The Trout Rock caves (Hamilton Cave, Trout Cave, New Trout Cave) are located in a hill named Cave Knob that overlooks the South Branch of the Potomac River in Pendleton County, West Virginia (U.S.A). The geologic structure of this hill is a northeasttrending anticline, and the caves are located at different elevations primarily along the contact between the Devonian New Creek Limestone (Helderberg Group) and the overlying Devonian Corriganville Limestone (Helderberg Group). The entrance to New Trout Cave (Stop 1) is located on the east flank of Cave Knob anticline at an elevation of 585 m (1,920 ft) relative to sea level, or 39 m (128 ft) above the modern river. Much of the cave consists of passages that extend to the northeast along strike, and many of these passages have developed along primary joints that trend N40E or secondary joints that trend N40W. Sediments in New Trout Cave include mud and sand (some of which was mined for nitrate during the American Civil War), as well as large boulders in the front part of the cave. Gypsum crusts are present in a maze section of the cave ~213 to 305 m (700 to 1,000 ft) from the cave entrance. Excavations in New Trout Cave have produced vertebrate fossils of Rancholabrean age, ~300,000 to 10,000 years Before Present (BP). The entrance to Trout Cave (Stop 2) is located on the east flank of Cave Knob anticline ~100 m (328 ft) northwest of the New Trout Cave entrance at an elevation of 622 m (2,040 ft) relative to sea level, or 76 m (249 ft) above the modern river. Much of the cave consists of passages that extend to the northeast along strike, although a small area of network maze passages is present in the western portion of Trout Cave that is closest to Hamilton Cave. Many of the passages of Trout Cave have developed along primary joints that trend N40E or secondary joints that trend N40W. Sediments in Trout Cave include mud (also mined for nitrate during the American Civil War), as well as large boulders in the front part of the cave. Excavations in the upper levels of Trout Cave have produced vertebrate fossils of Rancholabrean age (~300,000 to 10,000 years BP), whereas excavations in the lower levels of the cave have produced vertebrate fossils of Irvingtonian age (~1,810,000 to 300,000 years BP). The entrance to Hamilton Cave (Stop 3) is located along the axis of Cave Knob anticline ~165 m (540 ft) northwest of the Trout Cave entrance at an elevation of 640 m (2,100 ft) relative to sea level, or 94 m (308 ft) above the modern river. The front (upper) part of Hamilton Cave has a classic network maze pattern that is an angular grid of relatively horizontal passages, most of which follow vertical or near-vertical primary joints that trend N40W and N50W and secondary joints that trend N60W and N80E. This part of the cave lies along the axis of Cave Knob anticline. In contrast, the passages in the back (lower) part of Hamilton Cave lie along the west flank of Cave Knob anticline at ~58 to 85 m (190 to 279 ft) above the modern river. These passages do not display a classic maze pattern, and instead they may be divided into the following two categories: (1) longer northeast-trending passages that are relatively horizontal and follow the strike of the beds; and (2) shorter northwest-trending passages that descend steeply to the west and follow the dip of the beds. Sediments in Hamilton Cave include mud (which was apparently not mined for nitrate during the American Civil War), as well as large boulders in the front part of the cave. Gypsum crusts are present along passage walls of the New Creek Limestone from the Slab Room to the Airblower. Excavations in the front part of Hamilton Cave (maze section) have produced vertebrate fossils of Irvingtonian age (~1,810,000 to 300,000 years BP). The network maze portions of Hamilton Cave are interpreted as having developed at or near the water table where water did not have a free surface in contact with air and where the following conditions were present: (1) Location on or near the axis of an anticline (the location of the greatest amount of flexure); (2) Abundant vertical or near vertical joints, which are favored by location in the area of greatest flexure and by a lithologic unit (chert-rich limestone) that is more likely to experience brittle rather than ductile deformation; (3) Widening of joints to enhance ease of water infiltration, favored by location in area of greatest amount of flexure; and (4) Dissolution along nearly all major joints to produce cave passages of approximately the same size (which would most likely occur via water without a free surface in contact with air). The cave passages that are located along anticline axes and along strike at the New Creek-Corriganville contact are interpreted as having formed initially during times of base level stillstand at or near the water table where water did not have a free surface in contact with air and where the water flowed along the hydraulic gradient at gentle slopes. Under such conditions, dissolution occurred in all directions to produce cave passages with relatively linear wall morphologies. In the lower portions of some of the along-strike passages, the cave walls have a more sinuous (meandering) morphology, which is interpreted as having formed during subsequent initial base level fall as cave development continued under vadose conditions where the water had a free surface in contact with air, and where water flow was governed primarily by gravitational processes. Steeply inclined cave passages that are located along dip at the New Creek-Corriganville contact are interpreted as having formed during subsequent true vadose conditions (after base level fall). This chronology of base level stasis (with cave development in the phreatic zone a short distance below top of water table) followed by base level fall (with cave development in the vadose or epiphreatic zone) has repeated multiple times at Cave Knob during the past ~4 to 3 million years, resulting in multiple cave passages at different elevations, with different passage morphologies, and at different passage locations with respect to strike and dip.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Geological Society of America Field Guide","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Geological Society of America","doi":"10.1130/2020.0057(03)","collaboration":"","usgsCitation":"Swezey, C.S., and Brent, E.L., 2020, Geology of the Trout Rock caves (Hamilton Cave, Trout Cave, New Trout Cave) in Pendleton County, West Virginia (USA), and implications regarding the origin of maze caves, chap. of Geological Society of America Field Guide, v. 57, p. 43-77, https://doi.org/10.1130/2020.0057(03).","productDescription":"35 p.","startPage":"43","endPage":"77","ipdsId":"IP-113405","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":457583,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/2020.0057(03)","text":"Publisher Index Page"},{"id":373863,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"West Virginia","county":"Pendleton County","otherGeospatial":"Trout Rock Caves","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.06036376953125,\n 38.768004230175954\n ],\n [\n -79.37759399414062,\n 38.975424875431436\n ],\n [\n -79.4586181640625,\n 38.932707274379595\n ],\n [\n -79.53826904296875,\n 38.839707613545144\n ],\n [\n -79.66323852539062,\n 38.59970036588819\n ],\n [\n -79.53414916992186,\n 38.543869175876154\n ],\n [\n -79.47509765625,\n 38.460041065720446\n ],\n [\n -79.33364868164062,\n 38.415938460513274\n ],\n [\n -79.27322387695312,\n 38.41486245064945\n ],\n [\n -79.20867919921875,\n 38.50304202775689\n ],\n [\n -79.21005249023438,\n 38.515937313413474\n ],\n [\n -79.12216186523438,\n 38.66299474019031\n ],\n [\n -79.1015625,\n 38.659777730712534\n ],\n [\n -79.08233642578124,\n 38.6897975322717\n ],\n [\n -79.06036376953125,\n 38.768004230175954\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"57","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Swezey, Christopher S. 0000-0003-4019-9264 cswezey@usgs.gov","orcid":"https://orcid.org/0000-0003-4019-9264","contributorId":173033,"corporation":false,"usgs":true,"family":"Swezey","given":"Christopher","email":"cswezey@usgs.gov","middleInitial":"S.