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 northernmost part of the Harrat Rahat volcanic field contains early Pleistocene to Holocene mafic eruptive products within the vicinity of the city of Al Madīnah, Kingdom of Saudi Arabia. A detailed geologic investigation into the eruptive history of a 570 square kilometer (km2) area covering Al Madīnah and the surrounding area has yielded 33 mapped Quaternary volcanic units consisting of lava flows, scoria cones, and shield volcanoes. These eruptive products consist of continental, intraplate alkalic and minor transitional basalts, hawaiites, and a single mugearite that were emplaced from at least 1,014±14 thousand years ago (ka) to a single Holocene eruption in 1256 C.E. Lava flows are generally 10 to 15 kilometers (km) long (but can reach 23 km long), 1 to 3 km wide, and at least 10 meters thick. Most of the mapped units erupted episodically between 400 and 340 ka and 180 and 100 ka. Despite small individual volumes (less than 1 cubic kilometers dense rock equivalent), each unit represents eruption of a distinct magma batch that was strongly influenced by clinopyroxene, olivine, and plagioclase fractionation. Some of these units are interpreted to have undergone magma mixing pre- and (or) syneruptively. Integrating eruption ages, geochemistry, and paleomagnetic data yields evidence that some eruptions were temporally and (or) spatially clustered. Aligned scoria cones and elongate vent edifices were constructed atop fissure vent systems that reflect the local stress field, which controls dike ascent through the middle and upper crust.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1862C","collaboration":"Jointly published with the Saudi Geological Survey [as Saudi Geological Survey Special Report SGS–SP–2021–1]","usgsCitation":"Downs, D.T., Stelten, M.E., Champion, D.E., Dietterich, H.R., Hassan, K., and Shawali, J., 2023, Eruptive history within the vicinity of Al Madīnah in northern Harrat Rahat, Kingdom of Saudi Arabia, chap. C 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], 41 p., https://doi.org/10.3133/pp1862C.","productDescription":"Report: vii, 41 p.; Data Release","numberOfPages":"41","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-104009","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":423975,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91HL91C","text":"USGS data release","linkHelpText":"Major and trace-element chemical analyses of rocks from the northern Harrat Rahat volcanic field and surrounding area, Kingdom of Saudi Arabia"},{"id":423974,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1862/c/pp1862c.pdf","text":"Report","size":"13.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1862-C"},{"id":423973,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1862/c/coverthbc.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 37.797830302240726,\n 26.450894948969335\n ],\n [\n 37.797830302240726,\n 23.09993673871402\n ],\n [\n 41.6650178022403,\n 23.09993673871402\n ],\n [\n 41.6650178022403,\n 26.450894948969335\n ],\n [\n 37.797830302240726,\n 26.450894948969335\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, 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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":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":374,"text":"Maryland 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}]}} ,{"id":70250964,"text":"70250964 - 2023 - Bedform distributions and dynamics in a large, channelized river: Implications for benthic ecological processes","interactions":[],"lastModifiedDate":"2024-01-17T13:13:13.793676","indexId":"70250964","displayToPublicDate":"2023-12-29T07:09:57","publicationYear":"2023","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Bedform distributions and dynamics in a large, channelized river: Implications for benthic ecological processes","docAbstract":"Sand bedforms are fundamental habitat elements for benthic fish in large, sand-bedded rivers and are hypothesized to provide flow refugia, food transport, and ecological disturbance. We explored bedform distributions and dynamics in the Lower Missouri River, Missouri, with the objective of understanding the implications of these features for benthic fish habitat, particularly for the endangered pallid sturgeon (Scaphirhynchus albus) and shovelnose sturgeon (Scaphirhynchus platorynchus) during their early life stages. We mapped bathymetry in a 3-kilometer-long reach of the highly engineered Lower Missouri River 22 times over a three-year period from 2019-2021 using a multibeam echosounder. Surveys included precise water surface and bed elevations over discharges ranging from 1,360-8,550 cubic meters per second. This included weekly surveys during a large flood event with a peak of 9,290 cubic meters per second in the spring and summer of 2019. Velocity was mapped with an acoustic Doppler current profiler during 11 of the 22 multibeam surveys. The dataset illustrates how bedforms are distributed in a typical Missouri River reach and how they evolve with changes in discharge. We measured a variety of bedform characteristics, including height, length, lee-slope angle, and crest orientation, and examined their relationship to larval sturgeon catch in the reach in 2020\nand 2021. Bedform shapes are controlled by depositional environment and discharge and range in size from less than a meter in wavelength and amplitude to greater than 4 meters high and 75 meters long and generally have low angle lee-slopes. Small dunes were located in lower velocity regions on the inside of a bend and behind wing-dikes, as well as superimposed on larger dunes. Larger dunes were generally located in the channel thalweg and were associated with higher flow velocities. However, bedform size did not necessarily scale with discharge over the course of the 2019 flood, possibly due to sediment supply limitations and hysteresis effects. Changes in bedform size over the course of the flood event were most pronounced in the thalweg; less change in bedform size occurred behind wing dikes on the inside of channel bends, indicating some degree of habitat stability. Despite rarely getting caught in the thalweg, larval sturgeon drift in the thalweg until they are intercepted into off-channel habitats in wing dike fields, where they are caught in much higher numbers. Bedform orientations were affected by flow expansion around wing dikes, indicative of the role of wing dikes in influencing exchange of material between the thalweg and channel margins. Increased understanding of bedform distributions and dynamics will inform future sampling and habitat restoration designs for\nlarval pallid sturgeon and contribute to increased understanding of their influence on benthic\necological processes.","language":"English","publisher":"SEDHYD","usgsCitation":"Elliott, C.M., Jacobson, R., Call, B., and Roberts, M.O., 2023, Bedform distributions and dynamics in a large, channelized river: Implications for benthic ecological processes, 15 p.","productDescription":"15 p.","ipdsId":"IP-148167","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":424489,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":424463,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.sedhyd.org/past/2023Proceedings/110.pdf"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Elliott, Caroline M. 0000-0002-9190-7462 celliott@usgs.gov","orcid":"https://orcid.org/0000-0002-9190-7462","contributorId":2380,"corporation":false,"usgs":true,"family":"Elliott","given":"Caroline","email":"celliott@usgs.gov","middleInitial":"M.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":892488,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jacobson, R. B. 0000-0002-8368-2064","orcid":"https://orcid.org/0000-0002-8368-2064","contributorId":92614,"corporation":false,"usgs":true,"family":"Jacobson","given":"R. B.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":892489,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Call, Bruce 0000-0001-9064-2231","orcid":"https://orcid.org/0000-0001-9064-2231","contributorId":217707,"corporation":false,"usgs":true,"family":"Call","given":"Bruce","email":"","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":892490,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Roberts, Maura O 0000-0002-5575-0330","orcid":"https://orcid.org/0000-0002-5575-0330","contributorId":291406,"corporation":false,"usgs":true,"family":"Roberts","given":"Maura","email":"","middleInitial":"O","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":892695,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70252921,"text":"70252921 - 2023 - Sea-ice conditions predict polar bear land use around military installations in Alaska","interactions":[],"lastModifiedDate":"2024-04-11T12:06:38.792532","indexId":"70252921","displayToPublicDate":"2023-12-29T07:02:27","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1914,"text":"Human-Wildlife Interactions","active":true,"publicationSubtype":{"id":10}},"title":"Sea-ice conditions predict polar bear land use around military installations in Alaska","docAbstract":"Polar bears (Ursus maritimus) are threatened by sea-ice loss due to climate change, which is concurrently opening the Arctic to natural resource extraction and a broader scope of national security responsibilities. Mitigating the risk of human–bear conflicts is an emerging challenge as many polar bears spend longer ice-free summers on land where they have limited access to food and come into more frequent contact with people. We investigated a suite of physical and ecological variables that influence the timing of polar bear arrival on, and departure from, land using remote-sensing data on sea-ice extent and satellite telemetry data from 72 radio-collared adult female polar bears from 1986 to 2015. Analyses encompassed the coastline of the Southern Beaufort Sea north of Alaska, USA, and focused on zones within a 35-km radius (mean daily travel distance of a polar bear) of 5 military installations. Sea ice in the Southern Beaufort Sea retreated approximately 1 month earlier in spring, and reformed 1 month later in fall, in 2015 compared to 1979. In generalized linear mixed models, the most important predictors of polar bear arrival and departure were the dates of sea-ice breakup and formation, respectively, in localized marine areas surrounding each military zone. Region-wide sea-ice conditions also influenced land use, although to a lesser extent. We found that polar bears spent longer periods on land in the military zones compared to outside the zones, which may reflect increased land use in areas with human activity and potential attractants (noting that some military installations were in proximity to other human settlements). Our results demonstrate that the timing of polar bear land use in northern Alaska is influenced by sea-ice conditions on multiple spatial scales. This information can be used to predict and manage the presence of polar bears around military installations and other places of interest.
