tsunami wave models. In this report, we used seismic noise recorded by a seismometer located on the Barry Arm landslide in Alaska to calculate the horizontal-to-vertical spectral ratio (HVSR) to investigate the site fundamental frequency (f0) and depth of the failure surface. To ensure that observed peak frequencies in the spectral ratio were related to the underlying stratigraphy (and not caused by other noise sources like nearby glaciers, topographic resonance, weather, or human activities), we also calculated HVSRs using earthquake signals, HVSRs at other seismic stations within a 2.5-kilometer radius, and a standard spectral ratio between the landslide station and other sites. We observed multiple peaks in the landslide HVSR curves at 1.5 hertz (Hz), 4–5 Hz, and 7–11 Hz. The frequencies of these peaks were consistent at the landslide site through time and across methods and were dissimilar to those identified at other seismic stations in the area, making it unlikely the peaks were caused by local noise.
Directional HVSRs calculated at 15-degree intervals showed amplification of the higher frequency peaks in the direction parallel to slip, indicating two-dimensional site effects. We used the distinct frequency peaks in the seismic record to develop a 4-layer conceptual model of the landslide wherein the top of the deepest layer represents the primary failure surface, or the boundary between damaged (mobile) and undamaged material. We inverted Rayleigh wave ellipticity curves within this 4-layer configuration with constraints on S-wave velocity and layer thickness based on analogous material properties identified in the literature. This was necessary absent any site-specific subsurface S-wave velocity data. The best-fitting models indicate a mean slope-normal depth to the failure surface of 188 (±9) meters (m), with additional stratigraphic boundaries at 4 and 20 m below ground surface, potentially representing layered motion. These results agree with and improve upon ranges estimated by previous studies and can support future modeling and assessment efforts at Barry Arm.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/ofr20241071","programNote":"Landslide Hazards Program","usgsCitation":"Collins, A.L., Allstadt, K.E., and Staley, D.M., 2024, Using the horizontal-to-vertical spectral ratio method to estimate thickness of the Barry Arm landslide, Prince William Sound, Alaska: U.S. Geological Survey Open-File Report 2024–1071, 25 p., https://doi.org/10.3133/ofr20241071.","productDescription":"vii, 25 p.","onlineOnly":"Y","ipdsId":"IP-164227","costCenters":[{"id":78941,"text":"Geologic Hazards Science Center - Landslides / Earthquake Geology","active":true,"usgs":true}],"links":[{"id":464747,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20241071/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2024-1043"},{"id":464705,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2024/1071/ofr20241071.xml"},{"id":464704,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2024/1071/images"},{"id":464670,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2024/1071/ofr20241071.pdf","text":"Report","size":"12.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2024-1071"},{"id":464669,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2024/1071/coverthb.jpg"},{"id":497896,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118058.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Alaska","otherGeospatial":"Barry Arm landslide","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -148.08474908024374,\n 61.17012644718048\n ],\n [\n -148.15558320312988,\n 61.17012644718048\n ],\n [\n -148.1702846248608,\n 61.12691732704323\n ],\n [\n -148.11415192370606,\n 61.12498100886924\n ],\n [\n -148.08474908024374,\n 61.17012644718048\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Geologic Hazards Science Center
U.S. Geological Survey
Box 25046, Mail Stop 966
Denver, CO 80225
An acoustic telemetry study was conducted during August 2023–February 2024 to evaluate outmigration behavior and survival of juvenile Chinook salmon (Oncorhynchus tshawytscha) in the Middle Fork Willamette River, Oregon, during an experimental operation that was designed to facilitate downstream passage through two reservoirs and two dams. The experimental operation consisted of lowering the water surface elevation of Lookout Point Reservoir by nearly 100 feet between August and December 2023, and passing water through regulating outlets at Lookout Point Dam. This operation was intended to reduce residence time for juvenile Chinook salmon in Lookout Point Reservoir so that these fish would enter the free-flowing Willamette River as quickly as possible. During our study, acoustic-tagged juvenile Chinook salmon were released weekly during late August to late October to determine how fish responded to the drawdown. Data collected during the study were analyzed using a temporally stratified multistate mark-recapture model. We found that Lookout Point Reservoir became isothermic during the drawdown and water temperature exceeded 18 degrees Celsius during most of September 2023. This appeared to adversely affect juvenile Chinook salmon because the proportion of tagged fish that were subsequently detected in the forebay of Lookout Point Dam following release at the head of Lookout Point Reservoir during August 30–September 29 ranged from 0.01 to 0.05 for weekly release groups. Detections increased to 0.44–0.52 for fish released later in the year when water temperatures decreased. We found that fish size was a significant predictor of survival as fork length was positively related to survival probability in reservoir and free-flowing river reaches of our study area, but negatively related to survival probability for fish passing Lookout Point Dam. We also found that increased regulating outlet flow at Lookout Point Dam resulted in increased survival probability for juvenile Chinook salmon and water temperature was inversely related to survival. Results from this study suggest that the drawdown failed to create conditions that facilitated downstream passage and survival of juvenile Chinook salmon through the Lookout Point Project. Our analysis provides insights into several key factors that influence survival. This information can be used by resource managers when considering revised operations that may lead to improved outmigration survival in the future.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20241069","collaboration":"Prepared in cooperation with U.S. Army Corps of Engineers","usgsCitation":"Hance, D.J., Kock, T.J., Kelley, J.R., Hansen, A.C., Perry, R.W., and Fielding, S.D., 2024, Outmigration behavior and survival of juvenile Chinook salmon (Oncorhynchus tshawytscha) in response to deep drawdown of the Lookout Point Project, Middle Fork Willamette River, Oregon: U.S. Geological Survey Open-File Report 2024–1069, 20 p., https://doi.org/10.3133/ofr20241069.","productDescription":"Report: vii, 20 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-169049","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":497903,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118055.htm","linkFileType":{"id":5,"text":"html"}},{"id":464547,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2024/1069/coverthb2.jpg"},{"id":464548,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2024/1069/ofr20241069.pdf","text":"Report","size":"5.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2024-1069"},{"id":464549,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20241069/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2024-1069"},{"id":464552,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2024/1069/ofr20241069.XML"},{"id":464551,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2024/1069/images"},{"id":464550,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P14BRZVC","text":"USGS data release","description":"USGS data release","linkHelpText":"Acoustic-tagged juvenile Chinook salmon (Oncorhynchus tshawytscha) detections in Lookout Point Reservoir and downstream in the Middle Fork Willamette River, Oregon"}],"country":"United States","state":"Oregon","otherGeospatial":"Lookout Point Project, Middle Fork Willamette River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.83475416812524,\n 43.945953407421115\n ],\n [\n -122.83475416812524,\n 43.89190767942003\n ],\n [\n -122.73141100618557,\n 43.89190767942003\n ],\n [\n -122.73141100618557,\n 43.945953407421115\n ],\n [\n -122.83475416812524,\n 43.945953407421115\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
Pacific Coastal and Marine Science Center
U.S. Geological Survey
2885 Mission St.
Santa Cruz, CA 95060
The purpose of this report is to provide the Marine Corps with an annual summary of abundance, breeding activity, demography, and habitat use of endangered Least Bell’s Vireos (Vireo bellii pusillus) at Marine Corps Base Camp Pendleton, California (MCBCP or Base). Surveys for the Least Bell's Vireo were completed at MCBCP between April 11 and July 20, 2023. Core survey areas and a subset of non-core areas in drainages containing riparian habitat suitable for vireos were surveyed two to four times. We detected 561 territorial male vireos and 28 transient vireos in core survey areas. An additional 103 territorial male vireos and 15 transients were detected in non-core survey areas. Transient vireos were detected on 10 of the 15 drainages/sites surveyed (core and non-core areas). In core survey areas, 90 percent of vireo territories were on the four most populated drainages, with the Santa Margarita River containing 72 percent of all territories in core areas surveyed on Base. In core areas, 79 percent of male vireos were confirmed as paired; 69 percent of male vireos in non-core areas were confirmed as paired.
The number of documented Least Bell’s Vireo territories in core survey areas on MCBCP decreased 2 percent from 2022. In two core survey area drainages, the number of territories increased by at least three, and in two core survey area drainages, the number of vireo territories decreased by at least four between 2022 and 2023. The number of vireo territories at the lower San Luis Rey River increased 2 percent from 2022, in contrast to the decrease at MCBCP; however, this change was negligible overall. Although the 10-percent decrease at Marine Corps Air Station, Camp Pendleton from 2022 to 2023 was superficially less trivial, this 10-percent decrease represented the loss of a single territory. The proportion of surveys during which Brown-headed Cowbirds (Molothrus ater) were detected decreased to 0.20 from a peak of 0.45 in 2022. Cowbirds were detected from April through July in 2023.
Most core-area vireos (62 percent, including transients) used mixed willow (Salix spp.) riparian habitat. An additional 7 percent of birds occupied willow habitat co-dominated by Western sycamores (Platanus racemosa) or Fremont cottonwoods (Populus fremontii). Riparian scrub dominated by mule fat (Baccharis salicifolia), sandbar willow (S. exigua), or blue elderberry (Sambucus mexicana) was used by 29 percent of vireos. Habitat dominated by coast live oak (Quercus agrifolia) and sycamore or non-native habitat was used by 1 percent of vireos; fewer than 1 percent of vireo territories were in upland scrub and habitat dominated by white alder (Alnus rhombifolia).
In 2019, MCBCP began operating an artificial seep along the Santa Margarita River; then in 2021, two additional artificial seeps became operational. The artificial seeps pumped water to the surface starting in March and ending in August each year during daylight hours and were designed to increase the amount of surface water present to enhance Southwestern Willow Flycatcher (Empidonax traillii extimus) breeding habitat. Although this enhancement was designed to benefit flycatchers, few flycatchers have inhabited MCBCP, including the seep areas, within the past several years; therefore, vireos were selected as a surrogate species to determine effects of the habitat enhancement. This report presents the fourth year of analyses of vireo and vegetation response to the artificial seeps.
In 2020, we established four study sites along the Santa Margarita River, two surrounding and extending downstream of seep pumps at the Old Treatment Ponds and along Pump Road, and two Reference sites in similar habitat but further downstream of the Seep sites. In 2023, seep pumps at one Seep site did not function, and we recategorized that study site as Intermediate. Soil moisture was higher at sites that had surface water augmentation (Seep and Intermediate sites) than at the Reference site, and soil moisture also decreased with increasing distance from the seep pumps. We sampled vegetation at these sites to determine the effects of surface water enhancement by seep pumps. Soil moisture was positively related to total foliage cover, woody cover, and native herbaceous cover below 1 meter (m), and also positively related to native herbaceous cover between 1 and 2 m. The Seep site had greater total vegetation cover in the understory (71–79 percent) than the Intermediate (52–66 percent) and Reference (61–69 percent) sites. Total herbaceous cover below 3 m was higher at the Seep site than at the Intermediate site; total herbaceous cover between 1 and 3 m was higher at the Seep site than at the Reference sites. Native herbaceous cover below 3 m was greater at the Seep site than at the Reference sites; native herbaceous cover between 2 and 3 m was also greater at the Seep site than at the Intermediate site. Non-native cover below 3 m was greater at Seep and Reference sites than at the Intermediate site. We found no difference in woody cover among site types at any height.
Vireo territory density among the Seep, Intermediate, and Reference sites was similar before the seep pumps were installed. However, vireo territory density at Seep and Intermediate sites combined was significantly higher than at Reference sites after the seep pumps were installed.
The U.S. Geological Survey has been color banding Least Bell’s Vireos on Marine Corps Base Camp Pendleton since 1995. By the end of 2022, over 1,000 Least Bell’s Vireos had been color banded on Base. In 2023, we continued to color band and resight color banded Least Bell’s Vireos to evaluate adult survival, site fidelity, between-year movement, and the effect of surface water enhancement on vireo return rate, site fidelity, and between-year movement. We banded 180 Least Bell's Vireos for the first time during the 2023 season, including 1 adult vireo and 179 nestlings. Adult vireos were banded with unique color combinations, whereas nestlings were banded with a single gold numbered federal band on the right leg.
We resighted 57 Least Bell's Vireos on Base in 2023 that had been banded before the 2023 breeding season, 20 of which we were unable to identify. Of the 37 that we could identify, 34 were banded on Base, 2 were originally banded on the San Luis Rey River, and 1 was banded at Marine Corps Air Station, Camp Pendleton. Adult birds of known age ranged from 1 to 8 years old.
Base-wide survival of vireos was affected by sex, age, and year. Males had significantly higher annual survival than females. Adults had higher annual survival than first-year vireos. Survival for adults and first-year birds was lowest from 2020 to 2021 and highest from 2007 to 2008 and from 2012 to 2013. The return rate of adult vireos to Seep, Intermediate, or Reference sites was not affected by the original banding site (Seep versus Intermediate versus Reference).
Most returning adult vireos, predominantly males, showed strong between-year site fidelity. Of the adults present in 2022, 88 percent (96 percent of males; 25 percent of females) returned in 2023 to within 100 m of their previous territory. The discrepancy between male and female return rates follows the pattern observed in previous years. The average between-year movement for returning adult vireos was 0.4±1.9 kilometers (km). The average movement of first-year vireos detected in 2023 that fledged from a known nest on MCBCP in 2022 was 0.9±0.5 km.