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":786454,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brent, Emily L","contributorId":223860,"corporation":false,"usgs":false,"family":"Brent","given":"Emily","email":"","middleInitial":"L","affiliations":[],"preferred":false,"id":786455,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70209422,"text":"70209422 - 2020 - Foreward: Geology Field Trips in and around the U.S. Capital","interactions":[],"lastModifiedDate":"2020-04-28T20:30:35.335374","indexId":"70209422","displayToPublicDate":"2020-02-26T12:11:17","publicationYear":"2020","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Foreward: Geology Field Trips in and around the U.S. Capital","docAbstract":"The first annual meeting of the Geological Society of America (GSA) was held in 1888 in Ithaca, New York (Fairchild, 1932), but official Sections of GSA formed much later. During the spring of 1949, a symposium in Knoxville, Tennessee, on mineral resources of the southeastern United States became the catalyst for the creation of the Southeastern Section of the Geological Society of America (King, 1964), and the first annual meeting of the Southeastern Section was held in 1952 in Roanoke, Virginia (Wilson, 1954). The Northeastern Section formed much later, and its first annual meeting was held in 1966 in Philadelphia, Pennsylvania (Socolow, 1968). At all of these section meetings, field trips have been important venues for geologists and especially students to gather together, examine rocks in the field, and discuss ideas. These field trips have been especially important at combined section meetings because they provide settings for geologists who are experienced in one geographic region to examine and compare the geology of other regions. The first combined meeting of the Southeastern and Northeastern sections occurred in 1976 in Arlington, Virginia. Since then, the Southeastern and Northeastern sections have met together on numerous occasions, including 1982 in Washington, DC; 1991 in Baltimore, Maryland; 2004 in Tysons Corner, Virginia; and 2010 in Baltimore, Maryland. \n Since the first combined section meeting in 1976, there has been a gradual increase in the role of technology in geology field studies. In fact, during the past several decades there has been an increase in emphasis in our society on the instrumental component of science, the goal of which is operational techniques to do or control things, and a corresponding decrease in emphasis on the natural philosophy component of science, the goal of which is a greater understanding of the natural world (Dear, 2006). The modern education acronym STEM (Science, Technology, Engineering, and Mathematics), for example, is often used as a catch-all term that implies that science and technology are relatively synonymous, and implies that greater technology leads automatically to greater understanding of the natural world. This assumption, however, is not always valid (Dear, 2006), and technology should not be promoted as a substitute for field experiences. Technology can be a tool that leads to greater understanding of the natural world, but not all Science uses technology as a means of providing greater understanding. The benefits of new technologies include: (1) data of greater resolution; and (2) greater efficiency of capturing, storing, and visualizing data. The risks of new technologies include: (1) an overabundance of data, some of which may be of little value; (2) less time available for analysis of data, if geologists become occupied primarily with capturing and storing data; and (3) errors that arise from complacency and the perception that field-checking may not be necessary. In other words, there is a risk that a glut of data and vast amounts of time devoted to the capturing and storing of data may result in a reduced interest and (or) willingness to field-check data. \nIn the spirit of the early GSA section meetings, we feel that there are still enormous advantages to conducting geology field trips in conjunction with traditional meeting presentations and posters. In 2020, with this current combined Southeastern and Northeastern section meeting in Reston, Virginia, we have assembled eight different field trips that cover a wide range of territory in and around the Nation’s capital. These field trip localities include the immediate vicinity of Washington, DC, as well as various locations in nearby areas of Virginia, Maryland, and West Virginia. The physiographic provinces include Mesozoic Rift Basins, the Piedmont, the Blue Ridge, the Valley and Ridge, and the Allegheny Plateau of the Appalachian Basin. The field trip sites exhibit a wide range of igneous, metamorphic, and sedimentary rocks, as well as rocks with a wide range of geologic ages from the Mesoproterozoic to the Holocene. We hope that this guidebook provides new motivation for geologists to examine rocks in the field, to discuss ideas with colleagues in the field, and to avoid becoming complacent. \n The editors of this volume would like to thank the authors of the different field trip guides, the field trip leaders, and all of the reviewers who made suggestions for improving the field trip manuscripts. The editors would also like to thank Elle Derwent of GSA for her logistical help and guidance regarding the field trips, and April Leo and the staff of the GSA Publications Department for seeing this book through to publication.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Geological Society of America Field Guide","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Geological Society of America","doi":"10.1130/2020.0057(00)","collaboration":"","usgsCitation":"Swezey, C.S., and Carter, M.W., 2020, Foreward: Geology Field Trips in and around the U.S. Capital, chap. of Geological Society of America Field Guide, v. 57, p. v-vi, https://doi.org/10.1130/2020.0057(00).","productDescription":"2 p.","startPage":"v","endPage":"vi","ipdsId":"IP-113973","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":373862,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland, Virginia, West Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.870361328125,\n 36.84006462037767\n ],\n [\n -75.8056640625,\n 36.84006462037767\n ],\n [\n -75.8056640625,\n 39.65222681530652\n ],\n [\n -80.870361328125,\n 39.65222681530652\n ],\n [\n -80.870361328125,\n 36.84006462037767\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"57","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Swezey, Christopher S. 0000-0003-4019-9264 cswezey@usgs.gov","orcid":"https://orcid.org/0000-0003-4019-9264","contributorId":173033,"corporation":false,"usgs":true,"family":"Swezey","given":"Christopher","email":"cswezey@usgs.gov","middleInitial":"S.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":786450,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carter, Mark W. 0000-0003-0460-7638 mcarter@usgs.gov","orcid":"https://orcid.org/0000-0003-0460-7638","contributorId":4808,"corporation":false,"usgs":true,"family":"Carter","given":"Mark","email":"mcarter@usgs.gov","middleInitial":"W.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":786451,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70211287,"text":"70211287 - 2020 - The role of Northeast Pacific meltwater events in deglacial climate change","interactions":[],"lastModifiedDate":"2020-07-22T15:13:57.928397","indexId":"70211287","displayToPublicDate":"2020-02-26T10:11:20","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5010,"text":"Science Advances","active":true,"publicationSubtype":{"id":10}},"title":"The role of Northeast Pacific meltwater events in deglacial climate change","docAbstract":"Columbia River megafloods occurred repeatedly during the last deglaciation, but the impacts of this fresh water on Pacific hydrography are largely unknown. To reconstruct changes in ocean circulation during this period, we used a numerical model to simulate the flow trajectory of Columbia River megafloods and compiled records of sea surface temperature, paleo-salinity, and deep-water radiocarbon from marine sediment cores in the Northeast Pacific. The North Pacific sea surface cooled and freshened during the early deglacial (19.0-16.5 ka) and Younger Dryas (12.9-11.7 ka) intervals, coincident with the appearance of subsurface water masses depleted in radiocarbon relative to the sea surface. We infer that Pacific meltwater fluxes contributed to net Northern Hemisphere cooling prior to North Atlantic Heinrich Events, and again during the Younger Dryas stadial. Abrupt warming in the Northeast Pacific similarly contributed to hemispheric warming during the Bølling and Holocene transitions. These findings underscore the importance of changes in North Pacific freshwater fluxes and circulation in deglacial climate events.","language":"English","publisher":"AAAS","doi":"10.1126/sciadv.aay2915","usgsCitation":"Praetorius, S.K., Condron, A., Mix, A., Walczak, M., McKay, J., and Du, J., 2020, The role of Northeast Pacific meltwater events in deglacial climate change: Science Advances, v. 6, no. 9, eaay2915, 18 p., https://doi.org/10.1126/sciadv.aay2915.","productDescription":"eaay2915, 18 p.","ipdsId":"IP-093675","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":457590,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1126/sciadv.aay2915","text":"Publisher Index Page"},{"id":376636,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","issue":"9","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Praetorius, Summer K. 0000-0003-2683-3652","orcid":"https://orcid.org/0000-0003-2683-3652","contributorId":206966,"corporation":false,"usgs":true,"family":"Praetorius","given":"Summer","email":"","middleInitial":"K.