{"pageNumber":"333","pageRowStart":"8300","pageSize":"25","recordCount":41075,"records":[{"id":70205595,"text":"70205595 - 2019 - Modeling transient soil moisture limitations on microbial carbon respiration: A cost-performance comparison","interactions":[],"lastModifiedDate":"2019-09-27T09:43:37","indexId":"70205595","displayToPublicDate":"2019-07-02T09:06:55","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1011,"text":"Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Modeling transient soil moisture limitations on microbial carbon respiration: A cost-performance comparison","docAbstract":"Soil microorganisms are known to survive periods of aridity and to recover rapidly after wetting events, with the ability to transition between a dormant state in dry conditions and an active state in wet conditions. Though this dynamic behavior has been previously incorporated into soil carbon respiration modeling frameworks, a direct comparison between this active-dormant transition mechanism and a more simplified first-order model has yet to be made. Here, we demonstrate the necessary extent of model complexity needed to reproduce transient carbon respiration rates obtained from a set of soil incubation experiments implemented over a range of soil depths and time intervals. Two approaches are tested, one uses simplified first-order kinetics whereas the other employs a transition between active and dormant biomass. The performance of each model is evaluated using an Akaike Information Criterion (AIC) based on the accuracy with which they reproduce an experimental dataset consisting of two sets of time series soil incubations collected across a range of time and depth resolutions. Based on the AIC evaluation and model-data comparison, we conclude that a dormancy-enabled model featuring two distinct microbial strategists performs best for the majority of the soil profile (above 108 cm) for both high- and low- depth resolution and sampling frequency, despite the added parameters required. In contrast, the first-order model achieves better AIC scores when simulating our deepest soils (112-165 cm), where moisture fluctuations are expected to be less prevalent. These results guide how and where we choose to apply more cost intensive models.","language":"English","doi":"10.1029/2018JG004628","usgsCitation":"Liu, Y., Lawrence, C.R., Mathew Winnick, Hsiao-Tieh Hsu, Maher, K., and Druhan, J., 2019, Modeling transient soil moisture limitations on microbial carbon respiration: A cost-performance comparison: Biogeosciences, v. 124, no. 7, p. 2222-2247, https://doi.org/10.1029/2018JG004628.","productDescription":"26 p.","startPage":"2222","endPage":"2247","ipdsId":"IP-091717","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":467487,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2018jg004628","text":"Publisher Index Page"},{"id":367761,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"124","issue":"7","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-07-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Liu, Yuchen","contributorId":219247,"corporation":false,"usgs":false,"family":"Liu","given":"Yuchen","email":"","affiliations":[{"id":39974,"text":"University Illinois","active":true,"usgs":false}],"preferred":false,"id":771792,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lawrence, Corey R. 0000-0001-6143-7781","orcid":"https://orcid.org/0000-0001-6143-7781","contributorId":202390,"corporation":false,"usgs":true,"family":"Lawrence","given":"Corey","email":"","middleInitial":"R.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":771793,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mathew Winnick","contributorId":219248,"corporation":false,"usgs":false,"family":"Mathew Winnick","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":771794,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hsiao-Tieh Hsu","contributorId":219249,"corporation":false,"usgs":false,"family":"Hsiao-Tieh Hsu","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":771795,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Maher, Katherine","contributorId":219250,"corporation":false,"usgs":false,"family":"Maher","given":"Katherine","email":"","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":771796,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Druhan, Jennifer","contributorId":202381,"corporation":false,"usgs":false,"family":"Druhan","given":"Jennifer","email":"","affiliations":[{"id":36403,"text":"University of Illinois","active":true,"usgs":false}],"preferred":false,"id":771797,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70204105,"text":"70204105 - 2019 - Sharp savanna-forest transitions in the Midwest followed environmental gradients but are absent from the modern landscape","interactions":[],"lastModifiedDate":"2019-07-05T16:23:45","indexId":"70204105","displayToPublicDate":"2019-07-01T16:12:49","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5153,"text":"The American Midland Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"Sharp savanna-forest transitions in the Midwest followed environmental gradients but are absent from the modern landscape","docAbstract":"Historically, closed eastern forests transitioned into open savannas and prairies in the US Midwest, but this transition is poorly understood. To investigate the eastern boundary of the prairie-forest ecotone, we conducted a case study of historic and modern vegetation patterns of the Yellow River watershed in northwest Indiana. Historic vegetation came from the Public Land Survey notes collected in the early 1800s, whereas modern vegetation came from the Forest Inventory Analysis and USGS National Land Cover Database. We mapped historical survey vegetation data using GIS to reconstruct the region’s past and current forest composition and structure. We also mapped climate, topography, and soil composition across the watershed to investigate the relationship between historic vegetation and environmental gradients. We found a sharp transition in the presettlement forest structure and composition, with dense deciduous forests in the eastern portion of our study area and open oak savannas in the west. The savanna ecosystem dominated in sandy well-drained soils and was at a slightly lower elevation than the adjacent closed forest. Modest environmental changes accompanied major vegetation changes in the past, which might suggest fire and hydrological patterns helped maintain the sharp ecotone. By contrast, the modern forest shows no difference in tree density and composition across the watershed, which is consistent with major land use and hydrology changes in the watershed since settlement. On the modern landscape, land that was historically closed forest now has higher agricultural productivity compared to land that was historically savanna, whereas the historic savanna currently supports more mesic forest. These results suggest the environmental gradient continues to subtly shape the landscape. Though land use change has largely removed the closed mixed hardwood forests and oak savannas from this area, a better understanding of the historic vegetation and the conditions that supported it can help inform land management and restoration, as well as reveal ecological processes that drive vegetation transitions.","language":"English","publisher":"BioOne","doi":"10.1674/0003-0031-180.1.1","usgsCitation":"Broderick, C.M., Heilman, K.A., Patterson, T., Peters, J., and McLachlan, J.S., 2019, Sharp savanna-forest transitions in the Midwest followed environmental gradients but are absent from the modern landscape: The American Midland Naturalist, v. 180, no. 1, p. 1-17, https://doi.org/10.1674/0003-0031-180.1.1.","productDescription":"17","startPage":"1","endPage":"17","ipdsId":"IP-086114","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":365314,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Indiana","otherGeospatial":"Yellow River Watershed Area","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -86.84005737304688,\n              41.24683746537623\n            ],\n            [\n              -86.38412475585938,\n              41.24683746537623\n            ],\n            [\n              -86.38412475585938,\n              41.422134246213616\n            ],\n            [\n              -86.84005737304688,\n              41.422134246213616\n            ],\n            [\n              -86.84005737304688,\n              41.24683746537623\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"180","issue":"1","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Broderick, Caitlin M.","contributorId":216788,"corporation":false,"usgs":false,"family":"Broderick","given":"Caitlin","email":"","middleInitial":"M.","affiliations":[{"id":39516,"text":"University of Notre Dame","active":true,"usgs":false}],"preferred":false,"id":765533,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Heilman, Kelly A 0000-0001-5932-1317","orcid":"https://orcid.org/0000-0001-5932-1317","contributorId":216789,"corporation":false,"usgs":false,"family":"Heilman","given":"Kelly","email":"","middleInitial":"A","affiliations":[{"id":39516,"text":"University of Notre Dame","active":true,"usgs":false}],"preferred":false,"id":765534,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Patterson, Tamatha 0000-0002-1648-8114 tpatterson@usgs.gov","orcid":"https://orcid.org/0000-0002-1648-8114","contributorId":201149,"corporation":false,"usgs":true,"family":"Patterson","given":"Tamatha","email":"tpatterson@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":765532,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Peters, Jody","contributorId":216790,"corporation":false,"usgs":false,"family":"Peters","given":"Jody","affiliations":[{"id":39516,"text":"University of Notre Dame","active":true,"usgs":false}],"preferred":false,"id":765535,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McLachlan, Jason S.","contributorId":167179,"corporation":false,"usgs":false,"family":"McLachlan","given":"Jason","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":765536,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70202564,"text":"70202564 - 2019 - The relationship of channel planform and point bar architecture on a reach of the Wabash River near Grayville, Illinois","interactions":[],"lastModifiedDate":"2022-01-12T15:27:29.925999","indexId":"70202564","displayToPublicDate":"2019-07-01T12:13:34","publicationYear":"2019","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"The relationship of channel planform and point bar architecture on a reach of the Wabash River near Grayville, Illinois","docAbstract":"<p>The erosional and depositional characteristics of meandering rivers lead to the formation and maintenance of point bars along the inner banks of meander bends. Point bars are composed of sediment layers in patterns resulting from the rate and style of channel migration, hydrodynamics, and sediment transport and deposition within the river system (e.g. Jackson, 1976; Dietrich and Smith, 1984; Dietrich, 1987, Abad and Garcia, 2009). The distribution of the sediments preserved in the internal architecture of a river point bar provides a record of channel planform evolution. Geophysical methods are used to gain a large-scale visualization of the subsurface and aid in the interpretation of historic channel patterns (Best et al., 2003; Woodward et al., 2003; Sambrook Smith et al., 2006). Comparing known surficial extents of the point bar to features identified in the subsurface can also enhance the understanding of historic channel planform. This study investigates two point bars along bends with different styles of migration, Maier and TB3, in a well-documented reach of the Wabash River near Grayville, IL. Evidence from historic aerial photography, modern lidar, photogrammetry, and geophysical surveys were used to determine the relationship between the point bar architecture and channel planform. Airborne lidar was flown in 2011 and is used to create the 2011 point bar surface. In 2017, a terrestrial lidar and Real Time Kinematic-Global Navigation Satellite System (RTK-GNSS) topographic survey were combined to create the surface for TB3. In 2018, a photogrammetric survey collected with a small unmanned aerial system (sUAS) was used to create a structure-frommotion (SfM) derived surface for Maier bend. The 2018 survey-based point bar surfaces were differenced from the 2011 point bar surfaces to get a Digital Elevation Model (DEM) of difference (DoD) to visualize areas of erosion and deposition. In addition, geophysical surveys using ground penetrating radar (GPR) were conducted in transverse and streamwise lines across the point bars in 2018. Elevation profiles from the 2011 point bar surfaces are extracted and overlain onto the 2018 GPR images to determine how the point bar is preserving the structure of sediments previously deposited. Results from this study provide an update to current models of point bar architecture. </p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of SEDHYD 2019","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"SEDHYD 2019 Conference","conferenceDate":"June 24-28, 2019","conferenceLocation":"Reno, NV","language":"English","publisher":"Federal Interagency Sedimentation Conference (FISC) and Federal Interagency Hydrologic Modeling Conference (FIHMC)","usgsCitation":"Rowley, T., Konsoer, K., Ursic, M., and Langendoen, E.J., 2019, The relationship of channel planform and point bar architecture on a reach of the Wabash River near Grayville, Illinois, <i>in</i> Proceedings of SEDHYD 2019, v. 1, Reno, NV, June 24-28, 2019, 5 p.","productDescription":"5 p.","ipdsId":"IP-104932","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":368663,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":368662,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.sedhyd.org/2019/#sedhyd-2019-proceedings"}],"country":"United States","state":"Illinois","city":"Grayville","otherGeospatial":"Wabash River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -87.95722961425781,\n              38.25476238074633\n            ],\n            [\n              -87.901611328125,\n              38.25476238074633\n            ],\n            [\n              -87.901611328125,\n              38.30920107060575\n            ],\n            [\n              -87.95722961425781,\n              38.30920107060575\n            ],\n            [\n              -87.95722961425781,\n              38.25476238074633\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"1","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Rowley, Taylor 0000-0003-3786-6273","orcid":"https://orcid.org/0000-0003-3786-6273","contributorId":208374,"corporation":false,"usgs":true,"family":"Rowley","given":"Taylor","email":"","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":759117,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Konsoer, Kory","contributorId":220049,"corporation":false,"usgs":false,"family":"Konsoer","given":"Kory","email":"","affiliations":[],"preferred":false,"id":773986,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ursic, Mick","contributorId":220050,"corporation":false,"usgs":false,"family":"Ursic","given":"Mick","email":"","affiliations":[],"preferred":false,"id":773987,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Langendoen, Eddy J.","contributorId":66126,"corporation":false,"usgs":true,"family":"Langendoen","given":"Eddy","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":773988,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70203137,"text":"70203137 - 2019 - Channel modification and evolution alter hydraulic connectivity in the Atchafalaya River basin increasing vulnerability to sea-level rise","interactions":[],"lastModifiedDate":"2022-01-12T15:28:38.194711","indexId":"70203137","displayToPublicDate":"2019-07-01T11:45:33","publicationYear":"2019","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Channel modification and evolution alter hydraulic connectivity in the Atchafalaya River basin increasing vulnerability to sea-level rise","docAbstract":"Channel dredging and erosion in the Atchafalaya River basin have resulted in changes to the hydraulic connectivity of this floodplain swamp that have not been previously quantified. In this study, analyses were conducted to determine hydraulic and geomorphic factors that have changed since channel closure in 1962. Results indicated changes occurred in the Atchafalaya main channel cross-section between 1962 and 2010, and hydraulic and geomorphic changes were detected in portions of the interior eastern basin floodplain. Analyses of hydrographs in relation to floodplain elevations indicated that there was a lack of mineral sediment deposition sufficient to offset subsidence and rising sea level. This deficit has resulted in extended hydroperiods over the floodplain which could prevent tree regeneration and promote hypoxia.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of SEDHYD 2019","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"SEDHYD 2019 Conference","conferenceDate":"June 24-28, 2019","conferenceLocation":"Reno, NV","language":"English","publisher":"Federal Interagency Sedimentation Conference (FISC) and Federal Interagency Hydrologic Modeling Conference (FIHMC)","usgsCitation":"Kroes, D., Day, R.H., Demas, C.R., Allen, Y.C., and Roberts, S., 2019, Channel modification and evolution alter hydraulic connectivity in the Atchafalaya River basin increasing vulnerability to sea-level rise, <i>in</i> Proceedings of SEDHYD 2019, v. 1, Reno, NV, June 24-28, 2019, 11 p.","productDescription":"11 p.","ipdsId":"IP-104703","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":368657,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":368656,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.sedhyd.org/2019/#sedhyd-2019-proceedings"}],"country":"United States","state":"Louisiana","otherGeospatial":"Atchafalaya River Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -92.40325927734375,\n              29.685666670118724\n            ],\n            [\n              -91.14532470703125,\n              29.685666670118724\n            ],\n            [\n              -91.14532470703125,\n              30.850363469502362\n            ],\n            [\n              -92.40325927734375,\n              30.850363469502362\n            ],\n            [\n              -92.40325927734375,\n              29.685666670118724\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"1","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kroes, Daniel 0000-0001-9104-9077 dkroes@usgs.gov","orcid":"https://orcid.org/0000-0001-9104-9077","contributorId":3830,"corporation":false,"usgs":true,"family":"Kroes","given":"Daniel","email":"dkroes@usgs.gov","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":761356,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Day, Richard H. 0000-0002-5959-7054 dayr@usgs.gov","orcid":"https://orcid.org/0000-0002-5959-7054","contributorId":2427,"corporation":false,"usgs":true,"family":"Day","given":"Richard","email":"dayr@usgs.gov","middleInitial":"H.