{"pageNumber":"110","pageRowStart":"2725","pageSize":"25","recordCount":68784,"records":[{"id":70243646,"text":"70243646 - 2023 - Examining terrestrial and subterranean sediment sources and transport processes in an urban sewershed with an entirely buried stream network, Washington, D.C., United States","interactions":[],"lastModifiedDate":"2023-06-12T14:51:29.812761","indexId":"70243646","displayToPublicDate":"2023-04-15T09:42:44","publicationYear":"2023","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Examining terrestrial and subterranean sediment sources and transport processes in an urban sewershed with an entirely buried stream network, Washington, D.C., United States","docAbstract":"Excessive fine-grained sediment runoff due to anthropogenic activities is a major environmental concern for watersheds worldwide, especially so for urban areas such as Washington, D.C. Dated grey infrastructure, i.e., the network of buried pipes and reservoirs managing water resources, can amplify existing issues with sediment runoff and associated pollutants. This infrastructure, which is generally designed to quickly transport stormwaters away from urban areas, contributes to urban stream syndrome. Recent studies have suggested aging subterranean infrastructure may be an unaccounted-for source of sediments. The composition of this possible sediment source, and the extent to which it contributes to urban sediment runoff, is poorly understood. Our study seeks to examine sediment sources and transport processes in an urban watershed with an entirely buried drainage network using sediment fingerprinting, with specific attention paid to differentiating between terrestrial and subterranean sources. We demonstrate here multiple novel approaches to sampling subterranean sources including augering and entering the buried drainage network itself. The results of this study may inform sediment managers and infrastructure engineers and allow for targeted sediment reduction responses.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"SEDHYD 2023","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"SEDHYD","usgsCitation":"Clifton, Z.J., Gellis, A.C., Staub, L.E., Cashman, M.J., Conaway, C., Lane, C., and Pilat, D., 2023, Examining terrestrial and subterranean sediment sources and transport processes in an urban sewershed with an entirely buried stream network, Washington, D.C., United States, in SEDHYD 2023, 4 p.","productDescription":"4 p.","ipdsId":"IP-147983","costCenters":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":418002,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":418001,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.sedhyd.org/2023Program/s53.html","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"District of Columbia","city":"Washington D.C.","otherGeospatial":"Hickey Run watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -76.94958336012286,\n 38.92687361638758\n ],\n [\n -76.97486693402884,\n 38.92687361638758\n ],\n [\n -76.97486693402884,\n 38.911511964679875\n ],\n [\n -76.94958336012286,\n 38.911511964679875\n ],\n [\n -76.94958336012286,\n 38.92687361638758\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Clifton, Zachary J. 0000-0002-8148-5454","orcid":"https://orcid.org/0000-0002-8148-5454","contributorId":220551,"corporation":false,"usgs":true,"family":"Clifton","given":"Zachary","middleInitial":"J.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":872704,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gellis, Allen C. 0000-0002-3449-2889 agellis@usgs.gov","orcid":"https://orcid.org/0000-0002-3449-2889","contributorId":197684,"corporation":false,"usgs":true,"family":"Gellis","given":"Allen","email":"agellis@usgs.gov","middleInitial":"C.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":872706,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Staub, Leah Ellen 0000-0002-1460-6084","orcid":"https://orcid.org/0000-0002-1460-6084","contributorId":299035,"corporation":false,"usgs":true,"family":"Staub","given":"Leah","email":"","middleInitial":"Ellen","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":872705,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cashman, Matthew J. 0000-0002-6635-4309","orcid":"https://orcid.org/0000-0002-6635-4309","contributorId":203315,"corporation":false,"usgs":true,"family":"Cashman","given":"Matthew","middleInitial":"J.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":872707,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Conaway, Christopher H. 0000-0002-0991-033X","orcid":"https://orcid.org/0000-0002-0991-033X","contributorId":201932,"corporation":false,"usgs":true,"family":"Conaway","given":"Christopher H.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":872710,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lane, Cecilia","contributorId":305405,"corporation":false,"usgs":false,"family":"Lane","given":"Cecilia","affiliations":[{"id":66226,"text":"DC Department of Energy and the Environment","active":true,"usgs":false}],"preferred":false,"id":872708,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pilat, David","contributorId":305406,"corporation":false,"usgs":false,"family":"Pilat","given":"David","email":"","affiliations":[{"id":66226,"text":"DC Department of Energy and the Environment","active":true,"usgs":false}],"preferred":false,"id":872709,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70242969,"text":"70242969 - 2023 - Contributions to uncertainty in runup forecasts","interactions":[],"lastModifiedDate":"2025-03-21T13:53:32.806654","indexId":"70242969","displayToPublicDate":"2023-04-15T09:33:01","publicationYear":"2023","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Contributions to uncertainty in runup forecasts","docAbstract":"

The U.S. Geological Survey (USGS) provides operational forecasts of total water levels (TWL) and coastal change. Uncertainties around forecast TWL are based on the temporal and spatial range of observed beach slopes near the forecast site. This paper investigates other sources of uncertainty that are not accounted for, focusing on four beaches where the USGS has deployed remote cameras, and on outer Cape Cod, which has diverse bar morphologies. We find that the range of runup indicated by ten formulae is nearly as large as the variations caused by the range of beach slopes. A formula that accounts for bar morphology substantially decreases calculated runup, and might improve forecasts. Errors in the timing of forecast storm landfall generate uncertainties in TWL where tides are large. Analyses suggest that the effect of off-normal incident waves is relatively small. These results suggest opportunities for improving the TWL forecasts.

","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Coastal sediments 2023","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"Coastal Sediments 2023","conferenceDate":"April 11-15, 2023","conferenceLocation":"New Orleans, LA","language":"English","publisher":"World Scientific","doi":"10.1142/9789811275135_0037","usgsCitation":"Sherwood, C.R., Aretxabaleta, A., Traykovski, P.A., Over, J.R., Foster, D.S., Miselis, J.L., Nelson, T., and Sogut, E., 2023, Contributions to uncertainty in runup forecasts, in Coastal sediments 2023, New Orleans, LA, April 11-15, 2023, p. 401-418, https://doi.org/10.1142/9789811275135_0037.","productDescription":"18 p.","startPage":"401","endPage":"418","ipdsId":"IP-142392","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":416237,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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jover@usgs.gov","orcid":"https://orcid.org/0000-0001-6753-7185","contributorId":260178,"corporation":false,"usgs":true,"family":"Over","given":"Jin-Si","email":"jover@usgs.gov","middleInitial":"R.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":870392,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"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":870393,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Miselis, Jennifer L. 0000-0002-4925-3979 jmiselis@usgs.gov","orcid":"https://orcid.org/0000-0002-4925-3979","contributorId":3914,"corporation":false,"usgs":true,"family":"Miselis","given":"Jennifer","email":"jmiselis@usgs.gov","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":870394,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Nelson, Tim","contributorId":174639,"corporation":false,"usgs":false,"family":"Nelson","given":"Tim","email":"","affiliations":[],"preferred":false,"id":870395,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sogut, Erdinc 0000-0002-8291-9429","orcid":"https://orcid.org/0000-0002-8291-9429","contributorId":304424,"corporation":false,"usgs":true,"family":"Sogut","given":"Erdinc","email":"","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":870477,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70238112,"text":"70238112 - 2023 - Modeling fluvial sediment plumes: Impacts to coral reefs","interactions":[],"lastModifiedDate":"2023-06-13T13:47:30.856984","indexId":"70238112","displayToPublicDate":"2023-04-15T09:31:43","publicationYear":"2023","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Modeling fluvial sediment plumes: Impacts to coral reefs","docAbstract":"

To help guide watershed restoration to reduce the impacts to adjacent coral reefs, the United States Geological Survey and Deltares acquired and analyzed oceanographic and sedimentologic data off 5 West Maui watersheds to calibrate and validate physics-based, numerical hydrodynamic and sediment transport models of the study area. The results indicated sheltered sites are impacted by terrestrial sediment from single stream mouths, with most of the sediment delivered within hours of a flood event. Once this sediment enters the nearshore, it settles out and remains on the reef for a prolonged period. In contrast, the coral reefs along “open” sections of coastline are more exposed to waves and terrestrial sediment from multiple stream sources and the terrestrial sediment can rarely settle but instead remains in suspension, causing turbidity. These analyses underscore the importance of understanding how hydro-dynamics can lead to different sediment dynamics on coral reefs in the same region.

","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"The proceedings of the coastal sediments 2023","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"Coastal Sediments 2023","conferenceDate":"April 11-15, 2023","conferenceLocation":"New Orleans, LA","language":"English","publisher":"World Scientific","doi":"10.1142/9789811275135_0151","usgsCitation":"Storlazzi, C.D., van der Heijden, L., Cheriton, O.M., McCall, R.T., and Winter, G., 2023, Modeling fluvial sediment plumes: Impacts to coral reefs, in The proceedings of the coastal sediments 2023, New Orleans, LA, April 11-15, 2023, p. 1633-1644, https://doi.org/10.1142/9789811275135_0151.","productDescription":"12 p.","startPage":"1633","endPage":"1644","ipdsId":"IP-139394","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":416378,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2023-03-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Storlazzi, Curt D. 0000-0001-8057-4490","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":213610,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt","middleInitial":"D.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":856904,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"van der Heijden, Luuk","contributorId":299030,"corporation":false,"usgs":false,"family":"van der Heijden","given":"Luuk","affiliations":[{"id":36257,"text":"Deltares","active":true,"usgs":false}],"preferred":false,"id":856905,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cheriton, Olivia M. 0000-0003-3011-9136","orcid":"https://orcid.org/0000-0003-3011-9136","contributorId":204459,"corporation":false,"usgs":true,"family":"Cheriton","given":"Olivia","middleInitial":"M.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":856906,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McCall, Robert T.","contributorId":148986,"corporation":false,"usgs":false,"family":"McCall","given":"Robert","email":"","middleInitial":"T.","affiliations":[{"id":12474,"text":"Deltares, Netherlands","active":true,"usgs":false}],"preferred":false,"id":856907,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Winter, Gundula","contributorId":204988,"corporation":false,"usgs":false,"family":"Winter","given":"Gundula","email":"","affiliations":[],"preferred":false,"id":856908,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70243278,"text":"70243278 - 2023 - Sand- and gravel-trapping efficiencies derived for four types of pressure-difference bedload samplers","interactions":[],"lastModifiedDate":"2023-05-05T14:49:51.798384","indexId":"70243278","displayToPublicDate":"2023-04-15T09:31:22","publicationYear":"2023","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Sand- and gravel-trapping efficiencies derived for four types of pressure-difference bedload samplers","docAbstract":"Bedload-trapping efficiencies (coefficients) were derived for four types of pressure-difference bedload samplers at the St. Anthony Falls Laboratory, University of Minnesota during the first two phases of flume experiments in January-March, 2006, referred to as “StreamLab06.” The bedload-sampler research component was part of a series of community-led, large-scale laboratory experiments performed under the auspices of the National Center for Earth-surface Dynamics (Marr and others, 2010; Singh and others, 2013; Gray and others, 2010, 2019, 2021).\n\nA bedload-trapping coefficient is the ratio of the mass of bedload – sediment transported by rolling, sliding, or skipping in close contact with the riverbed – collected by the deployed sampler, to the mass of bedload that would have passed through the width of the sample section at the same time but in the absence of the sampler (Hubbell, 1964). A trapping coefficient of 1.0 would mean the mass of every particle-size fraction of sediment in the collected sample is in the same proportion as those in transport. \n\nFor the 2006 experiments, a Helley-Smith (intake-nozzle width of 76.2 millimeter [mm] and height of 76.2 mm), BLH-84 (76.2 mm × 76.2 mm), Elwha (203 mm × 102 mm) and Toutle River-2 (TR-2; 305 mm × 152 mm) were repeatedly deployed by a hand-held rod with a stabilizing tether line in the main flume. Six combinations of bedload sampler types and bed compositions were tested: The BLH-84, Elwha, and Helley-Smith samplers were deployed on a sand bed (d50 = 1.0 mm) during five steady flows ranging from 2.0-3.6 cubic meters per second (m3/s). The BLH-84, Elwha, and TR-2 samplers were deployed on a gravel bed (d50 = 11.2 mm) at four steady flows ranging from 4.0-5.5 m3/s.\n \nBedload samples collected manually as part of 37 trials – each associated with a unique combination of a bedload sampler type, steady-flow rate, and bed composition – and associated ancillary data were used to calculate 2,030 instantaneous, at-a-point bedload-transport rates (1,000 as part of 19 sand-bed trials, and 1,030 as part of 27 gravel-bed trials.). Five contiguous weigh drums embedded in a slot spanning the width of the flume independently and continuously weighed captured bedload on approximately 1.1-second intervals. Approximately 3.8-million individual weigh-drum time-series measurements were recorded during the bedload sampler experiments (Groten and Gray, 2021; Gray and others, 2021). \n ","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"SEDHYD 2023","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"SEDHYD-2023, Sedimentation and Hydrologic Modeling Conference","conferenceDate":"May 8-12, 2023","conferenceLocation":"St. Louis, MO","language":"English","publisher":"SEDHYD","usgsCitation":"Gray, J., Groten, J.T., Czuba, J.A., Schwarz, G.E., Strom, K., and Diplas, P., 2023, Sand- and gravel-trapping efficiencies derived for four types of pressure-difference bedload samplers, in SEDHYD 2023, St. Louis, MO, May 8-12, 2023, 4 p.","productDescription":"4 p.","ipdsId":"IP-151010","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":416760,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":416744,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.sedhyd.org/2023Program/s169.html","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gray, John","contributorId":304862,"corporation":false,"usgs":false,"family":"Gray","given":"John","affiliations":[{"id":66176,"text":"Gray Sedimentology","active":true,"usgs":false}],"preferred":false,"id":871781,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Groten, Joel T. 0000-0002-0441-8442 jgroten@usgs.gov","orcid":"https://orcid.org/0000-0002-0441-8442","contributorId":173464,"corporation":false,"usgs":true,"family":"Groten","given":"Joel","email":"jgroten@usgs.gov","middleInitial":"T.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":871782,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Czuba, Jonathan A. 0000-0002-9485-2604","orcid":"https://orcid.org/0000-0002-9485-2604","contributorId":301942,"corporation":false,"usgs":false,"family":"Czuba","given":"Jonathan","email":"","middleInitial":"A.","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":871783,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schwarz, Gregory E. 0000-0002-9239-4566 gschwarz@usgs.gov","orcid":"https://orcid.org/0000-0002-9239-4566","contributorId":213621,"corporation":false,"usgs":true,"family":"Schwarz","given":"Gregory","email":"gschwarz@usgs.gov","middleInitial":"E.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","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":871784,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Strom, Kyle","contributorId":304863,"corporation":false,"usgs":false,"family":"Strom","given":"Kyle","email":"","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":871785,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Diplas, Panayiotis","contributorId":304864,"corporation":false,"usgs":false,"family":"Diplas","given":"Panayiotis","email":"","affiliations":[{"id":16160,"text":"Lehigh University","active":true,"usgs":false}],"preferred":false,"id":871786,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70243262,"text":"70243262 - 2023 - How machine learning can improve predictions and provide insight into fluvial sediment transport in Minnesota","interactions":[],"lastModifiedDate":"2023-05-05T14:30:38.523906","indexId":"70243262","displayToPublicDate":"2023-04-15T09:25:15","publicationYear":"2023","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"How machine learning can improve predictions and provide insight into fluvial sediment transport in Minnesota","docAbstract":"

