{"pageNumber":"232","pageRowStart":"5775","pageSize":"25","recordCount":40783,"records":[{"id":70219037,"text":"ofr20211023 - 2021 - Black abalone surveys at Naval Base Ventura County, San Nicolas Island, California—2020, annual report","interactions":[],"lastModifiedDate":"2021-03-19T22:20:55.486396","indexId":"ofr20211023","displayToPublicDate":"2021-03-19T13:42:37","publicationYear":"2021","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":"2021-1023","displayTitle":"Black Abalone Surveys at Naval Base Ventura County, San Nicolas Island, California: 2020, Annual Report","title":"Black abalone surveys at Naval Base Ventura County, San Nicolas Island, California—2020, annual report","docAbstract":"

The U.S. Geological Survey monitors a suite of intertidal black abalone sites at San Nicolas Island, California, in cooperation with the U.S. Navy, which owns the island. The nine rocky intertidal sites were established in 1980 to study the potential impact of translocated sea otters on the intertidal black abalone population at the island. The sites were monitored from 1981 to 1997, usually annually or biennially. Monitoring resumed in 2001 and has been completed annually since then. At the time of this report, the work is conducted by the Western Ecological Research Center’s Santa Cruz Field Station, Santa Cruz, California. The study sites became particularly important, from a management perspective, after a virulent disease decimated black abalone populations throughout southern California beginning in the mid-1980s. The disease, withering syndrome, was first observed on San Nicolas Island in 1992 and during the next few years, it reduced the population there by more than 99 percent. The species was subsequently listed as endangered under the Endangered Species Act in 2009.

The subject of this report is the 2020 monitoring cycle of the sites and how the current status fits into the long-term data at San Nicolas Island. Since 2001, the monitored population has increased twelvefold to approximately 9.6 percent of the pre-disease level. This increase has resulted from generally higher levels of recruitment than seen in the first two decades of monitoring, punctuated by a few unexplained high recruitment events. Most of the population growth has been at two of the nine sites (sites 7 and 8). This pattern continued in 2020, but with increasing numbers at all sites and the highest number of abalone counted and measured island-wide since 1993. Recruitment rates have fallen since a peak in 2017, but 2020 continued to show moderate levels of additional recruitment. The distance between adjacent black abalone has decreased substantially since it was first consistently measured in 2005, potentially indicating that the abalone are close enough to one another to reproduce successfully. Sand burial can have devastating localized consequences to black abalone, but there is evidence suggesting that they may be able to escape periodic sand inundation if suitable refugia exist. These data suggest that monitoring can inform adaptive management of the resource by base resource managers.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211023","collaboration":"Prepared in cooperation with the U.S. Navy","usgsCitation":"Kenner, M.C., 2021, Black abalone surveys at Naval Base Ventura County, San Nicolas Island, California—2020, annual report: U.S. Geological Survey Open-File Report 2021–1023, 33 p., https://doi.org/10.3133/ofr20211023.","productDescription":"vii, 33 p.","numberOfPages":"33","onlineOnly":"Y","ipdsId":"IP-125069","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":384507,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1023/covrthb.jpg"},{"id":384508,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1023/ofr20211023.pdf","text":"Report","size":"5 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":384509,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1023/ofr20211023.xml"},{"id":384510,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1023/images"}],"country":"United States","state":"California","otherGeospatial":"San Nicolas Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.59442138671875,\n 33.20996748987798\n ],\n [\n -119.42928314208984,\n 33.20996748987798\n ],\n [\n -119.42928314208984,\n 33.28806392819752\n ],\n [\n -119.59442138671875,\n 33.28806392819752\n ],\n [\n -119.59442138671875,\n 33.20996748987798\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director,
Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819

","tableOfContents":"","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2021-03-19","noUsgsAuthors":false,"publicationDate":"2021-03-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Kenner, Michael C. 0000-0003-4659-461X","orcid":"https://orcid.org/0000-0003-4659-461X","contributorId":208151,"corporation":false,"usgs":true,"family":"Kenner","given":"Michael","email":"","middleInitial":"C.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":812526,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70223703,"text":"70223703 - 2021 - The 2018 update of the US National Seismic Hazard Model: Ground motion models in the central and eastern US","interactions":[],"lastModifiedDate":"2021-09-02T12:58:27.982991","indexId":"70223703","displayToPublicDate":"2021-03-19T07:56:09","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1436,"text":"Earthquake Spectra","active":true,"publicationSubtype":{"id":10}},"title":"The 2018 update of the US National Seismic Hazard Model: Ground motion models in the central and eastern US","docAbstract":"

The United States Geological Survey (USGS) National Seismic Hazard Model (NSHM) is the scientific foundation of seismic design regulations in the United States and is regularly updated to consider the best available science and data. The 2018 update of the conterminous US NSHM includes major changes to the underlying ground motion models (GMMs). Most of the changes are motivated by the new multi-period response spectra requirements of seismic design regulations that use hazard results for 22 spectral periods and 8 site classes. In the central and eastern United States (CEUS), the 2018 NSHM incorporates 31 new GMMs for hard-rock site conditions (VS30=3000m/s)\">(VS30=3000m/s)(VS30=3000m/s), including the Next Generation Attenuation (NGA)-East GMMs. New aleatory variability and site-effect models, both specific to the CEUS, are applied to all median hard-rock GMMs. This article documents the changes to the USGS GMM selection criteria and provides details on the new CEUS GMMs used in the 2018 NSHM update. The median GMMs, their weights, epistemic uncertainty, and aleatory variability are compared with those considered in prior NSHMs. This article further provides implementation details on the CEUS site-effect model, which allows conversion of hard-rock ground motions to other site conditions in the CEUS for the first time in NSHMs. Compared with the 2014 NSHM hard-rock ground motions, the weighted average of median GMMs increases for large magnitude events at middle to large distance range, epistemic uncertainty increases in almost all situations, but aleatory variability is not significantly different. Finally, the total effect on hazard is demonstrated for an assumed earthquake source model in the CEUS, which shows an increased ring of ground motions in the vicinity of the New Madrid seismic zone and decreased ground motions near the East Tennessee seismic zone.

","language":"English","publisher":"Sage Pubs","doi":"10.1177/8755293021993837","usgsCitation":"Rezaeian, S., Powers, P.M., Shumway, A., Petersen, M.D., Luco, N., Frankel, A.D., Moschetti, M.P., Thompson, E.M., and McNamara, D., 2021, The 2018 update of the US National Seismic Hazard Model: Ground motion models in the central and eastern US: Earthquake Spectra, v. 37, no. 1, p. 1354-1390, https://doi.org/10.1177/8755293021993837.","productDescription":"37 p.","startPage":"1354","endPage":"1390","ipdsId":"IP-123714","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":486985,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1177/8755293021993837","text":"Publisher Index Page"},{"id":388801,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"37","issue":"1","noUsgsAuthors":false,"publicationDate":"2021-03-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Rezaeian, Sanaz 0000-0001-7589-7893 srezaeian@usgs.gov","orcid":"https://orcid.org/0000-0001-7589-7893","contributorId":4395,"corporation":false,"usgs":true,"family":"Rezaeian","given":"Sanaz","email":"srezaeian@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":822387,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Powers, Peter M. 0000-0003-2124-6184 pmpowers@usgs.gov","orcid":"https://orcid.org/0000-0003-2124-6184","contributorId":176814,"corporation":false,"usgs":true,"family":"Powers","given":"Peter","email":"pmpowers@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":822388,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shumway, Allison 0000-0003-1142-7141 ashumway@usgs.gov","orcid":"https://orcid.org/0000-0003-1142-7141","contributorId":147862,"corporation":false,"usgs":true,"family":"Shumway","given":"Allison","email":"ashumway@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":822389,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Petersen, Mark D. 0000-0001-8542-3990 mpetersen@usgs.gov","orcid":"https://orcid.org/0000-0001-8542-3990","contributorId":1163,"corporation":false,"usgs":true,"family":"Petersen","given":"Mark","email":"mpetersen@usgs.gov","middleInitial":"D.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":822390,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Luco, Nico 0000-0002-5763-9847 nluco@usgs.gov","orcid":"https://orcid.org/0000-0002-5763-9847","contributorId":145730,"corporation":false,"usgs":true,"family":"Luco","given":"Nico","email":"nluco@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":822391,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Frankel, Arthur D. 0000-0001-9119-6106 afrankel@usgs.gov","orcid":"https://orcid.org/0000-0001-9119-6106","contributorId":146285,"corporation":false,"usgs":true,"family":"Frankel","given":"Arthur","email":"afrankel@usgs.gov","middleInitial":"D.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":822392,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Moschetti, Morgan P. 0000-0001-7261-0295 mmoschetti@usgs.gov","orcid":"https://orcid.org/0000-0001-7261-0295","contributorId":1662,"corporation":false,"usgs":true,"family":"Moschetti","given":"Morgan","email":"mmoschetti@usgs.gov","middleInitial":"P.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":822393,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Thompson, Eric M. 0000-0002-6943-4806 emthompson@usgs.gov","orcid":"https://orcid.org/0000-0002-6943-4806","contributorId":150897,"corporation":false,"usgs":true,"family":"Thompson","given":"Eric","email":"emthompson@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":822394,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"McNamara, Daniel 0000-0001-6860-0350","orcid":"https://orcid.org/0000-0001-6860-0350","contributorId":265165,"corporation":false,"usgs":false,"family":"McNamara","given":"Daniel","affiliations":[{"id":24583,"text":"former USGS employee","active":true,"usgs":false}],"preferred":false,"id":822395,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70219101,"text":"70219101 - 2021 - Dating fault damage along the eastern Denali fault zone with hematite (U-Th)/He thermochronometry","interactions":[],"lastModifiedDate":"2021-03-25T11:47:28.121179","indexId":"70219101","displayToPublicDate":"2021-03-19T07:19:35","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1427,"text":"Earth and Planetary Science Letters","active":true,"publicationSubtype":{"id":10}},"title":"Dating fault damage along the eastern Denali fault zone with hematite (U-Th)/He thermochronometry","docAbstract":"

Unraveling complex slip histories in fault damage zones to understand relations among deformation, hydrothermal alteration, and surface uplift remains a challenge. The dextral eastern Denali fault zone (EDFZ; southwest Yukon, Canada) bounds the Kluane Ranges and hosts a variety of fault-related rocks, including hematite fault surfaces, which have been exhumed through the brittle regime over a protracted period of geologic time. Scanning electron microscopy-based microtextural observations and hematite (U-Th)/He (hematite He) thermochronometry from these surfaces indicate multiple generations of foliated, high-aspect ratio hematite plates. Single-aliquot hematite He dates (n=38\">n=38) from 11 samples range from 11.5 ± 3.2 Ma (2σ) to 3.4 ± 2.1 Ma and exhibit moderate inter- and intrasample dispersion. A subset of dates is 15-20 Myr younger than previously published apatite (U-Th)/He dates from collocated host rocks, despite similar closure temperatures, precluding a simple ambient cooling interpretation for our hematite He data. Mixture modeling defines hematite He date populations at ∼8 Ma, ∼6 Ma, and ∼4 Ma, and when combined with microtextural observations, supports episodes of hydrothermal alteration and fault reactivation at aseismic to subseismic slip rates. There is no evidence that hematite experienced deformation- or hydrothermal fluid-related He loss. Hematite He dates overlap previously documented Kluane Ranges surface uplift and shifting dynamics of the Yakutat microplate, pinpointing fault networks and deformation processes that accommodate regional deformation in response to far-field plate boundary processes.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.epsl.2021.116872","usgsCitation":"McDermott, R.G., Ault, A.K., and Caine, J., 2021, Dating fault damage along the eastern Denali fault zone with hematite (U-Th)/He thermochronometry: Earth and Planetary Science Letters, v. 563, 116872, 11 p., https://doi.org/10.1016/j.epsl.2021.116872.","productDescription":"116872, 11 p.","ipdsId":"IP-122292","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":453016,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.epsl.2021.116872","text":"Publisher Index Page"},{"id":384629,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Denali fault zone","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -150.732421875,\n 59.31076795603884\n ],\n [\n -141.416015625,\n 59.31076795603884\n ],\n [\n -141.416015625,\n 62.02152819100765\n ],\n [\n -150.732421875,\n 62.02152819100765\n ],\n [\n -150.732421875,\n 59.31076795603884\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"563","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"McDermott, Robert G. 0000-0002-2550-0322","orcid":"https://orcid.org/0000-0002-2550-0322","contributorId":218595,"corporation":false,"usgs":false,"family":"McDermott","given":"Robert","email":"","middleInitial":"G.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":812787,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ault, Alexis K. 0000-0001-6361-3179","orcid":"https://orcid.org/0000-0001-6361-3179","contributorId":218596,"corporation":false,"usgs":false,"family":"Ault","given":"Alexis","email":"","middleInitial":"K.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":812788,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Caine, Jonathan Saul 0000-0002-7269-6989 jscaine@usgs.gov","orcid":"https://orcid.org/0000-0002-7269-6989","contributorId":199295,"corporation":false,"usgs":true,"family":"Caine","given":"Jonathan Saul","email":"jscaine@usgs.gov","affiliations":[],"preferred":true,"id":812789,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70222613,"text":"70222613 - 2021 - A numerical study of wave-driven mean flows and setup dynamics at a coral reef-lagoon system","interactions":[],"lastModifiedDate":"2021-08-09T13:25:19.177377","indexId":"70222613","displayToPublicDate":"2021-03-18T08:22:36","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9137,"text":"Journal of Geophysical Research-Oceans","active":true,"publicationSubtype":{"id":10}},"title":"A numerical study of wave-driven mean flows and setup dynamics at a coral reef-lagoon system","docAbstract":"

Two-dimensional mean wave-driven flow and setup dynamics were investigated at a reef-lagoon system at Ningaloo Reef, Western Australia, using the numerical wave-flow model, SWASH. Phase-resolved numerical simulations of the wave and flow fields, validated with highly detailed field observations (including >10 sensors through the energetic surf zone), were used to quantify the main mechanisms that govern the mean momentum balances and resulting mean current and setup patterns, with particular attention to the role of nonlinear wave shapes. Momentum balances from the phase-resolved model indicated that onshore flows near the reef crest were primarily driven by the wave force (dominated by radiation stress gradients) due to intense breaking, whereas the flow over the reef flat and inside the lagoon and channels was primarily driven by a pressure gradient. Wave setup inside the lagoon was primarily controlled by the wave force and bottom stress. The bottom stress reduced the setup on the reef flat and inside the lagoon. Excluding the bottom stress contribution in the setup balance resulted in an over prediction of the wave-setup inside the lagoon by up to 200–370%. The bottom stress was found to be caused by the combined presence of onshore directed wave-driven currents and (nonlinear) waves. Exclusion of the bottom stress contribution from nonlinear wave shapes led to an over prediction of the setup inside the lagoon by approximately 20–40%. The inclusion of the nonlinear wave shape contribution to the bottom stress term was found to be particularly relevant in reef regions that experience a net onshore mass flux over the reef crest.

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020JC016811","usgsCitation":"Rijnsdorp, D.P., Buckley, M.L., da Silva, R., Cuttler, M., Hansen, J., Lowe, R., Green, R.H., and Storlazzi, C.D., 2021, A numerical study of wave-driven mean flows and setup dynamics at a coral reef-lagoon system: Journal of Geophysical Research-Oceans, v. 126, no. 4, e2020JC016811, 22 p., https://doi.org/10.1029/2020JC016811.","productDescription":"e2020JC016811, 22 p.","ipdsId":"IP-122175","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":453029,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2020jc016811","text":"Publisher Index Page"},{"id":387775,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"126","issue":"4","noUsgsAuthors":false,"publicationDate":"2021-04-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Rijnsdorp, Dirk P.","contributorId":261463,"corporation":false,"usgs":false,"family":"Rijnsdorp","given":"Dirk","email":"","middleInitial":"P.","affiliations":[{"id":17614,"text":"Delft University of Technology","active":true,"usgs":false}],"preferred":false,"id":820750,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":820751,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"da Silva, Renan","contributorId":243607,"corporation":false,"usgs":false,"family":"da Silva","given":"Renan","affiliations":[{"id":48753,"text":"Deltares and UWA","active":true,"usgs":false}],"preferred":false,"id":820752,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cuttler, Mike","contributorId":261910,"corporation":false,"usgs":false,"family":"Cuttler","given":"Mike","email":"","affiliations":[{"id":53078,"text":"UWA","active":true,"usgs":false}],"preferred":false,"id":820753,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hansen, Jeff","contributorId":149139,"corporation":false,"usgs":false,"family":"Hansen","given":"Jeff","affiliations":[],"preferred":false,"id":820754,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lowe, Ryan","contributorId":177845,"corporation":false,"usgs":false,"family":"Lowe","given":"Ryan","affiliations":[],"preferred":false,"id":820755,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Green, Rebecca H.","contributorId":208503,"corporation":false,"usgs":false,"family":"Green","given":"Rebecca","email":"","middleInitial":"H.","affiliations":[{"id":24588,"text":"The University of Western Australia","active":true,"usgs":false}],"preferred":false,"id":820756,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"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":820757,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70241892,"text":"70241892 - 2021 - A comparison between generalized least squares regression and top-kriging for homogeneous cross-correlated flood regions","interactions":[],"lastModifiedDate":"2023-03-30T12:08:50.610487","indexId":"70241892","displayToPublicDate":"2021-03-18T07:06:08","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1927,"text":"Hydrological Sciences Journal","active":true,"publicationSubtype":{"id":10}},"title":"A comparison between generalized least squares regression and top-kriging for homogeneous cross-correlated flood regions","docAbstract":"

Spatial cross-correlation among flood sequences impacts the accuracy of regional predictors. Our study investigates this impact for two regionalization procedures, generalized least squares (GLS) regression and top-kriging (TK), which deal with cross-correlation in two fundamentally different ways and therefore might be associated with different accuracy and uncertainty of predicted flood quantiles. We perform a Monte Carlo experiment based on a dataset of annual maximum flood series for 20 catchments in a hydrologically homogeneous region. Based on a log-Pearson type III parent distribution, we generate 3000 realizations of the region with different degrees of cross-correlation. For each realization, GLS and TK are applied in leave-one-out cross-validation to predict at-site flood quantiles. Our study shows that (a) TK outperforms GLS when catchment area is the only catchment descriptor used for predicting “true” population (theoretical) flood quantiles, regardless of the level of cross-correlation, and (b) GLS and TK perform similarly when multiple catchment descriptors are used.

