Lakes and bogs in northeastern North America preserve tephra deposits sourced from multiple volcanic systems in the Northern Hemisphere. However, most studies of these deposits focus on specific Holocene intervals and the latest Pleistocene, providing snapshots rather than a full picture. We combine new data with previous work, supplemented by a broad review of the characteristics and ages of potential source regions and volcanoes, to develop the first composite tephrostratigraphic framework covering the last ~14,000 years for this region. We report new cryptotephra records from three ombrotrophic peat bogs—Irwin Smith (Michigan), Bloomingdale (New York), and Sidney Bog (Maine)—as well as new analyses and age models from previously reported sites, Nordan’s Pond Bog (Newfoundland) and Thin-Ice Pond (Nova Scotia). A new tephra (Iliinsky) from the NGRIP and GRIP ice cores is also presented as it can be correlated to new data from these terrestrial records and helps validate radiocarbon age models. We identify 21 new tephra in addition to the 15 already known, several of which cover the entire region – the White River Ash east, Newberry Pumice, Ruppert (NDN230), and Mazama. For the first time we find Mount St. Helens Yn (ca. 3660 cal yr BP) and a set P tephra (~3000–2550 cal yr BP), and confirm the presence of Jala Pumice from Volcan Ceboruco, Mexico, and KS1 from Ksudach volcano, Kamchatka. We describe new “ultra-distal” tephra, including the early Holocene KS2 eruption, and propose correlations to volcanoes Iliinsky and Shiveluch of Kamchatka, and Ushishir of the Kurile Islands. Not all of these tephra represent large eruptions, with several plausible correlations to sub-Plinian events. Using Bayesian age-modeling, we present new age estimates for the newly described tephra, for tephra with previously poor age control, and for several proximal correlatives. Overall, we demonstrate northeastern North America’s importance for providing transcontinental linkages between paleoenvironmental records and providing insights into ash distribution from different styles and sizes of eruptions.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.quascirev.2021.107242","usgsCitation":"Jensen, B.J., Davies, L.J., Nolan, C.J., Pyne-O’Donnell, S., Monteath, A., Ponomareva, V., Portnyagin, M., Booth, R.K., Bursik, M., Cook, E., Plunkett, G., Vallance, J.W., Luo, Y., Cwynar, L., Hughes, P., and Pearson, D., 2024, A latest Pleistocene and Holocene composite tephrostratigraphic framework for northeastern North America: Quaternary Science Reviews, v. 272, 107242, 31 p., https://doi.org/10.1016/j.quascirev.2021.107242.","productDescription":"107242, 31 p.","ipdsId":"IP-133544","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":467060,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.quascirev.2021.107242","text":"Publisher Index Page"},{"id":465569,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"northeastern North America","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -86.70710190314398,\n 45.89875407338073\n ],\n [\n -87.25715165097691,\n 41.88494584293869\n ],\n [\n -70.39038584514105,\n 42.568403377972174\n ],\n [\n -61.02421079487245,\n 44.282776992445974\n ],\n [\n -51.839625858910196,\n 47.329526024513775\n ],\n [\n -51.90792307454112,\n 48.349799922260345\n ],\n [\n -54.77047158421425,\n 51.839642161004456\n ],\n [\n -65.24334883460824,\n 49.434251662776575\n ],\n [\n -86.70710190314398,\n 45.89875407338073\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"272","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Jensen, Britta J.L. 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0000-0002-2780-2041","orcid":"https://orcid.org/0000-0002-2780-2041","contributorId":300684,"corporation":false,"usgs":false,"family":"Nolan","given":"Connor","email":"","middleInitial":"J.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":922147,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pyne-O’Donnell, Sean 0000-0002-1808-0366","orcid":"https://orcid.org/0000-0002-1808-0366","contributorId":347674,"corporation":false,"usgs":false,"family":"Pyne-O’Donnell","given":"Sean","affiliations":[{"id":83200,"text":"Archaeology & Palaeoecology, School of Natural and Built Environment, Queen’s University Belfast, UK","active":true,"usgs":false}],"preferred":false,"id":922148,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Monteath, Alistair J.","contributorId":347675,"corporation":false,"usgs":false,"family":"Monteath","given":"Alistair J.","affiliations":[{"id":83201,"text":"4Department of Geography and Environment, University of Southampton, Southampton, UK","active":true,"usgs":false}],"preferred":false,"id":922149,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ponomareva, Vera 0000-0001-6771-9923","orcid":"https://orcid.org/0000-0001-6771-9923","contributorId":347676,"corporation":false,"usgs":false,"family":"Ponomareva","given":"Vera","affiliations":[{"id":83202,"text":"Institute of Volcanology and Seismology, Petropavlovsk-Kamchatsky, Russia","active":true,"usgs":false}],"preferred":false,"id":922150,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Portnyagin, Maxim 0000-0001-5197-6562","orcid":"https://orcid.org/0000-0001-5197-6562","contributorId":347677,"corporation":false,"usgs":false,"family":"Portnyagin","given":"Maxim","affiliations":[{"id":83203,"text":"GEOMAR Helmholtz Center for Ocean Research Kiel, Kiel, 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University","active":true,"usgs":false}],"preferred":false,"id":922154,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Plunkett, Gill 0000-0003-1014-3454","orcid":"https://orcid.org/0000-0003-1014-3454","contributorId":288522,"corporation":false,"usgs":false,"family":"Plunkett","given":"Gill","email":"","affiliations":[{"id":61787,"text":"Queen’s University Belfast","active":true,"usgs":false}],"preferred":false,"id":922155,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Vallance, James W. 0000-0002-3083-5469 jvallance@usgs.gov","orcid":"https://orcid.org/0000-0002-3083-5469","contributorId":547,"corporation":false,"usgs":true,"family":"Vallance","given":"James","email":"jvallance@usgs.gov","middleInitial":"W.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":922156,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Luo, Yantao","contributorId":204972,"corporation":false,"usgs":false,"family":"Luo","given":"Yantao","email":"","affiliations":[{"id":37017,"text":"College of Mathematics and System Sciences, Xinjiang University","active":true,"usgs":false}],"preferred":false,"id":922157,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Cwynar, Les C. 0000-0002-4415-6352","orcid":"https://orcid.org/0000-0002-4415-6352","contributorId":347678,"corporation":false,"usgs":false,"family":"Cwynar","given":"Les C.","affiliations":[{"id":83204,"text":"Department of Biology, University of New Brunswick, Fredericton, Canada","active":true,"usgs":false}],"preferred":false,"id":922158,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Hughes, Paul","contributorId":220209,"corporation":false,"usgs":false,"family":"Hughes","given":"Paul","email":"","affiliations":[{"id":40153,"text":"University of South Hampton, UK","active":true,"usgs":false}],"preferred":false,"id":922159,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Pearson, D. Graham","contributorId":347679,"corporation":false,"usgs":false,"family":"Pearson","given":"D. Graham","affiliations":[{"id":83205,"text":"Department of Earth and Atmospheric Sciences, University of Alberta, Canada","active":true,"usgs":false}],"preferred":false,"id":922160,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}} ,{"id":70261208,"text":"70261208 - 2024 - Mapping and classification of volcanic deposits using multi-sensor unoccupied aerial systems","interactions":[],"lastModifiedDate":"2024-11-29T15:29:11.814371","indexId":"70261208","displayToPublicDate":"2021-10-01T00:00:00","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"Mapping and classification of volcanic deposits using multi-sensor unoccupied aerial systems","docAbstract":"The deposits from volcanic eruptions represent the record of activity at a volcano. Identification, classification, and interpretation of these deposits are crucial to the understanding of volcanic processes and assessing hazards. However, deposits often cover large areas and can be difficult or dangerous to access, making field mapping dangerous and time-consuming. Remote sensing techniques are often used to map and identify the deposits of volcanic eruptions, though these techniques present their own trade-offs in terms of image resolution, wavelength, and observation frequency. Here, we present a new approach for mapping and classifying volcanic deposits using a multi-sensor unoccupied aerial system (UAS), and demonstrate its application on lava and tephra deposits associated with the 2018 eruption of Sierra Negra volcano (Galápagos Archipelago, Ecuador). We surveyed the study area and collected visible and thermal infrared (TIR) images. We used structure-from-motion photogrammetry to create a digital elevation model (DEM) from the visual images and calculated the solar heating rate of the surface from temperature maps based on the TIR images. We find that the solar heating rate is highest for tephra deposits and lowest for ʻaʻā lava, with pāhoehoe lava having intermediate values. This is consistent with the solar heating rate correlating to the density and particle size of the surface. The solar heating rate for the lava flow also decreases with increasing distance from the vent, consistent with an increase in density as the lava degasses. We combined the surface roughness (calculated from the DEM) and the solar heating rate of the surface to remotely classify tephra deposits and different lava morphologies. We applied both supervised and unsupervised machine learning algorithms and demonstrate that supervised methods can replicate the manual classification while the unsupervised method can identify major surface units with no ground truth information. These methods allow for remote mapping and classification at high spatial resolution (< 1 meter) of a variety of volcanic deposits, with potential for application to deposits from other processes (e.g., fluvial, glacial) and deposits on other planetary bodies.","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2021.112581","usgsCitation":"Carr, B.B., Lev, E., Sawi, T., Bennett, K.A., Edwards, C., Soule, S.A., Vallejo Vargas, S., and Marliyani, G.I., 2024, Mapping and classification of volcanic deposits using multi-sensor unoccupied aerial systems: Remote Sensing of Environment, v. 264, 112581, 19 p., https://doi.org/10.1016/j.rse.2021.112581.","productDescription":"112581, 19 p.","ipdsId":"IP-120876","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":467061,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rse.2021.112581","text":"Publisher Index Page"},{"id":464592,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Ecuador","otherGeospatial":"Galápagos Archipelago, Sierra Negra volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -91.2511100637289,\n -0.5953009426430782\n ],\n [\n -91.2511100637289,\n -0.8970296668221494\n ],\n [\n -91.0263665395592,\n -0.8970296668221494\n ],\n [\n -91.0263665395592,\n -0.5953009426430782\n ],\n [\n -91.2511100637289,\n -0.5953009426430782\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"264","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Carr, Brett B. 0000-0002-1033-3082","orcid":"https://orcid.org/0000-0002-1033-3082","contributorId":305984,"corporation":false,"usgs":true,"family":"Carr","given":"Brett","email":"","middleInitial":"B.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":919860,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lev, Einat 0000-0002-8174-0558","orcid":"https://orcid.org/0000-0002-8174-0558","contributorId":194355,"corporation":false,"usgs":false,"family":"Lev","given":"Einat","email":"","affiliations":[{"id":27369,"text":"Lamont-Doherty Earth Observatory at Columbia University","active":true,"usgs":false}],"preferred":false,"id":919861,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sawi, Theresa","contributorId":346761,"corporation":false,"usgs":false,"family":"Sawi","given":"Theresa","email":"","affiliations":[{"id":82958,"text":"Lamont-Doherty Earth Observatory, Columbia University, Palisades, NY","active":true,"usgs":false}],"preferred":false,"id":919862,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bennett, Kristen A. 0000-0001-8105-7129","orcid":"https://orcid.org/0000-0001-8105-7129","contributorId":237068,"corporation":false,"usgs":true,"family":"Bennett","given":"Kristen","email":"","middleInitial":"A.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":919863,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Edwards, Christopher S.","contributorId":206168,"corporation":false,"usgs":false,"family":"Edwards","given":"Christopher S.","affiliations":[{"id":7202,"text":"NAU","active":true,"usgs":false}],"preferred":false,"id":919864,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Soule, S. Adam 0000-0002-4691-6300","orcid":"https://orcid.org/0000-0002-4691-6300","contributorId":221052,"corporation":false,"usgs":false,"family":"Soule","given":"S.","email":"","middleInitial":"Adam","affiliations":[{"id":36711,"text":"Woods Hole Oceanographic Institution","active":true,"usgs":false}],"preferred":false,"id":919865,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Vallejo Vargas, Silvia","contributorId":212772,"corporation":false,"usgs":false,"family":"Vallejo Vargas","given":"Silvia","email":"","affiliations":[{"id":38680,"text":"Instituto Geofisico","active":true,"usgs":false}],"preferred":false,"id":919866,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Marliyani, Gayatri Indah 0000-0003-1356-9645","orcid":"https://orcid.org/0000-0003-1356-9645","contributorId":346762,"corporation":false,"usgs":false,"family":"Marliyani","given":"Gayatri","email":"","middleInitial":"Indah","affiliations":[{"id":82960,"text":"Department of Geological Engineering, Faculty of Engineering, Universitas Gadjah Mada, Yogyakarta, Indonesia","active":true,"usgs":false}],"preferred":false,"id":919867,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70261217,"text":"70261217 - 2024 - Historical and prehistorical water levels of Mormon Lake, Arizona as a measure of climate change on the southwest Colorado Plateau, USA","interactions":[],"lastModifiedDate":"2024-12-02T15:12:29.409176","indexId":"70261217","displayToPublicDate":"2021-03-01T00:00:00","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3218,"text":"Quaternary Research","active":true,"publicationSubtype":{"id":10}},"title":"Historical and prehistorical water levels of Mormon Lake, Arizona as a measure of climate change on the southwest Colorado Plateau, USA","docAbstract":"Mormon Lake, elevation 2166 m with maximum historic surface area of 31.4 km2, lies in a forested endorheic basin covering 103 km2. It is the largest unaltered freshwater body on the 337,000 km2 Colorado Plateau. Prehistorical (before AD 1878) highstands were ca. 9 and 24 m relative to depocenter datum. These levels likely occurred during four multidecadal episodes of cool, wet conditions between ca. 3.55 and 0.20 ka BP. Maximum historical levels (early 1900s) were up to 7.9 m, whereas modern (post-1941) levels were frequently zero or relatively low. Historical climate records indicate reconstructed lake levels correlate directly with annual precipitation and inversely with temperature. Early highstands were associated with above average precipitation and the lowest temperatures of the 116 yr record. The lake receded after 1941; thereafter, frequent drying and low-water levels resulted from recurrent drought and steadily increasing temperatures. Consequently, a wet episode from the 1970s to the 1990s had precipitation like the early 1900s, but highstands were only ca. 3.8 m. The historical lake-level chronology is consistent with changes of hydrologic balance predicted by climate models, that is, reduced effective precipitation (precipitation minus evaporation). These changes, particularly aridification, apparently began in the 1970s or earlier. Global oceanic and atmospheric climate modulate lake levels and regional hydroclimate.
