{"pageNumber":"285","pageRowStart":"7100","pageSize":"25","recordCount":184769,"records":[{"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":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","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":70238846,"text":"70238846 - 2023 - Changes in sediment transport processes at the Chandeleur Islands, Louisiana in response to storm impact","interactions":[],"lastModifiedDate":"2023-04-26T15:11:06.150988","indexId":"70238846","displayToPublicDate":"2023-04-15T09:25:36","publicationYear":"2023","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Changes in sediment transport processes at the Chandeleur Islands, Louisiana in response to storm impact","docAbstract":"

We analyzed elevation changes at the northern Chandeleur Islands, Louisiana, to quantify sediment fluxes and assess sediment transport processes over two time periods (1920 – 2007 and 2007 – 2015). Wave-driven alongshore sediment transport is the predominant fair-weather process, whereas storms transport sediment across the island platform and promote shoreline retreat. Major storm impacts, where storm surge exceeds island elevation, severely erode the island platform and remove sediment from the system. During periods of recovery, onshore bar migration and welding contribute to subaerial island growth. The analyses show changes in dominant transport processes type and dominance relative to storm response over the two time periods. These results provide understanding on the sediment transport processes that drive the geomorphic evolution of barrier islands which is crucial for predicting future resilience.

","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_0003","usgsCitation":"Flocks, J., and Bernier, J., 2023, Changes in sediment transport processes at the Chandeleur Islands, Louisiana in response to storm impact, in The proceedings of the coastal sediments 2023, New Orleans, LA, April 11-15, 2023, p. 24-35, https://doi.org/10.1142/9789811275135_0003.","productDescription":"12 p.","startPage":"24","endPage":"35","ipdsId":"IP-147600","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":416371,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Chandeleur Islands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -88.97760848369228,\n 29.6330492556649\n ],\n [\n -88.80826187109011,\n 29.818733306044066\n ],\n [\n -88.80141958371236,\n 29.952212734679904\n ],\n [\n -88.86300017011308,\n 30.058867458511088\n ],\n [\n -88.88523760409095,\n 30.04850328211937\n ],\n [\n -88.84589445166849,\n 29.922566087016705\n ],\n [\n -88.87326360117996,\n 29.832089287753902\n ],\n [\n -88.9177384691361,\n 29.743015714404763\n ],\n [\n -89.0135304924261,\n 29.6464299800531\n ],\n [\n -89.00839877689286,\n 29.625614751671378\n ],\n [\n -88.97760848369228,\n 29.6330492556649\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2023-03-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Flocks, James 0000-0002-6177-7433","orcid":"https://orcid.org/0000-0002-6177-7433","contributorId":221107,"corporation":false,"usgs":true,"family":"Flocks","given":"James","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":858895,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bernier, Julie 0000-0002-9918-5353 jbernier@usgs.gov","orcid":"https://orcid.org/0000-0002-9918-5353","contributorId":3549,"corporation":false,"usgs":true,"family":"Bernier","given":"Julie","email":"jbernier@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":858896,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"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). 

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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":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":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":70242890,"text":"70242890 - 2023 - Barrier islands and spits of northern Alaska: Decadal scale morphological change","interactions":[],"lastModifiedDate":"2023-04-26T15:27:20.116064","indexId":"70242890","displayToPublicDate":"2023-04-15T09:23:24","publicationYear":"2023","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Barrier islands and spits of northern Alaska: Decadal scale morphological change","docAbstract":"

Arctic barrier islands and spits are dynamic features influenced by a variety of oceanographic, geologic, and environmental factors. Many serve as habitat and protection for native species and shelter the coast from waves and storms that can flood and erode the adjacent mainland. This paper summarizes results of a study documenting changes to barrier morphology along the North Slope coast of Alaska between the United States-Canadian border and Cape Beaufort, from 1947 to 2020. Changes considered include number of barriers, area and perimeter, shoreline length, barrier sinuosity and width, presence and number of relict terminus features, presence and coverage of tundra vegetation, barrier orientation, termini migration rates, and elevation metrics. Wave conditions are also summarized and related to changes in barrier morphology. The results of this study help to better predict future barrier evolution and prevalence along Alaska’s coast by increasing our understanding of Arctic barrier development, migration, and degradation via the evaluation of historical morphometrics.