","language":"English","publisher":"Taylor and Francis","doi":"10.1080/02626667.2021.1879389","usgsCitation":"Simone, P., Salinas, J.L., Stedinger, J.R., Farmer, W., Lun, D., Viglione, A., Bloschl, G., and Castellarin, A., 2021, A comparison between generalized least squares regression and top-kriging for homogeneous cross-correlated flood regions: Hydrological Sciences Journal, v. 66, no. 2, p. 565-579, https://doi.org/10.1080/02626667.2021.1879389.","productDescription":"15 p.","startPage":"565","endPage":"579","ipdsId":"IP-109767","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":453039,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/02626667.2021.1879389","text":"Publisher Index Page"},{"id":414953,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"66","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-03-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Simone, Persiano 0000-0002-9857-738X","orcid":"https://orcid.org/0000-0002-9857-738X","contributorId":303797,"corporation":false,"usgs":false,"family":"Simone","given":"Persiano","email":"","affiliations":[{"id":65911,"text":"University of Bologna","active":true,"usgs":false}],"preferred":false,"id":868114,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Salinas, Jose Luis","contributorId":303798,"corporation":false,"usgs":false,"family":"Salinas","given":"Jose","email":"","middleInitial":"Luis","affiliations":[{"id":65912,"text":"Vienna University of Technology","active":true,"usgs":false}],"preferred":false,"id":868115,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stedinger, Jery Russell","contributorId":303799,"corporation":false,"usgs":false,"family":"Stedinger","given":"Jery","email":"","middleInitial":"Russell","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":868116,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Farmer, William H. 0000-0002-2865-2196","orcid":"https://orcid.org/0000-0002-2865-2196","contributorId":223181,"corporation":false,"usgs":true,"family":"Farmer","given":"William H.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":868117,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lun, David","contributorId":303800,"corporation":false,"usgs":false,"family":"Lun","given":"David","email":"","affiliations":[{"id":65912,"text":"Vienna University of Technology","active":true,"usgs":false}],"preferred":false,"id":868118,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Viglione, Alberto","contributorId":176326,"corporation":false,"usgs":false,"family":"Viglione","given":"Alberto","email":"","affiliations":[],"preferred":false,"id":868119,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bloschl, Gunter","contributorId":303801,"corporation":false,"usgs":false,"family":"Bloschl","given":"Gunter","email":"","affiliations":[{"id":65912,"text":"Vienna University of Technology","active":true,"usgs":false}],"preferred":false,"id":868120,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Castellarin, Attilio","contributorId":138747,"corporation":false,"usgs":false,"family":"Castellarin","given":"Attilio","email":"","affiliations":[{"id":12516,"text":"Dept. DICAM, Sch of CE, U of Bol, Italy","active":true,"usgs":false}],"preferred":false,"id":868121,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70219197,"text":"70219197 - 2021 - Lava effusion rate evolution and erupted volume during the 2018 Kīlauea lower East Rift Zone eruption","interactions":[],"lastModifiedDate":"2021-03-30T11:50:15.466149","indexId":"70219197","displayToPublicDate":"2021-03-18T06:44:09","publicationYear":"2021","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":"Lava effusion rate evolution and erupted volume during the 2018 Kīlauea lower East Rift Zone eruption","docAbstract":"

The 2018 eruption on the lower East Rift Zone of Kīlauea Volcano produced one of the largest and most destructive lava flows in Hawai’i during the past 200 years. Over the course of more than 3 months, twenty-four fissures erupted, and the rate of lava effusion varied by two orders of magnitude, with significant implications for evolving flow behavior and hazards. Syn-eruptive data were collected to quantify these changes in lava effusion rate, including video of flow through channels and digital elevation models acquired using small unoccupied aircraft systems, airborne lidar, and airborne single-pass interferometric synthetic aperture radar. Topographic data through time allowed calculation of subaerial lava flow volume and time-averaged discharge rate over the course of the eruption, which we integrated with pre- and post-eruption bathymetric surveys. Repeat videos of the near-vent channel were analyzed with particle velocimetry to extract flow velocities, and these were combined with open channel flow theory to calculate a time series of instantaneous effusion rates. Results show a general increase in dense rock equivalent (DRE) effusion rate from ~7 to ~100 m3/s from early to late May for the whole flow field and ≥ 200 m3/s by mid-June after the eruption had focused at a primary vent. By the end of the eruption in August, 0.9–1.4 km3 DRE of lava had erupted, with 0.4 km3 deposited on land and at least 0.5 km3 offshore. The trends in effusion rate through time reflect magmatic processes in the connected summit and rift zone system that controlled eruption rate, with resulting implications for lava flow dynamics and hazards.

","language":"English","publisher":"Springer","doi":"10.1007/s00445-021-01443-6","usgsCitation":"Dietterich, H., Diefenbach, A., Soule, S.A., Zoeller, M.H., Patrick, M.R., Major, J., and Lundgren, P., 2021, Lava effusion rate evolution and erupted volume during the 2018 Kīlauea lower East Rift Zone eruption: Bulletin of Volcanology, v. 83, no. 25, 18 p., https://doi.org/10.1007/s00445-021-01443-6.","productDescription":"18 p.","ipdsId":"IP-122554","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":488679,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://digitalcommons.uri.edu/gsofacpubs/2493","text":"External Repository"},{"id":384747,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kīlauea volcano, Hawaii volcanoes National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.0507354736328,\n 19.321511226817176\n ],\n [\n -155.25054931640625,\n 19.369454073094243\n ],\n [\n -155.35011291503906,\n 19.39082944712291\n ],\n [\n -155.4242706298828,\n 19.204186382298897\n ],\n [\n -155.39749145507812,\n 19.191217165341648\n ],\n [\n -155.12832641601562,\n 19.2748506284423\n ],\n [\n -155.0507354736328,\n 19.321511226817176\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"83","issue":"25","noUsgsAuthors":false,"publicationDate":"2021-03-18","publicationStatus":"PW","contributors":{"authors":[{"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":813189,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Diefenbach, Angela K. 0000-0003-0214-7818","orcid":"https://orcid.org/0000-0003-0214-7818","contributorId":204743,"corporation":false,"usgs":true,"family":"Diefenbach","given":"Angela K.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":813190,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Soule, S. Adam 0000-0002-4691-6300","orcid":"https://orcid.org/0000-0002-4691-6300","contributorId":221052,"corporation":false,"usgs":false,"family":"Soule","given":"S.","email":"","middleInitial":"Adam","affiliations":[{"id":36711,"text":"Woods Hole Oceanographic Institution","active":true,"usgs":false}],"preferred":false,"id":813191,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zoeller, Michael H. 0000-0003-4716-8567","orcid":"https://orcid.org/0000-0003-4716-8567","contributorId":214557,"corporation":false,"usgs":true,"family":"Zoeller","given":"Michael","email":"","middleInitial":"H.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":813192,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Patrick, Matthew R. 0000-0002-8042-6639 mpatrick@usgs.gov","orcid":"https://orcid.org/0000-0002-8042-6639","contributorId":2070,"corporation":false,"usgs":true,"family":"Patrick","given":"Matthew","email":"mpatrick@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":813193,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Major, J. J. 0000-0003-2449-4466","orcid":"https://orcid.org/0000-0003-2449-4466","contributorId":29461,"corporation":false,"usgs":true,"family":"Major","given":"J. J.","affiliations":[{"id":157,"text":"Cascades Volcano Observatory","active":false,"usgs":true}],"preferred":true,"id":813194,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lundgren, Paul 0000-0002-6771-2876","orcid":"https://orcid.org/0000-0002-6771-2876","contributorId":215622,"corporation":false,"usgs":false,"family":"Lundgren","given":"Paul","email":"","affiliations":[{"id":36276,"text":"JPL","active":true,"usgs":false}],"preferred":false,"id":813195,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70218820,"text":"sir20215005 - 2021 - Supporting data and simulation of hypothetical bighead carp egg and larvae development and transport in the Ohio River between Markland Locks and Dam and McAlpine Locks and Dam, Kentucky and Indiana, by use of the Fluvial Egg Drift Simulator","interactions":[],"lastModifiedDate":"2021-03-18T11:47:02.407154","indexId":"sir20215005","displayToPublicDate":"2021-03-17T12:49:05","publicationYear":"2021","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":"2021-5005","displayTitle":"Supporting Data and Simulation of Hypothetical Bighead Carp Egg and Larvae Development and Transport in the Ohio River between Markland Locks and Dam and McAlpine Locks and Dam, Kentucky and Indiana, by use of the Fluvial Egg Drift Simulator","title":"Supporting data and simulation of hypothetical bighead carp egg and larvae development and transport in the Ohio River between Markland Locks and Dam and McAlpine Locks and Dam, Kentucky and Indiana, by use of the Fluvial Egg Drift Simulator","docAbstract":"

Data collection, along with hydraulic and fluvial egg transport modeling, was completed along a 70.9-mile reach of the Ohio River between Markland Locks and Dam and McAlpine Locks and Dam in Kentucky and Indiana. Water-quality data collected in this reach included surface measurements and vertical profiles of water temperature, specific conductance, pH, dissolved oxygen, turbidity, relative chlorophyll, and relative phycocyanin. Data were collected during two surveys: October 27–November 4, 2016, and June 26–29, 2017. Streamflow and velocity data were collected simultaneously with the water-quality data at cross sections and along longitudinal lines (corresponding to the water-quality surface measurements) and at selected stationary locations (corresponding to the water-quality vertical profiles). The data were collected to understand variability of flow and water-quality conditions relative to simulated reaches of the Ohio River and to aid in identifying parts of the reach that may provide conditions favorable to spawning and recruitment habitat for Hypophthalmichthys nobilis (bighead carp).

A copy of an existing step-backwater model of Ohio River flows was obtained from the National Weather Service and used to simulate hydraulic conditions for four different streamflows. Streamflows were selected to represent typical conditions ranging from a high-streamflow event to a seasonal dry-weather event, with two streamflows between these extremes for this reach of the Ohio River. Outputs from the hydraulic model, a range of five water temperatures observed in water-quality data, and four potential spawning locations were used as input to the Fluvial Egg Drift Simulator to simulate the extents and quantile positions of developing bighead carp, from egg hatching to the gas bladder inflation stage, under each scenario. A total of 80 simulations were run.

Results from the Fluvial Egg Drift Simulator scenarios (which include only the hydraulic influences on survival that result from settling, irrespective of mortality from other physical or biological factors such as excess turbulence, fertilization failure, predation, or starvation) indicate that most eggs will hatch, about half will die, and a quarter of the surviving larvae will reach the gas bladder inflation stage within the model reach. The overall mean percentage of embryos surviving to the gas bladder inflation stage was 13.1 percent. Individual simulations have embryo survival percentages as high as 49.1 percent. The highest embryo survival percentages occurred for eggs spawned at a streamflow of 38,100 cubic feet per second and water temperatures of 24 to 30 degrees Celsius. Conversely, embryo survival percentages were lowest for the lowest and highest streamflows regardless of water temperature or spawn location. Under low water temperature and high-streamflow conditions, some of the eggs did not hatch nor did the larvae reach the gas bladder inflation stage until passing beyond the downstream model domain. Although the final quantile positions of the eggs and larvae beyond the downstream model domain are unknown, the outcomes still provide useful information about conditions favorable to spawning and recruitment habitat for bighead carp in the Ohio River.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215005","collaboration":"Biological Threats and Invasive Species Research Program","usgsCitation":"Ostheimer, C.J., Boldt, J.A., and Buszka, P.M., 2021, Supporting data and simulation of hypothetical bighead carp egg and larvae development and transport in the Ohio River between Markland Locks and Dam and McAlpine Locks and Dam, Kentucky and Indiana, by use of the Fluvial Egg Drift Simulator: U.S. Geological Survey Scientific Investigations Report 2021–5005, 30 p., https://doi.org/10.3133/sir20215005.","productDescription":"Report: v, 30 p.; 2 Data Releases","numberOfPages":"38","onlineOnly":"Y","ipdsId":"IP-116266","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":384390,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5005/coverthb.jpg"},{"id":384391,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5005/sir20215005.pdf","text":"Report","size":"10.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5005"},{"id":384392,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9MQHEPU","text":"USGS data release","linkHelpText":"Velocity and water-quality surveys in the Ohio River between Markland Locks and Dam and McAlpine Locks and Dam, Kentucky and Indiana, October 27–November 4, 2016, and June 26–29, 2017"},{"id":384393,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9JHLGZL","text":"USGS data release","linkHelpText":"Geospatial data and models for the simulation of hypothetical bighead carp egg and larvae development and transport in the Ohio River between Markland Locks and Dam and McAlpine Locks and Dam, Kentucky and Indiana, by use of the Fluvial Egg Drift Simulator"}],"country":"United States","state":"Indiana, Kentucky","otherGeospatial":"Ohio River, Markland Locks and Dam, McAlpine Locks and Dam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -85.660400390625,\n 38.40194908237822\n ],\n [\n -84.935302734375,\n 38.40194908237822\n ],\n [\n -84.935302734375,\n 38.85682013474361\n ],\n [\n -85.660400390625,\n 38.85682013474361\n ],\n [\n -85.660400390625,\n 38.40194908237822\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Ohio-Kentucky-Indiana Water Science Center
U.S. Geological Survey
6460 Busch Blvd., Suite 100
Columbus, OH 43229–1737

","tableOfContents":"","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"publishedDate":"2021-03-17","noUsgsAuthors":false,"publicationDate":"2021-03-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Ostheimer, Chad J. 0000-0002-4528-8867","orcid":"https://orcid.org/0000-0002-4528-8867","contributorId":213950,"corporation":false,"usgs":true,"family":"Ostheimer","given":"Chad","email":"","middleInitial":"J.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":812274,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boldt, Justin A. 0000-0002-0771-3658","orcid":"https://orcid.org/0000-0002-0771-3658","contributorId":207849,"corporation":false,"usgs":true,"family":"Boldt","given":"Justin","email":"","middleInitial":"A.","affiliations":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true},{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true}],"preferred":true,"id":812275,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buszka, Paul M. 0000-0001-8218-826X pmbuszka@usgs.gov","orcid":"https://orcid.org/0000-0001-8218-826X","contributorId":1786,"corporation":false,"usgs":true,"family":"Buszka","given":"Paul","email":"pmbuszka@usgs.gov","middleInitial":"M.","affiliations":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true},{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true}],"preferred":true,"id":812276,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70219045,"text":"70219045 - 2021 - Machine learning models of arsenic in private wells throughout the conterminous United States as a tool for exposure assessment in human health studies","interactions":[],"lastModifiedDate":"2021-04-22T18:25:04.371556","indexId":"70219045","displayToPublicDate":"2021-03-17T08:29:53","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5925,"text":"Environmental Science and Technology","active":true,"publicationSubtype":{"id":10}},"title":"Machine learning models of arsenic in private wells throughout the conterminous United States as a tool for exposure assessment in human health studies","docAbstract":"

Arsenic from geologic sources is widespread in groundwater within the United States (U.S.). In several areas, groundwater arsenic concentrations exceed the U.S. Environmental Protection Agency maximum contaminant level of 10 μg per liter (μg/L). However, this standard applies only to public-supply drinking water and not to private-supply, which is not federally regulated and is rarely monitored. As a result, arsenic exposure from private wells is a potentially substantial, but largely hidden, public health concern. Machine learning models using boosted regression trees (BRT) and random forest classification (RFC) techniques were developed to estimate probabilities and concentration ranges of arsenic in private wells throughout the conterminous U.S. Three BRT models were fit separately to estimate the probability of private well arsenic concentrations exceeding 1, 5, or 10 μg/L whereas the RFC model estimates the most probable category (≤5, >5 to ≤10, or >10 μg/L). Overall, the models perform best at identifying areas with low concentrations of arsenic in private wells. The BRT 10 μg/L model estimates for testing data have an overall accuracy of 91.2%, sensitivity of 33.9%, and specificity of 98.2%. Influential variables identified across all models included average annual precipitation and soil geochemistry. Models were developed in collaboration with public health experts to support U.S.-based studies focused on health effects from arsenic exposure.