","language":"English","publisher":"Cambridge University Press","doi":"10.1017/qua.2020.92","usgsCitation":"Hereford, R., and Amoroso, L., 2024, Historical and prehistorical water levels of Mormon Lake, Arizona as a measure of climate change on the southwest Colorado Plateau, USA: Quaternary Research, v. 100, p. 32-51, https://doi.org/10.1017/qua.2020.92.","productDescription":"20 p.","startPage":"32","endPage":"51","ipdsId":"IP-113940","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":464625,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Mormon Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111.48876598336788,\n 34.98966103819039\n ],\n [\n -111.48876598336788,\n 34.906130634842924\n ],\n [\n -111.42028354514014,\n 34.906130634842924\n ],\n [\n -111.42028354514014,\n 34.98966103819039\n ],\n [\n -111.48876598336788,\n 34.98966103819039\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"100","noUsgsAuthors":false,"publicationDate":"2020-12-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Hereford, Richard 0000-0002-0892-7367 rhereford@usgs.gov","orcid":"https://orcid.org/0000-0002-0892-7367","contributorId":3620,"corporation":false,"usgs":true,"family":"Hereford","given":"Richard","email":"rhereford@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":919934,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Amoroso, Lee 0000-0003-1342-7487","orcid":"https://orcid.org/0000-0003-1342-7487","contributorId":346805,"corporation":false,"usgs":false,"family":"Amoroso","given":"Lee","affiliations":[],"preferred":false,"id":919935,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70261874,"text":"70261874 - 2024 - Petrology and geochemistry of three early Holocene eruptions from Makushin volcano, Alaska","interactions":[],"lastModifiedDate":"2024-12-31T15:58:26.095859","indexId":"70261874","displayToPublicDate":"2020-10-19T00:00:00","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1109,"text":"Bulletin of Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"Petrology and geochemistry of three early Holocene eruptions from Makushin volcano, Alaska","docAbstract":"Makushin stratovolcano, Alaska, produced three, highly explosive, andesitic eruptions between ~ 9292 and 6215 yBP. Those eruptions are informally named the CFE (“crater-forming eruption”), Nateekin, and Driftwood Pumice, and they deposited significant tephra fallout in the present-day port of Dutch Harbor and City of Unalaska area. The focus of this study is to examine the geochemistry and petrology of those eruptions to better understand Makushin volcano hazards, andesite petrogenesis and eruption triggering by mafic recharge processes. The CFE, Nateekin, and Driftwood Pumice samples range from basaltic andesite to dacite but are predominantly andesitic (SiO2 = 55.6 to 63.5 wt%). The CFE deposits are slightly compositionally stratified, with the top CFE samples slightly more mafic (55 to 60 wt% SiO2) than the basal deposits (58 to 60 wt% SiO2). Disequilibrium mineral compositions and textures in the CFE, Nateekin, and Driftwood Pumice samples, combined with two pyroxene thermometry and An-rich plagioclase microlites (An80) found only in the top of the CFE deposits, provide evidence for repetitive mafic recharge triggering those eruptions, consistent with prior studies. We compare the Makushin geochemical data with data from select satellite vents and cones in the Makushin Volcanic Field (MVF) from prior studies, to examine possible genetic relationships. The geochemical data and Rhyolite-MELTS models run at crustal storage conditions (2 kbar, fO2 = Ni-NiO, and 1.5 and 3.5 wt% H2O) indicate that no single parental magma supplies the MVF satellite cones and Makushin volcano. Instead, two component mixing models better fit the MVF geochemical array. Our Makushin results compare well with models of predominantly andesitic volcanoes that require mafic recharge to mobilize the andesites and trigger eruptions.
","language":"English","publisher":"Springer Nature","doi":"10.1007/s00445-020-01412-5","usgsCitation":"Larsen, J., Schaefer, J., Vallance, J.W., and Neill, O., 2024, Petrology and geochemistry of three early Holocene eruptions from Makushin volcano, Alaska: Bulletin of Volcanology, v. 82, 72, 17 p., https://doi.org/10.1007/s00445-020-01412-5.","productDescription":"72, 17 p.","ipdsId":"IP-120635","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":465566,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Makushin volcano, Unalaska Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -167.01083004545683,\n 53.926684657654704\n ],\n [\n -167.01083004545683,\n 53.84297653402467\n ],\n [\n -166.85080239678533,\n 53.84297653402467\n ],\n [\n -166.85080239678533,\n 53.926684657654704\n ],\n [\n -167.01083004545683,\n 53.926684657654704\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"82","noUsgsAuthors":false,"publicationDate":"2020-10-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Larsen, Jessica 0000-0003-1171-129X","orcid":"https://orcid.org/0000-0003-1171-129X","contributorId":242808,"corporation":false,"usgs":false,"family":"Larsen","given":"Jessica","email":"","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":922107,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schaefer, Janet","contributorId":199547,"corporation":false,"usgs":false,"family":"Schaefer","given":"Janet","affiliations":[],"preferred":false,"id":922108,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vallance, James W. 0000-0002-3083-5469 jvallance@usgs.gov","orcid":"https://orcid.org/0000-0002-3083-5469","contributorId":547,"corporation":false,"usgs":true,"family":"Vallance","given":"James","email":"jvallance@usgs.gov","middleInitial":"W.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":922109,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Neill, O.K.","contributorId":347659,"corporation":false,"usgs":false,"family":"Neill","given":"O.K.","affiliations":[{"id":37387,"text":"University of Michigan","active":true,"usgs":false}],"preferred":false,"id":922110,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70240757,"text":"70240757 - 2024 - Efficient mammal biodiversity surveys for ecological restoration monitoring","interactions":[],"lastModifiedDate":"2024-10-23T15:47:31.059833","indexId":"70240757","displayToPublicDate":"2020-04-01T16:13:20","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2006,"text":"Integrated Environmental Assessment and Management","active":true,"publicationSubtype":{"id":10}},"title":"Efficient mammal biodiversity surveys for ecological restoration monitoring","docAbstract":"Efficient biodiversity surveys are critical for successful restoration monitoring and management. We studied the effect of varying sampling effort on the observed species richness of surveys of small mammals (trapping transects), bats (passive acoustic detection), and medium to large mammals (trail cameras). Field studies provided mammalian biodiversity data for 4 bottomland hardwood restoration sites in northeastern Indiana. Subsampled data were used to simulate monitoring surveys with a range of levels of effort. We then used hierarchical Bayesian nonlinear mixed models to analyze how different components of sampling effort affected observed species richness, a key monitoring outcome. We found that observed small mammal richness increased with the increased number of transects in a survey, while observed bat and medium to large mammal richness increased with the increased duration of sampling. Variation between sites was important for the observed richness of small mammals and bats but not for medium to large mammals. The key driver of richness observed in simulated surveys was related to the spatial scale at which target fauna interact with the habitat, with decreasing richness accompanied by a greater spatial scale of animal–habitat interactions. Our findings suggest taxon-specific recommendations for efficiently quantifying the mammalian diversity of managed sites.
","language":"English","publisher":"Wiley","doi":"10.1002/ieam.4324","usgsCitation":"Green, N., Wildhaber, M.L., Albers, J.L., Pettit, T.W., and Hooper, M.J., 2024, Efficient mammal biodiversity surveys for ecological restoration monitoring: Integrated Environmental Assessment and Management, v. 20, no. 6, p. 1969-1981, https://doi.org/10.1002/ieam.4324.","productDescription":"13 p.","startPage":"1969","endPage":"1981","ipdsId":"IP-110582","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":435587,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9RXPYRL","text":"USGS data release","linkHelpText":"Mammalian biodiversity data for four bottomland hardwood restoration sites in Northeastern Indiana USA May 2015-August 2016"},{"id":413227,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":445571,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ieam.4324","text":"Publisher Index Page"}],"country":"United States","state":"Indiana","city":"Bluffton, New Haven","otherGeospatial":"Bluffton Native Habitat Waterway Project, Deetz Nature Preserve, Fish Creek complex","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -85.20456175119196,\n 40.762112614423955\n ],\n [\n -85.20456175119196,\n 40.70016025503452\n ],\n [\n -85.08914278782409,\n 40.70016025503452\n ],\n [\n -85.08914278782409,\n 40.762112614423955\n ],\n [\n -85.20456175119196,\n 40.762112614423955\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -84.97371420873174,\n 41.57466064563525\n ],\n [\n -84.97371420873174,\n 41.508602936877736\n ],\n [\n -84.83648016376709,\n 41.508602936877736\n ],\n [\n -84.83648016376709,\n 41.57466064563525\n ],\n [\n -84.97371420873174,\n 41.57466064563525\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -85.07991405934287,\n 41.11589628289104\n ],\n [\n -85.07991405934287,\n 41.048923920315474\n ],\n [\n -84.97206799999923,\n 41.048923920315474\n ],\n [\n -84.97206799999923,\n 41.11589628289104\n ],\n [\n -85.07991405934287,\n 41.11589628289104\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"20","issue":"6","noUsgsAuthors":false,"publicationDate":"2020-08-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Green, Nicholas S. 0000-0002-8538-4191","orcid":"https://orcid.org/0000-0002-8538-4191","contributorId":202040,"corporation":false,"usgs":true,"family":"Green","given":"Nicholas S.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":864719,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wildhaber, Mark L. 0000-0002-6538-9083 mwildhaber@usgs.gov","orcid":"https://orcid.org/0000-0002-6538-9083","contributorId":1386,"corporation":false,"usgs":true,"family":"Wildhaber","given":"Mark","email":"mwildhaber@usgs.gov","middleInitial":"L.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":864720,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Albers, Janice L. 0000-0002-6312-8269 jalbers@usgs.gov","orcid":"https://orcid.org/0000-0002-6312-8269","contributorId":3972,"corporation":false,"usgs":true,"family":"Albers","given":"Janice","email":"jalbers@usgs.gov","middleInitial":"L.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":864721,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pettit, Thomas W.","contributorId":239722,"corporation":false,"usgs":false,"family":"Pettit","given":"Thomas","email":"","middleInitial":"W.","affiliations":[{"id":47988,"text":"University of Maryland University College-Asia, Unit 5060","active":true,"usgs":false}],"preferred":false,"id":864722,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hooper, Michael J. 0000-0002-4161-8961 mhooper@usgs.gov","orcid":"https://orcid.org/0000-0002-4161-8961","contributorId":3251,"corporation":false,"usgs":true,"family":"Hooper","given":"Michael","email":"mhooper@usgs.gov","middleInitial":"J.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":864723,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70261302,"text":"70261302 - 2024 - Mapping the resistivity structure of Walker Ridge 313 in the Gulf of Mexico using the marine CSEM method","interactions":[],"lastModifiedDate":"2024-12-05T15:17:07.841811","indexId":"70261302","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2682,"text":"Marine and Petroleum Geology","active":true,"publicationSubtype":{"id":10}},"title":"Mapping the resistivity structure of Walker Ridge 313 in the Gulf of Mexico using the marine CSEM method","docAbstract":"A marine controlled source electromagnetic (CSEM) campaign was carried out in the Gulf of Mexico to further develop marine electromagnetic techniques in order to aid the detection and mapping of gas hydrate deposits. Marine CSEM methods are used to obtain an electrical resistivity structure of the subsurface which can indicate the type of substance filling the pore space, such as gas hydrates which are more resistive. Results from the Walker Ridge 313 study (WR 313) are presented in this paper and compared with the Gulf of Mexico Gas Hydrate Joint Industry Project II (JIP2) logging while drilling (LWD) results and available seismic data. The hydrate, known to exist within sheeted sand deposits, is mapped as a resistive region in the two dimensional (2D) CSEM inversion models. This is consistent with the JIP2 LWD resistivity results. CSEM inversions that use seismic horizons provide more realistic results compared to the unconstrained inversions by providing sharp boundaries and architectural control on the location of the resistive and conductive regions in the CSEM model. The seismic horizons include: 1) the base of the gas hydrate stability zone (BGHSZ), 2) the top of salt, and 3) the top and bottom of a fine grained marine mud interval with near vertical hydrate filled fractures, to constrain the CSEM inversion model. The top of salt provides improved location for brines, water saturated salt, and resistive salt. Inversions of the CSEM data map the occurrence of a ‘halo’ of conductive brines above salt. The use of the BGHSZ as a constraint on the inversion helps distinguish between free gas and gas hydrate as well as gas hydrate and water saturated sediments.","language":"English","publisher":"Elsevier","doi":"10.1016/j.marpetgeo.2017.08.039","usgsCitation":"Weitemeyer, K., Constable, S., Shelander, D., and Haines, S.S., 2024, Mapping the resistivity structure of Walker Ridge 313 in the Gulf of Mexico using the marine CSEM method: Marine and Petroleum Geology, v. 88, p. 1013-1031, https://doi.org/10.1016/j.marpetgeo.2017.08.039.","productDescription":"19 p.","startPage":"1013","endPage":"1031","ipdsId":"IP-088265","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":467064,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.marpetgeo.2017.08.039","text":"Publisher Index Page"},{"id":464802,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","city":"Houma","otherGeospatial":"Gulf of Mexico, Walker Ridge 313","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -91.65721574777587,\n 29.904859799956952\n ],\n [\n -91.65721574777587,\n 25.48122420526559\n ],\n [\n -88.62636230717828,\n 25.48122420526559\n ],\n [\n -88.62636230717828,\n 29.904859799956952\n ],\n [\n -91.65721574777587,\n 29.904859799956952\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"88","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Weitemeyer, Karen","contributorId":346936,"corporation":false,"usgs":false,"family":"Weitemeyer","given":"Karen","affiliations":[{"id":37955,"text":"University of Southampton","active":true,"usgs":false}],"preferred":false,"id":920301,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Constable, Steven","contributorId":346937,"corporation":false,"usgs":false,"family":"Constable","given":"Steven","affiliations":[{"id":83021,"text":"Scripps Institute for Oceanography","active":true,"usgs":false}],"preferred":false,"id":920302,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shelander, Dianna","contributorId":346938,"corporation":false,"usgs":false,"family":"Shelander","given":"Dianna","affiliations":[{"id":27162,"text":"Schlumberger","active":true,"usgs":false}],"preferred":false,"id":920303,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Haines, Seth S. 0000-0003-2611-8165 shaines@usgs.gov","orcid":"https://orcid.org/0000-0003-2611-8165","contributorId":1344,"corporation":false,"usgs":true,"family":"Haines","given":"Seth","email":"shaines@usgs.gov","middleInitial":"S.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":920304,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70242629,"text":"ofr20231032 - 2023 - Re-prioritization of the U.S. Geological Survey Federal Priority Streamgage Network, 2022","interactions":[],"lastModifiedDate":"2025-04-08T14:39:10.436307","indexId":"ofr20231032","displayToPublicDate":"2025-04-07T15:50:00","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-1032","displayTitle":"Re-Prioritization of the U.S. Geological Survey Federal Priority Streamgage Network, 2022","title":"Re-prioritization of the U.S. Geological Survey Federal Priority Streamgage Network, 2022","docAbstract":"The Federal Priority Streamgage (FPS) network of the U.S. Geological Survey (USGS), created in 1999 as the National Streamflow Information Program, receives Congressional appropriations to support the operation of a federally-funded “backbone” network of streamflow gages across the United States that are designated to meet the “Federal needs” or priorities of the country. Anticipating the evolution of Federal stakeholder water-data needs, the USGS launched a re-evaluation of the fundamental priorities for the FPS network in October 2020. In March 2022, the FPS Re-Prioritization Project used an online survey to solicit feedback from 767 stakeholders representing 22 Federal agencies who benefit from the FPS network. Additional feedback from survey respondents was obtained during online listening sessions to validate the USGS’s understanding of current Federal water-data needs. Results of the feedback show that the original five network priorities identified by the U.S. Geological Survey in 1999 are still valid but require modification to better incorporate additional needs, including Federal water operations, streamflow trends and extremes, water rights involving Federal lands, and streamflow data supporting ecosystem health. Federal stakeholder feedback also indicated that the inclusion of precipitation and water-temperature data collection, along with stream imagery, would enhance the value of the FPS network.