We monitored Least Bell's Vireo pairs to evaluate the effects of surface water enhancement on nest success and breeding productivity. We monitored vireo nesting activity at 13 territories in the Seep site, 12 territories at the Intermediate site, and 25 territories in the Reference sites between April 8 and July 26. All territories except one at a Seep site and one at a Reference site were occupied by pairs, and all were fully monitored, meaning that all nesting attempts were monitored at these territories. During the monitoring period, 99 nests (26 in the Seep site, 28 at the Intermediate site, and 45 in Reference sites) were monitored.
Breeding productivity was similar among Seep, Intermediate, and Reference sites (2.9, 3.6, and 3.0 young fledged per pair, respectively), and a similar percentage of pairs at Seep, Intermediate, and Reference sites fledged at least 1 young (83, 83, and 96 percent, respectively). Other measures of breeding productivity were also similar among Seep, Intermediate, and Reference site pairs. According to the best model, daily nest survival in 2023 was not related to site. Fledging success appeared lower at Intermediate and Seep sites than at the Reference sites in 2023 (48, 46, and 67 percent, respectively), although the difference was not statistically significant. Predation was believed to be the primary source of nest failure at all sites. Predation accounted for 85, 77, and 71 percent of nest failures at Seep, Intermediate, and Reference sites, respectively. Failure of the remaining nests was attributed to infertile eggs, collapse of the vegetation supporting the nest, and other unknown causes. We found no relationships between vireo productivity and understory (below 3 m) vegetation cover.
Vireos placed their nests in 15 plant species in 2023. We found few differences in nest placement between successful and unsuccessful vireo nests. At Reference sites, successful vireo nests were placed slightly but significantly higher in the vegetation than unsuccessful nests, and at Intermediate sites, successful nests were placed significantly closer to the edge of the nest plant than unsuccessful nests. We did not find differences in nest placement among Seep, Intermediate, and Reference sites.
We found that as bio-year precipitation increased, the number of fledglings produced per vireo pair also increased. We did not find a link between bio-year precipitation and adult survival.
Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
This report addresses system characterization of the Airbus Vision-1 satellite and is part of a series of system characterization reports produced and delivered by the U.S. Geological Survey Earth Resources Observation and Science Cal/Val Center of Excellence. These reports present and detail the methodology and procedures for characterization; present technical and operational information about the specific sensing system being evaluated; and provide a summary of test measurements, data retention practices, data analysis results, and conclusions.
Vision-1 is a high-resolution Earth observation satellite launched in September 2018 as a collaborative effort between Airbus and Surrey Satellite Technology Ltd. It features a Newtonian telescope with a refractive relay, capturing images in panchromatic and multispectral bands. Operating in a Sun-synchronous orbit at an altitude of 583 kilometers, Vision-1 ensures consistent illumination conditions during image acquisition. It has a revisit time of 1 to 8 days depending on latitude and viewing angle, and it features an off-pointing agility of plus or minus 45 degrees, allowing for multiple target captures in a single pass using spot, strip, and mosaic imaging modes. The panchromatic band offers a resolution of 0.87 meter (m), whereas the multispectral bands (blue, green, red, and near infrared) provide a resolution of 3.48 m. These capabilities support a variety of applications including urban planning, agricultural monitoring, land classification, natural resource management, and disaster response. More information on the Vision-1 satellite and sensors is available in the “2022 Joint Agency Commercial Imagery Evaluation—Remote Sensing Satellite Compendium.”
The Earth Resources Observation and Science Cal/Val Center of Excellence system characterization team completed data analyses to characterize the geometric (interior and exterior), radiometric, and spatial performances. Results of these analyses indicate that the Vision-1 satellite has an interior geometric performance in the range of 0 to 0.02 m in easting and −0.01 to 0.03 m in northing in band-to-band registration, an exterior geometric performance of 1.7 to 2.2 m in easting and −1.1 to −0.7 m in northing offset with a 90-percent circular error of 3.4 to 3.7 m, a radiometric performance in the range of −0.029 to 0.017 in offset and 0.884 to 0.984 in slope, and a spatial performance in the range of 0.992 to 1.092 pixels for multispectral full width at half maximum and 1.895 pixels for the panchromatic band full width at half maximum, with a modulation transfer function at a Nyquist frequency in the range of 0.29 to 0.36 for the multispectral bands and 0.05 for the panchromatic band.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211030Q","usgsCitation":"Vrabel, J.C., Bresnahan, P., Sampath, A., Kim, M., Park, S., and Clauson, J., 2024, System characterization report on Vision-1, chap. Q of Ramaseri Chandra, S.N., comp., System characterization of Earth observation sensors: U.S. Geological Survey Open-File Report 2021–1030, 14 p., https://doi.org/10.3133/ofr20211030Q.","productDescription":"iv, 14 p.","numberOfPages":"22","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-168556","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":464467,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1030/q/coverthb.jpg"},{"id":464468,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1030/q/ofr20211030q.pdf","text":"Report","size":"1.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021–1030–Q"},{"id":464469,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1030/q/ofr20211030q.XML"},{"id":464470,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1030/q/images/"},{"id":464471,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20211030Q/full"}],"contact":"Director, Earth Resources Observation and Science Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD 57198
The U.S. Geological Survey (USGS) developed and released a survey to assess the terrestrial analog needs of the planetary science community. The goal was to assess the current state of terrestrial analog studies and determine community needs related to the use of field sites for training and research, data dissemination and archiving, and sample collections.
The survey was designed to gather feedback from community members who have a self-described interest in the use of terrestrial analogs. The web-based questionnaire contained a total of 33 questions and was designed to take <10 minutes to complete. The questionnaire was divided into four sections: (1) “Respondent Details,” (2) “Field Analog Use,” (3) “Data Portal Use,” and (4) “Geologic Materials Collection Use.” Comment boxes were provided for 12 of the 33 questions, which allowed respondents to provide more detailed comments to individual questions. The questionnaire received a total of 248 responses. We identified 21 notable findings which are matched with one or more recommendations to be addressed by the planetary science community.
In general, the findings highlight the importance of terrestrial analog studies to the planetary science community. The findings address how and why the community uses terrestrial analogs, areas in which further support can lead to a greater return on investment, and how the community can better manage data and samples from these studies.
The results from this survey identify a need for additional training opportunities and analog-focused workshops. There is a gap in formal education related to field techniques for a significant part of researchers who conduct fieldwork. There is also a subset of the community who are interested in conducting field-based studies but are, however, unaware of relevant sites and methods. Workshops would provide an opportunity for scientists at all career stages to share their results and discuss common challenges such as logistics, field safety, funding, and data and sample archiving. Trainings, workshops, and better communication may also lead to increased field-analog work at locations in closer proximity to home institutions, reducing costs associated with large field expeditions and ultimately leading to more available funding for more localized field studies.
The survey also shows that the ability to archive a diverse array of field data is a major challenge for terrestrial studies and finds that existing practices are not compliant with National Aeronautics and Space Administration (NASA) data management policies. The survey points to a strong need for a central data repository, allowing for easier access to existing analog data and the archiving of new field data.
The community would benefit from additional physical sample archiving, consolidated into several key institutions to promote easier access, such as NASA and USGS centers. Though scientists would still need to acquire their own samples in the field for certain studies, many studies would benefit from an archive of existing samples and associated data for widely used analog sites, reducing redundant sampling practices.
This report finds that a coordinated effort to improve and standardize training, data archiving, sample curation, and communication regarding terrestrial analog studies will best serve the planetary science community in our exploration goals.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20241042","collaboration":"Prepared in cooperation with the National Aeronautics and Space Administration","usgsCitation":"Edgar, L.A., Rumpf, M.E., Skinner, J.A., Jr., Gullikson, A.L., Keszthelyi, L., Hunter, M.A., Gaither, T., 2024, Assessing community needs for terrestrial analog studies: U.S. Geological Survey Open-File Report 2024–1042, 63 p., https://doi.org/10.3133/ofr20241042.","productDescription":"iii, 63 p.","onlineOnly":"Y","ipdsId":"IP-124254","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":464364,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2024/1042/covrthb.jpg"},{"id":464365,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2024/1042/ofr20241042.pdf","text":"Report","size":"8 MB","linkFileType":{"id":1,"text":"pdf"}}],"contact":"Astrogeology Science Center
U.S. Geological Survey
2255 N. Gemini Dr.
Flagstaff, AZ 86001
Pesticide formulations containing the active ingredient antimycin–a (ANT–A) have been used by fisheries and aquaculture managers for several decades to remove nuisance fish species. Analytical methods for measuring ANT–A during pesticide treatments have been done using high performance liquid chromatography (HPLC) paired with multiple detection methods (for example, electrochemical, ultraviolet, fluorescence, mass spectrometry). However, instruments and analytical chemistry methods can advance over time because of the need to develop timely, reliable, cost effective, and reproducible methods. Subsequently, ANT–A analytical chemistry methods and sample processing techniques also have improved over the past several decades. In the present study, we describe a liquid chromatography–mass spectrometry method and its verification across three analysts. Each analyst group created a single calibration curve and verified ANT–A in a liquid formulation using the averaged total response of all major ANT–A homologs (A1, A3, A3, A4). The advantage of this technique is that it creates a more resilient ANT–A quantification method amendable to batch-batch differences in major homologs. The method demonstrated how ANT–A can be effectively measured with high accuracy (98–99 percent), precision (2.7–16.2 percent), and specificity within a pesticide liquid formulation using a method applicable for Federal registration requirements.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20241068","usgsCitation":"Saari, G.N., Steiner, J.N., Lada, B., and Carmosini, N., 2024, Determination of antimycin–a in a liquid formulation by high performance liquid chromatography–mass spectrometry: U.S. Geological Survey Open-File Report 2024–1068, 7 p., https://doi.org/10.3133/ofr20241068.","productDescription":"Report: vii, 7 p; Data Release","numberOfPages":"20","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-166047","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":464197,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2024/1068/ofr20241068.pdf","text":"Report","size":"671 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR-2024-1068"},{"id":464198,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2024/1068/images"},{"id":464200,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2024/1068/ofr20241068.XML","linkFileType":{"id":8,"text":"xml"},"description":"OFR-2024-1068"},{"id":464204,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/ofr20241068/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":464206,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1GT55QY","text":"USGS data release","linkHelpText":"Data release for determination of antimycin–a in liquid formulation by high performance liquid chromatography–mass spectrometry"},{"id":464196,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2024/1068/coverthb.jpg"}],"contact":"Director, Upper Midwest Environmental Sciences Center
U.S. Geological Survey
2630 Fanta Reed Road
La Crosse, Wisconsin 54603
The Decompartmentalization Physical Model (DPM) was an experimental facility in the central Everglades operated between 2010 and 2022 to release high flows through a levee-enclosed area of degraded ridge and slough wetland that had been isolated from flow for sixty years. The purpose of DPM experimental program was to make measurements before, during, and after seasonal high-flow releases that could help guide the Congressionally authorized Everglades restoration project known as the Decompartmentalization and Sheet Flow Enhancement Project.
The DPM facility was operated by the South Florida Water Management District, with the U.S. Geological Survey (USGS) and several universities participating in experimental design and leading aspects of the research. The USGS research at DPM focused on measuring high-flow hydraulics and its sedimentary and ecological responses in downstream wetlands. USGS investigated interactions between flow and vegetation and microtopography that influenced flow velocity and water depth, bed shear stress, sediment entrainment, and the resulting downstream transport of suspended sediment and fate of particle-associated phosphorus. USGS also investigated high-flow changes in water-column mixing and gas exchange and resulting effects on metabolism of the aquatic ecosystem (primary productivity and respiration). USGS also investigated effects of built structures such as levee gaps that were constructed to reconnect levee-enclosed basins. This report describes the methods and results of the USGS-led data collection at DPM.