","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.0c05239","usgsCitation":"Lombard, M.A., Scannell Bryan, M., Jones, D.K., Bulka, C., Bradley, P., Backer, L.C., Focazio, M.J., Silverman, D.T., Toccalino, P., Argos, M., Gribble, M.O., and Ayotte, J.D., 2021, Machine learning models of arsenic in private wells throughout the conterminous United States as a tool for exposure assessment in human health studies: Environmental Science and Technology, v. 55, no. 8, p. 5012-5023, https://doi.org/10.1021/acs.est.0c05239.","productDescription":"12 p.","startPage":"5012","endPage":"5023","ipdsId":"IP-115591","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":38131,"text":"WMA - Office of Planning and Programming","active":true,"usgs":true}],"links":[{"id":453049,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1021/acs.est.0c05239","text":"Publisher Index Page"},{"id":436455,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P90RBJXS","text":"USGS data release","linkHelpText":"Data used to model and map arsenic concentration exceedances in private wells throughout the conterminous United States for human health studies"},{"id":384539,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"geometry\": {\n \"type\": \"MultiPolygon\",\n \"coordinates\": [\n [\n [\n [\n -94.81758,\n 49.38905\n ],\n [\n -94.64,\n 48.84\n ],\n [\n -94.32914,\n 48.67074\n ],\n [\n -93.63087,\n 48.60926\n ],\n [\n -92.61,\n 48.45\n ],\n [\n -91.64,\n 48.14\n ],\n [\n -90.83,\n 48.27\n ],\n [\n -89.6,\n 48.01\n ],\n [\n -89.27292,\n 48.01981\n ],\n [\n -88.37811,\n 48.30292\n ],\n [\n -87.43979,\n 47.94\n ],\n [\n -86.46199,\n 47.55334\n ],\n [\n -85.65236,\n 47.22022\n ],\n [\n -84.87608,\n 46.90008\n ],\n [\n -84.77924,\n 46.6371\n ],\n [\n -84.54375,\n 46.53868\n ],\n [\n -84.6049,\n 46.4396\n ],\n [\n -84.3367,\n 46.40877\n ],\n [\n -84.14212,\n 46.51223\n ],\n [\n -84.09185,\n 46.27542\n ],\n [\n -83.89077,\n 46.11693\n ],\n [\n -83.61613,\n 46.11693\n ],\n [\n -83.46955,\n 45.99469\n ],\n [\n -83.59285,\n 45.81689\n ],\n [\n -82.55092,\n 45.34752\n ],\n [\n -82.33776,\n 44.44\n ],\n [\n -82.13764,\n 43.57109\n ],\n [\n -82.43,\n 42.98\n ],\n [\n -82.9,\n 42.43\n ],\n [\n -83.12,\n 42.08\n ],\n [\n -83.142,\n 41.97568\n ],\n [\n -83.02981,\n 41.8328\n ],\n [\n -82.69009,\n 41.67511\n ],\n [\n -82.43928,\n 41.67511\n ],\n [\n -81.27775,\n 42.20903\n ],\n [\n -80.24745,\n 42.3662\n ],\n [\n -78.93936,\n 42.86361\n ],\n [\n -78.92,\n 42.965\n ],\n [\n -79.01,\n 43.27\n ],\n [\n -79.17167,\n 43.46634\n ],\n [\n -78.72028,\n 43.62509\n ],\n [\n -77.73789,\n 43.62906\n ],\n [\n -76.82003,\n 43.62878\n ],\n [\n -76.5,\n 44.01846\n ],\n [\n -76.375,\n 44.09631\n ],\n [\n -75.31821,\n 44.81645\n ],\n [\n -74.867,\n 45.00048\n ],\n [\n -73.34783,\n 45.00738\n ],\n [\n -71.50506,\n 45.0082\n ],\n [\n -71.405,\n 45.255\n ],\n [\n -71.08482,\n 45.30524\n ],\n [\n -70.66,\n 45.46\n ],\n [\n -70.305,\n 45.915\n ],\n [\n -69.99997,\n 46.69307\n ],\n [\n -69.23722,\n 47.44778\n ],\n [\n -68.905,\n 47.185\n ],\n [\n -68.23444,\n 47.35486\n ],\n [\n -67.79046,\n 47.06636\n ],\n [\n -67.79134,\n 45.70281\n ],\n [\n -67.13741,\n 45.13753\n ],\n [\n -66.96466,\n 44.8097\n ],\n [\n -68.03252,\n 44.3252\n ],\n [\n -69.06,\n 43.98\n ],\n [\n -70.11617,\n 43.68405\n ],\n [\n -70.64548,\n 43.09024\n ],\n [\n -70.81489,\n 42.8653\n ],\n [\n -70.825,\n 42.335\n ],\n [\n -70.495,\n 41.805\n ],\n [\n -70.08,\n 41.78\n ],\n [\n -70.185,\n 42.145\n ],\n [\n -69.88497,\n 41.92283\n ],\n [\n -69.96503,\n 41.63717\n ],\n [\n -70.64,\n 41.475\n ],\n [\n -71.12039,\n 41.49445\n ],\n [\n -71.86,\n 41.32\n ],\n [\n -72.295,\n 41.27\n ],\n [\n -72.87643,\n 41.22065\n ],\n [\n -73.71,\n 40.9311\n ],\n [\n -72.24126,\n 41.11948\n ],\n [\n -71.945,\n 40.93\n ],\n [\n -73.345,\n 40.63\n ],\n [\n -73.982,\n 40.628\n ],\n [\n -73.95232,\n 40.75075\n ],\n [\n -74.25671,\n 40.47351\n ],\n [\n -73.96244,\n 40.42763\n ],\n [\n -74.17838,\n 39.70926\n ],\n [\n -74.90604,\n 38.93954\n ],\n [\n -74.98041,\n 39.1964\n ],\n [\n -75.20002,\n 39.24845\n ],\n [\n -75.52805,\n 39.4985\n ],\n [\n -75.32,\n 38.96\n ],\n [\n -75.07183,\n 38.78203\n ],\n [\n -75.05673,\n 38.40412\n ],\n [\n -75.37747,\n 38.01551\n ],\n [\n -75.94023,\n 37.21689\n ],\n [\n -76.03127,\n 37.2566\n ],\n [\n -75.72205,\n 37.93705\n ],\n [\n -76.23287,\n 38.31921\n ],\n [\n -76.35,\n 39.15\n ],\n [\n -76.54272,\n 38.71762\n ],\n [\n -76.32933,\n 38.08326\n ],\n [\n -76.99,\n 38.23999\n ],\n [\n -76.30162,\n 37.91794\n ],\n [\n -76.25874,\n 36.9664\n ],\n [\n -75.9718,\n 36.89726\n ],\n [\n -75.86804,\n 36.55125\n ],\n [\n -75.72749,\n 35.55074\n ],\n [\n -76.36318,\n 34.80854\n ],\n [\n -77.39763,\n 34.51201\n ],\n [\n -78.05496,\n 33.92547\n ],\n [\n -78.55435,\n 33.86133\n ],\n [\n -79.06067,\n 33.49395\n ],\n [\n -79.20357,\n 33.15839\n ],\n [\n -80.30132,\n 32.50935\n ],\n [\n -80.86498,\n 32.0333\n ],\n [\n -81.33629,\n 31.44049\n ],\n [\n -81.49042,\n 30.72999\n ],\n [\n -81.31371,\n 30.03552\n ],\n [\n -80.98,\n 29.18\n ],\n [\n -80.53558,\n 28.47213\n ],\n [\n -80.53,\n 28.04\n ],\n [\n -80.05654,\n 26.88\n ],\n [\n -80.08801,\n 26.20576\n ],\n [\n -80.13156,\n 25.81677\n ],\n [\n -80.38103,\n 25.20616\n ],\n [\n -80.68,\n 25.08\n ],\n [\n -81.17213,\n 25.20126\n ],\n [\n -81.33,\n 25.64\n ],\n [\n -81.71,\n 25.87\n ],\n [\n -82.24,\n 26.73\n ],\n [\n -82.70515,\n 27.49504\n ],\n [\n -82.85526,\n 27.88624\n ],\n [\n -82.65,\n 28.55\n ],\n [\n -82.93,\n 29.1\n ],\n [\n -83.70959,\n 29.93656\n ],\n [\n -84.1,\n 30.09\n ],\n [\n -85.10882,\n 29.63615\n ],\n [\n -85.28784,\n 29.68612\n ],\n [\n -85.7731,\n 30.15261\n ],\n [\n -86.4,\n 30.4\n ],\n [\n -87.53036,\n 30.27433\n ],\n [\n -88.41782,\n 30.3849\n ],\n [\n -89.18049,\n 30.31598\n ],\n [\n -89.59383,\n 30.15999\n ],\n [\n -89.41373,\n 29.89419\n ],\n [\n -89.43,\n 29.48864\n ],\n [\n -89.21767,\n 29.29108\n ],\n [\n -89.40823,\n 29.15961\n ],\n [\n -89.77928,\n 29.30714\n ],\n [\n -90.15463,\n 29.11743\n ],\n [\n -90.88022,\n 29.14854\n ],\n [\n -91.62678,\n 29.677\n ],\n [\n -92.49906,\n 29.5523\n ],\n [\n -93.22637,\n 29.78375\n ],\n [\n -93.84842,\n 29.71363\n ],\n [\n -94.69,\n 29.48\n ],\n [\n -95.60026,\n 28.73863\n ],\n [\n -96.59404,\n 28.30748\n ],\n [\n -97.14,\n 27.83\n ],\n [\n -97.37,\n 27.38\n ],\n [\n -97.38,\n 26.69\n ],\n [\n -97.33,\n 26.21\n ],\n [\n -97.14,\n 25.87\n ],\n [\n -97.53,\n 25.84\n ],\n [\n -98.24,\n 26.06\n ],\n [\n -99.02,\n 26.37\n ],\n [\n -99.3,\n 26.84\n ],\n [\n -99.52,\n 27.54\n ],\n [\n -100.11,\n 28.11\n ],\n [\n -100.45584,\n 28.69612\n ],\n [\n -100.9576,\n 29.38071\n ],\n [\n -101.6624,\n 29.7793\n ],\n [\n -102.48,\n 29.76\n ],\n [\n -103.11,\n 28.97\n ],\n [\n -103.94,\n 29.27\n ],\n [\n -104.45697,\n 29.57196\n ],\n [\n -104.70575,\n 30.12173\n ],\n [\n -105.03737,\n 30.64402\n ],\n [\n -105.63159,\n 31.08383\n ],\n [\n -106.1429,\n 31.39995\n ],\n [\n -106.50759,\n 31.75452\n ],\n [\n -108.24,\n 31.75485\n ],\n [\n -108.24194,\n 31.34222\n ],\n [\n -109.035,\n 31.34194\n ],\n [\n -111.02361,\n 31.33472\n ],\n [\n -113.30498,\n 32.03914\n ],\n [\n -114.815,\n 32.52528\n ],\n [\n -114.72139,\n 32.72083\n ],\n [\n -115.99135,\n 32.61239\n ],\n [\n -117.12776,\n 32.53534\n ],\n [\n -117.29594,\n 33.04622\n ],\n [\n -117.944,\n 33.62124\n ],\n [\n -118.4106,\n 33.74091\n ],\n [\n -118.51989,\n 34.02778\n ],\n [\n -119.081,\n 34.078\n ],\n [\n -119.43884,\n 34.34848\n ],\n [\n -120.36778,\n 34.44711\n ],\n [\n -120.62286,\n 34.60855\n ],\n [\n -120.74433,\n 35.15686\n ],\n [\n -121.71457,\n 36.16153\n ],\n [\n -122.54747,\n 37.55176\n ],\n [\n -122.51201,\n 37.78339\n ],\n [\n -122.95319,\n 38.11371\n ],\n [\n -123.7272,\n 38.95166\n ],\n [\n -123.86517,\n 39.76699\n ],\n [\n -124.39807,\n 40.3132\n ],\n [\n -124.17886,\n 41.14202\n ],\n [\n -124.2137,\n 41.99964\n ],\n [\n -124.53284,\n 42.76599\n ],\n [\n -124.14214,\n 43.70838\n ],\n [\n -124.02053,\n 44.6159\n ],\n [\n -123.89893,\n 45.52341\n ],\n [\n -124.07963,\n 46.86475\n ],\n [\n -124.39567,\n 47.72017\n ],\n [\n -124.68721,\n 48.18443\n ],\n [\n -124.5661,\n 48.37971\n ],\n [\n -123.12,\n 48.04\n ],\n [\n -122.58736,\n 47.096\n ],\n [\n -122.34,\n 47.36\n ],\n [\n -122.5,\n 48.18\n ],\n [\n -122.84,\n 49\n ],\n [\n -120,\n 49\n ],\n [\n -117.03121,\n 49\n ],\n [\n -116.04818,\n 49\n ],\n [\n -113,\n 49\n ],\n [\n -110.05,\n 49\n ],\n [\n -107.05,\n 49\n ],\n [\n -104.04826,\n 48.99986\n ],\n [\n -100.65,\n 49\n ],\n [\n -97.22872,\n 49.0007\n ],\n [\n -95.15907,\n 49\n ],\n [\n -95.15609,\n 49.38425\n ],\n [\n -94.81758,\n 49.38905\n ]\n ]\n ]\n ]\n },\n \"properties\": {\n \"name\": \"United States\"\n }\n }\n ]\n}","volume":"55","issue":"8","noUsgsAuthors":false,"publicationDate":"2021-03-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Lombard, Melissa A. 0000-0001-5924-6556 mlombard@usgs.gov","orcid":"https://orcid.org/0000-0001-5924-6556","contributorId":198254,"corporation":false,"usgs":true,"family":"Lombard","given":"Melissa","email":"mlombard@usgs.gov","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":812542,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Scannell Bryan, Molly","contributorId":255545,"corporation":false,"usgs":false,"family":"Scannell Bryan","given":"Molly","email":"","affiliations":[{"id":18137,"text":"University of Illinois at Chicago","active":true,"usgs":false}],"preferred":false,"id":812543,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jones, Daniel K. 0000-0003-0724-8001 dkjones@usgs.gov","orcid":"https://orcid.org/0000-0003-0724-8001","contributorId":4959,"corporation":false,"usgs":true,"family":"Jones","given":"Daniel","email":"dkjones@usgs.gov","middleInitial":"K.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":812544,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bulka, Catherine","contributorId":255546,"corporation":false,"usgs":false,"family":"Bulka","given":"Catherine","email":"","affiliations":[{"id":7043,"text":"University of North Carolina","active":true,"usgs":false}],"preferred":false,"id":812545,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bradley, Paul M. 0000-0001-7522-8606","orcid":"https://orcid.org/0000-0001-7522-8606","contributorId":221226,"corporation":false,"usgs":true,"family":"Bradley","given":"Paul M.","affiliations":[{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":812546,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Backer, Lorraine C.","contributorId":198459,"corporation":false,"usgs":false,"family":"Backer","given":"Lorraine","email":"","middleInitial":"C.","affiliations":[{"id":16974,"text":"US Centers for Disease Control and Prevention (CDC)","active":true,"usgs":false}],"preferred":true,"id":812547,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Focazio, Michael J. 0000-0003-0967-5576 mfocazio@usgs.gov","orcid":"https://orcid.org/0000-0003-0967-5576","contributorId":1276,"corporation":false,"usgs":true,"family":"Focazio","given":"Michael","email":"mfocazio@usgs.gov","middleInitial":"J.","affiliations":[{"id":5056,"text":"Office of the AD Energy and Minerals, and Environmental Health","active":true,"usgs":true},{"id":38175,"text":"Toxics Substances Hydrology Program","active":true,"usgs":true}],"preferred":true,"id":812548,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Silverman, Debra T.","contributorId":255547,"corporation":false,"usgs":false,"family":"Silverman","given":"Debra","email":"","middleInitial":"T.","affiliations":[{"id":29855,"text":"National Cancer Institute","active":true,"usgs":false}],"preferred":false,"id":812549,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Toccalino, Patricia 0000-0003-1066-1702","orcid":"https://orcid.org/0000-0003-1066-1702","contributorId":213727,"corporation":false,"usgs":true,"family":"Toccalino","given":"Patricia","email":"","affiliations":[{"id":38131,"text":"WMA - Office of Planning and Programming","active":true,"usgs":true}],"preferred":true,"id":812550,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Argos, Maria 0000-0003-4234-252X","orcid":"https://orcid.org/0000-0003-4234-252X","contributorId":204352,"corporation":false,"usgs":false,"family":"Argos","given":"Maria","email":"","affiliations":[{"id":18125,"text":"University of Illinois, Chicago","active":true,"usgs":false}],"preferred":false,"id":812551,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Gribble, Matthew O.","contributorId":255548,"corporation":false,"usgs":false,"family":"Gribble","given":"Matthew","email":"","middleInitial":"O.","affiliations":[{"id":40432,"text":"Emory University","active":true,"usgs":false}],"preferred":false,"id":812552,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Ayotte, Joseph D. 0000-0002-1892-2738 jayotte@usgs.gov","orcid":"https://orcid.org/0000-0002-1892-2738","contributorId":149619,"corporation":false,"usgs":true,"family":"Ayotte","given":"Joseph","email":"jayotte@usgs.gov","middleInitial":"D.","affiliations":[{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":812553,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70219163,"text":"70219163 - 2021 - Quantifying thresholds of barrier geomorphic change in a cross-shore sediment-partitioning model","interactions":[],"lastModifiedDate":"2021-03-29T13:27:54.953637","indexId":"70219163","displayToPublicDate":"2021-03-17T08:24:58","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7942,"text":"Earth Surface Dynamics","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying thresholds of barrier geomorphic change in a cross-shore sediment-partitioning model","docAbstract":"

Barrier coasts, including barrier islands, beach-ridge plains, and associated landforms, can assume a broad spectrum of morphologies over multi-decadal scales that reflect conditions of sediment availability, accommodation, and relative sea-level rise. However, the quantitative thresholds of these controls on barrier-system behavior remain largely unexplored, even as modern sea-level rise and anthropogenic modification of sediment availability increasingly reshape the world's sandy coastlines. In this study, we conceptualize barrier coasts as sediment-partitioning frameworks, distributing sand delivered from the shoreface to the subaqueous and subaerial components of the coastal system. Using an idealized morphodynamic model, we explore thresholds of behavioral and morphologic change over decadal to centennial timescales, simulating barrier evolution within quasi-stratigraphic morphological cross sections. Our results indicate a wide diversity of barrier behaviors can be explained by the balance of fluxes delivered to the beach vs. the dune or backbarrier, including previously understudied forms of transgression that allow the subaerial system to continue accumulating sediment during landward migration. Most importantly, our results show that barrier state transitions between progradation, cross-shore amalgamation, aggradation, and transgression are controlled largely through balances within a narrow range of relative sea-level rise and sediment flux. This suggests that, in the face of rising sea levels, subtle changes in sediment fluxes could result in significant changes in barrier morphology. We also demonstrate that modeled barriers with reduced vertical sediment accommodation are highly sensitive to the magnitude and direction of shoreface fluxes. Therefore, natural barriers with limited sediment accommodation could allow for exploration of the future effects of sea-level rise and changing flux magnitudes over a period of years as opposed to the decades required for similar responses in sediment-rich barrier systems. Finally, because our model creates stratigraphy generated under different input parameters, we propose that it could be used in combination with stratigraphic data to hindcast the sensitivity of existing barriers and infer changes in prehistoric morphology, which we anticipate will provide a baseline to assess the reliability of forward modeling predictions.