Results of the FPS Re-Prioritization Project and Open Season that ended in May 2024 revealed that the number of FPS locations meeting the updated eligibility criteria nearly tripled, which illustrates the value of the information provided by the FPS network. The Water Forecasting & Operations and the Water Quality network priorities contributed to the largest number of new eligible FPS sites, demonstrating the importance of the FPS network in supporting informed decisions related to the protection of life, property, the environment, and the economy of the United States.
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Water Mission Area
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, Virginia 20192
Numerical modeling of groundwater flow systems was once accessible only to modeling specialists in the hydrogeological community. Software such as MODFLOW—the most frequently used groundwater modeling program in the world—and associated graphical user interfaces (GUIs) have made modeling possible for most groundwater scientists. This book provides the bridge from understanding to implementing models by introducing the basics of MODFLOW version 6 and providing readers who have a working knowledge of groundwater flow with a guide through construction of their first groundwater model.
","language":"English","publisher":"Groundwater Project","doi":"10.21083/978-1-77470-030-3","usgsCitation":"Winston, R.B., 2023, Getting Started with MODFLFOW, 243 p., https://doi.org/10.21083/978-1-77470-030-3.","productDescription":"243 p.","ipdsId":"IP-159533","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":462868,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Winston, Richard B. 0000-0002-6287-8834 rbwinst@usgs.gov","orcid":"https://orcid.org/0000-0002-6287-8834","contributorId":3567,"corporation":false,"usgs":true,"family":"Winston","given":"Richard","email":"rbwinst@usgs.gov","middleInitial":"B.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":915747,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70259931,"text":"70259931 - 2023 - The presence of silicate melt may enhance rates of cation diffusion in olivine","interactions":[],"lastModifiedDate":"2024-10-28T11:18:22.113863","indexId":"70259931","displayToPublicDate":"2024-09-27T06:17:16","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1427,"text":"Earth and Planetary Science Letters","active":true,"publicationSubtype":{"id":10}},"title":"The presence of silicate melt may enhance rates of cation diffusion in olivine","docAbstract":"From 2020 to 2023, a new spill program was implemented to aid the downstream passage of juvenile salmonids at mainstem dams on the Snake and Columbia rivers. Under this program, the total dissolved gas (TDG) cap was increased to 125% and monitoring of nonsalmonids for gas bubble trauma (GBT) became a requirement. The primary objective of this work and report was to measure the incidence and severity of GBT in nonsalmonids resulting from increased juvenile salmonid passage spill and associated levels of TDG during the spring spill period in 2023. Nonsalmonids were collected downstream from Bonneville, McNary, Ice Harbor, and Lower Granite dams and examined for the incidence and severity of GBT in 2023. Fish were collected at each location weekly (3 April to 20 June) during the spring spill period by backpack electrofishing and beach seining. Washington and Oregon State water quality agencies established minimum and target sample sizes for monitoring, but the minimum sample size of 50 fish and target sample size of 100 fish were not met in all weeks at individual projects due to high water flows and resulting low fish collections. Collected fish were examined for GBT according to the criteria and protocol established for the regional smolt monitoring program (SMP). TDG levels were often high relative to the 10-year average. GBT incidence rates and severity (according to SMP criteria) were low to moderate in most weeks. We found no apparent relationship between GBT incidence and TDG due to exposure history and interspecies susceptibility to elevated TDG that could not be quantified. GBT incidence rates exceeded the 15% threshold on two occasions below Ice Harbor Dam, triggering a reduction in spill under the State water quality standards. In the weeks immediately following the spill reductions, GBT incidence was zero or relatively low at this location. Sculpin (genus Cottus) was the main species collected at all locations. As in past years, we did find GBT in non-SMP protocol areas, particularly in sculpin. The variability in GBT incidence rates is likely due to variability in environmental conditions, fish exposure history to TDG, and species sensitivity to TDG. Many of the species encountered in shallow shoreline habitats rear for extended times and probably do not seek the water depths that would help them reduce the effects of exposure to elevated TDG through depth compensation. Limited systematic sampling of TDG in the tailraces of each project showed that TDG can vary spatially within the tailrace and with percentage of water spilled.
We investigated GBT progression and mortality in sculpin and threespine stickleback (Gasterosteus aculeatus) in laboratory experiments (Chapter Two of this report). Fish were tested at 120%, 125%, and 130% TDG. We found that sculpin are more sensitive to TDG than stickleback and that GBT and associated mortality progress faster in sculpin than in stickleback. GBT prevalence and severity increased through time at all TDG levels tested, but relationships between severity and exposure time were weak or nonexistent. GBT and mortality progressed more rapidly as TDG increased in both species. The SMP criteria used to rank GBT did not fully capture the incidence and severity of GBT in sculpin and stickleback compared to using criteria based on all areas of the fish. The lateral line, body, dorsal fin, and pectoral fins were common locations of GBT in sculpin at 120 and 125% TDG, but signs were more prevalent in all areas at 130% TDG. In stickleback, GBT was most common on the head and body at all TDG levels tested. Positive buoyancy of fish with severe GBT was observed in both species and may have consequences for similarly impaired fish in the wild. The proximate cause of GBT-related death in sculpin and stickleback was bubbles in the gills and heart, but unlike in other species, bubbles appeared rapidly just before the point of death. Our results help fill the information void GBT progression and mortality for sculpin and stickleback.
","language":"English","publisher":"Bonneville Power Administration","usgsCitation":"Tiffan, K., Liedtke, B.D., and Benson, S.L., 2023, Nonsalmonid gas bubble trauma investigations, iv, 72 p.","productDescription":"iv, 72 p.","ipdsId":"IP-161003","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":427256,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://www.cbfish.org/PiscesPublication.mvc/SearchByTitleDescriptionAuthorOrDate","linkFileType":{"id":5,"text":"html"}},{"id":427266,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon, Washington","otherGeospatial":"Columbia River, Snake River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -115.5048072586187,\n 46.75882851790945\n ],\n [\n -121.95470738831573,\n 46.75882851790945\n ],\n [\n -121.95470738831573,\n 44.57823653678298\n ],\n [\n -115.5048072586187,\n 44.57823653678298\n ],\n [\n -115.5048072586187,\n 46.75882851790945\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"editors":[{"text":"Tiffan, Kenneth 0000-0002-5831-2846","orcid":"https://orcid.org/0000-0002-5831-2846","contributorId":217812,"corporation":false,"usgs":true,"family":"Tiffan","given":"Kenneth","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":897761,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Tiffan, Kenneth 0000-0002-5831-2846","orcid":"https://orcid.org/0000-0002-5831-2846","contributorId":217812,"corporation":false,"usgs":true,"family":"Tiffan","given":"Kenneth","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":897723,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Liedtke, Brad D. 0000-0002-0458-7377","orcid":"https://orcid.org/0000-0002-0458-7377","contributorId":303795,"corporation":false,"usgs":true,"family":"Liedtke","given":"Brad","middleInitial":"D.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":897724,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Benson, Scott Louis 0000-0003-0397-1200","orcid":"https://orcid.org/0000-0003-0397-1200","contributorId":303796,"corporation":false,"usgs":true,"family":"Benson","given":"Scott","email":"","middleInitial":"Louis","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":897725,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70252082,"text":"70252082 - 2023 - A characterization of the deep-sea coral and sponge community along the Oregon Coast using a remotely operated vehicle on the EXPRESS 2022 expedition","interactions":[],"lastModifiedDate":"2024-03-13T12:00:53.285075","indexId":"70252082","displayToPublicDate":"2023-12-31T06:58:52","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"A characterization of the deep-sea coral and sponge community along the Oregon Coast using a remotely operated vehicle on the EXPRESS 2022 expedition","docAbstract":"Deep-sea coral and sponge (DSCS) communities serve as essential fish habitat (EFH) by providing shelter and nursery habitat, increasing diversity, and increasing prey availability (Freese and Wing, 2003; Bright, 2007; Baillon et al., 2012; Henderson et al., 2020). Off the U.S. West Coast, threats to these long-lived, fragile organisms from bottom contact fishing gear, potential offshore renewable energy development, and ocean warming and acidification have been the subject of recent research (Gomez et al., 2018; Salgado et al., 2018; Yoklavich, et al., 2018; Gugliotti et al., 2019). Other DSCS studies have reported new species (Yoklavich and Love, 2005), analyzed species distribution and abundance (Tissot et al., 2006, Watters et al., 2022), developed predictive distribution models (Huff et al., 2013; Rooper et al., 2017; Kreidler, 2020), and discovered medicinal uses for corals and sponges (Essack et al., 2011; Shrestha et al., 2018). Due to the vast area of unexplored seafloor within the territorial waters and the U.S. exclusive economic zone (EEZ; 12-200 nautical miles off the coast) and the technological requirements and expense of deep-sea research, there is still much to learn about the distributions and biology of DSCS. This information is critical to resource managers for effective conservation and management of DSCS habitats. In order to minimize the adverse impacts of fishing on EFH, the Pacific Fishery Management Council (PFMC) and National Marine Fisheries Service (NMFS) designated several seafloor habitat areas as EFH conservation areas (EFHCA), first in 2006 (as part of Amendment 19 to the Pacific coast groundfish fishery management plan) and then again in 2020 (as part of Amendment 28). These areas are closed to bottom trawl fishing at a minimum, and in some cases to all bottom contact fishing gears. In addition to protections afforded by EFH-related regulations, the National Marine Sanctuary Program prohibits certain non-fishing activities within areas designated as national marine sanctuaries, such as oil and gas exploration or extraction, cable laying, and other forms of seabed alteration or construction that disturb benthic communities. NOAA’s Deep-Sea Coral and Research Technology Program (DSCRTP) began a 4-yr funding initiative for the U.S. West Coast in 2017. The goals of the West Coast Deep-Sea Coral Initiative (WCDSCI) were to: 1) gather baseline information on areas subject to fishing regulation changes prior to the implementation of Amendment 28; 2) improve our understanding of known DSCS bycatch “hot spots”; and 3) explore and assess DSCS resources within NOAA National Marine Sanctuaries with emphasis on areas of sanctuary resource protection and management concerns. As part of the WCDSCU, an 11-day expedition (3 Sep – 13 Sep 2022) was launched from the NOAA Ship Bell M. Shimada, beginning and ending in Newport, OR. The science team assembled for this cruise were members of the EXpanding Pacific Research and Exploration of Submerged Systems (EXPRESS) campaign, which brings together researchers from federal and nonfederal institutions to collaborate on scientific expeditions targeting the deepwater areas off California, Oregon, and Washington. EXPRESS supports researchers leveraging funding, resources, personnel, and expertise to accomplish more science than would have been possible by a single entity alone. The 2022 expedition included research partners from National Marine Fisheries Service (NMFS) Southwest Fisheries Science Center (SWFSC) and Northwest Fisheries Science Center (NWFSC), Bureau of Ocean Energy Management (BOEM), U.S. Geological Survey (USGS), Pacific Fisheries Management Council Habitat Committee, and Woods Hole Oceanographic Institution.