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":793519,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Condron, Alan 0000-0002-7337-1713","orcid":"https://orcid.org/0000-0002-7337-1713","contributorId":229547,"corporation":false,"usgs":false,"family":"Condron","given":"Alan","email":"","affiliations":[{"id":36711,"text":"Woods Hole Oceanographic Institution","active":true,"usgs":false}],"preferred":false,"id":793520,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mix, Alan","contributorId":184163,"corporation":false,"usgs":false,"family":"Mix","given":"Alan","affiliations":[],"preferred":false,"id":793521,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Walczak, Maureen 0000-0002-4123-6998","orcid":"https://orcid.org/0000-0002-4123-6998","contributorId":206972,"corporation":false,"usgs":false,"family":"Walczak","given":"Maureen","email":"","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":793522,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McKay, Jennifer","contributorId":229548,"corporation":false,"usgs":false,"family":"McKay","given":"Jennifer","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":793523,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Du, Jianghui 0000-0002-3386-9314","orcid":"https://orcid.org/0000-0002-3386-9314","contributorId":206970,"corporation":false,"usgs":false,"family":"Du","given":"Jianghui","email":"","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":793524,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70263647,"text":"70263647 - 2020 - Near-field ground motions from the July, 2019 Ridgecrest, California, earthquake sequence","interactions":[],"lastModifiedDate":"2025-02-19T14:20:57.140542","indexId":"70263647","displayToPublicDate":"2020-02-26T09:53:35","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Near-field ground motions from the July, 2019 Ridgecrest, California, earthquake sequence","docAbstract":"The 2019 Ridgecrest, California, earthquake sequence, including an Mw 6.4 event on 4 July and an Mw 7.1 approximately 34 hr later, was recorded by 15 instruments within 55 km nearest‐fault distance. To characterize and explore near‐field ground motions from the Mw 6.4 foreshock and Mw 7.1 mainshock, we augment these records with available macroseismic information, including conventional intensities and displaced rocks. We conclude that near‐field shaking intensities were generally below modified Mercalli intensity 9, with concentrations of locally high values toward the northern and southern termini of the mainshock rupture. We further show that, relative to near‐field ground motions at hard‐rock sites, instrumental ground motions at alluvial near‐field sites for both the Mw 6.4 foreshock and Mw 7.1 mainshock were depleted in energy at frequencies higher than 2–3 Hz, as expected from ground‐motion models. Both the macroseismic and instrumental observations suggest that sediments in the Indian Wells Valley experienced a pervasively nonlinear response, which helps explain why shaking intensities and damage in the closest population center, Ridgecrest, were relatively modest given its proximity to the earthquakes.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220190279","usgsCitation":"Hough, S.E., Thompson, E.M., Parker, G., Graves, R., Hudnut, K.W., Patton, J., Dawson, T., Ladinsky, T.C., Oskin, M., Sirorattanakul, K., Blake, K., Baltay Sundstrom, A.S., and Cochran, E.S., 2020, Near-field ground motions from the July, 2019 Ridgecrest, California, earthquake sequence: Seismological Research Letters, v. 91, no. 3, p. 1542-1555, https://doi.org/10.1785/0220190279.","productDescription":"14 p.","startPage":"1542","endPage":"1555","ipdsId":"IP-112076","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":482164,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n 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emthompson@usgs.gov","orcid":"https://orcid.org/0000-0002-6943-4806","contributorId":150897,"corporation":false,"usgs":true,"family":"Thompson","given":"Eric","email":"emthompson@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":927654,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Parker, Grace A.","contributorId":350992,"corporation":false,"usgs":false,"family":"Parker","given":"Grace A.","affiliations":[],"preferred":false,"id":927655,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Graves, Robert 0000-0001-9758-453X rwgraves@usgs.gov","orcid":"https://orcid.org/0000-0001-9758-453X","contributorId":140738,"corporation":false,"usgs":true,"family":"Graves","given":"Robert","email":"rwgraves@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science 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Program","active":true,"usgs":true}],"preferred":true,"id":927664,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Cochran, Elizabeth S. 0000-0003-2485-4484 ecochran@usgs.gov","orcid":"https://orcid.org/0000-0003-2485-4484","contributorId":2025,"corporation":false,"usgs":true,"family":"Cochran","given":"Elizabeth","email":"ecochran@usgs.gov","middleInitial":"S.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927665,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70223337,"text":"70223337 - 2020 - Trends in cheetah Acinonyx jubatus density in north-central Namibia","interactions":[],"lastModifiedDate":"2021-08-24T13:13:40.57478","indexId":"70223337","displayToPublicDate":"2020-02-26T08:09:04","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3103,"text":"Population Ecology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Trends in cheetah Acinonyx jubatus density in north-central Namibia","title":"Trends in cheetah Acinonyx jubatus density in north-central Namibia","docAbstract":"Assessing trends in abundance and density of species of conservation concern is vital to inform conservation and management strategies. The remaining population of the cheetah (Acinonyx jubatus) largely exists outside of protected areas, where they are often in conflict with humans. Despite this, the population status and dynamics of cheetah outside of protected areas have received relatively limited attention across its range. We analyzed remote camera trapping data of nine surveys conducted from 2005 to 2014 in the Waterberg Conservancy, north-central Namibia, which included detections of 74 individuals (52 adult males, 7 adult females and 15 dependents). Using spatial capture–recapture methods, we assessed annual and seasonal trends in cheetah density. We found evidence of a stable trend in cheetah density over the study period, with an average density of 1.94/100 km2 (95% confidence interval 1.33–2.84). This apparent stability of cheetah density is likely the result of stable and abundant prey availability, a high tolerance to carnivores by farmers and low turnover rates in home range tenure. This study highlights the importance of promoting long-term surveys that capture a broad range of environmental variation that may influence species density and the importance of nonprotected areas for cheetah conservation.
In 2015, the total amount of water withdrawn in Florida was estimated to be 15,319 million gallons per day (Mgal/d). Saline water accounted for 9,598 Mgal/d (63 percent) and freshwater accounted for 5,721 Mgal/d (37 percent) of the total. Groundwater accounted for 3,604 Mgal/d (63 percent) of freshwater withdrawals and surface water accounted for the remaining 2,117 Mgal/d (37 percent). Surface-water sources accounted for 9,401 Mgal/d (98 percent) of the saline-water withdrawals, and groundwater sources accounted for the remaining 198 Mgal/d (2 percent). The majority of groundwater withdrawals (almost 62 percent) in 2015 were from the Floridan aquifer system, which is used throughout most of the State while the majority of fresh surface-water withdrawals (52 percent) occurred in the Southern Florida Subregion, a hydrologic unit that includes Lake Okeechobee and canals in the Everglades Agricultural Area. Groundwater provided drinking water (public supplied and self-supplied) for 18.324 million people (92 percent of Florida’s population), and fresh surface water provided drinking water for 1.491 million people (8 percent).
Overall, public supply accounted for 39 percent of the total freshwater withdrawals (ground and surface) and 53 percent of groundwater withdrawals, followed by agricultural self-supplied uses, which accounted for 37 percent of the total freshwater withdrawals and 28 percent of groundwater withdrawals. Other self-supplied groundwater withdrawals include commercial-industrial-mining self-supplied (8 percent), recreational-landscape irrigation and domestic self-supplied (5 percent each), and power generation (less than 1 percent). Agricultural self-supplied withdrawals accounted for 51 percent of fresh surface-water withdrawals, followed by power generation (19 percent), public supply (15 percent), recreational-landscape irrigation (10 percent), and commercial-industrial-mining self-supplied (5 percent).