","language":"English","publisher":"Copernicus Publications","doi":"10.5194/esurf-9-183-2021","usgsCitation":"Ciarletta, D.J., Miselis, J.L., Shawler, J.L., and Hein, C.J., 2021, Quantifying thresholds of barrier geomorphic change in a cross-shore sediment-partitioning model: Earth Surface Dynamics, v. 9, p. 183-203, https://doi.org/10.5194/esurf-9-183-2021.","productDescription":"21 p.","startPage":"183","endPage":"203","ipdsId":"IP-122455","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":453052,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/esurf-9-183-2021","text":"Publisher Index Page"},{"id":436457,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9O3D29V","text":"USGS data release","linkHelpText":"Python-based Subaerial Barrier Sediment Partitioning (pySBSP) model (ver. 1.0, February 2024)"},{"id":436456,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9DE6QCL","text":"USGS data release","linkHelpText":"Subaerial Barrier Sediment Partitioning (SBSP) Model Version 1.0"},{"id":384718,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","noUsgsAuthors":false,"publicationDate":"2021-03-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Ciarletta, Daniel J. 0000-0002-8555-2239","orcid":"https://orcid.org/0000-0002-8555-2239","contributorId":256700,"corporation":false,"usgs":true,"family":"Ciarletta","given":"Daniel","email":"","middleInitial":"J.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":813078,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miselis, Jennifer L. 0000-0002-4925-3979 jmiselis@usgs.gov","orcid":"https://orcid.org/0000-0002-4925-3979","contributorId":3914,"corporation":false,"usgs":true,"family":"Miselis","given":"Jennifer","email":"jmiselis@usgs.gov","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":813079,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shawler, Justin L.","contributorId":256701,"corporation":false,"usgs":false,"family":"Shawler","given":"Justin","email":"","middleInitial":"L.","affiliations":[{"id":6708,"text":"Virginia Institute of Marine Science","active":true,"usgs":false}],"preferred":false,"id":813080,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hein, Christopher J.","contributorId":256702,"corporation":false,"usgs":false,"family":"Hein","given":"Christopher","email":"","middleInitial":"J.","affiliations":[{"id":6708,"text":"Virginia Institute of Marine Science","active":true,"usgs":false}],"preferred":false,"id":813081,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70221345,"text":"70221345 - 2021 - Towards improved environmental modeling outcomes: Enabling low-cost access to high-dimensional, geostatistical-based decision-support analyses","interactions":[],"lastModifiedDate":"2021-06-11T12:10:19.688015","indexId":"70221345","displayToPublicDate":"2021-03-17T07:06:27","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7164,"text":"Environmental Modelling & Software","active":true,"publicationSubtype":{"id":10}},"title":"Towards improved environmental modeling outcomes: Enabling low-cost access to high-dimensional, geostatistical-based decision-support analyses","docAbstract":"

Computer models of environmental systems routinely inform decision making for water resource management. In this context, quantifying uncertainty in the important simulated outputs, and reducing uncertainty through assimilating historic system-state observations, is as important as the numerical model. However, implementing high-dimensional and stochastic workflows are challenging, often requiring that practitioners have theoretical and practical understanding of several advanced topics. Worse, implementing these important analyses can take substantial time and effort. This additional effort is often cited as justification for postponing, or even forgoing, these analyses.

Herein, we present scripting tools to facilitate the efficient and repeatable construction of high-dimensional, geostatistical-based PEST interfaces, including uncertainty analyses. As demonstrated, these tools can be applied with minimal effort to a model with varied temporal and spatial discretization. Ultimately, these tools can enable low-cost access to valuable decision-support analyses earlier and more frequently during the modeling workflow.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2021.105022","usgsCitation":"White, J., Hemmings, B., Fienen, M., and Knowling, M., 2021, Towards improved environmental modeling outcomes: Enabling low-cost access to high-dimensional, geostatistical-based decision-support analyses: Environmental Modelling & Software, v. 139, 105022, 9 p., https://doi.org/10.1016/j.envsoft.2021.105022.","productDescription":"105022, 9 p.","ipdsId":"IP-127193","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":386411,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"139","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"White, Jeremy","contributorId":260166,"corporation":false,"usgs":false,"family":"White","given":"Jeremy","affiliations":[{"id":52529,"text":"Interra","active":true,"usgs":false}],"preferred":false,"id":817388,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hemmings, Brioch","contributorId":260167,"corporation":false,"usgs":false,"family":"Hemmings","given":"Brioch","email":"","affiliations":[{"id":36277,"text":"GNS Science","active":true,"usgs":false}],"preferred":false,"id":817389,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fienen, Michael N. 0000-0002-7756-4651","orcid":"https://orcid.org/0000-0002-7756-4651","contributorId":245632,"corporation":false,"usgs":true,"family":"Fienen","given":"Michael N.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":817390,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Knowling, Matthew","contributorId":260168,"corporation":false,"usgs":false,"family":"Knowling","given":"Matthew","affiliations":[{"id":36897,"text":"University of Adelaide","active":true,"usgs":false}],"preferred":false,"id":817391,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70228966,"text":"70228966 - 2021 - Filling knowledge gaps for a threatened species: Age and growth of Green Sturgeon of the southern distinct population segment","interactions":[],"lastModifiedDate":"2022-02-25T17:01:49.76587","indexId":"70228966","displayToPublicDate":"2021-03-16T10:56:27","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Filling knowledge gaps for a threatened species: Age and growth of Green Sturgeon of the southern distinct population segment","docAbstract":"

The Green Sturgeon Acipenser medirostris is an anadromous, long-lived species that is distributed along the Pacific coast of North America. Green Sturgeon is vulnerable to global change because of its sensitive life history (e.g., delayed maturation) and few spawning locations. The persistence of Green Sturgeon is threatened by habitat modification, altered flows, and rising river temperatures. In 2006, because of persistent stressors, the U.S. Endangered Species Act listed the southern distinct population segment as threatened. Despite increased research efforts on this species after the listing, substantial gaps in basic population information for Green Sturgeon remain. We present the only published information on age structure and growth of a threatened population of Green Sturgeon. By analyzing archived fin rays collected from 1984 to 2016, we revealed highly variable growth among individuals. We detected several age classes from 0 to 26 y and found similar growth rates of southern distinct population segment Green Sturgeon compared with northern population Green Sturgeon. Although limited, this analysis is an important first step to understanding Green Sturgeon population dynamics and highlights critical research needs.

","language":"English","publisher":"U.S. Fish and Wildlife Service","doi":"10.3996/JFWM-20-073","usgsCitation":"Ulaski, M., and Quist, M.C., 2021, Filling knowledge gaps for a threatened species: Age and growth of Green Sturgeon of the southern distinct population segment: Journal of Fish and Wildlife Management, v. 12, no. 1, p. 234-240, https://doi.org/10.3996/JFWM-20-073.","productDescription":"7 p.","startPage":"234","endPage":"240","ipdsId":"IP-123529","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":453064,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/jfwm-20-073","text":"Publisher Index Page"},{"id":396498,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Oregon, Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -126.826171875,\n 33.063924198120645\n ],\n [\n -115.48828125000001,\n 33.063924198120645\n ],\n [\n -115.48828125000001,\n 48.8936153614802\n ],\n [\n -126.826171875,\n 48.8936153614802\n ],\n [\n -126.826171875,\n 33.063924198120645\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"12","issue":"1","noUsgsAuthors":false,"publicationDate":"2021-03-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Ulaski, Marta","contributorId":280108,"corporation":false,"usgs":false,"family":"Ulaski","given":"Marta","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":836042,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Quist, Michael C. 0000-0001-8268-1839","orcid":"https://orcid.org/0000-0001-8268-1839","contributorId":207142,"corporation":false,"usgs":true,"family":"Quist","given":"Michael","middleInitial":"C.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":836043,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70236348,"text":"70236348 - 2021 - A probabilistic framework to model distributions of VS30","interactions":[],"lastModifiedDate":"2022-09-02T15:02:57.58682","indexId":"70236348","displayToPublicDate":"2021-03-16T09:56:31","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"displayTitle":"A probabilistic framework to model distributions of VS30","title":"A probabilistic framework to model distributions of VS30","docAbstract":"

The time‐averaged shear‐wave velocity in the upper 30 m depth from the ground surface, or VS30\">VS30⁠, is often used as a predictor to describe local site effects in ground‐motion models. Although VS30\">VS30 is typically determined from in situ measurements, it is not always feasible to obtain such measurements due to project restrictions or site accessibility. This motivates the development and use of proxy‐based VS30\">VS30 predictions that leverage more readily available secondary information such as surface geology, topographic slope, or geomorphic terrain classes to estimate the mean VS30\">VS30 and associated uncertainty. Traditionally, empirical distributions of VS30\">VS30 have been observed to have long right tails, leading to high levels of associated uncertainty. In this study, we present a physical framework that is grounded in fundamental principles of geostatistics and probability to explain the uncertainty and skewness associated with VS30\">VS30 measurements. Specifically, by invoking Lyapunov’s central limit theorem, we hypothesize that the distribution of VS30\">VS30 can be theoretically approximated by a reciprocal–normal distribution. We show that a non‐normal and skewed distribution of VS30\">VS30 is to be expected and is not a sign of measurement error or sampling bias, although sampling bias can exaggerate such skewness. Our framework also enables us to propose the mode as a characteristic value of VS30\">VS30 measurements, as opposed to the mean or median, which can overestimate the most probable value.