","language":"English","publisher":"NOAA","doi":"10.25923/tmb0-ce70","usgsCitation":"Laidig, T., Watters, D., Everett, M., Prouty, N.G., and Clarke, E., 2023, A characterization of the deep-sea coral and sponge community along the Oregon Coast using a remotely operated vehicle on the EXPRESS 2022 expedition, 42 p., https://doi.org/10.25923/tmb0-ce70.","productDescription":"42 p.","ipdsId":"IP-161913","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":426580,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Laidig, Tom","contributorId":270131,"corporation":false,"usgs":false,"family":"Laidig","given":"Tom","email":"","affiliations":[{"id":56090,"text":"NOAA Fisheries, SWFSC, Fisheries Ecology Division, Santa Cruz, CA","active":true,"usgs":false}],"preferred":false,"id":896545,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Watters, Diana","contributorId":270132,"corporation":false,"usgs":false,"family":"Watters","given":"Diana","email":"","affiliations":[{"id":56090,"text":"NOAA Fisheries, SWFSC, Fisheries Ecology Division, Santa Cruz, CA","active":true,"usgs":false}],"preferred":false,"id":896546,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Everett, Meredith","contributorId":270133,"corporation":false,"usgs":false,"family":"Everett","given":"Meredith","email":"","affiliations":[{"id":56092,"text":"NOAA Fisheries, NWFSC, Seattle WA","active":true,"usgs":false}],"preferred":false,"id":896547,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Prouty, Nancy G. 0000-0002-8922-0688 nprouty@usgs.gov","orcid":"https://orcid.org/0000-0002-8922-0688","contributorId":3350,"corporation":false,"usgs":true,"family":"Prouty","given":"Nancy","email":"nprouty@usgs.gov","middleInitial":"G.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":896548,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Clarke, Elizabeth","contributorId":334799,"corporation":false,"usgs":false,"family":"Clarke","given":"Elizabeth","email":"","affiliations":[{"id":80252,"text":"NOAA Fisheries, Northwest Fisheries Science Center, Seattle, Washington","active":true,"usgs":false}],"preferred":false,"id":896549,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70251032,"text":"70251032 - 2023 - Predicting large hydrothermal systems","interactions":[],"lastModifiedDate":"2024-01-19T00:54:41.01672","indexId":"70251032","displayToPublicDate":"2023-12-29T18:53:20","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1827,"text":"Geothermal Resources Council Transactions","active":true,"publicationSubtype":{"id":10}},"title":"Predicting large hydrothermal systems","docAbstract":"We train five models using two machine learning (ML) regression algorithms (i.e., linear regression and XGBoost) to predict hydrothermal upflow in the Great Basin. Feature data are extracted from datasets supporting the INnovative Geothermal Exploration through Novel Investigations Of Undiscovered Systems project (INGENIOUS). The label data (the reported convective signals) are extracted from measured thermal gradients in wells by comparing the total estimated heat flow at the wells to the modeled background conductive heat flow. That is, the reported convective signal is the difference between the background conductive heat flow and the well heat flow. The reported convective signals contain outliers that may affect upflow prediction, so the influence of outliers is tested by constructing models for two cases: 1) using all the data (i.e., -91 to 11,105 mW/m2), and 2) truncating the range of labels to include only reported convective signals between -25 and 200 mW/m2. Because hydrothermal systems are sparse, models that predict high convective signal in smaller areas better match the natural frequency of hydrothermal systems. Early results demonstrate that XGBoost outperforms linear regression. For XGBoost using the truncated range of labels, half of the high reported signals are within < 3 % of the highest predictions. For XGBoost using the entire range of labels, half of the high reported signals are in < 13 % of the highest predictions. While this implies that the truncated regression is superior, the all-data model better predicts the locations of power-producing systems (i.e., the operating power plants are in a smaller fraction of the study area given by the highest predictions). Even though the models generally predict greater hydrothermal upflow for higher reported convective signals than for lower reported convective signals, both XGBoost models consistently underpredict the magnitude of higher signals. This behavior is attributed to low resolution/granularity of input features compared with the scale of a hydrothermal upflow zone (a few km or less across). Trouble estimating exact values while still reliably predicting high versus low convective signals suggests that a future strategy such as ranked ordinal regression (e.g., classifying into ordered bins for low, medium, high, and very high convective signal) might fit better models, since doing so reduces problems introduced by outliers while preserving the property of larger versus smaller signals.","language":"English","publisher":"Geothermal Rising","usgsCitation":"Mordensky, S.P., Burns, E.R., DeAngelo, J., and Lipor, J., 2023, Predicting large hydrothermal systems: Geothermal Resources Council Transactions, v. 47, p. 1763-1796.","productDescription":"34 p.","startPage":"1763","endPage":"1796","ipdsId":"IP-154718","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":424578,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.geothermal-library.org/index.php?mode=pubs&action=view&record=1034861"},{"id":424600,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"47","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Mordensky, Stanley Paul 0000-0001-8607-303X","orcid":"https://orcid.org/0000-0001-8607-303X","contributorId":292014,"corporation":false,"usgs":true,"family":"Mordensky","given":"Stanley","email":"","middleInitial":"Paul","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":892806,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burns, Erick R. 0000-0002-1747-0506 eburns@usgs.gov","orcid":"https://orcid.org/0000-0002-1747-0506","contributorId":192154,"corporation":false,"usgs":true,"family":"Burns","given":"Erick","email":"eburns@usgs.gov","middleInitial":"R.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":892807,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DeAngelo, Jacob 0000-0002-7348-7839 jdeangelo@usgs.gov","orcid":"https://orcid.org/0000-0002-7348-7839","contributorId":237879,"corporation":false,"usgs":true,"family":"DeAngelo","given":"Jacob","email":"jdeangelo@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":892808,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lipor, John 0000-0002-0990-5493","orcid":"https://orcid.org/0000-0002-0990-5493","contributorId":292015,"corporation":false,"usgs":false,"family":"Lipor","given":"John","email":"","affiliations":[{"id":6929,"text":"Portland State University","active":true,"usgs":false}],"preferred":false,"id":892809,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70251029,"text":"70251029 - 2023 - Cursed? Why one does not simply add new data sets to supervised geothermal machine learning models","interactions":[],"lastModifiedDate":"2024-01-19T00:50:22.910296","indexId":"70251029","displayToPublicDate":"2023-12-29T18:49:27","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1827,"text":"Geothermal Resources Council Transactions","active":true,"publicationSubtype":{"id":10}},"title":"Cursed? Why one does not simply add new data sets to supervised geothermal machine learning models","docAbstract":"Recent advances in machine learning (ML) identifying areas favorable to hydrothermal systems indicate that the resolution of feature data remains a subject of necessary improvement before ML can reliably produce better models. Herein, we consider the value of adding new features or replacing other, low-value features with new input features in existing ML pipelines. Our previous work identified stress and seismicity as having less value than the other feature types (i.e., heat flow, distance to faults, and distance to magmatic activity) for the 2008 USGS hydrothermal energy assessment; hence, a fundamental question regards if the addition of new but partially correlated features will improve resulting models for hydrothermal favorability. Therefore, we add new maps for shear strain rate and dilation strain rate to fit logistic regression and XGBoost models, resulting in new 7-feature models that are compared to the old 5-feature models. Because these new features share a degree of correlation with the original relatively uninformative stress and seismicity features, we also consider replacement of the two lower-value features with the two new features, creating new 5-feature models.\n\nAdding the new features improves the predictive skill of the new 7-feature model over that of the old 5-feature model; albeit, that improvement is not statistically significant because the new features are correlated with the old features and, consequently, the new features do not present considerable new information. However, the new 5-feature XGBoost model has a statistically significant increase in predictive skill for known positives over the old 5-feature model at p = 0.06. This improved performance is due to the lower-dimensional feature space of the former than that of the latter. In higher-dimensional feature space, relationships between features and the presence or absence of hydrothermal systems are harder to discern (i.e., the 7-feature model likely suffers from the “curse of dimensionality”).","language":"English","publisher":"Geothermal Rising","usgsCitation":"Mordensky, S.P., Burns, E.R., Lipor, J., and DeAngelo, J., 2023, Cursed? Why one does not simply add new data sets to supervised geothermal machine learning models: Geothermal Resources Council Transactions, v. 47, p. 1288-1313.","productDescription":"26 p.","startPage":"1288","endPage":"1313","ipdsId":"IP-153961","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":424577,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.geothermal-library.org/index.php?mode=pubs&action=view&record=1034860"},{"id":424599,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"47","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Mordensky, Stanley Paul 0000-0001-8607-303X","orcid":"https://orcid.org/0000-0001-8607-303X","contributorId":292014,"corporation":false,"usgs":true,"family":"Mordensky","given":"Stanley","email":"","middleInitial":"Paul","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":892802,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burns, Erick R. 0000-0002-1747-0506 eburns@usgs.gov","orcid":"https://orcid.org/0000-0002-1747-0506","contributorId":192154,"corporation":false,"usgs":true,"family":"Burns","given":"Erick","email":"eburns@usgs.gov","middleInitial":"R.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":892803,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lipor, John 0000-0002-0990-5493","orcid":"https://orcid.org/0000-0002-0990-5493","contributorId":292015,"corporation":false,"usgs":false,"family":"Lipor","given":"John","email":"","affiliations":[{"id":6929,"text":"Portland State University","active":true,"usgs":false}],"preferred":false,"id":892804,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"DeAngelo, Jacob 0000-0002-7348-7839 jdeangelo@usgs.gov","orcid":"https://orcid.org/0000-0002-7348-7839","contributorId":237879,"corporation":false,"usgs":true,"family":"DeAngelo","given":"Jacob","email":"jdeangelo@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":892805,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70251035,"text":"70251035 - 2023 - Don’t Let Negatives Hold You Back: Accounting for Underlying Physics and Natural Distributions of Hydrothermal Systems When Selecting Negative Training Sites Leads to Better Machine Learning Predictions","interactions":[],"lastModifiedDate":"2024-01-19T00:46:05.573324","indexId":"70251035","displayToPublicDate":"2023-12-29T18:45:02","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1827,"text":"Geothermal Resources Council Transactions","active":true,"publicationSubtype":{"id":10}},"title":"Don’t Let Negatives Hold You Back: Accounting for Underlying Physics and Natural Distributions of Hydrothermal Systems When Selecting Negative Training Sites Leads to Better Machine Learning Predictions","docAbstract":"Selecting negative training sites is an important challenge to resolve when utilizing machine learning (ML) for predicting hydrothermal resource favorability because ideal models would discriminate between hydrothermal systems (positives) and all types of locations without hydrothermal systems (negatives). The Nevada Machine Learning project (NVML) fit an artificial neural network to identify areas favorable for hydrothermal systems by selecting 62 negative sites where the research team had confidence that no hydrothermal resource exists. Herein, we compare the implications of the expert selection of negatives (i.e., the NVML strategy) with a random sample strategy, where it is assumed that areas outside the favorable structural ellipses defined by NVML are negative. Because hydrothermal systems are sparse, it is highly probable that, in the absence of a favorable geological structure, hydrothermal favorability is low. We compare three training strategies: 1) the positive and negative labeled examples from NVML; 2) the positive examples from NVML with randomly selected negatives in equal frequency as NVML; and 3) the positive examples from NVML with randomly selected negatives reflecting the expected natural distribution of hydrothermal systems relative to the total area. We apply these training strategies to the NVML feature data (input data) using two ML algorithms (XGBoost and logistic regression) to create six favorability maps for hydrothermal resources. When accounting for the expected natural distribution of hydrothermal systems, we find that XGBoost performs better than the NVML neural network and its negatives. Model validation was less reliable using F1 scores, a common performance metric, than comparing probability estimates at known positives, likely because of the extreme natural class imbalance and the lack of negatively labeled sites. This work demonstrates that expert selection of negatives for training in NVML likely imparted modeling bias. Accounting for the sparsity of hydrothermal systems and all the types of locations without hydrothermal systems allows us to create better models for predicting hydrothermal resource favorability.","language":"English","publisher":"Geothermal Rising","usgsCitation":"Caraccioli, P.D., Mordensky, S.P., Lindsey, C.R., DeAngelo, J., Burns, E.R., and Lipor, J., 2023, Don’t Let Negatives Hold You Back: Accounting for Underlying Physics and Natural Distributions of Hydrothermal Systems When Selecting Negative Training Sites Leads to Better Machine Learning Predictions: Geothermal Resources Council Transactions, v. 47, p. 1672-1693.","productDescription":"22 p.","startPage":"1672","endPage":"1693","ipdsId":"IP-155549","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":424598,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":424597,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.geothermal-library.org/index.php?mode=pubs&action=view&record=1034774"}],"volume":"47","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Caraccioli, Pascal D. 0009-0003-6711-8257","orcid":"https://orcid.org/0009-0003-6711-8257","contributorId":333435,"corporation":false,"usgs":false,"family":"Caraccioli","given":"Pascal","email":"","middleInitial":"D.","affiliations":[{"id":6929,"text":"Portland State University","active":true,"usgs":false}],"preferred":false,"id":892810,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mordensky, Stanley Paul 0000-0001-8607-303X","orcid":"https://orcid.org/0000-0001-8607-303X","contributorId":292014,"corporation":false,"usgs":true,"family":"Mordensky","given":"Stanley","email":"","middleInitial":"Paul","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":892811,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lindsey, Cary R. 0000-0001-5693-9664","orcid":"https://orcid.org/0000-0001-5693-9664","contributorId":333436,"corporation":false,"usgs":false,"family":"Lindsey","given":"Cary","email":"","middleInitial":"R.","affiliations":[{"id":79883,"text":"USGS for this work (just joined GBCGE at UNR)","active":true,"usgs":false}],"preferred":false,"id":892812,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"DeAngelo, Jacob 0000-0002-7348-7839 jdeangelo@usgs.gov","orcid":"https://orcid.org/0000-0002-7348-7839","contributorId":237879,"corporation":false,"usgs":true,"family":"DeAngelo","given":"Jacob","email":"jdeangelo@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":892813,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Burns, Erick R. 0000-0002-1747-0506 eburns@usgs.gov","orcid":"https://orcid.org/0000-0002-1747-0506","contributorId":192154,"corporation":false,"usgs":true,"family":"Burns","given":"Erick","email":"eburns@usgs.gov","middleInitial":"R.