In 1975, agricultural water withdrawals accounted for 43 percent of the total freshwater withdrawals, followed by power generation (24 percent) and public supply (17 percent). By 2000, agricultural withdrawals increased to 48 percent of the total freshwater withdrawals, followed by public supply (30 percent). For 2015, agricultural self-supplied decreased to 37 percent of total freshwater withdrawals, and was surpassed by public supply at 39 percent. Over the 40-year period between 1975 and 2015, increases in freshwater withdrawals caused by large gains in population and the expansion of irrigated acreage were offset by decreases in water used for power generation and commercial-industrial-mining withdrawals. Since 2000, however, irrigated acreage has decreased statewide because of crop disease, storm damage, and urbanization. This decline, coupled with large gains in water conservation measures in the farming industry, has led to agricultural withdrawals in Florida being less than public-supply withdrawals for the first time since water-use data were first reported in 1965.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195147","collaboration":"Prepared in cooperation with the Florida Department of Agricultural and Consumer Services","usgsCitation":"Marella, R.L., 2020, Water withdrawals, uses, and trends in Florida, 2015: U.S. Geological Survey Scientific Investigations Report 2019–5147, 52 p., https://doi.org/10.3133/sir20195147.","productDescription":"Report: vii, 52 p.; Data Release","numberOfPages":"64","onlineOnly":"Y","ipdsId":"IP-093230","costCenters":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":372545,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5147/sir20195147.pdf","text":"Report","size":"2.34 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019–5147"},{"id":372544,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5147/coverthb.jpg"},{"id":399620,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109728.htm"},{"id":372546,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7N29W5M","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Data tables summarizing the source-specific estimated water withdrawals in Florida by category, county, and water management district, 2015"}],"country":"United 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\"}}]}","contact":"Director, Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559
The behavior of wildlife varies seasonally, and that variation can have substantial demographic consequences. This is especially true for long‐distance migrants where the use of landscapes varies by season and, sometimes, age cohort. We tested the hypothesis that distributional patterns of Golden Eagles (Aquila chrysaetos) wintering in eastern North America are age‐structured (i.e., birds of similar ages winter together) through the analysis of 370,307 images collected by motion‐sensitive trail cameras set over bait during the winters of 2012–2013 and 2013–2014. At nine sites with sufficient data for analysis, we documented 145 eagle visits in 2012–2013 and 146 in 2013–2014. We found significant between‐year variation in age structure of wintering eastern Golden Eagles, driven largely by annual differences in the proportion of first‐winter birds. However, although many other species show spatial structure in wintering behavior, our analysis revealed no latitudinal organization among age cohorts of wintering eastern Golden Eagles. The lack of age‐related latitudinal segregation in wintering behavior does not exclude the possibility that these eagles have sex‐based or other types of dominance hierarchies that could result in spatial or temporal segregation. Alternatively, other mechanisms such as food availability or habitat structure may determine the distribution and abundance of Golden Eagles in winter.
Recent technological and methodological advances have revolutionized wildlife monitoring. Although most biodiversity monitoring initiatives are geared towards focal species of conservation concern, researchers are increasingly studying entire communities, specifically the spatiotemporal drivers of community size and structure and interactions among species. This has resulted in the emergence of multi‐species occupancy models (MSOMs) as a promising and efficient approach for the study of community ecology. Given the potential of MSOMs for conservation and management action, it is critical to know whether study design and model assumptions are consistent with inference objectives. This is especially true for studies that are designed for a focal species but can give insights about a community. Here, we review the recent literature on MSOMs, identify areas of improvement in the multi‐species study workflow, and provide a reference model for best practices for focal species and community monitoring study design. We reviewed 92 studies published between 2009 and early 2018, spanning 27 countries and a variety of taxa. There is a consistent under‐reporting of details that are central to determining the adequacy of designs for generating data that can be used to make inferences about community‐level patterns of occupancy, including the spatial and temporal extent, types of detectors used, covariates considered, and choice of field methods and statistical tools. This reporting bias could consequently result in skewed estimates, affecting conservation actions and management plans. On the other hand, comprehensive reporting is likely to help researchers working on MSOMs assess the robustness of inferences, in addition to making strides in terms of reproducibility and reusability of data. We use our literature review to inform a roadmap with best practices for MSOM studies, from simulations to design considerations and reporting, for the collection of new data as well as those involving existing datasets.
","language":"English","publisher":"Wiley","doi":"10.1111/ecog.04957","usgsCitation":"Devarajan, K., Tenan, S., and Morelli, T.L., 2020, Multi‐species occupancy models: Review, roadmap, and recommendations: Ecography, v. 43, no. 11, p. 1612-1624, https://doi.org/10.1111/ecog.04957.","productDescription":"14 p.","startPage":"1612","endPage":"1624","ipdsId":"IP-114395","costCenters":[{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":457599,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ecog.04957","text":"Publisher Index Page"},{"id":376821,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"43","issue":"11","noUsgsAuthors":false,"publicationDate":"2020-02-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Devarajan, Kadambari","contributorId":236828,"corporation":false,"usgs":false,"family":"Devarajan","given":"Kadambari","email":"","affiliations":[],"preferred":false,"id":794271,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tenan, Simone","contributorId":177519,"corporation":false,"usgs":false,"family":"Tenan","given":"Simone","email":"","affiliations":[],"preferred":false,"id":794272,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Morelli, Toni Lyn 0000-0001-5865-5294 tmorelli@usgs.gov","orcid":"https://orcid.org/0000-0001-5865-5294","contributorId":197458,"corporation":false,"usgs":true,"family":"Morelli","given":"Toni","email":"tmorelli@usgs.gov","middleInitial":"Lyn","affiliations":[{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":794273,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70208399,"text":"fs20203009 - 2020 - Water-quality comparison of the Gulf Coast aquifer system and Carrizo-Wilcox aquifer in Texas from National Water-Quality Assessment Project Principal Aquifer Surveys, 2013 and 2015","interactions":[],"lastModifiedDate":"2022-04-20T18:25:46.361216","indexId":"fs20203009","displayToPublicDate":"2020-02-25T15:26:57","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-3009","displayTitle":"Water-Quality Comparison of the Gulf Coast Aquifer System and Carrizo-Wilcox Aquifer in Texas From National Water-Quality Assessment Project Principal Aquifer Surveys, 2013 and 2015","title":"Water-quality comparison of the Gulf Coast aquifer system and Carrizo-Wilcox aquifer in Texas from National Water-Quality Assessment Project Principal Aquifer Surveys, 2013 and 2015","docAbstract":"The U.S. Geological Survey’s National Water-Quality Assessment (NAWQA) Project assessed the quality of groundwater in aquifers that are important sources of drinking water in the United States. One major aquifer in Texas that was assessed by NAWQA in 2013 is the coastal lowlands aquifer system, which is often referred to in Texas as the “Gulf Coast aquifer system.” The coastal lowlands aquifer system supplies water for millions of people; self-supplied (private) well withdrawals in 2005 from this aquifer system were the sixth largest among all major aquifer systems in the Nation. A major aquifer in Texas that was assessed by NAWQA in 2015 is the Texas coastal uplands aquifer system; the Carrizo-Wilcox aquifer is one of several aquifers that compose this aquifer system in Texas. The rocks composing the Texas coastal uplands aquifer system extend east from Texas as part of the Mississippi embayment aquifer system and underlie areas of several States. The Texas coastal uplands aquifer system and Mississippi embayment aquifer system are often collectively referred to as the “Mississippi embayment-Texas coastal uplands aquifer system.” Self-supplied withdrawals from the Mississippi embayment-Texas coastal uplands aquifer system in 2005 were the eighth largest among all major aquifer systems in the Nation. The coastal lowlands aquifer system and Mississippi embayment-Texas coastal uplands aquifer system were assessed as part of the NAWQA Principal Aquifer Surveys (PAS), which were designed to evaluate constituent concentrations in water samples obtained from domestic and public-supply wells prior to any treatment. PAS assessments like these allow for the comparison of water-quality concentrations in untreated groundwater using preestablished benchmarks for the protection of human health and for aesthetic qualities such as taste, color, and odor. The use of preestablished benchmarks can provide a basis for comparison of groundwater quality among principal aquifers.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20203009","collaboration":"U.S. Geological Survey National Water-Quality Assessment","usgsCitation":"Ging, P.B., 2020, Water-quality comparison of the Gulf Coast aquifer system and Carrizo-Wilcox aquifer in Texas from National Water-Quality Assessment Project Principal Aquifer Surveys, 2013 and 2015: U.S. Geological Survey Fact Sheet 2020–3009, 4 p., https://doi.org/10.3133/fs20203009.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"N","ipdsId":"IP-111986","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":399199,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109727.htm"},{"id":372560,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2020/3009/fs20203009.pdf","text":"Report","size":"1.01 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 20220–3009"},{"id":372559,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2020/3009/coverthb.jpg"}],"country":"United States","state":"Texas","otherGeospatial":"Gulf Coast aquifer system, Carrizo-Wilcox aquifer","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -100.5,\n 25.8378\n ],\n [\n -93.5069,\n 25.8378\n ],\n [\n -93.5069,\n 33.5433\n ],\n [\n -100.5,\n 33.5433\n ],\n [\n -100.5,\n 25.8378\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oklahoma-Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, TX 78754–4501
Phytoplankton play key roles in the oceans by regulating global biogeochemical cycles and production in marine food webs. Global warming is thought to affect phytoplankton production both directly, by impacting their photosynthetic metabolism, and indirectly by modifying the physical environment in which they grow. In this respect, the Bermuda Atlantic Time-series Study (BATS) in the Sargasso Sea (North Atlantic gyre) provides a unique opportunity to explore effects of warming on phytoplankton production across the vast oligotrophic ocean regions because it is one of the few multidecadal records of measured net primary productivity (NPP). We analysed the time series of phytoplankton primary productivity at BATS site using machine learning techniques (ML) to show that increased water temperature over a 27-year period (1990–2016), and the consequent weakening of vertical mixing in the upper ocean, induced a negative feedback on phytoplankton productivity by reducing the availability of essential resources, nitrogen and light. The unbalanced availability of these resources with warming, coupled with ecological changes at the community level, is expected to intensify the oligotrophic state of open-ocean regions that are far from land-based nutrient sources.