","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"The proceedings of the coastal sediments 2023","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"Coastal Sediments 2023","conferenceDate":"Apr 11-15, 2023","conferenceLocation":"New Orleans, LA","language":"English","publisher":"World Scientific","doi":"10.1142/9789811275135_0004","usgsCitation":"Gibbs, A.E., Erikson, L.H., and Hamilton, A., 2023, Barrier islands and spits of northern Alaska: Decadal scale morphological change, in The proceedings of the coastal sediments 2023, New Orleans, LA, Apr 11-15, 2023, p. 36-43, https://doi.org/10.1142/9789811275135_0004.","productDescription":"8 p.","startPage":"36","endPage":"43","ipdsId":"IP-142955","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":416236,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -163.42335256181659,\n 69.0995277856907\n ],\n [\n -162.87983129296867,\n 69.64048859864712\n ],\n [\n -161.91672608588226,\n 70.1528449804403\n ],\n [\n -160.5624612093187,\n 70.3363915880316\n ],\n [\n -159.516096091215,\n 70.71745022826315\n ],\n [\n -158.04400532669445,\n 70.75672901453629\n ],\n [\n -157.40466961071726,\n 70.8676811601508\n ],\n [\n -156.64743292467915,\n 71.25636424074338\n ],\n [\n -155.74445149424355,\n 71.04370814678796\n ],\n [\n -156.15430533931752,\n 70.79363973950063\n ],\n [\n -155.44986979205538,\n 70.77234882195742\n ],\n [\n -154.1965180180089,\n 70.46782572412022\n ],\n [\n -152.78851915364106,\n 70.43164835456875\n ],\n [\n -150.67327890887,\n 70.33442328699834\n ],\n [\n -149.30371661915854,\n 70.36389418289272\n ],\n [\n -147.9060578157725,\n 70.16393032923233\n ],\n [\n -146.1587058241269,\n 70.06791748849497\n ],\n [\n -144.7554641660867,\n 69.87614439971492\n ],\n [\n -143.47450950992425,\n 69.9925644467153\n ],\n [\n -141.04012909766612,\n 69.52717114277019\n ],\n [\n -140.78380081194413,\n 70.18263172457915\n ],\n [\n -145.11234255342293,\n 70.51672278288129\n ],\n [\n -151.10982675892876,\n 71.07270778847237\n ],\n [\n -155.37976387041476,\n 71.61590065290574\n ],\n [\n -157.0540200350941,\n 71.57130230096828\n ],\n [\n -159.85173502083515,\n 70.93692107832385\n ],\n [\n -162.56534263215494,\n 70.38693616436714\n ],\n [\n -164.08021682837645,\n 69.49188311703958\n ],\n [\n -164.2308587824812,\n 69.26843165216309\n ],\n [\n -163.42335256181659,\n 69.0995277856907\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2023-03-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Gibbs, Ann E. 0000-0002-0883-3774 agibbs@usgs.gov","orcid":"https://orcid.org/0000-0002-0883-3774","contributorId":2644,"corporation":false,"usgs":true,"family":"Gibbs","given":"Ann","email":"agibbs@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":870113,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Erikson, Li H. 0000-0002-8607-7695 lerikson@usgs.gov","orcid":"https://orcid.org/0000-0002-8607-7695","contributorId":149963,"corporation":false,"usgs":true,"family":"Erikson","given":"Li","email":"lerikson@usgs.gov","middleInitial":"H.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":870114,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hamilton, Anna I","contributorId":304304,"corporation":false,"usgs":false,"family":"Hamilton","given":"Anna I","affiliations":[{"id":63998,"text":"Former USGS volunteer","active":true,"usgs":false}],"preferred":false,"id":870115,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"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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}\n ]\n}","noUsgsAuthors":false,"publicationDate":"2023-03-23","publicationStatus":"PW","contributors":{"authors":[{"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":870396,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aretxabaleta, Alfredo 0000-0002-9914-8018 aaretxabaleta@usgs.gov","orcid":"https://orcid.org/0000-0002-9914-8018","contributorId":140090,"corporation":false,"usgs":true,"family":"Aretxabaleta","given":"Alfredo","email":"aaretxabaleta@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":870397,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ashton, Andrew","contributorId":184098,"corporation":false,"usgs":false,"family":"Ashton","given":"Andrew","affiliations":[],"preferred":false,"id":870398,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barnhardt, Walter 0000-0001-8840-6280 wbarnhardt@usgs.gov","orcid":"https://orcid.org/0000-0001-8840-6280","contributorId":223483,"corporation":false,"usgs":true,"family":"Barnhardt","given":"Walter","email":"wbarnhardt@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":870399,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Doran, Kara S. 0000-0001-8050-5727","orcid":"https://orcid.org/0000-0001-8050-5727","contributorId":292448,"corporation":false,"usgs":true,"family":"Doran","given":"Kara S.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":870400,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"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":870401,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70242974,"text":"70242974 - 2023 - Wave asymmetry impacts on sediment processes at the nearshore of Fire Island, New York","interactions":[],"lastModifiedDate":"2023-04-26T10:59:36.753951","indexId":"70242974","displayToPublicDate":"2023-04-15T08:53:42","publicationYear":"2023","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Wave asymmetry impacts on sediment processes at the nearshore of Fire Island, New York","docAbstract":"

Effects of wave asymmetry on sediment processes and coastal evolution were investigated using a field data set and a numerical model. Field observations at the nearshore of Fire Island, New York revealed sediment fluxes during various wave energy levels. The preliminary results indicate a strong correlation between the wave asymmetry and the onshore bedload fluxes. The model results captured the observed hydrodynamics and the sediment processes reasonably well. Ongoing work involves in-depth analysis of the model performance, followed by the evaluation of the nearshore morphodynamics at the island and shelf scales.