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":892814,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lipor, John 0000-0002-0990-5493","orcid":"https://orcid.org/0000-0002-0990-5493","contributorId":292015,"corporation":false,"usgs":false,"family":"Lipor","given":"John","email":"","affiliations":[{"id":6929,"text":"Portland State University","active":true,"usgs":false}],"preferred":false,"id":892815,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70250726,"text":"pp1862O - 2023 - Ground-motion prediction equations for the western Kingdom of Saudi Arabia","interactions":[{"subject":{"id":70250726,"text":"pp1862O - 2023 - Ground-motion prediction equations for the western Kingdom of Saudi Arabia","indexId":"pp1862O","publicationYear":"2023","noYear":false,"chapter":"O","displayTitle":"Ground-Motion Prediction Equations for the Western Kingdom of Saudi Arabia","title":"Ground-motion prediction equations for the western Kingdom of Saudi Arabia"},"predicate":"IS_PART_OF","object":{"id":70250730,"text":"pp1862 - 2023 - Active volcanism on the Arabian Shield—Geology, volcanology, and geophysics of northern Harrat Rahat and vicinity, Kingdom of Saudi Arabia","indexId":"pp1862","publicationYear":"2023","noYear":false,"title":"Active volcanism on the Arabian Shield—Geology, volcanology, and geophysics of northern Harrat Rahat and vicinity, Kingdom of Saudi Arabia"},"id":1}],"isPartOf":{"id":70250730,"text":"pp1862 - 2023 - Active volcanism on the Arabian Shield—Geology, volcanology, and geophysics of northern Harrat Rahat and vicinity, Kingdom of Saudi Arabia","indexId":"pp1862","publicationYear":"2023","noYear":false,"title":"Active volcanism on the Arabian Shield—Geology, volcanology, and geophysics of northern Harrat Rahat and vicinity, Kingdom of Saudi Arabia"},"lastModifiedDate":"2024-01-02T17:07:03.833538","indexId":"pp1862O","displayToPublicDate":"2023-12-29T14:30:20","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":331,"text":"Professional Paper","code":"PP","onlineIssn":"2330-7102","printIssn":"1044-9612","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1862","chapter":"O","displayTitle":"Ground-Motion Prediction Equations for the Western Kingdom of Saudi Arabia","title":"Ground-motion prediction equations for the western Kingdom of Saudi Arabia","docAbstract":"Ground-motion prediction equations (GMPEs) for the western Kingdom of Saudi Arabia are developed by employing a mixed-effects regression model to modify the Boore and others (2014) Next Generation Attenuation-West2 (NGA-West2) project GMPEs. NGA-West2 addressed several key issues concerning GMPEs for shallow crustal earthquakes in active tectonic regions. However, the NGA-West2 input data do not include many earthquakes in extensional regimes, such as those occurring in Saudi Arabia. This deficiency is redressed by calculating a magnitude scaling of the new Saudi Arabia-specific GMPEs compared to those of Boore and others (2014). Furthermore, there is a clear difference in distance scaling for the Saudi Arabian GMPEs in comparison with the NGA-West2 GMPEs. This difference is especially significant at large distances and is mainly due to lower anelastic attenuation in the crystalline crust of western Saudi Arabia. Our empirical data demonstrate that the GMPEs presented here are in good agreement with observed earthquake ground motions in western Saudi Arabia.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1862O","collaboration":"Jointly published with the Saudi Geological Survey [as Saudi Geological Survey Special Report SGS–SP–2021–1]","usgsCitation":"Kiuchi, R., Mooney, W.D., and Zahran, H.M., 2023, Ground-motion prediction equations for the western Kingdom of Saudi Arabia, chap. O of Sisson, T.W., Calvert, A.T., and Mooney, W.D., eds., Active volcanism on the Arabian Shield—Geology, volcanology, and geophysics of northern Harrat Rahat and vicinity, Kingdom of Saudi Arabia: U.S. Geological Survey Professional Paper 1862 [also released as Saudi Geological Survey Special Report SGS–SP–2021–1], 31 p., https://doi.org/10.3133/pp1862O.","productDescription":"vi, 31 p.","numberOfPages":"31","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-129536","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":423991,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1862/o/pp1862o.pdf","text":"Report","size":"11.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1862-O"},{"id":423990,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1862/o/coverthbo.jpg"}],"country":"Kingdom of Saudi Arabia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 42.75602070222271,\n 16.211495469022466\n ],\n [\n 44.958829363645094,\n 18.547056756745135\n ],\n [\n 37.40933785513795,\n 29.652243786014196\n ],\n [\n 34.965989081794106,\n 29.331606356788228\n ],\n [\n 34.66613879992957,\n 27.900404207046776\n ],\n [\n 40.467446295287004,\n 18.152186962033795\n ],\n [\n 42.75602070222271,\n 16.211495469022466\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Volcano Science Center - Menlo Park
U.S. Geological Survey
345 Middlefield Road, MS 910
Menlo Park, CA 94025
Harrat Rahat is a Cenozoic volcanic field in the west-central part of the Kingdom of Saudi Arabia, 150 kilometers east of the Red Sea, and is the site of the most recent eruption in the country (1256 C.E.; 654 in the year of the Hijra). The city of Al Madīnah lies at the north end of Harrat Rahat, and its volcanic and seismic risks are frequently reassessed. In 2009 C.E. an earthquake swarm at Harrat Lunayyir, 200 km west-northwest of Al Madīnah, produced significant shaking and some building damage in nearby communities, which prompted a revision of seismic hazard models for the region. A network of seismic stations on this volcanically active western side of the Arabia Plate was installed, and stations were also added in the tectonically active northern part of the country. Although regional earthquakes may be used to determine the crustal structure of the western Arabia Plate, such crustal models are hindered by insufficient numbers of earthquakes in the stable plate interior. Tomography studies can be used to infer material properties of the subsurface, such as presence of partial melt, and are beneficial for volcanic hazard assessments. We use ambient seismic noise to compute Rayleigh and Love surface-wave dispersion maps between 5 and 12 second periods for a subset of seismic stations within and near northern Harrat Rahat. The surface-wave maps are inverted to produce shear-wave velocities using a neighborhood algorithm and interpolated into a pseudo three-dimensional model. The distributions of surface-wave and shear-wave velocities are heterogenous, varying from ±3–8 percent. However, low velocities are not restricted to Harrat Rahat. We observed a difference between Rayleigh- and Love-wave velocities that extends north of the site of the 1256 C.E. eruption and coincides with a low gravity anomaly. We obtain a shear-wave velocity increase of 10–15 percent between 15- and 25-kilometers depth, which is consistent with the presence of a transition between the felsic upper crust and the mafic lower crust of the Arabian Shield. The average shear-wave velocities of the upper and lower crust are estimated to be 3.64 and 3.95 kilometers per second using Rayleigh waves and 3.53 and 4.16 kilometers per second using Love waves, which are in good agreement with the results of other geophysical surveys in this area. The modest magnitude of the low-velocity anomalies within the crust and their locations extending well beyond the limits of Harrat Rahat indicate that they are not caused by a crustal magma chamber. If magma chambers exist, they are smaller than can be imaged with our seismological method (resolution corresponds to a 15-kilometer wavelength), deeper than 30 kilometers, or shallower than 5 kilometers with a small velocity contrast. The last possibility is discounted by weak-to-absent surface geothermal activity and by a lack of shallow seismicity that characterizes other areas with known shallow magmas, such as Hawaiʻi. We then expanded our work to the entire Arabian Shield with principally the same methodology to look at large-scale regional patterns. We found modest shear-wave velocity deviations on the order of only ±3 percent, which are within expected ranges for lithological variation.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1862N","collaboration":"Jointly published with the Saudi Geological Survey [as Saudi Geological Survey Special Report SGS–SP–2021–1]","usgsCitation":"Civilini, F., Mooney, W.D., Savage, M.K., and Townend, J., 2023, Ambient seismic noise tomography of the Kingdom of Saudi Arabia, chap. N of Sisson, T.W., Calvert, A.T., and Mooney, W.D., eds., Active volcanism on the Arabian Shield—Geology, volcanology, and geophysics of northern Harrat Rahat and vicinity, Kingdom of Saudi Arabia: U.S. Geological Survey Professional Paper 1862 [also released as Saudi Geological Survey Special Report SGS–SP–2021–1], 57 p., https://doi.org/10.3133/pp1862N.","productDescription":"vii, 57 p.","numberOfPages":"57","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-118735","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":423988,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1862/n/coverthbn.jpg"},{"id":423989,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1862/n/pp1862n.pdf","text":"Report","size":"10.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1862-N"}],"country":"Kingdom of Saudi Arabia","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[42.77933,16.34789],[42.64957,16.77464],[42.34799,17.07581],[42.27089,17.47472],[41.75438,17.83305],[41.22139,18.6716],[40.93934,19.48649],[40.24765,20.17463],[39.80168,20.33886],[39.1394,21.2919],[39.0237,21.98688],[39.06633,22.57966],[38.49277,23.68845],[38.02386,24.07869],[37.48363,24.28549],[37.15482,24.85848],[37.20949,25.08454],[36.93163,25.60296],[36.6396,25.82623],[36.24914,26.57014],[35.64018,27.37652],[35.13019,28.06335],[34.63234,28.05855],[34.78778,28.60743],[34.83222,28.95748],[34.95604,29.35655],[36.06894,29.19749],[36.50121,29.50525],[36.74053,29.86528],[37.50358,30.00378],[37.66812,30.33867],[37.99885,30.5085],[37.00217,31.50841],[39.00489,32.01022],[39.19547,32.16101],[40.39999,31.88999],[41.88998,31.19001],[44.7095,29.17889],[46.56871,29.09903],[47.45982,29.00252],[47.70885,28.52606],[48.41609,28.552],[48.80759,27.68963],[49.29955,27.46122],[49.47091,27.11],[50.15242,26.68966],[50.21294,26.27703],[50.1133,25.94397],[50.23986,25.60805],[50.52739,25.32781],[50.66056,24.9999],[50.81011,24.75474],[51.11242,24.55633],[51.38961,24.62739],[51.57952,24.2455],[51.61771,24.01422],[52.00073,23.00115],[55.0068,22.49695],[55.20834,22.70833],[55.66666,22],[54.99998,19.99999],[52.00001,19],[49.11667,18.61667],[48.18334,18.16667],[47.46669,17.11668],[47,16.95],[46.74999,17.28334],[46.36666,17.23332],[45.4,17.33334],[45.21665,17.43333],[44.06261,17.41036],[43.79152,17.31998],[43.38079,17.57999],[43.1158,17.08844],[43.21838,16.66689],[42.77933,16.34789]]]},\"properties\":{\"name\":\"Saudi Arabia\"}}]}","contact":"Volcano Science Center - Menlo Park
U.S. Geological Survey
345 Middlefield Road, MS 910
Menlo Park, CA 94025
Volcanism within the harrats (Arabic for “volcanic field”) of the Kingdom of Saudi Arabia includes at least one historical eruption occurring close to the holy city of Al Madīnah in 1256 C.E. As part of a volcanic- and seismic-hazard assessment of northern Harrat Rahat, magnetotelluric (MT) data were collected to investigate the structural setting of the area, the presence or absence of melt within the crust, and the mantle-derived magmatic source. Collected MT data were modeled in both two dimensions, where anisotropy can be estimated, and three dimensions. Interpretation of the preferred resistivity model includes a shallow sediment-filled graben beneath northern Harrat Rahat lavas, a melt-free upper crust, and a region of decompression melting in the asthenosphere below 60–70 kilometers depth. Models in two dimensions image the lower crust as anisotropic, demonstrating that a series of elongate conductivity anomalies with a strike of N. 10° E. within the lower crust of the three-dimensional model are artifacts of inverting anisotropic data with an isotropic modeling algorithm. Careful examination of the resistivity models, in combination with regional geological and geophysical data, suggests an anisotropic lower crust that is free of large zones of melt. Azimuthal anisotropy in the lower crust extends well beyond the limits of Harrat Rahat volcanic rocks, with a conductive direction oriented N. 10° E. and an anisotropy factor of 2–5 between the most and least conductive directions. Enhanced conductivity is likely caused by interconnected grain-boundary graphite, where the direction of anisotropy reflects either frozen-in fabric from the Neoproterozoic stabilization of the Arabian Shield or ductile deformation driven by channelized asthenospheric flow coupled with a thin rigid mantle lid. Asthenospheric melt is interpreted to transect the crust largely through diking, with limited melt storage and short residence times within the crustal column.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1862L","collaboration":"Jointly published with the Saudi Geological Survey [as Saudi Geological Survey Special Report SGS–SP–2021–1]","usgsCitation":"Peacock, J.R., Bedrosian, P.A., Al-Dhahry, M.K., Shareef, A., Feucht, D.W., Taylor, C.D., Bloss, B., and Zahran, H.M., 2023, Magnetotelluric investigation of northern Harrat Rahat, Kingdom of Saudi Arabia, chap. L of Sisson, T.W., Calvert, A.T., and Mooney, W.D., eds., Active volcanism on the Arabian Shield—Geology, volcanology, and geophysics of northern Harrat Rahat and vicinity, Kingdom of Saudi Arabia: U.S. Geological Survey Professional Paper 1862 [also released as Saudi Geological Survey Special Report SGS–SP–2021–1], 111 p., https://doi.org/10.3133/pp1862L.","productDescription":"Report: vi, 111 p.; Data Release","numberOfPages":"111","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-105223","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"links":[{"id":424018,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1862/l/covrthbl.jpg"},{"id":424020,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P99H8HJ7","text":"USGS Data Release","description":"Bedrosian, P.A., Peacock, J.R., and Feucht, D.W., 2023, Magnetotelluric data from northern Harrat Rahat, Saudi Arabia, 2016: U.S. Geological Survey data release, https://doi.org/10.5066/P99H8HJ7.","linkHelpText":"Magnetotelluric data from northern Harrat Rahat, Saudi Arabia, 2016"},{"id":424019,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1862/l/pp1862l.pdf","text":"Report","size":"38 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"Kingdom of Saudi Arabia","otherGeospatial":"northern Harrat Rahat","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 39,\n 25\n ],\n [\n 39,\n 23.75\n ],\n [\n 40.5,\n 23.75\n ],\n [\n 40.5,\n 25\n ],\n [\n 39,\n 25\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Volcano Science Center - Menlo Park