Understanding fluvial sediment transport is critical to addressing many environmental concerns such as exacerbated flooding, degradation of aquatic habitat, excess nutrients, and the economic challenges of restoring aquatic systems. However, fluvial sediment transport is difficult to understand because of the multitude of factors controlling the potential sources, delivery, mechanics, and storage of sediment in aquatic systems. While physical fluvial sediment samples are an integral part of developing solutions for these environmental concerns, samples cannot be collected at every river and time of interest. Therefore, accurate and cost-effective estimates of sediment loading are needed to manage riverine sediment transport at a multitude of scales (Ellison et al. 2016); also needed are methods to estimate sediment transport at sites where little or no physical samples have been collected (Gray & Simes 2008). The application of machine learning (ML) approaches to estimate sediment transport has grown over the past two decades (Afan et al. 2016). ML used in sediment transport research has shown multiple benefits over traditional approaches, such as increased prediction accuracy, the ability to learn complex linear and non-linear relations amongst the dataset and providing the ability to interpret these complex relations with important features used in the model (Cisty et al. 2021; Francke et al. 2008; Khan et al. 2021; Zounemat-Kermani et al. 2020; Cutler et al. 2007). 

","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"SEDHYD 2023","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"SEDHYD-2023, Sedimentation and Hydrologic Modeling Conference","conferenceDate":"May 8-12, 2023","conferenceLocation":"St. Louis, MO","language":"English","publisher":"SEDHYD","usgsCitation":"Lund, J., Groten, J.T., Karwan, D.L., and Babcock, C., 2023, How machine learning can improve predictions and provide insight into fluvial sediment transport in Minnesota, in SEDHYD 2023, St. Louis, MO, May 8-12, 2023, 5 p.","productDescription":"5 p.","ipdsId":"IP-148054","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":416759,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":416740,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.sedhyd.org/2023Program/s18.html"}],"country":"United 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William","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":871722,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Groten, Joel T. 0000-0002-0441-8442 jgroten@usgs.gov","orcid":"https://orcid.org/0000-0002-0441-8442","contributorId":173464,"corporation":false,"usgs":true,"family":"Groten","given":"Joel","email":"jgroten@usgs.gov","middleInitial":"T.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":871723,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Karwan, Diana L.","contributorId":207315,"corporation":false,"usgs":false,"family":"Karwan","given":"Diana","email":"","middleInitial":"L.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":871724,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Babcock, Chad","contributorId":150502,"corporation":false,"usgs":false,"family":"Babcock","given":"Chad","email":"","affiliations":[{"id":18039,"text":"Department of Geography, Michigan State University, East Lansing, Michigan USA","active":true,"usgs":false}],"preferred":false,"id":871725,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70238893,"text":"70238893 - 2023 - Modeling total water level and coastal change at Pea Island, North Carolina, USA","interactions":[],"lastModifiedDate":"2023-04-26T15:15:18.007805","indexId":"70238893","displayToPublicDate":"2023-04-15T09:05:12","publicationYear":"2023","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Modeling total water level and coastal change at Pea Island, North Carolina, USA","docAbstract":"

The DUring Nearshore Event eXperiment (DUNEX) was carried out on Pea Island, North Carolina, USA between September-October 2021. We use a coupled numerical model (Windsurf) to hindcast the evolution of the DUNEX transect and produce a time series of hourly water levels at the shoreline from the model output. In addition to assessing the ability of Windsurf to reproduce TWL, we use model output paired with an ensemble of empirical models to assess how TWL forecasts can be improved by incorporating dynamic morphology. The morphological hindcast achieved an RMSE of 0.10 m and a BSS of 0.47, while the total water level (TWL) time series from the model correlates with the U.S. Geological Survey forecast (r2 = 0.61) for the study period but with a 0.47 m bias that is primarily due to the much steeper beach slope used to produce the forecast compared to that surveyed at the start of the study period. We find that using dynamic morphology provides a small but statistically significant (α = 0.05) improvement in predicting TWL versus applying the pre-storm beach slope to the whole time series.

","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"The proceedings of the coastal sediments 2023","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"Coastal Sediments 2023","conferenceDate":"April 11-15, 2023","conferenceLocation":"New Orleans, LA","language":"English","publisher":"World Scientific","doi":"10.1142/9789811275135_0065","usgsCitation":"Itzkin, M., Palmsten, M.L., Buckley, M.L., Sherwood, C.R., Brown, J., Over, J., and Peter A. Traykovski, 2023, Modeling total water level and coastal change at Pea Island, North Carolina, USA, in The proceedings of the coastal sediments 2023, New Orleans, LA, April 11-15, 2023, p. 698-710, https://doi.org/10.1142/9789811275135_0065.","productDescription":"13 p.","startPage":"698","endPage":"710","ipdsId":"IP-147703","costCenters":[{"id":574,"text":"St. Petersburg 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":416370,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina","otherGeospatial":"Pea Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -75.5389833081896,\n 35.774620167631255\n ],\n [\n -75.5389833081896,\n 35.61317806103199\n ],\n [\n -75.43927736569074,\n 35.61317806103199\n ],\n [\n -75.43927736569074,\n 35.774620167631255\n ],\n [\n -75.5389833081896,\n 35.774620167631255\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2023-03-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Itzkin, Michael 0000-0003-0693-0607","orcid":"https://orcid.org/0000-0003-0693-0607","contributorId":291846,"corporation":false,"usgs":true,"family":"Itzkin","given":"Michael","email":"","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":859077,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Palmsten, Margaret L. 0000-0002-6424-2338","orcid":"https://orcid.org/0000-0002-6424-2338","contributorId":239955,"corporation":false,"usgs":true,"family":"Palmsten","given":"Margaret","email":"","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":859078,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buckley, Mark L. 0000-0002-1909-4831","orcid":"https://orcid.org/0000-0002-1909-4831","contributorId":203481,"corporation":false,"usgs":true,"family":"Buckley","given":"Mark","email":"","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":859079,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sherwood, Christopher R. 0000-0001-6135-3553 csherwood@usgs.gov","orcid":"https://orcid.org/0000-0001-6135-3553","contributorId":2866,"corporation":false,"usgs":true,"family":"Sherwood","given":"Christopher","email":"csherwood@usgs.gov","middleInitial":"R.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":859080,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brown, Jenna A. 0000-0003-3137-7073","orcid":"https://orcid.org/0000-0003-3137-7073","contributorId":208564,"corporation":false,"usgs":true,"family":"Brown","given":"Jenna A.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":859081,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Over, Jin-Si R. 0000-0001-6753-7185","orcid":"https://orcid.org/0000-0001-6753-7185","contributorId":299942,"corporation":false,"usgs":false,"family":"Over","given":"Jin-Si R.","affiliations":[],"preferred":false,"id":859082,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Peter A. Traykovski","contributorId":299943,"corporation":false,"usgs":false,"family":"Peter A. Traykovski","affiliations":[{"id":13294,"text":"Woods Hole Oceanographic Institute","active":true,"usgs":false}],"preferred":false,"id":859083,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70242972,"text":"70242972 - 2023 - Toward a total water level forecast of the Great Lakes","interactions":[],"lastModifiedDate":"2023-04-26T10:59:03.669428","indexId":"70242972","displayToPublicDate":"2023-04-15T09:03:50","publicationYear":"2023","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Toward a total water level forecast of the Great Lakes","docAbstract":"

The combined effect of storm surge and large waves is the main driving mechanism that erodes beaches, inundates low-lying areas, leading to millions of dollars in property damage, loss of natural resources, and lives. The U.S. Geological Survey (USGS) aims to expand the real-time total water level (TWL) forecast provided in the Operational Total Water Level and Coastal Change Forecasts (TWL&CC) to the Great Lakes short- (0 – 36 hours) to medium-term (3 – 5 days) coastal-hazard forecasts to inform planners and emergency responders. This study assesses the skill of forecast water levels and wave characteristics required as input to the TWL forecasts. It finds that, while skill generally decreases as forecast period increases, these data are suitable as input to the TWL forecast system. As the TWL predictions depend on the water level and wave forecasts, validation against field observations allow evaluation of their suitability for the Great Lakes. These results have implications on the prediction of water levels and their potential impacts on coastal resiliency in North America.

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modeling approaches in Michigan rivers","docAbstract":"

Excess or limited fluvial sediment transport can contribute to and exacerbate many environmental issues including nutrient loading, aquatic habitat degradation, flooding, channel navigation dredging, dam operation, and stream degradation or aggradation. However, fluvial sediment transport is difficult and expensive to comprehensively characterize because it can vary substantially both temporally and spatially. Having better estimates of fluvial sediment transport is important for understanding and solving these environmental issues when it is not possible to collect fluvial sediment samples. Different modeling approaches can be used to help estimate suspended sediment when sampling data are limited or unavailable. This study compared dimensionless sediment rating curves (DSRCs) developed in Pagosa Springs Colorado, Minnesota, and Michigan to determine if these DSRCs were suitable to make predictions of suspended sediment for Michigan rivers.

Approximately 3,000 suspended sediment samples collected in or near Michigan from the mid-1960s through August 2022 were used to develop two DSRC models. The DSRCs developed in Michigan include a pooled DSRC model which uses nonlinear least squares regression, and a mixed-effects DSRC model which uses a mixed-effects modeling approach. In general, there was not a noticeable improvement in the performance of the Michigan mixed-effects DSRC model over the Michigan pooled DSRC model. The two Michigan DSRCs were evaluated against DSRCs developed for Pagosa Springs and Minnesota. The results showed DSRC models developed from Minnesota and Michigan were similar to each other. In contrast, the Pagosa Springs DSRC predicts higher suspended-sediment concentration (SSC) at low flows and increases at a higher rate due to having a greater exponent. The Pagosa Springs DSRC produces higher SSC predictions that do not approximate the observed data well at most of the Michigan sites in the study. The results suggest that the Pagosa Springs DSRC was not suitable to make predictions of suspended sediment for Michigan rivers. The similarity of the DSRC equations developed for Minnesota and Michigan compared to the Pagosa Springs DSRC equation suggest that there may be regional patterns of SSC in the upper Midwest rivers that differ from those in other areas of the country like Pagosa Springs. A regionally applicable model could be developed and strengthened by combining data from additional midwestern states. Since the Michigan DSRCs goodness-of-fit metrics were comparable to the site-specific simple linear regressions (SLRs) and outperformed them in the aggregate goodness-of-fit metrics, the Michigan DSRCs are suitable to make predictions of suspended sediment in Michigan rivers with limited data. However, the availability of the DSRCs from this study should not diminish the value of collecting physical samples and exploring alternative modeling approaches because of the uncertainty associated with using DSRCs. Approximately 3,000 suspended sediment samples collected in or near Michigan from the mid-1960s through August 2022 were used to develop two DSRC models. The DSRCs developed in Michigan include a pooled DSRC model which uses nonlinear least squares regression, and a mixed-effects DSRC model which uses a mixed-effects modeling approach. In general, there was not a noticeable improvement in the performance of the Michigan mixed-effects DSRC model over the Michigan pooled DSRC model. The two Michigan DSRCs were evaluated against DSRCs developed for Pagosa Springs and Minnesota. The results showed DSRC models developed from Minnesota and Michigan were similar to each other. In contrast, the Pagosa Springs DSRC predicts higher suspended-sediment concentration (SSC) at low flows and increases at a higher rate due to having a greater exponent. The Pagosa Springs DSRC produces higher SSC predictions that do not approximate the observed data well at most of the Michigan sites in the study. The results suggest that the Pagosa Springs DSRC was not suitable to make predictions of suspended sediment for Michigan rivers. The similarity of the DSRC equations developed for Minnesota and Michigan compared to the Pagosa Springs DSRC equation suggest that there may be regional patterns of SSC in the upper Midwest rivers that differ from those in other areas of the country like Pagosa Springs. A regionally applicable model could be developed and strengthened by combining data from additional midwestern states. Since the Michigan DSRCs goodness-of-fit metrics were comparable to the site-specific simple linear regressions (SLRs) and outperformed them in the aggregate goodness-of-fit metrics, the Michigan DSRCs are suitable to make predictions of suspended sediment in Michigan rivers with limited data. However, the availability of the DSRCs from this study should not diminish the value of collecting physical samples and exploring alternative modeling approaches because of the uncertainty associated with using DSRCs.