The Puget Sound basin encompasses the 13,700-square-mile area that drains to the Puget Sound and the adjacent marine waters of Washington State. Well more than 4 million people live within the basin, with numbers continuing to increase, who rely on the basin’s natural resources including groundwater. The Puget Sound Partnership was created by a Washington State statute to implement a science-based recovery of the Puget Sound to help address impacts to these resources. As part of the recovery, the partnership developed the Puget Sound Vital Signs as measures of ecosystem health that guide the assessment of progress toward Puget Sound recovery goals. The Puget Sound Partnership Leadership Council adopted a Drinking Water Vital Sign associated with human health and quality of life, recognizing certain indicators as integral to the sustainability of Puget Sound recovery efforts. One such Vital Sign indicator was the vulnerability of groundwater throughout the aquifers of the Puget Sound basin to elevated nitrate concentrations as defined by the probability of exceeding 2 milligrams/liter (mg/L) at a specific location and well depth. The U.S. Geological Survey (USGS) led the effort to characterize groundwater vulnerability. For this study, groundwater vulnerability refers to a probability with which a contaminant applied at or near the land surface can migrate to the aquifer of interest for a given set of land-use practices. Nitrate concentration data were selected for evaluation because elevated nitrate concentrations are typically caused by anthropogenic activities and have been associated with deleterious impacts on human health.
To identify groundwater vulnerability to elevated nitrate concentrations, logistic regression was used to relate anthropogenic (human associated) and natural variables to the occurrence of elevated nitrate concentrations in untreated groundwater from large public water supply system wells found within the Washington State Department of Health Sentry database. Variables that were analyzed included well depth, soil hydraulic conductivity, precipitation, population density, fertilizer application amounts, and land-use types. Statistically significant models that predicted the probabilities of groundwater nitrate concentrations greater than 2 mg/L based on the predictor variables were created for the time periods 2000–04, 2005–09, 2010–14, and 2015–19. For all time periods, well depth and a measure of the abundance of urban and agricultural land over or near the well consistently helped explain the vulnerability of the well to elevated nitrate concentrations defined as a probability of exceeding 2 mg/L of nitrate. Precipitation and (or) soil hydraulic conductivity were also important predictor variables in the models.
The models for each time period were used to create maps of groundwater vulnerability at 150- and 300-foot depths throughout the Puget Sound basin. As expected, the most vulnerable locations were associated with shallower well depths and increased agriculture and urban land cover. Across all four time periods, groundwater vulnerability throughout the Puget Sound was low, with probabilities of exceeding 2 mg/L concentrations of nitrate at depths at 150 and 300 feet typically less than 50 percent. Results also found a slight decrease in probabilities of elevated nitrate concentrations throughout the basin over time. More specifically, additional statistical tests found that groundwater with probabilities of less than about 60 percent declined from 2000 to 2019 and represented more than 75 percent of the modeled Puget Sound basin aquifer. Wells with greater than 60 percent probability increased over the same time period but represented only about 25 percent of the aquifer. The maps and statistical analysis presented in the study provide valuable and informative evaluation of the vulnerability of groundwater in the Puget Sound basin to elevated nitrate concentrations. The probability maps do not represent measured nitrate concentrations in groundwater, but rather they present the probability that nitrate concentrations exceed 2 mg/L. The models and predictions from this study are a viable indicator for the Puget Sound Partnership’s Healthy Human Population—Drinking Water Vital Sign. The logistic regression modeling approach presented here benefits water managers by allowing them to assess temporal trends in a range of probabilities, explore vulnerability changes as new regional land cover and anthropogenic data are generated, and distinguish vulnerabilities at different depths within the aquifer.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235117","collaboration":"Prepared in cooperation with Puget Sound Partnership","usgsCitation":"Black, R.W., Wright, E.E., Bright, V.A.L., and Headman, A.O., 2023, Prediction of the probability of elevated nitrate concentrations at groundwater depths used for drinking-water supply in the Puget Sound basin, Washington, 2004–19: U.S. Geological Survey Scientific Investigations Report 2023–5117, 40 p., https://doi.org/10.3133/sir20235117.","productDescription":"Report: vi, 40 p.; Data Release","numberOfPages":"40","onlineOnly":"Y","ipdsId":"IP-135130","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":424530,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5117/images"},{"id":424531,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5117/sir20235117.XML"},{"id":423904,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5117/covrthb.jpg"},{"id":423905,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5117/sir20235117.pdf","text":"Report","size":"16 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5117"},{"id":501157,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115891.htm","linkFileType":{"id":5,"text":"html"}},{"id":423906,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9TOWGYM","text":"USGS Data Release","description":"Wright, E.E., Bright, V.A.L., Black, R.W., and Headman, A.O., 2022, Index of vulnerability for elevated nitrates in groundwater in the Puget Sound Basin, Washington, 2000–2019: U.S. Geological Survey data release, https://doi.org/10.5066/P9TOWGYM.","linkHelpText":"Index of vulnerability for elevated nitrates in groundwater in the Puget Sound Basin, Washington, 2000–2019"},{"id":424529,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235117/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2023-5117"}],"country":"United States","state":"Washington","otherGeospatial":"Puget Sound basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -124.38747179984844,\n 49.222164372548065\n ],\n [\n -124.38747179984844,\n 46.31382574682385\n ],\n [\n -120.38844836234833,\n 46.31382574682385\n ],\n [\n -120.38844836234833,\n 49.222164372548065\n ],\n [\n -124.38747179984844,\n 49.222164372548065\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director,
Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402
The entire Lower Fox River and inner bay of Green Bay, in northeastern Wisconsin, have been listed as impaired by the Wisconsin Department of Natural Resources (WDNR) for low dissolved oxygen and degraded habitat, with total phosphorus (TP) and total suspended solids (TSS) concentrations listed as the likely causes of these impairments. To restore the Fox River and Green Bay, total maximum daily loads (TMDLs) were developed for TP and TSS, and actions were taken throughout the Fox River Basin to improve water quality. In this study, we estimated concentrations and loads of TP, dissolved phosphorus (DP), and TSS at the Lake Winnebago outlet, De Pere, and the mouth of the Fox River from water year (WY) 1989 to WY 2021; described changes in concentrations and loads through time during this period; and compared the concentrations and loads for the most recent 5-year period (WYs 2017–21) with the WDNR criteria for TP impairment and the TMDL loading goals.
TP, DP, TSS, and total suspended sediment concentration data were obtained from NEW Water (the brand of the Green Bay Metropolitan Sewerage District), the WDNR, and the U.S. Geological Survey and combined into one dataset. All the TSS and total suspended sediment data were used together with no adjustment factor and are referred to as simply “TSS.” During WYs 1989–2021, mean annual TP concentrations increased from 0.089 milligram per liter (mg/L) at the Lake Winnebago outlet to 0.128 mg/L at the mouth of the Fox River, and concentrations decreased at all three sites from WY 1989 to WY 2021. The most recent (WYs 2017–21) median May–October TP concentrations were just less than the 0.1-mg/L WDNR criterion for TP impairment at the two upstream sites (Lake Winnebago outlet and De Pere) but were slightly greater than the criterion for impairment at the mouth of the Fox River. Mean annual DP concentrations increased from 0.024 mg/L at the Lake Winnebago outlet to 0.036 mg/L at the mouth of the Fox River. DP concentrations increased from WY 1989 to WY 2021 at the Lake Winnebago outlet but not at the other sites. Mean annual TSS concentrations increased from 13.5 mg/L at the Lake Winnebago outlet to 23.9 mg/L at the mouth of the Fox River and have decreased at all three sites from WY 1989 to WY 2021. The recent median May–October TSS concentrations were less than the 20-mg/L WDNR criterion for impairment at all three sites. Streamflow and TP, DP, and TSS loads increased from the Lake Winnebago outlet to the mouth of the Fox River (TP loads increased from 360,000 to 557,000 kilograms per year [kg/yr], DP loads increased from 114,000 to 162,000 kg/yr, and TSS loads increased from 60,400 metric tons per year [t/yr] to 122,600 t/yr).