","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_0173","usgsCitation":"Parlak, M., Ayhan, B., Warner, J.C., Kalra, T., and Safak, I., 2023, Wave asymmetry impacts on sediment processes at the nearshore of Fire Island, New York, in The proceedings of the coastal sediments 2023, New Orleans, LA, April 11-15, 2023, p. 1896-1901, https://doi.org/10.1142/9789811275135_0173.","productDescription":"6 p.","startPage":"1896","endPage":"1901","ipdsId":"IP-142354","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":416234,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Fire Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -73.30955844155562,\n 40.626327489934454\n ],\n [\n -73.3060815625671,\n 40.55151810050168\n ],\n [\n -72.74862196476813,\n 40.7107174407181\n ],\n [\n -72.44149751006759,\n 40.794124158036254\n ],\n [\n -72.47278942096254,\n 40.85025428939389\n ],\n [\n -72.8077287635072,\n 40.758140832620455\n ],\n [\n -73.18555151547386,\n 40.661505049457986\n ],\n [\n -73.3153549977056,\n 40.63600469144072\n ],\n [\n -73.30955844155562,\n 40.626327489934454\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2023-03-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Parlak, M. S.","contributorId":304426,"corporation":false,"usgs":false,"family":"Parlak","given":"M. S.","affiliations":[{"id":66065,"text":"Dept. Civil Engineering, Istanbul Bilgi University, Istanbul, Türkiye","active":true,"usgs":false}],"preferred":false,"id":870402,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ayhan, B. U.","contributorId":304427,"corporation":false,"usgs":false,"family":"Ayhan","given":"B. U.","affiliations":[{"id":66065,"text":"Dept. Civil Engineering, Istanbul Bilgi University, Istanbul, Türkiye","active":true,"usgs":false}],"preferred":false,"id":870403,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Warner, John C. 0000-0002-3734-8903 jcwarner@usgs.gov","orcid":"https://orcid.org/0000-0002-3734-8903","contributorId":258015,"corporation":false,"usgs":true,"family":"Warner","given":"John","email":"jcwarner@usgs.gov","middleInitial":"C.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":870404,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kalra, Tarandeep 0000-0001-5468-248X tkalra@usgs.gov","orcid":"https://orcid.org/0000-0001-5468-248X","contributorId":304428,"corporation":false,"usgs":false,"family":"Kalra","given":"Tarandeep","email":"tkalra@usgs.gov","affiliations":[{"id":66067,"text":"Jupiter Intelligence, San Mateo, California","active":true,"usgs":false}],"preferred":false,"id":870405,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Safak, Ilgar","contributorId":304429,"corporation":false,"usgs":false,"family":"Safak","given":"Ilgar","affiliations":[{"id":66065,"text":"Dept. Civil Engineering, Istanbul Bilgi University, Istanbul, Türkiye","active":true,"usgs":false}],"preferred":false,"id":870406,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70243286,"text":"70243286 - 2023 - Comparing empirical sediment transport modeling approaches in Michigan rivers","interactions":[],"lastModifiedDate":"2023-05-05T14:04:32.563372","indexId":"70243286","displayToPublicDate":"2023-04-15T08:51:14","publicationYear":"2023","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Comparing empirical sediment transport 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.

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\"}}]}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"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":871849,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Levin, Sara B. 0000-0002-2448-3129","orcid":"https://orcid.org/0000-0002-2448-3129","contributorId":209947,"corporation":false,"usgs":true,"family":"Levin","given":"Sara B.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":871850,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Coenen, Erin N. 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 - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":879573,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Goodling, Phillip J. 0000-0001-5715-8579","orcid":"https://orcid.org/0000-0001-5715-8579","contributorId":239738,"corporation":false,"usgs":true,"family":"Goodling","given":"Phillip","email":"","middleInitial":"J.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":879574,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hafen, Konrad 0000-0002-1451-362X","orcid":"https://orcid.org/0000-0002-1451-362X","contributorId":215959,"corporation":false,"usgs":true,"family":"Hafen","given":"Konrad","email":"","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":879575,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hammond, John C. 0000-0002-4935-0736","orcid":"https://orcid.org/0000-0002-4935-0736","contributorId":223108,"corporation":false,"usgs":true,"family":"Hammond","given":"John C.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":879576,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McShane, Ryan R. 0000-0002-3128-0039","orcid":"https://orcid.org/0000-0002-3128-0039","contributorId":219009,"corporation":false,"usgs":true,"family":"McShane","given":"Ryan R.","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":879577,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sando, Roy 0000-0003-0704-6258","orcid":"https://orcid.org/0000-0003-0704-6258","contributorId":3874,"corporation":false,"usgs":true,"family":"Sando","given":"Roy","email":"","affiliations":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"preferred":true,"id":879578,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Shastry, Apoorva Ramesh 0000-0002-3996-4857","orcid":"https://orcid.org/0000-0002-3996-4857","contributorId":317867,"corporation":false,"usgs":true,"family":"Shastry","given":"Apoorva","email":"","middleInitial":"Ramesh","affiliations":[{"id":227,"text":"Earth Surface Dynamics Program","active":true,"usgs":true}],"preferred":true,"id":879579,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Simeone, Caelan E. 0000-0003-3263-6452 csimeone@usgs.gov","orcid":"https://orcid.org/0000-0003-3263-6452","contributorId":221126,"corporation":false,"usgs":true,"family":"Simeone","given":"Caelan","email":"csimeone@usgs.gov","middleInitial":"E.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":879580,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Watkins, David 0000-0002-7544-0700","orcid":"https://orcid.org/0000-0002-7544-0700","contributorId":317375,"corporation":false,"usgs":true,"family":"Watkins","given":"David","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":879581,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"White, Elaheh 0000-0003-1248-5247","orcid":"https://orcid.org/0000-0003-1248-5247","contributorId":295260,"corporation":false,"usgs":true,"family":"White","given":"Elaheh","email":"","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":879582,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"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":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":374,"text":"Maryland Water Science Center","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":879583,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70242991,"text":"70242991 - 2023 - Processes controlling coastal erosion along Cape Cod Bay, MA","interactions":[],"lastModifiedDate":"2023-04-26T11:00:06.393489","indexId":"70242991","displayToPublicDate":"2023-04-15T08:43:40","publicationYear":"2023","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Processes controlling coastal erosion along Cape Cod Bay, MA","docAbstract":"