","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120200281","usgsCitation":"Mital, U., Ahdi, S.K., Herrick, J.A., Iwahashi, J., Savvaidis, A., and Yong, A., 2021, A probabilistic framework to model distributions of VS30: Bulletin of the Seismological Society of America, v. 111, no. 4, p. 1677-1692, https://doi.org/10.1785/0120200281.","productDescription":"16 p.","startPage":"1677","endPage":"1692","ipdsId":"IP-122307","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":406142,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -130.67138671875,\n 54.686534234529695\n ],\n [\n -129.9462890625,\n 55.36662484928637\n ],\n [\n -130.1220703125,\n 56.145549500679074\n ],\n [\n -131.9677734375,\n 56.9449741808516\n ],\n [\n -135.3076171875,\n 59.833775202184206\n ],\n [\n -136.38427734375,\n 59.65664225341022\n ],\n [\n -136.6259765625,\n 59.23217626921806\n ],\n [\n -137.52685546875,\n 58.938673187948304\n ],\n [\n -137.65869140625,\n 59.33318942659219\n ],\n [\n -138.8232421875,\n 60.009970961180386\n ],\n [\n -139.21874999999997,\n 60.108670463036\n ],\n [\n -139.04296875,\n 60.403001945865476\n ],\n [\n -139.85595703125,\n 60.337823495982015\n ],\n [\n -140.99853515625,\n 60.337823495982015\n ],\n [\n -141.15234374999997,\n 69.71810669906763\n ],\n [\n -143.4375,\n 70.17020068549206\n ],\n [\n -145.1953125,\n 70.08056215839737\n ],\n [\n -149.765625,\n 70.58341752317065\n ],\n [\n -152.40234375,\n 70.61261423801925\n ],\n [\n -152.314453125,\n 70.95969716686398\n ],\n [\n -157.1484375,\n 71.35706654962706\n ],\n [\n -159.9609375,\n 70.8734913192635\n ],\n [\n -162.0703125,\n 70.31873847853124\n ],\n [\n -163.916015625,\n 69.06856318696033\n ],\n [\n -166.376953125,\n 68.942606818121\n ],\n [\n -166.376953125,\n 68.26938680456564\n ],\n [\n -163.30078125,\n 66.86108230224609\n ],\n [\n -161.982421875,\n 66.47820814385636\n ],\n [\n -163.564453125,\n 66.08936427047088\n ],\n [\n -163.564453125,\n 66.6181218846659\n ],\n [\n -165.76171875,\n 66.40795547978848\n ],\n [\n -168.0908203125,\n 65.69447579373418\n ],\n [\n -166.55273437499997,\n 65.14611484756372\n ],\n [\n -166.904296875,\n 65.05360170595502\n ],\n [\n -166.3330078125,\n 64.41592147626879\n ],\n [\n -162.861328125,\n 64.39693778132846\n ],\n [\n -160.927734375,\n 64.90491004905083\n ],\n [\n -161.0595703125,\n 64.47279382008166\n ],\n [\n -161.4990234375,\n 64.49172504435471\n ],\n [\n -160.8837890625,\n 63.87939001720202\n ],\n [\n -161.1474609375,\n 63.470144746565424\n ],\n [\n -162.6416015625,\n 63.64625919492172\n ],\n [\n -163.212890625,\n 63.05495931065107\n ],\n [\n -164.2236328125,\n 63.37183226679281\n ],\n [\n -166.1572265625,\n 61.75233128411639\n ],\n [\n -165.3662109375,\n 60.54377524118842\n ],\n [\n -167.431640625,\n 60.326947742998414\n ],\n [\n -167.255859375,\n 59.866883195210214\n ],\n [\n -165.8935546875,\n 59.7563950493563\n ],\n [\n -162.68554687499997,\n 59.734253447591364\n ],\n [\n -162.3779296875,\n 60.174306261926034\n ],\n [\n -161.806640625,\n 59.46740794183739\n ],\n [\n -162.0263671875,\n 59.108308258604964\n ],\n [\n -161.806640625,\n 58.768200159239576\n ],\n [\n -162.20214843749997,\n 58.65408464530598\n ],\n [\n -160.83984375,\n 58.44773280389084\n ],\n [\n -159.9609375,\n 58.6769376725869\n ],\n [\n -159.08203125,\n 58.309488840677645\n ],\n [\n -156.88476562499997,\n 58.92733441827545\n ],\n [\n -157.5,\n 58.516651799363785\n ],\n [\n -157.8076171875,\n 57.61010702068388\n ],\n [\n -161.54296875,\n 56.022948079627454\n ],\n [\n -168.6181640625,\n 53.4357192066942\n ],\n [\n -174.9462890625,\n 52.26815737376817\n ],\n [\n -178.2421875,\n 51.83577752045248\n ],\n [\n -173.1884765625,\n 51.590722643120145\n ],\n [\n -162.5537109375,\n 54.23955053156177\n ],\n [\n -155.302734375,\n 55.52863052257191\n ],\n [\n -151.4794921875,\n 57.51582286553883\n ],\n [\n -146.9970703125,\n 60.08676274626006\n ],\n [\n -145.546875,\n 60.21799073323445\n ],\n [\n -144.228515625,\n 59.689926220143356\n ],\n [\n -142.3828125,\n 59.93300042374631\n ],\n [\n -138.3837890625,\n 58.83649009392136\n ],\n [\n -135.6591796875,\n 56.31653672211301\n ],\n [\n -133.2421875,\n 54.521081495443596\n ],\n [\n -130.67138671875,\n 54.686534234529695\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -66.796875,\n 44.902577996288876\n ],\n [\n -67.67578124999999,\n 45.583289756006316\n ],\n [\n -67.939453125,\n 47.57652571374621\n ],\n [\n -69.2578125,\n 47.338822694822\n ],\n [\n -71.19140625,\n 45.27488643704891\n ],\n [\n -75.146484375,\n 44.96479793033101\n ],\n [\n -78.046875,\n 43.644025847699496\n ],\n [\n -79.1015625,\n 43.51668853502906\n ],\n [\n -79.1015625,\n 42.87596410238256\n ],\n [\n -82.68310546875,\n 41.65649719441145\n ],\n [\n -83.14453125,\n 42.049292638686836\n ],\n [\n -83.07861328125,\n 42.374778361114195\n ],\n [\n -82.529296875,\n 42.601619944327965\n ],\n [\n -82.24365234375,\n 43.6599240747891\n ],\n [\n -82.41943359375,\n 45.058001435398275\n ],\n [\n -83.60595703125,\n 45.85941212790755\n ],\n [\n -83.49609375,\n 46.027481852486645\n ],\n [\n -83.7158203125,\n 46.164614496897094\n ],\n [\n -83.95751953125,\n 46.07323062540835\n ],\n [\n -84.24316406249999,\n 46.558860303117164\n ],\n [\n -84.72656249999999,\n 46.558860303117164\n ],\n [\n -84.90234375,\n 46.92025531537451\n ],\n [\n -88.41796875,\n 48.3416461723746\n ],\n [\n -89.3408203125,\n 47.96050238891509\n ],\n [\n -90.76904296874999,\n 48.122101028190805\n ],\n [\n -90.87890625,\n 48.22467264956519\n ],\n [\n -91.51611328125,\n 48.10743118848039\n ],\n [\n -92.2412109375,\n 48.37084770238366\n ],\n [\n -92.39501953125,\n 48.23930899024907\n ],\n [\n -92.94433593749999,\n 48.61838518688487\n ],\n [\n -93.44970703125,\n 48.63290858589535\n ],\n [\n -94.7021484375,\n 48.748945343432936\n ],\n [\n -94.833984375,\n 49.23912083246698\n ],\n [\n -95.1416015625,\n 49.396675075193976\n ],\n [\n -95.20751953125,\n 49.009050809382046\n ],\n [\n -123.22265625000001,\n 48.99463598353405\n ],\n [\n -123.0908203125,\n 48.80686346108517\n ],\n [\n -123.24462890625,\n 48.66194284607006\n ],\n [\n -123.1787109375,\n 48.32703913063476\n ],\n [\n -124.78271484375,\n 48.472921272487824\n ],\n [\n -124.93652343749999,\n 48.16608541901253\n ],\n [\n -124.365234375,\n 46.58906908309182\n ],\n [\n -124.541015625,\n 44.15068115978094\n ],\n [\n -124.93652343749999,\n 42.69858589169842\n ],\n [\n -124.541015625,\n 41.22824901518529\n ],\n [\n -124.73876953125,\n 40.43022363450862\n ],\n [\n -124.03564453125,\n 39.35129035526705\n ],\n [\n -124.01367187499999,\n 38.8225909761771\n ],\n [\n -122.05810546875,\n 36.12012758978146\n ],\n [\n -120.95947265624999,\n 34.88593094075317\n ],\n [\n -120.80566406250001,\n 34.08906131584994\n ],\n [\n -118.21289062499999,\n 32.2313896627376\n ],\n [\n -117.22412109375,\n 32.54681317351514\n ],\n [\n -114.78515624999999,\n 32.713355353177555\n ],\n [\n -114.78515624999999,\n 32.491230287947594\n ],\n [\n -110.98388671874999,\n 31.3348710339506\n ],\n [\n -108.21533203125,\n 31.297327991404266\n ],\n [\n -108.2373046875,\n 31.765537409484374\n ],\n [\n -106.435546875,\n 31.765537409484374\n ],\n [\n -104.9853515625,\n 30.600093873550072\n ],\n [\n -104.47998046875,\n 29.592565403314087\n ],\n [\n -103.20556640625,\n 28.94086176940557\n ],\n [\n -102.65625,\n 29.76437737516313\n ],\n [\n -102.3486328125,\n 29.84064389983441\n ],\n [\n -101.49169921875,\n 29.7453016622136\n ],\n [\n -100.83251953125,\n 29.267232865200878\n ],\n [\n -100.30517578125,\n 28.246327971048842\n ],\n [\n -99.60205078124999,\n 27.586197857692664\n ],\n [\n -99.47021484375,\n 27.31321389856826\n ],\n [\n -99.228515625,\n 26.52956523826758\n ],\n [\n -98.2177734375,\n 26.05678288577881\n ],\n [\n -97.75634765625,\n 26.03704188651584\n ],\n [\n -97.44873046875,\n 25.839449402063185\n ],\n [\n -97.20703125,\n 25.93828707492375\n ],\n [\n -96.8994140625,\n 26.194876675795218\n ],\n [\n -96.78955078125,\n 27.858503954841247\n ],\n [\n -93.75732421875,\n 29.420460341013133\n ],\n [\n -90.2197265625,\n 28.998531814051795\n ],\n [\n -88.22021484375,\n 29.05616970274342\n ],\n [\n -87.91259765625,\n 30.14512718337613\n ],\n [\n -86.5283203125,\n 30.183121842195515\n ],\n [\n -85.2978515625,\n 29.49698759653577\n ],\n [\n -84.13330078125,\n 29.80251790576445\n ],\n [\n -82.81494140625,\n 28.555576049185973\n ],\n [\n -83.21044921875,\n 27.800209937418252\n ],\n [\n -82.77099609375,\n 26.941659545381516\n ],\n [\n -82.08984375,\n 25.878994400196202\n ],\n [\n -81.5625,\n 25.264568475331583\n ],\n [\n -82.28759765625,\n 24.467150664739002\n ],\n [\n -82.0458984375,\n 24.046463999666567\n ],\n [\n -80.6396484375,\n 24.56710835257599\n ],\n [\n -79.78271484375,\n 25.34402602913433\n ],\n [\n -79.60693359375,\n 27.27416111737468\n ],\n [\n -80.68359375,\n 30.713503990354965\n ],\n [\n -80.66162109375,\n 31.50362930577303\n ],\n [\n -76.81640625,\n 34.07086232376631\n ],\n [\n -75.16845703124999,\n 35.263561862152095\n ],\n [\n -75.498046875,\n 37.055177106660814\n ],\n [\n -73.58642578125,\n 39.90973623453719\n ],\n [\n -71.3671875,\n 40.84706035607122\n ],\n [\n -69.63134765625,\n 40.9964840143779\n ],\n [\n -70.0048828125,\n 42.342305278572816\n ],\n [\n -70.3564453125,\n 42.89206418807337\n ],\n [\n -67.2802734375,\n 44.37098696297173\n ],\n [\n -67.0166015625,\n 44.69989765840318\n ],\n [\n -66.796875,\n 44.902577996288876\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.56640625,\n 18.771115062337024\n ],\n [\n -154.68749999999997,\n 19.642587534013032\n ],\n [\n -156.9287109375,\n 21.453068633086783\n ],\n [\n -159.521484375,\n 22.43134015636061\n ],\n [\n -160.5322265625,\n 21.983801417384697\n ],\n [\n -159.9609375,\n 21.207458730482642\n ],\n [\n -158.291015625,\n 20.92039691397189\n ],\n [\n -156.97265625,\n 19.932041306115536\n ],\n [\n -155.9619140625,\n 18.8543103618898\n ],\n [\n -155.56640625,\n 18.771115062337024\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -67.060546875,\n 18.020527657852337\n ],\n [\n -66.2255859375,\n 17.916022703877665\n ],\n [\n -65.6103515625,\n 17.97873309555617\n ],\n [\n -65.2587890625,\n 18.124970639386515\n ],\n [\n -65.5224609375,\n 18.458768120015126\n ],\n [\n -66.11572265625,\n 18.542116654448996\n ],\n [\n -66.95068359374999,\n 18.60460138845525\n ],\n [\n -67.34619140625,\n 18.542116654448996\n ],\n [\n -67.2802734375,\n 17.99963161491187\n ],\n [\n -67.060546875,\n 18.020527657852337\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"111","issue":"4","noUsgsAuthors":false,"publicationDate":"2021-03-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Mital, Utkarsh","contributorId":296119,"corporation":false,"usgs":false,"family":"Mital","given":"Utkarsh","email":"","affiliations":[{"id":34214,"text":"Lawrence Berkeley National Laboratory, Berkeley, California","active":true,"usgs":false}],"preferred":false,"id":850697,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ahdi, Sean K","contributorId":217355,"corporation":false,"usgs":false,"family":"Ahdi","given":"Sean","email":"","middleInitial":"K","affiliations":[{"id":39605,"text":"Exponent, Inc. and UCLA","active":true,"usgs":false}],"preferred":false,"id":850698,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Herrick, Julie A. 0000-0003-0682-760X","orcid":"https://orcid.org/0000-0003-0682-760X","contributorId":243649,"corporation":false,"usgs":true,"family":"Herrick","given":"Julie","middleInitial":"A.","affiliations":[],"preferred":true,"id":850699,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Iwahashi, Junko","contributorId":296120,"corporation":false,"usgs":false,"family":"Iwahashi","given":"Junko","affiliations":[{"id":63994,"text":"Geospatial Information Authority of Japan, Tsukuba, Ibaraki, Japan","active":true,"usgs":false}],"preferred":false,"id":850700,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Savvaidis, Alexandros","contributorId":147429,"corporation":false,"usgs":false,"family":"Savvaidis","given":"Alexandros","email":"","affiliations":[{"id":16852,"text":"Institute of Engineering Seismology and Earthquake Engineering, Greece","active":true,"usgs":false}],"preferred":false,"id":850701,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Yong, Alan 0000-0003-1807-5847","orcid":"https://orcid.org/0000-0003-1807-5847","contributorId":204730,"corporation":false,"usgs":true,"family":"Yong","given":"Alan","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":850702,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70236138,"text":"70236138 - 2021 - Water balance of the turn-of-the-century drought in the Southwestern United States","interactions":[],"lastModifiedDate":"2022-08-30T14:10:34.354097","indexId":"70236138","displayToPublicDate":"2021-03-16T09:01:54","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1562,"text":"Environmental Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Water balance of the turn-of-the-century drought in the Southwestern United States","docAbstract":"

Analysis of the water balance of the southwestern United States (SWUS) during 1900 through 2018 was used to evaluate the magnitude of the turn-of-the-century (TOC) drought in the SWUS. Results indicate that the warm season (April through September) soil moisture and runoff during the TOC drought were among the lowest values of the 1900 through 2018 period. Additionally, increases in temperature were identified as a significant driver of low soil moisture and runoff conditions during the warm season. In contrast, during the cool seasons (October through March) and the water year (October 1 through September 30) during the TOC drought, soil moisture and runoff did not indicate extremely dry conditions even though temperatures were the highest of the 1900 through 2018 period.

","language":"English","publisher":"IOP Science","doi":"10.1088/1748-9326/abbfc1","usgsCitation":"McCabe, G.J., and Wolock, D.M., 2021, Water balance of the turn-of-the-century drought in the Southwestern United States: Environmental Research Letters, v. 16, 044015, 9 p., https://doi.org/10.1088/1748-9326/abbfc1.","productDescription":"044015, 9 p.","ipdsId":"IP-122582","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":453071,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/1748-9326/abbfc1","text":"Publisher Index Page"},{"id":405904,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Soputhwestern United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -100,\n 40\n ],\n [\n -108.08349609375,\n 40\n ],\n [\n -124,\n 40\n ],\n [\n -120.05859375,\n 34.161818161230386\n ],\n [\n -117.24609374999999,\n 32.39851580247402\n ],\n [\n -114.9609375,\n 32.76880048488168\n ],\n [\n -111.1376953125,\n 31.42866311735861\n ],\n [\n -108.2373046875,\n 31.316101383495624\n ],\n [\n -108.06152343749999,\n 31.765537409484374\n ],\n [\n -106.61132812499999,\n 31.765537409484374\n ],\n [\n -103.9306640625,\n 29.305561325527698\n ],\n [\n -103.0517578125,\n 29.075375179558346\n ],\n [\n -102.26074218749999,\n 29.954934549656144\n ],\n [\n -100.986328125,\n 29.6880527498568\n ],\n [\n -99.7998046875,\n 27.800209937418252\n ],\n [\n -99.5361328125,\n 27.68352808378776\n ],\n [\n -100,\n 40\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"16","noUsgsAuthors":false,"publicationDate":"2021-03-16","publicationStatus":"PW","contributors":{"authors":[{"text":"McCabe, Gregory J. 0000-0002-9258-2997 gmccabe@usgs.gov","orcid":"https://orcid.org/0000-0002-9258-2997","contributorId":200854,"corporation":false,"usgs":true,"family":"McCabe","given":"Gregory","email":"gmccabe@usgs.gov","middleInitial":"J.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":850205,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wolock, David M. 0000-0002-6209-938X","orcid":"https://orcid.org/0000-0002-6209-938X","contributorId":219213,"corporation":false,"usgs":true,"family":"Wolock","given":"David","email":"","middleInitial":"M.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":850206,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70219181,"text":"70219181 - 2021 - American Woodcock singing-ground survey: Comparison of four models for trend in population size","interactions":[],"lastModifiedDate":"2021-08-03T13:58:58.411403","indexId":"70219181","displayToPublicDate":"2021-03-16T07:14:46","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"American Woodcock singing-ground survey: Comparison of four models for trend in population size","docAbstract":"

Wildlife biologists monitor the status and trends of American woodcock Scolopax minor populations in the eastern and central United States and Canada via a singing-ground survey, conducted just after sunset along roadsides in spring. Annual analyses of the survey produce estimates of trend and annual indexes of abundance for 25 states and provinces, management regions, and survey-wide. In recent years, researchers have used a log-linear hierarchical model that defines year effects as random effects in the context of a slope parameter (the S model) to model population change. Recently, researchers have proposed alternative models suitable for analysis of singing-ground survey data. Analysis of a similar roadside survey, the North American Breeding Bird Survey, has indicated that alternative models are preferable for almost all species analyzed in the Breeding Bird Survey. Here, we use leave-one-out cross-validation to compare model fit for the present singing-ground survey model to fits of three alternative models, including a model that describes population change as the difference in expected counts between successive years (the D model) and two models that include t-distributed extra-Poisson overdispersion effects (H models) as opposed to normally distributed extra-Poisson overdispersion. Leave-one-out cross-validation results indicate that the Bayesian predictive information criterion favored the D model, but a pairwise t-test indicated that the D model was not significantly better-fitting to singing-ground survey data than the S model. The H models are not preferable to the alternatives with normally distributed overdispersion. All models provided generally similar estimates of trend and annual indexes suggesting that, within this model set, choice of model will not lead to alternative conclusions regarding population change. However, as in Breeding Bird Survey analyses, we note a tendency for S model results to provide slightly more extreme estimates of trend relative to D models. We recommend use of the D model for future singing-ground survey analyses.

","language":"English","publisher":"Allen Press","doi":"10.3996/JFWM-20-079","usgsCitation":"Sauer, J.R., Link, W., Seamans, M.E., and Rau, R.D., 2021, American Woodcock singing-ground survey: Comparison of four models for trend in population size: Journal of Fish and Wildlife Management, v. 12, no. 1, p. 83-97, https://doi.org/10.3996/JFWM-20-079.","productDescription":"15 p.","startPage":"83","endPage":"97","onlineOnly":"N","ipdsId":"IP-127453","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":453075,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/jfwm-20-079","text":"Publisher Index Page"},{"id":384754,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States, Canada","otherGeospatial":"Eastern and Central United States and Canada","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -67.412109375,\n 50.17689812200107\n ],\n [\n -95.537109375,\n 51.069016659603896\n ],\n [\n -95.888671875,\n 48.922499263758255\n ],\n [\n -95.00976562499999,\n 43.58039085560784\n ],\n [\n -93.955078125,\n 39.027718840211605\n ],\n [\n -93.515625,\n 30.826780904779774\n ],\n [\n -86.748046875,\n 32.10118973232094\n ],\n [\n -82.6171875,\n 29.99300228455108\n ],\n [\n -77.783203125,\n 34.161818161230386\n ],\n [\n -75.76171875,\n 35.88905007936091\n ],\n [\n -60.29296874999999,\n 45.706179285330855\n ],\n [\n -60.29296874999999,\n 47.100044694025215\n ],\n [\n -67.412109375,\n 50.17689812200107\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"12","issue":"1","noUsgsAuthors":false,"publicationDate":"2021-03-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Sauer, John R. 0000-0002-4557-3019 jrsauer@usgs.gov","orcid":"https://orcid.org/0000-0002-4557-3019","contributorId":146917,"corporation":false,"usgs":true,"family":"Sauer","given":"John","email":"jrsauer@usgs.gov","middleInitial":"R.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":813142,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Link, William 0000-0002-9913-0256","orcid":"https://orcid.org/0000-0002-9913-0256","contributorId":221718,"corporation":false,"usgs":true,"family":"Link","given":"William","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":813143,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Seamans, Mark E","contributorId":256724,"corporation":false,"usgs":false,"family":"Seamans","given":"Mark","email":"","middleInitial":"E","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":813144,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rau, Rebecca D.","contributorId":256726,"corporation":false,"usgs":false,"family":"Rau","given":"Rebecca","email":"","middleInitial":"D.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":813145,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70218843,"text":"70218843 - 2021 - A systematic review of potential habitat suitability for the jaguar Panthera onca in central Arizona and New Mexico, USA","interactions":[],"lastModifiedDate":"2021-03-17T12:09:21.458718","indexId":"70218843","displayToPublicDate":"2021-03-16T07:00:01","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2968,"text":"Oryx","active":true,"publicationSubtype":{"id":10}},"title":"A systematic review of potential habitat suitability for the jaguar Panthera onca in central Arizona and New Mexico, USA","docAbstract":"

In April 2019, the U.S. Fish and Wildlife Service (USFWS) released its recovery plan for the jaguar Panthera onca after several decades of discussion, litigation and controversy about the status of the species in the USA. The USFWS estimated that potential habitat, south of the Interstate-10 highway in Arizona and New Mexico, had a carrying capacity of c. six jaguars, and so focused its recovery programme on areas south of the USA–Mexico border. Here we present a systematic review of the modelling and assessment efforts over the last 25 years, with a focus on areas north of Interstate-10 in Arizona and New Mexico, outside the recovery unit considered by the USFWS. Despite differences in data inputs, methods, and analytical extent, the nine previous studies found support for potential suitable jaguar habitat in the central mountain ranges of Arizona and New Mexico. Applying slightly modified versions of the USFWS model and recalculating an Arizona-focused model over both states provided additional confirmation. Extending the area of consideration also substantially raised the carrying capacity of habitats in Arizona and New Mexico, from six to 90 or 151 adult jaguars, using the modified USFWS models. This review demonstrates the crucial ways in which choosing the extent of analysis influences the conclusions of a conservation plan. More importantly, it opens a new opportunity for jaguar conservation in North America that could help address threats from habitat losses, climate change and border infrastructure.