U.S. Geological Survey
345 Middlefield Road, MS 910
Menlo Park, CA 94025
Quaternary volcanic rocks of northern Harrat Rahat, Kingdom of Saudi Arabia, are chiefly alkali basalts with subordinate transitional basalts, hawaiites, mugearites, benmoreites, and trachytes. Geochemical and isotopic results indicate that crystallization-differentiation, mixing, and cumulate reassimilation within the magmatic system produced most of its compositional diversity, with only minor involvement of Neoproterozoic crust. With increasing evolution, crystal assemblages that separated from and drove basalt-to-hawaiite differentiation passed from (1) dunitic or troctolitic to (2) olivine gabbroic to (3) titanomagnetite-bearing olivine gabbroic, with typical hawaiites representing about 20 weight percent residual liquids from an estimated primary alkali basaltic parent. Crystallization-differentiation simulations for midcrustal pressures yield the closest compositional match to the basalt-hawaiite suite, and stagnation in the midcrustal area (near 20 kilometers [km] depth) may result from density trapping beneath the lower density upper continental crust. Least differentiated alkali basalts have fractionation-adjusted major-oxide compositions that are consistent with separation from the deeper parts (60–70 km) of the spinel-lherzolite stability field at pressures that are close to the local lithosphere-asthenosphere boundary (60–80 km). Mantle potential temperature estimates are strongly sensitive to modeling approach, but potential temperatures (1,345–1,390 degrees Celsius [°C]) are not discernably greater than for midocean ridge basalts (MORB; 1,350–1,410 °C) if adherence to spinel-lherzolite melting relations is required. Inversion of the trace-element concentrations of the lesser fractionated basalts indicates a depleted mantle source, similar to MORB-source estimates, but one that is enriched in Sr and includes a greater relative proportion of melting in the garnet-peridotite stability field. These geochemical and thermal relations, as well as radiogenic isotopes, point to a dominantly depleted mantle asthenospheric source for Harrat Rahat basalts, admixed with subordinate materials either from the Afar mantle plume or an enriched MORB component in the ambient asthenosphere. The lithosphere-asthenosphere boundary is shallower beneath the belt of major volcanic fields on the Arabia Plate, and restoration of rifting across the Red Sea and Gulf of Aden places the south end of this belt adjacent to the northern part of the Afar region, suggesting a once-continuous structure, possibly an arch, a weakness, or a discontinuity along the base of the lithosphere. Magma generation can be ascribed to focused upwelling and decompression melting, perhaps driven by a magmatic-feedback mechanism whereby basaltic intrusions into the deep lithosphere solidify as eclogites, causing lithospheric foundering and further asthenospheric upwelling and decompression melting in a restricted region.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1862I","collaboration":"Jointly published with the Saudi Geological Survey [as Saudi Geological Survey Special Report SGS–SP–2021–1]","usgsCitation":"Sisson, T.W., Downs, D.T., Calvert, A.T., Dietterich, H.R., Mahood, G.A., Salters, V.J.M., Stelten, M.E., and Shawali, J., 2023, Mantle origin and crustal differentiation of basalts and hawaiites of northern Harrat Rahat, Kingdom of Saudi Arabia, chap. I of Sisson, T.W., Calvert, A.T., and Mooney, W.D., eds., Active volcanism on the Arabian Shield—Geology, volcanology, and geophysics of northern Harrat Rahat and vicinity, Kingdom of Saudi Arabia: U.S. Geological Survey Professional Paper 1862 [also released as Saudi Geological Survey Special Report SGS–SP–2021–1], 42 p., https://doi.org/10.3133/pp1862I.","productDescription":"vii, 42 p.","numberOfPages":"42","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-118554","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":424010,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1862/i/covrthbi.jpg"},{"id":424011,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1862/i/pp1862i.pdf","text":"Report","size":"8 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"Kingdom of Saudi Arabia","otherGeospatial":"northern Harrat Rahat","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 39.4,\n 24.6\n ],\n [\n 39.4,\n 23.75\n ],\n [\n 40.25,\n 23.75\n ],\n [\n 40.25,\n 24.6\n ],\n [\n 39.4,\n 24.6\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Volcano Science Center - Menlo Park
U.S. Geological Survey
345 Middlefield Road, MS 910
Menlo Park, CA 94025
Mafic volcanic fields are widespread, but few have erupted in historical times, providing limited observations of the magnitudes, dynamics, and timescales of lava flow emplacement in these settings. The Harrat Rahat volcanic field in western Saudi Arabia offers a good opportunity to study eruptions in such a setting, with a historical eruption in 1256 C.E. (654 in the year of the Hijra) and numerous well-preserved late Pleistocene lava flows. We combine historical observations and rheological and morphological analyses of the youngest flows with analytical models to reconstruct eruptive histories and lava flow emplacement conditions in Harrat Rahat. Petrologic analysis of samples for emplacement temperatures and crystallinities show cooling trends from vent to toe of ~1,140 to ~1,090 degrees Celsius (°C) at rates of 2 to 7 °C per kilometer, crystallinities increasing from 0.5 to 60 volume percent, and apparent viscosities increasing from 102 to 109 pascal seconds. High-resolution topographic data facilitate quantitative analysis of morphology and interpolation of preeruptive surfaces to measure flow thicknesses, channels, and levees, and enable calculation of eruptive volumes. Analytical models relating flow morphology to emplacement conditions are applied to estimate effusion rates. Within the suite of studied flows, minimum volume estimates range from 0.07 to 0.42 cubic kilometers dense rock equivalent, with effusion rates on the order of tens to hundreds of cubic meters per second and durations from 1 to 15 weeks. These integrated analyses quantify past lava flow emplacement conditions and dynamics in Harrat Rahat, improving our understanding and observations of fundamental parameters and controls of effusive eruptions in Harrat Rahat and other mafic volcanic fields.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1862E","collaboration":"Jointly published with the Saudi Geological Survey [as Saudi Geological Survey Special Report SGS–SP–2021–1]","usgsCitation":"Dietterich, H.R., Downs, D.T., and Stelten, M.E., 2023, Lava flow emplacement in Harrat Rahat with implications for eruptions in mafic volcanic fields, chap. E of Sisson, T.W., Calvert, A.T., and Mooney, W.D., eds., Active volcanism on the Arabian Shield—Geology, volcanology, and geophysics of northern Harrat Rahat and vicinity, Kingdom of Saudi Arabia: U.S. Geological Survey Professional Paper 1862 [also released as Saudi Geological Survey Special Report SGS–SP–2021–1], 49 p., https://doi.org/10.3133/pp1862E.","productDescription":"vi, 49 p.","numberOfPages":"49","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-111360","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":423979,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1862/e/coverthbe.jpg"},{"id":423980,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1862/e/pp1862e.pdf","text":"Report","size":"6.56 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1862-E"}],"country":"Kingdom of Saudi Arabia","otherGeospatial":"northeastern Harrat Rahat","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 39.675,\n 24.6\n ],\n [\n 39.675,\n 24.2\n ],\n [\n 40,\n 24.2\n ],\n [\n 40,\n 24.6\n ],\n [\n 39.675,\n 24.6\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Volcano Science Center - Menlo Park
U.S. Geological Survey
345 Middlefield Road, MS 910
Menlo Park, CA 94025
Harrat Rahat, one of several large, basalt-dominated volcanic fields in the western part of the Kingdom of Saudi Arabia, is a prime example of continental, intraplate volcanism. Excellent exposure makes this an outstanding site to investigate changing volcanic flux and composition through time. We present 93 40Ar/39Ar ages and 6 36Cl surface-exposure ages for volcanic deposits throughout northern Harrat Rahat that, integrated with a new geologic map, define 12 eruptive stages. Exposed volcanic deposits in the study area erupted less than 1.2 million years ago (Ma), and 214 of 234 identified eruptions occurred less than 570 thousand years ago (ka). Two eruptions were in the Holocene, including a historically described basaltic eruption in 1256 C.E. and a trachyte eruption newly recognized as Holocene (4.2±5.2 ka). An estimated approximately 82 cubic kilometers (km3; dense rock equivalent) of volcanic products can be documented as having erupted since 1.2 Ma, though this is a lower limit because of concealment of deposits older than 570 ka. Over the last 570 thousand years (k.y.), the average eruption rate was 0.14 cubic kilometers per thousand years (km3/k.y.), but volcanism was episodic with periods alternating between low (0.04–0.06 km3/k.y.) and high (0.1–0.3 km3/k.y.) effusion rates. Before 180 ka, eruptions vented from the volcanic field’s dominant eastern vent axis and from a subsidiary, diffuse, western vent axis. After 180 ka, volcanism focused along the eastern vent axis, and the composition of volcanism varied systematically along its length from basalt dominated in the north to trachyte dominated in the south. We hypothesize that these compositional variations younger than 180 k.y. reflect the growth of a mafic intrusive complex beneath the southern part of the vent axis, which led to the development of evolved magmas. Lastly, these new age data allow for a reassessment of the volcanic recurrence interval at northern Harrat Rahat. Based on available data, volcanism in northern Harrat Rahat over the last 180 k.y. is poorly described using a Poisson distribution with a single recurrence interval. Instead, data for northern Harrat Rahat are better described using a mixed exponential distribution that is applicable for volcanic systems characterized by two different eruptive states, where one state with a longer recurrence interval corresponding to periods of low eruption frequency and one state with a shorter recurrence interval corresponding to periods of high eruption frequency. The preferred model for northern Harrat Rahat over the last 180 k.y. uses a long recurrence interval of 4.0 k.y. and a short recurrence interval of 0.22 k.y.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1862D","collaboration":"Jointly published with the Saudi Geological Survey [as Saudi Geological Survey Special Report SGS–SP–2021–1]","usgsCitation":"Stelten, M.E., Downs, D.T., Champion, D.E., Dietterich, H.R., Calvert, A.T., Sisson, T.W., Mahood, G.A., and Zahran, H.M., 2023, Eruptive history of northern Harrat Rahat—Volume, timing, and composition of volcanism over the past 1.2 million years, chap. D of Sisson, T.W., Calvert, A.T., and Mooney, W.D., eds., Active volcanism on the Arabian Shield—Geology, volcanology, and geophysics of northern Harrat Rahat and vicinity, Kingdom of Saudi Arabia: U.S. Geological Survey Professional Paper 1862 [also released as Saudi Geological Survey Special Report SGS–SP–2021–1], 46 p., https://doi.org/10.3133/pp1862D.","productDescription":"Report: vii, 46 p.; Data Release","numberOfPages":"46","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-112590","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":423978,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P92FB6AQ","text":"USGS data release","linkHelpText":"Ar isotope data for volcanic rocks from the northern Harrat Rahat volcanic field and surrounding area, Kingdom of Saudi Arabia"},{"id":423977,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1862/d/pp1862d.pdf","text":"Report","size":"12.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"pp 1862-D"},{"id":423976,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1862/d/coverthbd.jpg"}],"country":"Kingdom of Saudi Arabia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 38.462137339848226,\n 25.895423004545833\n ],\n [\n 38.462137339848226,\n 22.346642935140807\n ],\n [\n 42.32932483984882,\n 22.346642935140807\n ],\n [\n 42.32932483984882,\n 25.895423004545833\n ],\n [\n 38.462137339848226,\n 25.895423004545833\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Volcano Science Center - Menlo Park
U.S. Geological Survey
345 Middlefield Road, MS 910
Menlo Park, CA 94025
The Humboldt River Basin is the only river basin that is contained entirely within the State of Nevada. The effect of groundwater pumping on the Humboldt River is not well understood. Tools are needed to determine stream capture and manage groundwater pumping in the Humboldt River Basin. The objective of this study is to estimate capture and storage change caused by groundwater withdrawals in the lower Humboldt River Basin that can provide the Nevada State Engineer with data and information needed to manage groundwater and surface-water resources.
A numerical groundwater flow model was developed for the purpose of estimating stream capture from pre-2016 and future pumping as well as for any location of potential future pumping within the lower Humboldt River Basin. This model was developed using MODFLOW-NWT to represent the lower Humboldt River Basin hydrologic system, including Humboldt River; Rye Patch Reservoir; groundwater evapotranspiration; pumping from municipal, agricultural, mining, and domestic wells; and agricultural drains. Aquifer properties were calibrated using results from numerous single- and multi-well aquifer tests (Nadler, 2020) and through the process of model calibration.
Historical capture was estimated for 1960–2016 and predictive capture for the system was projected 100 years into the future (2017–2116) based on historical pumping patterns. Stream capture and drain capture are relatively low for the historical and predictive periods. During the historical period, increased pumping during dry years caused increased connections with capture sources and less water sourced to wells from aquifer storage. Storage and groundwater levels generally recovered during subsequent wet years. Overall, storage change has been the main source of water to wells in the lower Humboldt River Basin, followed by groundwater evapotranspiration capture. During the predictive period, pumping is projected to remain constant and capture 9 percent of stream water after 100 years.