At the Lake Winnebago outlet, DP concentrations and TP and DP loads increased from WY 1989 to WY 2021 because of an increase in DP concentrations in Lake Winnebago resulting from the lake becoming nitrogen limited as a result of biological processes not consuming the DP in the lake and an increase in streamflow leaving the lake. Although TP and TSS concentrations decreased at De Pere and the mouth of the Fox River, there was little change in the loading because of an increase in flow. Flow-normalized TP and TSS loads at De Pere and the mouth of the Fox River decreased possibly because of implementation of agricultural conservation management practices, reductions in point-source discharges in its drainage basin, and deposition of sediment and phosphorus in recently dredged areas of the Lower Fox River. Additional studies are needed to determine the relative importance of each of these actions and whether the decrease in concentrations and flow-normalized loads will continue to be observed in the Fox River.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235112","collaboration":"Prepared in cooperation with NEW Water, the brand of the Green Bay Metropolitan Sewerage District","usgsCitation":"Robertson, D.M., Diebel, M.W., Bartlett, S.L., and Fermanich, K.J., 2023, Changes in phosphorus and suspended solids loading in the Fox River, northeastern Wisconsin, 1989–2021: U.S. Geological Survey Scientific Investigations Report 2023–5112, 29 p., https://doi.org/10.3133/sir20235112","productDescription":"Report: viii, 29 p.; Data Release; Dataset","numberOfPages":"42","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-150822","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":423702,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5112/sir20235112.XML"},{"id":423701,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5112/sir20235112.pdf","text":"Report","size":"3.29 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023–5112"},{"id":423700,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5112/coverthb.jpg"},{"id":423703,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5112/images/"},{"id":501154,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115890.htm","linkFileType":{"id":5,"text":"html"}},{"id":423706,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235112/full"},{"id":423705,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":423704,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P950EOGH","text":"USGS data release","linkHelpText":"Concentrations and loads of phosphorus and suspended solids in the Fox River, northeastern Wisconsin, 1989–2021"}],"country":"United States","state":"Wisconsin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -90.27750277664309,\n 45.85677045828476\n ],\n [\n -90.27750277664309,\n 43.06901481985196\n ],\n [\n -87.32441235531145,\n 43.06901481985196\n ],\n [\n -87.32441235531145,\n 45.85677045828476\n ],\n [\n -90.27750277664309,\n 45.85677045828476\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Upper Midwest Water Science Center
U.S. Geological Survey
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Conservation of the American Goshawk (Accipiter atricapillus; hereafter goshawk) has been contentious in relation to forest management. Higher quality goshawk nesting habitat is generally considered to consist of contiguous tracts of mature forest, due to goshawks' large home ranges, territoriality, and food requirements. The large trees of mature forest have the greatest economic value to timber companies. We used long-term (1965–2019) data from 281 goshawk nest site locations in the Black Hills National Forest (BHNF), South Dakota, and Wyoming, USA, to evaluate (1) abiotic and biotic factors associated with goshawk nest site habitat suitability (hereafter habitat suitability); (2) changes in habitat suitability over time; and (3) the effect of anthropogenic activities and natural disturbances on habitat suitability. We evaluated forest attributes across five spatial scales relevant to goshawks, used information-theoretic methods to rank and select models, and assessed the predictive capability of the best-approximating models using the concordance statistic. The best-approximating model had excellent predictive capability (concordance = 0.821). Forest attributes at the 12-ha scale were a better predictor of goshawk habitat suitability than covariates evaluated at the point or >12-ha scales, indicating the importance of managing goshawk habitat beyond the nest tree, but within the nest stand. Goshawk habitat suitability was positively related to mean percent canopy cover and median canopy base height, and negatively related to variability in canopy base height within 12 ha of the location. As mean percent canopy cover within 12 ha of a location increased, goshawk habitat suitability increased more slowly in burned compared to unburned areas. Commercial thinning treatments were more likely to occur in closed canopy forest that already had a higher likelihood of goshawk nesting, and we documented a positive relationship between habitat suitability and the interaction of canopy cover with commercial thinning. Goshawk habitat suitability was negatively related to slope and distance to drainage bottoms, and positively related to distance to ridges, which may be related to microclimatic factors. Our results indicate goshawk habitat suitability decreased across the BHNF over the past three decades and much high-quality nesting habitat was lost during this period due to a combination of unsustainable timber harvest and natural disturbances. Minimizing forest management activities that decrease canopy cover and canopy base height, and increase variability in canopy base height in areas of high- and medium-quality goshawk habitat are likely to slow the loss of higher-quality habitat and allow development of future nesting habitat. In addition to informing management, this study demonstrates the value of using existing long-term legacy datasets in conjunction with time series of remotely sensed habitat attributes to evaluate changes in habitat suitability for raptors in heavily managed landscapes with extensive natural disturbances.
","language":"English","publisher":"The Raptor Research Foundation, Inc.","doi":"10.3356/JRR-22-116","usgsCitation":"Bruggeman, J., Kennedy, P., Andersen, D.E., Deisch, S., and Dowd Stukel, E., 2023, Declining American Goshawk (Accipiter atricapillus) nest site habitat suitability in a timber production landscape: Effects of abiotic, biotic, and forest management factors: Journal of Raptor Research, v. 57, no. 4, p. 595-616, https://doi.org/10.3356/JRR-22-116.","productDescription":"22 p.","startPage":"595","endPage":"616","ipdsId":"IP-131063","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":433252,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"South Dakota, Wyoming","otherGeospatial":"Black Hills National Forest","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -103.43693855745735,\n 43.356145430824284\n ],\n [\n -103.2453110990768,\n 43.65127660509563\n ],\n [\n -103.28799233163049,\n 44.184936790000336\n ],\n [\n -103.5682101102287,\n 44.47034928011246\n ],\n [\n -104.02419632305251,\n 44.568539246903015\n ],\n [\n -104.35190822302025,\n 44.83186690058787\n ],\n [\n -104.60789383129,\n 44.58876639683757\n ],\n [\n -104.61727412202488,\n 44.439874040779614\n ],\n [\n -104.32767875182326,\n 44.24995062651524\n ],\n [\n -104.05715060176854,\n 44.1638696947999\n ],\n [\n -104.03414949657513,\n 43.9000787982707\n ],\n [\n -103.98071548762339,\n 43.5157370272095\n ],\n [\n -103.75626279313133,\n 43.3596577295468\n ],\n [\n -103.43693855745735,\n 43.356145430824284\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"57","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bruggeman, Jason E.","contributorId":342294,"corporation":false,"usgs":false,"family":"Bruggeman","given":"Jason E.","affiliations":[{"id":81853,"text":"Beartooth Wildlife Research LLC","active":true,"usgs":false}],"preferred":false,"id":909974,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kennedy, Patricia L.","contributorId":342295,"corporation":false,"usgs":false,"family":"Kennedy","given":"Patricia L.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":909975,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Andersen, David E. 0000-0001-9535-3404 dea@usgs.gov","orcid":"https://orcid.org/0000-0001-9535-3404","contributorId":199408,"corporation":false,"usgs":true,"family":"Andersen","given":"David","email":"dea@usgs.gov","middleInitial":"E.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":909973,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Deisch, Shelly","contributorId":342296,"corporation":false,"usgs":false,"family":"Deisch","given":"Shelly","email":"","affiliations":[{"id":56698,"text":"South Dakota Department of Game, Fish, and Parks","active":true,"usgs":false}],"preferred":false,"id":909976,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dowd Stukel, Eileen","contributorId":342297,"corporation":false,"usgs":false,"family":"Dowd Stukel","given":"Eileen","email":"","affiliations":[{"id":56698,"text":"South Dakota Department of Game, Fish, and Parks","active":true,"usgs":false}],"preferred":false,"id":909977,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70251309,"text":"70251309 - 2023 - Winter distribution of golden eagles in the Eastern USA","interactions":[],"lastModifiedDate":"2024-02-03T15:20:51.605387","indexId":"70251309","displayToPublicDate":"2023-12-27T09:13:00","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2442,"text":"Journal of Raptor Research","active":true,"publicationSubtype":{"id":10}},"title":"Winter distribution of golden eagles in the Eastern USA","docAbstract":"Golden Eagles (Aquila chrysaetos) have a Holarctic distribution, but some details of that overall distribution are poorly understood, including parts of the range in eastern North America. Recent studies in the region suggest that Golden Eagles may be more widely distributed than previously recognized. For species specific conservation efforts to be effective, an understanding of the distribution of the species is essential. Thus, the goal of this study was to map the winter distribution of Golden Eagles in the eastern half of the USA. To accomplish this, we reviewed and compiled 11,981 Golden Eagle records from eight data sources, including literature and ornithology records, community science data, survey data, and telemetry data. We found that Golden Eagles were observed in winter in each of the 31 states that lie completely east of the 100th meridian and in 1244 of the 2045 counties (61%) in those states. The proportion of counties with records varied by physiographic province, with higher proportions in physiographic provinces with more rugged terrain and greater forest cover. Our study shows that Golden Eagles are more widely distributed during winter in eastern USA states than was previously recognized. This work provides an important foundation for future management and research at a time when threats to this species are expanding rapidly on the landscape.