","language":"English","publisher":"Cambridge University Press","doi":"10.1017/S0030605320000459","usgsCitation":"Sanderson, E.W., Fisher, K., Peters, R., Beckmann, J.P., Bird, B., Bradley, C., Bravo, J., Grigione, M.M., Hatten, J., Gonzalez, C., Menke, K., Miller, J., Miller, P., Mormorunni, C., Robinson, M., Thomas, R.E., and Wilcox, S., 2021, A systematic review of potential habitat suitability for the jaguar Panthera onca in central Arizona and New Mexico, USA: Oryx, p. 1-12, https://doi.org/10.1017/S0030605320000459.","productDescription":"12 p.","startPage":"1","endPage":"12","ipdsId":"IP-114595","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":453076,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1017/s0030605320000459","text":"Publisher Index Page"},{"id":384446,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, New Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.45556640625,\n 33.97980872872457\n ],\n [\n -114.6533203125,\n 33.394759218577995\n ],\n [\n -114.6533203125,\n 33.137551192346145\n ],\n [\n -114.43359375,\n 32.84267363195431\n ],\n [\n -114.82910156249999,\n 32.58384932565662\n ],\n [\n -110.76416015625,\n 31.297327991404266\n ],\n [\n -109.00634765625,\n 31.3348710339506\n ],\n [\n -108.1494140625,\n 31.372399104880525\n ],\n [\n -108.19335937499999,\n 31.82156451492074\n ],\n [\n -102.98583984374999,\n 32.045332838858506\n ],\n [\n -103.0517578125,\n 33.26624989076275\n ],\n [\n -114.45556640625,\n 33.97980872872457\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2021-03-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Sanderson, Eric W 0000-0002-7477-0193","orcid":"https://orcid.org/0000-0002-7477-0193","contributorId":255462,"corporation":false,"usgs":false,"family":"Sanderson","given":"Eric","email":"","middleInitial":"W","affiliations":[{"id":51534,"text":"Wildlife Conservation Society, Global Conservation Programs","active":true,"usgs":false}],"preferred":false,"id":812394,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fisher, Kim","contributorId":255463,"corporation":false,"usgs":false,"family":"Fisher","given":"Kim","email":"","affiliations":[{"id":51534,"text":"Wildlife Conservation Society, Global Conservation Programs","active":true,"usgs":false}],"preferred":false,"id":812395,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Peters, Rob","contributorId":255464,"corporation":false,"usgs":false,"family":"Peters","given":"Rob","email":"","affiliations":[{"id":51535,"text":"Defenders of Wildlife, Field Conservation, Southwest Office","active":true,"usgs":false}],"preferred":false,"id":812396,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Beckmann, Jon P.","contributorId":210843,"corporation":false,"usgs":false,"family":"Beckmann","given":"Jon","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":812397,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bird, Bryan","contributorId":255465,"corporation":false,"usgs":false,"family":"Bird","given":"Bryan","email":"","affiliations":[{"id":51535,"text":"Defenders of Wildlife, Field Conservation, Southwest Office","active":true,"usgs":false}],"preferred":false,"id":812398,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bradley, Curtis","contributorId":255466,"corporation":false,"usgs":false,"family":"Bradley","given":"Curtis","email":"","affiliations":[{"id":51536,"text":"Center for Biological Diversity, Geographic Information Systems","active":true,"usgs":false}],"preferred":false,"id":812399,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bravo, Juan","contributorId":255467,"corporation":false,"usgs":false,"family":"Bravo","given":"Juan","affiliations":[{"id":51537,"text":"Wildlands Network, Mexico Program","active":true,"usgs":false}],"preferred":false,"id":812400,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Grigione, Melissa M.","contributorId":255468,"corporation":false,"usgs":false,"family":"Grigione","given":"Melissa","email":"","middleInitial":"M.","affiliations":[{"id":51538,"text":"Pace University, Biology Department","active":true,"usgs":false}],"preferred":false,"id":812401,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hatten, James 0000-0003-4676-8093","orcid":"https://orcid.org/0000-0003-4676-8093","contributorId":220165,"corporation":false,"usgs":true,"family":"Hatten","given":"James","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":812402,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Gonzalez, Carlos","contributorId":255469,"corporation":false,"usgs":false,"family":"Gonzalez","given":"Carlos","email":"","affiliations":[{"id":51539,"text":"Universidad Autonoma de Queretaro, Biologia Department","active":true,"usgs":false}],"preferred":false,"id":812403,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Menke, Kurt","contributorId":255470,"corporation":false,"usgs":false,"family":"Menke","given":"Kurt","email":"","affiliations":[{"id":51540,"text":"Bird's Eye View, Geographic information systems","active":true,"usgs":false}],"preferred":false,"id":812404,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Miller, Jennie","contributorId":255471,"corporation":false,"usgs":false,"family":"Miller","given":"Jennie","email":"","affiliations":[{"id":51541,"text":"Defenders of Wildlife, Center for Conservation Innovation","active":true,"usgs":false}],"preferred":false,"id":812405,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Miller, Philip 0000-0001-6806-392X","orcid":"https://orcid.org/0000-0001-6806-392X","contributorId":255472,"corporation":false,"usgs":false,"family":"Miller","given":"Philip","email":"","affiliations":[{"id":51542,"text":"IUCN, Conservation Planning Specialist Group","active":true,"usgs":false}],"preferred":false,"id":812406,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Mormorunni, Cristina","contributorId":255473,"corporation":false,"usgs":false,"family":"Mormorunni","given":"Cristina","email":"","affiliations":[{"id":51544,"text":"Wildlife Conservation Society, Rocky Mountain West Program","active":true,"usgs":false}],"preferred":false,"id":812407,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Robinson, Michael","contributorId":255474,"corporation":false,"usgs":false,"family":"Robinson","given":"Michael","affiliations":[{"id":51536,"text":"Center for Biological Diversity, Geographic Information Systems","active":true,"usgs":false}],"preferred":false,"id":812408,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Thomas, Robert E","contributorId":255475,"corporation":false,"usgs":false,"family":"Thomas","given":"Robert","email":"","middleInitial":"E","affiliations":[{"id":51545,"text":"Bordercats Working Group, Lakewood, USA","active":true,"usgs":false}],"preferred":false,"id":812409,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Wilcox, Sharon","contributorId":255476,"corporation":false,"usgs":false,"family":"Wilcox","given":"Sharon","email":"","affiliations":[{"id":51546,"text":"Field Conservation, Southwest Office, Defenders of Wildlife, Santa Fe, USA","active":true,"usgs":false}],"preferred":false,"id":812410,"contributorType":{"id":1,"text":"Authors"},"rank":17}]}} ,{"id":70219123,"text":"70219123 - 2021 - Integrating environmental DNA results with diverse data sets to improve biosurveillance of river health","interactions":[],"lastModifiedDate":"2021-03-24T11:41:22.219976","indexId":"70219123","displayToPublicDate":"2021-03-16T06:33:48","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3910,"text":"Frontiers in Ecology and Evolution","onlineIssn":"2296-701X","active":true,"publicationSubtype":{"id":10}},"title":"Integrating environmental DNA results with diverse data sets to improve biosurveillance of river health","docAbstract":"

Autonomous, robotic environmental (e)DNA samplers now make it possible for biological observations to match the scale and quality of abiotic measurements collected by automated sensor networks. Merging these automated data streams may allow for improved insight into biotic responses to environmental change and stressors. Here, we merged eDNA data collected by robotic samplers installed at three U.S. Geological Survey (USGS) streamgages with gridded daily weather data, and daily water quality and quantity data into a cloud-hosted database. The eDNA targets were a rare fish parasite and a more common salmonid fish. We then used computationally expedient Bayesian hierarchical occupancy models to evaluate associations between abiotic conditions and eDNA detections and to simulate how uncertainty in result interpretation changes with the frequency of autonomous robotic eDNA sample collection. We developed scripts to automate data merging, cleaning and analysis steps into a chained-step, workflow. We found that inclusion of abiotic covariates only provided improved insight for the more common salmonid fish since its DNA was more frequently detected. Rare fish parasite DNA was infrequently detected, which caused occupancy parameter estimates and covariate associations to have high uncertainty. Our simulations found that collecting samples at least once per day resulted in more detections and less parameter uncertainty than less frequent sampling. Our occupancy and simulation results together demonstrate the advantages of robotic eDNA samplers and how these samples can be combined with easy to acquire, publicly available data to foster real-time biosurveillance and forecasting.

","language":"English","publisher":"Frontiers","doi":"10.3389/fevo.2021.620715","usgsCitation":"Sepulveda, A., Hoegh, A.B., Gage, J.A., Caldwell Eldridge, S.L., Birch, J.M., Stratton, C., Hutchins, P.R., and Barnhart, E.P., 2021, Integrating environmental DNA results with diverse data sets to improve biosurveillance of river health: Frontiers in Ecology and Evolution, v. 9, 13 p., https://doi.org/10.3389/fevo.2021.620715.","productDescription":"13 p.","ipdsId":"IP-123750","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":453078,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fevo.2021.620715","text":"Publisher Index Page"},{"id":384620,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Wyoming, Montana","otherGeospatial":"Yellowstone River, Snake River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.400390625,\n 43.89789239125797\n ],\n [\n -107.666015625,\n 43.89789239125797\n ],\n [\n -107.666015625,\n 46.49839225859763\n ],\n [\n -115.400390625,\n 46.49839225859763\n ],\n [\n -115.400390625,\n 43.89789239125797\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","noUsgsAuthors":false,"publicationDate":"2021-03-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Sepulveda, Adam 0000-0001-7621-7028 asepulveda@usgs.gov","orcid":"https://orcid.org/0000-0001-7621-7028","contributorId":4187,"corporation":false,"usgs":true,"family":"Sepulveda","given":"Adam","email":"asepulveda@usgs.gov","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":812861,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hoegh, Andrew B.","contributorId":166684,"corporation":false,"usgs":false,"family":"Hoegh","given":"Andrew","email":"","middleInitial":"B.","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":812862,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gage, Joshua A.","contributorId":255726,"corporation":false,"usgs":false,"family":"Gage","given":"Joshua","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":812863,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Caldwell Eldridge, Sara L. 0000-0001-8838-8940 seldridge@usgs.gov","orcid":"https://orcid.org/0000-0001-8838-8940","contributorId":4981,"corporation":false,"usgs":true,"family":"Caldwell Eldridge","given":"Sara","email":"seldridge@usgs.gov","middleInitial":"L.","affiliations":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"preferred":true,"id":812864,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Birch, James M.","contributorId":255728,"corporation":false,"usgs":false,"family":"Birch","given":"James","email":"","middleInitial":"M.","affiliations":[{"id":16837,"text":"MBARI","active":true,"usgs":false}],"preferred":false,"id":812865,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stratton, Christian","contributorId":217711,"corporation":false,"usgs":false,"family":"Stratton","given":"Christian","email":"","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":812866,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hutchins, Patrick R. 0000-0001-5232-0821 phutchins@usgs.gov","orcid":"https://orcid.org/0000-0001-5232-0821","contributorId":198337,"corporation":false,"usgs":true,"family":"Hutchins","given":"Patrick","email":"phutchins@usgs.gov","middleInitial":"R.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":812867,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Barnhart, Elliott P. 0000-0002-8788-8393","orcid":"https://orcid.org/0000-0002-8788-8393","contributorId":203225,"corporation":false,"usgs":true,"family":"Barnhart","given":"Elliott","middleInitial":"P.","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":812868,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70219207,"text":"70219207 - 2021 - Potential Pb+2 mobilization, transport, and sequestration in shallow aquifers impacted by multiphase CO2 leakage: A natural analogue study from the Virgin River Basin in Southwest Utah","interactions":[],"lastModifiedDate":"2021-05-18T14:07:03.389177","indexId":"70219207","displayToPublicDate":"2021-03-15T13:32:45","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3042,"text":"Petroleum Geoscience","active":true,"publicationSubtype":{"id":10}},"title":"Potential Pb+2 mobilization, transport, and sequestration in shallow aquifers impacted by multiphase CO2 leakage: A natural analogue study from the Virgin River Basin in Southwest Utah","docAbstract":"

Geological carbon sequestration (GCS) is necessary to help meet emissions reduction goals, but groundwater contamination may occur if CO2 and/or brine were to leak out of deep storage formations into the shallow subsurface. For this study, a natural analogue was investigated: in the Virgin River Basin of southwest Utah, water with moderate salinity and high CO2 concentrations is leaking upward into shallow aquifers that contain heavy metal-bearing concretions. The aquifer system is comprised of the Navajo and Kayenta formations, which are pervasive across southern Utah and have been considered as a potential GCS injection unit where they are sufficiently deep. Numerical models of the site were constructed based on measured water chemistry and head distributions from previous studies. Simulations were used to improve understanding of the rate and distribution of the upwelling flow into the aquifers, and to assess the reactive transport processes that may occur if the upwelling fluids were to interact with a zone of iron oxide and other heavy metals, representing the concretions that are common in the area. Various mineralogies were tested, including one in which Pb+2 was adsorbed onto ferrihydrite, and another in which it was bound within a solid mixture of litharge (PbO) and hematite (Fe2O3). Results indicate that metal mobilization depends strongly on the source zone composition and that Pb+2 transport can be naturally attenuated by gas phase formation and carbonate mineral precipitation. These findings could be used to improve risk assessment and mitigation strategies at geological carbon sequestration sites.