","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"SEDHYD 2023","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"SEDHYD-2023, Sedimentation and Hydrologic Modeling Conference","conferenceDate":"May 8-12, 2023","conferenceLocation":"St. Louis, MO","language":"English","publisher":"SEDHYD","usgsCitation":"Groten, J.T., Levin, S., Coenen, E., Lund, J., and Matousek, B., 2023, Comparing empirical sediment transport modeling approaches in Michigan rivers, in SEDHYD 2023, St. Louis, MO, May 8-12, 2023.","ipdsId":"IP-127397","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":416758,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":416746,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.sedhyd.org/2023Program/s17.html"}],"country":"United 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0000-0003-2470-3854","orcid":"https://orcid.org/0000-0003-2470-3854","contributorId":211159,"corporation":false,"usgs":true,"family":"Coenen","given":"Erin N.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":871851,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lund, J. William 0000-0002-8830-4468","orcid":"https://orcid.org/0000-0002-8830-4468","contributorId":289132,"corporation":false,"usgs":true,"family":"Lund","given":"J. William","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":871852,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Matousek, Bethany","contributorId":304881,"corporation":false,"usgs":false,"family":"Matousek","given":"Bethany","email":"","affiliations":[{"id":66186,"text":"Michigan Department of Environment, Great Lakes, and Energy","active":true,"usgs":false}],"preferred":false,"id":871853,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70247427,"text":"70247427 - 2023 - Regional streamflow drought forecasting in the Colorado River Basin using Deep Neural Network models","interactions":[],"lastModifiedDate":"2023-08-07T14:02:02.242741","indexId":"70247427","displayToPublicDate":"2023-04-15T08:48:17","publicationYear":"2023","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Regional streamflow drought forecasting in the Colorado River Basin using Deep Neural Network models","docAbstract":"

Process-based, large-scale (e.g., conterminous United States [CONUS]) hydrologic models have struggled to achieve reliable streamflow drought performance in arid regions and for low-flow periods. Deep learning has recently seen broad implementation in streamflow prediction and forecasting research projects throughout the world with performance often equaling or exceeding that of process-based models. Deep learning models are a possible approach to increase the accuracy of streamflow drought predictions and to expand the spatial coverage of river locations with available streamflow drought forecasts.

As part of a multi-component Data-Driven Drought Prediction project, the U.S. Geological Survey is developing and testing deep learning models for streamflow drought forecasting. In this work, we present preliminary results of a deep learning model capable of predicting streamflow drought occurrence at ungaged locations for the Colorado River Basin (CRB). A long short-term memory (LSTM) neural network model was trained using 40 years (1980-2020) of daily streamflow data from 425 streamgages within and surrounding the CRB using static watershed attributes as well as meteorological and remotely sensed dynamic forcing inputs. Model tests were performed to evaluate model accuracy for now-casting streamflow drought conditions at ungaged locations and for forecasting drought conditions at lead times ranging from 0 to 14 days. Nearly all model configurations showed behavioral performance for predicting daily streamflow percentiles. Comparisons of LSTM model performance for predicting drought using fixed drought thresholds (calculated over all days and years) and variable drought thresholds (unique threshold calculated for each day of the year) identify differences in model skill between locations with implications for model design.

","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of SEDHYD 2023","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"SEDHYD","conferenceDate":"May 8-12, 2023","conferenceLocation":"St. Louis, MO","language":"English","publisher":"SEDHYD","usgsCitation":"Hamshaw, S.D., Goodling, P.J., Hafen, K., Hammond, J., McShane, R., Sando, R., Shastry, A.R., Simeone, C.E., Watkins, D., White, E., and Wieczorek, M., 2023, Regional streamflow drought forecasting in the Colorado River Basin using Deep Neural Network models, in Proceedings of SEDHYD 2023, St. Louis, MO, May 8-12, 2023, 15 p.","productDescription":"15 p.","ipdsId":"IP-151973","costCenters":[{"id":227,"text":"Earth Surface Dynamics Program","active":true,"usgs":true},{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":419560,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":419548,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.sedhyd.org/2023Program/s181.html"}],"country":"United States","otherGeospatial":"Colorado River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -114.60045372623478,\n 31.258330936607123\n ],\n [\n -110.59254302741863,\n 31.054063075754513\n ],\n [\n -108.59802952983767,\n 31.359920476818175\n ],\n [\n -107.77329728728904,\n 32.667013027627036\n ],\n [\n -105.33291815667258,\n 38.21996621737378\n ],\n [\n -105.64401667449579,\n 40.61584869706027\n ],\n [\n -108.25906974720414,\n 42.992213339755665\n ],\n [\n -110.41906640637575,\n 43.12924273929244\n ],\n [\n -111.27275669412631,\n 41.39663030950132\n ],\n [\n -112.47810183593663,\n 38.504465490675386\n ],\n [\n -113.09970923969854,\n 37.353465042204334\n ],\n [\n -114.3929667988645,\n 37.49906345159148\n ],\n [\n -114.6266795454161,\n 38.107130943367025\n ],\n [\n -115.48463166591264,\n 39.43479765478551\n ],\n [\n -115.68353845853977,\n 37.41554450267796\n ],\n [\n -115.1115276804997,\n 33.75507968847421\n ],\n [\n -115.55059550089697,\n 31.937316150454635\n ],\n [\n -114.60045372623478,\n 31.258330936607123\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hamshaw, Scott Douglas 0000-0002-0583-4237","orcid":"https://orcid.org/0000-0002-0583-4237","contributorId":305601,"corporation":false,"usgs":true,"family":"Hamshaw","given":"Scott","email":"","middleInitial":"Douglas","affiliations":[{"id":37778,"text":"WMA - 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2023 - Sediment sources and connectivity linked to hydrologic pathways and geomorphic processes: A conceptual model to specify sediment sources and pathways through space and time","interactions":[],"lastModifiedDate":"2023-05-31T13:46:59.201583","indexId":"70244030","displayToPublicDate":"2023-04-15T08:43:15","publicationYear":"2023","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Sediment sources and connectivity linked to hydrologic pathways and geomorphic processes: A conceptual model to specify sediment sources and pathways through space and time","docAbstract":"

Sediment connectivity is a framework for transfer and storage of sediment among different geomorphic compartments across upland and channel network of the catchment sediment cascade. Sediment connectivity and dysconnectivity (i.e., source delivery and storage processes) are linked to the water cycle and hydrologic systems with the associated multiscale interactions with climate, soil, topography, ecology, and landuse/landcover under natural variability and human intervention. We review the sediment connectivity concept and frameworks developed in the last few decades to examine and quantify water and sediment transfer in catchment systems. Past conceptual models of connectivity have attempted to integrate multiple processes into sediment domain, including geomorphic, hydrologic, and ecological processes (i.e., “holistic approach to connectivity”). In particular, multiple studies highlight the importance of sediment and water interaction in defining landscape connectivity. There are also efforts to quantify the topographic controls on sediment connectivity, in the advent of increasingly high-resolution digital terrain models. More recent modeling efforts have integrated structural and functional connectivity through coupling topographic information with hydrologic simulation models. Though this recent modeling development is encouraging, a comprehensive sediment connectivity framework that integrates geomorphic and hydrologic processes across spatiotemporal scales is yet to be conceived. Such an effort will require understanding the governing hydrologic and geomorphic processes that control sediment source, storage, and transport. A conceptual model is proposed to describe dominant hydrologic-sediment connectivity regimes through spatial-temporal feedbacks between hydrologic processes (rainfall, flow routing, and water residence time) and geomorphic drivers (upland soil erosion and deposition, and geomorphic channel erosion and deposition response). Recent advancements in landscape monitoring techniques using geochemical tracers, remote-sensing, increasing availability of hydrologic monitoring data, and the integration of various analytic methods (e.g., isotopic hydrograph separation, stormflow concentration-discharge, hysteretic behavior analysis) have the potential to broaden the spatial and temporal scales of geomorphic observations and understanding of landscape sediment connectivity. Using the conceptual model as a “thinking” space, we examine sediment and hydrologic interactions in real world examples of watershed studies using multiple lines of evidence and modeling techniques.

","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"SEDHYD 2023","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"SEDHYD-2023, Sedimentation and Hydrologic Modeling Conference","language":"English","publisher":"SEDHYD","usgsCitation":"Cho, J., Karwan, D., Skalak, K., Pizzuto, J., and Huffman, M., 2023, Sediment sources and connectivity linked to hydrologic pathways and geomorphic processes: A conceptual model to specify sediment sources and pathways through space and time, in SEDHYD 2023, 14 p.","productDescription":"14 p.","ipdsId":"IP-150563","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":417576,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":417575,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.sedhyd.org/2023Program/s252.html","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Cho, Jong 0000-0001-5514-6056","orcid":"https://orcid.org/0000-0001-5514-6056","contributorId":291384,"corporation":false,"usgs":true,"family":"Cho","given":"Jong","email":"","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":874198,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Karwan, Diana","contributorId":305967,"corporation":false,"usgs":false,"family":"Karwan","given":"Diana","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":874199,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":874200,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pizzuto, James","contributorId":305968,"corporation":false,"usgs":false,"family":"Pizzuto","given":"James","affiliations":[{"id":13359,"text":"University of Delaware","active":true,"usgs":false}],"preferred":false,"id":874201,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Huffman, Max","contributorId":305969,"corporation":false,"usgs":false,"family":"Huffman","given":"Max","email":"","affiliations":[{"id":13359,"text":"University of Delaware","active":true,"usgs":false}],"preferred":false,"id":874202,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70242982,"text":"70242982 - 2023 - Wave-scale observations of sediment resuspension and subsequent transport across a fringing reef flat","interactions":[],"lastModifiedDate":"2023-04-26T15:33:51.787502","indexId":"70242982","displayToPublicDate":"2023-04-15T08:26:20","publicationYear":"2023","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Wave-scale observations of sediment resuspension and subsequent transport across a fringing reef flat","docAbstract":"

During a 3-month deployment on a broad, fringing reef flat in Moloka’i, Hawai’i, we observed over 28,000 wave-driven resuspension (WDR) events of coarse-grained sediment in order to identify major factors. These events were short-lived (2-11 s) and distinct from the longer-duration patterns of water-column backscatter. The wave-driven transport of WDR events was onshore, but the net cross-shore transport was ultimately controlled by water levels. Higher water levels produced larger reef-flat waves, which were requisite for these events to occur. But rising water levels also drove stronger offshore flows. Consequently, onshore net transport of WDR events only occurred within a narrow water-level range, when waves were sufficiently large, but the offshore flow was still weak. Our observations demonstrate how cross-shore transport of coarse-grained material over reef flats is sensitive to changing water levels. Rising sea levels will likely alter transport patterns, which will in turn affect cross-shore delivery of carbonate sand to adjacent shorelines.

","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"The proceedings of the coastal sediments 2023","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"Coastal Sediments 2023","conferenceDate":"April 11-15, 2023","conferenceLocation":"New Orleans, LA","language":"English","publisher":"World Scientific","doi":"10.1142/9789811275135_0149","usgsCitation":"Cheriton, O.M., Storlazzi, C.D., Rosenberger, K.J., Logan, J.B., Pomeroy, A.W., Buckley, M.L., Hansen, J., and Lowe, R.J., 2023, Wave-scale observations of sediment resuspension and subsequent transport across a fringing reef flat, in The proceedings of the coastal sediments 2023, New Orleans, LA, April 11-15, 2023, p. 1607-1620, https://doi.org/10.1142/9789811275135_0149.","productDescription":"14 p.","startPage":"1607","endPage":"1620","ipdsId":"IP-146881","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":416232,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Moloka’i","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -157.3653823397134,\n 21.357607270544236\n ],\n [\n -157.3653823397134,\n 20.982311984976448\n ],\n [\n -156.62350443964868,\n 20.982311984976448\n ],\n [\n -156.62350443964868,\n 21.357607270544236\n ],\n [\n -157.3653823397134,\n 21.357607270544236\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2023-03-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Cheriton, Olivia M. 0000-0003-3011-9136","orcid":"https://orcid.org/0000-0003-3011-9136","contributorId":204459,"corporation":false,"usgs":true,"family":"Cheriton","given":"Olivia","middleInitial":"M.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":870422,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Storlazzi, Curt D. 0000-0001-8057-4490","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":213610,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt","middleInitial":"D.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":870423,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rosenberger, Kurt J. 0000-0002-5185-5776 krosenberger@usgs.gov","orcid":"https://orcid.org/0000-0002-5185-5776","contributorId":140453,"corporation":false,"usgs":true,"family":"Rosenberger","given":"Kurt","email":"krosenberger@usgs.gov","middleInitial":"J.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":870424,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Logan, Joshua B. 0000-0002-6191-4119 jlogan@usgs.gov","orcid":"https://orcid.org/0000-0002-6191-4119","contributorId":2335,"corporation":false,"usgs":true,"family":"Logan","given":"Joshua","email":"jlogan@usgs.gov","middleInitial":"B.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":870425,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pomeroy, Andrew W. M.","contributorId":304433,"corporation":false,"usgs":false,"family":"Pomeroy","given":"Andrew","email":"","middleInitial":"W. M.","affiliations":[{"id":13336,"text":"University of Melbourne","active":true,"usgs":false}],"preferred":false,"id":870426,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Buckley, Mark L. 0000-0002-1909-4831","orcid":"https://orcid.org/0000-0002-1909-4831","contributorId":203481,"corporation":false,"usgs":true,"family":"Buckley","given":"Mark","email":"","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":870427,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hansen, Jeff E.","contributorId":298815,"corporation":false,"usgs":false,"family":"Hansen","given":"Jeff E.","affiliations":[{"id":24588,"text":"The University of Western Australia","active":true,"usgs":false}],"preferred":false,"id":870428,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lowe, Ryan J.","contributorId":152265,"corporation":false,"usgs":false,"family":"Lowe","given":"Ryan","email":"","middleInitial":"J.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":870429,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70243156,"text":"70243156 - 2023 - Hindcast of Hurricane Sally impacts on barrier islands in the Gulf of Mexico","interactions":[],"lastModifiedDate":"2023-05-02T13:26:41.325537","indexId":"70243156","displayToPublicDate":"2023-04-15T08:22:50","publicationYear":"2023","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Hindcast of Hurricane Sally impacts on barrier islands in the Gulf of Mexico","docAbstract":"

We performed XBeach and ADIRC+SWAN model simulations of Hurricane Sally over Dauphin and Petit Bois Islands off the Alabama-Mississippi coast to evaluate the morphologic response. Simulated water levels compared well with NOAA tide gauge observations to the east of Dauphin Island with a high model skill of 0.9. In addition, the XBeach model results of water levels, mean current speeds and significant wave heights agreed with ADCIRC+SWAN simulations near the offshore boundary and in the channel. Qualitative comparisons between the XBeach simulations and post-storm lidar observations confirmed model predictions of overwash. However, XBeach predicted minor breaches in Dauphin Island, which were not observed. This effort is part of a larger project in which several hydrodynamic and morphodynamic models will be coupled to produce hindcasts over a 15-year period for a larger region along the coast. These evaluations will provide local managers with strategic tools to make decisions about various coastal restoration alternatives.