","language":"English","publisher":"BioOne","doi":"10.3356/JRR-23-00012","usgsCitation":"Miller, T., Lanzone, M., Braham, M., Adam Duerr, Cooper, J., Somershoe, S., Hanni, D., Soehren, E.C., Threadgill, C., Maddox, M., Stober, J., Kelly, C.A., Salo, T., Berry, A., Martell, M., Mehus, S., Dirks, B., Sargent, R., and Katzner, T., 2023, Winter distribution of golden eagles in the Eastern USA: Journal of Raptor Research, v. 57, no. 4, p. 522-532, https://doi.org/10.3356/JRR-23-00012.","productDescription":"11 p.","startPage":"522","endPage":"532","ipdsId":"IP-151100","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":425370,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 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Robert","contributorId":288449,"corporation":false,"usgs":false,"family":"Sargent","given":"Robert","email":"","affiliations":[],"preferred":false,"id":894068,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Katzner, Todd E. 0000-0003-4503-8435 tkatzner@usgs.gov","orcid":"https://orcid.org/0000-0003-4503-8435","contributorId":191353,"corporation":false,"usgs":true,"family":"Katzner","given":"Todd E.","email":"tkatzner@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":894069,"contributorType":{"id":1,"text":"Authors"},"rank":19}]}} ,{"id":70243946,"text":"sir20235051 - 2023 - Automated construction of Streamflow-Routing networks for MODFLOW—Application in the Mississippi Embayment region","interactions":[],"lastModifiedDate":"2023-12-23T14:28:31.061588","indexId":"sir20235051","displayToPublicDate":"2023-12-22T15:44:25","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-5051","displayTitle":"Automated Construction of Streamflow-Routing Networks for MODFLOW—Application in the Mississippi Embayment Region","title":"Automated construction of Streamflow-Routing networks for MODFLOW—Application in the Mississippi Embayment region","docAbstract":"In humid regions with dense stream networks, surface water exerts a fundamental control on the water levels and flow directions of shallow groundwater. Understanding interactions between groundwater and surface water is critical for managing groundwater resources and groundwater-dependent ecosystems. Representing streams in groundwater models has historically been arduous and error prone. In recent years, however, all the information needed to numerically describe stream boundary conditions for a model area has become readily available online, as have robust open-source software tools for translating that information to a model grid. The SFRmaker Python package leverages geospatial capabilities in the scientific Python ecosystem to robustly automate the production of input to the Streamflow-Routing (SFR) Package of MODFLOW from the National Hydrography Dataset Plus or other hydrography data. This report documents an application of SFRmaker to automate production of SFR Package input for groundwater models within the Mississippi Embayment Regional Aquifer Study area. SFR Package input was developed in three steps: (1) preprocessing to develop a single set of grid-independent flowlines from National Hydrography Dataset Plus version 2 data; (2) setting up the SFR package from the preprocessed flowlines, and (3) correcting streambed top elevations after an initial model run. Separating the hydrography preprocessing from the construction of SFR Package input was advantageous in that it minimized the need to repeat computationally expensive geoprocessing (thereby speeding model construction) and also allowed for the curation of a single set of grid-independent SFR input data that can be used for any MODFLOW model within the study area.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235051","usgsCitation":"Leaf, A.T., 2023, Automated construction of Streamflow-Routing networks for MODFLOW—Application in the Mississippi Embayment region: U.S. Geological Survey Scientific Investigations Report 2023–5051, 28 p., https://doi.org/10.3133/sir20235051.","productDescription":"Report: vii, 28 p.; 4 Data Releases; Dataset","numberOfPages":"40","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-105069","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":417495,"rank":9,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P971LPOB","text":"USGS data release","linkHelpText":"MODFLOW–6 models of the Mississippi embayment (MERAS 3) and Mississippi Delta"},{"id":417456,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9CXDIPL","text":"USGS data release","linkHelpText":"Datasets used to map the potentiometric surface, Mississippi River Valley alluvial aquifer, spring 2020"},{"id":423683,"rank":12,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20235100","text":"SIR 2023–5100","linkHelpText":"—Simulating groundwater flow in the Mississippi Alluvial Plain with a focus on the Mississippi Delta"},{"id":417488,"rank":8,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5051/images"},{"id":417481,"rank":7,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5051/sir20235051.XML","text":"Report","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2023–5051"},{"id":417457,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":423682,"rank":11,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20235080","text":"SIR 2023–5080","linkHelpText":"—Updated estimates of water budget components for the Mississippi embayment region using a Soil-Water-Balance model, 2000–2020"},{"id":417455,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7P84B24","text":"USGS data release","linkHelpText":"National-scale grid to support regional groundwater availability studies and a national hydrogeologic database"},{"id":423152,"rank":10,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235051/full"},{"id":417450,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5051/coverthb2.jpg"},{"id":417454,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WQPRFB","text":"USGS data release","linkHelpText":"Waterborne resistivity inverted models, Mississippi Alluvial Plain, 2016–2018"},{"id":417451,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5051/sir20235051.pdf","text":"Report","size":"46.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023–5051"}],"country":"United States","otherGeospatial":"Mississippi Embayment Region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -94.88995719655937,\n 28.910338985045087\n ],\n [\n -85.96905875905937,\n 28.910338985045087\n ],\n [\n -85.96905875905937,\n 37.74314338343309\n ],\n [\n -94.88995719655937,\n 37.74314338343309\n ],\n [\n -94.88995719655937,\n 28.910338985045087\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Upper Midwest Water Science Center
U.S. Geological Survey
1 Gifford Pinchot Drive
Madison, WI 53726
The Mississippi Alluvial Plain has become one of the most important agricultural regions in the United States but relies heavily on groundwater for irrigation. On average, more than 12 billion gallons are withdrawn daily from the Mississippi River Valley alluvial aquifer. Declining groundwater levels, especially in the Delta region of northwest Mississippi and the Cache and Grand Prairie regions of eastern Arkansas, have led to concerns about future sustainability. The U.S. Geological Survey Mississippi Alluvial Plain Project is focused on quantifying the groundwater system in the alluvial plain and the response of groundwater resources to future development. A key objective of the project is to provide updated groundwater flow models supported by extensive data collection and analyses. MODFLOW 6, PEST++, and several open-source python packages were used to develop a simplified, faster running version of the Mississippi Embayment Regional Aquifer Study model that can provide boundary conditions for local inset models, including the Mississippi Delta model described in this report. An automated workflow was used for model construction, history matching, and development of baseline future climate scenarios. The models incorporate information from a Soil-Water-Balance code simulation of the terrestrial water balance, metering-based estimates of water use from thousands of wells, measured and estimated streamflow and stages, and the largest airborne electromagnetic survey flown to date in the United States. Baseline scenarios for the Mississippi Delta under potential future climates were constructed using recharge, surface runoff and irrigation pumping forcings from a future version of the Soil-Water-Balance model, driven by downscaled temperature and precipitation output from 10 general circulation model simulations, including high and moderate carbon emissions pathways.
Results indicate a complex water balance that varies in time and space in terms of the terrestrial recharge, stream leakage, and regional groundwater flow components, which are affected by seasonal forcings, human activity, and alluvial geomorphology. The general circulation model outputs indicate a continued rise in average temperatures but no clear precipitation trend. Increased crop water demand is anticipated from the higher temperatures, resulting in increased irrigation withdrawals to sustain current levels of irrigated agriculture. Simulated drawdowns in groundwater levels at the mid-21st century vary greatly. Under moderate or wet climate scenarios, and in parts of the aquifer that are well connected to surface water, little to no additional drawdown is anticipated. Under dry or warm scenarios, drawdowns of as much as 10 meters or more are possible in parts of the aquifer that are relatively disconnected from surface water. Under dry or warm scenarios, the portion of the Delta with greater than 60 feet of saturated thickness could be reduced from near 100 percent currently (2018) to 80–90 percent by mid-century. Future simulations with the model could include alternative management scenarios to identify options for improving groundwater sustainability. The automated model construction workflows are designed to facilitate regular updating, making this a “living” framework that the Mississippi Department of Environmental Quality and other stakeholders can use for adaptive management going forward.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235100","programNote":"Water Use and Availability Science Program","usgsCitation":"Leaf, A.T., Duncan, L.L., Haugh, C.J., Hunt, R.J., and Rigby, J.R., 2023, Simulating groundwater flow in the Mississippi Alluvial Plain with a focus on the Mississippi Delta: U.S. Geological Survey Scientific Investigations Report 2023–5100, 143 p., https://doi.org/10.3133/sir20235100.","productDescription":"Report: viii, 143 p.; 4 Data Releases","numberOfPages":"156","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-135342","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":423184,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P971LPOB","text":"USGS data release","linkHelpText":"MODFLOW 6 models for simulating groundwater flow in the Mississippi Embayment with a focus on the Mississippi Delta"},{"id":423183,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5100/images/"},{"id":501149,"rank":12,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115886.htm","linkFileType":{"id":5,"text":"html"}},{"id":423188,"rank":9,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235100/full"},{"id":423187,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P97KK17G","text":"USGS data release","linkHelpText":"Model archive and output files for net infiltration, runoff, and irrigation water use for the Mississippi Embayment Regional Aquifer System, 2000 to 2020, simulated with the Soil-Water-Balance model"},{"id":423186,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9BC6UB8","text":"USGS data release","linkHelpText":"Soil-Water-Balance forecasted climate model output for simulations of water budget components in the Mississippi Embayment Regional Aquifer System, 2020 to 2055"},{"id":423185,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9TSDEAC","text":"USGS data release","linkHelpText":"Digital surfaces and site data of well-screen top and bottom altitudes defining the irrigation production zone of the Mississippi River Valley alluvial aquifer within the Mississippi Alluvial Plain project region"},{"id":423182,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5100/sir20235100.XML"},{"id":423181,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5100/sir20235100.pdf","text":"Report","size":"59.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023–5100"},{"id":423180,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5100/coverthb.jpg"},{"id":423680,"rank":10,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20235051","text":"SIR 2023–5051","linkHelpText":"—Automated construction of Streamflow-Routing networks for MODFLOW—Application in the Mississippi Embayment region"},{"id":423681,"rank":11,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20235080","text":"SIR 2023–5080","linkHelpText":"—Updated estimates of water budget components for the Mississippi embayment region using a Soil-Water-Balance model, 2000–2020"}],"country":"United States","state":"Arkansas, Louisiana, Mississippi","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -92.14337516530937,\n 32.22047635687272\n ],\n [\n -89.39679313405937,\n 32.22047635687272\n ],\n [\n -89.39679313405937,\n 35.046419541331645\n ],\n [\n -92.14337516530937,\n 35.046419541331645\n ],\n [\n -92.14337516530937,\n 32.22047635687272\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Upper Midwest Water Science Center