","language":"English","publisher":"The Geological Society of London","doi":"10.1144/petgeo2020-109","usgsCitation":"Plampin, M.R., Blondes, M., Sonnenthal, E., and Craddock, W.H., 2021, Potential Pb+2 mobilization, transport, and sequestration in shallow aquifers impacted by multiphase CO2 leakage: A natural analogue study from the Virgin River Basin in Southwest Utah: Petroleum Geoscience, v. 27, no. 3, petgeo2020-109, 15 p., https://doi.org/10.1144/petgeo2020-109.","productDescription":"petgeo2020-109, 15 p.","ipdsId":"IP-120620","costCenters":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":384769,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"id\":\"47\",\"properties\":{\"name\":\"Utah\",\"nation\":\"USA \"},\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-111.046551,41.251716],[-111.046723,40.997959],[-110.750727,40.996847],[-110.715026,40.996347],[-110.539819,40.996346],[-110.500718,40.994746],[-110.375714,40.994947],[-110.250709,40.996089],[-110.237848,40.995427],[-110.125709,40.99655],[-110.121639,40.997101],[-110.048476,40.997555],[-110.006495,40.997815],[-110.000708,40.997352],[-109.999838,40.99733],[-109.97553,40.997912],[-109.855299,40.997614],[-109.854302,40.997661],[-109.715409,40.998191],[-109.713877,40.998266],[-109.676421,40.998395],[-109.534926,40.998143],[-109.500694,40.999127],[-109.250735,41.001009],[-109.231985,41.002059],[-109.173682,41.000859],[-109.050076,41.000659],[-109.048455,40.826081],[-109.049088,40.714562],[-109.048373,40.662602],[-109.048249,40.653601],[-109.048044,40.619231],[-109.050074,40.540358],[-109.049955,40.539901],[-109.050698,40.499963],[-109.050314,40.495092],[-109.050946,40.444368],[-109.050969,40.222662],[-109.050973,40.180849],[-109.050944,40.180712],[-109.050813,40.059579],[-109.050873,40.058915],[-109.050615,39.87497],[-109.05104,39.660472],[-109.051363,39.497674],[-109.050765,39.366677],[-109.051512,39.126095],[-109.052436,38.999985],[-109.053292,38.942878],[-109.053233,38.942467],[-109.053797,38.905284],[-109.053943,38.904414],[-109.054189,38.874984],[-109.057388,38.795456],[-109.059541,38.719888],[-109.060253,38.599328],[-109.059962,38.499987],[-109.060062,38.275489],[-109.054648,38.244921],[-109.041762,38.16469],[-109.041837,38.153022],[-109.04282,37.999301],[-109.042819,37.997068],[-109.043121,37.97426],[-109.041058,37.907236],[-109.041653,37.88117],[-109.041844,37.872788],[-109.041723,37.842051],[-109.041754,37.835826],[-109.041461,37.800105],[-109.042098,37.74999],[-109.041636,37.74021],[-109.04176,37.713182],[-109.041732,37.711214],[-109.042269,37.666067],[-109.042089,37.623795],[-109.042131,37.617662],[-109.041806,37.604171],[-109.041865,37.530726],[-109.041915,37.530653],[-109.043137,37.499992],[-109.043464,37.484711],[-109.04581,37.374993],[-109.046039,37.249993],[-109.045584,37.249351],[-109.045487,37.210844],[-109.045978,37.201831],[-109.045995,37.177279],[-109.045156,37.112064],[-109.045203,37.111958],[-109.045173,37.109464],[-109.045189,37.096271],[-109.044995,37.086429],[-109.045058,37.074661],[-109.045166,37.072742],[-109.045223,36.999084],[-109.181196,36.999271],[-109.233848,36.999266],[-109.246917,36.999346],[-109.26339,36.999263],[-109.268213,36.999242],[-109.270097,36.999266],[-109.378039,36.999135],[-109.381226,36.999148],[-109.495338,36.999105],[-109.625668,36.998308],[-109.875673,36.998504],[-110.000677,36.997968],[-110.000876,36.998502],[-110.021778,36.998602],[-110.47019,36.997997],[-110.490908,37.003566],[-110.50069,37.00426],[-110.599512,37.003448],[-110.625605,37.003416],[-110.62569,37.003721],[-110.75069,37.003197],[-111.066496,37.002389],[-111.133718,37.000779],[-111.254853,37.001077],[-111.278286,37.000465],[-111.405517,37.001497],[-111.405869,37.001481],[-111.412784,37.001478],[-112.35769,37.001025],[-112.368946,37.001125],[-112.534545,37.000684],[-112.538593,37.000674],[-112.540368,37.000669],[-112.545094,37.000734],[-112.558974,37.000692],[-112.609787,37.000753],[-112.899366,37.000319],[-112.966471,37.000219],[-113.965907,36.999976],[-113.965907,37.000025],[-114.0506,37.000396],[-114.051749,37.088434],[-114.051822,37.090976],[-114.052827,37.103961],[-114.051867,37.134292],[-114.052179,37.14711],[-114.051673,37.172368],[-114.051405,37.233854],[-114.051974,37.283848],[-114.051974,37.284511],[-114.0518,37.293044],[-114.0518,37.293548],[-114.051927,37.370459],[-114.051927,37.370734],[-114.051765,37.418083],[-114.052448,37.43144],[-114.052701,37.492014],[-114.052685,37.502513],[-114.052718,37.517264],[-114.052689,37.517859],[-114.052962,37.592783],[-114.052472,37.604776],[-114.051728,37.745997],[-114.051785,37.746249],[-114.05167,37.746958],[-114.051109,37.756276],[-114.049919,37.765586],[-114.048473,37.809861],[-114.049677,37.823645],[-114.049928,37.852508],[-114.049658,37.881368],[-114.050423,37.999961],[-114.049903,38.148601],[-114.050138,38.24996],[-114.049417,38.2647],[-114.05012,38.404536],[-114.050091,38.404673],[-114.050485,38.499955],[-114.049834,38.543784],[-114.049862,38.547764],[-114.050154,38.57292],[-114.049883,38.677365],[-114.049749,38.72921],[-114.049168,38.749951],[-114.049465,38.874949],[-114.048521,38.876197],[-114.048054,38.878693],[-114.049104,39.005509],[-114.047079,39.499943],[-114.047728,39.542742],[-114.047273,39.759413],[-114.047783,39.79416],[-114.047214,39.821024],[-114.047134,39.906037],[-114.046555,39.996899],[-114.046835,40.030131],[-114.046386,40.097896],[-114.046741,40.104231],[-114.046683,40.116931],[-114.046153,40.231971],[-114.046178,40.398313],[-114.045826,40.424823],[-114.045218,40.430282],[-114.045518,40.494474],[-114.045577,40.495801],[-114.045281,40.506586],[-114.043505,40.726292],[-114.043831,40.758666],[-114.043803,40.759205],[-114.043176,40.771675],[-114.042145,40.999926],[-114.041447,41.207752],[-114.042553,41.210923],[-114.041396,41.219958],[-114.040231,41.49169],[-114.040942,41.499921],[-114.040437,41.615377],[-114.039968,41.62492],[-114.039901,41.753781],[-114.041152,41.850595],[-114.041107,41.850573],[-114.039648,41.884816],[-114.041723,41.99372],[-113.993903,41.992698],[-113.893261,41.988057],[-113.822163,41.988479],[-113.796082,41.989104],[-113.76453,41.989459],[-113.500837,41.992799],[-113.496548,41.993305],[-113.431563,41.993799],[-113.40223,41.994161],[-113.396497,41.99425],[-113.357611,41.993859],[-113.340072,41.994747],[-113.250829,41.99561],[-113.249159,41.996203],[-113.000821,41.998223],[-113.00082,41.998223],[-112.979218,41.998263],[-112.909587,41.998791],[-112.882367,41.998922],[-112.880619,41.998921],[-112.833125,41.999345],[-112.833084,41.999305],[-112.788542,41.999681],[-112.709375,42.000309],[-112.648019,42.000307],[-112.450814,42.000953],[-112.450567,42.001092],[-112.38617,42.001126],[-112.264936,42.000991],[-112.239107,42.001217],[-112.192976,42.001167],[-112.173352,41.996568],[-112.163956,41.996708],[-112.109532,41.997598],[-112.01218,41.99835],[-111.915837,41.998519],[-111.915622,41.998496],[-111.876491,41.998528],[-111.750778,41.99933],[-111.507264,41.999518],[-111.471381,41.999739],[-111.425535,42.00084],[-111.420898,42.000793],[-111.415873,42.000748],[-111.046689,42.001567],[-111.045818,41.579845],[-111.045789,41.565571],[-111.046264,41.377731],[-111.0466,41.360692],[-111.046551,41.251716]]]}}]}","volume":"27","issue":"3","noUsgsAuthors":false,"publicationDate":"2021-05-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Plampin, Michelle R. 0000-0003-4068-5801 mplampin@usgs.gov","orcid":"https://orcid.org/0000-0003-4068-5801","contributorId":204983,"corporation":false,"usgs":true,"family":"Plampin","given":"Michelle","email":"mplampin@usgs.gov","middleInitial":"R.","affiliations":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"preferred":true,"id":813215,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blondes, Madalyn S. 0000-0003-0320-0107 mblondes@usgs.gov","orcid":"https://orcid.org/0000-0003-0320-0107","contributorId":3598,"corporation":false,"usgs":true,"family":"Blondes","given":"Madalyn S.","email":"mblondes@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":813216,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sonnenthal, Eric","contributorId":146807,"corporation":false,"usgs":false,"family":"Sonnenthal","given":"Eric","affiliations":[],"preferred":false,"id":813217,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Craddock, William H. 0000-0002-4181-4735 wcraddock@usgs.gov","orcid":"https://orcid.org/0000-0002-4181-4735","contributorId":3411,"corporation":false,"usgs":true,"family":"Craddock","given":"William","email":"wcraddock@usgs.gov","middleInitial":"H.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":813218,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70218647,"text":"sir20215004 - 2021 - Numerical simulation of the effects of groundwater withdrawal and injection of high-salinity water on salinity and groundwater discharge, Kaloko-Honokōhau National Historical Park, Hawaiʻi","interactions":[],"lastModifiedDate":"2021-03-16T11:43:44.760872","indexId":"sir20215004","displayToPublicDate":"2021-03-15T08:46:16","publicationYear":"2021","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":"2021-5004","displayTitle":"Numerical Simulation of the Effects of Groundwater Withdrawal and Injection of High-Salinity Water on Salinity and Groundwater Discharge, Kaloko-Honokōhau National Historical Park, Hawaiʻi","title":"Numerical simulation of the effects of groundwater withdrawal and injection of high-salinity water on salinity and groundwater discharge, Kaloko-Honokōhau National Historical Park, Hawaiʻi","docAbstract":"

Kaloko-Honokōhau National Historical Park (KAHO) is located on the west coast of the island of Hawaiʻi and contains water resources exposed in fishponds, anchialine pools, and marine waters that are cultural resources and that provide habitat for threatened, endangered, and other culturally important native species. KAHO’s water resources are sustained by and dependent on groundwater discharge. In 1978, the year of KAHO authorization, the lands immediately surrounding KAHO were undeveloped and zoned for conservation purposes; at present, most surrounding lands are either developed or zoned for industrial, commercial, or residential use. Urbanization of the North Kona District has increased the need for additional drinking and nonpotable (irrigation) water. Because KAHO’s water resources may be affected by existing and proposed groundwater withdrawals and injections of high-salinity water in the surrounding area, the U.S. Geological Survey, in cooperation with the National Park Service, undertook this study to refine the understanding of how groundwater withdrawals and injection of high-salinity water may affect KAHO’s water resources.

Changes in KAHO water resources, in terms of changes in salinity and groundwater discharge, were modeled for selected scenarios of groundwater withdrawal and high-salinity water injection in the aquifer. The numerical model was developed using the model code SUTRA, which accounts for density-dependent flow and salinity transport, and included the coastal-confined groundwater system beneath the coastal freshwater-lens system. Model results indicate that withdrawal of additional groundwater from the coastal freshwater-lens system will affect the salinity of KAHO’s anchialine pools, which provide habitat for the endangered orangeblack Hawaiian damselfly (Megalagrion xanthomelas). The magnitude of the effect is dependent on the amount and location of the withdrawal. Greater withdrawal rates cause greater increases in salinity in KAHO, other factors being equal. For a given withdrawal rate, the greatest increase in salinity in KAHO is associated with wells withdrawing groundwater in an area inland of KAHO and the least increase in salinity is associated with wells near the coast. Model results also indicate that withdrawal of additional groundwater from the coastal freshwater-lens system will affect the groundwater discharge, in terms of the freshwater component (water with zero salinity) of the discharge, through KAHO. Greater withdrawal rates cause greater reductions in freshwater discharge through KAHO. For a given withdrawal rate, the greatest reduction in freshwater discharge through KAHO is associated with wells near the north boundary of KAHO and the least reduction is associated with wells near the coast to the north and south of KAHO.

Injection of high-salinity water that is denser than ocean water can affect the salinity of damselfly habitat in KAHO, with the magnitude of the effect dependent on the location of the injection. Model results indicate that salinity may either increase or decrease in the anchialine pools that provide damselfly habitat in KAHO, depending on the site of injection. Injection inland of KAHO and at sites immediately north and south of KAHO causes a simulated decrease in salinity at the damselfly habitat, whereas injection farther north and south of KAHO causes an increase in salinity. Injection of high-salinity water also causes a reduction in freshwater discharge through KAHO, with the greatest reduction associated with distant injection wells to the north and south of KAHO and the least reduction associated with wells located near and immediately inland from KAHO.

The numerical groundwater models developed for this study have a number of limitations. Lack of understanding of the subsurface geology constrains the ability to accurately model the groundwater-flow system. The models developed for this study are nonunique, cannot account for local-scale heterogeneities in the aquifer, and contain uncertainties related to recharge, boundary conditions, assigned parameter values in the model, and representations of the different hydrogeological features. Confidence in model results can be improved by addressing these and other limitations. In spite of these limitations, the three-dimensional numerical model developed for this study provides a useful conceptual understanding of the potential effects of additional withdrawals and injections on groundwater resources in KAHO. Further evaluation of the ecologic effects of the simulated changes in groundwater quality and quantity in KAHO is needed but is beyond the scope of this study.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215004","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Oki, D.S., 2021, Numerical simulation of the effects of groundwater withdrawal and injection of high-salinity water on salinity and groundwater discharge, Kaloko-Honokōhau National Historical Park, Hawaiʻi: U.S. Geological Survey Scientific Investigations Report 2021–5004, 59 p., https://doi.org/10.3133/sir20215004.","productDescription":"Report: viii, 59 p.; Data Release","numberOfPages":"59","ipdsId":"IP-119308","costCenters":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"links":[{"id":383763,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9IZ3EVJ","linkHelpText":"SUTRA Model Used to Evaluate the Effects of Groundwater Withdrawal and Injection, Kaloko-Honokōhau National Historical Park, Hawaiʻi"},{"id":383762,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5004/sir20215004.pdf","text":"Report","size":"13 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":383761,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5004/covrthb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kaloko-Honokōhau National Historical Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -156.03761672973633,\n 19.66829132832601\n ],\n [\n -156.01186752319336,\n 19.66829132832601\n ],\n [\n -156.01186752319336,\n 19.69350614042769\n ],\n [\n -156.03761672973633,\n 19.69350614042769\n ],\n [\n -156.03761672973633,\n 19.66829132832601\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director,
Pacific Islands Water Science Center
U.S. Geological Survey
Inouye Regional Center
1845 Wasp Blvd., B176
Honolulu, HI 96818

","tableOfContents":"","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2021-03-15","noUsgsAuthors":false,"publicationDate":"2021-03-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Oki, Delwyn S. 0000-0002-6913-8804 dsoki@usgs.gov","orcid":"https://orcid.org/0000-0002-6913-8804","contributorId":1901,"corporation":false,"usgs":true,"family":"Oki","given":"Delwyn","email":"dsoki@usgs.gov","middleInitial":"S.","affiliations":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"preferred":true,"id":811269,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70218781,"text":"sir20205141 - 2021 - Assessment of water availability in the Osage Nation using an integrated hydrologic-flow model","interactions":[],"lastModifiedDate":"2021-03-15T16:09:57.254165","indexId":"sir20205141","displayToPublicDate":"2021-03-15T07:54:17","publicationYear":"2021","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":"2020-5141","displayTitle":"Assessment of Water Availability in the Osage Nation Using an Integrated Hydrologic-Flow Model","title":"Assessment of water availability in the Osage Nation using an integrated hydrologic-flow model","docAbstract":"

The Osage Nation of northeastern Oklahoma, conterminous with Osage County, covers about 2,900 square miles. The area is primarily rural with 62 percent of the land being native prairie grass, and much of the area is used for cattle ranching and extraction of petroleum and natural gas. Protection of water rights are important to the Osage Nation because of its reliance on cattle ranching and the potential for impairment of water quality by petroleum extraction. Additionally, the potential for future population increases, demands for water from neighboring areas such as the Tulsa metropolitan area, and expansion of petroleum and natural-gas extraction on water resources of this area further the need for the Osage Nation to better understand its water availability. Therefore, the U.S. Geological Survey, in cooperation with the Osage Nation, completed a hydrologic investigation to assess the status and availability of surface-water and groundwater resources in the Osage Nation.

A transient integrated hydrologic-flow model was constructed using the U.S. Geological Survey fully integrated hydrologic-flow model called the MODFLOW One-Water Hydrologic Model. The integrated hydrologic-flow model, called the Osage Nation Integrated Hydrologic Model (ONIHM), was constructed and uses an orthogonal grid of 276 rows and 289 columns, and each grid cell measures 1,312.34 feet (ft; 400 meters) per side, with eight variably thick vertical layers that represented the alluvial and bedrock aquifers within the study area, including the alluvial aquifer, the Vamoosa-Ada aquifer, and the minor Pennsylvanian bedrock aquifers, and the confining units. Landscape and groundwater-flow processes were simulated for two periods: (1) the 1950–2014 period from January 1950 through September 2014 and (2) the forecast period from October 2014 through December 2099. The 1950–2014 period ONIHM simulated past conditions using measured or estimated inputs, and the forecast-period ONIHM simulated three separate potential forecast conditions under constant dry, average, or wet climate conditions using calibrated input values from the 1950–2014 period ONIHM.

The 1950–2014 period ONIHM was calibrated by linking the Parameter Estimation software (PEST) with the MODFLOW One-Water Hydrologic Model. PEST uses statistical parameter estimation techniques to identify the best set of parameter values to minimize the difference between measured or estimated calibration targets and their simulated equivalent values (residuals). Tikhonov regularization and singular-value decomposition-assist features of PEST were used during the calibration process. The 1950–2014 period ONIHM was calibrated to 713 measured groundwater levels at 195 wells; 95,636 estimated monthly mean groundwater levels at 124 wells; 5,307 measured streamflows at 13 streamgages; and 8,679 simulated mean monthly streamflows at 10 streamgages extracted from a surface-water model by adjusting 231 parameters. The estimated groundwater-level observations and streamflows were included as observations to improve the spatial and temporal density of observation targets during calibration. The best set of parameter values obtained during the calibration process of the 1950–2014 model was then used as the input parameter values for the forecast model simulations. A comparison of the calibration targets to their corresponding simulated values indicated that the model adequately reproduced streamflows and groundwater levels for some streamgages and wells and underestimated streamflows and groundwater levels at other locations. Measured and simulated streamflows correlated adequately with a coefficient of determination of 0.938, as did water levels with a coefficient of determination of 0.795. The 1950–2014 period ONIHM underestimated certain groundwater levels and streamflows, but generally measured or estimated calibration targets correlated well with simulated equivalents, which indicated that the model can adequately simulate the response of the hydrologic system to stresses in the 1950–2014 and forecast periods.