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":773980,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Demas, Charles R.","contributorId":36121,"corporation":false,"usgs":true,"family":"Demas","given":"Charles","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":773981,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Allen, Yvonne C.","contributorId":94403,"corporation":false,"usgs":true,"family":"Allen","given":"Yvonne","email":"","middleInitial":"C.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":false,"id":773982,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Roberts, Steve","contributorId":52674,"corporation":false,"usgs":true,"family":"Roberts","given":"Steve","affiliations":[],"preferred":false,"id":773983,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70203189,"text":"70203189 - 2019 - Sediment monitoring to support modeling a reservoir sediment flush on a sand-bed river in Northern Nebraska","interactions":[],"lastModifiedDate":"2022-01-12T15:29:09.638114","indexId":"70203189","displayToPublicDate":"2019-07-01T11:38:01","publicationYear":"2019","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Sediment monitoring to support modeling a reservoir sediment flush on a sand-bed river in Northern Nebraska","docAbstract":"The U.S. Geological Survey (USGS) in cooperation with the U.S. Army Corps of Engineers (USACE), monitored a sediment flush event from Spencer Dam located on the Niobrara River near Spencer, Nebraska, during the fall of 2014. Data collected during the flush was used to validate a one-dimensional sediment transport model developed by the USACE. The USACE surveyed 26 cross sections within the reservoir and as far as 1 kilometer (km) upstream from the reservoir pool to about 10 km downstream from the dam before and after the flushing event to measure erosion and deposition. They also collected surficial sediment samples from sandbars within the reservoir. The USGS assisted USACE in its model validation efforts by collecting sediment data before, during and after the flush using both traditional sampling techniques and a continuous laser-diffraction particle-size analyzer. From the context of longitudinal volumetric change, the model replicated erosion in the upper half of the reservoir within four percent of that observed by survey data and it replicated deposition downstream of the dam within 5 percent. However, the model underpredicted the erosion of the accumulated delta sediments in the reservoir by 43 percent. The timing and magnitude of suspended sediment concentrations produced by the model compared reasonably well to the discrete suspended-sediment sample results. These results indicate cross-sectional survey data and discrete sediment data may be adequate for developing sediment flush models for reservoirs in similar well-sorted sand-bed streams.\n\nThe USGS installed a continuous particle-size analyzer immediately downstream from the dam. Although the particle-size analyzer was successful in providing a large dataset during the flushing event, based on discrete point samples, it overestimated the amount of fine particles and underrepresented the amount of coarse material. It also required a significant amount of maintenance during the flushing event because of the large sediment load and the rapid bed aggradation. The maintenance issues with the particle-size analyzer along with uncertainty in the correlation to discrete suspended-sediment samples reduced its value for model validation. However, these issues may have been specific to the flushing event at Spencer Dam, which involved a sand-bed dominated stream and a wide channel. It is foreseeable that other sediment flush models developed for different streams with dissimilar sediment gradations may benefit from similar continuous sediment data, but adequate planning and evaluation should be performed.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of SEDHYD 2019","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"SEDHYD 2019 Conference","conferenceDate":"June 24-28, 2019","conferenceLocation":"Reno, NV","language":"English","publisher":"Federal Interagency Sedimentation Conference (FISC) and Federal Interagency Hydrologic Modeling Conference (FIHMC)","usgsCitation":"Schaepe, N.J., and Boyd, P.M., 2019, Sediment monitoring to support modeling a reservoir sediment flush on a sand-bed river in Northern Nebraska, <i>in</i> Proceedings of SEDHYD 2019, v. 2, Reno, NV, June 24-28, 2019, 14 p.","productDescription":"14 p.","ipdsId":"IP-105260","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":368654,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.sedhyd.org/2019/#sedhyd-2019-proceedings"},{"id":368655,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nebraska","city":"Spencer","otherGeospatial":"Niobara River, Spencer Dam","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -98.68452072143555,\n              42.79514872764227\n            ],\n            [\n              -98.61997604370117,\n              42.79514872764227\n            ],\n            [\n              -98.61997604370117,\n              42.81391436163743\n            ],\n            [\n              -98.68452072143555,\n              42.81391436163743\n            ],\n            [\n              -98.68452072143555,\n              42.79514872764227\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"2","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Schaepe, Nathaniel J. 0000-0003-1776-7411 nschaepe@usgs.gov","orcid":"https://orcid.org/0000-0003-1776-7411","contributorId":2377,"corporation":false,"usgs":true,"family":"Schaepe","given":"Nathaniel","email":"nschaepe@usgs.gov","middleInitial":"J.","affiliations":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"preferred":true,"id":761566,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boyd, Paul M","contributorId":215066,"corporation":false,"usgs":false,"family":"Boyd","given":"Paul","email":"","middleInitial":"M","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":761567,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70203325,"text":"70203325 - 2019 - Field-scale sediment feed flume: Upper Santa Ana River, California","interactions":[],"lastModifiedDate":"2022-01-12T15:29:35.164663","indexId":"70203325","displayToPublicDate":"2019-07-01T11:31:20","publicationYear":"2019","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Field-scale sediment feed flume: Upper Santa Ana River, California","docAbstract":"Along the San Bernardino Valley, the Santa Ana River decreases in slope, increases in width, and deposits particles from boulders to sand as it loses transport capacity. Episodic rainfalls feed very large winter floods, but dry summer and fall periods lead to extensive dry alluvial reaches due to surface water infiltration into subsurface aquifers. Within one of these dry reaches, a small inset channel has developed to effectively convey year-round wastewater discharges. This flow creates a coarse bed substrate composed of gravel and cobble that is home for diatoms and algae, the diet for the Santa Ana Sucker, a threatened native fish. \n\nField-based observations include:\n•\tShear stresses in the inset channel are capable of transporting sand as bedload, but not gravel and cobble. Bedload measurements (at several locations and times under wastewater discharge conditions) indicate that about 90% of the bedload is sand. The median grain size of bedload samples is consistently in the 0.5–1-mm range with little longitudinal variability.\n\n•\tThe upstream supply of sand decreases through time as winnowing proceeds in the downstream direction. Bedload transport rates increase in the downstream direction by an order of magnitude over just 7 km, despite the fact that water discharge decreases downstream due to infiltration (typically by 25–50% over the 7-km reach). \n\n•\tThe location of the gravel-to-sand bed transition is variable from year to year and is related to the amount of time that has elapsed since the most recent upstream runoff event. These events supply new sediment to the reach and reset the winnowing process.\n\n•\tDirect observations of the inset channel following upstream runoff events revealed many instances of large areas of substantial sand deposition in the channel, in areas that were previously entirely gravel and cobble sizes.\n\nWe propose a qualitative function to predict the bed substrate of the inset channel at any given time and location. A one-dimensional model of bedload transport and bed substrate in the study reach is being developed to quantify and test the predictive function. Preliminary results indicate that the winnowing process is quite sensitive to wastewater discharge levels. The calibrated model will be used to assess how treatment plant discharge scenarios might be used to strategically manage winnowing rates and the amount of gravel and cobble exposed on the bed in the reach.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of SEDHYD 2019","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"SEDHYD 2019 Conference","conferenceDate":"June 24-28, 2019","conferenceLocation":"Reno, NV","language":"English","publisher":"Federal Interagency Sedimentation Conference (FISC) and Federal Interagency Hydrologic Modeling Conference (FIHMC)","usgsCitation":"Wright, S., and Minear, J.T., 2019, Field-scale sediment feed flume: Upper Santa Ana River, California, <i>in</i> Proceedings of SEDHYD 2019, v. 1, Reno, NV, June 24-28, 2019, 2 p.","productDescription":"2 p.","ipdsId":"IP-107058","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":363507,"type":{"id":15,"text":"Index Page"},"url":"https://www.sedhyd.org/2019/#sedhyd-2019-proceedings"},{"id":368653,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Upper Santa Ana River Valley","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -117.44178771972656,\n              33.965572781967936\n            ],\n            [\n              -117.24128723144531,\n              33.965572781967936\n            ],\n            [\n              -117.24128723144531,\n              34.11407854333859\n            ],\n            [\n              -117.44178771972656,\n              34.11407854333859\n            ],\n            [\n              -117.44178771972656,\n              33.965572781967936\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"1","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Wright, Scott 0000-0002-0387-5713 sawright@usgs.gov","orcid":"https://orcid.org/0000-0002-0387-5713","contributorId":1536,"corporation":false,"usgs":true,"family":"Wright","given":"Scott","email":"sawright@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":762154,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Minear, J. Toby","contributorId":215361,"corporation":false,"usgs":false,"family":"Minear","given":"J.","email":"","middleInitial":"Toby","affiliations":[{"id":39229,"text":"Cooperative Institute for Research in Environmental Sciences, University of Colorado","active":true,"usgs":false}],"preferred":false,"id":762155,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70203958,"text":"70203958 - 2019 - Near-field remote sensing of Alaskan Rivers","interactions":[],"lastModifiedDate":"2019-10-17T11:29:25","indexId":"70203958","displayToPublicDate":"2019-07-01T11:24:13","publicationYear":"2019","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Near-field remote sensing of Alaskan Rivers","docAbstract":"The U.S. Geological Survey (USGS) Geomorphology and Sediment Transport Laboratory (GSTL), in collaboration with the U.S. Army Corps of Engineers Cold Regions Research and Engineering Laboratory (CRREL), acquired remotely sensed data from several Alaskan rivers in 2017 and 2018 with the goal of developing a methodology for measuring streamflow from a helicopter. CRREL operates a custom airborne lidar system that can be deployed in a helicopter-based pod (HeliPod). Data were collected with the HeliPod near existing USGS streamflow information stations on the Knik, Matanuska, Chena, and Salcha Rivers in both 2017 and 2018. Sites on the Tanana and Snow Rivers were added in 2018. In 2018, the HeliPod was modified to accommodate both a thermal infrared and a visible camera. The cameras were integrated with the flight management software to simultaneously acquire imagery with lidar. The Global Navigation Satellite System (GNSS) and inertial measurement unit (IMU) in the HeliPod were used to compute trajectories with precise position and orientation information needed for image orthorectification. The HeliPod sensors provide data for measuring river channel characteristics. Lidar can map the elevation of the water surface and thus be used to measure water-surface slopes and return intensity can be used to delineate the extent of the wetted river channel. Various approaches are currently being evaluated to estimate surface flow velocity from visible and thermal image time series. In this paper, we examine and compare water-surface elevation returns and slopes derived from the HeliPod lidar and found good agreement with measurements made using conventional field-based techniques.","conferenceTitle":"Federal Interagency Sedimentation and Hydrologic Modeling Conference (SEDHYD 2019)","conferenceDate":"June 24-28, 2019","conferenceLocation":"Reno, Nevada","language":"English","publisher":"Federal Interagency Sedimentation and Hydrologic Modeling Conference (SEDHYD 2019)","usgsCitation":"Kinzel, P.J., Legleiter, C.J., Nelson, J.M., Conaway, J., LeWinter, A., Gadomski, P., and Filiano, D., 2019, Near-field remote sensing of Alaskan Rivers, Federal Interagency Sedimentation and Hydrologic Modeling Conference (SEDHYD 2019), Reno, Nevada, June 24-28, 2019, 10 p.","productDescription":"10 p.","ipdsId":"IP-106032","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":368383,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":364998,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.sedhyd.org/2019/openconf/modules/request.php?module=oc_program&action=program.php&p=program"}],"country":"United States","state":"Alaska","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -153.3251953125,\n              59.085738569819505\n            ],\n            [\n              -144.3603515625,\n              59.085738569819505\n            ],\n            [\n              -144.3603515625,\n              66.47820814385636\n            ],\n            [\n              -153.3251953125,\n              66.47820814385636\n            ],\n            [\n              -153.3251953125,\n              59.085738569819505\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kinzel, Paul J. 0000-0002-6076-9730 pjkinzel@usgs.gov","orcid":"https://orcid.org/0000-0002-6076-9730","contributorId":743,"corporation":false,"usgs":true,"family":"Kinzel","given":"Paul","email":"pjkinzel@usgs.gov","middleInitial":"J.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":764968,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Legleiter, Carl J. 0000-0003-0940-8013 cjl@usgs.gov","orcid":"https://orcid.org/0000-0003-0940-8013","contributorId":169002,"corporation":false,"usgs":true,"family":"Legleiter","given":"Carl","email":"cjl@usgs.gov","middleInitial":"J.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":764969,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nelson, Jonathan M. 0000-0002-7632-8526 jmn@usgs.gov","orcid":"https://orcid.org/0000-0002-7632-8526","contributorId":2812,"corporation":false,"usgs":true,"family":"Nelson","given":"Jonathan","email":"jmn@usgs.gov","middleInitial":"M.