U.S. Geological Survey
1 Gifford Pinchot Drive
Madison, WI 53726
A Soil-Water-Balance (SWB) model for the Mississippi embayment region in Arkansas, Tennessee, Mississippi, and Louisiana was constructed and calibrated to gain insight into potential recharge patterns for the Mississippi River Valley alluvial aquifer, which has had substantial drawdown under intense pumping stress over the last several decades. An analysis of the net infiltration term from the SWB model combined with newly gathered airborne electromagnetic geophysical data on the surficial sediments in a calibrated modular three-dimensional finite-difference (MODFLOW 6) groundwater flow model of one area in the alluvial plain found that the distribution of net infiltration was significantly different from the recharge that gets to the water table through the complicated silt and clay stratigraphy of the unsaturated zone. The net infiltration of water through the rooting zone as simulated by SWB ranges from 5.7 to 12.3 inches per year in the alluvial plain part of the model domain, and is fairly evenly distributed within local areas. Recharge to the underlying aquifer is less and is much more focused in particular zones where the connectivity through the upper layers of the unsaturated zone above the water table is greater, indicating possible horizontal flow and perched water table conditions in the unsaturated zone. Runoff and net infiltration together account for 32 percent of the incoming precipitation overall and somewhat higher percentages in the alluvial plain area on an annual basis. These terms are much higher in the fall and winter than in the summer. Actual evapotranspiration accounts for between 62 and 72 percent on average of the annual precipitation but dominates all other terms in the summer months. Without irrigation, summertime net infiltration and runoff would be near zero in the crop-dominated alluvial plain area. The SWB model reproduced reported irrigation rates for corn, soybeans, rice, and cotton on an annual basis fairly well. The SWB model for the Mississippi embayment region was calibrated using more than 15,000 observations representing four parts of the calculated water budget: actual evapotranspiration, surface runoff, net infiltration, and irrigation. Using a Monte Carlo approach to determine the uncertainty in the model results stemming from the uncertainty in the model parameters used in the calibration, the uncertainty in the annual actual evapotranspiration values was around 5 percent, whereas the uncertainty in the irrigation, net infiltration, and runoff was around 20 percent.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235080","programNote":"Water Availability and Use Science Program","usgsCitation":"Nielsen, M.G., and Westenbroek, S.M., 2023, Updated estimates of water budget components for the Mississippi embayment region using a Soil-Water-Balance model, 2000–2020: U.S. Geological Survey Scientific Investigations Report 2023–5080, 58 p., https://doi.org/10.3133/sir20235080","productDescription":"Report: vii, 58 p.; Data Release; Dataset","numberOfPages":"72","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-132665","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":501044,"rank":10,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115885.htm","linkFileType":{"id":5,"text":"html"}},{"id":423679,"rank":9,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20235051","text":"SIR 2023–5051","linkHelpText":"— Automated construction of Streamflow-Routing networks for MODFLOW—Application in the Mississippi Embayment region"},{"id":423678,"rank":8,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20235100","text":"SIR 2023–5100","linkHelpText":"—Simulating groundwater flow in the Mississippi Alluvial Plain with a focus on the Mississippi Delta"},{"id":423159,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235080/full"},{"id":423153,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5080/coverthb.jpg"},{"id":423155,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5080/sir20235080.XML"},{"id":423154,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5080/sir20235080.pdf","text":"Report","size":"14.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023–5080"},{"id":423156,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5080/images/"},{"id":423158,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":423157,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P97KK17G","text":"USGS data release","linkHelpText":"Model archive and output files for net infiltration, runoff, and irrigation water use for the Mississippi Embayment Regional Aquifer System, 2000 to 2020, simulated with the Soil-Water-Balance model"}],"country":"United States","otherGeospatial":"Mississippi Embayment Region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -94.12089542031869,\n 28.886284478842654\n ],\n [\n -86.65019229531852,\n 28.886284478842654\n ],\n [\n -86.65019229531852,\n 37.89501192204163\n ],\n [\n -94.12089542031869,\n 37.89501192204163\n ],\n [\n -94.12089542031869,\n 28.886284478842654\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Upper Midwest Water Science Center
U.S. Geological Survey
1 Gifford Pinchot Drive
Madison, WI 53726
Sea level rise is leading to the rapid migration of marshes into coastal forests and other terrestrial ecosystems. Although complex biophysical interactions likely govern these ecosystem transitions, projections of sea level driven land conversion commonly rely on a simplified “threshold elevation” that represents the elevation of the marsh-upland boundary based on tidal datums alone. To determine the influence of biophysical drivers on threshold elevations, and their implication for land conversion, we examined almost 100,000 high-resolution marsh-forest boundary elevation points, determined independently from tidal datums, alongside hydrologic, ecologic, and geomorphic data in the Chesapeake Bay, the largest estuary in the U.S. located along the mid-Atlantic coast. We find five-fold variations in threshold elevation across the entire estuary, driven not only by tidal range, but also salinity and slope. However, more than half of the variability is unexplained by these variables, which we attribute largely to uncaptured local factors including groundwater discharge, microtopography, and anthropogenic impacts. In the Chesapeake Bay, observed threshold elevations deviate from predicted elevations used to determine sea level driven land conversion by as much as the amount of projected regional sea level rise by 2050. These results suggest that local drivers strongly mediate coastal ecosystem transitions, and that predictions based on elevation and tidal datums alone may misrepresent future land conversion.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2023JG007525","usgsCitation":"Molino, G., Carr, J., Ganju, N., and Kirwan, M., 2023, Biophysical drivers of coastal treeline elevation: JGR Biogeosciences, v. 128, no. 12, e2023JG007525, 18 p., https://doi.org/10.1029/2023JG007525.","productDescription":"e2023JG007525, 18 p.","ipdsId":"IP-152726","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":441370,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2023jg007525","text":"Publisher Index Page"},{"id":424278,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Delaware, Maryland, Virginia","otherGeospatial":"Chesapeake Bay area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -76.8511875475028,\n 39.673022111699964\n ],\n [\n -76.8511875475028,\n 36.994029518343055\n ],\n [\n -75.03985116290059,\n 36.994029518343055\n ],\n [\n -75.03985116290059,\n 39.673022111699964\n ],\n [\n -76.8511875475028,\n 39.673022111699964\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"128","issue":"12","noUsgsAuthors":false,"publicationDate":"2023-12-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Molino, Grace 0000-0001-7345-8619","orcid":"https://orcid.org/0000-0001-7345-8619","contributorId":292186,"corporation":false,"usgs":false,"family":"Molino","given":"Grace","affiliations":[{"id":6708,"text":"Virginia Institute of Marine Science","active":true,"usgs":false}],"preferred":false,"id":891909,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carr, Joel A. 0000-0002-9164-4156 jcarr@usgs.gov","orcid":"https://orcid.org/0000-0002-9164-4156","contributorId":168645,"corporation":false,"usgs":true,"family":"Carr","given":"Joel A.","email":"jcarr@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":891910,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ganju, Neil K. 0000-0002-1096-0465","orcid":"https://orcid.org/0000-0002-1096-0465","contributorId":202878,"corporation":false,"usgs":true,"family":"Ganju","given":"Neil K.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":891911,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kirwan, Mathew 0000-0002-0658-3038","orcid":"https://orcid.org/0000-0002-0658-3038","contributorId":333093,"corporation":false,"usgs":false,"family":"Kirwan","given":"Mathew","email":"","affiliations":[{"id":6708,"text":"Virginia Institute of Marine Science","active":true,"usgs":false}],"preferred":false,"id":891912,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70250566,"text":"cir1516 - 2023 - Integrated science strategy for assessing and monitoring water availability and migratory birds for terminal lakes across the Great Basin, United States","interactions":[],"lastModifiedDate":"2025-08-07T21:10:28.947951","indexId":"cir1516","displayToPublicDate":"2023-12-22T07:00:34","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":307,"text":"Circular","code":"CIR","onlineIssn":"2330-5703","printIssn":"1067-084X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1516","displayTitle":"Integrated Science Strategy for Assessing and Monitoring Water Availability and Migratory Birds for Terminal Lakes Across the Great Basin, United States","title":"Integrated science strategy for assessing and monitoring water availability and migratory birds for terminal lakes across the Great Basin, United States","docAbstract":"In 2022, the U.S. Geological Survey (USGS) established the Saline Lake Ecosystems Integrated Water Availability Assessment (IWAAs) to monitor and assess the hydrology of terminal lakes in the Great Basin and the migratory birds and other wildlife dependent on those habitats. Scientists from across the USGS (with specialties in water quantity, water quality, limnology, avian biology, data science, landscape ecology, and science communication) formed the Saline Lake Ecosystems IWAAs Team. The team has developed this regional strategic science plan to guide data collection and assessment activities at terminal lakes in the Great Basin.
The U.S. Congress requested the USGS to establish the Saline Lake Ecosystems IWAAs in response to historically low water levels at terminal lakes and associated wetlands across the Great Basin. Not all Great Basin terminal lakes have high salinity; however, all terminal lakes occur in endorheic, closed, basins with no surface-water outflow. Low lake levels across the Great Basin are the result of increased water use for agriculture and municipalities, drought conditions, and a warming climate. Great Basin terminal lake water extents have decreased by as much as 90 percent over the last 150 years, and terminal lake wetlands have decreased in area by as much as 47 percent since 1984. Lake elevations and wetland areas are primarily supported by freshwater inputs from snowmelt feeding upgradient rivers, streams, and springs. These freshwater inputs have been severely reduced because of continued and increased surface-water diversions and surface-water capture through groundwater pumping for agriculture, mining, and public supply as well as unprecedented drought conditions and warming temperatures related to climate change.