The USGS studies at DPM have identified factors that influence effectiveness of restoration, specifically how high-flow releases maximize sheet flow and affect sediment and nutrient dynamics while minimizing undesirable outcomes caused by past management that bypassed wetlands by conveying polluted water through canals to ecologically sensitive downstream areas. The DPM high-flow experiments reconnected the Water Conservation Area 3A and Water Conservation Area 3B basins, and it therefore has become a central feature of the restoration’s Decompartmentalization and Sheet Flow Enhancement Project. DPM’s scientific findings have already influenced the adaptive management of Everglades restoration in guiding elements of the final design and implementation of the Central Everglades Planning Project-South. In addition to serving Everglades restoration, the DPM has the potential to influence similar adaptive management programs throughout the nation’s network of federal and state-managed river corridors, floodplains, and riparian ecosystems.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/ofr20241063","usgsCitation":"Harvey, J., Choi, J., Larsen, L., Skalak, K., Maglio, M., Quion, K., Swartz, A., Lin, J.T.Y., Gomez-Velez, J., and Schmadel, N., 2024, High-flow experimental outcomes to inform Everglades restoration, 2010–22: U.S. Geological Survey Open-File Report 2024–1063, 72 p., https://doi.org/10.3133/ofr20241063.","productDescription":"Report: xi, 72 p.; 3 Data Releases","numberOfPages":"72","onlineOnly":"Y","ipdsId":"IP-148372","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":464267,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2024/1063/coverthb.jpg"},{"id":464268,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2024/1063/ofr20241063.pdf","text":"Report","size":"5.4 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":464271,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20241063/full"},{"id":464270,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2024/1063/images"},{"id":464269,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2024/1063/ofr20241063.XML"},{"id":464274,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9A9SQ85","text":"USGS Data Release","description":"Harvey, J.W., Choi, J., Quion, K., Lin, J.T., Swartz, A., Larsen, L.G., Haase, K., and Schmadel, N., 2024, High-flow Experimental Outcomes for Everglades Hydraulics and Aquatic Metabolism: U.S. Geological Survey, data release, https://doi.org/10.5066/P9A9SQ85.","linkHelpText":"- High-flow Experimental Outcomes for Everglades Hydraulics and Aquatic Metabolism"},{"id":464272,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9DQYB1O","text":"USGS Data Release","description":"Harvey, J.W., and Choi, J., 2022, Biophysical Data for Simulating Overland Flow in the Everglades: U.S. Geological Survey data release, https://doi.org/10.5066/P9DQYB1O.","linkHelpText":"- Biophysical Data for Simulating Overland Flow in the Everglades"},{"id":464273,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9SP0HM1","text":"USGS Data Release","description":"Harvey, J.W., Choi, J., Larsen, L., Skalak, K., Maglio, M.M., Quion, K.M., Lin, T., Psaltakis, J.W., Buskirk, B.A., Swartz, A.G., Lewis, J.M., Gomez-Velez, J.D., and Schmadel, N.M., 2022, High-Flow Field Experiments to Inform Everglades Restoration: Experimental Data 2010 to 2022 (ver. 2.0, October 2023): U.S. Geological Survey data release, https://doi.org/10.5066/P9SP0HM1.","linkHelpText":"- High-Flow Field Experiments to Inform Everglades Restoration: Experimental Data 2010 to 2022 (ver. 2.0, October 2023)"}],"country":"United States","state":"Florida","otherGeospatial":"Everglades","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -82.1076224101966,\n 26.691819233104567\n ],\n [\n -82.1076224101966,\n 24.751056659514802\n ],\n [\n -79.55347920896048,\n 24.751056659514802\n ],\n [\n -79.55347920896048,\n 26.691819233104567\n ],\n [\n -82.1076224101966,\n 26.691819233104567\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Water Resources Mission Area
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
Understanding the geomorphic processes and causes for long-term hydrogeomorphic changes along the Upper Mississippi River System (UMRS) is necessary for scientific studies ranging from habitat needs assessments, sediment transport, and nutrient processing, and making sound management decisions and prioritizing ecological restoration activities. From 2018 through 2020 the U.S. Geological Survey and U.S. Army Corps of Engineers led a series of calls and meetings, and a workshop to develop a draft UMRS hydrogeomorphic change conceptual model and hierarchical classification scheme. This project was funded through an Upper Mississippi River Restoration 2018 science in support of restoration proposal entitled, “Conceptual Model and Hierarchical Classification of Hydrogeomorphic Settings in the Upper Mississippi River System.” This report documents the background leading up to and the major findings from the workshop. The resulting conceptual model focuses on the drivers and boundary conditions that affect the major hydrogeomorphic processes along the valley corridor using a continuum of spatial and temporal scales and resolutions. The draft hierarchical classification was based on three existing and three new nested geospatial datasets that ultimately can be used to characterize hydrogeomorphic settings that span the UMRS valley corridor. The conceptual model and hierarchical classification will help characterize recent (mid-1990s through mid-2010s) decadal-scale processes and sources for potential hydrogeomorphic change that span a range of spatial scales from watershed hydrology and sediment sources to channel hydraulics and sediment transport.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20241051","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Fitzpatrick, F.A., Rogala, J.T., Hendrickson, J.S., Sawyer, L., Stone, J., Erwin, S., Brauer, E.J., and Vaughan, A.A., 2024, Upper Mississippi River System hydrogeomorphic change conceptual model and hierarchical classification: U.S. Geological Survey Open-File Report 2024–1051, 24 p., https://doi.org/10.3133/ofr20241051.","productDescription":"vi, 24 p.","numberOfPages":"34","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-154820","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":463608,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2024/1051/ofr20241051.pdf","text":"Report","size":"3.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2024–1051"},{"id":463607,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2024/1051/coverthb.jpg"},{"id":463611,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20241051/full"},{"id":463609,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2024/1051/ofr20241051.XML"},{"id":463610,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2024/1051/images/"},{"id":497918,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117772.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Illinois, Indiana, Iowa, Minnesota, Missouri, South Dakota, Wisconsin","otherGeospatial":"Upper Mississippi River System","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -87.50342683246095,\n 40.74721296729754\n ],\n [\n -86.22485822523954,\n 41.12212957640983\n ],\n [\n -86.47633619015835,\n 41.49085772032035\n ],\n [\n -87.70997806528162,\n 41.54161184649007\n ],\n [\n -87.96780499446993,\n 42.13710516972478\n ],\n [\n -88.45256695171824,\n 43.2601947483673\n ],\n [\n -88.90796053029793,\n 43.953704040844826\n ],\n [\n -89.31966888436784,\n 43.88619768580165\n ],\n [\n -88.82098034404291,\n 45.84620970391856\n ],\n [\n -89.77751644898966,\n 46.14284357021026\n ],\n [\n -92.3836871160787,\n 46.36717699384113\n ],\n [\n -93.57654031001726,\n 47.5843117955113\n ],\n [\n -96.69363739805445,\n 47.520997934475815\n ],\n [\n -96.5298693029927,\n 46.26717241479707\n ],\n [\n -97.88294379082475,\n 46.288663271101996\n ],\n [\n -96.96809715353103,\n 45.32804185048016\n ],\n [\n -95.79932895452089,\n 43.51835880034011\n ],\n [\n -93.73471399415848,\n 39.80187490699902\n ],\n [\n -90.99752932951242,\n 36.93622008574626\n ],\n [\n -89.6631770431625,\n 36.64968232220457\n ],\n [\n -89.28540446277691,\n 37.166100746132656\n ],\n [\n -87.50342683246095,\n 40.74721296729754\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"The Upper Floridan aquifer is the uppermost reliable groundwater source in southwest Georgia. The aquifer lies on top of the Claiborne, Clayton, and Cretaceous aquifers, all of which exhibited water-level declines in the 1960s and 1970s. The U.S. Geological Survey has been working cooperatively with Albany Utilities to monitor groundwater quality and availability in these aquifers since 1977.
Flow direction in the Upper Floridan aquifer is to the south and toward the Flint River. During the past 3 years, water levels varied above and below period-of-record median values. Water levels in the Upper Floridan aquifer were primarily above or at median levels during 2020 and 2021 and at or below median levels during 2022. Water levels in the Claiborne aquifer were above median levels, whereas water levels in the Clayton aquifer were at or below median levels, and in the Cretaceous aquifer system were close to median levels.
During January 2021, eight wells were sampled for major ions, including nitrate plus nitrite as nitrogen (N). Nitrate plus nitrite as N concentrations ranged from 2.3 to 10.5 milligrams per liter (mg/L). During December 2021, seven wells were sampled for major ions, including nitrate plus nitrite as N. Nitrate plus nitrite as N concentrations ranged from 3.9 to 9.9 mg/L. During November 2022, eight wells were sampled for major ions, including nitrate plus nitrite as N. Nitrate plus nitrite as N concentrations ranged from 3.9 to 10.0 mg/L. Two wells were also sampled for per- and polyfluoroalkyl substances during November 2022.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20241060","issn":"2331-1258","collaboration":"Prepared in cooperation with Albany Utilities","usgsCitation":"Gordon, D.W., 2024, Groundwater quality and groundwater levels in Dougherty County, Georgia, April 2020 through January 2023: U.S. Geological Survey Open-File Report 2024–1060, 14 p., https://doi.org/10.3133/ofr20241060.","productDescription":"Report: vi, 14 p.; Data Release","numberOfPages":"24","onlineOnly":"Y","ipdsId":"IP-148818","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":497924,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117773.htm","linkFileType":{"id":5,"text":"html"}},{"id":463594,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS Water Data for the Nation","linkHelpText":"- USGS NWIS database"},{"id":463593,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20241060/full","linkFileType":{"id":5,"text":"html"},"description":"OFR 2024-1060 HTML"},{"id":463592,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2024/1060/ofr20241060.XML","linkFileType":{"id":8,"text":"xml"},"description":"OFR 2024-1060 XML"},{"id":463591,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2024/1060/ofr20241060.pdf","size":"5.45 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2024-1060"},{"id":463590,"rank":2,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2024/1060/images"},{"id":463589,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2024/1060/coverthb.jpg"}],"country":"United States","state":"Georgia","county":"Dougherty County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-84.0186,31.6501],[-83.9997,31.6498],[-83.9933,31.6499],[-83.9937,31.6417],[-84.0002,31.6416],[-84.0028,31.6416],[-84.0028,31.6338],[-84.0124,31.6333],[-84.0123,31.6242],[-83.9957,31.6252],[-83.995,31.6156],[-83.995,31.6138],[-83.9959,31.6042],[-83.9964,31.5988],[-83.9964,31.5933],[-83.9965,31.5636],[-83.982,31.5633],[-83.9819,31.5519],[-83.9969,31.5517],[-83.9966,31.5307],[-83.9969,31.5107],[-83.9973,31.5002],[-83.9976,31.476],[-83.9826,31.4757],[-83.9824,31.4629],[-83.9974,31.4632],[-83.9977,31.444],[-83.9999,31.444],[-84.0192,31.4434],[-84.0358,31.4432],[-84.0648,31.4434],[-84.0975,31.4426],[-84.0991,31.4426],[-84.1227,31.4424],[-84.1377,31.4427],[-84.1388,31.4418],[-84.1409,31.4404],[-84.1506,31.4403],[-84.1565,31.4402],[-84.1581,31.4402],[-84.1742,31.4405],[-84.1989,31.4402],[-84.2112,31.4405],[-84.2117,31.4373],[-84.2117,31.436],[-84.239,31.4357],[-84.2498,31.436],[-84.2583,31.4359],[-84.2846,31.4361],[-84.3007,31.4363],[-84.3131,31.4362],[-84.3388,31.4363],[-84.3694,31.4364],[-84.4021,31.4365],[-84.4091,31.4364],[-84.43,31.4366],[-84.43,31.4375],[-84.429,31.4384],[-84.4284,31.4389],[-84.4279,31.4393],[-84.4285,31.4398],[-84.4285,31.4407],[-84.4285,31.4416],[-84.428,31.4421],[-84.4274,31.4426],[-84.4275,31.4435],[-84.4269,31.4439],[-84.4264,31.4444],[-84.4264,31.4453],[-84.4264,31.4462],[-84.4259,31.4462],[-84.4259,31.4471],[-84.4259,31.448],[-84.4254,31.448],[-84.4249,31.4485],[-84.4238,31.449],[-84.4233,31.4485],[-84.4227,31.4485],[-84.4222,31.4486],[-84.4216,31.449],[-84.4211,31.449],[-84.4206,31.4495],[-84.4201,31.4495],[-84.4195,31.4509],[-84.4196,31.4518],[-84.419,31.4522],[-84.4185,31.4532],[-84.4175,31.455],[-84.4169,31.4555],[-84.4159,31.4555],[-84.4143,31.4564],[-84.4137,31.4564],[-84.4127,31.4569],[-84.4127,31.4578],[-84.4127,31.4587],[-84.4132,31.4596],[-84.4138,31.4605],[-84.4138,31.4624],[-84.4138,31.4633],[-84.4144,31.4642],[-84.415,31.4651],[-84.4155,31.4651],[-84.4155,31.466],[-84.4161,31.4669],[-84.4166,31.4673],[-84.4172,31.4678],[-84.4177,31.4687],[-84.4177,31.4696],[-84.4183,31.4696],[-84.4183,31.4705],[-84.4183,31.4714],[-84.4188,31.4714],[-84.4188,31.4723],[-84.4194,31.4723],[-84.4205,31.4728],[-84.421,31.4732],[-84.4215,31.4732],[-84.4221,31.4737],[-84.4232,31.4736],[-84.4237,31.4736],[-84.4242,31.4745],[-84.4248,31.475],[-84.4248,31.4764],[-84.4254,31.4773],[-84.4254,31.4782],[-84.4259,31.4791],[-84.4265,31.4804],[-84.426,31.4818],[-84.4255,31.4818],[-84.4255,31.4827],[-84.4249,31.4828],[-84.4249,31.4837],[-84.4244,31.4846],[-84.4239,31.4851],[-84.4234,31.4851],[-84.4228,31.4864],[-84.4229,31.4892],[-84.4218,31.4901],[-84.4219,31.491],[-84.4224,31.4915],[-84.4224,31.4924],[-84.423,31.4928],[-84.4235,31.4933],[-84.4241,31.4942],[-84.4251,31.4946],[-84.4257,31.4951],[-84.4257,31.496],[-84.4257,31.4969],[-84.4257,31.4978],[-84.4263,31.4978],[-84.4268,31.4987],[-84.4274,31.4987],[-84.4279,31.4991],[-84.4284,31.4991],[-84.429,31.4996],[-84.4295,31.5005],[