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":764970,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Conaway, Jeff 0000-0002-3036-592X","orcid":"https://orcid.org/0000-0002-3036-592X","contributorId":214226,"corporation":false,"usgs":true,"family":"Conaway","given":"Jeff","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":764971,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"LeWinter, Adam","contributorId":192072,"corporation":false,"usgs":false,"family":"LeWinter","given":"Adam","affiliations":[],"preferred":false,"id":764972,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gadomski, Peter","contributorId":216532,"corporation":false,"usgs":false,"family":"Gadomski","given":"Peter","email":"","affiliations":[{"id":12537,"text":"USACE","active":true,"usgs":false}],"preferred":false,"id":764973,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Filiano, Dominic","contributorId":216533,"corporation":false,"usgs":false,"family":"Filiano","given":"Dominic","email":"","affiliations":[{"id":12537,"text":"USACE","active":true,"usgs":false}],"preferred":false,"id":764974,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70203891,"text":"70203891 - 2019 - Integrated hydrologic modeling of the Salinas River, California, for sustainable water management","interactions":[],"lastModifiedDate":"2022-01-12T15:30:43.909015","indexId":"70203891","displayToPublicDate":"2019-07-01T11:16:49","publicationYear":"2019","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Integrated hydrologic modeling of the Salinas River, California, for sustainable water management","docAbstract":"The Salinas River is the largest river in California’s Central Coast region. Groundwater resources of the Salinas River basin are used to meet water supply needs, including crop irrigation and municipal water supply. Two large multipurpose reservoirs also supply irrigation and municipal water uses. Historical imbalances between supply and demand have resulted in sinking groundwater levels, seawater intrusion, regulatory actions on pumping, adjudication, and requirements for minimum in-stream fish flows. Present needs include finding replacement water supplies and improving watershed management to comply with legal mandates, adapt to future climate variability and landuse conversions, and improve environmental conditions. The Salinas Valley Integrated Hydrologic Model (SVIHM) was developed to help water managers evaluate and adjust to projected impacts on water supplies and demands in the Salinas Valley watershed caused by changes in land use, population, and climate. The SVIHM includes four modeling components: (1) the Basin Characterization Model (BCM), (2) the Hydrologic Simulation Program – FORTRAN (HSPF), (3) MODFLOW - One Water Hydrologic Model (MF-OWHM), and (4) the Surface Water Operations (SWO) package.  The BCM and HSPF components compose the Salinas Valley Watershed Model (SVWM). The 4,530 square-mile (mi2) SVWM domain encompasses the entire Salinas River watershed, as well as coastal drainages adjacent to the Salinas River outflow, and includes two separate and connected HSPF model domains, the 2,540 mi2 upper Salinas River and the 1,990 mi2 lower Salinas River models. SVWM (1) simulates the water budget for the entire Salinas River basin containing both the SVIHM domain as well as the mountainous terrain of the tributary headwater areas not included in the SVIHM; and (2) was used to develop the 148 boundary inflows for the SVIHM. Simulated evapotranspiration (ET) is the largest component of the water budget after precipitation, with a 71-year average basin-wide ET of 13.9 in/yr, compared to the basin-wide average precipitation of 18.4 in/yr. Simulated ET ranges from 15 to 29 in/yr along the western side of the SVWM to less than 10 in/yr throughout the valley floor and in the southeast part of the Salinas River watershed. The simulated total 71-year average inflow to the SVIHM was 890 ft3/sec (about 640,000 acre-feet per year), with the highest average inflow of 270 ft3/sec simulated for the Nacimiento River; whereas, the simulated 71-year average streamflow at the mouth of the Salinas River was only about 190 ft3/sec, indicating that most of the streamflow generated in the Salinas River basin is lost to channel seepage. The lack of sustained baseflow causes streamflow to be highly sensitive to the temporal variability in precipitation, especially during the drier periods, and this increases the importance of developing adequate reservoir management, flow augmentation, and conjunctive water use scenarios for potential future drought periods and potentially increased temporal variability in precipitation.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of SEDHYD 2019","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"SEDHYD 2019 Conference","conferenceDate":"June 24-28, 2019","conferenceLocation":"Reno, NV","language":"English","publisher":"Federal Interagency Sedimentation Conference (FISC) and Federal Interagency Hydrologic Modeling Conference (FIHMC)","usgsCitation":"Hevesi, J.A., Henson, W.R., Hanson, R.T., and Boyce, S.E., 2019, Integrated hydrologic modeling of the Salinas River, California, for sustainable water management, <i>in</i> Proceedings of SEDHYD 2019, v. 4, Reno, NV, June 24-28, 2019, 15 p.","productDescription":"15 p.","ipdsId":"IP-107062","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":364813,"type":{"id":15,"text":"Index Page"},"url":"https://www.sedhyd.org/2019/#sedhyd-2019-proceedings"},{"id":368648,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Salinas River Valley","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -121.4044189453125,\n              36.796089518731506\n            ],\n            [\n              -121.607666015625,\n              36.96744946416934\n            ],\n            [\n              -121.98669433593749,\n              36.54936246839778\n            ],\n            [\n              -120.8770751953125,\n              35.39352808136067\n            ],\n            [\n              -119.65209960937501,\n              35.25459097465022\n            ],\n            [\n              -121.4044189453125,\n              36.796089518731506\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"4","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hevesi, Joseph 0000-0003-2898-1800 jhevesi@usgs.gov","orcid":"https://orcid.org/0000-0003-2898-1800","contributorId":1507,"corporation":false,"usgs":true,"family":"Hevesi","given":"Joseph","email":"jhevesi@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":764610,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Henson, Wesley R. 0000-0003-4962-5565 whenson@usgs.gov","orcid":"https://orcid.org/0000-0003-4962-5565","contributorId":384,"corporation":false,"usgs":true,"family":"Henson","given":"Wesley","email":"whenson@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":764611,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hanson, Randall T. 0000-0002-9819-7141 rthanson@usgs.gov","orcid":"https://orcid.org/0000-0002-9819-7141","contributorId":801,"corporation":false,"usgs":true,"family":"Hanson","given":"Randall","email":"rthanson@usgs.gov","middleInitial":"T.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":764612,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Boyce, Scott 0000-0003-0626-9492 seboyce@usgs.gov","orcid":"https://orcid.org/0000-0003-0626-9492","contributorId":4766,"corporation":false,"usgs":true,"family":"Boyce","given":"Scott","email":"seboyce@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":764613,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70216496,"text":"70216496 - 2019 - Measurement of sounds emitted by certain high-resolution geophysical survey systems","interactions":[],"lastModifiedDate":"2020-11-23T17:15:21.846135","indexId":"70216496","displayToPublicDate":"2019-07-01T11:12:00","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1941,"text":"IEEE Journal of Oceanic Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Measurement of sounds emitted by certain high-resolution geophysical survey systems","docAbstract":"<p><span>Scientific questions regarding the impact of anthropomorphic noise in the marine environment have resulted in an increasing number of regulatory requirements and precautionary mitigation strategies to reduce the risks associated with high-resolution marine geophysical surveys performed in waters subjected to government jurisdiction. An example of regulatory frameworks includes the Marine Mammal Protection Act in the United States and the Marine Strategy Framework Directive 2008/56/EC in the European Union. Regulatory compliance often requires an assessment of the potential ecological risks before initiating a marine geophysical survey. However, the acoustic source data needed to estimate the risk associated with the operation of a given high-resolution survey system are frequently lacking. A comprehensive measurement program was performed to quantify the characteristics of sounds radiated by a variety of commercial marine geophysical survey systems, including boomers, sparkers, airguns, chirp sub-bottom profilers, sidescan sonars, and swath-bathymetric sonars [Crocker and Fratantonio, “Characteristics of high-frequency sounds emitted during high-resolution marine geophysical surveys,” Naval Undersea Warfare Center, Newport, RI, USA, NUWC-NPT Tech. Rep. 12, 203, 2016]. Calibrated acoustic source data, including source levels, source spectra, and beam patterns, were acquired for a total of 18 different marine geophysical survey systems. The data support modeling to estimate the potential ecological impacts resulting from the operation of certain high-resolution marine geophysical survey systems.</span></p>","language":"English","publisher":"IEEE","doi":"10.1109/JOE.2018.2829958","usgsCitation":"Crocker, S.E., Fratantonio, F.D., Hart, P.E., Foster, D.S., O’Brien, T.F., and Labak, S., 2019, Measurement of sounds emitted by certain high-resolution geophysical survey systems: IEEE Journal of Oceanic Engineering, v. 44, no. 3, p. 796-813, https://doi.org/10.1109/JOE.2018.2829958.","productDescription":"18 p.","startPage":"796","endPage":"813","ipdsId":"IP-085103","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":467490,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1109/joe.2018.2829958","text":"Publisher Index Page"},{"id":380704,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"44","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Crocker, Steven E","contributorId":245144,"corporation":false,"usgs":false,"family":"Crocker","given":"Steven","email":"","middleInitial":"E","affiliations":[{"id":49092,"text":"Naval Undersea Warfare Center,","active":true,"usgs":false}],"preferred":false,"id":805438,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fratantonio, Frank D","contributorId":245145,"corporation":false,"usgs":false,"family":"Fratantonio","given":"Frank","email":"","middleInitial":"D","affiliations":[{"id":49092,"text":"Naval Undersea Warfare Center,","active":true,"usgs":false}],"preferred":false,"id":805439,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hart, Patrick E. 0000-0002-5080-1426 hart@usgs.gov","orcid":"https://orcid.org/0000-0002-5080-1426","contributorId":2879,"corporation":false,"usgs":true,"family":"Hart","given":"Patrick","email":"hart@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":805440,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Foster, David S. 0000-0003-1205-0884 dfoster@usgs.gov","orcid":"https://orcid.org/0000-0003-1205-0884","contributorId":1320,"corporation":false,"usgs":true,"family":"Foster","given":"David","email":"dfoster@usgs.gov","middleInitial":"S.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":805441,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"O’Brien, Thomas F. 0000-0003-0906-8450 tobrien@usgs.gov","orcid":"https://orcid.org/0000-0003-0906-8450","contributorId":4151,"corporation":false,"usgs":true,"family":"O’Brien","given":"Thomas","email":"tobrien@usgs.gov","middleInitial":"F.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":805442,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Labak, Stanley","contributorId":245146,"corporation":false,"usgs":false,"family":"Labak","given":"Stanley","email":"","affiliations":[{"id":49093,"text":"Bureau of Ocean Energy Management,","active":true,"usgs":false}],"preferred":false,"id":805443,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70227424,"text":"70227424 - 2019 - Characterization of hydrology and sediment transport following drought and wildfire in Cache Creek, California","interactions":[],"lastModifiedDate":"2022-01-14T16:47:03.777945","indexId":"70227424","displayToPublicDate":"2019-07-01T10:39:51","publicationYear":"2019","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Characterization of hydrology and sediment transport following drought and wildfire in Cache Creek, California","docAbstract":"The worst drought in California in over 1,200 years occurred between 2012-2017 (Griffin, 2014), depleting surface water and groundwater supply and drying out the soils past wilting point. In the summer of 2015, the Jerusalem and Rocky fires burned roughly 40,000 acres within the Cache Creek watershed. To fully characterize the post-fire effects in the Cache Creek watershed, an hourly model of streamflow and sediment transport was developed using the Hydrological Simulation Program – FORTRAN (HSPF). This model requires air temperature, precipitation, and potential evapotranspiration as climate inputs. Hourly station data are sparse in the area and may not capture the variability of elevation and local climatology patterns within the watershed. \n\nA technique used previously to spatially-interpolate daily-climate station data has improved the characterization of local and regional climate patterns on a daily scale in areas with sparse data (Flint et al., 2014). This technique was extended to hourly observed data to produce spatially-varying climate inputs for the Cache Creek hydrologic model to run as a continuous multi-year simulation with hourly time steps. Monthly PRISM grids were used in a two-step scaling method with climate Gradient and Inverse Distance Squared (GIDS) maps (Nalder and Wein, 1998) to develop daily grids, then the daily grids were used to scale hourly climate GIDS maps. This method captures the temporal variability at each climate station yet preserves the regional monthly spatial structure of the PRISM data.\n\nHydrologic calibration used data from water year 2015, and validation used the same parameters for water year 2016. The model was run through water year 2017 to characterize the effects of wildfire on hydrology and sediment transport. For final simulations, the model was run at an hourly time step from June 2014 through September 2017 to ensure a model initiation period of 4 months prior to the target simulation period used for analysis. Sediment parameters were initially set using the existing Sacramento River Basin model for this sub-watershed area and then iteratively adjusted in the calibration process. To simulate a fire across the landscape, sediment parameters for water years 2016-17 were further modified for burned sub-basins to represent post-fire vegetation and soils in 2016, then partial recovery in 2017. \n\nResults were inconclusive for drought and wildfire effects on runoff. Modeled peak flows generally underpredicted observed peak flows; however, the modeled storm volumes were only slightly under or over the observed storm volumes. Sediment transport was sensitive to the watershed disturbances and R^2 values for daily mean suspended concentrations (SSC) and sediment discharge were 0.70 and 0.75, respectively.  Simulated hourly values correlated less strongly with observed instantaneous SSC and sediment discharge (R^2 values of 0.56 and 0.46, respectively).","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of SEDHYD 2019","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"SEDHYD 2019 Conference","conferenceDate":"June 24-28, 2019","conferenceLocation":"Reno, NV","language":"English","publisher":"Federal Interagency Sedimentation Conference (FISC) and Federal Interagency Hydrologic Modeling Conference (FIHMC)","usgsCitation":"Stern, M.A., Flint, L.E., and Flint, A.L., 2019, Characterization of hydrology and sediment transport following drought and wildfire in Cache Creek, California, <i>in</i> Proceedings of SEDHYD 2019, v. 5, Reno, NV, June 24-28, 2019, 8 p.","productDescription":"8 p.","ipdsId":"IP-107472","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":394386,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":394372,"type":{"id":15,"text":"Index Page"},"url":"https://www.sedhyd.org/2019/#sedhyd-2019-proceedings"}],"country":"United States","state":"California","otherGeospatial":"Cache Creek","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.76397705078124,\n              38.792626957868904\n            ],\n            [\n              -122.36297607421874,\n              38.792626957868904\n            ],\n            [\n              -122.36297607421874,\n              39.17478791493289\n            ],\n            [\n              -122.76397705078124,\n              39.17478791493289\n            ],\n            [\n              -122.76397705078124,\n              38.792626957868904\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"5","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Stern, Michelle A. 0000-0003-3030-7065 mstern@usgs.gov","orcid":"https://orcid.org/0000-0003-3030-7065","contributorId":4244,"corporation":false,"usgs":true,"family":"Stern","given":"Michelle","email":"mstern@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":830818,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Flint, Lorraine E. 0000-0002-7868-441X lflint@usgs.gov","orcid":"https://orcid.org/0000-0002-7868-441X","contributorId":1184,"corporation":false,"usgs":true,"family":"Flint","given":"Lorraine","email":"lflint@usgs.gov","middleInitial":"E.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":830819,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Flint, Alan L. 0000-0002-5118-751X aflint@usgs.gov","orcid":"https://orcid.org/0000-0002-5118-751X","contributorId":1492,"corporation":false,"usgs":true,"family":"Flint","given":"Alan","email":"aflint@usgs.gov","middleInitial":"L.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":830820,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70204519,"text":"70204519 - 2019 - Evaluation of environmental DNA surveys for identifying occupancy and spatial distribution of Pacific Lamprey (Entosphenus tridentatus) and Lampetra spp. in a Washington coast watershed","interactions":[],"lastModifiedDate":"2019-08-01T09:06:53","indexId":"70204519","displayToPublicDate":"2019-07-01T09:04:41","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5840,"text":"Environmental DNA","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of environmental DNA surveys for identifying occupancy and spatial distribution of Pacific Lamprey (Entosphenus tridentatus) and Lampetra spp. in a Washington coast watershed","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Surveys of environmental DNA (eDNA) have become an important and multifaceted tool for monitoring and identifying distributions and occupancy of aquatic species. This tool is attractive because it is powerful, easy to apply, and provides an alternative to traditional field survey methods. However, validating eDNA survey methods against traditional field survey methods is warranted prior to their application. We used eDNA and electrofishing to survey 10 sites in 3 tributaries of the Chehalis River, Washington, to infer distribution and occupancy of<span>&nbsp;</span><i>Entosphenus tridentatus</i><span>&nbsp;</span>and<span>&nbsp;</span><i>Lampetra</i><span>&nbsp;</span>spp. Both methods produced similar detection rates for<span>&nbsp;</span><i>E</i>.