Water quality, specifically salinity, is highly variable for terminal lakes of the Great Basin, and this variability is a result of the balance between freshwater inflow and evaporation. Variability of salinity at each of the terminal lakes can be affected by lake morphology, hydrogeologic features of the basin, annual variability in weather patterns, and changes in upgradient water use. Hypersaline terminal lakes provide abundant food resources such as brine shrimp and brine flies that support nesting and migrating birds. The density and composition of invertebrates are closely tied to lake salinity. Increased salinity can exceed the tolerance of invertebrates, severely limiting their biomass. In contrast, decreased salinity can lead to altered invertebrate community composition, reducing the abundance of optimal avian prey resources.
Great Basin terminal lake ecosystems, including open-water and adjacent aquatic and terrestrial environments, provide resources necessary to sustain many animal populations throughout the year. Although a variety of taxa use terminal lakes, these ecosystems are of acute importance for the millions of migratory waterbirds (for example, shorebirds, wading birds, and waterfowl) dependent on the network of terminal lakes and their associated wetlands. Migratory birds transiting the Pacific and Central Flyways use Great Basin terminal lake ecosystems throughout the year to feed, nest, and transit between wintering and breeding ranges. As such, successful conservation of birds and their habitats requires coordinated management of water and habitats across the Great Basin network of terminal lakes and wetlands.
The linkages between water availability and ecosystem vulnerability of terminal lakes in the Great Basin are not well understood. The vulnerability of terminal lakes is related to the factors driving change and adaptive capacity of the lake ecosystem. Saline lake ecosystems are vulnerable when changes in water quantity affect ecosystem function. Water quantity affects salinity, which affects food webs and habitat; these linkages can be investigated with water-quality and food web monitoring. Water quantity also affects inundated habitat, which can be quantified through remote sensing. It is necessary to quantify hydroclimatic and water use controls on water availability to terminal lakes to assess the response of the ecosystems. Remotely sensed data can provide a broad-scale and long-term synoptic view of terminal lake hydrologic characteristics, but ground observations are required to interpret changes in water quality and ecological functions. Some terminal lake basins have ongoing monitoring and modeling efforts within the Great Basin (for example, Great Salt Lake, Carson River Basin), yet most monitoring locations are hydrologically upgradient and too far away from lake inflows to provide an accurate assessment of hydrological trends for the lake ecosystems. Other terminal lakes have no long-term hydrological monitoring in their respective watersheds (for example, Lake Abert).
Ecological data collection in the Great Basin is also insufficient to understand how many birds exist on the landscape, how birds use the mosaic of terminal-lake habitats as an interconnected system, and how Great Basin terminal lakes are linked to the larger continental system of the Pacific and Central Flyways. Across agencies and organizations, tracking bird movement, abundance, and diversity is inconsistent, with some lakes having once- or twice-a-year bird survey efforts and a few locations having more intensive ecological data-gathering efforts (for example, Great Salt Lake, Lake Abert). Bridging hydrological and ecological information gaps will improve understanding of the trends in water supply and water quality, habitat availability and usage, and impacts on vulnerable waterbird species, all of which would be used by managers in coordinated conservation of this unique network of terminal-lake habitats.
The terminal lakes of the Great Basin are part of the Basin and Range physiographic province that extends from the Colorado Plateau on the east to the Sierra Nevada on the west, and from the Snake River Plain on the north to the Garlock fault and the Mojave block on the south. The Great Basin is larger than 650,000 square kilometers and encompasses most of the State of Nevada but also extends to western Utah, eastern California, southeastern Idaho, southwestern Wyoming, and southeastern Oregon. The climate is arid to semiarid with a hydrologic regime that is snowmelt dominated, providing as much as 75 percent of total annual runoff for the region. Terminal lakes of the Great Basin occupy the lowest areas of closed (endorheic) drainage basins, such that lake levels and water quality respond rapidly to surface-water inflow. Terminal lakes provide local and regional economic value to the States in the Great Basin, including mineral extraction, aquaculture, public works, and recreational uses. As an example, assessments of Great Salt Lake’s ecological health and economic impact find hemispheric importance for the former and regional importance for the latter. Great Salt Lake creates about 7,000 jobs and $2 billion of economic output per year, most of which would be lost with further declines in lake level.
The objectives of this Science Strategy are threefold: (1) to identify how changing water availability affects the quality, diversity, and abundance of habitats supporting continental waterbird populations; (2) to highlight the scientific monitoring and assessment needs of Great Basin terminal lakes; and (3) to support coordinated management and conservation actions to benefit those ecosystems, migratory birds, and other wildlife. There are long-term hydrological, ecological, and societal challenges associated with terminal lakes ecosystems in the Great Basin. This Science Strategy benefits partners by providing a conceptual model, nested at different spatial extents, that identifies key scientific information needs to inform coordinated implementation of management and conservation plans within and among hydrologic basins to address these complex challenges.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1516","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Frus, R.J., Aldridge, C.L., Casazza, M.L., Eagles-Smith, C.A., Herring, G., Hynek, S.A., Jones, D.K., Kemp, S.K., Marston, T.M., Morris, C.M., Naranjo, R.C., Nell, C.S., O’Leary, D.R., Overton, C.T., Pulver, B.A., Reichert, B.E., Rumsey, C.A., Schuster, R., and Smith, C.D., 2023, Integrated science strategy for assessing and monitoring water availability and migratory birds for terminal lakes across the Great Basin, United States (ver. 1.1, May 2025): U.S. Geological Survey Circular 1516, 80 p., https://doi.org/10.3133/cir1516.","productDescription":"Report: v, 68 p.; 2 Data Releases","onlineOnly":"Y","ipdsId":"IP-150954","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":493768,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115888.htm","linkFileType":{"id":5,"text":"html"}},{"id":486001,"rank":5,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/circ/1516/versionHistory.txt","size":"2 KB","linkFileType":{"id":2,"text":"txt"},"description":"Version history"},{"id":423645,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9Q9LQ4B","text":"USGS data release","description":"USGS data release","linkHelpText":"Protected areas database of the United States (PAD-US) 3.0"},{"id":423641,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/circ/1516/coverthb.jpg"},{"id":423642,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1516/cir1516.pdf","text":"Report","size":"10.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Circular 1516"},{"id":423644,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9G5CGA7","text":"USGS data release","description":"USGS data release","linkHelpText":"Bibliography of hydrological and ecological research in the Great Basin terminal lakes, USA"},{"id":423646,"rank":6,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/circ/1516/images"},{"id":423647,"rank":7,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/circ/1516/cir1516.XML"}],"country":"United States","state":"California, Idaho, Nevada, Oregon, Utah, Wyoming","otherGeospatial":"Great Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -119.12391771230867,\n 44.77405073422017\n ],\n [\n -121.23711112053633,\n 42.97675607274502\n ],\n [\n -120.58454292500758,\n 41.114625765489706\n ],\n [\n -120.53050233969739,\n 39.38852576977999\n ],\n [\n -121.00002831582353,\n 38.53773263098702\n ],\n [\n -116.23219239369243,\n 34.14172761189964\n ],\n [\n -115.35960273905562,\n 33.921557217133085\n ],\n [\n -115.48689980188553,\n 34.74795954290249\n ],\n [\n -116.28333189096784,\n 36.47975443280677\n ],\n [\n -115.18568355055748,\n 36.991906804073\n ],\n [\n -114.24156554808329,\n 36.95599163233307\n ],\n [\n -113.37134736473482,\n 37.12638077251309\n ],\n [\n -110.81542598426338,\n 37.47470809636182\n ],\n [\n -109.75571598007943,\n 37.95141366251099\n ],\n [\n -109.25899321449629,\n 41.77121949987571\n ],\n [\n -109.56993210264781,\n 42.456264038882864\n ],\n [\n -111.91699262765405,\n 42.330119018284336\n ],\n [\n -115.47461542510021,\n 41.37630387146504\n ],\n [\n -117.71290028552804,\n 42.12092395037371\n ],\n [\n -119.12391771230867,\n 44.77405073422017\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Version 1.0: December 23, 2023; Version 1.1: April 2025","contact":"Director, Forest and Rangeland Ecosystem Science Center
U.S. Geological Survey
777 NW 9th Street, Suite 400
Corvallis, Oregon 97330
Director, Utah Water Science Center
U.S. Geological Survey
2329 West Orton Circle
Salt Lake City, Utah 84119-2047
Highway runoff is a source of sediment and associated constituents to downstream waterbodies that can be managed with the use of stormwater-control measures that reduce sediment loads. The use of open-graded friction course (OGFC) pavement has been identified as a method to reduce loads from highway runoff because it retains sediment in pavement voids; however, few datasets are available in New England to characterize runoff quality from OGFC pavement. To meet this data need, the U.S. Geological Survey, in cooperation with the Massachusetts Department of Transportation, conducted a field study from October 2018 through September 2021 to monitor runoff from a section of traditional dense-graded hot-mix asphalt (HMA) and from a section of OGFC pavement on Interstate 95 near Needham, Massachusetts. A robust dataset that includes suspended sediment concentrations for nearly every runoff event during the study period was generated to compare runoff from the two 4,180-square-foot sections of highway pavement under identical traffic volume and maintenance characteristics.