Cape Cod Bay, MA, is a semi-enclosed embayment in the northeastern United States, open on the north to the Gulf of Maine. The coastline experiences impacts typically from strong Nor’easter storms that occur in the late fall or winter months, with some sections of this coastline being affected more severely than others. We investigate the processes that cause spatial variability in storm impacts by using geophysical surveys, shoreline-change analysis, and numerical modeling. We simulated the Gulf of Maine and Cape Cod Bay from Jan–April, 2021, using the COAWST modeling system, including ocean, wave, infragravity wave, and sediment transport models. Results identify bay-scale circulation of alongshore sediment fluxes and convergences at regional shoals. Nearshore modeling also revealed zones of increased wave heights that correlate with regions of increased erosion and coastal angle orientation. Modeled and computed shoreline-change have some correlation but the model does not capture all the variability. This overall approach can potentially be used for other coastal locations to identify regions of storm impacts and to manage coastal resources.

","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_0171","usgsCitation":"Warner, J.C., Brothers, L.L., Himmelstoss, E.A., Sherwood, C.R., Aretxabaleta, A., Foster, D.S., and Farris, A.S., 2023, Processes controlling coastal erosion along Cape Cod Bay, MA, in The proceedings of the coastal sediments 2023, New Orleans, LA, April 11-15, 2023, p. 1872-1883, https://doi.org/10.1142/9789811275135_0171.","productDescription":"12 p.","startPage":"1872","endPage":"1883","ipdsId":"IP-142387","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":416233,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Massachusetts","otherGeospatial":"Cape Cod Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -70.64819420423547,\n 42.075734354731\n ],\n [\n -70.64819420423547,\n 41.73638149646493\n ],\n [\n -69.99225888262333,\n 41.73638149646493\n ],\n [\n -69.99225888262333,\n 42.075734354731\n ],\n [\n -70.64819420423547,\n 42.075734354731\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2023-03-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Warner, John C. 0000-0002-3734-8903 jcwarner@usgs.gov","orcid":"https://orcid.org/0000-0002-3734-8903","contributorId":258015,"corporation":false,"usgs":true,"family":"Warner","given":"John","email":"jcwarner@usgs.gov","middleInitial":"C.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":870455,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brothers, Laura L. 0000-0003-2986-5166 lbrothers@usgs.gov","orcid":"https://orcid.org/0000-0003-2986-5166","contributorId":176698,"corporation":false,"usgs":true,"family":"Brothers","given":"Laura","email":"lbrothers@usgs.gov","middleInitial":"L.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":870456,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Himmelstoss, Emily A. 0000-0002-1760-5474 ehimmelstoss@usgs.gov","orcid":"https://orcid.org/0000-0002-1760-5474","contributorId":194838,"corporation":false,"usgs":true,"family":"Himmelstoss","given":"Emily","email":"ehimmelstoss@usgs.gov","middleInitial":"A.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":870457,"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":870458,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Aretxabaleta, Alfredo 0000-0002-9914-8018 aaretxabaleta@usgs.gov","orcid":"https://orcid.org/0000-0002-9914-8018","contributorId":140090,"corporation":false,"usgs":true,"family":"Aretxabaleta","given":"Alfredo","email":"aaretxabaleta@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":870459,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"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":870460,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Farris, Amy S. 0000-0002-4668-7261 afarris@usgs.gov","orcid":"https://orcid.org/0000-0002-4668-7261","contributorId":196866,"corporation":false,"usgs":true,"family":"Farris","given":"Amy","email":"afarris@usgs.gov","middleInitial":"S.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":870461,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70244030,"text":"70244030 - 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. A., Ahlering, M., Chase, K.J., Crausbay, S., Davidson, A.D., Elliott, J., Giocomo, J., Hoover, D.L., Klemm, T., Lightfoot, D., McKenna, O.P., Miller, B.W., Mosher, D., Nagy, R.C., Nippert, J.B., Pittman, J., Porensky, L., Stephens, J., and Zale, A.V., 2023, Synthesis of climate and ecological science to support grassland management priorities in the North Central Region: U.S. Geological Survey Open-File Report 2023–1036, 21 p., https://doi.org/10.3133/ofr20231036.","productDescription":"ix, 21 p.","onlineOnly":"Y","ipdsId":"IP-151694","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":40927,"text":"North Central Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":499779,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114667.htm","linkFileType":{"id":5,"text":"html"}},{"id":415810,"rank":3,"type":{"id":22,"text":"Related 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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