<span>&nbsp;</span><i>tridentatus</i>, and<span>&nbsp;</span><i>Lampetra</i><span>&nbsp;</span>spp. were detected at slightly greater frequency with eDNA in the Black River and Skookumchuck River. Within each of the three tributaries, eDNA concentration was negatively related to sample distance from the Chehalis River mainstem for<span>&nbsp;</span><i>E</i>.<span>&nbsp;</span><i>tridentatus</i><span>&nbsp;</span>but not for<span>&nbsp;</span><i>Lampetra</i><span>&nbsp;</span>spp., which indicates<span>&nbsp;</span><i>E</i>.<span>&nbsp;</span><i>tridentatus</i><span>&nbsp;</span>and<span>&nbsp;</span><i>Lampetra</i><span>&nbsp;</span>spp. may be distributed differently within tributaries. Application of lamprey eDNA data to a multiscale occupancy model indicated high probability of detecting eDNA in water samples and quantitative PCR (qPCR) assays. Broad distribution and high detection of<span>&nbsp;</span><i>E. tridentatus</i><span>&nbsp;</span>and<span>&nbsp;</span><i>Lampetra</i><span>&nbsp;</span>spp. suggest robust populations inhabit the Chehalis River basin. Our findings suggest eDNA surveys may be comparable to electrofishing for informing lamprey occupancy and distributions. Such sampling is efficient and cost‐effective and we anticipate that eDNA surveys will become a valuable tool in addressing key research and monitoring needs for conservation and restoration of lampreys in general.</p></div></div><div id=\"edn315-sec-0001\" class=\"article-section__content\"><br data-mce-bogus=\"1\"></div>","language":"English","publisher":"Wiley","doi":"10.1002/edn3.15","usgsCitation":"Ostberg, C., Chase, D.M., Hoy, M., Duda, J., Hayes, M., Jolley, J., Silver, G.S., and Cook-Tabor, C., 2019, Evaluation of environmental DNA surveys for identifying occupancy and spatial distribution of Pacific Lamprey (Entosphenus tridentatus) and Lampetra spp. in a Washington coast watershed: Environmental DNA, v. 1, no. 2, p. 131-143, https://doi.org/10.1002/edn3.15.","productDescription":"13 p.","startPage":"131","endPage":"143","ipdsId":"IP-103297","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":467493,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/edn3.15","text":"Publisher Index Page"},{"id":437399,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ZU4EU7","text":"USGS data release","linkHelpText":"2015 environmental DNA surveys for lampreys in Chehalis River tributaries, Washington"},{"id":366062,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":366052,"type":{"id":15,"text":"Index Page"},"url":"https://ecos.fws.gov/ServCat/"}],"country":"United States","state":"Washington","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -126.177978515625,\n              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Center","active":true,"usgs":true}],"preferred":true,"id":767374,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chase, Dorothy Murphy","contributorId":217722,"corporation":false,"usgs":true,"family":"Chase","given":"Dorothy","email":"","middleInitial":"Murphy","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":767375,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hoy, Marshal 0000-0003-2828-9697 mhoy@usgs.gov","orcid":"https://orcid.org/0000-0003-2828-9697","contributorId":217723,"corporation":false,"usgs":true,"family":"Hoy","given":"Marshal","email":"mhoy@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":767376,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Duda, Jeff","contributorId":217724,"corporation":false,"usgs":true,"family":"Duda","given":"Jeff","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":767377,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hayes, Michael 0000-0002-9060-0565 mhayes@usgs.gov","orcid":"https://orcid.org/0000-0002-9060-0565","contributorId":217725,"corporation":false,"usgs":true,"family":"Hayes","given":"Michael","email":"mhayes@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":767378,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jolley, Jeffrey","contributorId":217726,"corporation":false,"usgs":true,"family":"Jolley","given":"Jeffrey","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":767379,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Silver, Gregory S","contributorId":214023,"corporation":false,"usgs":false,"family":"Silver","given":"Gregory","email":"","middleInitial":"S","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":767380,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Cook-Tabor, Carrie","contributorId":214025,"corporation":false,"usgs":false,"family":"Cook-Tabor","given":"Carrie","email":"","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":767381,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70208749,"text":"70208749 - 2019 - Combining numerical and statistical models to predict storm-induced dune erosion","interactions":[],"lastModifiedDate":"2020-02-28T06:35:00","indexId":"70208749","displayToPublicDate":"2019-07-01T06:32:57","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5739,"text":"Journal of Geophysical Research: Earth Surface","onlineIssn":"2169-9011","active":true,"publicationSubtype":{"id":10}},"title":"Combining numerical and statistical models to predict storm-induced dune erosion","docAbstract":"Dune erosion is an important aspect to consider when assessing coastal flood risk, as dune elevation loss makes the protected areas more susceptible to flooding. However, most advanced dune erosion numerical models are computationally expensive, which hinders their application in early-warning systems. Based on a combination of probabilistic and process-based numerical modeling, we develop an efficient statistical tool to predict dune erosion during storms. The analysis focuses on Dauphin Island, AL in the northern Gulf of Mexico, where we combine synthetic sea storms with a calibrated and validated XBeach model to develop and test a range of different surrogate models for their ability to predict barrier-island geometric parameters under storm conditions. Surrogate models are developed by combining the oceanographic forcing from 100 optimally sampled sea-storm events covering the entire multivariate parameter space (used as XBeach input) and associated changes in the dune system (XBeach output). We test four surrogate models using a k-fold approach for validation. All models perform well in predicting changes in dune elevation, barrier-island area, and width, but are less accurate in predicting alterations in the cross-shore locations of dune morphological features. Multivariate adaptive regression splines are identified as the best surrogate model based on their fast development and good performance, attaining a modified Mielke index of 0.81 for dune crest height. As demonstrated at Dauphin Island, our approach shows potential to be used in an operational framework to predict dune response (in particular crest elevation change) when water level and wave forecasts are available.","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2019JF005016","usgsCitation":"Malagon-Santos, V., Wahl, T., Long, J.W., Passeri, D., and Plant, N.G., 2019, Combining numerical and statistical models to predict storm-induced dune erosion: Journal of Geophysical Research: Earth Surface, v. 124, no. 7, p. 1817-1834, https://doi.org/10.1029/2019JF005016.","productDescription":"18 p.","startPage":"1817","endPage":"1834","ipdsId":"IP-108807","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":372719,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alabama","otherGeospatial":"Dauphin Island","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -88.22021484375,\n              30.219321866895765\n            ],\n            [\n              -88.06503295898438,\n              30.219321866895765\n            ],\n            [\n              -88.06503295898438,\n              30.278044377800153\n            ],\n            [\n              -88.22021484375,\n              30.278044377800153\n            ],\n            [\n              -88.22021484375,\n              30.219321866895765\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"124","issue":"7","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2019-07-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Malagon-Santos, Victor","contributorId":216004,"corporation":false,"usgs":false,"family":"Malagon-Santos","given":"Victor","email":"","affiliations":[{"id":18879,"text":"University of Central Florida","active":true,"usgs":false}],"preferred":false,"id":783266,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wahl, Thomas","contributorId":141017,"corporation":false,"usgs":false,"family":"Wahl","given":"Thomas","email":"","affiliations":[{"id":13653,"text":"University South Florida","active":true,"usgs":false}],"preferred":false,"id":783267,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Long, Joseph W","contributorId":216005,"corporation":false,"usgs":false,"family":"Long","given":"Joseph","email":"","middleInitial":"W","affiliations":[{"id":32398,"text":"University of North Carolina Wilmington","active":true,"usgs":false}],"preferred":false,"id":783268,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Passeri, Davina L. 0000-0002-9760-3195 dpasseri@usgs.gov","orcid":"https://orcid.org/0000-0002-9760-3195","contributorId":166889,"corporation":false,"usgs":true,"family":"Passeri","given":"Davina","email":"dpasseri@usgs.gov","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":783265,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Plant, Nathaniel G. 0000-0002-5703-5672 nplant@usgs.gov","orcid":"https://orcid.org/0000-0002-5703-5672","contributorId":3503,"corporation":false,"usgs":true,"family":"Plant","given":"Nathaniel","email":"nplant@usgs.gov","middleInitial":"G.","affiliations":[{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":783269,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70208422,"text":"70208422 - 2019 - Seismic design and hazard maps: Before and after","interactions":[],"lastModifiedDate":"2020-02-10T17:56:45","indexId":"70208422","displayToPublicDate":"2019-06-30T17:54:07","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5928,"text":"Structure","active":true,"publicationSubtype":{"id":10}},"title":"Seismic design and hazard maps: Before and after","docAbstract":"<p>The 1994 Northridge earthquake generated world-record ground motions. At the time, the horizontal peak ground acceleration of 1.8<span>&nbsp;</span><i>g</i><span>&nbsp;</span>measured by a seismometer in Tarzana was the largest ever. The same is true of the peak ground velocity of 148 cm/s measured in Granada Hills. Both measurements were within approximately 15 km of the source of the earthquake; they were also near most of the damage described in other articles of this series.<span>&nbsp;</span><span id=\"more-14562\"></span>Consequently, the near-source design forces from the seismic zone maps in the<span>&nbsp;</span><i>Uniform Building Code</i><span>&nbsp;</span>(UBC) were increased. From the 1994 to 1997 editions, acceleration- and velocity-related near-source factors were introduced. The factors increased the design forces in Zone 4, already the highest seismic zone, by a multiplier as large as 2.0. More enduringly, generational changes were made to the seismic design maps in the NEHRP<span>&nbsp;</span><i>Recommended Seismic Provisions for New Buildings and Other Structures</i>. The NEHRP maps were – and continue to be – adopted into the<span>&nbsp;</span><i>International Building Code</i><span>&nbsp;</span>(IBC), which supplanted the UBC and other model building codes. As described below, the changes to the NEHRP maps took advantage of another post-Northridge change: the modern generation of U.S. Geological Survey (USGS) National Seismic Hazard Maps.</p>","language":"English","publisher":"National Council of Structural Engineers Associations","usgsCitation":"Luco, N., 2019, Seismic design and hazard maps: Before and after: Structure, p. 28-30.","productDescription":"3 p.","startPage":"28","endPage":"30","ipdsId":"IP-106546","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":372201,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":372155,"type":{"id":15,"text":"Index Page"},"url":"https://www.structuremag.org/?p=14562"}],"country":"United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"geometry\": {\n        \"type\": \"MultiPolygon\",\n        \"coordinates\": 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-75.07183,\n                38.78203\n              ],\n              [\n                -75.05673,\n                38.40412\n              ],\n              [\n                -75.37747,\n                38.01551\n              ],\n              [\n                -75.94023,\n                37.21689\n              ],\n              [\n                -76.03127,\n                37.2566\n              ],\n              [\n                -75.72205,\n                37.93705\n              ],\n              [\n                -76.23287,\n                38.31921\n              ],\n              [\n                -76.35,\n                39.15\n              ],\n              [\n                -76.54272,\n                38.71762\n              ],\n              [\n                -76.32933,\n                38.08326\n              ],\n              [\n                -76.99,\n                38.23999\n              ],\n              [\n                -76.30162,\n                37.91794\n              ],\n              [\n                -76.25874,\n                36.9664\n              ],\n              [\n                -75.9718,\n                36.89726\n              ],\n              [\n                -75.86804,\n                36.55125\n              ],\n              [\n                -75.72749,\n                35.55074\n              ],\n              [\n                -76.36318,\n                34.80854\n              ],\n              [\n                -77.39763,\n                34.51201\n              ],\n              [\n                -78.05496,\n                33.92547\n              ],\n              [\n                -78.55435,\n                33.86133\n              ],\n              [\n                -79.06067,\n                33.49395\n              ],\n              [\n                -79.20357,\n                33.15839\n              ],\n              [\n                -80.30132,\n                32.50935\n              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    [\n                -85.28784,\n                29.68612\n              ],\n              [\n                -85.7731,\n                30.15261\n              ],\n              [\n                -86.4,\n                30.4\n              ],\n              [\n                -87.53036,\n                30.27433\n              ],\n              [\n                -88.41782,\n                30.3849\n              ],\n              [\n                -89.18049,\n                30.31598\n              ],\n              [\n                -89.59383,\n                30.15999\n              ],\n              [\n                -89.41373,\n                29.89419\n              ],\n              [\n                -89.43,\n                29.48864\n              ],\n              [\n                -89.21767,\n                29.29108\n              ],\n              [\n                -89.40823,\n                29.15961\n              ],\n              [\n                -89.77928,\n                29.30714\n              ],\n              [\n                -90.15463,\n                29.11743\n              ],\n              [\n                -90.88022,\n                29.14854\n              ],\n              [\n                -91.62678,\n                29.677\n              ],\n              [\n                -92.49906,\n                29.5523\n              ],\n              [\n                -93.22637,\n                29.78375\n              ],\n              [\n                -93.84842,\n                29.71363\n              ],\n              [\n                -94.69,\n                29.48\n              ],\n              [\n                -95.60026,\n                28.73863\n              ],\n              [\n                -96.59404,\n                28.30748\n              ],\n              [\n                -97.14,\n                27.83\n              ],\n              [\n                -97.37,\n                27.38\n              ],\n              [\n                -97.38,\n                26.69\n              ],\n              [\n                -97.33,\n                26.21\n              ],\n              [\n                -97.14,\n                25.87\n              ],\n              [\n                -97.53,\n                25.84\n              ],\n              [\n                -98.24,\n                26.06\n              ],\n              [\n                -99.02,\n                26.37\n              ],\n              [\n                -99.3,\n                26.84\n              ],\n              [\n                -99.52,\n                27.54\n              ],\n              [\n                -100.11,\n                28.11\n              ],\n              [\n                -100.45584,\n                28.69612\n              ],\n              [\n                -100.9576,\n                29.38071\n              ],\n              [\n                -101.6624,\n                29.7793\n              ],\n              [\n                -102.48,\n                29.76\n              ],\n              [\n                -103.11,\n                28.97\n              ],\n              [\n                -103.94,\n                29.27\n              ],\n              [\n                -104.45697,\n                29.57196\n              ],\n              [\n                -104.70575,\n                30.12173\n              ],\n              [\n                -105.03737,\n                30.64402\n              ],\n              [\n                -105.63159,\n                31.08383\n              ],\n              [\n                -106.1429,\n                31.39995\n              ],\n              [\n                -106.50759,\n                31.75452\n              ],\n              [\n                -108.24,\n                31.75485\n              ],\n              [\n                -108.24194,\n                31.34222\n              ],\n              [\n                -109.035,\n                31.34194\n              ],\n              [\n                -111.02361,\n                31.33472\n              ],\n              [\n                -113.30498,\n                32.03914\n              ],\n              [\n                -114.815,\n                32.52528\n              ],\n              [\n                -114.72139,\n                32.72083\n              ],\n              [\n                -115.99135,\n                32.61239\n              ],\n              [\n                -117.12776,\n                32.53534\n              ],\n              [\n                -117.29594,\n                33.04622\n              ],\n              [\n                -117.944,\n                33.62124\n              ],\n              [\n                -118.4106,\n                33.74091\n              ],\n              [\n                -118.51989,\n                34.02778\n              ],\n              [\n                -119.081,\n                34.078\n              ],\n              [\n                -119.43884,\n                34.34848\n              ],\n              [\n                -120.36778,\n                34.44711\n              ],\n              [\n                -120.62286,\n                34.60855\n              ],\n              [\n                -120.74433,\n                35.15686\n              ],\n              [\n                -121.71457,\n                36.16153\n              ],\n              [\n                -122.54747,\n                37.55176\n              ],\n              [\n                -122.51201,\n                37.78339\n              ],\n              [\n                -122.95319,\n                38.11371\n              ],\n              [\n                -123.7272,\n                38.95166\n              ],\n              [\n                -123.86517,\n                39.76699\n              ],\n              [\n                -124.39807,\n                40.3132\n              ],\n              [\n                -124.17886,\n                41.14202\n              ],\n              [\n                -124.2137,\n                41.99964\n              ],\n              [\n                -124.53284,\n                42.76599\n              ],\n              [\n                -124.14214,\n                43.70838\n              ],\n              [\n                -124.02053,\n                44.6159\n              ],\n              [\n                -123.89893,\n                45.52341\n              ],\n              [\n                -124.07963,\n                46.86475\n              ],\n              [\n                -124.39567,\n                47.72017\n              ],\n              [\n                -124.68721,\n                48.18443\n              ],\n              [\n                -124.5661,\n                48.37971\n              ],\n              [\n                -123.12,\n                48.04\n              ],\n              [\n                -122.58736,\n                47.096\n              ],\n              [\n                -122.34,\n                47.36\n              ],\n              [\n                -122.5,\n                48.18\n              ],\n              [\n                -122.84,\n                49\n              ],\n              [\n                -120,\n                49\n              ],\n              [\n                -117.03121,\n                49\n              ],\n              [\n                -116.04818,\n                49\n              ],\n              [\n                -113,\n                49\n              ],\n              [\n                -110.05,\n                49\n              ],\n              [\n                -107.05,\n                49\n              ],\n              [\n                -104.04826,\n                48.99986\n              ],\n              [\n                -100.65,\n                49\n              ],\n              [\n                -97.22872,\n                49.0007\n              ],\n              [\n                -95.15907,\n                49\n              ],\n              [\n                -95.15609,\n                49.38425\n              ],\n              [\n                -94.81758,\n                49.38905\n              ]\n            ]\n          ]\n        ]\n      },\n      \"properties\": {\n        \"name\": \"United States\"\n      }\n    }\n  ]\n}","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Luco, Nico 0000-0002-5763-9847 nluco@usgs.gov","orcid":"https://orcid.org/0000-0002-5763-9847","contributorId":145730,"corporation":false,"usgs":true,"family":"Luco","given":"Nico","email":"nluco@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":781818,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70209570,"text":"70209570 - 2019 - Climate change adaptation for coastal national wildlife refuges","interactions":[],"lastModifiedDate":"2020-12-14T17:53:28.904407","indexId":"70209570","displayToPublicDate":"2019-06-30T11:52:13","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":9,"text":"Other Report"},"seriesTitle":{"id":7461,"text":"Final Project Memorandum","active":true,"publicationSubtype":{"id":9}},"title":"Climate change adaptation for coastal national wildlife refuges","docAbstract":"<p>National Wildlife Refuges (NWRs) along the East Coast of the United States protect habitat for a host of wildlife species, while also offering storm surge protection, improving water quality, supporting nurseries for commercially important fish and shellfish, and providing recreation opportunities for coastal communities. Yet in the last century, coastal ecosystems in the eastern U.S. have been severely altered by human development activities as well as sea-level rise and more frequent extreme events related to climate change. These influences threaten the ability of NWRs to protect our nation’s natural resources and to sustain their many beneficial services.</p><p>Through this project, researchers are collaborating with managers of the North Carolina Coastal Refuges Complex, Cape Romain NWR, South Carolina, and other local interested partners to assist with their long-term planning under uncertain conditions regarding sea-level rise and other global change processes. Researchers are using a variety of state-of-the-art approaches, including formal decision science for systematically analyzing management alternatives and scenario planning methods for engaging with stakeholders to explore possible futures. These approaches are aimed at helping NWR staff develop management objectives, identify and weigh potential management actions for adaptation, and generate decision-support tools and models. Outcomes and products from these efforts will aid managers as they plan for and adapt to the complex challenges facing the NWR system as changing climate&nbsp;and other conditions make their work increasingly more difficult.</p>","language":"English","publisher":"Southeast Climate Adaptation Science Center","usgsCitation":"Eaton, M.J., Costanza, J.K., Johnson, F.A., Martin, J., and Taylor, L., 2019, Climate change adaptation for coastal national wildlife refuges: Final Project Memorandum, 12 p.","productDescription":"12 p.","ipdsId":"IP-115967","costCenters":[{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true},{"id":40926,"text":"Southeast Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":381264,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":381263,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://cascprojects.org/#/project/4f8c6557e4b0546c0c397b4c/553fddf0e4b0a658d7938ef5"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Eaton, Mitchell J. 0000-0001-7324-6333","orcid":"https://orcid.org/0000-0001-7324-6333","contributorId":213526,"corporation":false,"usgs":true,"family":"Eaton","given":"Mitchell","middleInitial":"J.","affiliations":[{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":786933,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Costanza, Jennifer K.","contributorId":176907,"corporation":false,"usgs":false,"family":"Costanza","given":"Jennifer","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":786934,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Fred A 0000-0002-5854-3695","orcid":"https://orcid.org/0000-0002-5854-3695","contributorId":224058,"corporation":false,"usgs":false,"family":"Johnson","given":"Fred","email":"","middleInitial":"A","affiliations":[{"id":37318,"text":"Aarhus University","active":true,"usgs":false}],"preferred":false,"id":786935,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Martin, Julien 0000-0002-7375-129X","orcid":"https://orcid.org/0000-0002-7375-129X","contributorId":218445,"corporation":false,"usgs":true,"family":"Martin","given":"Julien","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":786936,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Taylor, Laura","contributorId":224059,"corporation":false,"usgs":false,"family":"Taylor","given":"Laura","affiliations":[{"id":25510,"text":"NC State University","active":true,"usgs":false}],"preferred":false,"id":786937,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70227825,"text":"70227825 - 2019 - Evaluation of a microsatellite panel for use across North American populations of white-tailed deer (Odocoileus virginianus)","interactions":[],"lastModifiedDate":"2022-02-02T14:38:48.7666","indexId":"70227825","displayToPublicDate":"2019-06-30T11:51:28","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10076,"text":"BMC Genetics","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Evaluation of a microsatellite panel for use across North American populations of white-tailed deer (<i>Odocoileus virginianus</i>)","title":"Evaluation of a microsatellite panel for use across North American populations of white-tailed deer (Odocoileus virginianus)","docAbstract":"<p>Background Microsatellite loci have been used extensively over the past two decades to study the genetic characteristics of non-model species. The relative ease of microsatellite development and ability to adapt markers from related species has led to the proliferation of available markers, particularly for those species that are intensively studied and managed. Because it is often infeasible to genotype individuals across all available loci, researchers generally rely on subsets of markers. Marker choice and genotyping errors can bias inferences made using disparate suites of microsatellite loci. This can limit comparative and collaborative efforts among research groups and has been a primary motivation for panel standardization efforts. Here, we develop a methodology for identifying a suite of markers from previous literature that can be generalizable across the range of commonly studied organisms. We specifically focus on producing a broadly applicable microsatellite panel for white-tailed deer (<i>Odocoileus virginianus</i>). Results We reviewed microsatellite panels from 58 previous or ongoing projects and identified a total of 106 candidate loci. We developed a multiplex protocol and evaluated the efficacy of 17 of the most commonly used loci using 720 DNA samples collected from the Mid-Atlantic region of the United States, an area where few previous studies were conducted. Amplification errors were detected in six of these loci. The properties of the remaining 11 loci suggest that they are applicable for many common research objectives. Specifically, this panel is highly polymorphic (eight to 20 alleles per locus, polymorphic information criterion = 0.492 to 0.917), exhibits low frequencies of genotyping errors (null alleles &lt; 10%), and is relatively easy to interpret with the aid of allele binning software. Conclusions We were able to identify a panel of microsatellite markers that show potential for broad applicability over the geographic range of white-tailed deer, as evidenced by the distribution of previous studies that utilized them. Validation in an additional region confirmed this. These results suggest that marker standardization and evaluation procedures based on literature reviews offers an effective method for identifying consolidated panels for future studies. This simple procedure addresses previous concerns about the infeasibility of standardization efforts.</p>","language":"English","doi":"10.1186/s12863-019-0750-z","usgsCitation":"Miller, W.L., Edson, J., Pietrandrea, P., Cassandra Miller-Butterworth, and Walter, W., 2019, Evaluation of a microsatellite panel for use across North American populations of white-tailed deer (Odocoileus virginianus): BMC Genetics, v. 20, no. 1, 49, 14 p., https://doi.org/10.1186/s12863-019-0750-z.","productDescription":"49, 14 p.","ipdsId":"IP-099036","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":467494,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s12863-019-0750-z","text":"Publisher Index Page"},{"id":395250,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland, Pennsylvania, Virginia","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -79.7607421875,\n              38.805470223177466\n            ],\n            [\n              -76.4208984375,\n              38.805470223177466\n            ],\n            [\n              -76.4208984375,\n              41.178653972331674\n            ],\n            [\n              -79.7607421875,\n              41.178653972331674\n            ],\n            [\n              -79.7607421875,\n              38.805470223177466\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"20","issue":"1","noUsgsAuthors":false,"publicationDate":"2019-06-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Miller, William L.","contributorId":272898,"corporation":false,"usgs":false,"family":"Miller","given":"William","email":"","middleInitial":"L.","affiliations":[{"id":6975,"text":"Penn State","active":true,"usgs":false}],"preferred":false,"id":832375,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Edson, Jessie","contributorId":272899,"corporation":false,"usgs":false,"family":"Edson","given":"Jessie","email":"","affiliations":[{"id":6975,"text":"Penn State","active":true,"usgs":false}],"preferred":false,"id":832376,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pietrandrea, Peter","contributorId":272902,"corporation":false,"usgs":false,"family":"Pietrandrea","given":"Peter","email":"","affiliations":[{"id":56403,"text":"Penn  State","active":true,"usgs":false}],"preferred":false,"id":832377,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cassandra Miller-Butterworth","contributorId":272903,"corporation":false,"usgs":false,"family":"Cassandra Miller-Butterworth","affiliations":[{"id":6975,"text":"Penn State","active":true,"usgs":false}],"preferred":false,"id":832378,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Walter, W. David 0000-0003-3068-1073","orcid":"https://orcid.org/0000-0003-3068-1073","contributorId":219540,"corporation":false,"usgs":true,"family":"Walter","given":"W. David","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":832374,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70204474,"text":"70204474 - 2019 - Harvest assessment for Taiga bean geese in the Central Management Unit: 2019","interactions":[],"lastModifiedDate":"2019-08-16T15:36:23","indexId":"70204474","displayToPublicDate":"2019-06-30T11:50:11","publicationYear":"2019","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"title":"Harvest assessment for Taiga bean geese in the Central Management Unit: 2019","docAbstract":"In 2016 the European Goose Management International Working Group (EGM IWG) began development of an Adaptive Harvest Management (AHM) program for Taiga Bean Geese. In 2017, the IWG adopted an Interim Harvest Strategy consisting of a constant harvest rate (on adults) of 3% for the Central Management Unit (MU) of Taiga Bean Geese. The interim strategy is intended to provide limited hunting opportunity while rebuilding the population. Based on a January count of 41,927, the harvest quota for the 2019 hunting season is 1,740 Taiga Bean Geese (compared to 2,335 and 1,610 for the 2017 and 2018 seasons, respectively). We emphasize that these quotas include both, harvest during the regular season and derogation shooting. Going forward, we describe how an Integrated Population Model (IPM) will use counts at multiple times during the year, along with other demographic information, to estimate population size (and its precision). The IPM can be used to develop an adaptive harvest strategy if unambiguous management objectives can be agreed upon. We provide some initial guidance for formulating those objectives.