Automatic-monitoring techniques were used to collect over 6,500 samples at each station to characterize all runoff-generating events during the study period (226 events for the HMA site and 168 events for the OGFC site). Suspended sediment concentrations were consistently lower in runoff from the OGFC pavement throughout the study period, with median event-mean concentrations for all runoff events of 29 and 15 milligrams per liter for the HMA and OGFC sites, respectively. The total load of sediment less than 6.0 millimeters in diameter from the HMA section (202 kilograms [kg]) was 41 percent greater than the load measured from the OGFC pavement (120 kg), and the total load of sediment less than 2.0 mm in diameter was 49 percent greater (168 kg and 85 kg from the HMA and OGFC sites, respectively). The greatest differences in loads between the two pavement segments were in the particle-size ranges less than 2.0 millimeters in diameter, indicating that these particles are retained by the voids in the OGFC pavement. The relative difference between annual sediment-load estimates at each site over the study period indicates that OGFC pavement became clogged, a condition that permeameter test results also reflected. Specifically, the average total load of sediment for the first 2 years of the study was 68 percent lower at the OGFC site than the HMA site, but the difference between the respective loads decreased to 19 percent in the third year of the study.
Study-period loads for most total-recoverable metals in runoff from each pavement type were between 7 and 64 percent higher from the HMA site, except for loads of arsenic, cadmium, and zinc, which were higher from the OGFC pavement. Study-period loads for total phosphorus were similar from each pavement type. Despite the same application rate of deicing chemicals, sodium and chloride loads in runoff were about two times greater from the OGFC section than from the HMA pavement during years with average snowfall amounts but were approximately equal at both sites during the mild winter in 2020.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235127","collaboration":"Prepared in cooperation with the Massachusetts Department of Transportation","usgsCitation":"Smith, K.P., Spaetzel, A.B., and Woodford, P.A., 2023, Highway-runoff quality from segments of open-graded friction course and dense-graded hot-mix asphalt pavement on Interstate 95, Massachusetts, 2018–21: U.S. Geological Survey Scientific Investigations Report 2023–5127, 59 p., https://doi.org/10.3133/sir20235127","productDescription":"Report: xi, 59 p.; Data Release","numberOfPages":"59","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-151162","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":423760,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FASAUV","text":"USGS data release","linkHelpText":"Highway-monitoring data from segments of open-graded friction course and dense-graded hot-mix asphalt pavement in eastern Massachusetts, 2018–2021"},{"id":423755,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5127/coverthb.jpg"},{"id":423756,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5127/sir20235127.pdf","text":"Report","size":"4.80 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5127"},{"id":424094,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235127/full","text":"Report"},{"id":423758,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5127/sir20235127.XML"},{"id":423759,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5127/images/"},{"id":501162,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115712.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Massachusetts","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -71.24249515694652,\n 42.31584615373151\n ],\n [\n -71.24249515694652,\n 42.25488827654789\n ],\n [\n -71.18207035225896,\n 42.25488827654789\n ],\n [\n -71.18207035225896,\n 42.31584615373151\n ],\n [\n -71.24249515694652,\n 42.31584615373151\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
Innovations in geodesy enable widespread analysis of glacier surface elevation change and geodetic mass balance. However, coincident glacier area data are less widely available, causing inconsistent handling of glacier area change. Here we quantify the bias introduced into meters water equivalent (m w.e.) specific geodetic mass balance results when using a fixed, maximum glacier area, and illustrate the bias for five North American glaciers. Sites span latitudes from the northern U.S. Rocky Mountains (48°N) to the Central Alaska Range (63°N) between 1948 and 2021. Results show that fixed (maximum) area treatment subdues the m w.e. mass change signal, underestimating mass balance by up to 19% in our test cases. This bias scales with relative glacier area change and the mass balance magnitude. Thus, the bias for specific geodetic mass balances will be most pronounced across rapidly deglaciating regions. Our analysis underscores the need for temporally resolved glacier area in geodetic mass balance studies.
Site fidelity, the tendency to return to a previously visited site, is commonly observed in migratory birds. This behaviour would be advantageous if birds returning to the same site, benefit from their previous knowledge about local resources. However, when habitat quality declines at a site over time, birds with lower site fidelity might benefit from a tendency to move to sites with better habitats. As a first step towards understanding the influence of site fidelity on how animals cope with habitat deterioration, here we describe site fidelity variation in two species of sympatric migratory shorebirds (Bar-tailed Godwits Limosa lapponica and Great Knots Calidris tenuirostris). Both species are being impacted by the rapid loss and deterioration of intertidal habitats in the Yellow Sea where they fuel up during their annual long-distance migrations.
Using satellite tracking and mark-resighting data, we measured site fidelity in the non-breeding (austral summer) and migration periods, during which both species live and co-occur in Northwest Australia and the Yellow Sea, respectively.
Site fidelity was generally high in both species, with the majority of individuals using only one site during the non-breeding season and revisiting the same sites during migration. Nevertheless, Great Knots did exhibit lower site fidelity than Bar-tailed Godwits in both Northwest Australia and the Yellow Sea across data types.
Great Knots encountered substantial habitat deterioration just before and during our study period but show the same rate of decline in population size and individual survival as the less habitat-impacted Bar-tailed Godwits. This suggests that the lower site fidelity of Great Knots might have helped them to cope with the habitat changes. Future studies on movement patterns and their consequences under different environmental conditions by individuals with different degrees of site fidelity could help broaden our understanding of how species might react to, and recover from, local habitat deterioration.
","language":"English","publisher":"Springer","doi":"10.1186/s40462-023-00443-9","usgsCitation":"Chan, Y., Chan, D.T., Tibbitts, T., Hassell, C.J., and Piersma, T., 2023, Site fidelity of migratory shorebirds facing habitat deterioration: Insights from satellite tracking and mark-resighting: Movement Ecology, v. 11, 79, 13 p., https://doi.org/10.1186/s40462-023-00443-9.","productDescription":"79, 13 p.","ipdsId":"IP-151596","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":441386,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s40462-023-00443-9","text":"Publisher Index Page"},{"id":426959,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","noUsgsAuthors":false,"publicationDate":"2023-12-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Chan, Ying-Chi","contributorId":167762,"corporation":false,"usgs":false,"family":"Chan","given":"Ying-Chi","email":"","affiliations":[{"id":24822,"text":"Department of Marine Ecology, NIOZ Royal Netherlands Institute for Sea Research","active":true,"usgs":false}],"preferred":false,"id":897211,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chan, David Tsz-Chung","contributorId":334994,"corporation":false,"usgs":false,"family":"Chan","given":"David","email":"","middleInitial":"Tsz-Chung","affiliations":[{"id":36570,"text":"NIOZ Royal Netherlands Institute for Sea Research","active":true,"usgs":false}],"preferred":false,"id":897212,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tibbitts, T. Lee 0000-0002-0290-7592","orcid":"https://orcid.org/0000-0002-0290-7592","contributorId":224104,"corporation":false,"usgs":true,"family":"Tibbitts","given":"T. Lee","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":897213,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hassell, Chris J.","contributorId":127818,"corporation":false,"usgs":false,"family":"Hassell","given":"Chris","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":897234,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Piersma, Theunis","contributorId":45863,"corporation":false,"usgs":true,"family":"Piersma","given":"Theunis","affiliations":[],"preferred":false,"id":897235,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70250626,"text":"dr1186 - 2023 - Water-level data for the Albuquerque Basin and adjacent areas, central New Mexico, period of record through September 30, 2022","interactions":[],"lastModifiedDate":"2026-02-04T20:19:51.548438","indexId":"dr1186","displayToPublicDate":"2023-12-20T16:01:03","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":9318,"text":"Data Report","code":"DR","onlineIssn":"2771-9448","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1186","displayTitle":"Water-Level Data for the Albuquerque Basin and Adjacent Areas, Central New Mexico, Period of Record Through September 30, 2022","title":"Water-level data for the Albuquerque Basin and adjacent areas, central New Mexico, period of record through September 30, 2022","docAbstract":"The Albuquerque Basin, located in central New Mexico, is about 100 miles long and 25–40 miles wide. The basin is hydrologically defined as the extent of consolidated and unconsolidated deposits of Tertiary and Quaternary age that encompasses the structural Rio Grande Rift between San Acacia to the south and Cochiti Lake to the north. Drinking-water supplies throughout the basin were obtained primarily from groundwater resources until December 2008, when the Albuquerque Bernalillo County Water Utility Authority (ABCWUA) began treatment and distribution of surface water from the Rio Grande through the San Juan-Chama Drinking Water Project.