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Executive Summary

Understanding how climate change and variability will impact grassland ecosystems is crucial for successful grassland management in the 21st century. In 2020, the U.S. Geological Survey North Central Climate Adaptation Science Center (USGS NC CASC) began a project to establish a baseline of information to best serve grassland managers (that is, those who develop grassland management plans or implement those plans on the ground) at Federal, State, and Tribal agen-cies and nongovernmental organizations to help meet regional grassland management goals. This project “A Synthesis of Climate Impacts, Stakeholder Needs, and Adaptation in Northern Great Plains Grassland Ecosystems” (hereafter, the Grasslands Synthesis Project), had two primary goals: (1) to synthesize management goals and challenges for grassland managers across the region and (2) to assess the state-of-the-science and identify knowledge gaps for addressing the goals and challenges within the context of climate change. The findings from the Grasslands Syn-thesis Project are described in two volumes. This report serves several purposes, including providing (1) a synthesis of regional grassland management goals and challenges, (2) identification of information needs relevant to grassland management in a changing climate, and (3) summaries of grassland management issues by ecoregion and management organization or agency.

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\"}}]}","contact":"

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":{"editors":[{"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":869654,"contributorType":{"id":2,"text":"Editors"},"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":869655,"contributorType":{"id":2,"text":"Editors"},"rank":2}]}} ,{"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":70243044,"text":"70243044 - 2023 - Coordinating science during an eruption: Lessons from the 2020–2021 Kīlauea volcanic eruption","interactions":[],"lastModifiedDate":"2023-04-27T12:09:14.397858","indexId":"70243044","displayToPublicDate":"2023-04-14T07:06:51","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1109,"text":"Bulletin of Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"Coordinating science during an eruption: Lessons from the 2020–2021 Kīlauea volcanic eruption","docAbstract":"

Data collected during well-observed eruptions can lead to dramatic increases in our understanding of volcanic processes. However, the necessary prioritization of public safety and hazard mitigation during a crisis means that scientific opportunities may be sacrificed. Thus, maximizing the scientific gains from eruptions requires improved planning and coordinating science activities among governmental organizations and academia before and during volcanic eruptions. One tool to facilitate this coordination is a Scientific Advisory Committee (SAC). In the USA, the Community Network for Volcanic Eruption Response (CONVERSE) has been developing and testing this concept during workshops and scenario-based activities. The December 2020 eruption of Kīlauea volcano, Hawaii, provided an opportunity to test and refine this model in real-time and in a real-world setting. We present here the working model of a SAC developed during this eruption. Successes of the Kīlauea SAC (K-SAC) included broadening the pool of scientists involved in eruption response and developing and codifying procedures that may form the basis of operation for future SACs. Challenges encountered by the K-SAC included a process of review and facilitation of research proposals that was too slow to include outside participation in the early parts of the eruption and a decision process that fell on a small number of individuals at the responding volcano observatory. Possible ways to address these challenges include (1) supporting community-building activities between eruptions that make connections among scientists within and outside formal observatories, (2) identifying key science questions and pre-planning science activities, which would facilitate more rapid implementation across a broader scientific group, and (3) continued dialog among observatory scientists, emergency responders, and non-observatory scientists about the role of SACs. The SAC model holds promise to become an integral part of future efforts, leading in the short and longer term to more effective hazard response and greater scientific discovery and understanding.