","largerWorkTitle":"The proceedings of the coastal sediments 2023","conferenceTitle":"Coastal Sediments 2023","conferenceDate":"April 11-15, 2023","conferenceLocation":"New Orleans, LA","language":"English","publisher":"World Scientific","doi":"10.1142/9789811275135_0204","usgsCitation":"Frank-Gilchrist, D.P., Passeri, D., and Bilskie, M.V., 2023, Hindcast of Hurricane Sally impacts on barrier islands in the Gulf of Mexico, in The proceedings of the coastal sediments 2023, New Orleans, LA, April 11-15, 2023, p. 2220-2227, https://doi.org/10.1142/9789811275135_0204.","productDescription":"8 p.","startPage":"2220","endPage":"2227","ipdsId":"IP-147624","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":416614,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alabama, Mississippi","otherGeospatial":"Dauphin and Petit Bois Islands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -88.043598091522,\n 30.30917051732709\n ],\n [\n -88.53511493858724,\n 30.30917051732709\n ],\n [\n -88.53511493858724,\n 30.152412222672723\n ],\n [\n -88.043598091522,\n 30.152412222672723\n ],\n [\n -88.043598091522,\n 30.30917051732709\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2023-03-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Frank-Gilchrist, Donya P. 0000-0002-7146-0069","orcid":"https://orcid.org/0000-0002-7146-0069","contributorId":292926,"corporation":false,"usgs":true,"family":"Frank-Gilchrist","given":"Donya","email":"","middleInitial":"P.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":871297,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Passeri, Davina 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","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":871298,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bilskie, Matthew V.","contributorId":166891,"corporation":false,"usgs":false,"family":"Bilskie","given":"Matthew","email":"","middleInitial":"V.","affiliations":[{"id":16154,"text":"LSU","active":true,"usgs":false}],"preferred":false,"id":871299,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70246239,"text":"70246239 - 2023 - Evaluating Muskellunge catch-and-release mortality at elevated summer water temperature","interactions":[],"lastModifiedDate":"2023-10-11T15:28:34.704886","indexId":"70246239","displayToPublicDate":"2023-04-15T07:22:44","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating Muskellunge catch-and-release mortality at elevated summer water temperature","docAbstract":"

Angling for Muskellunge Esox masquinongy has become widespread and increasingly popular. Management strategies for Muskellunge include high minimum harvest lengths (>1016mm), closed seasons, and catch-and-release regulations. Due to these strategies and angler behaviors, up to 97% of Muskellunge caught are released, and anglers assume these fish survive to be caught again in the future. Previous research on catch-and-release mortality for Muskellunge has suggested relatively low mortality rates (0%-5%). However, these studies were all conducted within the range of water temperatures that are thermally optimal for Muskellunge and generally at water temperatures <25°C. Muskellunge populations in some latitudes routinely experience temperatures >25°C during the summer months. Fisheries managers and anglers have expressed concerns regarding warm water angling mortality, representing a need to evaluate mortality rates at various water temperatures and multiple latitudes. Our objective was to quantify warm-water (>25°C) catch-and-release mortality rates in Muskellunge (>760mm) and identify factors influencing mortality using experimental ponds. Adult Muskellunge (n=102) were stocked into eight earthen or plastic lined flow-through ponds (0.06-0.71 ha) at densities of <16 fish/ha. Muskellunge (n=50) were angled utilizing specialized Muskellunge fishing gear at water temperatures of 19.6–32.6°C, with 32 fish being caught at temperatures >25°C. Fish were closely monitored for 2 weeks after being angled to assess mortality, and fish that remained uncaught during the experiment were used as controls (n=53). Mortality was greater for angled (30.0%) compared to control fish (11.3%). Differences in catch-and-release mortality were compared across a range of temperature regimes using firth's logistic regression. Five-day cumulative temperature and net time were positively related to the probability of mortality, but size and sex were unrelated to mortality. Elevated catch-and-release mortality rates at warm water temperatures warrant investigations into the population level effects at varying levels of exploitation.

","language":"English","publisher":"American Fisheries Society","doi":"10.1002/tafs.10418","usgsCitation":"Booth, I.T., Hartman, K.J., Crane, D.P., Hansbarger, J., Weeks, J., Henesy, J., Walsh, H.L., and Williams, J., 2023, Evaluating Muskellunge catch-and-release mortality at elevated summer water temperature: Transactions of the American Fisheries Society, v. 152, no. 5, p. 577-593, https://doi.org/10.1002/tafs.10418.","productDescription":"17 p.","startPage":"577","endPage":"593","ipdsId":"IP-152778","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":443851,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/tafs.10418","text":"Publisher Index Page"},{"id":418581,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"152","issue":"5","noUsgsAuthors":false,"publicationDate":"2023-04-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Booth, Ian Taylor","contributorId":315375,"corporation":false,"usgs":false,"family":"Booth","given":"Ian","email":"","middleInitial":"Taylor","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":876366,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hartman, Kyle J.","contributorId":6414,"corporation":false,"usgs":false,"family":"Hartman","given":"Kyle","email":"","middleInitial":"J.","affiliations":[{"id":16210,"text":"Division of Forestry and Natural Resources, West Virginia University","active":true,"usgs":false}],"preferred":false,"id":876367,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Crane, Derek P.","contributorId":274432,"corporation":false,"usgs":false,"family":"Crane","given":"Derek","email":"","middleInitial":"P.","affiliations":[{"id":24750,"text":"Coastal Carolina University","active":true,"usgs":false}],"preferred":false,"id":876368,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hansbarger, Jeff L.","contributorId":274437,"corporation":false,"usgs":false,"family":"Hansbarger","given":"Jeff L.","affiliations":[{"id":56173,"text":"West Virginia DNR","active":true,"usgs":false}],"preferred":false,"id":876369,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Weeks, Jordan","contributorId":315376,"corporation":false,"usgs":false,"family":"Weeks","given":"Jordan","email":"","affiliations":[{"id":16117,"text":"Wisconsin DNR","active":true,"usgs":false}],"preferred":false,"id":876370,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Henesy, Josh","contributorId":222460,"corporation":false,"usgs":false,"family":"Henesy","given":"Josh","email":"","affiliations":[{"id":33964,"text":"Maryland Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":876371,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Walsh, Heather L. 0000-0001-6392-4604 hwalsh@usgs.gov","orcid":"https://orcid.org/0000-0001-6392-4604","contributorId":4696,"corporation":false,"usgs":true,"family":"Walsh","given":"Heather","email":"hwalsh@usgs.gov","middleInitial":"L.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":876372,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Williams, Jeffrey C.","contributorId":41333,"corporation":false,"usgs":false,"family":"Williams","given":"Jeffrey C.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":876373,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70242742,"text":"ofr20231036 - 2023 - Synthesis of climate and ecological science to support grassland management priorities in the North Central Region","interactions":[],"lastModifiedDate":"2026-02-11T21:15:38.958027","indexId":"ofr20231036","displayToPublicDate":"2023-04-14T23:50:00","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-1036","displayTitle":"Synthesis of Climate and Ecological Science to Support Grassland Management Priorities in the North Central Region","title":"Synthesis of climate and ecological science to support grassland management priorities in the North Central Region","docAbstract":"

Grasslands in the Great Plains are of ecological, economic, and cultural importance in the United States. In response to a need to understand how climate change and variability will impact grassland ecosystems and their management in the 21st century, the U.S. Geological Survey North Central Climate Adaptation Science Center led a synthesis of peer-reviewed climate and ecology literature relevant to grassland management in the North Central Region (including Montana, Wyoming, Colorado, North Dakota, South Dakota, Nebraska, and Kansas). This synthesis was done to begin to address grassland managers’ information needs and identify research gaps. This open-file report summarizes the impacts of climate change and variability on temperature, water availability, wildfire, vegetation, wildlife, large-bodied ruminants, grazing, and land-use change and the implications for grassland management in the North Central region. This open-file report also identifies areas in which further research is needed. U.S. Geological Survey funded this project.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231036","collaboration":"Prepared in cooperation with the University of Colorado Boulder","programNote":"U.S. Geological Survey North Central Climate Adaptation Science Center","usgsCitation":"Miller Hesed, C.D., Yocum, H.M., Rangwala, I., Symstad, A.J., Martin, J.M., Ellison, K., Wood, D.J. 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Director, North Central Climate Adaptation Science Center
U.S. Geological Survey
University of Colorado - Boulder
Sustainability, Energy and Environment Community
4001 Discovery Dr., Suite 348
Boulder, CO 80303

","tableOfContents":"","publishedDate":"2023-04-14","noUsgsAuthors":false,"publicationDate":"2023-04-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Miller Hesed, Christine D. 0000-0003-1644-1962","orcid":"https://orcid.org/0000-0003-1644-1962","contributorId":304175,"corporation":false,"usgs":false,"family":"Miller Hesed","given":"Christine","email":"","middleInitial":"D.","affiliations":[{"id":65990,"text":"CU B","active":true,"usgs":false}],"preferred":false,"id":869609,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yocum, Heather M. 0000-0002-3754-4330","orcid":"https://orcid.org/0000-0002-3754-4330","contributorId":265513,"corporation":false,"usgs":false,"family":"Yocum","given":"Heather","email":"","middleInitial":"M.","affiliations":[{"id":54706,"text":"Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, CO","active":true,"usgs":false}],"preferred":false,"id":869610,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rangwala, Imtiaz","contributorId":259891,"corporation":false,"usgs":false,"family":"Rangwala","given":"Imtiaz","affiliations":[{"id":52460,"text":"North Central Climate Adaptation Science Center","active":true,"usgs":false}],"preferred":false,"id":869629,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Symstad, Amy 0000-0003-4231-2873 asymstad@usgs.gov","orcid":"https://orcid.org/0000-0003-4231-2873","contributorId":201095,"corporation":false,"usgs":true,"family":"Symstad","given":"Amy","email":"asymstad@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":869631,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Martin, Jeff M. 0000-0002-4310-8973","orcid":"https://orcid.org/0000-0002-4310-8973","contributorId":304178,"corporation":false,"usgs":false,"family":"Martin","given":"Jeff","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":869621,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ellison, Kevin","contributorId":208254,"corporation":false,"usgs":false,"family":"Ellison","given":"Kevin","affiliations":[{"id":37767,"text":"World Wildlife Fund","active":true,"usgs":false}],"preferred":false,"id":869616,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wood, David J. A. 0000-0003-4315-5160 dwood@usgs.gov","orcid":"https://orcid.org/0000-0003-4315-5160","contributorId":177588,"corporation":false,"usgs":true,"family":"Wood","given":"David","email":"dwood@usgs.gov","middleInitial":"J. A.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":869632,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ahlering, Marissa 0000-0002-3913-428X","orcid":"https://orcid.org/0000-0002-3913-428X","contributorId":171943,"corporation":false,"usgs":false,"family":"Ahlering","given":"Marissa","affiliations":[{"id":7041,"text":"The Nature Conservancy","active":true,"usgs":false}],"preferred":false,"id":869611,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Chase, Katherine J. 0000-0002-5796-4148 kchase@usgs.gov","orcid":"https://orcid.org/0000-0002-5796-4148","contributorId":454,"corporation":false,"usgs":true,"family":"Chase","given":"Katherine","email":"kchase@usgs.gov","middleInitial":"J.","affiliations":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"preferred":true,"id":869612,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Crausbay, Shelley","contributorId":217758,"corporation":false,"usgs":false,"family":"Crausbay","given":"Shelley","affiliations":[{"id":13470,"text":"Conservation Science Partners","active":true,"usgs":false}],"preferred":false,"id":869613,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Davidson, Ana D. 0000-0003-4701-5923","orcid":"https://orcid.org/0000-0003-4701-5923","contributorId":304176,"corporation":false,"usgs":false,"family":"Davidson","given":"Ana","email":"","middleInitial":"D.","affiliations":[{"id":65991,"text":"CNHP","active":true,"usgs":false}],"preferred":false,"id":869614,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Elliott, Julie L.","contributorId":201260,"corporation":false,"usgs":false,"family":"Elliott","given":"Julie","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":869615,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Giocomo, Jim 0000-0002-9230-2422","orcid":"https://orcid.org/0000-0002-9230-2422","contributorId":304177,"corporation":false,"usgs":false,"family":"Giocomo","given":"Jim","affiliations":[{"id":65992,"text":"ABC","active":true,"usgs":false}],"preferred":false,"id":869617,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Hoover, David","contributorId":239685,"corporation":false,"usgs":false,"family":"Hoover","given":"David","affiliations":[{"id":47973,"text":"Rangeland Resources & Systems Research Unit, U.S. Department of Agriculture, Agricultural Research Service, Fort Collins 80526","active":true,"usgs":false}],"preferred":false,"id":869618,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Klemm, Toni","contributorId":257680,"corporation":false,"usgs":false,"family":"Klemm","given":"Toni","email":"","affiliations":[{"id":52084,"text":"TX A&M","active":true,"usgs":false}],"preferred":false,"id":869619,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Lightfoot, David A.","contributorId":273594,"corporation":false,"usgs":false,"family":"Lightfoot","given":"David","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":869620,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"McKenna, Owen P. 0000-0002-5937-9436 omckenna@usgs.gov","orcid":"https://orcid.org/0000-0002-5937-9436","contributorId":198598,"corporation":false,"usgs":true,"family":"McKenna","given":"Owen","email":"omckenna@usgs.gov","middleInitial":"P.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":869622,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Miller, Brian W. 0000-0003-1716-1161","orcid":"https://orcid.org/0000-0003-1716-1161","contributorId":196603,"corporation":false,"usgs":true,"family":"Miller","given":"Brian","email":"","middleInitial":"W.","affiliations":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":869623,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Mosher, Danika 0000-0002-3862-1326","orcid":"https://orcid.org/0000-0002-3862-1326","contributorId":304179,"corporation":false,"usgs":false,"family":"Mosher","given":"Danika","email":"","affiliations":[{"id":38050,"text":"Contractor","active":true,"usgs":false}],"preferred":false,"id":869624,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Nagy, R. Chelsea","contributorId":298272,"corporation":false,"usgs":false,"family":"Nagy","given":"R.","email":"","middleInitial":"Chelsea","affiliations":[{"id":13693,"text":"University of Colorado Boulder","active":true,"usgs":false}],"preferred":false,"id":869625,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Nippert, Jesse B. 0000-0002-7939-342X","orcid":"https://orcid.org/0000-0002-7939-342X","contributorId":304180,"corporation":false,"usgs":false,"family":"Nippert","given":"Jesse","email":"","middleInitial":"B.","affiliations":[{"id":48533,"text":"ksu","active":true,"usgs":false}],"preferred":false,"id":869626,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Pittman, Jeremy 0000-0001-8327-184X","orcid":"https://orcid.org/0000-0001-8327-184X","contributorId":304181,"corporation":false,"usgs":false,"family":"Pittman","given":"Jeremy","email":"","affiliations":[{"id":65993,"text":"Univ of Waterloo","active":true,"usgs":false}],"preferred":false,"id":869627,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Porensky, Lauren M. 0000-0001-6883-2442","orcid":"https://orcid.org/0000-0001-6883-2442","contributorId":239755,"corporation":false,"usgs":false,"family":"Porensky","given":"Lauren","email":"","middleInitial":"M.","affiliations":[{"id":6758,"text":"USDA-ARS","active":true,"usgs":false}],"preferred":false,"id":869628,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Stephens, Jilmarie 0000-0002-0066-2974","orcid":"https://orcid.org/0000-0002-0066-2974","contributorId":304182,"corporation":false,"usgs":false,"family":"Stephens","given":"Jilmarie","email":"","affiliations":[{"id":65990,"text":"CU B","active":true,"usgs":false}],"preferred":false,"id":869630,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Zale, Alexander V. 0000-0003-1703-885X","orcid":"https://orcid.org/0000-0003-1703-885X","contributorId":244099,"corporation":false,"usgs":true,"family":"Zale","given":"Alexander","email":"","middleInitial":"V.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":869633,"contributorType":{"id":1,"text":"Authors"},"rank":25}]}} ,{"id":70242708,"text":"fs20233009 - 2023 - Potential drivers of change in fluxes of nutrients and total suspended solids in the upper White River Basin, Indiana, Water Years 1997–2019","interactions":[],"lastModifiedDate":"2026-02-06T21:50:49.581974","indexId":"fs20233009","displayToPublicDate":"2023-04-14T13:32:00","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-3009","displayTitle":"Potential Drivers of Change in Fluxes of Nutrients and Total Suspended Solids in the Upper White River Basin, Indiana, Water Years 1997–2019","title":"Potential drivers of change in fluxes of nutrients and total suspended solids in the upper White River Basin, Indiana, Water Years 1997–2019","docAbstract":"