-84.429,31.5023],[-84.4307,31.5055],[-84.4318,31.5064],[-84.4323,31.5073],[-84.4329,31.5077],[-84.4334,31.5082],[-84.434,31.5087],[-84.4345,31.5091],[-84.4351,31.5091],[-84.4372,31.5086],[-84.4378,31.5095],[-84.4383,31.5104],[-84.4389,31.5122],[-84.4389,31.515],[-84.4389,31.5159],[-84.439,31.5168],[-84.439,31.5186],[-84.4395,31.5191],[-84.4401,31.5195],[-84.4396,31.5204],[-84.4396,31.5218],[-84.4396,31.5227],[-84.4401,31.5236],[-84.4402,31.5245],[-84.4412,31.5254],[-84.4418,31.5264],[-84.4418,31.5273],[-84.4418,31.5282],[-84.4424,31.5286],[-84.4429,31.5295],[-84.4435,31.53],[-84.4435,31.5309],[-84.444,31.5309],[-84.4446,31.5322],[-84.4446,31.5332],[-84.4446,31.5345],[-84.4447,31.5354],[-84.4452,31.5363],[-84.4458,31.5373],[-84.4463,31.5377],[-84.4463,31.5386],[-84.4469,31.5391],[-84.4474,31.5395],[-84.4474,31.5404],[-84.448,31.5413],[-84.4471,31.5425],[-84.4475,31.5432],[-84.4475,31.5441],[-84.4481,31.545],[-84.4486,31.5454],[-84.4502,31.5459],[-84.4508,31.5463],[-84.4519,31.5468],[-84.4524,31.5472],[-84.4529,31.5472],[-84.4535,31.5477],[-84.454,31.5476],[-84.4546,31.5481],[-84.4551,31.549],[-84.4551,31.5499],[-84.4552,31.5517],[-84.4552,31.5545],[-84.4552,31.5558],[-84.4552,31.5568],[-84.4547,31.5577],[-84.4542,31.5577],[-84.4542,31.5586],[-84.4548,31.5604],[-84.4543,31.5618],[-84.4543,31.5627],[-84.4543,31.5636],[-84.4538,31.565],[-84.4533,31.5655],[-84.4527,31.5659],[-84.4528,31.5668],[-84.4522,31.5687],[-84.4523,31.5696],[-84.4518,31.5723],[-84.4518,31.5737],[-84.4523,31.5746],[-84.4529,31.575],[-84.4535,31.5764],[-84.454,31.5769],[-84.454,31.5778],[-84.4546,31.5787],[-84.4541,31.5796],[-84.4546,31.5809],[-84.4552,31.5819],[-84.4557,31.5823],[-84.4563,31.5828],[-84.4568,31.5832],[-84.4573,31.5832],[-84.4574,31.5846],[-84.4569,31.5864],[-84.4558,31.5878],[-84.4553,31.5882],[-84.4553,31.5891],[-84.4548,31.5896],[-84.4542,31.5901],[-84.4537,31.5905],[-84.4543,31.5914],[-84.4538,31.5924],[-84.4532,31.5933],[-84.4522,31.5942],[-84.4506,31.5956],[-84.4501,31.5961],[-84.4495,31.5974],[-84.449,31.5984],[-84.4496,31.5993],[-84.4501,31.5997],[-84.4501,31.6011],[-84.4496,31.6016],[-84.4496,31.6025],[-84.4491,31.6025],[-84.4486,31.6029],[-84.448,31.6034],[-84.4475,31.6039],[-84.447,31.6048],[-84.447,31.6057],[-84.4476,31.6075],[-84.4476,31.6084],[-84.4493,31.6116],[-84.4488,31.613],[-84.4493,31.6134],[-84.4493,31.6143],[-84.4504,31.6143],[-84.4504,31.6152],[-84.4499,31.6166],[-84.4499,31.6175],[-84.4494,31.618],[-84.4494,31.6189],[-84.4499,31.6193],[-84.4505,31.6212],[-84.4505,31.6221],[-84.4328,31.6218],[-84.4016,31.6218],[-84.3887,31.6215],[-84.3699,31.6213],[-84.3435,31.6211],[-84.3182,31.6214],[-84.3005,31.6216],[-84.2978,31.6217],[-84.2892,31.6218],[-84.2553,31.6221],[-84.2499,31.6222],[-84.2317,31.6224],[-84.2048,31.6222],[-84.1994,31.6223],[-84.1924,31.6224],[-84.1801,31.6225],[-84.1575,31.6228],[-84.144,31.6229],[-84.1328,31.623],[-84.1306,31.623],[-84.108,31.6232],[-84.0983,31.6233],[-84.0822,31.623],[-84.0532,31.6233],[-84.043,31.6234],[-84.0424,31.6248],[-84.0425,31.6275],[-84.0414,31.6298],[-84.0409,31.6312],[-84.0409,31.6326],[-84.0409,31.6335],[-84.0394,31.6353],[-84.0367,31.6367],[-84.0362,31.6376],[-84.0351,31.6385],[-84.0351,31.6404],[-84.0351,31.6413],[-84.0341,31.6431],[-84.0335,31.6436],[-84.033,31.6436],[-84.0309,31.6431],[-84.0303,31.6427],[-84.0298,31.6436],[-84.0293,31.6445],[-84.0293,31.6455],[-84.0298,31.6468],[-84.0293,31.6477],[-84.0288,31.6486],[-84.0282,31.6487],[-84.0266,31.6491],[-84.025,31.6491],[-84.0229,31.6496],[-84.0218,31.6501],[-84.0213,31.6501],[-84.0196,31.6496],[-84.0186,31.6501]]]},\"properties\":{\"name\":\"Dougherty\",\"state\":\"GA\"}}]}","contact":"Director, South Atlantic Water Science Center
U.S. Geological Survey
1770 Corporate Drive, suite 500
Norcross, GA 30093
Contact Us- USGS Publications Warehouse
","tableOfContents":"More than 2 million Californians rely on groundwater from privately owned domestic wells for drinking-water supply. This report summarizes a water-quality survey of domestic and small-system drinking-water supply wells in the eastern Sacramento Valley and adjacent foothills where more than 25,000 residents are estimated to use privately owned domestic wells. Study results show that inorganic and organic constituents in groundwater were present above regulatory (maximum contaminant level, MCL) benchmarks for public drinking-water quality in 8 and 3 percent, respectively, of the aquifer area used for domestic drinking-water supply (herein, “domestic groundwater resources”; fig. 1).
The only inorganic constituent detected above regulatory benchmarks was arsenic. The only organic constituent exceeding regulatory benchmarks was the fumigant 1,2,3-trichloropropane (1,2,3-TCP). Three additional organic constituents—the disinfection by-product chloroform, the gasoline oxygenate methyl tert-butyl ether (MTBE), and the solvent tetrachloroethene (PCE)—were detected at low concentrations below one-tenth of regulatory benchmarks in 34, 10, and 10 percent of domestic groundwater resources, respectively. Total dissolved solids (TDS), iron, and manganese exceeded non-regulatory aesthetic guidelines for drinking water in 5, 10, and 26 percent of domestic groundwater resources, respectively. Per- and polyfluoroalkyl substances (PFASs) were detected in 29 percent of domestic groundwater resources,with 5 percent exceeding the recently enacted (April 2024) U.S. Environmental Protection Agency MCLs. Total coliform and enterococci bacteria were detected in 13 and 8 percent of domestic groundwater resources, respectively.
Redox sensitive constituents in this study included arsenic, manganese, nitrate, and iron. In the lower elevation portions of the eastern Sacramento Valley study area, reducing conditions in groundwater aquifers promote elevated arsenic, iron, and manganese, and conversely lower concentrations of nitrate. The presence of the volatile organic compound (VOC) 1,2,3-TCP was related to its past history in select agricultural land uses (on orchards or vineyards) in the Sacramento Valley; however, unlike in the San Joaquin Valley where orchards and vineyards are more common, its detection frequency was low (only detected in one well in this study). Chloroform was frequently detected in this study at low levels. Chloroform is a disinfection byproduct commonly found in domestic wells treated by shock chlorination. The solvent PCE is among the most frequently detected VOCs in groundwater, which is primarily related to its long history of use and its persistence in groundwater in oxic conditions. The gasoline oxygenate MTBE was a contaminant introduced to groundwater through atmospheric exchange when it was used as a fuel additive to decrease smog inducing emissions from vehicles. Its occurrence in groundwater at low levels is expected and makes it a potentially useful tracer of relatively recent recharge water being withdrawn from wells. The PFASs are anthropogenic chemicals with hundreds of uses, and they have been incorporated into many different products, processes, and applications worldwide. Like MTBE, the occurrence of PFASs in groundwater may be in part due to atmospheric exchange, but there are several other pathways that contribute PFASs to the environment.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20241061","collaboration":"Prepared in cooperation with California State Water Resources Control Board","usgsCitation":"Bennett, G.L., V, 2024, Quality of groundwater used for domestic supply in the eastern Sacramento Valley and adjacent foothills, California: U.S. Geological Survey Open-File Report 2024–1061, 15 p., https://doi.org/10.3133/ofr20241061.","productDescription":"15 p.","numberOfPages":"15","onlineOnly":"Y","ipdsId":"IP-150528","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":497891,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117769.htm","linkFileType":{"id":5,"text":"html"}},{"id":463494,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2024/1061/images"},{"id":463493,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2024/1061/ofr20241061.xml"},{"id":463495,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20241061/full"},{"id":463492,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2024/1061/ofr20241061.pdf","text":"Report","size":"10 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":463491,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2024/1061/covrthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Eastern Sacramento Valley and adjacent foothills","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.25,\n 40\n ],\n [\n -122.25,\n 38.666\n ],\n [\n -120.5,\n 38.666\n ],\n [\n -120.5,\n 40\n ],\n [\n -122.25,\n 40\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
Karst hydrogeologic systems represent challenging and unique conditions to scientists studying groundwater flow and contaminant transport. Karst terrains are characterized by distinct and beautiful landscapes, caverns, and springs, and many of the exceptional karst areas are designated as national or state parks. The range and complexity of landforms and groundwater flow systems associated with karst terrains are enormous, perhaps more than any other aquifer type. The U.S. Geological Survey (USGS) Karst Interest Group (KIG), formed in 2000, is a loosely knit, grassroots organization of USGS and non-USGS scientists and researchers devoted to fostering better communication among scientists working on, or interested in, karst aquifers. The primary mission of the KIG is to encourage and support interdisciplinary collaboration and technology transfer among scientists working in karst areas. To accomplish its mission, the KIG has organized a series of workshops. To date (2024), nine KIG workshops, including the workshop documented in this report, have been held. The abstracts and extended abstracts provide a snapshot in time of past and current karst related studies. The USGS Water Availability and Use Science Program funded the workshop and proceedings. The planning committee for the ninth workshop includes Thomas D. Byl (USGS and Tennessee State University), Allan K. Clark (USGS), Laura M. DeMott (USGS), Eve L. Kuniansky (USGS, Emeritus), Benjamin V. Miller (USGS), and Lawrence E. Spangler (USGS, Emeritus). The workshop proceedings are edited by Eve L. Kuniansky and Lawrence E. Spangler. The field trip guide was produced by Benjamin V. Miller and Brian Ham (Tennessee Department of Environment and Conservation) and included in the proceedings from the KIG’s 2021 virtual workshop to be used on the optional field trip held on Thursday, October 24, 2024.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20241067","usgsCitation":"Kuniansky, E.L., and Spangler, L.E., eds., 2024, U.S. Geological Survey Karst Interest Group proceedings, Nashville, Tennessee, October 22-24, 2024: U.S. Geological Survey Open-File Report 2024-1067, 109 p., https://doi.org/10.3133/ofr20241067.","productDescription":"iv, 109 p.","numberOfPages":"109","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-148827","costCenters":[{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true}],"links":[{"id":464512,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20241067/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2024-1067 HTML"},{"id":464367,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2024/1067/images/"},{"id":464366,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2024/1067/ofr20241067.XML","description":"OFR 2024-1067 XML"},{"id":462963,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20205019","text":"Scientific Investigations Report 2020–5019","linkHelpText":"- U.S. Geological Survey Karst Interest Group Proceedings, October 19–20, 2021"},{"id":462958,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2024/1067/coverthb.jpg"},{"id":462959,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2024/1067/ofr20241067.pdf","text":"Report","size":"5.85 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2024-1067 PDF"},{"id":499031,"rank":13,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117750.htm","text":"Results of tracer testing at Pah Tempe Hot Springs, Hurricane, Utah","linkFileType":{"id":5,"text":"html"}},{"id":499030,"rank":12,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117749.htm","text":"Modern cave monitoring informs interpretations of past climate change: applications to Titan cave, Wyoming","linkFileType":{"id":5,"text":"html"}},{"id":499029,"rank":11,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117748.htm","text":"Geophysical characterization of glacially influenced, submature karst drainage features in western New York","linkFileType":{"id":5,"text":"html"}},{"id":499028,"rank":10,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117747.htm","text":"Planned alternative water supply technologies utilizing the karst aquifers of Texas","linkFileType":{"id":5,"text":"html"}},{"id":499027,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117746.htm","text":"A karst-rich impact crater: drill cores from the Flynn Creek crater, north-central Tennessee","linkFileType":{"id":5,"text":"html"}},{"id":499026,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117745.htm","text":"The geologic framework of karst in Monroe County, West Virginia: a tale of two systems","linkFileType":{"id":5,"text":"html"}},{"id":499025,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117744.htm","text":"A national model of sinkhole susceptibility in karst and pseudokarst areas of the conterminous United States","linkFileType":{"id":5,"text":"html"}}],"contact":"Water Mission Area
U.S. Geological Survey
1770 Corporate Drive
Suite 500
Norcross, GA 30093
https://www.usgs.gov/mission-areas/
water-resources/science/karst-aquifers
Sediment from the Central Valley via the Sacramento-San Joaquin Delta (Delta) and Suisun Bay is a primary source of sand to San Francisco Bay, California. Sand is mined from San Francisco Bay for commercial purposes, such as for use in concrete for construction. To better understand the supply of sand to Suisun Bay and San Francisco Bay, the U.S. Geological Survey (USGS), in cooperation with the San Francisco Bay Estuary Institute (SFEI) and the San Francisco Bay Conservation Development Commission (BCDC), initiated this study to compile and synthesize historical data and estimate the total sediment and sand portion of sediment exiting the Delta to Suisun Bay for a 20-year period between water years 2001 and 2020.