","language":"English","publisher":"Springer","doi":"10.1007/s00445-023-01644-1","usgsCitation":"Cooper, K., Anderson, K.R., Cashman, K., Coombs, M.L., Dietterich, H., Fischer, T., Houghton, B.F., Johanson, I.A., Lynn, K.J., Manga, M., and Wauthier, C., 2023, Coordinating science during an eruption: Lessons from the 2020–2021 Kīlauea volcanic eruption: Bulletin of Volcanology, v. 85, 29, 13 p., https://doi.org/10.1007/s00445-023-01644-1.","productDescription":"29, 13 p.","ipdsId":"IP-143233","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":443854,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s00445-023-01644-1","text":"Publisher Index Page"},{"id":416433,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kīlauea volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -155.39072721010044,\n 19.500512921908012\n ],\n [\n -155.39072721010044,\n 19.207814708187342\n ],\n [\n -155.00637106037848,\n 19.207814708187342\n ],\n [\n -155.00637106037848,\n 19.500512921908012\n ],\n [\n -155.39072721010044,\n 19.500512921908012\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"85","noUsgsAuthors":false,"publicationDate":"2023-04-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Cooper, Kari M.","contributorId":304521,"corporation":false,"usgs":false,"family":"Cooper","given":"Kari M.","affiliations":[{"id":16975,"text":"University of California Davis","active":true,"usgs":false}],"preferred":false,"id":870784,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, Kyle R. 0000-0001-8041-3996 kranderson@usgs.gov","orcid":"https://orcid.org/0000-0001-8041-3996","contributorId":3522,"corporation":false,"usgs":true,"family":"Anderson","given":"Kyle","email":"kranderson@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":870785,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cashman, Kathy","contributorId":304522,"corporation":false,"usgs":false,"family":"Cashman","given":"Kathy","email":"","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":870786,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Coombs, Michelle L. 0000-0002-6002-6806 mcoombs@usgs.gov","orcid":"https://orcid.org/0000-0002-6002-6806","contributorId":2809,"corporation":false,"usgs":true,"family":"Coombs","given":"Michelle","email":"mcoombs@usgs.gov","middleInitial":"L.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":870787,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dietterich, Hannah R. 0000-0001-7898-4343","orcid":"https://orcid.org/0000-0001-7898-4343","contributorId":212771,"corporation":false,"usgs":true,"family":"Dietterich","given":"Hannah R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":870788,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fischer, Tobias","contributorId":267762,"corporation":false,"usgs":false,"family":"Fischer","given":"Tobias","affiliations":[{"id":36307,"text":"University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":870789,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Houghton, Bruce F. 0000-0002-7532-9770","orcid":"https://orcid.org/0000-0002-7532-9770","contributorId":140077,"corporation":false,"usgs":false,"family":"Houghton","given":"Bruce","email":"","middleInitial":"F.","affiliations":[{"id":6977,"text":"University of Hawai`i at Hilo","active":true,"usgs":false},{"id":13351,"text":"University of Hawaii Cooperative Studies Unit","active":true,"usgs":false}],"preferred":false,"id":870790,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Johanson, Ingrid A. 0000-0002-6049-2225","orcid":"https://orcid.org/0000-0002-6049-2225","contributorId":215613,"corporation":false,"usgs":true,"family":"Johanson","given":"Ingrid","email":"","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":870791,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Lynn, Kendra J. 0000-0001-7886-4376","orcid":"https://orcid.org/0000-0001-7886-4376","contributorId":290327,"corporation":false,"usgs":true,"family":"Lynn","given":"Kendra","email":"","middleInitial":"J.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":870792,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Manga, Michael 0000-0003-3286-4682","orcid":"https://orcid.org/0000-0003-3286-4682","contributorId":265640,"corporation":false,"usgs":false,"family":"Manga","given":"Michael","email":"","affiliations":[{"id":6609,"text":"UC Berkeley","active":true,"usgs":false}],"preferred":false,"id":870793,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Wauthier, Christelle","contributorId":176224,"corporation":false,"usgs":false,"family":"Wauthier","given":"Christelle","email":"","affiliations":[],"preferred":false,"id":870794,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70242872,"text":"70242872 - 2023 - Secondary forest within a timber plantation concession in Borneo contributes to a diverse mammal assemblage","interactions":[],"lastModifiedDate":"2023-04-21T12:07:33.703351","indexId":"70242872","displayToPublicDate":"2023-04-14T07:05:02","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3871,"text":"Global Ecology and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Secondary forest within a timber plantation concession in Borneo contributes to a diverse mammal assemblage","docAbstract":"