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"AEWA European Goose Management Platform","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"4th Meeting of the AEWA European Goose Management International Working Group","conferenceDate":"18-20 June, 2019","conferenceLocation":"Perth, Scotland, United Kingdom","language":"English","publisher":"Scottish National Heritage","usgsCitation":"Johnson, F., Heldbjerg, H., Alhainen, M., and Madsen, J., 2019, Harvest assessment for Taiga bean geese in the Central Management Unit: 2019, <i>in</i> AEWA European Goose Management Platform, Perth, Scotland, United Kingdom, 18-20 June, 2019.","productDescription":"10 p.","startPage":"1-10","ipdsId":"IP-108160","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":365985,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":365961,"type":{"id":15,"text":"Index Page"},"url":"https://egmp.aewa.info/meetings/iwg/detail/4th-meeting-aewa-european-goose-management-international-working-group-egm-iwg-4"}],"publicComments":"Document  AEWA/EGMIWG/4.10","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Johnson, Fred 0000-0002-5854-3695","orcid":"https://orcid.org/0000-0002-5854-3695","contributorId":217602,"corporation":false,"usgs":true,"family":"Johnson","given":"Fred","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":767153,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Heldbjerg, Henning","contributorId":174479,"corporation":false,"usgs":false,"family":"Heldbjerg","given":"Henning","email":"","affiliations":[],"preferred":false,"id":767154,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Alhainen, Mikko","contributorId":141140,"corporation":false,"usgs":false,"family":"Alhainen","given":"Mikko","email":"","affiliations":[{"id":13690,"text":"Finnish Wildlife Agency","active":true,"usgs":false}],"preferred":false,"id":767155,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Madsen, Jesper","contributorId":178168,"corporation":false,"usgs":false,"family":"Madsen","given":"Jesper","email":"","affiliations":[],"preferred":false,"id":767156,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70212624,"text":"70212624 - 2019 - Refining the Baseline Sediment Budget for the Klamath River, California","interactions":[],"lastModifiedDate":"2022-01-11T17:32:19.904133","indexId":"70212624","displayToPublicDate":"2019-06-30T10:39:35","publicationYear":"2019","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Refining the Baseline Sediment Budget for the Klamath River, California","docAbstract":"<p>Four dams in the Klamath River Hydroelectric Project (KHP) in Oregon and California (Figure 1) are currently scheduled to be removed over a period of a few weeks or months, beginning in January 2021. The Klamath dam removal will be the largest in the world by almost all measures, and is an unprecedented opportunity to advance science of river responses to such events. The KHP contains approximately 10-12 million cubic meters of mostly fine sediment and model estimates suggest approximately 1/3-2/3 of this volume is expected to be eroded from reservoirs. Much of this sediment is expected to be eventually transported by the river to, or through, the Klamath River Estuary, a distance of more than 300 kilometers. To improve the success of restoration activities following dam removal, agencies must understand the baseline conditions for biological, chemical, and physical processes, prior to the removal. We expect large changes in water quality (turbidity, suspended sediment, dissolved oxygen, temperature, and algal toxins) and in fish habitat in the Hydroelectric Reach and the main-stem of the Klamath River to the ocean. For example, modeled sediment concentrations in the Klamath River during dam removal were estimated exceed 10,000 – 15,000 mg/L, depending on streamflows, location, and the dam removal process, and to remain &gt; 100 – 1000 mg/L for months at a time. Final time to achieve background concentrations post dam removal may take over two years (Reclamation, 2011). Plans to assess many of these changes post-dam removal are still being formulated. </p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of SEDHYD 2019","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"SEDHYD 2019 Conference","conferenceDate":"Jun 24-28, 2019","conferenceLocation":"Reno, NV","language":"English","publisher":"Federal Interagency Sedimentation Conference (FISC) and Federal Interagency Hydrologic Modeling Conference (FIHMC)","usgsCitation":"Anderson, C.W., Wright, S., Schenk, L.N., Skalak, K., Curtis, J., East, A.E., and Benthem, A.J., 2019, Refining the Baseline Sediment Budget for the Klamath River, California, <i>in</i> Proceedings of SEDHYD 2019, v. 5, Reno, NV, Jun 24-28, 2019, 4 p.","productDescription":"4 p.","ipdsId":"IP-105518","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":377828,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":377827,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.sedhyd.org/2019/openconf/modules/request.php?module=oc_proceedings&action=proceedings.php&a=Accept"}],"country":"United States","state":"California, Oregon","otherGeospatial":"Klamath River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.49069213867188,\n              41.899210607606115\n            ],\n            [\n              -121.83563232421875,\n              41.899210607606115\n            ],\n            [\n              -121.83563232421875,\n              42.157295553651664\n            ],\n            [\n              -122.49069213867188,\n              42.157295553651664\n            ],\n            [\n              -122.49069213867188,\n              41.899210607606115\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"5","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Anderson, Chauncey W. 0000-0002-1016-3781 chauncey@usgs.gov","orcid":"https://orcid.org/0000-0002-1016-3781","contributorId":140160,"corporation":false,"usgs":true,"family":"Anderson","given":"Chauncey","email":"chauncey@usgs.gov","middleInitial":"W.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":797165,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wright, Scott 0000-0002-0387-5713 sawright@usgs.gov","orcid":"https://orcid.org/0000-0002-0387-5713","contributorId":1536,"corporation":false,"usgs":true,"family":"Wright","given":"Scott","email":"sawright@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":797166,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schenk, Liam N. 0000-0002-2491-0813 lschenk@usgs.gov","orcid":"https://orcid.org/0000-0002-2491-0813","contributorId":4273,"corporation":false,"usgs":true,"family":"Schenk","given":"Liam","email":"lschenk@usgs.gov","middleInitial":"N.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":797167,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Skalak, Katherine 0000-0003-4122-1240 kskalak@usgs.gov","orcid":"https://orcid.org/0000-0003-4122-1240","contributorId":3990,"corporation":false,"usgs":true,"family":"Skalak","given":"Katherine","email":"kskalak@usgs.gov","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":797168,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Curtis, Jennifer A. 0000-0001-7766-994X","orcid":"https://orcid.org/0000-0001-7766-994X","contributorId":239547,"corporation":false,"usgs":true,"family":"Curtis","given":"Jennifer A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":797169,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"East, Amy E. 0000-0002-9567-9460 aeast@usgs.gov","orcid":"https://orcid.org/0000-0002-9567-9460","contributorId":196364,"corporation":false,"usgs":true,"family":"East","given":"Amy","email":"aeast@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":797170,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Benthem, Adam J. 0000-0003-2372-0281","orcid":"https://orcid.org/0000-0003-2372-0281","contributorId":220000,"corporation":false,"usgs":true,"family":"Benthem","given":"Adam","middleInitial":"J.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":797171,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70204481,"text":"70204481 - 2019 - Hawai‘i Groundwater Recharge Tool","interactions":[],"lastModifiedDate":"2019-12-03T09:36:08","indexId":"70204481","displayToPublicDate":"2019-06-30T09:32:07","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":9,"text":"Other Report"},"title":"Hawai‘i Groundwater Recharge Tool","docAbstract":"The Hawai‘i Groundwater Recharge Tool allows users to evaluate the potential effects of land-cover and climate changes on groundwater recharge. This website provides a baseline estimate of recharge representing recent conditions of precipitation (1978–2008 average) and land cover (2010). Users can change land cover and rainfall conditions to evaluate the effects on groundwater recharge. Results will be displayed as on-screen maps, and users will be given options to generate interpretive graphics or export results in various formats. Results from this website are based on soil water-balance models. This is a pilot website that is currently limited to the island of O‘ahu, but the website has been designed to be expandable so that other islands and conditions can be added in the future.","language":"English","publisher":"University of Hawaii","usgsCitation":"McLean, J.H., Rotzoll, K., Cleaveland, S.B., and Izuka, S.K., 2019, Hawai‘i Groundwater Recharge Tool, HTML Document.","productDescription":"HTML Document","ipdsId":"IP-104867","costCenters":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"links":[{"id":369857,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":365986,"rank":1,"type":{"id":18,"text":"Project Site"},"url":"https://recharge.ikewai.org/#/workspace"}],"country":"United States","state":"Hawaii","otherGeospatial":"Oahu","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -158.33496093749997,\n              21.210019282760218\n            ],\n            [\n              -157.62359619140625,\n              21.210019282760218\n            ],\n            [\n              -157.62359619140625,\n              21.728885873951494\n            ],\n            [\n              -158.33496093749997,\n              21.728885873951494\n            ],\n            [\n              -158.33496093749997,\n              21.210019282760218\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"McLean, Jared H.","contributorId":217618,"corporation":false,"usgs":false,"family":"McLean","given":"Jared","email":"","middleInitial":"H.","affiliations":[{"id":37291,"text":"University of Hawaii at Hilo","active":true,"usgs":false}],"preferred":false,"id":767179,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rotzoll, Kolja 0000-0002-5910-888X kolja@usgs.gov","orcid":"https://orcid.org/0000-0002-5910-888X","contributorId":3325,"corporation":false,"usgs":true,"family":"Rotzoll","given":"Kolja","email":"kolja@usgs.gov","affiliations":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"preferred":false,"id":767180,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cleaveland, Sean B.","contributorId":217619,"corporation":false,"usgs":false,"family":"Cleaveland","given":"Sean","email":"","middleInitial":"B.","affiliations":[{"id":39036,"text":"University of Hawaii at Manoa","active":true,"usgs":false}],"preferred":false,"id":767181,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Izuka, Scot K. 0000-0002-8758-9414 skizuka@usgs.gov","orcid":"https://orcid.org/0000-0002-8758-9414","contributorId":2645,"corporation":false,"usgs":true,"family":"Izuka","given":"Scot","email":"skizuka@usgs.gov","middleInitial":"K.","affiliations":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"preferred":true,"id":767178,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70202422,"text":"70202422 - 2019 - Forecasts of coastal change hazards","interactions":[],"lastModifiedDate":"2019-12-05T08:27:47","indexId":"70202422","displayToPublicDate":"2019-06-30T08:27:37","publicationYear":"2019","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Forecasts of coastal change hazards","docAbstract":"<p><span>Model predictions of severe storm impacts provide coastal residents, emergency managers, and partner organizations valuable predictive information for planning and response to extreme storm events. The foundation of this work is a USGS-developed numerical model to forecast storm-induced coastal water levels and expected coastal change, including dune erosion, overwash, and inundation. The model is operated in three modes: generalized scenarios, real-time storms, and an operational forecast, with each mode requiring slightly different water level inputs. To evaluate and improve the accuracy of the models, we collect data on water levels and coastal change. In particular, observations before, after, and during storm conditions are used to test the different model applications. Forecast validation for Hurricanes Matthew (2016) and Irma (2017) illustrate three cases with demonstrated forecast skill and three cases with poor skill, and reveal elements of the modeling and/or testing approach which require improvement.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Coastal Sediments 2019: Proceedings of the 9th international conference ","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"Coastal Sediments 2019","conferenceDate":"May 27-31, 2019","conferenceLocation":"Tampa/St. Petersburg, FL","language":"English","publisher":"World Scientific","doi":"10.1142/9789811204487_0122","usgsCitation":"Doran, K.S., Stockdon, H.F., Joseph Long, and Plant, N.G., 2019, Forecasts of coastal change hazards, <i>in</i> Coastal Sediments 2019: Proceedings of the 9th international conference , Tampa/St. Petersburg, FL, May 27-31, 2019, p. 1400-1409, https://doi.org/10.1142/9789811204487_0122.","productDescription":"10 p.","startPage":"1400","endPage":"1409","ipdsId":"IP-105870","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":369944,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2019-05-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Doran, Kara S. 0000-0001-8050-5727 kdoran@usgs.gov","orcid":"https://orcid.org/0000-0001-8050-5727","contributorId":148059,"corporation":false,"usgs":true,"family":"Doran","given":"Kara","email":"kdoran@usgs.gov","middleInitial":"S.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":758393,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stockdon, Hilary F. 0000-0003-0791-4676 hstockdon@usgs.gov","orcid":"https://orcid.org/0000-0003-0791-4676","contributorId":2153,"corporation":false,"usgs":true,"family":"Stockdon","given":"Hilary","email":"hstockdon@usgs.gov","middleInitial":"F.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":758394,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Joseph Long","contributorId":213744,"corporation":false,"usgs":false,"family":"Joseph Long","affiliations":[{"id":38846,"text":"UNC Wilmington","active":true,"usgs":false}],"preferred":false,"id":758395,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Plant, Nathaniel G. 0000-0002-5703-5672 nplant@usgs.gov","orcid":"https://orcid.org/0000-0002-5703-5672","contributorId":3503,"corporation":false,"usgs":true,"family":"Plant","given":"Nathaniel","email":"nplant@usgs.gov","middleInitial":"G.","affiliations":[{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":758396,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70205847,"text":"70205847 - 2019 - Consistency counts: Modeling the effects of a change in protocol on Breeding Bird Survey counts","interactions":[],"lastModifiedDate":"2019-10-21T14:40:37","indexId":"70205847","displayToPublicDate":"2019-06-29T12:59:41","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3551,"text":"The Condor","active":true,"publicationSubtype":{"id":10}},"title":"Consistency counts: Modeling the effects of a change in protocol on Breeding Bird Survey counts","docAbstract":"Analysis of North American Breeding Bird Survey (BBS) data requires controls for factors that influence detectability of birds along survey routes.  Identifying factors that influence the counting process and incorporating them into analyses is a primary means of limiting bias in estimates of population change.   Twedt (2015) implemented an alternative counting protocol on operational and non-random BBS survey routes in the southeastern United States.  Observers on selected routes employed a time-distance protocol in which they recorded birds in 1-minute intervals and in 2 distance categories.  We hypothesized that processing and recording observations using this time-distance protocol could cause observers to count fewer birds relative to observers using the standard protocol.  We used a hierarchical log-linear model with a categorical covariate associated with protocol (standard vs time-distance) to assess whether use of the time-distance protocol had a measurable effect on counting birds along BBS routes.  We applied this model to BBS data from portions of eight states in which the time-distance protocol was implemented and estimated a protocol effect for 167 bird species.  We documented a significant overall effect of the time-distance protocol on observers’ counts of birds.  On average, the effect of the time-distance protocol was a 10% decline in count, and 80% of species had lower counts when the time-distance protocol was used on a survey route.   However, because the time-distance protocol was only used on a small portion of the operational BBS routes and for a limited time, including the covariate for the time-distance protocol data had insignificant effects on analysis of population change.   Although the covariate controlled for the effects of the time-distance protocol in BBS data, the results emphasize the importance of standardization as well as a need to track and, if necessary, control in analyses for changes in counting procedures along BBS routes.","language":"English","publisher":"Oxford Academic","doi":"10.1093/condor/duz009","usgsCitation":"Sauer, J.R., Link, W.A., Ziolkowski, D., Pardieck, K.L., and Twedt, D.J., 2019, Consistency counts: Modeling the effects of a change in protocol on Breeding Bird Survey counts: The Condor, v. 121, no. 2, duz009, 12 p., https://doi.org/10.1093/condor/duz009.","productDescription":"duz009, 12 p.","ipdsId":"IP-081193","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":467495,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/condor/duz009","text":"Publisher Index Page"},{"id":368104,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"121","issue":"2","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2019-06-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Sauer, John R. 0000-0002-4557-3019 jrsauer@usgs.gov","orcid":"https://orcid.org/0000-0002-4557-3019","contributorId":146917,"corporation":false,"usgs":true,"family":"Sauer","given":"John","email":"jrsauer@usgs.gov","middleInitial":"R.