Sediment exiting the Delta is a combination of suspended sediment and bedload sediment. Seaward bedload transport was estimated using bedload transport equations and available hydraulic data at the two downstream-most streamgages in the Delta (where velocity is measured). Those two streamgages are about 25 kilometers upstream from the “exit” of the Delta at Mallard Island. The combined average annual net (seaward) bedload at these two streamgages was estimated to be 0.102 million cubic meters per year (Mm3/yr) for the study period. This volume of bedload is equivalent to 0.155 million metric tons per year (Mt/yr), assuming a bulk density of 1.517 metric tons per cubic meter (t/m3). The bedload composition was estimated to be 88 percent sand.
Between the two streamgages and Mallard Island, an annual average of 0.076 Mm3/yr of material was removed through mining during the study period, of which 97.5 percent was sand. In addition, 0.053 Mm3/yr was removed through dredging to support shipping and navigation, of which 76 percent was sand. The total volume of mined and dredged sediment material was approximately 0.128 Mm3/yr, equivalent to 0.194 Mt/yr, assuming a bulk density of 1.517 t/m3.
Assuming the estimated bedload reaching Mallard Island was reduced by mining and dredging, a mean bedload flux of −0.009 Mm3/yr was computed (using a bulk density of 1.517 t/m3), suggesting a deficit or landward transport of bedload. However, the total suspended-sediment and suspended-sand flux was in the seaward direction. The average total suspended flux of sediment to Suisun Bay through the cross section at the Mallard Island streamgage was estimated to be 0.482 million metric tons per year (Mt/yr; 0.015 Mt/yr sand) in the seaward direction. The results indicate a net flux out of the Delta of 0.469 Mt/yr of total sediment and 0.003 Mt/yr of sand.
The primary limitation of the study was the lack of physical bedload measurements to validate the bedload estimates. To better refine the estimates of bedload, physical measurements of bedload or repeat bathymetry would be necessary for a range of flow conditions. Such measurements could be used to calibrate transport equations and quantify the uncertainty in such estimates.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20241055","collaboration":"Prepared in cooperation with the San Francisco Estuary Institute Aquatic Science Center, the California State Coastal Conservancy, and the San Francisco Bay Conservation and Development Commission","programNote":"Water Availability and Use Science Program","usgsCitation":"Marineau, M.D., Hart, D., Ely, C.P., and McKee, L., 2024, Sand supply to San Francisco Bay from the Sacramento and San Joaquin Rivers of the Central Valley, California: U.S. Geological Survey Open-File Report 2024–1055, 18 p., https://doi.org/10.3133/ofr20241055.","productDescription":"Report: viii, 18 p.; Data Release","numberOfPages":"18","onlineOnly":"Y","ipdsId":"IP-157560","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":463205,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2024/1055/images"},{"id":463204,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2024/1055/ofr20241055.xml"},{"id":463203,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2024/1055/ofr20241055.pdf","text":"Report","size":"6 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":463201,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9I18RGG","text":"USGS Data Release","description":"Ely, C.P., and Marineau, M.D., 2023, Estimated bedload transport rates at Rio Vista and Jersey Point, California, 2011–2020: U.S. Geological Survey data release, https://doi.org/10.5066/P9I18RGG.","linkHelpText":"Estimated bedload transport rates at Rio Vista and Jersey Point, California, 2011–2020"},{"id":497888,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117739.htm","linkFileType":{"id":5,"text":"html"}},{"id":463206,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/preview/ofr20241055/full"},{"id":463202,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2024/1055/covrthb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.29538442038356,\n 38.56577858557708\n ],\n [\n -122.29538442038356,\n 37.65383277017135\n ],\n [\n -121.19683028697757,\n 37.65383277017135\n ],\n [\n -121.19683028697757,\n 38.56577858557708\n ],\n [\n -122.29538442038356,\n 38.56577858557708\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
A continuous-flow streamside toxicity test was completed to evaluate the risk posed by the use of 4-nitro-3-(trifluoromethyl)phenol (TFM), used to control Petromyzon marinus (sea lamprey), to Percina caprodes (logperch). Logperch are a host fish to the parasitic glochidia life stage of the federally endangered Epioblasma triquetra (snuffbox mussel). Streams with an extant population of snuffbox must be treated before May 1, 2023, to prevent inadvertent take through TFM-related mortality of glochidia-infested fish. Although the concentration of TFM required to induce 99.9 percent mortality of sea lamprey was 6.52 milligrams per liter, the TFM required to induce 25 percent mortality of logperch was 10.14 milligrams per liter. Our data indicate that logperch are not as sensitive to TFM as previously suggested.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20241064","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service Sea Lamprey Control Program","usgsCitation":"Kirkeeng, C.A., Luoma, J.A., Schloesser, N., Schueller, J., and Kaye, C., 2024, Assessment of the sensitivity of Percina caprodes (logperch) to the pesticide 4-nitro-3-(trifluoromethyl)phenol: U.S. Geological Survey Open-File Report 2024–1064, 7 p., https://doi.org/10.3133/ofr20241064.","productDescription":"Report: vi, 7 p.; Data Release","numberOfPages":"18","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-161522","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":497880,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117735.htm","linkFileType":{"id":5,"text":"html"}},{"id":463108,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P14HHHKA","text":"USGS data release","linkHelpText":"Data and code release—Technical assistance bioassay to compare sea lamprey and logperch sensitivity to TFM"},{"id":463099,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20241064/full"},{"id":463097,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2024/1064/ofr20241064.XML"},{"id":463096,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2024/1064/ofr20241064.pdf","text":"Report","size":"1.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2024–1064"},{"id":463095,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2024/1064/coverthb.jpg"},{"id":463098,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2024/1064/images/"}],"country":"United States","state":"Michigan","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -83.8159644849273,\n 44\n ],\n [\n -85,\n 44\n ],\n [\n -85,\n 43.2\n ],\n [\n -83.8159644849273,\n 43.2\n ],\n [\n -83.8159644849273,\n 44\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Upper Midwest Environmental Sciences Center
U.S. Geological Survey
2630 Fanta Reed Road
La Crosse, WI 54603
In cooperation with the U.S. Fish and Wildlife Service, the U.S. Geological Survey Southwest Biological Science Center employed ground-based light detection and ranging (lidar) during February 2022 to help meet two resource management objectives at the Cabeza Prieta National Wildlife Refuge (CPNWR), Arizona. The two objectives are (1) characterize the water storage capacity for one developed and two modified tanks, which are bedrock catchments also referred to as tinajas, that are important water sources for desert bighorn sheep (Ovis canadensis mexicana) in designated wilderness at the CPNWR; and (2) develop a stage-storage model to estimate water volumes from monitoring observations of water surface levels in each tank. We measured storage capacity for the three tanks identified by refuge managers, Buckhorn, Senita, and Eagle, using ground-based lidar collected during February 2022. These data produced high-resolution (centimeter scale) topographic models that improved estimates of maximum water storage capacity over previous geometry-based estimates, permitting estimations of storage capacity at multiple water surface levels (stage heights). We found that the maximum water storage capacity for the Buckhorn, Senita, and Eagle tanks was 9,108.730, 8,623.308, and 6,039.603 US gallons (gal), respectively. For each tank we report a stage-storage model based on a polynomial function that best explained variability in water storage capacity as a function of water stage height. The results presented herein will permit the CPNWR managers to (1) easily estimate water available for wildlife at any point of time, (2) interpret tank recharge following rainstorms, and (3) decide whether and when to transport water via vehicles to mechanically refill the tanks in designated wilderness.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20241046","collaboration":"Prepared in cooperation with U.S. Fish and Wildlife Service","usgsCitation":"Sankey, J.B., Caster, J., Bransky, N., Fuest, S., Sesnie, S., and Bedford, A., 2024, Lidar estimation of storage capacity for managed water resources used by desert bighorn sheep (Ovis canadensis mexicana) at Cabeza Prieta National Wildlife Refuge, Arizona: U.S. Geological Survey Open-File Report 2024–1046, 51 p., https://doi.org/10.3133/ofr20241046.","productDescription":"Report: viii, 51 p.; Data Release","numberOfPages":"51","onlineOnly":"Y","ipdsId":"IP-147780","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":497879,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117733.htm","linkFileType":{"id":5,"text":"html"}},{"id":463012,"rank":6,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2024/1046/images"},{"id":463011,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20241046/full"},{"id":463010,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2024/1046/ofr20241046.xml"},{"id":463009,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2024/1046/ofr20241046.pdf","text":"Report","size":"15 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":463008,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2024/1046/covrthb.jpg"},{"id":463007,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9U6UYA0","description":"Caster, J., Bransky, N., Sankey, J.B., Doerries, S., Sesnie, S., and Bedford, A., 2024, Data collected for estimation of storage capacity at managed water resources used by Desert Bighorn Sheep in Cabeza Prieta National Wildlife Refuge, Arizona, February 2022: U.S. Geological Survey data release, https://doi.org/10.5066/P9U6UYA0.","linkHelpText":"Data collected for estimation of storage capacity at managed water resources used by Desert Bighorn Sheep in Cabeza Prieta National Wildlife Refuge, Arizona, February 2022"}],"country":"United States","state":"Arizona","otherGeospatial":"Cabeza Prieta National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -114.06241638536036,\n 32.216227063899524\n ],\n [\n -112.99182918961803,\n 31.87845678988026\n ],\n [\n -112.99601272237372,\n 32.134724889538845\n ],\n [\n -112.83497036004906,\n 32.13248007225823\n ],\n [\n -112.80727933959541,\n 32.37642090886048\n ],\n [\n -112.77701599473573,\n 32.66128486132219\n ],\n [\n -113.26041443223556,\n 32.66128486132219\n ],\n [\n -113.24942810411025,\n 32.550226527248725\n ],\n [\n -114.07340271348566,\n 32.540965452607495\n ],\n [\n -114.06241638536036,\n 32.216227063899524\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Southwest Biological Science Center
U.S. Geological Survey
2255 N. Gemini Drive
Flagstaff, AZ 86001
In 2024, the U.S. Geological Survey's (USGS) National Minerals Information Center (NMIC) completed the project titled \"Compilation of geospatial data for the mineral industries of select countries in the Indo-Pacific.\" This project aimed to leverage the expertise and capabilities of the NMIC to collect, synthesize, and interpret geospatial data to inform on the extractive resources of select countries in the Indo-Pacific region (area of study) and expand the NMIC's understanding on the impact of mineral industry of these countries in the global economy. The 19 countries of interest in the Indo-Pacific study area include Bangladesh, Bhutan, Brunei, Burma, Fiji, Malaysia, Mongolia, Nauru, New Caledonia, New Zealand, Papua New Guinea, Philippines, Singapore, Solomon Islands, South Korea (Republic of Korea), Sri Lanka, Taiwan, Timor-Leste, and Vietnam. The primary objective of this effort was to create a fully attributed Geographic Information System (GIS) portraying existing mining infrastructure, resources, and production capacities across the Indo-Pacific study area as well as highlight mineral production and processing sites under development and potential areas of future extractive industry operations and development in the region. The compiled GIS geodatabase with supporting documentation including comprehensive metadata was published as a USGS data release titled \"Compilation of Geospatial Data (GIS) for the Mineral Industries of Select Countries in the Indo-Pacific.\"