Commercial tree plantations of fast-growing species have become increasingly important in Southeast Asia to meet global demand for wood and wood fiber products. There is a growing need to understand more about their value for wildlife and how they can be managed for biodiversity. We evaluated the effects of landscape attributes on mammal communities in a timber concession consisting of 83 % secondary forest and 17 % tree plantations in northern Sabah, Malaysia. Using camera traps, we compared mammalian species assemblages of secondary forest and commercial tree plantation stands and identified habitat predictors associated with total mammal species detections and species richness in the landscape mosaic. We used 87 camera stations deployed for 23 days across two major land-use types: 62 sites in secondary forest (previously logged natural forest) and 25 sites in tree plantations. We evaluated variation in species richness in these two major land-use categories and assessed the effects of natural and anthropogenic predictors on variation in total mammal detections and species richness. We detected at least 23 large and medium-sized mammal species over 2035 trap nights. Fourteen of those species were classified as threatened or near-threatened by the International Union for the Conservation of Nature. Rarefaction did not reveal differences in mammal species richness or diversity between camera sites placed in tree plantations and secondary forests, likely because most camera sites in tree plantations were close to secondary forest and comprised < 30 % of all sites. However, generalized linear models indicated lower mammal diversity as proportions of tree plantation and proximity to human settlements increased. Total mammal records, including those of threatened mammals, increased with greater proportions of secondary forest. Retention of larger tracts of secondary forest around plantation areas appears to be important to maintain mammalian species richness and contributes to the conservation value of commercial timber plantations. These findings may assist in the management of mammals of conservation concern and implementation of adaptive management plans to enhance biodiversity conservation in commercial plantations.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.gecco.2023.e02474","usgsCitation":"William, W.O., van Manen, F.T., Sharp, S.P., and Ratnayeke, S., 2023, Secondary forest within a timber plantation concession in Borneo contributes to a diverse mammal assemblage: Global Ecology and Conservation, v. 43, e02474, 15 p., https://doi.org/10.1016/j.gecco.2023.e02474.","productDescription":"e02474, 15 p.","ipdsId":"IP-148208","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":443856,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gecco.2023.e02474","text":"Publisher Index Page"},{"id":416117,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Borneo","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 120.54949981760905,\n 8.408648527731742\n ],\n [\n 107.98654452383744,\n 8.408648527731742\n ],\n [\n 107.98654452383744,\n -4.82108241332746\n ],\n [\n 120.54949981760905,\n -4.82108241332746\n ],\n [\n 120.54949981760905,\n 8.408648527731742\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"43","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"William, Wilvia Olivia","contributorId":304283,"corporation":false,"usgs":false,"family":"William","given":"Wilvia","email":"","middleInitial":"Olivia","affiliations":[{"id":66015,"text":"Forest Solutions, Malaysia","active":true,"usgs":false}],"preferred":false,"id":870065,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"van Manen, Frank T. 0000-0001-5340-8489 fvanmanen@usgs.gov","orcid":"https://orcid.org/0000-0001-5340-8489","contributorId":2267,"corporation":false,"usgs":true,"family":"van Manen","given":"Frank","email":"fvanmanen@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":870066,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sharp, Stuart P.","contributorId":203981,"corporation":false,"usgs":false,"family":"Sharp","given":"Stuart","email":"","middleInitial":"P.","affiliations":[{"id":36781,"text":"Lancaster Environment Centre, Lancaster University, Lancaster, LA1 4YQ, UK","active":true,"usgs":false}],"preferred":false,"id":870067,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ratnayeke, Shyamala","contributorId":203978,"corporation":false,"usgs":false,"family":"Ratnayeke","given":"Shyamala","email":"","affiliations":[{"id":36779,"text":"Department of Biological Sciences, Sunway University, Malaysia","active":true,"usgs":false}],"preferred":false,"id":870068,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"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":70242790,"text":"70242790 - 2023 - The 2022 Hunga-Tonga megatsunami: Near-field simulation of a once-in-a-century event","interactions":[],"lastModifiedDate":"2023-04-18T11:45:23.942372","indexId":"70242790","displayToPublicDate":"2023-04-14T06:42:23","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5010,"text":"Science Advances","active":true,"publicationSubtype":{"id":10}},"title":"The 2022 Hunga-Tonga megatsunami: Near-field simulation of a once-in-a-century event","docAbstract":"
The Hunga Tonga–Hunga Ha’apai (HTHH) volcanic eruption in January 2022 generated catastrophic tsunami and contends for the largest natural explosion in more than a century. The main island, Tongatapu, suffered waves up to 17 m, and Tofua Island suffered waves up to 45 m, comfortably placing HTHH in the “megatsunami” league. We present a tsunami simulation of the Tongan Archipelago calibrated by field observations, drone, and satellite data. Our simulation emphasizes how the complex shallow bathymetry of the area acted as a low-velocity wave trap, capturing tsunami for more than 1 hour. Despite its size and long duration, few lives were lost. Simulation suggests that HTHH’s location relative to urban centers saved Tonga from a worse outcome. Whereas 2022 seems to have been a lucky escape, other oceanic volcanoes have the capacity to spawn future tsunami at HTHH scale. Our simulation amplifies the state of understanding of volcanic explosion tsunami and provides a framework for assessment of future hazards.
","language":"English","publisher":"American Association for the Advancement of Science’s (AAAS)","doi":"10.1126/sciadv.adf5493","usgsCitation":"Purkis, S., Ward, S., Fitzpatrick, N.M., Garvin, J.B., Slayback, D., Cronin, S.J., Palaseanu-Lovejoy, M., and Dempsey, A., 2023, The 2022 Hunga-Tonga megatsunami: Near-field simulation of a once-in-a-century event: Science Advances, v. 9, no. 15, eadf549, 14 p., https://doi.org/10.1126/sciadv.adf5493.","productDescription":"eadf549, 14 p.","ipdsId":"IP-146807","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":443858,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1126/sciadv.adf5493","text":"Publisher Index Page"},{"id":415908,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Tonga Archipelago","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -175.75159349411712,\n -19.246338052333215\n ],\n [\n -175.75159349411712,\n -21.500676205311535\n ],\n [\n -173.9725736011181,\n -21.500676205311535\n ],\n [\n -173.9725736011181,\n -19.246338052333215\n ],\n [\n -175.75159349411712,\n -19.246338052333215\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"9","issue":"15","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Purkis, Sam 0000-0001-8646-222X","orcid":"https://orcid.org/0000-0001-8646-222X","contributorId":304221,"corporation":false,"usgs":false,"family":"Purkis","given":"Sam","affiliations":[{"id":5112,"text":"University of Miami","active":true,"usgs":false}],"preferred":false,"id":869782,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ward, Steven N","contributorId":304222,"corporation":false,"usgs":false,"family":"Ward","given":"Steven N","affiliations":[{"id":27155,"text":"University of California Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":869783,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fitzpatrick, Nathan M.","contributorId":304223,"corporation":false,"usgs":false,"family":"Fitzpatrick","given":"Nathan","email":"","middleInitial":"M.","affiliations":[{"id":5112,"text":"University of Miami","active":true,"usgs":false}],"preferred":false,"id":869784,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Garvin, James B.","contributorId":22112,"corporation":false,"usgs":false,"family":"Garvin","given":"James","email":"","middleInitial":"B.","affiliations":[{"id":7049,"text":"NASA Goddard Space Flight Center","active":true,"usgs":false}],"preferred":false,"id":869785,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Slayback, Dan","contributorId":304224,"corporation":false,"usgs":false,"family":"Slayback","given":"Dan","email":"","affiliations":[{"id":7049,"text":"NASA Goddard Space Flight Center","active":true,"usgs":false}],"preferred":false,"id":869786,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cronin, Shane J.","contributorId":304225,"corporation":false,"usgs":false,"family":"Cronin","given":"Shane","email":"","middleInitial":"J.","affiliations":[{"id":13376,"text":"The University of Auckland","active":true,"usgs":false}],"preferred":false,"id":869787,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Palaseanu-Lovejoy, Monica 0000-0002-3786-5118 mpal@usgs.gov","orcid":"https://orcid.org/0000-0002-3786-5118","contributorId":3639,"corporation":false,"usgs":true,"family":"Palaseanu-Lovejoy","given":"Monica","email":"mpal@usgs.gov","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":5061,"text":"National Cooperative Geologic Mapping and Landslide Hazards","active":true,"usgs":true}],"preferred":true,"id":869788,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Dempsey, Alexandra","contributorId":304226,"corporation":false,"usgs":false,"family":"Dempsey","given":"Alexandra","email":"","affiliations":[{"id":66002,"text":"Khaled bin Sultan Living Oceans Foundation","active":true,"usgs":false}],"preferred":false,"id":869789,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70243363,"text":"70243363 - 2023 - Vital rates of a burgeoning population of Humpback Chub in western Grand Canyon","interactions":[],"lastModifiedDate":"2023-07-24T16:46:47.833694","indexId":"70243363","displayToPublicDate":"2023-04-14T06:41:41","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":"Vital rates of a burgeoning population of Humpback Chub in western Grand Canyon","docAbstract":"