An initial network of wells was established by the U.S. Geological Survey (USGS) in cooperation with the City of Albuquerque from April 1982 through September 1983 to monitor changes in groundwater levels throughout the Albuquerque Basin. In 1983, this network consisted of 6 wells with analog-to-digital recorders and 27 wells where water levels were measured monthly. As of water year 2022, the network consisted of 120 wells and piezometers at 54 locations. The USGS, in cooperation with the ABCWUA, the New Mexico Office of the State Engineer, and Bernalillo County, measures water levels at the wells and piezometers in the network; this report, prepared in cooperation with the ABCWUA, presents water-level data collected by USGS personnel at the sites through water year 2022 (October 1, 2021, through September 30, 2022). Water-level data that were collected in previous water years from wells that were later discontinued were published in previous USGS reports.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/dr1186","issn":"2771-9448","collaboration":"Prepared in cooperation with the Albuquerque Bernalillo County Water Utility Authority","usgsCitation":"Bell, M.T., and Montero, N.Y., 2023, Water-level data for the Albuquerque Basin and adjacent areas, central New Mexico, period of record through September 30, 2022: U.S. Geological Survey Data Report 1186, 42 p., https://doi.org/10.3133/dr1186.","productDescription":"Report: iv, 42 p.; Data Release","numberOfPages":"50","onlineOnly":"Y","ipdsId":"IP-153179","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":423823,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS water data for the Nation","linkHelpText":"U.S. Geological Survey National Water Information System database"},{"id":423820,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/dr/1186/dr1186.XML","linkFileType":{"id":8,"text":"xml"},"description":"DR 1186 XML"},{"id":423818,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/dr/1186/coverthb.jpg"},{"id":423819,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/dr/1186/dr1186.pdf","size":"3.88 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DR 1186"},{"id":423821,"rank":4,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/dr1186/full","linkFileType":{"id":5,"text":"html"},"description":"DR 1186 HTML"},{"id":423822,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/dr/1186/images"},{"id":499558,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115709.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"New Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -107.82700159405645,\n 34.09776221662605\n ],\n [\n -105.91538050030636,\n 34.09776221662605\n ],\n [\n -105.91538050030636,\n 36.30588569471621\n ],\n [\n -107.82700159405645,\n 36.30588569471621\n ],\n [\n -107.82700159405645,\n 34.09776221662605\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, New Mexico Water Science Center
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6700 Edith Blvd. NE
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Scientific experts from different disciplines often struggle to mesh their specialized perspectives into the shared mindset that is needed to address difficult and persistent environmental, ecological, and societal problems. Many traditional graduate programs provide excellent research and technical skill training. However, these programs often do not teach a systematic way to learn team skills, nor do they offer a protocol for identifying and tackling increasingly integrated interdisciplinary (among disciplines) and transdisciplinary (among researchers and stakeholders) questions. As a result, professionals trained in traditional graduate programs (e.g., current graduate students and employed practitioners) may not have all of the collaborative skills needed to advance solutions to difficult scientific problems. In the present article, we illustrate a tractable, widely implementable structured process called RISE that accelerates the development of these missing skills. The RISE process (Route to Identifying, learning, and practicing interdisciplinary and transdisciplinary team Skills to address difficult Environmental problems) can be used by diverse teams as a tool for research, professional interactions, or training. RISE helps professionals with different expertise learn from each other by repeatedly asking team-developed questions that are tested using an interactive quantitative tool (e.g., agent-based models, machine learning, case studies) applied to a shared problem framework and data set. Outputs from the quantitative tool are then discussed and interpreted as a team, considering all team members’ perspectives, disciplines, and expertise. After this synthesis, RISE is repeated with new questions that the team jointly identified in earlier data interpretation discussions. As a result, individual perspectives, originally informed by disciplinary training, are complemented by a shared understanding of team function and elevated interdisciplinary knowledge.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/biosci/biad097","usgsCitation":"Mather, M.E., Granco, G., Bergtold, J., Caldas, M., Heier Stamm, J., Sheshukov, A., Sanderson, M., and Daniels, M., 2023, Achieving success with RISE: A widely implementable, iterative, structured process for mastering interdisciplinary team science collaborations: BioScience, v. 73, no. 12, p. 891-905, https://doi.org/10.1093/biosci/biad097.","productDescription":"15 p.","startPage":"891","endPage":"905","ipdsId":"IP-148659","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":441388,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/biosci/biad097","text":"Publisher Index Page"},{"id":432344,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"73","issue":"12","noUsgsAuthors":false,"publicationDate":"2023-12-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Mather, Martha E. 0000-0003-0827-3006 mather@usgs.gov","orcid":"https://orcid.org/0000-0003-0827-3006","contributorId":340771,"corporation":false,"usgs":true,"family":"Mather","given":"Martha","email":"mather@usgs.gov","middleInitial":"E.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":907537,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Granco, Gabriel","contributorId":340772,"corporation":false,"usgs":false,"family":"Granco","given":"Gabriel","email":"","affiliations":[{"id":66019,"text":"Cal Poly Pomona","active":true,"usgs":false}],"preferred":false,"id":907538,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bergtold, Jason","contributorId":340773,"corporation":false,"usgs":false,"family":"Bergtold","given":"Jason","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":907539,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Caldas, Marcellus","contributorId":340774,"corporation":false,"usgs":false,"family":"Caldas","given":"Marcellus","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":907540,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Heier Stamm, Jessica","contributorId":340775,"corporation":false,"usgs":false,"family":"Heier Stamm","given":"Jessica","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":907541,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sheshukov, Aleksey","contributorId":340776,"corporation":false,"usgs":false,"family":"Sheshukov","given":"Aleksey","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":907542,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sanderson, Matthew","contributorId":340777,"corporation":false,"usgs":false,"family":"Sanderson","given":"Matthew","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":907543,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Daniels, Melinda","contributorId":340778,"corporation":false,"usgs":false,"family":"Daniels","given":"Melinda","affiliations":[{"id":37456,"text":"Stroud Water Research Center","active":true,"usgs":false}],"preferred":false,"id":907544,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70250792,"text":"70250792 - 2023 - Nitrate-nitrogen and total phosphorus river loads","interactions":[],"lastModifiedDate":"2024-01-09T16:09:43.991087","indexId":"70250792","displayToPublicDate":"2023-12-20T09:47:37","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"title":"Nitrate-nitrogen and total phosphorus river loads","docAbstract":"Nitrate-nitrogen and total phosphorus loads from the major rivers draining Illinois were updated through the 2021 water year (Figure 3.1). Beginning with the 2023 biennial update to the Illinois NLRS, nutrient loads were estimated using data from the U.S. Geological Survey continuous monitoring stations rather than the original Illinois EPA monitoring stations. To maintain consistency with previous biennial report updates, the loads from the new sites were rescaled to match the original drainage areas (Table 3.1). As before, the statewide nutrient load was estimated by summing the loads of the eight major rivers adjusting for out-of-state contributions and unmonitored areas.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Illinois nutrient loss reduction strategy 2023 biennial update","largerWorkSubtype":{"id":2,"text":"State or Local Government Series"},"language":"English","publisher":"Illinois EPA","usgsCitation":"Hodson, T.O., 2023, Nitrate-nitrogen and total phosphorus river loads, 11 p.","productDescription":"11 p.","startPage":"25","endPage":"35","ipdsId":"IP-148328","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":424178,"rank":2,"type":{"id":15,"text":"Index 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Report","code":"DR","onlineIssn":"2771-9448","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1166","displayTitle":"Evaluating Water-Quality Conditions in the Mainstem and Tidal Reaches of the Merrimack River in Massachusetts, June to September 2020","title":"Evaluating water-quality conditions in the mainstem and tidal reaches of the Merrimack River in Massachusetts, June to September 2020","docAbstract":"In summer and early fall (June to September) 2020, water-quality data were collected at 13 stations along the mainstem of the Merrimack River and into the Merrimack River estuary. The data are allocated among three different datasets: discrete water sample data, discrete vertical profile data, and continuous data. The collective purpose of these datasets is to enable assessment of the overall water-quality conditions in the Merrimack River and estuary and to identify areas for potentially more targeted water-quality monitoring in the future.
The highest concentrations of nutrients—nitrogen and phosphorus—were found at the stations downstream from wastewater treatment plants in Lowell, Lawrence, and Haverhill. Nutrient concentrations measured in the Merrimack River estuary were not as high as those measured in the Merrimack River, indicating that other processes are affecting nutrient concentrations in the system. These data were collected coincident with a severe flash drought in New England. Analysis of the vertical profile and continuous data indicated that, for intermittent periods up to 5 days, water quality in some sections of the Merrimack River may not support designated uses for the waterbody as established in the Massachusetts surface water quality standards.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/dr1166","collaboration":"Prepared in cooperation with the Massachusetts Department of Environmental Protection","usgsCitation":"Laabs, K., Beaudoin, C., Sorenson, J., and Bissell, A., 2023, Evaluating water-quality conditions in the mainstem and tidal reaches of the Merrimack River in Massachusetts, June to September 2020: U.S. Geological Survey Data Report 1166, 19 p., https://doi.org/10.3133/dr1166","productDescription":"Report: vi, 19 p.; Data Release","numberOfPages":"19","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-132656","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":423766,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9H19THP","text":"USGS data release","linkHelpText":"Water quality data for discrete samples and continuous monitoring on the Merrimack River, Massachusetts, June to September 2020"},{"id":423762,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/dr/1166/dr1166.pdf","text":"Report","size":"1.77 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DR 1166"},{"id":423761,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/dr/1166/coverthb.jpg"},{"id":499550,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115711.htm","linkFileType":{"id":5,"text":"html"}},{"id":423765,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/dr/1166/images/"},{"id":423764,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/dr/1166/dr1166.XML"},{"id":423763,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/dr1166/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"DR 1166"}],"country":"United States","state":"Massachusetts","otherGeospatial":"Merrimack River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -70.49210277817261,\n 42.90875513880272\n ],\n [\n -71.8214484812977,\n 42.90875513880272\n ],\n [\n -71.8214484812977,\n 42.34696579329744\n ],\n [\n -70.49210277817261,\n 42.34696579329744\n ],\n [\n -70.49210277817261,\n 42.90875513880272\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
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