","language":"English","publisher":"Nature Publications","doi":"10.1038/s41598-020-59989-y","usgsCitation":"D’Alelio, D., Rampone, S., Cusano, L.M., Morfino, V., Russo, L., Sanseverino, N., Cloern, J.E., and Lomas, M.W., 2020, Machine learning identifies a strong association between warming and reduced primary productivity in an oligotrophic ocean gyre: Scientific Reports, v. 10, 3287, 12 p., https://doi.org/10.1038/s41598-020-59989-y.","productDescription":"3287, 12 p.","ipdsId":"IP-111898","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":457603,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-020-59989-y","text":"Publisher Index Page"},{"id":387061,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"North Atlantic Gyre","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -64.3359375,\n 23.885837699862005\n ],\n [\n -38.84765625,\n 28.613459424004414\n ],\n [\n -19.51171875,\n 34.016241889667015\n ],\n [\n -17.75390625,\n 41.11246878918088\n ],\n [\n -26.3671875,\n 47.754097979680026\n ],\n [\n -41.66015625,\n 46.6795944656402\n ],\n [\n -61.17187499999999,\n 39.639537564366684\n ],\n [\n -69.78515625,\n 35.31736632923788\n ],\n [\n -76.9921875,\n 31.203404950917395\n ],\n [\n -75.41015624999999,\n 26.902476886279832\n ],\n [\n -71.54296874999999,\n 23.563987128451217\n ],\n [\n -64.3359375,\n 23.885837699862005\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","noUsgsAuthors":false,"publicationDate":"2020-02-25","publicationStatus":"PW","contributors":{"authors":[{"text":"D’Alelio, Domenico","contributorId":260813,"corporation":false,"usgs":false,"family":"D’Alelio","given":"Domenico","email":"","affiliations":[{"id":27945,"text":"Stazione Zoologica Anton Dohrn","active":true,"usgs":false}],"preferred":false,"id":818883,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rampone, Salvatore","contributorId":260814,"corporation":false,"usgs":false,"family":"Rampone","given":"Salvatore","email":"","affiliations":[{"id":52676,"text":"Università degli Studi del Sannio","active":true,"usgs":false}],"preferred":false,"id":818884,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cusano, Luigi Maria","contributorId":260815,"corporation":false,"usgs":false,"family":"Cusano","given":"Luigi","email":"","middleInitial":"Maria","affiliations":[{"id":52676,"text":"Università degli Studi del Sannio","active":true,"usgs":false}],"preferred":false,"id":818885,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Morfino, Valerio","contributorId":260816,"corporation":false,"usgs":false,"family":"Morfino","given":"Valerio","email":"","affiliations":[{"id":52676,"text":"Università degli Studi del Sannio","active":true,"usgs":false}],"preferred":false,"id":818886,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Russo, Luca","contributorId":260817,"corporation":false,"usgs":false,"family":"Russo","given":"Luca","email":"","affiliations":[{"id":27945,"text":"Stazione Zoologica Anton Dohrn","active":true,"usgs":false}],"preferred":false,"id":818887,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sanseverino, Nadia","contributorId":260818,"corporation":false,"usgs":false,"family":"Sanseverino","given":"Nadia","email":"","affiliations":[{"id":52676,"text":"Università degli Studi del Sannio","active":true,"usgs":false}],"preferred":false,"id":818888,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cloern, James E. 0000-0002-5880-6862 jecloern@usgs.gov","orcid":"https://orcid.org/0000-0002-5880-6862","contributorId":1488,"corporation":false,"usgs":true,"family":"Cloern","given":"James","email":"jecloern@usgs.gov","middleInitial":"E.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":818889,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lomas, Michael W.","contributorId":260819,"corporation":false,"usgs":false,"family":"Lomas","given":"Michael","email":"","middleInitial":"W.","affiliations":[{"id":13692,"text":"Bigelow Laboratory for Ocean Sciences","active":true,"usgs":false}],"preferred":false,"id":818890,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70209079,"text":"70209079 - 2020 - Prioritizing water security in the management of vector borne diseases: Lessons from Oaxaca, Mexico","interactions":[],"lastModifiedDate":"2020-03-16T06:18:12","indexId":"70209079","displayToPublicDate":"2020-02-25T14:22:00","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5050,"text":"Geohealth News","active":true,"publicationSubtype":{"id":10}},"title":"Prioritizing water security in the management of vector borne diseases: Lessons from Oaxaca, Mexico","docAbstract":"Changes in human water use, along with temperature and rainfall patterns, are facilitating habitat spread and distribution of Aedes aegypti and Aedes albopictus mosquitoes, the primary vectors for the transmission of Dengue, Chikungunya, and Zika viruses in the Americas. Artificial containers and wetspots provide major sources of mosquito larval habitat in residential areas. Mosquito abatement and control strategies remain the most effective public health interventions for minimizing the impact of these vector borne diseases. Understanding how water insecurity is conducive to the establishment and elimination of endemic mosquito populations, particularly in arid or semi-arid regions, is a vital component in shaping these intervention strategies.","language":"English","publisher":"AGU","doi":"10.1029/2019gh000201","usgsCitation":"Akanda, A.S., Johnson, K.D., Ginsberg, H., and Couret, J., 2020, Prioritizing water security in the management of vector borne diseases: Lessons from Oaxaca, Mexico: Geohealth News, v. 4, no. 3, e2019GH000201, 5 p., https://doi.org/10.1029/2019gh000201.","productDescription":"e2019GH000201, 5 p.","ipdsId":"IP-112940","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":457606,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2019gh000201","text":"Publisher Index Page"},{"id":373277,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico","city":"Oaxaca","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.18505859374999,\n 16.74142754700361\n ],\n [\n -95.877685546875,\n 16.74142754700361\n ],\n [\n -95.877685546875,\n 17.403062993328923\n ],\n [\n -97.18505859374999,\n 17.403062993328923\n ],\n [\n -97.18505859374999,\n 16.74142754700361\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"4","issue":"3","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2020-03-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Akanda, Ali S","contributorId":223365,"corporation":false,"usgs":false,"family":"Akanda","given":"Ali","email":"","middleInitial":"S","affiliations":[{"id":6922,"text":"University of Rhode Island","active":true,"usgs":false}],"preferred":false,"id":784850,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Kristine D.","contributorId":168716,"corporation":false,"usgs":false,"family":"Johnson","given":"Kristine","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":784851,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ginsberg, Howard S. 0000-0002-4933-2466 hginsberg@usgs.gov","orcid":"https://orcid.org/0000-0002-4933-2466","contributorId":147665,"corporation":false,"usgs":true,"family":"Ginsberg","given":"Howard S.","email":"hginsberg@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":784849,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Couret, Janelle","contributorId":194159,"corporation":false,"usgs":false,"family":"Couret","given":"Janelle","affiliations":[],"preferred":false,"id":784852,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70208576,"text":"ofr20201017 - 2020 - Have humans influenced volcanic activity on the lower East Rift Zone of Kīlauea Volcano? A publication review","interactions":[],"lastModifiedDate":"2022-04-21T20:42:02.667167","indexId":"ofr20201017","displayToPublicDate":"2020-02-25T09:56:47","publicationYear":"2020","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":"2020-1017","displayTitle":"Have Humans Influenced Volcanic Activity on the Lower East Rift Zone of Kīlauea Volcano? A Publication Review","title":"Have humans influenced volcanic activity on the lower East Rift Zone of Kīlauea Volcano? A publication review","docAbstract":"Since the 2018 eruption of Kīlauea Volcano, the topic of whether commercial developments not only caused the eruption to occur in the lower East Rift Zone (LERZ), but also caused its high eruption rate has been a subject of public discussion. We review Kīlauea Volcano publications from the past several decades and show that the eruptive behavior of the volcano has varied and that the 2018 eruption was similar to past eruptions in many ways. We find no evidence to support any human influence on Kīlauea Volcano.