This georeferenced portable document format (GeoPDF) map sheet presents a new geographic information product containing a partial representation of the GIS data. This GeoPDF map provides a visual comparison of the distribution of mineral industry GIS data, which contributes to a deeper understanding of the intersections and complexities of the extractive industries within the select countries in the Indo-Pacific region.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20241066","usgsCitation":"Neustaedter, E.R., and Wolfe, E.R., 2024, Geospatial PDF map of the compilation of GIS data for the mineral industries of select countries in the Indo-Pacific region: U.S. Geological Survey Open-File Report 2024–1066, 1 geospatial map, scale 1:42,500,000, https://doi.org/10.3133/ofr20241066.","productDescription":"Sheet: 12.00 x 18.00 inches; Data Release","numberOfPages":"1","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-168033","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":462739,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2024/1066/ofr20241066.pdf","text":"Report","size":"30.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2024-1066 PDF"},{"id":462738,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2024/1066/coverthb.jpg"},{"id":462796,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20241066/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2024-1066 PDF"},{"id":462797,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2024/1066/ofr20241066.XML","description":"OFR 2024-1066 XML"},{"id":462798,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2024/1066/images/"},{"id":462799,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13YRCDU","text":"USGS data release","linkHelpText":"- Compilation of Geospatial Data (GIS) for the Mineral Industries of Select Countries in the Indo-Pacific"}],"country":"New Zealand, Taiwan, Bangladesh, Brunei, Malaysia, Mongolia, Myanmar, Papua New Guinea, Philippines, South Korea, Vietnam,","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[173.02037,-40.91905],[173.24723,-41.332],[173.95841,-40.9267],[174.24759,-41.34916],[174.24852,-41.77001],[173.87645,-42.23318],[173.22274,-42.97004],[172.71125,-43.37229],[173.08011,-43.85334],[172.30858,-43.86569],[171.45293,-44.24252],[171.18514,-44.8971],[170.6167,-45.90893],[169.83142,-46.35577],[169.33233,-46.64124],[168.41135,-46.61994],[167.76374,-46.2902],[166.67689,-46.21992],[166.50914,-45.8527],[167.04642,-45.11094],[168.30376,-44.12397],[168.94941,-43.93582],[169.66781,-43.55533],[170.52492,-43.03169],[171.12509,-42.51275],[171.56971,-41.76742],[171.94871,-41.51442],[172.09723,-40.9561],[172.79858,-40.49396],[173.02037,-40.91905]]],[[[174.61201,-36.1564],[175.33662,-37.2091],[175.3576,-36.52619],[175.80889,-36.79894],[175.95849,-37.55538],[176.7632,-37.88125],[177.43881,-37.96125],[178.01035,-37.57982],[178.51709,-37.69537],[178.27473,-38.58281],[177.97046,-39.16634],[177.20699,-39.14578],[176.93998,-39.44974],[177.03295,-39.87994],[176.88582,-40.06598],[176.50802,-40.60481],[176.01244,-41.28962],[175.23957,-41.68831],[175.0679,-41.42589],[174.65097,-41.28182],[175.22763,-40.45924],[174.90016,-39.90893],[173.82405,-39.50885],[173.85226,-39.1466],[174.5748,-38.79768],[174.74347,-38.02781],[174.69702,-37.38113],[174.29203,-36.71109],[174.319,-36.53482],[173.841,-36.12198],[173.05417,-35.23713],[172.63601,-34.52911],[173.00704,-34.45066],[173.5513,-35.00618],[174.32939,-35.2655],[174.61201,-36.1564]]],[[[121.77782,24.39427],[121.17563,22.79086],[120.74708,21.97057],[120.22008,22.81486],[120.10619,23.55626],[120.69468,24.53845],[121.49504,25.29546],[121.95124,24.9976],[121.77782,24.39427]]],[[[92.36855,20.67088],[92.08289,21.1922],[92.02522,21.70157],[91.83489,22.18294],[91.41709,22.76502],[90.49601,22.80502],[90.58696,22.39279],[90.27297,21.83637],[89.84747,22.03915],[89.70205,21.85712],[89.41886,21.96618],[89.03196,22.05571],[88.87631,22.87915],[88.52977,23.63114],[88.69994,24.23371],[88.08442,24.50166],[88.30637,24.86608],[88.93155,25.23869],[88.20979,25.76807],[88.56305,26.44653],[89.35509,26.01441],[89.83248,25.96508],[89.92069,25.26975],[90.87221,25.1326],[91.7996,25.14743],[92.3762,24.97669],[91.91509,24.13041],[91.46773,24.07264],[91.15896,23.50353],[91.70648,22.98526],[91.86993,23.62435],[92.14603,23.6275],[92.67272,22.04124],[93.16613,22.27846],[93.06029,22.70311],[93.28633,23.04366],[93.32519,24.07856],[94.10674,23.85074],[94.55266,24.67524],[94.60325,25.1625],[95.15515,26.00131],[95.12477,26.57357],[96.41937,27.26459],[97.134,27.08377],[97.05199,27.69906],[97.40256,27.88254],[97.32711,28.26158],[97.91199,28.33595],[98.24623,27.74722],[98.68269,27.50881],[98.71209,26.74354],[98.67184,25.9187],[97.72461,25.08364],[97.60472,23.8974],[98.66026,24.06329],[98.89875,23.14272],[99.53199,22.94904],[99.2409,22.11831],[99.98349,21.74294],[100.41654,21.55884],[101.15003,21.84998],[101.18001,21.43657],[100.3291,20.78612],[100.11599,20.41785],[99.54331,20.1866],[98.95968,19.75298],[98.25372,19.7082],[97.79778,18.62708],[97.3759,18.44544],[97.85912,17.56795],[98.49376,16.83784],[98.90335,16.17782],[98.53738,15.3085],[98.19207,15.1237],[98.43082,14.62203],[99.09776,13.8275],[99.21201,13.26929],[99.19635,12.80475],[99.58729,11.89276],[99.03812,10.96055],[98.55355,9.93296],[98.45717,10.67527],[98.76455,11.44129],[98.42834,12.03299],[98.50957,13.12238],[98.1036,13.64046],[97.77773,14.83729],[97.59707,16.10057],[97.16454,16.92873],[96.50577,16.42724],[95.36935,15.71439],[94.8084,15.80345],[94.1888,16.03794],[94.53349,17.27724],[94.32482,18.21351],[93.54099,19.36649],[93.66325,19.72696],[93.07828,19.85514],[92.36855,20.67088]]],[[[114.20402,4.52587],[114.59996,4.90001],[115.45071,5.44773],[116.22074,6.14319],[116.7251,6.92477],[117.12963,6.92805],[117.64339,6.42217],[117.68908,5.98749],[118.34769,5.7087],[119.1819,5.40784],[119.11069,5.01613],[118.43973,4.96652],[118.61832,4.4782],[117.88203,4.13755],[117.01521,4.30609],[115.86552,4.30656],[115.51908,3.16924],[115.13404,2.82148],[114.62136,1.43069],[113.80585,1.21755],[112.85981,1.49779],[112.38025,1.41012],[111.79755,0.90444],[111.15914,0.97648],[110.51406,0.77313],[109.83023,1.33814],[109.66326,2.00647],[110.39614,1.66377],[111.16885,1.85064],[111.37008,2.6973],[111.79693,2.8859],[112.99561,3.10239],[113.71294,3.89351],[114.20402,4.52587]]],[[[101.07552,6.20487],[101.15422,5.69138],[101.81428,5.81081],[102.14119,6.22164],[102.37115,6.12821],[102.96171,5.5245],[103.38121,4.855],[103.43858,4.18161],[103.33212,3.7267],[103.42943,3.38287],[103.50245,2.79102],[103.85467,2.51545],[104.24793,1.63114],[104.22881,1.29305],[103.51971,1.22633],[102.57362,1.96712],[101.39064,2.76081],[101.27354,3.27029],[100.69544,3.93914],[100.55741,4.76728],[100.19671,5.31249],[100.30626,6.04056],[100.08576,6.46449],[100.2596,6.64282],[101.07552,6.20487]]],[[[87.75126,49.2972],[88.80557,49.47052],[90.71367,50.33181],[92.23471,50.80217],[93.10422,50.49529],[94.14757,50.48054],[94.81595,50.01343],[95.81403,49.97747],[97.25973,49.72606],[98.23176,50.4224],[97.82574,51.011],[98.86149,52.04737],[99.98173,51.63401],[100.88948,51.51686],[102.06522,51.25992],[102.25591,50.51056],[103.67655,50.08997],[104.62155,50.27533],[105.88659,50.40602],[106.8888,50.2743],[107.86818,49.79371],[108.47517,49.28255],[109.40245,49.29296],[110.66201,49.13013],[111.58123,49.37797],[112.89774,49.54357],[114.36246,50.2483],[114.96211,50.14025],[115.4857,49.80518],[116.6788,49.88853],[116.1918,49.1346],[115.48528,48.13538],[115.74284,47.72654],[116.30895,47.85341],[117.29551,47.69771],[118.06414,48.06673],[118.86657,47.74706],[119.77282,47.04806],[119.66327,46.69268],[118.87433,46.80541],[117.4217,46.67273],[116.71787,46.3882],[115.9851,45.72724],[114.46033,45.33982],[113.46391,44.80889],[112.43606,45.01165],[111.87331,45.10208],[111.34838,44.45744],[111.66774,44.07318],[111.82959,43.74312],[111.12968,43.40683],[110.4121,42.87123],[109.2436,42.51945],[107.74477,42.48152],[106.12932,42.13433],[104.96499,41.59741],[104.52228,41.90835],[103.31228,41.90747],[101.83304,42.51487],[100.84587,42.6638],[99.51582,42.52469],[97.45176,42.74889],[96.3494,42.72564],[95.76245,43.31945],[95.30688,44.24133],[94.68893,44.35233],[93.48073,44.97547],[92.13389,45.11508],[90.94554,45.28607],[90.58577,45.71972],[90.97081,46.88815],[90.28083,47.69355],[88.8543,48.06908],[88.01383,48.59946],[87.75126,49.2972]]],[[[155.88003,-6.82],[155.59999,-6.91999],[155.16699,-6.53593],[154.72919,-5.90083],[154.51411,-5.13912],[154.6525,-5.04243],[154.75999,-5.33998],[155.06292,-5.56679],[155.54775,-6.20065],[156.01997,-6.54001],[155.88003,-6.82]]],[[[151.9828,-5.47806],[151.45911,-5.56028],[151.30139,-5.84073],[150.75445,-6.08376],[150.2412,-6.31775],[149.70996,-6.31651],[148.89006,-6.02604],[148.31894,-5.74714],[148.40183,-5.43776],[149.29841,-5.58374],[149.84556,-5.5055],[149.99625,-5.0261],[150.13976,-5.00135],[150.23691,-5.53222],[150.80747,-5.45584],[151.08967,-5.11369],[151.64788,-4.75707],[151.53786,-4.16781],[152.13679,-4.14879],[152.33874,-4.31297],[152.31869,-4.86766],[151.9828,-5.47806]]],[[[147.19187,-7.38802],[148.08464,-8.04411],[148.73411,-9.10466],[149.30684,-9.07144],[149.26663,-9.51441],[150.03873,-9.68432],[149.7388,-9.87294],[150.80163,-10.29369],[150.69057,-10.58271],[150.02839,-10.65248],[149.78231,-10.39327],[148.92314,-10.28092],[147.91302,-10.13044],[147.13544,-9.49244],[146.56788,-8.94255],[146.04848,-8.06741],[144.74417,-7.63013],[143.89709,-7.91533],[143.28638,-8.24549],[143.41391,-8.98307],[142.62843,-9.32682],[142.06826,-9.1596],[141.03385,-9.11789],[141.01706,-5.85902],[141.00021,-2.60015],[142.73525,-3.28915],[144.58397,-3.86142],[145.27318,-4.37374],[145.82979,-4.8765],[145.98192,-5.46561],[147.64807,-6.08366],[147.89111,-6.61401],[146.97091,-6.72166],[147.19187,-7.38802]]],[[[153.14004,-4.49998],[152.82729,-4.76643],[152.63867,-4.17613],[152.40603,-3.78974],[151.95324,-3.46206],[151.38428,-3.03542],[150.66205,-2.74149],[150.93997,-2.5],[151.47998,-2.77999],[151.82002,-2.99997],[152.23999,-3.24001],[152.64002,-3.65998],[153.01999,-3.98002],[153.14004,-4.49998]]],[[[126.37681,8.41471],[126.47851,7.75035],[126.53742,7.18938],[126.19677,6.27429],[125.83142,7.29372],[125.36385,6.78649],[125.68316,6.04966],[125.39651,5.581],[124.21979,6.16136],[123.93872,6.88514],[124.24366,7.36061],[123.61021,7.83353],[123.29607,7.41888],[122.82551,7.45737],[122.0855,6.89942],[121.91993,7.19212],[122.31236,8.03496],[122.9424,8.31624],[123.48769,8.69301],[123.84115,8.24032],[124.60147,8.51416],[124.76461,8.96041],[125.47139,8.987],[125.41212,9.76033],[126.22271,9.28607],[126.30664,8.78249],[126.37681,8.41471]]],[[[123.98244,10.27878],[123.62318,9.95009],[123.30992,9.31827],[122.99588,9.02219],[122.38005,9.71336],[122.58609,9.98104],[122.83708,10.26116],[122.94741,10.88187],[123.49885,10.94062],[123.33777,10.26738],[124.07794,11.23273],[123.98244,10.27878]]],[[[118.50458,9.31638],[117.17427,8.3675],[117.66448,9.06689],[118.38691,9.6845],[118.98734,10.37629],[119.5115,11.36967],[119.68968,10.55429],[119.02946,10.00365],[118.50458,9.31638]]],[[[121.88355,11.89176],[122.48382,11.58219],[123.12022,11.58366],[123.10084,11.16593],[122.63771,10.74131],[122.00261,10.44102],[121.96737,10.90569],[122.03837,11.41584],[121.88355,11.89176]]],[[[125.50255,12.16269],[125.78346,11.04612],[125.01188,11.31145],[125.03276,10.97582],[125.27745,10.35872],[124.80182,10.13468],[124.76017,10.838],[124.4591,10.88993],[124.30252,11.49537],[124.89101,11.41558],[124.87799,11.79419],[124.26676,12.55776],[125.22712,12.53572],[125.50255,12.16269]]],[[[121.52739,13.06959],[121.26219,12.20556],[120.8339,12.7045],[120.32344,13.46641],[121.18013,13.4297],[121.52739,13.06959]]],[[[121.32131,18.50406],[121.9376,18.21855],[122.24601,18.47895],[122.33696,18.22488],[122.17428,17.81028],[122.51565,17.0935],[122.25231,16.26244],[121.66279,15.93102],[121.50507,15.12481],[121.72883,14.32838],[122.25893,14.2182],[122.70128,14.33654],[123.9503,13.78213],[123.85511,13.23777],[124.18129,12.99753],[124.07742,12.53668],[123.29804,13.02753],[122.92865,13.55292],[122.67136,13.18584],[122.03465,13.78448],[121.12638,13.63669],[120.62864,13.85766],[120.67938,14.27102],[120.99182,14.52539],[120.69334,14.75667],[120.56415,14.39628],[120.07043,14.97087],[119.92093,15.40635],[119.88377,16.3637],[120.28649,16.03463],[120.39005,17.59908],[120.71587,18.50523],[121.32131,18.50406]]],[[[128.34972,38.61224],[129.21292,37.43239],[129.46045,36.78419],[129.4683,35.63214],[129.09138,35.08248],[128.18585,34.89038],[127.38652,34.47567],[126.48575,34.39005],[126.37392,34.93456],[126.55923,35.68454],[126.1174,36.72548],[126.86014,36.89392],[126.17476,37.74969],[126.23734,37.84038],[126.68372,37.80477],[127.07331,38.25611],[127.78004,38.30454],[128.20575,38.3704],[128.34972,38.61224]]],[[[108.05018,21.55238],[106.71507,20.69685],[105.88168,19.75205],[105.66201,19.05817],[106.42682,18.00412],[107.36195,16.69746],[108.2695,16.07974],[108.87711,15.27669],[109.33527,13.42603],[109.20014,11.66686],[108.36613,11.00832],[107.22093,10.36448],[106.40511,9.53084],[105.15826,8.59976],[104.79519,9.24104],[105.0762,9.91849],[104.33433,10.48654],[105.19991,10.88931],[106.24967,10.96181],[105.81052,11.56761],[107.4914,12.33721],[107.61455,13.53553],[107.38273,14.20244],[107.56453,15.20217],[107.31271,15.90854],[106.55601,16.60428],[105.92576,17.48532],[105.0946,18.66697],[103.89653,19.26518],[104.18339,19.62467],[104.82257,19.88664],[104.435,20.75873],[103.20386,20.76656],[102.7549,21.67514],[102.17044,22.46475],[102.70699,22.7088],[103.50451,22.70376],[104.47686,22.81915],[105.32921,23.35206],[105.81125,22.97689],[106.7254,22.79427],[106.56727,22.2182],[107.04342,21.8119],[108.05018,21.55238]]]]},\"properties\":{\"name\":\"New Zealand\"}}]}","contact":"Director, National Minerals Information Center
U.S. Geological Survey
12201 Sunrise Valley Drive
988 National Center
Reston, VA 20192