The U.S. Geological Survey and The Nature Conservancy previously collaborated to evaluate changes and trends in the concentrations and flux of nutrients (total phosphorus, as phosphorus; nitrate plus nitrite, as nitrogen; and total Kjeldahl nitrogen, as nitrogen) and total suspended solids (TSS) at three study gages located on the upper White River at Muncie, near Nora, and near Centerton, Indiana. That work is extended and updated using 3 additional years of data (through 2020) and newer estimation methods. In addition, information is provided about climatic and anthropogenic factors that could influence the concentrations and fluxes of nutrients and TSS in the upper White River Basin.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20233009","usgsCitation":"Koltun, G.F. and Hauswald, C., 2023, Potential drivers of change in fluxes of nutrients and total suspended solids in the upper White River Basin, Indiana, Water Years 1997–2019: U.S. Geological Survey Fact Sheet 2023–3009, https://doi.org/10.3133/fs20233009.","productDescription":"6 p.","numberOfPages":"6","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-144087","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":415714,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/fs20233009/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"FS 2023-3009"},{"id":415713,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2023/3009/fs20233009.pdf","text":"Report","size":"2.99 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2023-3009"},{"id":415717,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.er.usgs.gov/publication/sir20235025","text":"Scientific Investigations Report 2023–5025","linkHelpText":"- Trends in Environmental, Anthropogenic, and Water-Quality Characteristics in the Upper White River Basin, Indiana"},{"id":415715,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2023/3009/images/"},{"id":415712,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2023/3009/coverthb2.jpg"},{"id":415716,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2023/3009/fs20233009.XML"},{"id":499659,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114665.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Indiana","otherGeospatial":"Upper White River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -84.808361236281,\n 40.56108404734479\n ],\n [\n -86.60385353569629,\n 40.56108404734479\n ],\n [\n -86.60385353569629,\n 39.19167595806789\n ],\n [\n -84.808361236281,\n 39.19167595806789\n ],\n [\n -84.808361236281,\n 40.56108404734479\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

Director, Ohio-Kentucky-Indiana Water Science Center
U.S. Geological Survey
6460 Busch Blvd, Suite 100
Columbus, OH 43229

Contact Pubs Warehouse

","tableOfContents":"","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"publishedDate":"2023-04-14","noUsgsAuthors":false,"publicationDate":"2023-04-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Koltun, G. F. 0000-0003-0255-2960 gfkoltun@usgs.gov","orcid":"https://orcid.org/0000-0003-0255-2960","contributorId":140048,"corporation":false,"usgs":true,"family":"Koltun","given":"G.","email":"gfkoltun@usgs.gov","middleInitial":"F.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":869429,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hauswald, Cassie 0000-0002-9265-0603","orcid":"https://orcid.org/0000-0002-9265-0603","contributorId":224621,"corporation":false,"usgs":false,"family":"Hauswald","given":"Cassie","email":"","affiliations":[{"id":7041,"text":"The Nature Conservancy","active":true,"usgs":false}],"preferred":true,"id":869430,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70242140,"text":"sir20235025 - 2023 - Trends in environmental, anthropogenic, and water-quality characteristics in the upper White River Basin, Indiana","interactions":[],"lastModifiedDate":"2026-03-06T20:47:41.551458","indexId":"sir20235025","displayToPublicDate":"2023-04-14T13:32:00","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-5025","displayTitle":"Trends in Environmental, Anthropogenic, and Water-Quality Characteristics in the Upper White River Basin, Indiana","title":"Trends in environmental, anthropogenic, and water-quality characteristics in the upper White River Basin, Indiana","docAbstract":"

The U.S. Geological Survey (USGS), in cooperation with The Nature Conservancy, undertook a study to update and extend results from a previous study (Koltun, 2019, https://doi.org/10.3133/sir20195119), using data from 3 additional years and newer estimation methods. Koltun (2019) assessed trends in streamflow, precipitation, and estimated annual mean concentrations and flux of nitrate plus nitrite, total Kjeldahl nitrogen, total phosphorus, and total suspended solids (TSS) for USGS streamflow gages on the upper White River at Muncie, near Nora, and near Centerton, Indiana. Annual mean and maximum daily streamflows had statistically significant upward trends at all study gages between water years 1978 and 2020. An abrupt increase in streamflow occurred around water year 2001. Annual total precipitation at the Indianapolis International Airport increased between calendar years 1932 and 2020 at an average rate of 0.089 inches per year.

The current study assessed the magnitude, direction, and likelihood of change in flow-normalized concentrations and flux of TSS, total phosphorus, nitrate plus nitrite, and total Kjeldahl nitrogen between water years 1997 and 2019. With two exceptions, concentration and flux changes that were statistically significant in Koltun (2019, https://doi.org/10.3133/sir20195119), which reported changes between water years 1997 and 2017, still have the same statistically significant change directions. The reliability of the current trend result for TSS is uncertain because of a large gap in the TSS record for the Centerton gage.

For each constituent, spatial patterns were examined in the sampled distribution of nutrient and TSS concentration data from 20 mainstem, tributary, and distributary locations in the upper White River Basin. The largest median concentrations of TSS, total phosphorus, and total Kjeldahl nitrogen were associated with mainstem upper White River sites downstream from Indianapolis. The median total phosphorus and total Kjeldahl nitrogen concentrations were elevated relative to bracketing upstream/downstream mainstem sites at the upper White River site immediately downstream from Muncie.

Data on several anthropogenic factors that could influence the concentrations and fluxes of nutrients and TSS were gathered and analyzed to better understand the factors’ spatial and temporal variations. Those anthropogenic factors included population, land cover, cropping and operational tillage practices, fertilizer application, and upgrades to wastewater treatment systems and delivery processes.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235025","collaboration":"Prepared in cooperation with The Nature Conservancy with generous support from the Nina Mason Pulliam Charitable Trust","usgsCitation":"Koltun, G.F., 2023, Trends in environmental, anthropogenic, and water-quality characteristics in the upper White River Basin, Indiana: U.S. Geological Survey Scientific Investigations Report 2023–5025, 46 p., https://doi.org/10.3133/sir20235025.","productDescription":"Report: x, 46 p.; Data Release","numberOfPages":"46","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-139275","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":415439,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9O6C9L3","text":"USGS data release","linkHelpText":"Model data archive—Trends in selected environmental, anthropogenic, and water-quality characteristics in the upper White River Basin, Indiana, 1991–2020"},{"id":415441,"rank":6,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5025/images/"},{"id":415438,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235025/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2023-5025"},{"id":415437,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5025/sir20235025.pdf","text":"Report","size":"5.05 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5025"},{"id":415436,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5025/coverthb.jpg"},{"id":415440,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5025/sir20235025.XML"},{"id":415718,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/fs20233009","text":"Fact Sheet 2023–3009","linkHelpText":"- Potential Drivers of Change in Fluxes of Nutrients and Total Suspended Solids in the Upper White River Basin, Indiana, Water Years 1997–2019"},{"id":500879,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114664.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Indiana","otherGeospatial":"Upper White River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -84.808361236281,\n 40.56108404734479\n ],\n [\n -86.60385353569629,\n 40.56108404734479\n ],\n [\n -86.60385353569629,\n 39.19167595806789\n ],\n [\n -84.808361236281,\n 39.19167595806789\n ],\n [\n -84.808361236281,\n 40.56108404734479\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

Director, Ohio-Kentucky-Indiana Water Science Center
U.S. Geological Survey
5957 Lakeside Blvd.
Indianapolis, IN 46278-1996

Contact Pubs Warehouse

","tableOfContents":"","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"publishedDate":"2023-04-14","noUsgsAuthors":false,"publicationDate":"2023-04-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Koltun, G. F. 0000-0003-0255-2960 gfkoltun@usgs.gov","orcid":"https://orcid.org/0000-0003-0255-2960","contributorId":140048,"corporation":false,"usgs":true,"family":"Koltun","given":"G.","email":"gfkoltun@usgs.gov","middleInitial":"F.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":868989,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70242712,"text":"pp1837D - 2023 - Evaluation of hydrologic processes in the eastern Snake River Plain aquifer using uranium and strontium isotopes, Idaho National Laboratory, eastern Idaho","interactions":[],"lastModifiedDate":"2026-02-18T22:12:09.217716","indexId":"pp1837D","displayToPublicDate":"2023-04-14T06:48:58","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":331,"text":"Professional Paper","code":"PP","onlineIssn":"2330-7102","printIssn":"1044-9612","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1837","chapter":"D","displayTitle":"Evaluation of Hydrologic Processes in the Eastern Snake River Plain Aquifer Using Uranium and Strontium Isotopes, Idaho National Laboratory, Eastern Idaho","title":"Evaluation of hydrologic processes in the eastern Snake River Plain aquifer using uranium and strontium isotopes, Idaho National Laboratory, eastern Idaho","docAbstract":"

Waste constituents discharged to the eastern Snake River Plain aquifer at the U.S. Department of Energy (DOE) Idaho National Laboratory (INL) pose risks to the water quality of the aquifer. To understand these risks, the U.S. Geological Survey, in cooperation with the DOE, is conducting geochemical studies to better understand the hydrologic processes at the INL that affect the movement of groundwater and waste constituents. In this study, we used natural uranium (234U/238U) and strontium (87Sr/86Sr) isotope ratios of surface water and groundwater to identify the sources of water, the mixing of different source waters, and the flow directions in the shallow part (upper 250 feet) of the aquifer at the INL.

Samples were collected from 17 sites at and near the INL that represent the source-water contributions to the aquifer. These source-water sites included surface water, regional groundwater, and springs. Groundwater samples from 63 sites were collected at and near the INL. For all sites, sample collection dates ranged from 1979 to 2019, but groundwater samples collected at the INL are representative of wet climate cycles when the Big Lost River (BLR) was flowing onto the INL.

The 234U/238U activity ratios and 87Sr/86Sr from groundwater at the INL were plotted on graphs within ternary mixing webs in which the three end members of the mixing web represented specific sources of recharge. The large number of sources of recharge required numerous mixing webs, representing various geographic locations at the INL, so that each mixing web represented an area with just three sources of recharge. Considerations for determining the sources of recharge to groundwater sites included chemical signatures in addition to 234U/238U and 87Sr/86Sr, hydrologic context, and geographic location. The mixing webs were used to estimate the percentage of recharge from specific sources to groundwater at wells.