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":772603,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Link, William A. 0000-0002-9913-0256 wlink@usgs.gov","orcid":"https://orcid.org/0000-0002-9913-0256","contributorId":146920,"corporation":false,"usgs":true,"family":"Link","given":"William","email":"wlink@usgs.gov","middleInitial":"A.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":773533,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ziolkowski, David 0000-0002-2500-4417 dziolkowski@usgs.gov","orcid":"https://orcid.org/0000-0002-2500-4417","contributorId":195409,"corporation":false,"usgs":true,"family":"Ziolkowski","given":"David","email":"dziolkowski@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":773534,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pardieck, Keith L. 0000-0003-2779-4392 kpardieck@usgs.gov","orcid":"https://orcid.org/0000-0003-2779-4392","contributorId":4104,"corporation":false,"usgs":true,"family":"Pardieck","given":"Keith","email":"kpardieck@usgs.gov","middleInitial":"L.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":773535,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Twedt, Daniel J. 0000-0003-1223-5045 dtwedt@usgs.gov","orcid":"https://orcid.org/0000-0003-1223-5045","contributorId":398,"corporation":false,"usgs":true,"family":"Twedt","given":"Daniel","email":"dtwedt@usgs.gov","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":773536,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70203002,"text":"sir20195029 - 2019 - Groundwater quality and hydrology with emphasis  on selenium mobilization and transport in the Lower Gunnison River Basin, Colorado, 2012–16","interactions":[],"lastModifiedDate":"2019-07-01T09:22:29","indexId":"sir20195029","displayToPublicDate":"2019-06-28T13:00:00","publicationYear":"2019","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":"2019-5029","title":"Groundwater quality and hydrology with emphasis  on selenium mobilization and transport in the Lower Gunnison River Basin, Colorado, 2012–16","docAbstract":"<p>Dissolved selenium is a contaminant of concern in the lower Gunnison River Basin, Colorado. Selenium is naturally present in the Cretaceous Mancos Shale and is leached to groundwater and surface water by irrigation. The groundwater on the east side of the Uncompahgre River in Delta and Montrose Counties is one of the primary sources of selenium concentration and load to surface water in the lower Gunnison River Basin. Although little information about the contribution of groundwater to surface water has been historically available, groundwater has often been implicated as an appreciable source of selenium to surface water. From 2012 to 2016, the U.S. Geological Survey, in cooperation with the Bureau of Reclamation, the Colorado Water Conservation Board, and the Gunnison Basin Selenium Management Program, established a 30-well groundwater-monitoring network on irrigated land to characterize the hydrology and groundwater quality of the shallow groundwater system on the east side of the Uncompahgre River in the lower Gunnison River Basin. The installation of the 30-well network and the data collected allowed for the development of a conceptual model of selenium mobilization and transport in the shallow groundwater system. Monitoring wells were completed in surficial deposits and in weathered Mancos Shale, which generally exhibited unconfined and confined conditions, respectively. Groundwater-quality monitoring provides information on the distribution of selenium and the geochemical processes controlling selenium concentrations in shallow groundwater. Monitoring wells were sampled between August 2013 and March 2015 to understand groundwater quality, seasonality, sources of recharge, and groundwater age. Concentrations of dissolved selenium ranged from below the limit of detection to 4,100 micrograms per liter (µg/L), with a median concentration of 14 µg/L. Concentrations showed a high degree of spatial variability and no seasonal difference. Similarly, no seasonal pattern was observed in specific conductance values of groundwater despite the considerably lower specific conductance value of irrigation water.</p><p>Reduction-oxidation processes are important controls on selenium mobility. Nitrate derived from geologic material was a primary control on reduction-oxidation conditions in&nbsp;groundwater and inhibited selenium reduction to less mobile forms. Nitrate was reduced by denitrification in groundwater, but it was not reduced to the extent necessary to allow for selenium reduction. Groundwater ages were determined for groundwater samples from eight wells and ranged from 6 to 20 years old. Isotopic data indicate groundwater was recharged by irrigation water; no information collected supported an older, deeper source of recharge to the shallow groundwater system. Data on water level in all wells showed response to irrigation practices, but the response was delayed in some wells, which may be an indication of distance from recharge source.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/sir20195029","collaboration":"Prepared in cooperation with the Bureau of Reclamation, the Colorado Water Conservation Board, and the Gunnison Basin Selenium Management Program","usgsCitation":"Thomas, J.C., McMahon, P.B., and Arnold, L.R., 2019, Groundwater quality and hydrology with emphasis on selenium mobilization and transport in the lower Gunnison River Basin, Colorado, 2012–16: U.S. Geological Survey Scientific Investigations Report 2019–5029, 69 p., https://doi.org/10.3133/sir20195029.","productDescription":"viii, 69 p.","onlineOnly":"Y","ipdsId":"IP-084069","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":365132,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5029/coverthb.jpg"},{"id":365133,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5029/sir20195029.pdf","text":"Report","size":"10.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019–5029"}],"country":"United States","state":"Colorado","otherGeospatial":"Lower Gunnison River Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -108.80584716796875,\n              39.01064750994083\n            ],\n            [\n              -109.11895751953125,\n              38.8782049970615\n            ],\n            [\n              -108.6328125,\n              38.10214399750345\n            ],\n            [\n              -108.69598388671875,\n              37.77288579232439\n            ],\n            [\n              -107.87750244140625,\n              37.309014074275915\n            ],\n            [\n              -107.4462890625,\n              37.31338308990806\n            ],\n            [\n              -107.1441650390625,\n              37.727280276860036\n            ],\n            [\n              -107.18536376953125,\n              38.07620357665235\n            ],\n            [\n              -107.26776123046875,\n              38.50304202775689\n            ],\n            [\n              -107.50671386718749,\n              38.9380483825641\n            ],\n            [\n              -107.6495361328125,\n              39.115144700901475\n            ],\n            [\n              -108.80584716796875,\n              39.01064750994083\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/co-water/\" data-mce-href=\"https://www.usgs.gov/centers/co-water/\">Colorado Water Science Center</a><br>U.S. Geological Survey<br>Box 25046, MS-415<br>Denver, CO 80225-0046</p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Study Area</li><li>Methods</li><li>Groundwater Quality</li><li>Groundwater Hydrology</li><li>Selenium Mobilization and Transport in Groundwater</li><li>Summary</li><li>References Cited</li><li>Appendix 1. Estimates of Recharge Using the Graphical Approach to the Water Table Fluctuation (WTF) Method</li></ul>","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"publishedDate":"2019-06-28","noUsgsAuthors":false,"publicationDate":"2019-06-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Thomas, Judith C. 0000-0001-7883-1419","orcid":"https://orcid.org/0000-0001-7883-1419","contributorId":202706,"corporation":false,"usgs":true,"family":"Thomas","given":"Judith","email":"","middleInitial":"C.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":760739,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McMahon, Peter B. 0000-0001-7452-2379 pmcmahon@usgs.gov","orcid":"https://orcid.org/0000-0001-7452-2379","contributorId":724,"corporation":false,"usgs":true,"family":"McMahon","given":"Peter","email":"pmcmahon@usgs.gov","middleInitial":"B.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":760740,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Arnold, L. R. 0000-0002-5110-9642 lrarnold@usgs.gov","orcid":"https://orcid.org/0000-0002-5110-9642","contributorId":1307,"corporation":false,"usgs":true,"family":"Arnold","given":"L.","email":"lrarnold@usgs.gov","middleInitial":"R.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":765251,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70204038,"text":"sir20195053 - 2019 - Assessing potential effects of highway and urban runoff on receiving streams in total maximum daily load watersheds in Oregon using the stochastic empirical loading and dilution model","interactions":[],"lastModifiedDate":"2024-01-22T22:09:00.604752","indexId":"sir20195053","displayToPublicDate":"2019-06-27T18:19:33","publicationYear":"2019","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":"2019-5053","displayTitle":"Assessing Potential Effects of Highway and Urban Runoff on Receiving Streams in Total Maximum Daily Load Watersheds in Oregon Using the Stochastic Empirical Loading and Dilution Model","title":"Assessing potential effects of highway and urban runoff on receiving streams in total maximum daily load watersheds in Oregon using the stochastic empirical loading and dilution model","docAbstract":"<p class=\"p1\">The Stochastic Empirical Loading and Dilution&nbsp;Model (SELDM) was developed by the U.S. Geological&nbsp;Survey (USGS) in cooperation with the Federal Highway&nbsp;Administration to simulate stormwater quality. To assess the&nbsp;effects of runoff, SELDM uses a stochastic mass-balance&nbsp;approach to estimate combinations of pre-storm streamflow,&nbsp;stormflow, highway runoff, event mean concentrations&nbsp;(EMCs) and stormwater constituent loads from a site of&nbsp;interest. In addition, SELDM can be used to assess the effects&nbsp;of stormwater Best Management Practices (BMPs), which&nbsp;are designed to mitigate the adverse effects of runoff into a&nbsp;waterbody.&nbsp;<br></p><p class=\"p1\">Adverse effects of stormwater on receiving waters&nbsp;are one of the greatest unsolved water-quality problems&nbsp;Nationwide. State DOTs, municipalities, Federal facilities,&nbsp;and private property owners who manage impervious surfaces&nbsp;need information about the potential magnitude of their&nbsp;contributions and the potential effectiveness of methods to&nbsp;mitigate the adverse effects of runoff. Because the efficacy of&nbsp;at-site controls are limited, information about the potential&nbsp;effectiveness of alternative strategies is needed.&nbsp;</p><p class=\"p1\">The USGS, in cooperation with the Oregon Department&nbsp;of Transportation (ODOT), conducted a study to research&nbsp;methods in which SELDM can be used to enhance the&nbsp;efficiency of ODOT’s stormwater program, support the&nbsp;development of a stormwater banking program, and meet&nbsp;environmental goals. Results can be used to develop a&nbsp;strategic, systems-level approach to stormwater management&nbsp;by considering entire watersheds instead of individual road&nbsp;crossings. Two watersheds, Bear Creek and Mill Creek,&nbsp;in western Oregon were selected for analysis. Within&nbsp;each watershed, seven road crossings were selected for&nbsp;demonstrating the utility of SELDM in nested basins.</p><p class=\"p1\">Precipitation statistics, pre-storm streamflow, runoff&nbsp;coefficients, and hydrograph recession factors were calculated&nbsp;for each location and used in SELDM to simulate flow,&nbsp;water-quality concentrations, and constituent loads in the&nbsp;upstream basin, from the highway (or developed area), and&nbsp;downstream from the road crossing. Three water-quality&nbsp;constituents were selected for modeling: suspended-sediment&nbsp;concentration (SSC), total phosphorus (TP), and total copper&nbsp;(TCu). Using water-quality transport curves, the relations&nbsp;between streamflow and SSC and between streamflow and&nbsp;TP were simulated. Concentrations of TCu were simulated by&nbsp;configuring a linear relation between SSC and TCu. A generic&nbsp;BMP was simulated using the median treatment statistics&nbsp;for flow reductions, hydrograph extensions, concentration&nbsp;reductions, and minimum irreducible concentrations from nine&nbsp;BMP categories with data from the 2012 International BMP&nbsp;database.&nbsp;</p><p class=\"p1\">Five simulation scenarios were modeled for&nbsp;demonstrative purposes. These simulations were used to&nbsp;evaluate potential effects of different watershed properties,&nbsp;water-quality inputs, and stormwater mitigation measures.&nbsp;Instream EMCs were compared to hypothetical water-quality&nbsp;criteria for suspended sediment, total phosphorus, and total&nbsp;copper to demonstrate the concept of water-quality risk&nbsp;analysis. For all five scenarios, it was assumed that highway runoff concentrations were independent of location or average&nbsp;annual daily traffic. These five scenarios are as follows:<br>• Simulation Scenario 1—Natural Conditions (hereafter&nbsp;Simulation Scenario 1) represents conditions in an&nbsp;undeveloped watershed. This scenario demonstrates&nbsp;that the strategic placement of a hypothetical road&nbsp;crossing within a watershed could be used to avoid&nbsp;exceeding water-quality standards of TP and SSC,&nbsp;but that no location choice results in meeting TCu&nbsp;standards. Implementation of BMP had the most&nbsp;pronounced effects on downstream water-quality&nbsp;constituent EMCs at road crossings with the highest&nbsp;ratio of highway catchment area to upstream drainage&nbsp;area, but the largest effect of BMP treatment on mean&nbsp;annual load is based on highway catchment area alone.</p><p class=\"p1\">• Simulation Scenario 2—Current Conditions (hereafter&nbsp;Simulation Scenario 2) represents current watershed&nbsp;conditions, where all developed area upstream from the&nbsp;road crossing was modeled as a highway and combined&nbsp;with the undeveloped part of the upstream drainage&nbsp;area (scenario 2A) and where the output from scenario&nbsp;2A is used for the upstream area (developed area and&nbsp;the undeveloped area), and where the road crossing&nbsp;&nbsp;is added as usual (scenario 2B). Scenario 2 results&nbsp;indicate that attaining water-quality standards is more&nbsp;difficult with upstream developed areas. Specific road-crossing sites can be selected to achieve the fewest&nbsp;water-quality exceedances per year, but water-quality&nbsp;targets are not met without BMP implementation, and&nbsp;in some instances are not achievable even with BMP&nbsp;implementation. Results from this scenario also serve&nbsp;to quantify the upper limit of constituent reduction if&nbsp;funding were available to implement BMPs to large&nbsp;areas of development, and to quantify how much area&nbsp;would need BMP implementation to achieve water-quality targets.&nbsp;</p><p class=\"p1\">• Simulation Scenario 3—Alternative Road Layouts&nbsp;(hereafter Simulation Scenario 3) was designed&nbsp;to assess the sensitivity of SELDM to various&nbsp;road layouts. In this scenario, different highway&nbsp;configurations were superimposed at one road&nbsp;crossing. Results indicate that downstream waterquality constituent EMCs did not exhibit much&nbsp;variation, but annual water-quality constituent loads&nbsp;varied considerably.<br>• Simulation Scenario 4—Varying Road Width (hereafter Simulation Scenario 4) was designed to assess the&nbsp;sensitivity of SELDM to road width. Similar to&nbsp;scenario 3, the results indicate little variation in&nbsp;downstream water-quality constituent EMCs, but&nbsp;annual water-quality constituent loads increased in&nbsp;proportion to road width.<br>• Simulation scenario 5—Changes to Impervious Area&nbsp;(hereafter Simulation Scenario 5) was designed&nbsp;to investigate the effects of changing amounts of&nbsp;imperviousness upstream from the road crossing.&nbsp;&nbsp;Results indicate that the downstream water-quality&nbsp;constituent EMCs are highly correlated with the&nbsp;percentage of impervious area upstream.