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201017","usgsCitation":"Kauahikaua, J. and Trusdell, F., 2020, Have humans influenced volcanic activity on the lower East Rift Zone of Kīlauea Volcano? A publication review: U.S. Geological Survey Open-File Report 2020–1017, 17 p., https://doi.org/10.3133/ofr20201017.","productDescription":"iv, 17","numberOfPages":"17","onlineOnly":"Y","ipdsId":"IP-111187","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":372511,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1017/ofr20201017.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1017"},{"id":372510,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1017/coverthb.jpg"},{"id":399456,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109729.htm"}],"country":"United States","state":"Hawaii","otherGeospatial":"Lower East Rift Zone of Kīlauea Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.3741455078125,\n 19.19835036116298\n ],\n [\n -155.26016235351562,\n 19.281332062593734\n ],\n [\n -155.20523071289062,\n 19.26059057084779\n ],\n [\n -155.14892578125,\n 19.264479800497103\n ],\n [\n -155.0665283203125,\n 19.30466310133747\n ],\n [\n -154.9456787109375,\n 19.37334071336406\n ],\n [\n -154.82070922851562,\n 19.474360774988355\n ],\n [\n -154.80422973632812,\n 19.530024424775405\n ],\n [\n -154.92233276367188,\n 19.596019240312494\n ],\n [\n -154.9456787109375,\n 19.621892180319374\n ],\n [\n -154.97177124023438,\n 19.641294152538578\n ],\n [\n -154.97177124023438,\n 19.676211792974332\n ],\n [\n -155.050048828125,\n 19.590844152960923\n ],\n [\n -155.12832641601562,\n 19.520964205879825\n ],\n [\n -155.18875122070312,\n 19.449759112405612\n ],\n [\n -155.26565551757812,\n 19.42256346067618\n ],\n [\n -155.35629272460938,\n 19.359089245934307\n ],\n [\n -155.38787841796872,\n 19.299478713495898\n ],\n [\n -155.4071044921875,\n 19.23206673568465\n ],\n [\n -155.4071044921875,\n 19.19186565046399\n ],\n [\n -155.3741455078125,\n 19.19835036116298\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contacts, Hawaiian Volcano Observatory
U.S. Geological Survey
1266 Kamehameha Avenue, Suite A-8
Hilo, HI 96720
Biological soil crusts (biocrusts) are a central component of dryland ecosystems. However, they are highly vulnerable to disturbance and natural recovery may be slow. Therefore, finding ways to enhance the reestablishment of biocrusts after disturbance has been of great interest to researchers. This article provides a review of the laboratory cultivation and field inoculations of biocrust materials in China (mostly published in Chinese). Larger filamentous cyanobacteria (e.g. Microcoleus) are relatively easy, although slow, to grow in culture compared to other biocrust components. Thus, most researchers have focused their efforts on the cyanobacteria and a few species of mosses that are also easily grown but at smaller scale. For all the studies, a small amount of biocrust material was collected and its biomass enhanced under controlled conditions. However, the enhancement was done using various methods and techniques in different regions. These materials were then applied to disturbed field sites, again with various methods. Results show that keeping the inoculated soil surface wet for some time period after inoculation was crucial for restoration success. Cyanobacterial establishment was improved by installing automatic sprinkling using micro‐irrigation techniques and/or physical structures that reduced sediment moving onto the inoculated area. Experimental applications in China showed that cyanobacteria can be successfully inoculated at a large scale (hundreds of ha). Moss inoculation, on the other hand, was only accomplished at a small scale (several m2). To assess whether biocrust restoration can enhance the establishment of a self‐supporting ecosystem, further research is needed on how inoculation affects vegetation diversity and structure and ecological processes.
","language":"English","publisher":"Wiley","doi":"10.1111/rec.13148","usgsCitation":"Zhou, X., Zhao, Y., Belnap, J., Zhang, B., Bu, C., and Zhang, Y., 2020, Practices of biological soil crust rehabilitation in China: Experiences and challenges: Restoration Ecology, v. 28, no. S2, p. 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of model-based nitrate-loading management decision support","interactions":[],"lastModifiedDate":"2021-02-23T13:39:06.774641","indexId":"70218295","displayToPublicDate":"2020-02-25T07:36:55","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1551,"text":"Environmental Modelling and Software","active":true,"publicationSubtype":{"id":10}},"title":"A non-intrusive approach for efficient stochastic emulation and optimization of model-based nitrate-loading management decision support","docAbstract":"Use of physically-motivated numerical models like groundwater flow-and-transport models for probabilistic impact assessments and optimization under uncertainty (OUU) typically incurs such a computational burdensome that these tools cannot be used during decision making. The computational challenges associated with these models can be addressed through emulation. In the land-use/water-quality context, the linear relation between nitrate loading and surface-water/groundwater nitrate concentrations presents an opportunity for employing an efficient model emulator through the application of impulse-response matrices. When paired with first-order second-moment techniques, the emulation strategy gives rise to the “stochastic impulse-response emulator” (SIRE). SIRE is shown to facilitate non-intrusive, near-real time, and risk-based evaluation of nitrate-loading change scenarios, as well as nitrate-loading OUU subject to surface-water/groundwater concentration constraints in high decision variable and parameter dimensions. Two case studies are used to demonstrate SIRE in the nitrate-loading context.
Use of physically-motivated numerical models like groundwater flow-and-transport models for probabilistic impact assessments and optimization under uncertainty (OUU) typically incurs such a computational burdensome that these tools cannot be used during decision making. The computational challenges associated with these models can be addressed through emulation. In the land-use/water-quality context, the linear relation between nitrate loading and surface-water/groundwater nitrate concentrations presents an opportunity for employing an efficient model emulator through the application of impulse-response matrices. When paired with first-order second-moment techniques, the emulation strategy gives rise to the “stochastic impulse-response emulator” (SIRE). SIRE is shown to facilitate non-intrusive, near-real time, and risk-based evaluation of nitrate-loading change scenarios, as well as nitrate-loading OUU subject to surface-water/groundwater concentration constraints in high decision variable and parameter dimensions. Two case studies are used to demonstrate SIRE in the nitrate-loading context.