The results of this study identified groundwater from the Lemhi Range as a source of recharge to the INL, which was a previously unsuspected source of recharge. The estimated spatial distribution of recharge from the BLR and groundwater from the Lost River Range also decreased and increased, respectively, relative to the spatial distribution estimated from an earlier study. Upwelling geothermal water was identified at only one well, which indicates that the upward movement of deep groundwater to the shallow part of the aquifer is largely nonexistent. Mixing between surface water and groundwater, different groundwater recharge sources, or both is ubiquitous at the INL. Mixing of water fully explains the distribution of 234U/238U and 87Sr/86Sr in groundwater at the INL and thus renders unnecessary the hypothesis that fast and slow flow zones at the INL are required to explain the distribution of 234U/238U and 87Sr/86Sr.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1837D","collaboration":"DOE/ID-22259
Prepared in cooperation with the U.S. Department of Energy","usgsCitation":"Rattray, G.W., and Paces, J.B., 2023, Evaluation of hydrologic processes in the eastern Snake River Plain aquifer using uranium and strontium isotopes, Idaho National Laboratory, eastern Idaho, with contributions by Treinen, K.C.: U.S. Geological Survey Professional Paper 1837–D (DOE/ID-22259), 65 p., https://doi.org/10.3133/pp1837D.","productDescription":"vi, 65 p.","onlineOnly":"Y","ipdsId":"IP-127503","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":415758,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/pp1837C","text":"PP 1837 Chapter C","description":"PP 1837 Chapter C"},{"id":415757,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/pp1837B","text":"PP 1837 Chapter B","description":"PP 1837 Chapter B"},{"id":415754,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1837/d/coverthb.jpg"},{"id":415755,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1837/d/pp1837d.pdf","text":"Report","size":"5.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1837 Chapter D"},{"id":415756,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/pp1837A","text":"PP 1837 Chapter A","description":"PP 1837 Chapter A"},{"id":500156,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114666.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Idaho","otherGeospatial":"Idaho National Laboratory","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -113.73997601464795,\n 43.235490275196184\n ],\n [\n -112.19156981148207,\n 43.235490275196184\n ],\n [\n -112.19156981148207,\n 44.2273523624917\n ],\n [\n -113.73997601464795,\n 44.2273523624917\n ],\n [\n -113.73997601464795,\n 43.235490275196184\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Road
Boise, Idaho 83702-4520

","tableOfContents":"","publishedDate":"2023-04-14","noUsgsAuthors":false,"publicationDate":"2023-04-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Rattray, Gordon W. 0000-0002-1690-3218 grattray@usgs.gov","orcid":"https://orcid.org/0000-0002-1690-3218","contributorId":2521,"corporation":false,"usgs":true,"family":"Rattray","given":"Gordon","email":"grattray@usgs.gov","middleInitial":"W.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":869458,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Paces, James B. 0000-0002-9809-8493 jbpaces@usgs.gov","orcid":"https://orcid.org/0000-0002-9809-8493","contributorId":2514,"corporation":false,"usgs":true,"family":"Paces","given":"James","email":"jbpaces@usgs.gov","middleInitial":"B.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":869459,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70242711,"text":"pp1837C - 2023 - Determining three-dimensional hydrologic processes in the eastern Snake River Plain aquifer using geochemical mass-balance modeling, Idaho National Laboratory, eastern Idaho, with contributions by Treinen, K.C.","interactions":[],"lastModifiedDate":"2023-04-17T11:04:59.33674","indexId":"pp1837C","displayToPublicDate":"2023-04-14T06:48:18","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":331,"text":"Professional Paper","code":"PP","onlineIssn":"2330-7102","printIssn":"1044-9612","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1837","chapter":"C","displayTitle":"Determining Three-Dimensional Hydrologic Processes in the Eastern Snake River Plain Aquifer Using Geochemical Mass-Balance Modeling, Idaho National Laboratory, Eastern Idaho","title":"Determining three-dimensional hydrologic processes in the eastern Snake River Plain aquifer using geochemical mass-balance modeling, Idaho National Laboratory, eastern Idaho, with contributions by Treinen, K.C.","docAbstract":"

Waste constituents discharged to the eastern Snake River Plain aquifer at the U.S. Department of Energy (DOE) Idaho National Laboratory (INL) pose risks to the water quality of the aquifer. To understand these risks, the U.S. Geological Survey, in cooperation with the DOE, used geochemical mass-balance modeling to identify three-dimensional hydrologic processes in that portion of the aquifer underlying the southwestern part of the INL that affect the movement of groundwater and waste constituents. Modeling was performed using water chemistry of 74 water samples collected from 30 wells. Fifty-four of the water samples were collected from 11 wells equipped with multilevel monitoring systems with vertically discrete sampling zones that encompass the upper 750 feet of the aquifer. Water samples from these multilevel wells were collected during 2007‒13, a period when conditions in the aquifer were approximately steady-state because there was little or no recharge from the Big Lost River.

The primary source of water in groundwater at the multilevel wells during 2007‒13 was the Big Lost River. Other sources of water include groundwater from the Little Lost River valley, precipitation, and wastewater. Horizontal groundwater-flow directions appear to be similar in both the shallow and deep parts of the aquifer, and surface-water sources of water in most deep groundwater shows that groundwater moves downward. Surface-water sources of water in deep groundwater noticeably decrease within and below the Matuyama flow and associated sedimentary interbeds, which indicates that these units are semi-impermeable and retard the downward movement of groundwater.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1837C","collaboration":"DOE/ID-22258
Prepared in cooperation with the U.S. Department of Energy","usgsCitation":"Suggested citation:\n\nRattray, G.W., 2023, Determining three-dimensional hydrologic processes in the eastern Snake River Plain aquifer using geochemical mass-balance modeling, Idaho National Laboratory, eastern Idaho, with contributions by Treinen, K.C.: U.S. Geological Survey Professional Paper 1837–C (DOE/ID-22258), 133 p., https://doi.org/10.3133/pp1837C.","productDescription":"Report: vii, 133 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-118750","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":415747,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/pp1837B","text":"PP 1837 Chapter B","description":"PP 1837 Chapter B"},{"id":415748,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/pp1837D","text":"PP 1837 Chapter D","description":"PP 1837 Chapter D"},{"id":415743,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1837/c/coverthb2.jpg"},{"id":415744,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1837/c/pp1837c.pdf","text":"Report","size":"9.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1837 Chapter C"},{"id":415745,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P92CEFXN","text":"USGS data release","description":"USGS data release","linkHelpText":"Data for tritium deposition in precipitation in the United States, 1953‒2012"},{"id":415746,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/pp1837A","text":"PP 1837 Chapter A","description":"PP 1837 Chapter A"}],"country":"United States","state":"Idaho","otherGeospatial":"Idaho National Laboratory","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -113.73997601464795,\n 43.235490275196184\n ],\n [\n -112.19156981148207,\n 43.235490275196184\n ],\n [\n -112.19156981148207,\n 44.2273523624917\n ],\n [\n -113.73997601464795,\n 44.2273523624917\n ],\n [\n -113.73997601464795,\n 43.235490275196184\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Road
Boise, Idaho 83702-4520

","tableOfContents":"","publishedDate":"2023-04-14","noUsgsAuthors":false,"publicationDate":"2023-04-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Rattray, Gordon W. 0000-0002-1690-3218 grattray@usgs.gov","orcid":"https://orcid.org/0000-0002-1690-3218","contributorId":2521,"corporation":false,"usgs":true,"family":"Rattray","given":"Gordon","email":"grattray@usgs.gov","middleInitial":"W.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":869457,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70254341,"text":"70254341 - 2023 - Predicting baseflow recession characteristics at ungauged stream locations using a physical and machine learning approach","interactions":[],"lastModifiedDate":"2024-05-20T11:34:51.897282","indexId":"70254341","displayToPublicDate":"2023-04-14T06:33:47","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":664,"text":"Advances in Water Resources","active":true,"publicationSubtype":{"id":10}},"title":"Predicting baseflow recession characteristics at ungauged stream locations using a physical and machine learning approach","docAbstract":"

Prediction of short- (i.e., aquifer is near or at saturated conditions) and long-time (i.e., aquifer is not near or at saturated conditions) baseflow recession characteristics at ungauged stream locations is a current challenge that has been primarily addressed by empirical approaches that relate these characteristics to basin attributes. However, the performance of these models is often only fair with coefficient of determination values ranging from 0.5 to 0.7. In this study, we propose a hybrid physical and machine learning approach to predict the long- and short-time baseflow recession characteristics at ungauged stream locations. This approach is compared to a machine learning method, random forest regression, that relates baseflow recession characteristics to basin attributes in 582 basins across the western and eastern United States. The new approach resulted in lower median and inner quartile ranges (IQR) of absolute normalized errors in predicting long-time baseflow recession characteristics (western: 23%, IQR=32%; eastern: 30%, IQR=39%) compared to estimates of those properties based on random forest regressions (western: 27%, IQR=34%; eastern: 38%, IQR=50%). For the short-time baseflow recession characteristics, the hybrid approach resulted in substantially lower median errors and IQR values (western: 79%, IQR=143%; eastern: 83%, IQR=140%) compared to estimates from random forest regressions (western: 1,577%, IQR=8,887%; eastern: 341%, IQR=2,154%). In addition, this approach identified four major regions in the western United States and three in the eastern United States where the baseflow recession characteristics are mostly constant, and these characteristics only vary based on the geometric properties of aquifers. Lastly, the inter-basin variability of the baseflow recession characteristics was not found to be strongly related to metrics measuring interstorm arrival periods, average number of storms, and average length of storms.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.advwatres.2023.104440","usgsCitation":"Eng, K., Wolock, D.M., and Wieczorek, M., 2023, Predicting baseflow recession characteristics at ungauged stream locations using a physical and machine learning approach: Advances in Water Resources, v. 175, 104440, https://doi.org/10.1016/j.advwatres.2023.104440.","productDescription":"104440","ipdsId":"IP-127260","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":428824,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"175","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Eng, Ken 0000-0001-6838-5849 keng@usgs.gov","orcid":"https://orcid.org/0000-0001-6838-5849","contributorId":3580,"corporation":false,"usgs":true,"family":"Eng","given":"Ken","email":"keng@usgs.gov","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":901033,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wolock, David M. 0000-0002-6209-938X","orcid":"https://orcid.org/0000-0002-6209-938X","contributorId":219213,"corporation":false,"usgs":true,"family":"Wolock","given":"David","email":"","middleInitial":"M.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":901034,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wieczorek, Michael 0000-0003-0999-5457","orcid":"https://orcid.org/0000-0003-0999-5457","contributorId":207911,"corporation":false,"usgs":true,"family":"Wieczorek","given":"Michael","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":true,"id":901035,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70242682,"text":"ofr20231026 - 2023 - Assessment of riparian vegetation patterns and change downstream from Glen Canyon Dam from 2014 to 2019","interactions":[],"lastModifiedDate":"2026-02-11T21:04:06.498805","indexId":"ofr20231026","displayToPublicDate":"2023-04-13T12:02:15","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-1026","displayTitle":"Assessment of Riparian Vegetation Patterns and Change Downstream from Glen Canyon Dam from 2014 to 2019","title":"Assessment of riparian vegetation patterns and change downstream from Glen Canyon Dam from 2014 to 2019","docAbstract":"

Changes in riparian vegetation cover and composition occur in relation to flow regime, geomorphic template, and climate, and can have cascading effects on aquatic and terrestrial ecosystems. Tracking such changes over time is therefore an important part of monitoring the condition and trajectory of riparian ecosystems. Maintaining diverse, self-sustaining riparian vegetation comprised of mostly native species is identified in the Glen Canyon Dam Long-Term Experimental and Management Plan as a key resource objective for the section of the Colorado River between Glen Canyon Dam and Lake Mead. The U.S. Geological Survey Grand Canyon Monitoring and Research Center implemented an annual monitoring program in 2014 to assess the status and trends of riparian vegetation along this section of river, particularly as they relate to flow regime. In this report, we summarize plant species composition and cover data collected under the annual monitoring program from 2014 to 2019, with special consideration given to the hydrologic position, associated geomorphic feature class, local climate patterns, native and nonnative species, and floristic region for key vegetation metrics and species. We divided the study area into four river segments (referred to as Glen Canyon, Marble Canyon, eastern Grand Canyon, and western Grand Canyon) on the basis of geography and floristic composition and calculated each recorded plant species’ relative frequency and foliar cover by river segment. These data were then used to evaluate species composition relationships among river segments, hydrologic zones, geomorphic features, and sampling years through ordination analysis. Temporal trends in our focal resource objectives—species richness, total foliar cover, proportion of native to nonnative species richness, proportion of native to nonnative species cover, Tamarix cover, Pluchea sericea cover, and Baccharis species cover—were assessed using mixed-effects models. Four patterns related to species composition emerged: (1) species composition of fixed-site sandbars differed from that of randomly selected sites (including randomly selected sandbars), (2) species composition of Glen Canyon sites differed from that of other previously identified floristic regions, (3) species composition differed across hydrologic zones related to dam operations, and (4) species composition within river segments did not change across years. For temporal patterns, four main findings emerged: (1) trends differed between fixed-sites and randomly selected sites; (2) although few directional changes were observed from 2014 to 2019, Baccharis species cover increased at randomly selected sites in areas influenced by daily water fluctuations; (3) native species cover and richness were greater than nonnative species cover and richness across all hydrologic zones; and (4) the temporal trend metrics used here can be used across floristic groups, enabling assessment of the Colorado River ecosystem as a whole. In addition to these findings, lists of recorded plant species are included as appendixes. The variations and patterns in vegetation status and trends presented in this report can be used as a baseline against which future monitoring can be compared.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231026","collaboration":"Prepared in cooperation with the Bureau of Reclamation Glen Canyon Adaptive Management Program","usgsCitation":"Palmquist, E.C., Butterfield, B.J., and Ralston, B.E., 2023, Assessment of riparian vegetation patterns and change downstream from Glen Canyon Dam from 2014 to 2019: U.S. Geological Survey Open-File Report 2023–1026, 55 p., https://doi.org/10.3133/ofr20231026.","productDescription":"Report: vii, 55 p.; Data Release","numberOfPages":"55","onlineOnly":"Y","ipdsId":"IP-132835","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":499774,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114661.htm","linkFileType":{"id":5,"text":"html"}},{"id":415675,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1026/images"},{"id":415674,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1026/ofr20231026.pdf","text":"Report","size":"5 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":415673,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1026/covrthb.jpg"},{"id":415672,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9KEHY2S","text":"Riparian vegetation data downstream of Glen Canyon Dam in Glen Canyon National Recreation Area and Grand Canyon National Park, AZ from 2014 to 2019","description":"Palmquist, E.C., Butterfield, B.J., and Ralston, B.E., 2022, Riparian vegetation data downstream of Glen Canyon Dam in Glen Canyon National Recreation Area and Grand Canyon National Park, AZ from 2014 to 2019: U.S. Geological Survey data release, https://doi.org/10.5066/P9KEHY2S."}],"country":"United States","state":"Arizona","otherGeospatial":"Glen Canyon Dam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -114.06028247701303,\n 36.94784441270309\n ],\n [\n -114.06028247701303,\n 35.55756259875736\n ],\n [\n -111.24899178190306,\n 35.55756259875736\n ],\n [\n -111.24899178190306,\n 36.94784441270309\n ],\n [\n -114.06028247701303,\n 36.94784441270309\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"
Southwest Biological Science Center
U.S. Geological Survey
2255 N. Gemini Drive
Flagstaff, AZ 86001
","tableOfContents":"","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2023-04-13","noUsgsAuthors":false,"publicationDate":"2023-04-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Palmquist, Emily C. 0000-0003-1069-2154 epalmquist@usgs.gov","orcid":"https://orcid.org/0000-0003-1069-2154","contributorId":5669,"corporation":false,"usgs":true,"family":"Palmquist","given":"Emily","email":"epalmquist@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":869339,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Butterfield, Bradley J.","contributorId":18096,"corporation":false,"usgs":true,"family":"Butterfield","given":"Bradley J.","affiliations":[],"preferred":false,"id":869340,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ralston, Barbara E. 0000-0001-9991-8994 bralston@usgs.gov","orcid":"https://orcid.org/0000-0001-9991-8994","contributorId":606,"corporation":false,"usgs":true,"family":"Ralston","given":"Barbara","email":"bralston@usgs.gov","middleInitial":"E.","affiliations":[{"id":501,"text":"Office of Science Quality and Integrity","active":true,"usgs":true}],"preferred":false,"id":869341,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70242683,"text":"ofr20221101 - 2023 - Bivalve effects on the food web supporting delta smelt—A long-term study of bivalve recruitment, biomass, and grazing rate patterns with varying freshwater outflow","interactions":[],"lastModifiedDate":"2023-04-14T11:04:01.354859","indexId":"ofr20221101","displayToPublicDate":"2023-04-13T11:38:35","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-1101","displayTitle":"Bivalve Effects on the Food Web Supporting Delta Smelt—A One-Year Study of Bivalve Recruitment, Biomass, and Grazing Rate Patterns with Varying Freshwater Outflow","title":"Bivalve effects on the food web supporting delta smelt—A long-term study of bivalve recruitment, biomass, and grazing rate patterns with varying freshwater outflow","docAbstract":"

Phytoplankton are an important and limiting food source in the Sacramento-San Joaquin Delta and San Francisco Bay in California. Decreasing phytoplankton biomass is one possible factor for the pelagic organism decline and the decline of the protected Hypomesus transpacificus (delta smelt). Bivalves Corbicula fluminea and Potamocorbula amurensis (hereafter C. fluminea and P. amurensis, respectively) have been shown to control phytoplankton biomass throughout San Francisco Bay and the Sacramento-San Joaquin Delta; therefore, their distribution and population dynamics are of great interest.