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195053","collaboration":"Prepared in cooperation with the Oregon Department of Transportation","usgsCitation":"Stonewall, A.J., Granato, G.E., and Glover-Cutter, K.M., 2019, Assessing potential effects of highway and urban runoff on receiving streams in total maximum daily load watersheds in Oregon using the Stochastic Empirical Loading and Dilution Model: U.S. Geological Survey Scientific Investigations Report 2019–5053, 116 p., https://doi.org/10.3133/sir20195053.","productDescription":"Report: xi, 116 p.; 3 Tables","onlineOnly":"Y","ipdsId":"IP-100821","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":365922,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9Y6YWG9","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Tools for use in Oregon with the Stochastic Empirical Loading Dilution Model"},{"id":424710,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_108892.htm","linkFileType":{"id":5,"text":"html"},"description":"108892"},{"id":424709,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_108893.htm","linkFileType":{"id":5,"text":"html"},"description":"108893"},{"id":365118,"rank":5,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2019/5053/sir20195053_table23.xlsx","text":"Table 23","size":"26 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2019-5053 Table 23"},{"id":365117,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2019/5053/sir20195053_table09.xlsx","text":"Table 9","size":"25 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2019-5053 Table 9"},{"id":365116,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2019/5053/sir20195053_table08.xlsx","text":"Table 8","size":"39 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2019-5053 Table 8"},{"id":365115,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5053/sir20195053.pdf","text":"Report","size":"40.3 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 \"}}]}","contact":"<p><a href=\"mailto:dc_or@usgs.gov\" data-mce-href=\"mailto:dc_or@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/centers/or-water\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/or-water\">Oregon Water Science Center</a><br>U.S. Geological Survey<br>2130 SW 5th Avenue<br>Portland, Oregon 97201</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>SELDM Background</li><li>Geographic Analysis of State Roadways and Upstream Land Use and Land Cover</li><li>Selection of Watersheds for Stormwater Analyses</li><li>Selection Of Nested Watersheds For Stormwater Analyses</li><li>Simulated Hydrology</li><li>Simulated Water Quality</li><li>Simulating Runoff Treatment</li><li>Example Runoff-Quality Simulations</li><li>Limitations Of The Analyses</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"publishedDate":"2019-06-27","noUsgsAuthors":false,"publicationDate":"2019-06-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Stonewall, Adam J. 0000-0002-3277-8736 stonewal@usgs.gov","orcid":"https://orcid.org/0000-0002-3277-8736","contributorId":138801,"corporation":false,"usgs":true,"family":"Stonewall","given":"Adam","email":"stonewal@usgs.gov","middleInitial":"J.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":false,"id":765228,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Granato, Gregory E. 0000-0002-2561-9913","orcid":"https://orcid.org/0000-0002-2561-9913","contributorId":203250,"corporation":false,"usgs":true,"family":"Granato","given":"Gregory E.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":765229,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Glover-Cutter, Kira M. 0000-0002-7321-8604","orcid":"https://orcid.org/0000-0002-7321-8604","contributorId":210818,"corporation":false,"usgs":false,"family":"Glover-Cutter","given":"Kira","email":"","middleInitial":"M.","affiliations":[{"id":38152,"text":"Oregon Department of Transportation","active":true,"usgs":false}],"preferred":false,"id":765230,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70204257,"text":"70204257 - 2019 - Hydrocarbons in upland groundwater, Marcellus Shale Region, Northeastern Pennsylvania and Southern New York, USA","interactions":[],"lastModifiedDate":"2019-07-17T11:44:31","indexId":"70204257","displayToPublicDate":"2019-06-27T14:57:31","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Hydrocarbons in upland groundwater, Marcellus Shale Region, Northeastern Pennsylvania and Southern New York, USA","docAbstract":"<p><span>Water samples from 50 domestic wells located &lt;1 km (proximal) and &gt;1 km (distal) from shale-gas wells in upland areas of the Marcellus Shale region were analyzed for chemical, isotopic, and groundwater-age tracers. Uplands were targeted because natural mixing with brine and hydrocarbons from deep formations is less common in those areas compared to valleys. CH</span><sub>4</sub><span>-isotope, predrill CH</span><sub>4</sub><span>-concentration, and other data indicate that one proximal sample (5% of proximal samples) contains thermogenic CH</span><sub>4</sub><span>&nbsp;(2.6 mg/L) from a relatively shallow source (Catskill/Lock Haven Formations) that appears to have been mobilized by shale-gas production activities. Another proximal sample contains five other volatile hydrocarbons (0.03–0.4 μg/L), including benzene, more hydrocarbons than in any other sample. Modeled groundwater-age distributions, calibrated to&nbsp;</span><sup>3</sup><span>H, SF</span><sub>6</sub><span>, and&nbsp;</span><sup>14</sup><span>C concentrations, indicate that water in that sample recharged prior to shale-gas development, suggesting that land-surface releases associated with shale-gas production were not the source of those hydrocarbons, although subsurface leakage from a nearby gas well directly into the groundwater cannot be ruled out. Age distributions in the samples span ∼20 to &gt;10000 years and have implications for relating occurrences of hydrocarbons in groundwater to land-surface releases associated with recent shale-gas production and for the time required to flush contaminants from the system.</span></p>","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.9b01440","usgsCitation":"McMahon, P.B., Lindsey, B.D., Conlon, M.D., Hunt, A.G., Belitz, K., Jurgens, B., and Varela, B.A., 2019, Hydrocarbons in upland groundwater, Marcellus Shale Region, Northeastern Pennsylvania and Southern New York, USA: Environmental Science & Technology, v.  53, no. 14, p. 8027-8035, https://doi.org/10.1021/acs.est.9b01440.","productDescription":"9 p.","startPage":"8027","endPage":"8035","ipdsId":"IP-104959","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true},{"id":5078,"text":"Southwest Regional Director's Office","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"links":[{"id":437401,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93M7JCD","text":"USGS data release","linkHelpText":"Data Release for Hydrocarbons in Upland Groundwater, Marcellus Shale Region, Northeastern Pennsylvania and Southern New York, USA"},{"id":365631,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York, Pennsylvania","volume":" 53","issue":"14","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-06-27","publicationStatus":"PW","contributors":{"authors":[{"text":"McMahon, Peter B. 0000-0001-7452-2379 pmcmahon@usgs.gov","orcid":"https://orcid.org/0000-0001-7452-2379","contributorId":724,"corporation":false,"usgs":true,"family":"McMahon","given":"Peter","email":"pmcmahon@usgs.gov","middleInitial":"B.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":766203,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lindsey, Bruce D. 0000-0002-7180-4319 blindsey@usgs.gov","orcid":"https://orcid.org/0000-0002-7180-4319","contributorId":175346,"corporation":false,"usgs":true,"family":"Lindsey","given":"Bruce","email":"blindsey@usgs.gov","middleInitial":"D.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":766204,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Conlon, Matthew D. 0000-0001-8266-9610 mconlon@usgs.gov","orcid":"https://orcid.org/0000-0001-8266-9610","contributorId":201291,"corporation":false,"usgs":true,"family":"Conlon","given":"Matthew","email":"mconlon@usgs.gov","middleInitial":"D.","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":766205,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hunt, Andrew G. 0000-0002-3810-8610 ahunt@usgs.gov","orcid":"https://orcid.org/0000-0002-3810-8610","contributorId":1582,"corporation":false,"usgs":true,"family":"Hunt","given":"Andrew","email":"ahunt@usgs.gov","middleInitial":"G.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":766206,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Belitz, Kenneth 0000-0003-4481-2345","orcid":"https://orcid.org/0000-0003-4481-2345","contributorId":201889,"corporation":false,"usgs":true,"family":"Belitz","given":"Kenneth","affiliations":[{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":766207,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jurgens, Bryant C. 0000-0002-1572-113X","orcid":"https://orcid.org/0000-0002-1572-113X","contributorId":203409,"corporation":false,"usgs":true,"family":"Jurgens","given":"Bryant","middleInitial":"C.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":766208,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Varela, Brian A. 0000-0001-9849-6742 bvarela@usgs.gov","orcid":"https://orcid.org/0000-0001-9849-6742","contributorId":178091,"corporation":false,"usgs":true,"family":"Varela","given":"Brian","email":"bvarela@usgs.gov","middleInitial":"A.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":766209,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70204037,"text":"70204037 - 2019 - Morphology and genesis of giant seafloor depressions on the southeasterncontinental shelf of the Korean Peninsula","interactions":[],"lastModifiedDate":"2019-06-28T09:25:09","indexId":"70204037","displayToPublicDate":"2019-06-27T14:31:58","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2667,"text":"Marine Geology","active":true,"publicationSubtype":{"id":10}},"title":"Morphology and genesis of giant seafloor depressions on the southeasterncontinental shelf of the Korean Peninsula","docAbstract":"<p><span>We identify and describe five giant seafloor depressions from the southeastern continental shelf of the Korean Peninsula using multibeam bathymetry, sub-bottom profiler, and multi-channel seismic reflection data, supplemented by piston cores. Multibeam bathymetry data from the shelf show four crescent-shaped depressions (SD1 to SD4) and one near-circular depression (SD5) within a group of NW-SE trending depressions, the largest covering an area of about 7 km</span><sup>2</sup><span>&nbsp;on the seafloor. The depressions reach up to ~4.5 km in width and ~2 km in length and have asymmetric cross-sections. Some have depths as large as 40 m below the surrounding seafloor with walls as steep as 45°. The depressions are confined to water depths between 130 and 170 m and bounded on the north by a large submarine channel that was plausibly formed by fluvial or tidal processes during the Last Glacial Maximum (LGM) sea-level lowstand. Multi-channel seismic and sub-bottom profiler data reveal truncated depression walls and the presence of sediment drift deposits within the depressions, indicating that both erosion and deposition are active processes. Flaser and lenticular bedding in the cored drift deposits along with variable grain size (ranging between ~2.6 phi and ~4.3 phi) are diagnostic features of the bottom currents influenced by tidal forces. Depressions SD1 to SD4 lack evidence of fluid or gas escape. In contrast, many features of depression SD5 are characteristic of gas escapes and blowouts, including acoustic anomalies, a 20-m-high carbonate mound or carbonate-encrusted mound, and mud dikes and mud patches in cores. Based on the SD5 example, we think it is likely that the other crescent-shaped seafloor depressions formed originally as pockmarks by gas/fluid venting, and have since become inactive. The pockmarks represent zones of weakened sediment that were eroded, expanded, and merged by bottom currents to form larger seafloor depressions. Modern currents are strong enough to transport shelf sediments, and these currents were probably much stronger at lower sea levels when the Korea Strait was a more restricted passage between the East China Sea and East Sea.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.margeo.2019.105966","usgsCitation":"Cukur, D., Kong, G., Chun, J., Kang, M., Um, I., Kwon, T., Jordan, S.E., and Kim, K., 2019, Morphology and genesis of giant seafloor depressions on the southeasterncontinental shelf of the Korean Peninsula: Marine Geology, v. 415, 105966, 13 p., https://doi.org/10.1016/j.margeo.2019.105966.","productDescription":"105966, 13 p.","ipdsId":"IP-106382","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":365123,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"North Korea, South Korea","otherGeospatial":"Korea Strait","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              127.869873046875,\n              33.284619968887675\n            ],\n            [\n              130.97900390625,\n              33.284619968887675\n            ],\n            [\n              130.97900390625,\n              37.18657859524883\n            ],\n            [\n              127.869873046875,\n              37.18657859524883\n            ],\n            [\n              127.869873046875,\n              33.284619968887675\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"415","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Cukur, Deniz","contributorId":216636,"corporation":false,"usgs":false,"family":"Cukur","given":"Deniz","email":"","affiliations":[{"id":39491,"text":"Korea Institute of Geoscience and Mineral Resources (KIGAM","active":true,"usgs":false}],"preferred":false,"id":765221,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kong, Gee-Soo","contributorId":216637,"corporation":false,"usgs":false,"family":"Kong","given":"Gee-Soo","email":"","affiliations":[{"id":39491,"text":"Korea Institute of Geoscience and Mineral Resources (KIGAM","active":true,"usgs":false}],"preferred":false,"id":765254,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chun, Jong-Hwa","contributorId":216638,"corporation":false,"usgs":false,"family":"Chun","given":"Jong-Hwa","email":"","affiliations":[{"id":39491,"text":"Korea Institute of Geoscience and Mineral Resources (KIGAM","active":true,"usgs":false}],"preferred":false,"id":765223,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kang, Moo-Hee","contributorId":216639,"corporation":false,"usgs":false,"family":"Kang","given":"Moo-Hee","email":"","affiliations":[{"id":39491,"text":"Korea Institute of Geoscience and Mineral Resources (KIGAM","active":true,"usgs":false}],"preferred":false,"id":765224,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Um, In-Kwon","contributorId":216640,"corporation":false,"usgs":false,"family":"Um","given":"In-Kwon","email":"","affiliations":[{"id":39491,"text":"Korea Institute of Geoscience and Mineral Resources (KIGAM","active":true,"usgs":false}],"preferred":false,"id":765225,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kwon, Taekhyun","contributorId":216641,"corporation":false,"usgs":false,"family":"Kwon","given":"Taekhyun","email":"","affiliations":[{"id":39491,"text":"Korea Institute of Geoscience and Mineral Resources (KIGAM","active":true,"usgs":false}],"preferred":false,"id":765226,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jordan, Samuel E. 0000-0001-6074-3330","orcid":"https://orcid.org/0000-0001-6074-3330","contributorId":216635,"corporation":false,"usgs":true,"family":"Jordan","given":"Samuel","email":"","middleInitial":"E.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":765220,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kim, Kyong-O","contributorId":216642,"corporation":false,"usgs":false,"family":"Kim","given":"Kyong-O","email":"","affiliations":[{"id":39491,"text":"Korea Institute of Geoscience and Mineral Resources (KIGAM","active":true,"usgs":false}],"preferred":false,"id":765227,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70263727,"text":"70263727 - 2019 - Evaluating tradeoffs in the response of Sora (Porzana carolina) and waterfowl to the timing of early autumn wetland inundation","interactions":[],"lastModifiedDate":"2025-02-20T19:12:23.90001","indexId":"70263727","displayToPublicDate":"2019-06-27T13:04:35","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3731,"text":"Waterbirds","onlineIssn":"19385390","printIssn":"15244695","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Evaluating tradeoffs in the response of Sora (<i>Porzana carolina</i>) and waterfowl to the timing of early autumn wetland inundation","title":"Evaluating tradeoffs in the response of Sora (Porzana carolina) and waterfowl to the timing of early autumn wetland inundation","docAbstract":"<p><span>Wetland loss has increased the importance of multi-species management in remaining wetlands, which provide habitat for a multitude of wetland-dependent species. Many public wetlands across the mid-latitude United States are managed as moist soil impoundments with emphasis on migratory waterfowl. However, how the timing of these water management decisions affects rails is still uncertain. Wetland managers identified this as an area of uncertainty regarding timing of alternative water management strategies to benefit waterfowl and rails, which was addressed through a 3-year management experiment. Sora (</span><i>Porzana carolina</i><span>) and waterfowl were surveyed on 10 public wetland properties in Missouri, USA from 2014-2016, and their responses to early autumn inundation of managed palustrine wetlands were compared. A total of 558 Sora surveys detected 5,755 birds (20.6 birds/survey ± 30.8 SD), and 1,304 waterfowl surveys detected 1,411,779 birds (15,686.4 birds/survey ± 23,933.9 SD). Sora responded positively (birds/ha) to inundation of moist soil impoundments earlier in autumn migration (August). The top model for Sora included treatment, year and region of Missouri. There was no difference in waterfowl abundance between early or late inundation. Inundating wetlands earlier in autumn migration can provide habitat for migrating Sora without negative effects on waterfowl use of those wetlands, and wetland managers can incorporate this into their decision-making framework.</span></p>","language":"English","publisher":"BioOne","doi":"10.1675/063.042.0203","usgsCitation":"Fournier, A., Mengel, D., Gbur, E., Raedeke, A., and Krementz, D.G., 2019, Evaluating tradeoffs in the response of Sora (Porzana carolina) and waterfowl to the timing of early autumn wetland inundation: Waterbirds, v. 42, no. 2, p. 168-178, https://doi.org/10.1675/063.042.0203.","productDescription":"11 p.","startPage":"168","endPage":"178","ipdsId":"IP-093134","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":489951,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1675/063.042.0203","text":"Publisher Index 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