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Moore, 2020, A non-intrusive approach for efficient stochastic emulation and optimization of model-based nitrate-loading management decision support: Environmental Modeling and Software, v. 126, 104657, 11 p., https://doi.org/10.1016/j.envsoft.2020.104657.","productDescription":"104657, 11 p.","ipdsId":"IP-114822","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":383585,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"New Zealand","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 175.31982421875,\n -37.65120864327175\n ],\n [\n 175.70159912109375,\n -37.65120864327175\n ],\n [\n 175.70159912109375,\n -37.208456662000174\n ],\n [\n 175.31982421875,\n -37.208456662000174\n ],\n [\n 175.31982421875,\n -37.65120864327175\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"126","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"White, Jeremy T. 0000-0002-4950-1469","orcid":"https://orcid.org/0000-0002-4950-1469","contributorId":214251,"corporation":false,"usgs":false,"family":"White","given":"Jeremy T.","affiliations":[{"id":36277,"text":"GNS Science","active":true,"usgs":false}],"preferred":false,"id":810818,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Knowling, Matthew J.","contributorId":251909,"corporation":false,"usgs":false,"family":"Knowling","given":"Matthew","email":"","middleInitial":"J.","affiliations":[{"id":36277,"text":"GNS Science","active":true,"usgs":false}],"preferred":false,"id":810819,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fienen, Michael N. 0000-0002-7756-4651","orcid":"https://orcid.org/0000-0002-7756-4651","contributorId":245632,"corporation":false,"usgs":true,"family":"Fienen","given":"Michael N.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":810820,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Feinstein, Daniel T. 0000-0003-1151-2530 dtfeinst@usgs.gov","orcid":"https://orcid.org/0000-0003-1151-2530","contributorId":1907,"corporation":false,"usgs":true,"family":"Feinstein","given":"Daniel","email":"dtfeinst@usgs.gov","middleInitial":"T.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":810821,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McDonald, Garry W. 0000-0003-3746-4346","orcid":"https://orcid.org/0000-0003-3746-4346","contributorId":251906,"corporation":false,"usgs":false,"family":"McDonald","given":"Garry","email":"","middleInitial":"W.","affiliations":[{"id":50421,"text":"Market Economics","active":true,"usgs":false}],"preferred":false,"id":810822,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Catherine R. 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We evaluated whether suitable conditions exist in the Bering Sea for the introduction, survival, and reproduction of NIS. We compiled temperature and salinity thresholds of known NIS and compared these to ocean conditions projected during two study periods: current (2003-2012) and mid-century (2030-2039). We also explored patterns of vessel traffic and connectivity for U.S. Bering Sea ports. We found the southeastern Bering Sea had suitable conditions for the year-round survival of 80% of NIS assessed (n=42). However, only 52% of NIS had conditions suitable for reproduction or development (n=25). Conditions north of 58° N that include sub-zero winter water temperatures were unsuitable for the survival and reproduction of most NIS. While mid-century models predicted a northward expansion of suitable conditions, conditions for reproduction remained marginal. Within the highly suitable southeastern Bering Sea is the port of Dutch Harbor, which received the most vessel arrivals and ballast water discharge in the U.S. Bering Sea. Our findings illustrate the potential vulnerability of a commercially important subarctic ecosystem and highlight the need to consider NIS reproductive and developmental life phases when evaluating limits to their establishment.","language":"English","publisher":"Oxford Academic","doi":"10.1093/icesjms/fsaa014","usgsCitation":"Droghini, A., Fischbach, A., Watson, J., and Reimer, J., 2020, Regional ocean models indicate changing limits to biological invasions in the Bering Sea: ICES Journal of Marine Science, fsaa014, 11 p., https://doi.org/10.1093/icesjms/fsaa014.","productDescription":"fsaa014, 11 p.","ipdsId":"IP-106911","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":457617,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/icesjms/fsaa014","text":"Publisher Index Page"},{"id":372591,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Bering Sea","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -175.95703125,\n 52.53627304145948\n ],\n [\n -165.7177734375,\n 54.23955053156177\n ],\n [\n -158.81835937499997,\n 57.633639928856965\n ],\n [\n -162.24609375,\n 58.37867853932655\n ],\n [\n -162.4658203125,\n 60.04290359809164\n ],\n [\n -166.06933593749997,\n 60.780618803458935\n ],\n [\n -165.498046875,\n 62.71446210149774\n ],\n [\n -162.24609375,\n 63.95667333648766\n ],\n [\n -165.234375,\n 64.51064316846676\n ],\n [\n -169.27734375,\n 65.53117097417717\n ],\n [\n -171.5625,\n 63.82128765261384\n ],\n [\n -174.0234375,\n 61.543641475549954\n ],\n [\n -175.95703125,\n 52.53627304145948\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 185.88867187499997,\n 64.11060221954631\n ],\n [\n 183.8671875,\n 64.99793920061401\n ],\n [\n 181.142578125,\n 65.6582745198266\n ],\n [\n 180.791015625,\n 65.23830662451157\n ],\n [\n 179.12109374999997,\n 64.35893097894458\n ],\n [\n 178.8134765625,\n 63.68524808030715\n ],\n [\n 180.3955078125,\n 62.512317938386914\n ],\n [\n 178.505859375,\n 62.14497603754045\n ],\n [\n 176.0888671875,\n 62.04213770379758\n ],\n [\n 172.6171875,\n 61.079544234557304\n ],\n [\n 170.3759765625,\n 59.77852198502987\n ],\n [\n 169.6728515625,\n 59.84481485969105\n ],\n [\n 168.6181640625,\n 60.28340847828243\n ],\n [\n 167.255859375,\n 60.19615576604439\n ],\n [\n 165.05859375,\n 59.17592824927136\n ],\n [\n 163.828125,\n 57.938183012205315\n ],\n [\n 164.70703125,\n 56.218923189166624\n ],\n [\n 168.310546875,\n 54.7246201949245\n ],\n [\n 174.111328125,\n 53.04121304075649\n ],\n [\n 179.0771484375,\n 51.944264879028765\n ],\n [\n 185.625,\n 52.429222277955134\n ],\n [\n 185.88867187499997,\n 64.11060221954631\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2020-02-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Droghini, Amanda 0000-0001-6692-2348","orcid":"https://orcid.org/0000-0001-6692-2348","contributorId":222312,"corporation":false,"usgs":false,"family":"Droghini","given":"Amanda","email":"","affiliations":[{"id":40516,"text":"Alaska Center for Conservation Science University of Alaska Anchorage","active":true,"usgs":false}],"preferred":false,"id":783024,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fischbach, Anthony S. 0000-0002-6555-865X afischbach@usgs.gov","orcid":"https://orcid.org/0000-0002-6555-865X","contributorId":200780,"corporation":false,"usgs":true,"family":"Fischbach","given":"Anthony S.","email":"afischbach@usgs.gov","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":783023,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Watson, Jordan 0000-0002-1686-0377","orcid":"https://orcid.org/0000-0002-1686-0377","contributorId":222313,"corporation":false,"usgs":false,"family":"Watson","given":"Jordan","email":"","affiliations":[{"id":40517,"text":"NOAA Alaska Fisheries Science Center Auke Bay Laboratories","active":true,"usgs":false}],"preferred":false,"id":783026,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Reimer, Jesika","contributorId":222724,"corporation":false,"usgs":false,"family":"Reimer","given":"Jesika","email":"","affiliations":[{"id":40516,"text":"Alaska Center for Conservation Science University of Alaska Anchorage","active":true,"usgs":false}],"preferred":false,"id":783025,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70208689,"text":"ofr20201002 - 2020 - Preliminary analyses of volcanic hazards at Kīlauea Volcano, Hawai‘i, 2017–2018","interactions":[],"lastModifiedDate":"2022-04-21T20:29:39.85756","indexId":"ofr20201002","displayToPublicDate":"2020-02-24T15:31:21","publicationYear":"2020","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":"2020-1002","displayTitle":"Preliminary Analyses of Volcanic Hazards at Kīlauea Volcano, Hawaiʻi, 2017–2018","title":"Preliminary analyses of volcanic hazards at Kīlauea Volcano, Hawai‘i, 2017–2018","docAbstract":"From 2017 to 2018, the U.S. Geological Survey (USGS) Hawaiian Volcano Observatory (HVO) responded to ongoing and changing eruptions at Kīlauea Volcano as part of its mission to monitor volcanic processes, issue warnings of dangerous activity, and assess volcanic hazards. To formalize short-term hazards assessments—and, in some cases, issue prognoses for future activity—and make results discoverable to both the public and the authorities, HVO released reports online. These reports were published rapidly, received peer review under the USGS’s Fundamental Science Practice guidelines, and were intended to address a focused question posed by one or more cooperating agencies—for this reason, they were called “cooperator reports.” This Open-File Report concatenates four such products issued in 2017 and 2018 into a single publication. These reports have been reformatted and lightly edited for clarity, but the content has not otherwise been changed from the versions first publicly released.