We describe the distribution and dynamics of bivalve biomass using samples from California Department of Water Resources’ (DWR) 2019 benthic monitoring program. As one element of DWR’s and the Bureau of Reclamation’s Environmental Monitoring Program (EMP), the DWR benthic monitoring program examines the effect of water project operations on the estuary as prescribed by a series of Water Rights Decisions mandated by the California State Water Resources Control Board (SWRCB).

The biomass and grazing rate values of both bivalves had similar patterns, therefore, comments on biomass distribution can be applied to grazing rate data. Biomass and recruitment values of C. fluminea were too low at station C9 (Old River upstream from Clift on Court Forebay Intake) to describe a temporal pattern. Corbicula fluminea biomass values were consistently high at station D24 (Sacramento River). Station D4L (confluence of San Joaquin and Sacramento Rivers) biomass values were low during the first half of the year and high the rest of the year. Corbicula fluminea biomass values at station P8 (San Joaquin River) were the highest and most consistent on that river. Station D16 (San Joaquin River) and station D28A (central delta) biomass values were near zero with a small peak in May.

Potamocorbula amurensis biomass values were near zero at station D4L (confluence of San Joaquin and Sacramento Rivers). Biomass values were strongly seasonal at station D6 (Suisun Bay). Station D41 (San Pablo Bay) had the highest P. amurensis biomass values. Station D7 (Grizzly Bay) and station D41A (San Pablo Bay) had low biomass values in January-June or July and maximum biomass values in August.

Corbicula fluminea recruits in the Sacramento River stations peaked twice, from January to June and from September to December. At the San Joaquin River stations, C. fluminea recruitment peaked from May to July or August and from November to December. Peak recruit abundance was higher on the Sacramento River than the San Joaquin River.

Potamocorbula amurensis recruitment was more seasonal than C. fluminea, with a high number of recruits followed by periods with no recruits. Station D4L had few recruits except in January. Station D6 had low recruitment from January to February, increased in August, and peaked from November to December. Station D7 had fewer recruits than station D6 but had a similar temporal pattern, although winter recruits continued into April instead of February. Station D41 recruits were sparce and present only from May to July. Station D41A had the most recruits from January to July, and again in September.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221101","collaboration":"Prepared in cooperation with California Department of Water Resources and Bureau of Reclamation","usgsCitation":"Zierdt Smith, E.L., Shrader, K.H., Thompson, J.K., Parchaso, F., Gehrts, K., and Wells, E., 2023, Bivalve effects on the food web supporting delta smelt—A long-term study of bivalve recruitment, biomass, and grazing rate patterns with varying freshwater outflow: U.S. Geological Survey Open-File Report 2022–1101, 13 p., https://doi.org/10.3133/ofr20221101.","productDescription":"Report: vi, 13 p.; Data Release","numberOfPages":"13","onlineOnly":"Y","ipdsId":"IP-123598","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":415676,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1101/covrthb.jpg"},{"id":415677,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1101/ofr20221101.pdf","text":"Report","size":"5 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":415678,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20221102","text":"Open-File Report 2022-1102","description":"Zierdt Smith, E.L., Shrader, K.H., Thompson, J.K., Parchaso, F., Gehrts, K., and Wells, E., 2023, Bivalve effects on the food web supporting delta smelt—A spatially intensive study of bivalve recruitment, biomass, and grazing rate patterns with varying freshwater outflow in 2019: U.S. Geological Survey Open-File Report 2022–1102, 15 p., http://doi.org/10.3133/ofr20221102.","linkHelpText":"- Bivalve Effects on the Food Web Supporting Delta Smelt—A Spatially Intensive Study of Bivalve Recruitment, Biomass, and Grazing Rate Patterns with Varying Freshwater Outflow in 2019"},{"id":415679,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9Q57NL0","text":"Bivalve metrics in the North San Francisco Bay and Sacramento-San Joaquin Delta","description":"Zierdt Smith, E.L., Shrader, K.H., Pearson S.A., Crauder, J.S., Parchaso, F., and Thompson, J.K., 2021, Bivalve metrics in the North San Francisco Bay and Sacramento-San Joaquin Delta: U.S. Geological Survey data release, https://doi.org/10.5066/P9Q57NL0."}],"country":"United States","state":"California","otherGeospatial":"Sacramento–San Joaquin Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.87943679633386,\n 38.21596776184356\n ],\n [\n -122.87943679633386,\n 37.37464201681941\n ],\n [\n -121.47296304678717,\n 37.37464201681941\n ],\n [\n -121.47296304678717,\n 38.21596776184356\n ],\n [\n -122.87943679633386,\n 38.21596776184356\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

Director,
Water Resources, Earth System Processes Division
U.S. Geological Survey
411 National Center
12201 Sunrise Valley Drive
Reston, VA 20192

","tableOfContents":"","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2023-04-13","noUsgsAuthors":false,"publicationDate":"2023-04-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Zierdt Smith, Emily L. 0000-0003-0787-1856 ezierdtsmith@usgs.gov","orcid":"https://orcid.org/0000-0003-0787-1856","contributorId":220320,"corporation":false,"usgs":true,"family":"Zierdt Smith","given":"Emily","email":"ezierdtsmith@usgs.gov","middleInitial":"L.","affiliations":[],"preferred":true,"id":869342,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shrader, Kelly H. 0000-0001-6550-7425 kshrader@usgs.gov","orcid":"https://orcid.org/0000-0001-6550-7425","contributorId":220319,"corporation":false,"usgs":true,"family":"Shrader","given":"Kelly","email":"kshrader@usgs.gov","middleInitial":"H.","affiliations":[],"preferred":true,"id":869343,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thompson, Janet K. 0000-0002-1528-8452 jthompso@usgs.gov","orcid":"https://orcid.org/0000-0002-1528-8452","contributorId":1009,"corporation":false,"usgs":true,"family":"Thompson","given":"Janet","email":"jthompso@usgs.gov","middleInitial":"K.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true}],"preferred":true,"id":869344,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Parchaso, Francis 0000-0002-9471-7787 parchaso@usgs.gov","orcid":"https://orcid.org/0000-0002-9471-7787","contributorId":150620,"corporation":false,"usgs":true,"family":"Parchaso","given":"Francis","email":"parchaso@usgs.gov","affiliations":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true}],"preferred":true,"id":869345,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gehrts, Karen","contributorId":46881,"corporation":false,"usgs":true,"family":"Gehrts","given":"Karen","email":"","affiliations":[],"preferred":false,"id":869346,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wells, Elizabeth","contributorId":152205,"corporation":false,"usgs":false,"family":"Wells","given":"Elizabeth","email":"","affiliations":[{"id":18881,"text":"CA Department of Water Resources, Sacramento, CA.","active":true,"usgs":false}],"preferred":false,"id":869347,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70242680,"text":"ofr20231020 - 2023 - Monitoring of wave, current, and sediment dynamics along the Chincoteague living shoreline, Virginia","interactions":[],"lastModifiedDate":"2026-02-11T20:56:22.819818","indexId":"ofr20231020","displayToPublicDate":"2023-04-13T10:15:44","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-1020","displayTitle":"Monitoring of Wave, Current, and Sediment Dynamics Along the Chincoteague Living Shoreline, Virginia","title":"Monitoring of wave, current, and sediment dynamics along the Chincoteague living shoreline, Virginia","docAbstract":"

Nature-based features, also called living shorelines, are increasingly applied in coastal protection and restoration. However, the processes and mechanisms (feedbacks and interactions) of wave attenuation, current velocity change, and sediment deposition and erosion along the living shoreline remain unclear, thus limiting the adaptive management of living shoreline restoration projects for coastal shoreline resilience under future storm conditions. In this study, wave, current, and sediment dynamics along the Little Toms Cove living shoreline, Chincoteague National Wildlife Refuge, Virginia, a low wave energy environment, were investigated during a 2-month winter period in 2019 to examine the effects of living shoreline structures on shoreline protection and oyster habitat enhancement. It was found that wave attenuation by the living shoreline structures (oyster castles or constructed oyster reefs) is dependent on water depth, wind speed, wind direction, and local bathymetry. Analysis of observed data indicate that the oyster castles along the Little Toms Cove living shoreline play a limited role in wave attenuation in this low wave energy environment. During the 2-month winter period, wave energy was attenuated by 39.7 percent when oyster castles were emergent or slightly submerged with southwest winds. In contrast, when the oyster castles were fully submerged, wave energy behind the oyster castles increased by 38.6 percent. The construction of oyster castles affected circulation patterns with increase or decrease in velocity at nearshore waters protected by the castles depending on locations of measurements in relation to the oyster castles. Bottom shear stress analysis indicates that tidal currents play a larger role than waves on shoreline and marsh edge erosion along the Little Toms Cove shoreline during the 2 months of field monitoring. The oyster castles protecting the marsh edge and tidal flat from erosion resulted in higher fine sediment concentration in the water column landward of the castles because more sediment was retained in the lee side of the castles. It is important to maximize sediment within the wetlands and adjacent mudflats behind the oyster castles. Erosion from the marsh edge and interior serves as the major source of sediment for this wetland system due to the limited sediment supply in Assateague Channel. Furthermore, it was found that the oyster castles along the Little Toms Cove living shoreline were inundated more than 60 percent of the time, leading to the enhanced oyster habitat as evidenced by suitable velocity (less than 10 centimeters per second) and mean grain size (less than 0.08 millimeters) for oyster feeding and the increased oyster shell density and growth in the intertidal zone protected by the castles than in the control area. More field data (for example, concurrent monitoring of sediment concentration and salinity) over other seasons (for example, summer) could help examine the long term and combined engineering and ecological benefits of living shoreline restoration projects under seasonal and enhanced future storm conditions.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231020","issn":"2331-1258","collaboration":"Prepared in collaboration with Northeastern University, U.S. Fish and Wildlife Service, The Nature Conservancy, Louisiana State University, and Shippensburg University","usgsCitation":"Wang, H., Chen, Q., Wang, N., Capurso, W.D., Niemoczynski, L.M., Zhu, L., Snedden, G.A., Holcomb, K.S., Lusk, B.W., Wilson, C.A., and Cornell, S.R., 2023, Monitoring of wave, current, and sediment dynamics along the Chincoteague living shoreline, Virginia: U.S. Geological Survey Open-File Report 2023–1020, 32 p., https://doi.org/10.3133/ofr20231020.","productDescription":"Report: viii, 32 p.; 2 Data Releases","numberOfPages":"44","onlineOnly":"Y","ipdsId":"IP-147055","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":415665,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1020/ofr20231020.pdf","text":"Report","size":"3.22 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1020 pdf"},{"id":415664,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1020/coverthb.jpg"},{"id":415667,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1020/images"},{"id":415669,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9CUF4UZ","text":"U.S. Geological Survey data release—Field observation of wind waves (2019) along the Chincoteague Living Shoreline, Virginia"},{"id":415670,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P903FIH7","text":"U.S. Geological Survey data release—Field observation of current velocities (2019) along the Chincoteague Living Shoreline, Virginia"},{"id":415736,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1020/ofr20231020.XML","linkFileType":{"id":8,"text":"xml"},"description":"OFR 2023-1020 XML"},{"id":415737,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/ofr20231020/full","description":"OFR 2023-1020 HTML"},{"id":499771,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114662.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Virginia","otherGeospatial":"Assateague Bay, Chincoteague National Wildlife Refuge, Little Tom's Cove","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -75.32920735620297,\n 37.90602658439137\n ],\n [\n -75.43123250187875,\n 37.90602658439137\n ],\n [\n -75.43123250187875,\n 37.83932564463906\n ],\n [\n -75.32920735620297,\n 37.83932564463906\n ],\n [\n -75.32920735620297,\n 37.90602658439137\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

Director, Wetland and Aquatic Research Center
U.S. Geological Survey
7920 NW 71st St.
Gainesville, FL 32653

For additional information, visit
https://www.usgs.gov/centers/wetland-and-aquatic-research-center-warc