Capture and storage change maps were created to visualize spatial variability in potential capture and storage change through time and to provide a database of results that can be used to manage groundwater and surface-water resources. These maps show that potential stream capture would be a minor source of water to wells located across most of the simulated area, except for locations close to the Humboldt River and Rye Patch Reservoir. Drains also would be a minor potential source of water to wells except for those directly adjacent to the drains. In general, the potential supply of water to wells is storage-dominated and over time groundwater evapotranspiration-dominated in the agricultural area.
Capture difference maps were generated to visualize where potential capture results might have greater limitations associated with nonlinear flow processes, such as head-dependent boundary conditions. Higher capture differences indicate larger capture map bias and therefore greater capture map uncertainty due to the inability of capture maps to account for nonlinear flow processes. Stream capture differences are highest directly adjacent to the river but are otherwise minimal. Drain capture differences are highest in the region of the agricultural drain network but are otherwise minimal. The Humboldt River, Rye Patch Reservoir, and drains introduce very little nonlinearity to the model, and their associated capture map bias is minimal. Potential groundwater evapotranspiration capture introduces a fair amount of nonlinearity to the model and has the potential to result in significant, localized groundwater evapotranspiration capture map bias over time. Groundwater evapotranspiration capture differences are the result of higher pumping rates lowering the water table below the root zone faster than lower pumping rates and essentially removing groundwater evapotranspiration as a potential source of capture faster than lower pumping rates. Wells that can no longer source their supply through groundwater evapotranspiration capture then generally source more of their water from storage. Thus, storage change bias increases over time as well.
Capture prediction uncertainty due to parameter estimation was evaluated using a covariance matrix adaptation-evolution strategy. One hundred Monte Carlo realizations of model parameters were applied to the model to assess capture uncertainty at 13 grid cell locations within the model domain. In general, results indicated that greater capture uncertainty for a given source (river, drains, or evapotranspiration) is associated with proximity of a pumping well to that source. The magnitude of maximum capture fraction uncertainties after 100 years of pumping for stream capture, drain capture, groundwater evapotranspiration capture, and storage change were plus or minus (±) 0.17, ±0.10, ±0.20, and ±0.22, respectively.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235110","collaboration":"Prepared in cooperation with the Nevada Division of Water Resources","usgsCitation":"Nadler, C.A., Rybarski, S.C., and Pham, H., 2023, Evaluation of stream capture related to groundwater pumping, Lower Humboldt River Basin, Nevada: U.S. Geological Survey Scientific Investigations Report 2023–5110, 77 p., https://doi.org/10.3133/sir20235110.","productDescription":"Report: x, 77 p.; Data Release","numberOfPages":"77","onlineOnly":"Y","ipdsId":"IP-093899","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":499384,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115938.htm","linkFileType":{"id":5,"text":"html"}},{"id":423640,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P99DN2R1","text":"USGS Data Release","description":"Nadler, C.A., Rybarski, S.C., and Pham, H., 2023, MODFLOW-NWT model and supplementary data used to characterize effects of pumping in Lovelock Valley, Nevada: U.S. Geological Survey data release, https://doi.org/10.5066/P99DN2R1.","linkHelpText":"MODFLOW-NWT Model and Supplementary Data Used to Characterize Effects of Pumping in Lovelock Valley, Nevada"},{"id":423639,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235110/full"},{"id":423635,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5110/covrthb.jpg"},{"id":423637,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5110/sir20235110.xml","linkFileType":{"id":8,"text":"xml"}},{"id":423636,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5110/sir20235110.pdf","text":"Report","size":"26 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":423638,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5110/images"}],"country":"United States","state":"Nevada","otherGeospatial":"Lower Humboldt River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -119.0,\n 40.5\n ],\n [\n -119.0,\n 39.5\n ],\n [\n -118.0,\n 39.5\n ],\n [\n -118.0,\n 40.5\n ],\n [\n -119.0,\n 40.5\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director,
Nevada Water Science Center
U.S. Geological Survey
2730 N. Deer Run Road
Carson City, Nevada 89701
Reintroduction of species at sites where populations have been extirpated has become a common technique in wildlife conservation. To track progress towards reintroduction success, effective postrelease monitoring is needed to document vital rates of individuals and the corresponding impact on population trajectories. We assessed growth and body size in Eastern Indigo Snakes (Drymarchon couperi) using a data set from multiple projects across the species' distribution, including free-ranging wild snakes, snakes reared in captive-breeding programs, and snakes released at two reintroduction sites. We used these data to fit a von Bertalanffy growth model in a Bayesian framework to quantify differences in growth among three broad categories of snakes (wild, captive, and reintroduced), while accounting for measurement error across various projects. We also compared changes in body mass of captive-born individuals from four captive rearing facilities. Asymptotic snout–vent length across all groups was 185 cm (95% credible interval = 177–194 cm) for males and 157 cm (95% credible interval = 153–161 cm) for females. Reintroduced snakes had a higher growth coefficient than either captive or wild snakes (e.g., captive females = 1.20 [1.06–1.35] d–1; wild females = 1.22 [0.95–1.49] d–1; reintroduced females = 1.62 [1.21–2.05] d–1), indicating that current captive-breeding and rearing efforts for indigo snakes produce similar or faster growth trends compared to wild populations. Furthermore, daily changes in juvenile body weight relative to body size were similar in three of the four captive rearing facilities (mean for females at Orianne Center for Indigo Conservation = 0.57 [0.48–0.65]; Zoo Atlanta = 0.55 [0.37–0.72]; Welaka National Fish Hatchery = 0.55, [0.36–0.73]; Auburn University = 0.39 [0.21–0.58]). Long-term project success for indigo snake reintroductions will depend on continuing to implement best practices in an adaptive management framework.
","language":"English","publisher":"BioOne","doi":"10.1655/Herpetologica-D-22-00041","usgsCitation":"Chandler, H.C., Steen, D., Blue, J., Bogan, J.E., Bolt, M.R., Brady, T., Breininger, D.R., Buening, J., Elliott, M., Godwin, J., Guyer, C., Hill, R.L., Hoffman, M., Hyslop, N.L., Jenkins, C., Lechowicz, C., Moore, M., Moulis, R.A., Piccolomini, S., Redmond, R., Snow, F.H., Stegenga, B.S., Stevenson, D., Stiles, J., Stiles, S., Wallace, M., Waters, J., Wines, M., and Bauder, J.M., 2023, Evaluating growth rates of captive, wild, and reintroduced populations of the imperiled Eastern Indigo Snake (Drymarchon couperi): Herpetologica, v. 79, no. 4, p. 220-230, https://doi.org/10.1655/Herpetologica-D-22-00041.","productDescription":"11 p.","startPage":"220","endPage":"230","ipdsId":"IP-146664","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":433101,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"79","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Chandler, Houston C.","contributorId":342515,"corporation":false,"usgs":false,"family":"Chandler","given":"Houston","email":"","middleInitial":"C.","affiliations":[{"id":13223,"text":"The Orianne Society","active":true,"usgs":false}],"preferred":false,"id":910155,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Steen, David","contributorId":342517,"corporation":false,"usgs":false,"family":"Steen","given":"David","affiliations":[{"id":12556,"text":"Florida Fish and Wildlife Conservation Commission","active":true,"usgs":false}],"preferred":false,"id":910156,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Blue, Jack","contributorId":342519,"corporation":false,"usgs":false,"family":"Blue","given":"Jack","email":"","affiliations":[{"id":13223,"text":"The Orianne Society","active":true,"usgs":false}],"preferred":false,"id":910157,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bogan, James E.","contributorId":342521,"corporation":false,"usgs":false,"family":"Bogan","given":"James","email":"","middleInitial":"E.","affiliations":[{"id":81884,"text":"Central Florida Zoo’s Orianne Center for Indigo Conservation","active":true,"usgs":false}],"preferred":false,"id":910158,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bolt, M. Rebecca","contributorId":342522,"corporation":false,"usgs":false,"family":"Bolt","given":"M.","email":"","middleInitial":"Rebecca","affiliations":[{"id":81886,"text":"Bolt Outdoors","active":true,"usgs":false}],"preferred":false,"id":910159,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brady, Tony","contributorId":342523,"corporation":false,"usgs":false,"family":"Brady","given":"Tony","email":"","affiliations":[{"id":81887,"text":"Welaka National Fish Hatchery","active":true,"usgs":false}],"preferred":false,"id":910160,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Breininger, David R.","contributorId":342524,"corporation":false,"usgs":false,"family":"Breininger","given":"David","email":"","middleInitial":"R.","affiliations":[{"id":18879,"text":"University of Central Florida","active":true,"usgs":false}],"preferred":false,"id":910161,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Buening, Jorge","contributorId":342525,"corporation":false,"usgs":false,"family":"Buening","given":"Jorge","email":"","affiliations":[{"id":81887,"text":"Welaka National Fish Hatchery","active":true,"usgs":false}],"preferred":false,"id":910162,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Elliott, Matt","contributorId":342527,"corporation":false,"usgs":false,"family":"Elliott","given":"Matt","email":"","affiliations":[{"id":36378,"text":"Georgia Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":910163,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Godwin, James","contributorId":342530,"corporation":false,"usgs":false,"family":"Godwin","given":"James","affiliations":[{"id":81888,"text":"Alabama Natural Heritage Program","active":true,"usgs":false}],"preferred":false,"id":910164,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Guyer, Craig","contributorId":342531,"corporation":false,"usgs":false,"family":"Guyer","given":"Craig","affiliations":[{"id":13360,"text":"Auburn University","active":true,"usgs":false}],"preferred":false,"id":910165,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Hill, Robert L.","contributorId":342532,"corporation":false,"usgs":false,"family":"Hill","given":"Robert","email":"","middleInitial":"L.","affiliations":[{"id":81890,"text":"Zoo Atlanta","active":true,"usgs":false}],"preferred":false,"id":910166,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Hoffman, Michelle","contributorId":342533,"corporation":false,"usgs":false,"family":"Hoffman","given":"Michelle","email":"","affiliations":[{"id":81884,"text":"Central Florida Zoo’s Orianne Center for Indigo Conservation","active":true,"usgs":false}],"preferred":false,"id":910167,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Hyslop, Natalie L.","contributorId":342534,"corporation":false,"usgs":false,"family":"Hyslop","given":"Natalie","email":"","middleInitial":"L.","affiliations":[{"id":7066,"text":"University of North Georgia","active":true,"usgs":false}],"preferred":false,"id":910168,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Jenkins, Christopher L.","contributorId":342535,"corporation":false,"usgs":false,"family":"Jenkins","given":"Christopher L.","affiliations":[{"id":13223,"text":"The Orianne Society","active":true,"usgs":false}],"preferred":false,"id":910169,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Lechowicz, Chris","contributorId":342536,"corporation":false,"usgs":false,"family":"Lechowicz","given":"Chris","affiliations":[{"id":81891,"text":"Sanibel-Captiva Conservation Foundation","active":true,"usgs":false}],"preferred":false,"id":910170,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Moore, Matt","contributorId":342537,"corporation":false,"usgs":false,"family":"Moore","given":"Matt","email":"","affiliations":[{"id":36378,"text":"Georgia Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":910171,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Moulis, Robert A.","contributorId":342538,"corporation":false,"usgs":false,"family":"Moulis","given":"Robert","email":"","middleInitial":"A.","affiliations":[{"id":13223,"text":"The Orianne Society","active":true,"usgs":false}],"preferred":false,"id":910172,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Piccolomini, Sara","contributorId":342539,"corporation":false,"usgs":false,"family":"Piccolomini","given":"Sara","affiliations":[{"id":13360,"text":"Auburn University","active":true,"usgs":false}],"preferred":false,"id":910173,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Redmond, Robert","contributorId":342540,"corporation":false,"usgs":false,"family":"Redmond","given":"Robert","email":"","affiliations":[{"id":13223,"text":"The Orianne Society","active":true,"usgs":false}],"preferred":false,"id":910174,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Snow, Frankie H.","contributorId":342541,"corporation":false,"usgs":false,"family":"Snow","given":"Frankie","email":"","middleInitial":"H.","affiliations":[{"id":81892,"text":"South Georgia State College","active":true,"usgs":false}],"preferred":false,"id":910175,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Stegenga, Benjamin S.","contributorId":342542,"corporation":false,"usgs":false,"family":"Stegenga","given":"Benjamin","email":"","middleInitial":"S.","affiliations":[{"id":13223,"text":"The Orianne Society","active":true,"usgs":false}],"preferred":false,"id":910176,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Stevenson, Dirk J.","contributorId":342543,"corporation":false,"usgs":false,"family":"Stevenson","given":"Dirk J.","affiliations":[{"id":13223,"text":"The Orianne Society","active":true,"usgs":false}],"preferred":false,"id":910177,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Stiles, James","contributorId":342544,"corporation":false,"usgs":false,"family":"Stiles","given":"James","email":"","affiliations":[{"id":81888,"text":"Alabama Natural Heritage Program","active":true,"usgs":false}],"preferred":false,"id":910178,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Stiles, Sierra","contributorId":342545,"corporation":false,"usgs":false,"family":"Stiles","given":"Sierra","email":"","affiliations":[{"id":13360,"text":"Auburn University","active":true,"usgs":false}],"preferred":false,"id":910179,"contributorType":{"id":1,"text":"Authors"},"rank":25},{"text":"Wallace, Mark","contributorId":342546,"corporation":false,"usgs":false,"family":"Wallace","given":"Mark","affiliations":[{"id":13223,"text":"The Orianne Society","active":true,"usgs":false}],"preferred":false,"id":910180,"contributorType":{"id":1,"text":"Authors"},"rank":26},{"text":"Waters, Jimmy","contributorId":342547,"corporation":false,"usgs":false,"family":"Waters","given":"Jimmy","email":"","affiliations":[{"id":13223,"text":"The Orianne Society","active":true,"usgs":false}],"preferred":false,"id":910181,"contributorType":{"id":1,"text":"Authors"},"rank":27},{"text":"Wines, Michael","contributorId":342548,"corporation":false,"usgs":false,"family":"Wines","given":"Michael","email":"","affiliations":[{"id":81888,"text":"Alabama Natural Heritage Program","active":true,"usgs":false}],"preferred":false,"id":910182,"contributorType":{"id":1,"text":"Authors"},"rank":28},{"text":"Bauder, Javan Mathias 0000-0002-2055-5324","orcid":"https://orcid.org/0000-0002-2055-5324","contributorId":337814,"corporation":false,"usgs":true,"family":"Bauder","given":"Javan","email":"","middleInitial":"Mathias","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":910183,"contributorType":{"id":1,"text":"Authors"},"rank":29}]}} ,{"id":70251162,"text":"70251162 - 2023 - Atmospheric correction intercomparison of hyperspectral and multispectral imagery over agricultural study sites","interactions":[],"lastModifiedDate":"2024-01-25T13:15:36.730049","indexId":"70251162","displayToPublicDate":"2023-12-29T07:14:19","publicationYear":"2023","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Atmospheric correction intercomparison of hyperspectral and multispectral imagery over agricultural study sites","docAbstract":"In this research effort we assess the performance of atmospheric correction-based surface reflectance (SR) retrievals from two satellite image sources, one with very high spatial resolution (VHR) (<5-m) and the other high spectral resolution (~10-nm). The VHR images are from MAXARs WorldView-3 (WV3) satellite and the high spectral resolution images are from Agenzia Spaziale Italianas (ASI) PRecursore IperSpettrale della Missione Applicativa (PRISMA) satellite. We use various atmospheric correction (AC) tools to provide intercomparisons of both AC tools and image source SR estimates. The AC tools we evaluated include Fast Line-of-sight Atmospheric Analysis of Hypercubes (FLAASH) within ENVI version 4.7, MODerate resolution atmospheric TRANsmission (MODTRAN) versions 5.3.3 and 6.0, and ASIs Level-2D correction for PRISMA imagery. Prior to correcting WV3 and PRISMA imagery to SR, we performed manual geometric corrections of imagery as both image sources were found to lack consistent georegistration.