The Colorado River ecosystem has experienced habitat alterations and non-native species invasions, and as a result, many of its native species have experienced extirpations, abundance declines, and range constrictions. Despite these pitfalls, Humpback Chub, Gila cypha, have persisted and, in the last 10-15 years, expanded their range to become abundant in western Grand Canyon, a river segment in which it had been rare for the prior three decades. Here we analyze a 6-year mark-recapture study from a fixed monitoring reach in western Grand Canyon and provide the first estimates of survival and growth (vital rates) for this relatively ‘new’ group of Humpback Chub. We compare vital rates in western Grand Canyon to two life history forms (residents and migrants, which represent fast and slow life history trajectories, respectively) from the more established Little Colorado River (LCR) aggregation in eastern Grand Canyon. Compared to LCR-migrants and LCR-residents, Humpback Chub in western Grand Canyon had intermediate values for apparent survival, growth, and asymptotic length. Relatively high survival of subadults coupled with fast growth allows for rapid population growth in western Grand Canyon. However, a large cohort in 2017 failed to lead to noticeable increases in adults. Seasonal survival patterns were distinct in all three groups, and apparent survival was lowest in western Grand Canyon during spring months. Adult Humpback Chub in western Grand Canyon were mobile and had a high probability of transience (i.e., just passing through the reach) and temporary emigration, demonstrating the need for future movement studies in western Grand Canyon to better distinguish emigration from survival. We discuss how observations are related to disparate temperature regimes experienced by the three groups, and if(how) the relationship between metabolism and temperature influences vital rates within the river network.

","language":"English","publisher":"American Fisheries Society","doi":"10.1002/tafs.10415","usgsCitation":"Dzul, M.C., Yackulic, C., Giardina, M.A., Van Haverbeke, D., and Yard, M., 2023, Vital rates of a burgeoning population of Humpback Chub in western Grand Canyon: Transactions of the American Fisheries Society, v. 152, no. 4, p. 443-459, https://doi.org/10.1002/tafs.10415.","productDescription":"17 p.","startPage":"443","endPage":"459","ipdsId":"IP-148437","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":498968,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/tafs.10415","text":"Publisher Index Page"},{"id":435374,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9E96ADU","text":"USGS data release","linkHelpText":"Humpback chub (Gila cypha) capture histories and growth data for two areas in the Colorado River network from 2009-2022 and 2017-2022"},{"id":416898,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Grand Canyon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111.601457318797,\n 36.65987844880918\n ],\n [\n -113.91812426407165,\n 36.65987844880918\n ],\n [\n -113.91812426407165,\n 35.63520969136876\n ],\n [\n -111.601457318797,\n 35.63520969136876\n ],\n [\n -111.601457318797,\n 36.65987844880918\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"152","issue":"4","noUsgsAuthors":false,"publicationDate":"2023-04-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Dzul, Maria C. 0000-0002-4798-5930 mdzul@usgs.gov","orcid":"https://orcid.org/0000-0002-4798-5930","contributorId":5469,"corporation":false,"usgs":true,"family":"Dzul","given":"Maria","email":"mdzul@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":872166,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yackulic, Charles B. 0000-0001-9661-0724","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":218825,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":872167,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Giardina, Mariah Aurelia 0000-0001-6753-0450","orcid":"https://orcid.org/0000-0001-6753-0450","contributorId":300798,"corporation":false,"usgs":true,"family":"Giardina","given":"Mariah","email":"","middleInitial":"Aurelia","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":872168,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Van Haverbeke, David R.","contributorId":83838,"corporation":false,"usgs":false,"family":"Van Haverbeke","given":"David R.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":872169,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Yard, Michael D. 0000-0002-6580-6027","orcid":"https://orcid.org/0000-0002-6580-6027","contributorId":291738,"corporation":false,"usgs":false,"family":"Yard","given":"Michael D.","affiliations":[{"id":62744,"text":"Retired, US Geological Survey, Southwest Biological Science Center, Flagstaff, AZ","active":true,"usgs":false}],"preferred":false,"id":872170,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ]}