Contact Pubs Warehouse
https://pubs.er.usgs.gov/contact
","tableOfContents":"","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2023-04-13","noUsgsAuthors":false,"publicationDate":"2023-04-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Wang, Hongqing 0000-0002-2977-7732","orcid":"https://orcid.org/0000-0002-2977-7732","contributorId":222807,"corporation":false,"usgs":true,"family":"Wang","given":"Hongqing","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":869317,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chen, Q. 0000-0002-6540-8758","orcid":"https://orcid.org/0000-0002-6540-8758","contributorId":56532,"corporation":false,"usgs":false,"family":"Chen","given":"Q.","affiliations":[{"id":38331,"text":"Northeastern University","active":true,"usgs":false}],"preferred":true,"id":869318,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wang, Nan 0000-0001-7569-9598","orcid":"https://orcid.org/0000-0001-7569-9598","contributorId":291600,"corporation":false,"usgs":false,"family":"Wang","given":"Nan","email":"","affiliations":[{"id":38331,"text":"Northeastern University","active":true,"usgs":false}],"preferred":false,"id":869319,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Capurso, William D. 0000-0003-1182-2846","orcid":"https://orcid.org/0000-0003-1182-2846","contributorId":218672,"corporation":false,"usgs":true,"family":"Capurso","given":"William","email":"","middleInitial":"D.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":869320,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Niemoczynski, L.M. 0000-0003-2008-9148","orcid":"https://orcid.org/0000-0003-2008-9148","contributorId":222166,"corporation":false,"usgs":true,"family":"Niemoczynski","given":"L.M.","email":"","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":869321,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zhu, Ling 0000-0003-0261-6848","orcid":"https://orcid.org/0000-0003-0261-6848","contributorId":222169,"corporation":false,"usgs":false,"family":"Zhu","given":"Ling","affiliations":[{"id":38331,"text":"Northeastern University","active":true,"usgs":false}],"preferred":false,"id":869322,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Snedden, Gregg A. 0000-0001-7821-3709","orcid":"https://orcid.org/0000-0001-7821-3709","contributorId":212275,"corporation":false,"usgs":true,"family":"Snedden","given":"Gregg","middleInitial":"A.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":869323,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Holcomb, Kevin S.","contributorId":215603,"corporation":false,"usgs":false,"family":"Holcomb","given":"Kevin","email":"","middleInitial":"S.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":869324,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Lusk, Bowdoin W.","contributorId":304123,"corporation":false,"usgs":false,"family":"Lusk","given":"Bowdoin","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":869328,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Wilson, Carol W.","contributorId":40611,"corporation":false,"usgs":true,"family":"Wilson","given":"Carol","email":"","middleInitial":"W.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":869326,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Cornell, Sean R.","contributorId":304121,"corporation":false,"usgs":false,"family":"Cornell","given":"Sean","email":"","middleInitial":"R.","affiliations":[{"id":37222,"text":"Shippensburg University","active":true,"usgs":false}],"preferred":false,"id":869327,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70243034,"text":"70243034 - 2023 - Data integration reveals dynamic and systematic patterns of breeding habitat use by a threatened shorebird","interactions":[],"lastModifiedDate":"2023-04-27T12:06:00.830801","indexId":"70243034","displayToPublicDate":"2023-04-13T07:01:48","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Data integration reveals dynamic and systematic patterns of breeding habitat use by a threatened shorebird","docAbstract":"

Incorporating species distributions into conservation planning has traditionally involved long-term representations of habitat use where temporal variation is averaged to reveal habitats that are most suitable across time. Advances in remote sensing and analytical tools have allowed for the integration of dynamic processes into species distribution modeling. Our objective was to develop a spatiotemporal model of breeding habitat use for a federally threatened shorebird (piping plover, Charadrius melodus). Piping plovers are an ideal candidate species for dynamic habitat models because they depend on habitat created and maintained by variable hydrological processes and disturbance. We integrated a 20-year (2000–2019) nesting dataset with volunteer-collected sightings (eBird) using point process modeling. Our analysis incorporated spatiotemporal autocorrelation, differential observation processes within data streams, and dynamic environmental covariates. We evaluated the transferability of this model in space and time and the contribution of the eBird dataset. eBird data provided more complete spatial coverage in our study system than nest monitoring data. Patterns of observed breeding density depended on both dynamic (e.g., surface water levels) and long-term (e.g., proximity to permanent wetland basins) environmental processes. Our study provides a framework for quantifying dynamic spatiotemporal patterns of breeding density. This assessment can be iteratively updated with additional data to improve conservation and management efforts, because reducing temporal variability to average patterns of use may cause a loss in precision for such actions.

","language":"English","publisher":"Nature","doi":"10.1038/s41598-023-32886-w","usgsCitation":"Ellis, K.S., Anteau, M.J., MacDonald, G.J., Swift, R.J., Ring, M., Toy, D.L., Sherfy, M.H., and Post van der Burg, M., 2023, Data integration reveals dynamic and systematic patterns of breeding habitat use by a threatened shorebird: Scientific Reports, v. 13, 6087, 12 p., https://doi.org/10.1038/s41598-023-32886-w.","productDescription":"6087, 12 p.","ipdsId":"IP-143601","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":443865,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-023-32886-w","text":"Publisher Index Page"},{"id":435376,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9KWK13B","text":"USGS data release","linkHelpText":"Piping plover nesting habitat distribution maps for the U.S. Prairie Pothole Region, 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Center","active":true,"usgs":true}],"preferred":true,"id":870753,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Post van der Burg, Max 0000-0002-3943-4194","orcid":"https://orcid.org/0000-0002-3943-4194","contributorId":219400,"corporation":false,"usgs":true,"family":"Post van der Burg","given":"Max","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":870754,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70242030,"text":"sir20235026 - 2023 - Strontium isotope chronostratigraphic age of a sirenian fossil site on Santa Rosa Island, Channel Islands National Park, California","interactions":[],"lastModifiedDate":"2026-03-06T20:49:41.383683","indexId":"sir20235026","displayToPublicDate":"2023-04-12T14:09:00","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-5026","displayTitle":"Strontium Isotope Chronostratigraphic Age of a Sirenian Fossil Site on Santa Rosa Island, Channel Islands National Park, California","title":"Strontium isotope chronostratigraphic age of a sirenian fossil site on Santa Rosa Island, Channel Islands National Park, California","docAbstract":"

Fossils in the order Sirenia (family Dugongidae) from Santa Rosa Island, part of Channel Islands National Park in southern California, provide rare temporal and spatial links between earlier and later evolutionary forms of dugongids, and add information about their dispersal into the northeastern Pacific region. Marine sedimentary rocks containing these fossils have characteristics of both the late Oligocene to middle Miocene Vaqueros Sandstone and the early to middle Miocene Rincon formation observed elsewhere. To determine a more precise age of the fossils, marine invertebrate shells were collected from the same exposures as the sirenian fossils for chronostratigraphic assessment using strontium isotope compositions and the well-calibrated seawater strontium evolution curve. Shells used for analysis were from bivalve mollusks (Pycnodonte sp. [oyster] and Lyropecten sp. [scallop]) and crustaceans (Balanus sp. [barnacle]). Results show a wide range of 87Sr/86Sr values, indicating that shell materials experienced varying degrees of diagenetic alteration. Strontium concentrations and 87Sr/86Sr values in subsamples of Pycnodonte shell show correlations between original shell material and a secondary component having lower strontium concentrations and less radiogenic (lower) 87Sr/86Sr. In contrast, all Lyropecten shell analyses yielded a uniform 87Sr/86Sr value (0.708440±0.000010 [2× standard deviation]) over a wide range of strontium concentrations (around 900 to 1,800 micrograms per gram [μg/g]). Results for Balanus shell subsamples show a range of strontium compositional behavior between the other two types of shell. Acetic acid leachates of sandy matrix confirm that diagenetic fluids had low 87Sr/86Sr values consistent with the least radiogenic values in Pycnodonte subsamples. A simple mixing model between two calcite end-members can explain observed Pycnodonte data, although actual diagenetic processes likely involved secondary dissolution/reprecipitation or strontium ion exchange between shell material and pore fluid. Data indicate that only Lyropecten subsamples have retained their original 87Sr/86Sr compositions, resulting in a best-estimate age of 20.08±0.11 million years ago (Ma) (±95-percent confidence interval [CI]). Although Dugongidae fossils have been found in Miocene and younger sediments along the west coast of North America, the Santa Rosa Island specimens represent some of the earliest and most accurately dated sirenian fossils in the region. Chronostratigraphic results also constrain the timing of the transgressional processes represented by shallow-water (Vaqueros Sandstone) to deep-water (Rincon formation) depositional environments.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235026","collaboration":"Prepared in cooperation with the U.S. National Park Service","usgsCitation":"Paces, J.B., Minor, S.A., Schmidt, K.M., and Hoffman, J., 2023, Strontium isotope chronostratigraphic age of a sirenian fossil site on Santa Rosa Island, Channel Islands National Park, California: U.S. Geological Survey Scientific Investigations Report 2023–5026, 27 p., https://doi.org/10.3133/sir20235026.","productDescription":"Report: vii, 27 p.; Data Release","numberOfPages":"27","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-135728","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":415211,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9GG6NB5","text":"USGS data release","linkHelpText":"Sr concentrations and 87Sr/86Sr data used to determine the Sr-chronostratigraphic age of sirenian fossils on Santa Rosa Island, Channel Islands National Park: California, USA"},{"id":415210,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5026/images/"},{"id":415208,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/sir20235026/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2023-5026"},{"id":415206,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5026/coverthb.jpg"},{"id":415207,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5026/sir20235026.pdf","text":"Report","size":"42.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5026"},{"id":415209,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5026/sir20235026.XML"},{"id":500882,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114663.htm"}],"country":"United States","state":"California","otherGeospatial":"Santa Rosa Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -120.27493358761777,\n 34.050843485499456\n ],\n [\n -120.27493358761777,\n 33.868674166486116\n ],\n [\n -119.93999465714583,\n 33.868674166486116\n ],\n [\n -119.93999465714583,\n 34.050843485499456\n ],\n [\n -120.27493358761777,\n 34.050843485499456\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

Center Director, Geosciences and Environmental Change Science Center
U.S. Geological Survey
Box 25046, Mail Stop 980
Denver, CO 80225

Contact Pubs Warehouse

","tableOfContents":"","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2023-04-12","noUsgsAuthors":false,"publicationDate":"2023-04-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Paces, James B. 0000-0002-9809-8493","orcid":"https://orcid.org/0000-0002-9809-8493","contributorId":118216,"corporation":false,"usgs":true,"family":"Paces","given":"James B.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":868609,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Minor, Scott A. 0000-0002-6976-9235 sminor@usgs.gov","orcid":"https://orcid.org/0000-0002-6976-9235","contributorId":765,"corporation":false,"usgs":true,"family":"Minor","given":"Scott","email":"sminor@usgs.gov","middleInitial":"A.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":868610,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schmidt, Kevin M. 0000-0003-2365-8035 kschmidt@usgs.gov","orcid":"https://orcid.org/0000-0003-2365-8035","contributorId":1985,"corporation":false,"usgs":true,"family":"Schmidt","given":"Kevin","email":"kschmidt@usgs.gov","middleInitial":"M.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":868611,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hoffman, Jonathan","contributorId":303915,"corporation":false,"usgs":false,"family":"Hoffman","given":"Jonathan","affiliations":[{"id":34644,"text":"Santa Barbara Museum of Natural History","active":true,"usgs":false}],"preferred":false,"id":868612,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70246323,"text":"70246323 - 2023 - Sediment and nutrient deposition over a reconnected floodplain during large-scale river diversions, the Bonnet Carré spillway in 2011, 2016, and 2019","interactions":[],"lastModifiedDate":"2023-07-05T14:13:25.298908","indexId":"70246323","displayToPublicDate":"2023-04-12T08:52:27","publicationYear":"2023","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Sediment and nutrient deposition over a reconnected floodplain during large-scale river diversions, the Bonnet Carré spillway in 2011, 2016, and 2019","docAbstract":"

In hopes of reversing or slowing the decline of the river delta, water diversions have been built and planned, and natural diversions have formed and been allowed to develop along the lower Mississippi River. In addition to the possibility of building land, these diversions allow for the storage of nutrients within the deposited sediments and provide a buffer from coastal storm surge flooding. Deposition from diversions reduces nutrient loading to the receiving waterbodies. Along the Mississippi River delta in Louisiana, modern planned diversions after 2017 (CPRA 2017) seek to bring sediment-laden water from the river to a receiving area that may once have been part of the historic delta floodplain. Many of the existing diversions discharge directly into open-water bays of the subaqueous delta, however some flood diversions outflow to the subaerial floodplain (Kroes et al. 2015). The effects of diversion outflows to bays are difficult to physically analyze and quantify due to the complex hydrodynamics of subaqueous sites, such as storm-driven resuspension, and tidal currents that mobilize deposited fine sediments downcoast or off the continental shelf. In contrast, flood diversions that outflow to subaerial floodplains offer clear and numerous sediment deposition measurement opportunities and clearly identifiable material to analyze. Flood diversions, while similar, may not exhibit identical depositional environments due to hydraulic gradient and vegetation differences. Because flood diversions draw water from the river at a greater height above the riverbed, they may entrain less bed sediment than non-flood diversions (Karmaker et al. 2010). Previous studies indicate that the large discharges through flood diversion control structures deposit large masses of sediment (Nittrouer et al. 2012) and nutrients and can provide depositional curves that may be extrapolated to other diversions (Kroes et al. 2015).

","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of SEDHYD2023","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"SEDHYD2023: The sedimentation and hydrologic modeling conference","conferenceDate":"May 8-12, 2023","conferenceLocation":"St. Louis, MO","language":"English","publisher":"SEDHYD","usgsCitation":"Kroes, D., Noe, G.E., Ramirez, D., and Vosburg, B., 2023, Sediment and nutrient deposition over a reconnected floodplain during large-scale river diversions, the Bonnet Carré spillway in 2011, 2016, and 2019, in Proceedings of SEDHYD2023, St. Louis, MO, May 8-12, 2023, 11 p.","productDescription":"11 p.","ipdsId":"IP-151842","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":418678,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":418675,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://www.sedhyd.org/2023Program/s68.html","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Louisiana","otherGeospatial":"Bonnet Carré spillway, Lake Pontchartrain, Mississippi River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -90.42757540318235,\n 30.082894344072514\n ],\n [\n -90.42757540318235,\n 30.01150844828244\n ],\n [\n -90.3745696787966,\n 30.01150844828244\n ],\n [\n -90.3745696787966,\n 30.082894344072514\n ],\n [\n -90.42757540318235,\n 30.082894344072514\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","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":876812,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Noe, Gregory E. 0000-0002-6661-2646 gnoe@usgs.gov","orcid":"https://orcid.org/0000-0002-6661-2646","contributorId":139100,"corporation":false,"usgs":true,"family":"Noe","given":"Gregory","email":"gnoe@usgs.gov","middleInitial":"E.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":876813,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ramirez, David","contributorId":315549,"corporation":false,"usgs":false,"family":"Ramirez","given":"David","email":"","affiliations":[{"id":12537,"text":"USACE","active":true,"usgs":false}],"preferred":false,"id":876814,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vosburg, Brian","contributorId":315550,"corporation":false,"usgs":false,"family":"Vosburg","given":"Brian","email":"","affiliations":[{"id":68350,"text":"Grey Boat Group","active":true,"usgs":false}],"preferred":false,"id":876815,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}