China’s export controls on gallium and germanium exemplify concerns regarding the reliability of supplies of mineral commodities that are essential to economic development, national security, and transition to renewable energy. This report presents a new model that quantifies the potential effects of mineral commodity supply disruptions on the U.S. economy. After calculating postdisruption equilibrium prices and quantities, a nonlinear optimization routine was used along with economic input-output tables to estimate the effects of varying Chinese net export restrictions of gallium and germanium on U.S. gross domestic product (GDP). The results indicated that a complete restriction of China’s net exports of gallium and germanium could cause the U.S. GDP to decrease by $3.1 billion (with lower and upper estimates of $1.7 billion to $8.2 billion) and $0.4 billion ($0.01 billion to $1.1 billion), respectively, if disrupted separately, and $3.4 billion ($1.7 billion to $9.0 billion) if disrupted simultaneously. The proposed model can be applied to other commodities and disruption scenarios.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20241057","usgsCitation":"Nassar, N.T., Shojaeddini, E., Alonso, E., Jaskula, B., and Tolcin, A., 2024, Quantifying potential effects of China’s gallium and germanium export restrictions on the U.S. economy: U.S. Geological Survey Open-File Report 2024–1057, 66 p., https://doi.org/10.3133/ofr20241057.","productDescription":"vi, 66 p.","numberOfPages":"66","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-164579","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":462693,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2024/1057/coverthb.jpg"},{"id":462696,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2024/1057/ofr20241057.XML","linkFileType":{"id":8,"text":"xml"},"description":"OFR 2024-1057 XML"},{"id":462697,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2024/1057/images/"},{"id":462694,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2024/1057/ofr20241057.pdf","text":"Report","size":"2.77 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2024-1057 PDF"},{"id":462695,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20241057/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2024-1057 HTML"}],"contact":"Director, National Minerals Information Center
U.S. Geological Survey
12201 Sunrise Valley Drive
988 National Center
Reston, VA 20192
China’s export controls on gallium and germanium illustrate concerns about the reliability of supplies of mineral commodities that are essential to economic development, national security, and transitioning to renewable energy. The U.S. Geological Survey created a new model to quantify the potential effects of mineral commodity supply disruptions from Chinese net export restrictions of gallium and germanium on U.S. gross domestic product (GDP). The results indicated that a complete restriction of China’s net exports of gallium and germanium could cause the U.S. GDP to decrease by $3.1 billion (with lower and upper estimates of $1.7 billion to $8.2 billion) and $0.4 billion ($0.01 billion to $1.1 billion), respectively, if disrupted separately, and $3.4 billion ($1.7 billion to $9.0 billion) if disrupted simultaneously. The proposed model can be applied to other commodities and disruption scenarios.
","publicationDate":"2024-10-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Nassar, Nedal T. 0000-0001-8758-9732 nnassar@usgs.gov","orcid":"https://orcid.org/0000-0001-8758-9732","contributorId":197864,"corporation":false,"usgs":true,"family":"Nassar","given":"Nedal","email":"nnassar@usgs.gov","middleInitial":"T.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":915292,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shojaeddini, Ensieh 0000-0001-9584-6399","orcid":"https://orcid.org/0000-0001-9584-6399","contributorId":345023,"corporation":false,"usgs":false,"family":"Shojaeddini","given":"Ensieh","affiliations":[{"id":82464,"text":"Akima System Engineering","active":true,"usgs":false}],"preferred":false,"id":915293,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Alonso, Elisa 0000-0002-0090-8284","orcid":"https://orcid.org/0000-0002-0090-8284","contributorId":223015,"corporation":false,"usgs":true,"family":"Alonso","given":"Elisa","email":"","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":915294,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jaskula, Brian 0000-0002-4540-1639","orcid":"https://orcid.org/0000-0002-4540-1639","contributorId":345024,"corporation":false,"usgs":true,"family":"Jaskula","given":"Brian","email":"","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":915295,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tolcin, Amy 0000-0001-9447-2444 atolcin@usgs.gov","orcid":"https://orcid.org/0000-0001-9447-2444","contributorId":213768,"corporation":false,"usgs":true,"family":"Tolcin","given":"Amy","email":"atolcin@usgs.gov","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":915296,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70259485,"text":"ofr20241048 - 2024 - State of science, gap analysis, and prioritization for southeastern United States water-quality impacts from coastal storms—Fiscal year 2023 program report to the Water Resources Mission Area from the Water Availability Impacts of Extreme Events Program—Hurricanes","interactions":[],"lastModifiedDate":"2025-12-23T21:45:07.018203","indexId":"ofr20241048","displayToPublicDate":"2024-10-09T15:47:59","publicationYear":"2024","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":"2024-1048","displayTitle":"State of Science, Gap Analysis, and Prioritization for Southeastern United States Water-Quality Impacts from Coastal Storms—Fiscal Year 2023 Program Report to the Water Resources Mission Area from the Water Availability Impacts of Extreme Events Program—Hurricanes","title":"State of science, gap analysis, and prioritization for southeastern United States water-quality impacts from coastal storms—Fiscal year 2023 program report to the Water Resources Mission Area from the Water Availability Impacts of Extreme Events Program—Hurricanes","docAbstract":"Tropical cyclones (coastal storm events that include tropical depressions, tropical storms, and hurricanes) cause landscape-scale disturbances that can lead to impaired water quality and thus reduce water availability for use. Stakeholders and scientists at local and national scales have illustrated a need for understanding these risks to water quality. A regional and comprehensive understanding of the impacts of tropical storms and hurricanes on surface-water and groundwater quality—and thus water availability—is lacking for potentially impacted coastal and inland areas. As the U.S. Geological Survey considers development of tools to predict the extent to which water-quality impacts of hurricanes affect water availability, an assessment of the state of the science of hurricane impacts is needed, including a gap analysis and prioritization of data and science needs. This assessment focuses on the southeastern coastal States.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20241048","usgsCitation":"Windham-Myers, L., Root, T.L., Petkewich, M.D., Musgrove, M., Gill, A.C., Weaver, J.C., Conaway, C.H., Lindsey, B.D., Parchaso, F., Knowles, N., and Tomaszewski, E.J., 2024, State of science, gap analysis, and prioritization for southeastern United States water-quality impacts from coastal storms—Fiscal year 2023 program report to the Water Resources Mission Area from the Water Availability Impacts of Extreme Events Program—Hurricanes: U.S. Geological Survey Open-File Report 2024–1048, 64 p., https://doi.org/10.3133/ofr20241048.","productDescription":"vii, 64 p.","numberOfPages":"76","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-158415","costCenters":[{"id":156,"text":"Caribbean Water Science Center","active":true,"usgs":true},{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":497944,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117648.htm","linkFileType":{"id":5,"text":"html"}},{"id":462753,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2024/1048/ofr20241048.pdf","text":"Report","size":"8.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2024-1048"},{"id":462752,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2024/1048/coverthb.jpg"}],"country":"United States","otherGeospatial":"southeastern United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -68.26046308814853,\n 43.34065198513025\n ],\n [\n -71.1713607133797,\n 43.55896502744753\n ],\n [\n -75.09417377891708,\n 40.41702622060157\n ],\n [\n -76.94176883383484,\n 39.38997863980981\n ],\n [\n -77.22164958897736,\n 35.4797326167386\n ],\n [\n -81.98694844837883,\n 31.03632790667575\n ],\n [\n -91.39626305044476,\n 30.5137107036077\n ],\n [\n -91.2989713852823,\n 28.512692779158414\n ],\n [\n -88.18175904626855,\n 28.79591613221004\n ],\n [\n -86.89387148001948,\n 29.79601367137508\n ],\n [\n -83.99773737243493,\n 28.705053633372273\n ],\n [\n -82.26744490204806,\n 24.549161920326497\n ],\n [\n -81.77772710856374,\n 24.25613293881912\n ],\n [\n -79.25395823346736,\n 25.669131592981728\n ],\n [\n -80.8137017138734,\n 30.79934564119985\n ],\n [\n -75.38603247990801,\n 34.830905137914925\n ],\n [\n -74.53299323261764,\n 37.55917715000662\n ],\n [\n -72.8924569187813,\n 40.11126942721674\n ],\n [\n -69.38684780759837,\n 40.8712632604325\n ],\n [\n -69.5648600647653,\n 42.87442943706927\n ],\n [\n -68.26046308814853,\n 43.34065198513025\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Earth System Processes Division
Water Resources Mission Area
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
The U.S. Geological Survey (USGS) in partnership with the International Joint Commission installed and operated continuous water-quality monitors at three sites on the Souris River from May 2019 to October 2023. Continuously recorded data included dissolved oxygen (DO), water temperature, and specific conductance at the Souris River near Sherwood, North Dakota (USGS station 05114000), Souris River above Minot, N. Dak. (USGS station 05117500), and Souris River near Westhope, N. Dak (USGS station 05124000). The three sites on the Souris River were chosen for additional DO monitoring because they provided the best opportunity to capture potential effects on DO in areas downstream from major flow control structures and because identifying the connection of streamflow to DO at the international border is a focus of the International Souris River Board (ISRB).
The continuous water-quality monitoring at three sites on the Souris River from May 16, 2019, to October 1, 2023, indicated different patterns in DO among the three sites, and the different patterns indicate different factors affect DO concentrations among the sites. DO concentrations near Sherwood indicated the strong effect of algal dynamics at lower streamflow conditions with large diurnal fluctuations in DO concentration and indicated that streamflow does seem to affect DO concentrations when the streamflow is greater than about 100 cubic feet per second. DO concentrations were also frequently less than the water-quality objective (WQO) of 5 milligrams per liter in the summer and winter months, particularly during relatively low streamflow conditions in 2020 and 2021. DO concentrations above Minot had a different pattern with considerably fewer diurnal fluctuations than near Sherwood, high DO concentrations most winters except for the winter of 2021–22, and fewer instances when the DO was less than the WQO compared to Sherwood. The pattern of DO concentrations near Westhope seemed to be mainly influenced by the water chemistry coming out of J. Clark Salyer Pool 357 rather than streamflow and channel conditions at the site. The Westhope site also had the most days with daily minimum DO concentrations less than the WQO among the three sites, mainly in the winter when concentrations were consistently at or near 0 milligrams per liter for most of the winter months.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20241043","collaboration":"Prepared in cooperation with the International Joint Commission","usgsCitation":"Galloway, J.M., 2024, Dissolved oxygen monitoring on the Souris River, 2019–23: U.S. Geological Survey Open-File Report 2024–1043, 13 p., https://doi.org/10.3133/ofr20241043.","productDescription":"Report: iv, 13 p.; Dataset","numberOfPages":"20","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-167787","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":497955,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117500.htm","linkFileType":{"id":5,"text":"html"}},{"id":462183,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20241043/full"},{"id":462182,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"- USGS water data for the Nation"},{"id":462181,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2024/1043/images/"},{"id":462180,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2024/1043/ofr20241043.XML"},{"id":462179,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2024/1043/ofr20241043.pdf","text":"Report","size":"3.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2024–1043"},{"id":462178,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2024/1043/coverthb.jpg"}],"country":"Canada, United States","state":"North Dakota","otherGeospatial":"Souris River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -105.03302625208204,\n 50.79350866915286\n ],\n [\n -105.03302625208204,\n 47.533599370512235\n ],\n [\n -98.11163953333218,\n 47.533599370512235\n ],\n [\n -98.11163953333218,\n 50.79350866915286\n ],\n [\n -105.03302625208204,\n 50.79350866915286\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
The U.S. Geological Survey Earth Resources Observation and Science Calibration and Validation (Cal/Val) Center of Excellence (ECCOE) focuses on improving the accuracy, precision, calibration, and product quality of remote-sensing data, leveraging years of multiscale optical system geometric and radiometric calibration and characterization experience. The ECCOE Landsat Cal/Val Team continually monitors the geometric and radiometric performance of active Landsat missions and makes calibration adjustments, as needed, to maintain data quality at the highest level.