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201002","usgsCitation":"Neal, C.A., and Anderson, K.R., 2020, Preliminary analyses of volcanic hazards at Kīlauea Volcano, Hawai‘i, 2017–2018: U.S. Geological Survey Open-File Report 2020–1002, 34 p., https://doi.org/10.3133/ofr20201002.","productDescription":"iv, 34 p.","numberOfPages":"34","onlineOnly":"Y","ipdsId":"IP-114660","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":399444,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109722.htm"},{"id":372588,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1002/coverthb.jpg"},{"id":372589,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1002/ofr20201002.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Hawaii","otherGeospatial":"Kīlauea Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.3114,\n 19.1644\n ],\n [\n -154.8036,\n 19.1644\n ],\n [\n -154.8036,\n 19.4433\n ],\n [\n -155.3114,\n 19.4433\n ],\n [\n -155.3114,\n 19.1644\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Hawaiian Volcano Observatory
U.S. Geological Survey
1266 Kamehameha Avenue, Suite A-8
Hilo, HI 96720
To update and expand a part of the Federal Emergency Management Agency Flood Insurance Study, the U.S. Geological Survey, the Muskingum Watershed Conservancy District, and the Stark County Commissioners began a cooperative study. The study consisted of hydrologic and hydraulic analyses for selected reaches of 14 streams in Stark County, Ohio: Broad-Monter Creek, Chatham Ditch, East Branch Nimishillen Creek, Fairhope Ditch, Firestone Ditch, Hayden Ditch, Middle Branch Nimishillen Creek, Middle Branch Nimishillen Creek Tributary Number 1, Nimishillen Creek, Reemsnyder Ditch, Sherrick Run, unnamed stream, West Branch Nimishillen Creek, and Zimber Ditch. The study totaled nearly 50 miles of stream reaches.
Instantaneous peak streamflows for floods with 10-, 4-, 2-, 1-, and 0.2-percent and 1-percent plus annual exceedance probabilities were estimated using historical streamflow data from the streamgages Nimishillen Creek at North Industry, Ohio (U.S. Geological Survey station number 03118500), and Middle Branch Nimishillen Creek at Canton, Ohio (U.S. Geological Survey station number 03118000), regional flood regression equations, and streamflow urbanization techniques.
The annual exceedance probability streamflows were then used in a Hydrologic Engineering Center-River Analysis System step-backwater model to determine water-surface profiles, flood-inundation boundaries for the 10-, 4-, 2-, 1-, and 0.2-percent and 1-percent plus annual exceedance probability floods, and a regulatory floodway along a selected reach of each stream. Model input included DEM-derived cross sections supplemented with field surveys of open channel cross sections and hydraulic structures, field estimates of roughness values, and annual exceedance probability flood estimates from regional regression equations and historical streamflow data. Flood-inundation boundaries were mapped for the 1- and 0.2-percent annual exceedance probability floods and a regulatory floodway for each stream reach.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205011","collaboration":"Prepared in cooperation with Stark County and the Muskingum Watershed Conservancy District","usgsCitation":"Ostheimer, C.J. and Whitehead, M.T, 2020, Hydrologic and hydraulic analyses of selected streams in Stark County, Ohio: U.S. Geological Survey Scientific Investigations Report 2020–5011, 15 p., https://doi.org/10.3133/sir20205011.","productDescription":"Report: iv, 15 p.; 4 Appendixes; Data Release","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-106471","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":399632,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109726.htm"},{"id":372523,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5011/coverthb.jpg"},{"id":372525,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5011/sir20205011_appendix1.pdf","text":"Appendix 1","size":"3.09 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5011 Appendix 1","linkHelpText":"– Technical Support Data Notebook"},{"id":372526,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5011/sir20205011_appendix2.pdf","text":"Appendix 2","size":"780 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5011 Appendix 2","linkHelpText":"– Floodway data tables"},{"id":372524,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5011/sir20205011.pdf","text":"Report","size":"1.25 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5011"},{"id":372527,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5011/sir20205011_appendix3.pdf","text":"Appendix 3","size":"1.97 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5011 Appendix 3","linkHelpText":"– Water-surface profiles"},{"id":372528,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5011/sir20205011_appendix4.pdf","text":"Appendix 4","size":"8.48 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5011 Appendix 4","linkHelpText":"– Flood-inundation maps"},{"id":372529,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9YQJ8B7","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Geospatial datasets and hydraulic models for selected streams in Stark County, Ohio"}],"country":"United States","state":"Ohio","county":"Stark County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-81.0864,40.9879],[-81.0865,40.9839],[-81.0866,40.978],[-81.0869,40.9013],[-81.0873,40.728],[-81.0922,40.7285],[-81.1001,40.7281],[-81.1989,40.7292],[-81.1991,40.7224],[-81.2373,40.7237],[-81.241,40.6507],[-81.2755,40.651],[-81.2791,40.6511],[-81.304,40.6518],[-81.3173,40.6519],[-81.4372,40.6529],[-81.4365,40.6584],[-81.4395,40.6625],[-81.4467,40.6657],[-81.4589,40.6654],[-81.4675,40.6555],[-81.6489,40.6346],[-81.6491,40.6681],[-81.6483,40.7371],[-81.648,40.9145],[-81.4201,40.9064],[-81.4164,40.9889],[-81.3932,40.9887],[-81.1059,40.9882],[-81.0925,40.988],[-81.0864,40.9879]]]},\"properties\":{\"name\":\"Stark\",\"state\":\"OH\"}}]}","contact":"Director, Ohio-Kentucky-Indiana Water Science Center
U.S. Geological Survey
6460 Busch Boulevard Suite 100
Columbus, OH 43229–1737
The most upstream, pooled reach of the Klamath River in south-central Oregon, from Link River mouth to Keno Dam (Link-Keno), has a water-surface elevation that remains relatively constant throughout the year. Two model scenarios, using an existing two-dimensional hydrodynamic and water-quality model (CE-QUAL-W2), were constructed to examine the effects of lowering the water-surface elevation by 2 and 4 feet (ft) (0.61 and 1.2 meters) throughout an entire calendar year to mimic some of the potential effects of removal or modification of Keno Dam. Model results for these drawdown scenarios were analyzed for changes in velocity, travel time, water temperature, total dissolved solids, inorganic suspended sediment, nutrients, organic matter, chlorophyll a, and dissolved oxygen, compared to the base-case model. The model used in this study had been previously calibrated with the presence of aquatic plants (macrophytes). However, most model analyses were completed for model runs where macrophytes were “turned off” because the species, abundance, and distribution of macrophytes in a lowered-water scenario were all highly uncertain. For comparison, a few model scenario runs were completed with macrophytes enabled within the model. Findings from this study include the following:
Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201