\n\nWe performed comparisons at two study sites in Maryland, USA, including the United States Department of Agriculture Beltsville Agricultural Research Center (BARC) and an agricultural study site on Marylands Eastern Shore region. For the BARC site, we used WV3 imagery acquired on 2022-04-02 and PRISMA imagery acquired on 2022-04-28, focusing on evaluation of AC tool SR retrieval performance for each image source separately due to large time differences in image acquisitions where SR values are likely impacted by changing field conditions. For the Eastern Shore site, WV3 imagery was acquired on 2022-05-18 and 2022-05-30, and PRISMA imagery was acquired on 2022-05-21, allowing for quantitative evaluation of both AC tool performance and intercomparison between WV3 and PRISMA imagery. Having WV3 imagery acquired before and after PRISMA imagery allows for interpretation of major changes in field conditions and thus, identification of fields to exclude from intercomparisons. For intercomparison assessments, we computed relative percent difference (RPD) between the AC tool SR retrievals. For image source comparisons, 4-m WV3 pixels were resampled to 30-m PRISMA pixels after which 30-m WV3 bands and PRISMA spectra were compared to one another visually for both study sites. To provide rigorous SR retrieval intercomparisons between image sources, PRISMA spectra were resampled to WV3-equivalent bands for RPD computation for the Eastern Shore site.\n\nIn addition to the SR retrieval intercomparisons between the AC tools, we carry out a quasi-validation where we retrieve fractional crop residue cover (fR) from the satellite image sources by calculating established spectral indices (SIs) and calibrating SIs with ground-measured fR acquired within several days of satellite overpasses. These SIs include the Cellulose Absorption Index (CAI) (Nagler et al. 2000), Shortwave Infrared Normalized Difference Residue Index (SINDRI) (Serbin et al. 2009), Lignin-Cellulose Absorption Index (LCAI) (Daughtry et al. 2005), and Lignin-Cellulose Peak Center Difference Index (LCPCDI) (Hively et al. 2021) 1-4. The most accurate crop residue SIs are generally based on shortwave infrared (SWIR) reflectance bands ranging from 2000 nm to 2400 nm that measure dry vegetation lignocellulose absorption features at 2100 and 2300 nm 1-5. For instance, the CAI identifies a 2100 nm cellulose absorption feature with a central band positioned on this feature, and two spectrally adjacent bands at 2040 and 2210 nm, while the LCAI identifies the 2300 nm lignin absorption feature compared to bands at 2165 and 2210 nm. Particular focus on intercomparisons for the SWIR region is critical as atmospheric water, carbon dioxide, and methane impact accurate SR retrieval as shown in Figure 1.a. Our final analysis concludes with the selection of the top-performing AC approach between the WV3 and PRISMA imagery (as indicated by low SR RPD) and then compares PRIMSA and 30-m WV3 imagery with original 4-m WV3 imagery to assess the degree to which spatial resolution impacts the retrieval of fR. Figure 1 provides a comparative example of WV3 and PRISMA imagery used to compute SINDRI which is then calibrated to fR using second order polynomial equations from Hively et al. (2018) 6. Figure 1 fR calibrations will be updated with newly acquired ground survey data from May 2022 to further improve the accuracy of image source and AC tool intercomparisons.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"International Symposium on Geoscience and Remote Sensing (IGARSS): Conference Proceedings","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium","language":"English","publisher":"Institute of Electrical and Electronics Engineers (IEEE)","publisherLocation":"Pasadena, CA","doi":"10.1109/IGARSS52108.2023.10281710","usgsCitation":"Lamb, B.T., Hively, W.D., Jennewein, J., Thieme, A., and Soroka, A.M., 2023, Atmospheric correction intercomparison of hyperspectral and multispectral imagery over agricultural study sites, in International Symposium on Geoscience and Remote Sensing (IGARSS): Conference Proceedings, https://doi.org/10.1109/IGARSS52108.2023.10281710.","ipdsId":"IP-152772","costCenters":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":424952,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lamb, Brian T. 0000-0001-7957-5488","orcid":"https://orcid.org/0000-0001-7957-5488","contributorId":291893,"corporation":false,"usgs":true,"family":"Lamb","given":"Brian","middleInitial":"T.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":893309,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hively, W. Dean 0000-0002-5383-8064","orcid":"https://orcid.org/0000-0002-5383-8064","contributorId":201565,"corporation":false,"usgs":true,"family":"Hively","given":"W.","email":"","middleInitial":"Dean","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":893310,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jennewein, Jyoti","contributorId":243442,"corporation":false,"usgs":false,"family":"Jennewein","given":"Jyoti","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":893311,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thieme, Alison","contributorId":237963,"corporation":false,"usgs":false,"family":"Thieme","given":"Alison","email":"","affiliations":[{"id":47661,"text":"University of Maryland, Geographical Sciences","active":true,"usgs":false}],"preferred":false,"id":893312,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Soroka, Alexander M. 0000-0002-8002-5229","orcid":"https://orcid.org/0000-0002-8002-5229","contributorId":201664,"corporation":false,"usgs":true,"family":"Soroka","given":"Alexander","email":"","middleInitial":"M.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":893313,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70253136,"text":"70253136 - 2023 - Connecting flood-related fluvial erosion and deposition with vulnerable downstream road-stream crossings","interactions":[],"lastModifiedDate":"2024-04-23T12:17:39.530186","indexId":"70253136","displayToPublicDate":"2023-12-29T07:14:13","publicationYear":"2023","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Connecting flood-related fluvial erosion and deposition with vulnerable downstream road-stream crossings","docAbstract":"Fluvial erosion is increasingly responsible for infrastructure and building damages associated\nwith floods as the intensity of extreme rainfalls hit rural and urban rivers in a variety of climate\nsettings across the United States. Extreme floods in 2016 and 2018 caused widespread culvert\nblockages and road failures, including extensive damage along steep tributaries and ravines in\nthe Marengo River, Wisconsin, watershed during 2016 and 2018. A study conducted by the U.S.\nGeological Survey (USGS), Wisconsin Wetlands Association (WWA), Ashland County, and the\nNorthwest Wisconsin Regional Planning Commission (NWRPC) investigated the special\nconcern of fluvial erosion hazards (FEHs) associated with gullying, streamside landslides, and\nthe loss of wetland storage in headwaters. In 2019, a pilot study was begun to map and classify\nephemeral and perennial streams and wetlands in terms of their sensitivity to FEHs. This study\ncombined data from field-based rapid geomorphic assessments (RGAs) coupled with a stream\nnetwork-wide geographic information system (GIS) approach for mapping stream segments,\nreferred to as fluvial process zones (FPZ), sensitive to erosion, deposition, and channel change.\nThe GIS approach used nationally available 10-meter (m) resolution topology and an extended\nstream network to map FPZs based on Strahler stream order, stream power, channel slope,\npresence of adjacent steep valley sides and headwater flats, and adjacent landform setting.\nBankfull channel widths derived from RGA-based hydraulic geometry curves combined with\ndrainage areas, an estimate of bankfull flow, and channel slope were used to calculate specific\nstream power for the FPZs. Lastly, the FPZs were characterized by their location within three\nmajor landform settings that affect erosion potential. The resulting vulnerability maps provided\na screening framework to identify FPZs that are sensitive to incision, gullying and mass wasting\nalong steep headwater ephemeral channels, as well as downstream perennial channels that have\nthe potential for valley-side landslides, coarse sediment deposition, and channel change. Lastly,\neach FPZ was characterized in terms of hydrologic alteration associated with ditching. The\nvulnerability mapping products and rankings of sensitivity of FPZs will ultimately be used by\nAshland County and their collaborators to prioritize natural flood management projects that\nmitigate FEHs, restore hydrology, and reconnect channels with adjacent wetlands and\nfloodplains.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Federal Interagency Sedimentation and Hydrologic Modeling Conference (SedHyd) 2023 Conference Proceedings","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"Federal Interagency Sedimentation and Hydrologic Modeling Conference","conferenceDate":"May 8-12, 2023","conferenceLocation":"St. Louis, MO","language":"English","publisher":"SEDHYD Conference Proceedings","usgsCitation":"Fitzpatrick, F., Magyera, K.H., Laumann, J., Larson, C., Rockwood, S., Dantoin, E.D., Hollenhorst, T., Krumwiede, B., Nelson, B.R., Prokopec, J., and Johnson, K.E., 2023, Connecting flood-related fluvial erosion and deposition with vulnerable downstream road-stream crossings, in Federal Interagency Sedimentation and Hydrologic Modeling Conference (SedHyd) 2023 Conference Proceedings, St. Louis, MO, May 8-12, 2023, 15 p.","productDescription":"15 p.","ipdsId":"IP-152230","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":428025,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.sedhyd.org/2023Program/1/206.pdf"},{"id":428053,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Marengo River watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -91.38270139201421,\n 46.7339329743686\n ],\n [\n -91.38270139201421,\n 46.04415426363366\n ],\n [\n -90.60807272808239,\n 46.04415426363366\n ],\n [\n -90.60807272808239,\n 46.7339329743686\n ],\n [\n -91.38270139201421,\n 46.7339329743686\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Fitzpatrick, Faith A. 0000-0002-9748-7075","orcid":"https://orcid.org/0000-0002-9748-7075","contributorId":209444,"corporation":false,"usgs":true,"family":"Fitzpatrick","given":"Faith A.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":899272,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Magyera, Kyle H.","contributorId":292245,"corporation":false,"usgs":false,"family":"Magyera","given":"Kyle","email":"","middleInitial":"H.","affiliations":[{"id":62844,"text":"Wisconsin Wetlands Association","active":true,"usgs":false}],"preferred":false,"id":899273,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Laumann, Jason","contributorId":330643,"corporation":false,"usgs":false,"family":"Laumann","given":"Jason","email":"","affiliations":[{"id":78946,"text":"Northwest Regional Planning Commission","active":true,"usgs":false}],"preferred":false,"id":899274,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Larson, Clement","contributorId":330644,"corporation":false,"usgs":false,"family":"Larson","given":"Clement","email":"","affiliations":[{"id":78946,"text":"Northwest Regional Planning Commission","active":true,"usgs":false}],"preferred":false,"id":899275,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rockwood, Stephanie","contributorId":240930,"corporation":false,"usgs":false,"family":"Rockwood","given":"Stephanie","email":"","affiliations":[{"id":38111,"text":"National Park Service, Rapid City, SD","active":true,"usgs":false}],"preferred":false,"id":899276,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dantoin, Eric D. 0000-0002-8561-2924 edantoin@usgs.gov","orcid":"https://orcid.org/0000-0002-8561-2924","contributorId":2278,"corporation":false,"usgs":true,"family":"Dantoin","given":"Eric","email":"edantoin@usgs.gov","middleInitial":"D.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":899277,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hollenhorst, Tom","contributorId":335700,"corporation":false,"usgs":false,"family":"Hollenhorst","given":"Tom","email":"","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":899278,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Krumwiede, Brandon","contributorId":297013,"corporation":false,"usgs":false,"family":"Krumwiede","given":"Brandon","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":899279,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Nelson, Brandon Ray 0009-0008-2244-7563","orcid":"https://orcid.org/0009-0008-2244-7563","contributorId":335701,"corporation":false,"usgs":true,"family":"Nelson","given":"Brandon","email":"","middleInitial":"Ray","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":899280,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Prokopec, Julia G. 0000-0001-5937-2720","orcid":"https://orcid.org/0000-0001-5937-2720","contributorId":207862,"corporation":false,"usgs":true,"family":"Prokopec","given":"Julia G.","affiliations":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":899281,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Johnson, Keegan Eland 0000-0003-1940-4542","orcid":"https://orcid.org/0000-0003-1940-4542","contributorId":332782,"corporation":false,"usgs":true,"family":"Johnson","given":"Keegan","email":"","middleInitial":"Eland","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":899282,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ]}