This report provides observed geometric and radiometric analysis results for Landsats 8 and 9 for quarter 1 (January–March), 2024. All data used to compile the Cal/Val analysis results presented in this report are freely available from the U.S. Geological Survey EarthExplorer website:
https://earthexplorer.usgs.gov.
This quarterly report is the third to include analysis results for Landsat 9, which was launched in September 2021. The inclusion of Landsat 9 analysis results was dependent on two factors: a complete reprocessing of the Landsat 9 data archive and enough time elapsing to begin formulating lifetime trends. In April 2023, all Landsat 9 image data acquired since the satellite’s launch were reprocessed to take advantage of calibration updates identified by the ECCOE Landsat Cal/Val Team. Additional information about the Landsat 9 reprocessing effort is available at https://www.usgs.gov/landsat-missions/news/upcoming-reprocessing-all-landsat-9-data. Additional information about Landsat 9 prelaunch, commissioning, and early on-orbit imaging performance is available at https://www.mdpi.com/journal/remotesensing/special_issues/15B4V2K92K.
This quarterly report is the first to not include analysis results for Landsat 7 because Enhanced Thematic Mapper Plus imaging was suspended on January 19, 2024, after the satellite transitioned into full sunlight. The satellite has been drifting since early 2022 after being lowered from the nominal orbit altitude, and the transition into full sunlight is a result of the satellite operating in its extended science mission. Additional information about the imaging suspension is available at https://www.usgs.gov/landsat-missions/news/landsat-7-imaging-suspended. Additional information about the Landsat 7 extended science mission is available at https://www.usgs.gov/landsat-missions/landsat-7-extended-science-mission.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20241058","usgsCitation":"Haque, M.O., Hasan, M.N., Shrestha, A., Rengarajan, R., Lubke, M., Shaw, J.L., Ruslander, K., Micijevic, E., Choate, M.J., Anderson, C., Clauson, J., Thome, K., Barsi, J., Kaita, E., Levy, R., Miller, J., and Ding, L., 2024, ECCOE Landsat\nquarterly Calibration and Validation report—Quarter 1, 2024 (ver. 1.2, June 2026): U.S. Geological Survey Open-File Report 2024–1058, 57 p., https://doi.org/10.3133/ofr20241058.","productDescription":"Report: viii, 57 p.; Dataset","numberOfPages":"70","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-165326","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":505306,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2024/1058/ofr20241058.pdf","text":"Report","size":"5.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2024–1058 PDF"},{"id":505311,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20241058/full"},{"id":505307,"rank":6,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2024/1058/versionHist.txt","text":"Version History","size":"1 KB","linkFileType":{"id":2,"text":"txt"}},{"id":439142,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://earthexplorer.usgs.gov/","text":"USGS database","linkHelpText":"- EarthExplorer"},{"id":439140,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2024/1058/images/"},{"id":439137,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2024/1058/coverthb3.jpg"},{"id":439139,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2024/1058/ofr20241058.XML","description":"OFR 2024–1058 XML"}],"edition":"Version 1.0: September 24, 2024; Version 1.1: December 11, 2024; Version 1.2: June 11, 2026","contact":"Director, Earth Resources Observation and Science Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD 57198
Invasive carp pose substantial economic and ecological damage when populations are widespread in freshwater systems within the United States. Resource managers in the United States have few chemical control tools to selectively remove nuisance fish. This study examined whether Antimycin–A (antimycin) wax encapsulated microparticles could cause selective lethality in invasive carps. The antimycin microparticles were selective toward bighead carp (Hypophthalmichthys nobilis) and silver carp (Hypophthalmichthys molitrix) across multiple experimental scales. Microparticles applied in experimental pond studies caused approximately 50 percent lethality in invasive carp. Effluent pond studies performed at Rathbun Fish Hatchery (Moravia, Iowa) caused silver carp lethality at a lower rate than previous pond or laboratory studies (approximately 1 percent); however, minimal effects on other fish species were observed. The antimycin microparticle formulation shows the ability to cause lethality in filter-feeding invasive carp relative to other fish species and demonstrated the plausibility for delivering a typically nonselective toxicant in a selective manner to specific species based on their physiological feeding traits.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20241052","usgsCitation":"Sauey, B.W., Saari, G.N., Putnam, J.G., Nelson, J.E., Wamboldt, J.J., Steiner, J.N., and Calfee, R.D., 2024, A novel tool to selectively deliver a control agent to filter-feeding silver and bighead carp: U.S. Geological Survey Open-File Report 2024–1052, 17 p., https://doi.org/10.3133/ofr20241052.","productDescription":"Report: vii, 17 p.; Data Release","numberOfPages":"30","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-158198","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":433504,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2024/1052/images/"},{"id":433506,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20241052/full"},{"id":433501,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2024/1052/coverthb.jpg"},{"id":433502,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2024/1052/ofr20241052.pdf","text":"Report","size":"1.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2024–1052"},{"id":433503,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2024/1052/ofr20241052.XML"},{"id":499261,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117491.htm","linkFileType":{"id":5,"text":"html"}},{"id":433505,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1DHXFTG","text":"UGSS data release","linkHelpText":"Data release for a novel tool to selectively deliver a control agent to filter-feeding silver and bighead carp"}],"contact":"Director, Upper Midwest Environmental Sciences Center
U.S. Geological Survey
2630 Fanta Reed Road
La Crosse, WI 54603
The Aransas-Wood Buffalo population of Grus americana (Linnaeus, 1758; whooping cranes) migrates through the U.S. Great Plains, encountering places substantially altered by human activity. Using telemetry data from 2017 to 2022, we investigated whooping crane migration behavior around U.S. Air Force bases in Oklahoma. Our study focused on potential collision risks between whooping cranes and aircraft, a substantial concern for aviation safety. We determined that activity was greatest at Kegelman Air Force Auxiliary Airfield, near whooping crane critical habitat. On average, 61 percent of marked whooping cranes used locations west of Kegelman Air Force Auxiliary Airfield and Vance Air Force Base during autumn migration and 55 percent during spring migration, and few cranes approached within 5 kilometers of airfields. Flight characteristics revealed seasonal variations in altitude and timing; cranes flew at lower altitudes in autumn and had distinct flight patterns. Additionally, we assessed temporal aspects of migration, identifying average arrival and departure dates for spring and autumn migrations. Cranes indicated consistency in seasonal presence, which may aid in risk assessments. Our findings underscore the importance of monitoring potential interactions between whooping cranes and aircraft, particularly around whooping crane critical habitat like the Salt Plains National Wildlife Refuge in Oklahoma. Detailed summaries of migration patterns and flight behavior can be used to assist the U.S. Air Force in assessing collision risks and developing mitigation strategies. Furthermore, these summaries can provide insights for the conservation efforts of this endangered species managed by the U.S. Fish and Wildlife Service and serve as a step towards mitigating risks to aviation safety and the recovery of whooping cranes.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20241056","collaboration":"Prepared in cooperation with the U.S. Air Force and U.S. Fish and Wildlife Service","programNote":"Species Management Research Program","usgsCitation":"Brandt, D.A., and Pearse, A.T., 2024, Migrating whooping crane activity near U.S. Air Force bases and airfields in Oklahoma: U.S. Geological Survey Open-File Report 2024–1056, 23 p., https://doi.org/10.3133/ofr20241056.","productDescription":"Report: vi, 23 p.; 2 Data Releases","numberOfPages":"34","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-165140","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":433672,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2024/1056/coverthb.jpg"},{"id":433673,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2024/1056/ofr20241056.pdf","text":"Report","size":"17 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2024–1056"},{"id":433675,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2024/1056/images/"},{"id":433676,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9Y8KZJ9","text":"USGS data release","linkHelpText":"Location data for whooping cranes of the Aransas-Wood Buffalo Population, 2009–2018"},{"id":433677,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P138HGIX","text":"USGS data release","linkHelpText":"Whooping crane use around Air Force Bases in Oklahoma, 2017–2022"},{"id":433674,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2024/1056/ofr20241056.XML"},{"id":433678,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20241056/full"}],"country":"United States","state":"Oklahoma","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -100.13000204850229,\n 37.12806045019728\n ],\n [\n -100.13000204850229,\n 33.690676852817916\n ],\n [\n -97.31750204850259,\n 33.690676852817916\n ],\n [\n -97.31750204850259,\n 37.12806045019728\n ],\n [\n -100.13000204850229,\n 37.12806045019728\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Northern Prairie Wildlife Research Center
U.S. Geological Survey
8711 37th Street Southeast
Jamestown, ND 58401
The 2018 Carr Fire burned more than 90 percent of Whiskeytown National Recreation Area, with much of the park burning at high severity. California yellow pine and mixed conifer forests are not well adapted to large, high-severity fires, and forest recovery after these events may be problematic. Large, high-severity fire patches pose difficulties for recruitment with interiors that are long distances from potential seed trees and may develop fuel structures that can promote further high-severity fire. This report details patterns of forest structure derived from field plots measured 2–3 years after the Carr Fire, providing a characterization of immediate fire effects. We coupled these observations with remotely sensed information, including data collected from unoccupied aircraft system surveys. The remotely sensed data were used to depict erosion after the Carr Fire as well as to create a high-resolution land cover classification map, a debris flow risk map and hazard assessment, and a post-fire canopy vegetation loss map. Results indicated high levels of tree mortality after the Carr Fire, including high-value old growth forest stands, supporting remotely sensed assessments of fire severity. The high-resolution tree mortality model also aligned well with other remotely sensed estimates of immediate burn severity. Results of the land cover classification illustrated the high percentage of dead vegetation remaining in the understory and canopy 8 months post-fire. Changes in vegetation height identified areas with canopy vegetation loss from 1- to 8-months post-fire. Pairing the post-fire debris accumulation with debris flow probabilities may identify high-risk debris flow areas. The results of this study will help inform future decisions concerning wildland fire and vegetation management strategies at Whiskeytown National Recreation Area and are broadly relevant for management in the aftermath of large, high-severity fires in mixed, dry coniferous forests in the western United States.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231053","collaboration":"Prepared in cooperation with the National Park Service","programNote":"Ecosystems Mission Area—Land Change Science Program","usgsCitation":"van Mantgem, P.J., Wright, M.C., Thorne, K.M., Beckmann, J., Buffington, K., Rankin, L.L., Colley, A., and Engber, E.A., 2024, Learning from a high-severity fire event—Conditions following the 2018 Carr Fire at Whiskeytown National Recreation Area: U.S. Geological Survey Open-File Report 2023–1053, 52 p., https://doi.org/10.3133/ofr20231053.","productDescription":"Report: viii, 52 p.; 2 Data Releases","numberOfPages":"52","onlineOnly":"Y","ipdsId":"IP-145882","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":499189,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117307.htm","linkFileType":{"id":5,"text":"html"}},{"id":432970,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231053/full"},{"id":432965,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P97Y21L1","text":"USGS Data Release","description":"Wright, M.C., Engber, E., and van Mantgem, P.J., 2024, Forest conditions following the 2018 Carr Fire at Whiskeytown National Recreation Area: U.S. Geological Survey data release, available at https://doi.org/10.5066/P97Y21L1.","linkHelpText":"Forest conditions following the 2018 Carr Fire at Whiskeytown National Recreation Area"},{"id":432964,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9GS9V1J","text":"USGS Data Release","description":"Thorne, K.M., Freeman, C.M., and Rankin, L.L., 2024, UAS imagery at Whiskeytown National Recreation Area in 2018 and 2019 following the Carr Fire: U.S. Geological Survey data release, available at https://doi.org/10.5066/P9GS9V1J.","linkHelpText":"UAS imagery at Whiskeytown National Recreation Area in 2018 and 2019 following the Carr Fire"},{"id":432969,"rank":6,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1053/images"},{"id":432968,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1053/ofr20231053.xml"},{"id":432967,"rank":4,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1053/ofr20231053.pdf","text":"Report","size":"16 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":432966,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1053/covrthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Whiskeytown National Recreation Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.82661214645721,\n 40.425804364692084\n ],\n [\n -122.42999478567339,\n 40.425804364692084\n ],\n [\n -122.42999478567339,\n 40.713227651132485\n ],\n [\n -122.82661214645721,\n 40.713227651132485\n ],\n [\n -122.82661214645721,\n 40.425804364692084\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819