In the 1950–2014 period ONIHM, the calibrated mean horizontal hydraulic conductivity for layer 1 alluvial aquifer was 30.7 feet per day, and the seven lower layers had a calibrated mean horizontal hydraulic conductivity of less than 3.3 feet per day. The mean calibrated groundwater-level residual was 16.6 ft, and the mean calibrated streamflow residual of the Arkansas River at Ralston, Oklahoma, streamgage (U.S. Geological Survey station 07152500) was within 6 percent (373 cubic feet per second) of mean measured streamflow for the 1950–2014 period ONIHM.

The ONIHM simulated landscape fluxes of precipitation; groundwater applied by irrigation wells; evapotranspiration from precipitation, groundwater, and irrigation; runoff from precipitation; and deep percolation from precipitation. The largest loss of water from the landscape was evapotranspiration from precipitation with a calibrated mean annual outflow of 32 inches (in.): mean annual precipitation was about 36 in. Calibrated mean annual runoff and deep percolation (recharge to the water table) rates were 4.7 inches per year (in/yr) and 0.70 in/yr, respectively, for the 1950–2014 period ONIHM.

The calibrated 1950–2014 period ONIHM groundwater fluxes included net farm net recharge (calculated as the difference between the inflow of recharge to the water table and the outflow of evapotranspiration from the water table such that negative values indicate that evapotranspiration from the water table was greater than deep percolation [recharge to the water table] and vice versa). Net farm net recharge was the largest flux from the groundwater system with a mean annual net outflow of 153.4 cubic feet per second. Stream leakage was the largest flux to the groundwater system with a mean annual net inflow of 152.5 cubic feet per second, indicating that, on average, the groundwater/surface-water interaction was a “losing” system where stream water leaked into the subsurface and recharged the water table. Simulated monthly trends demonstrated that net stream leakage was the largest inflow to the groundwater-flow system for 10 of the 12 months; for the other 2 months (January and March), farm net recharge (January) and net storage (March) were the largest inflow to the groundwater-flow system.

A saline groundwater interface map was created for the study and compared to the water levels from the final stress period of the 1950–2014 model to identify the presence of fresh/marginal groundwater throughout the study area. Fresh/marginal groundwater was characterized as groundwater with less than 1,500 milligrams per liter of total dissolved solids. Fresh/marginal groundwater thickness ranged from 0 to 438.2 ft within the study area. The thickest regions of fresh/marginal groundwater were in the eastern part of the study area near Sand Creek, Bird Creek, and Hominy Creek and in the Arkansas River alluvial aquifer in the region downstream from the Arkansas River at Ralston, Okla.

Like the 1950–2014 model, forecast model results for the landscape indicated that transpiration from precipitation was the largest flux out of the landscape for all three forecasts, constituting 77, 73, and 58 percent of precipitation for the dry, average, and wet forecasts, respectively. The dry and average forecast landscape fluxes demonstrated similar trends and magnitudes, whereas the wet forecast landscape fluxes indicated the largest changes compared to the average forecast fluxes. Most notably, runoff increased from a mean of 1.1 and 1.6 in/yr for the dry and average forecasts, respectively, to 10 in/yr for the wet forecast. Similar changes occurred for the other wet forecast landscape fluxes.

The calibrated 1950–2014 period ONIHM simulated three forecasts to assess the effects of potential climatic changes on the hydrologic system from October 2014 to December 2099. The three forecasts simulated theoretical dry, average, and wet conditions using precipitation and potential evapotranspiration datasets from selected years in the calibrated 1950–2014 period ONIHM. Annual precipitation amounts were 26.89, 35.47, and 50.73 in. for the dry, average, and wet forecasts, respectively. Groundwater-flow component forecast results indicated that stream leakage is always a net inflow to the groundwater-flow system for dry, average, and wet conditions, meaning the study area stream network is always predominantly a “losing” regime where stream water infiltrates into the underlying aquifer. Storage was only a net outflow from the groundwater-flow system and indicated a replenishment to groundwater storage that resulted in an increase in groundwater levels only during the wet forecast. Further, these gains in groundwater storage for the wet forecast occurred only during February through June.

Mean fresh/marginal groundwater saturated thicknesses were 125 and 126 ft for the dry and average forecast conditions, respectively, and wet forecast average thickness was 145 ft and ranged from 0 to 443 ft. The spatial extents of fresh/marginal groundwater at the end of the dry, average, and wet forecast model periods (December 2099) did not change substantially from the end of the 1950–2014 model period (September 2014).

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205141","collaboration":"Prepared in cooperation with the Osage Nation","usgsCitation":"Traylor, J.P., Mashburn, S.L., Hanson, R.T., and Peterson, S.M., 2021, Assessment of water availability in the Osage Nation using an integrated hydrologic-flow model: U.S. Geological Survey Scientific Investigations Report 2020–5141, 96 p., https://doi.org/10.3133/sir20205141.","productDescription":"Report: xiii, 96 p.; 2 Interactive Figures; Data Release; Dataset","numberOfPages":"114","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-102662","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":384320,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5141/coverthb.jpg"},{"id":384321,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5141/sir20205141.pdf","text":"Report","size":"9.57 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5141"},{"id":384322,"rank":3,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/sir/2020/5141/sir20205141_figure8.pdf","text":"Figure 8 (layered)","size":"626 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5141 Figure 8","linkHelpText":"— Supergroups for the Osage Nation Integrated Hydrologic Model (note: some supergroups are hidden; in order to see a given supergroup, the reader may need to turn off layers for the overlying supergroups)."},{"id":384324,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91OKQ2C","text":"USGS data release","description":"USGS data release","linkHelpText":"MODFLOW-One Water Hydrologic Model integrated hydrologic-flow model used to evaluate water availability in the Osage Nation"},{"id":384323,"rank":4,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/sir/2020/5141/sir20205141_figure14.pdf","text":"Figure 14 (layered)","size":"711 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5141 Figure 14","linkHelpText":"— Simulated groundwater-level altitude contours for the final stress period of the calibrated Osage Nation Integrated Hydrologic Model (September 30, 2014), dry forecast (December 31, 2099), average forecast (December 31, 2099), and wet forecast (December 31, 2099). This figure is a layered PDF."},{"id":384325,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"U.S. Geological Survey National Water Information System database","linkHelpText":"— USGS water data for the Nation"}],"country":"United States","state":"Kansas, Oklahoma","otherGeospatial":"Osage Nation","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -95.99578857421875,\n 36.13565654678543\n ],\n [\n -95.99853515625,\n 37.00035919622158\n ],\n [\n -95.97930908203125,\n 37.081475648860525\n ],\n [\n -96.29241943359375,\n 37.13623498442895\n ],\n [\n -96.48193359375,\n 36.96306042436515\n ],\n [\n -96.9873046875,\n 36.94989178681327\n ],\n [\n -97.12188720703125,\n 36.6992553955527\n ],\n [\n -97.14385986328125,\n 36.36822190085111\n ],\n [\n -96.6412353515625,\n 36.213255233061844\n ],\n [\n -96.26220703125,\n 36.11125252076156\n ],\n [\n -95.99578857421875,\n 36.13565654678543\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Nebraska Water Science Center
U.S. Geological Survey
5231 South 19th Street
Lincoln, NE 68512 

","tableOfContents":"","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2021-03-15","noUsgsAuthors":false,"publicationDate":"2021-03-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Traylor, Jonathan P. 0000-0002-2008-1923 jtraylor@usgs.gov","orcid":"https://orcid.org/0000-0002-2008-1923","contributorId":5322,"corporation":false,"usgs":true,"family":"Traylor","given":"Jonathan","email":"jtraylor@usgs.gov","middleInitial":"P.","affiliations":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"preferred":true,"id":811834,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mashburn, Shana L. 0000-0001-5163-778X shanam@usgs.gov","orcid":"https://orcid.org/0000-0001-5163-778X","contributorId":2140,"corporation":false,"usgs":true,"family":"Mashburn","given":"Shana","email":"shanam@usgs.gov","middleInitial":"L.","affiliations":[{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true}],"preferred":true,"id":811835,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hanson, Randall T. 0000-0002-9819-7141 rthanson@usgs.gov","orcid":"https://orcid.org/0000-0002-9819-7141","contributorId":801,"corporation":false,"usgs":true,"family":"Hanson","given":"Randall","email":"rthanson@usgs.gov","middleInitial":"T.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":811836,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Peterson, Steven M. 0000-0002-9130-1284 speterson@usgs.gov","orcid":"https://orcid.org/0000-0002-9130-1284","contributorId":847,"corporation":false,"usgs":true,"family":"Peterson","given":"Steven","email":"speterson@usgs.gov","middleInitial":"M.","affiliations":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"preferred":true,"id":811837,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70218779,"text":"sir20215003 - 2021 - Hydrogeology and model-simulated groundwater availability in the Salt Fork Red River aquifer, southwestern Oklahoma, 1980–2015","interactions":[],"lastModifiedDate":"2025-08-14T19:33:27.82199","indexId":"sir20215003","displayToPublicDate":"2021-03-15T07:44:56","publicationYear":"2021","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":"2021-5003","displayTitle":"Hydrogeology and Model-Simulated Groundwater Availability in the Salt Fork Red River Aquifer, Southwestern Oklahoma, 1980–2015","title":"Hydrogeology and model-simulated groundwater availability in the Salt Fork Red River aquifer, southwestern Oklahoma, 1980–2015","docAbstract":"

The 1973 Oklahoma Water Law (82 OK Stat § 82-1020.5) requires that the Oklahoma Water Resources Board (OWRB) conduct hydrologic investigations of the State’s groundwater basins to support a determination of the maximum annual yield for each groundwater basin (hereinafter referred to as an “aquifer”). The maximum annual yield allocated per acre of land is known as the equal-proportionate-share (EPS) pumping rate. At present (2021), the OWRB has not yet established a maximum annual yield and EPS pumping rate for the Salt Fork Red River aquifer. To provide updated information to the OWRB that could support evaluation and determination of an appropriate maximum annual yield, the U.S. Geological Survey (USGS), in cooperation with the OWRB, conducted a hydrologic investigation and evaluated the effects of potential groundwater withdrawals on groundwater availability in the Salt Fork Red River aquifer.

The Salt Fork Red River aquifer in Greer, Harmon, and Jackson Counties of southwestern Oklahoma is composed of about 274.5 square miles of alluvium and terrace deposits associated with the Salt Fork Red River. The mean annual recharge rate to the Salt Fork Red River aquifer for the period 1980–2015 was estimated to be about 2.94 inches per year, or 10.0 percent of the mean annual precipitation for the same period (29.4 inches per year). This 1980–2015 mean annual recharge rate is equivalent to a mean annual recharge rate of about 38,000 acre-feet per year (acre-ft/yr) for the Salt Fork Red River aquifer excluding about 19,764 acres comprising the Mulberry Creek and Horse Creek terraces. The mean annual recharge rates upgradient and downgradient from USGS streamgage 07300500 Salt Fork Red River at Mangum, Okla. (hereinafter referred to as the “Mangum gage”), apportioned by aquifer area (41.5 and 58.5 percent, respectively), were about 16,000 and 22,000 acre-ft/yr, respectively. Mean annual groundwater use for the study period (1980–2015) was 3,532.7 acre-ft/yr; about 77 percent of that groundwater use was for irrigation, and about 23 percent was for public supply. Most groundwater use for irrigation was associated with wells in the Martha terrace.

A hydrogeologic framework was developed for the Salt Fork Red River aquifer and included a definition of the aquifer extent and potentiometric surface, as well as a description of the textural and hydraulic properties of aquifer materials. The hydrogeologic framework was used in the construction of the numerical groundwater-flow model of the Salt Fork Red River aquifer described in this report. A conceptual model for the Salt Fork Red River aquifer that reasonably represents the groundwater-flow system was developed to constrain the construction and calibration of the numerical model. The conceptual-model water budget estimated mean annual inflows to, and outflows from, the Salt Fork Red River aquifer for the period 1980–2015 and included a subaccounting of mean annual inflows and outflows for the portions of the aquifer that were upgradient and downgradient from the Mangum gage.

The numerical groundwater-flow model of the Salt Fork Red River aquifer was constructed by using MODFLOW-2005 with the Newton formulation solver. The model of the Salt Fork Red River aquifer was spatially discretized into 1,050 rows, 1,125 columns, about 170,000 active cells measuring 200 by 200 feet (ft), and a single convertible layer. The model was temporally discretized into 432 monthly transient stress periods (each with two time steps to improve model stability). An initial steady-state stress period represented mean annual inflows to, and outflows from, the aquifer and produced a solution that was used as the initial condition for subsequent transient stress periods as well as some groundwater-availability scenarios. The model was calibrated to water-table-altitude observations at selected wells and base-flow observations at selected streamgages.

The simulated saturated thickness of the Salt Fork Red River aquifer was determined by subtracting the altitude of the aquifer base from the simulated water-table altitude at the end of the numerical-model period (2015). The simulated saturated thickness was more than 75 ft in a paleochannel in the Dodson terrace near the Texas border. The mean aquifer thickness (sum of saturated and unsaturated) was 49.62 ft, and the mean saturated thickness was 28.55 ft. A simulated mean transmissivity of 1,024 feet squared per day was computed from the calibrated hydraulic conductivity and saturated thickness of each cell. The simulated available water in storage at the end of the numerical-model period (2015) was 526,117 acre-feet (acre-ft); about 42 percent of that total was available upgradient from the Mangum gage, and about 58 percent of that total was available downgradient from the Mangum gage (including the Mangum terrace).

Three types of groundwater-availability scenarios were run using the calibrated numerical model. These scenarios were used to (1) estimate the EPS pumping rate that ensures a minimum 20-, 40-, and 50-year life of the aquifer, (2) quantify the potential effects of projected well withdrawals on groundwater storage over a 50-year period, and (3) simulate the potential effects of a hypothetical 10-year drought on base flow and groundwater storage. The 20-, 40-, and 50-year EPS pumping rates under normal recharge conditions were about 0.51, 0.48, and 0.48 acre-foot per acre per year, respectively. Given the 155,929-acre modeled aquifer area, these rates correspond to annual yields of about 78,800, 74,900, and 74,700 acre-ft/yr, respectively. For the 20-year EPS scenario, decreasing and increasing recharge by 10 percent resulted in a 6-percent change in the EPS pumping rate in both cases; for the 40- and 50-year EPS scenarios, decreasing and increasing recharge by 10 percent resulted in a 7-percent change in the EPS pumping rate in both cases.

Projected 50-year pumping scenarios were used to simulate the effects of selected well withdrawal rates on groundwater storage of the Salt Fork Red River aquifer and base flows in the Salt Fork Red River. The effects of well withdrawals were evaluated by quantifying differences in groundwater storage and base flow in four 50-year scenarios, which applied (1) no groundwater pumping, (2) mean pumping rates for the study period (1980–2015), (3) 2015 pumping rates, and (4) increasing demand pumping rates at simulated wells. The increasing demand pumping rates assumed a cumulative 20.4-percent increase in pumping over 50 years based on 2010–60 demand projections for southwestern Oklahoma. Groundwater storage after 50 years with no pumping was 535,000 acre-ft, or 8,900 acre-ft (1.7 percent) greater than the initial groundwater storage; this groundwater storage increase is equivalent to a mean water-table-altitude increase of 0.48 ft. Groundwater storage after 50 years of pumping at the mean rate for the study period (1980–2015) was 519,900 acre-ft, or 6,200 acre-ft (1.2 percent) less than the initial groundwater storage; this groundwater storage decrease is equivalent to a mean water-table-altitude decline of 0.34 ft. Groundwater storage at the end of the 50-year period with 2015 pumping rates was 513,100 acre-ft, or 13,000 acre-ft (2.5 percent) less than the initial storage; this groundwater storage decrease is equivalent to a mean water-table-altitude decline of 0.71 ft. Groundwater storage at the end of the 50-year period with increasing demand pumping rates was 509,700 acre-ft, or 16,500 acre-ft (3.1 percent) less than the initial storage; this groundwater storage decrease is equivalent to a mean water-table-altitude decline of 0.89 ft.

A hypothetical 10-year drought scenario was used to simulate the effects of a prolonged period of reduced recharge on groundwater storage. The period January 1983–December 1992 was chosen as the simulated drought period. Drought effects were quantified by comparing the results of the drought scenario to those of the calibrated numerical model (no drought) at the end of the simulated drought period (1992). To simulate the hypothetical drought, recharge in the calibrated numerical model was reduced by 50 percent during the simulated drought period (1983–92). Upstream inflows from the Salt Fork Red River, Turkey Creek, and Bitter Creek were reduced by 75 percent. Groundwater storage at the end of the drought period (1992) was 479,200 acre-ft, or 53,200 acre-ft (10.0 percent) less than the groundwater storage of the calibrated numerical model at the end of the drought period. This decrease in groundwater storage is equivalent to a mean water-table-altitude decline of 2.9 ft. At the end of the 10-year hypothetical drought period, simulated base flows at the Mangum gage and USGS streamgage 07301110 Salt Fork Red River near Elmer, Okla., had decreased by about 80 and 70 percent, respectively.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215003","issn":"2328-0328","collaboration":"Prepared in cooperation with the Oklahoma Water Resources Board","usgsCitation":"Smith, S.J., Ellis, J.H., Paizis, N.C., Becker, C.J., Wagner, D.L., Correll, J.S., and Hernandez, R.J., 2021, Hydrogeology and model-simulated groundwater availability in the Salt Fork Red River aquifer, southwestern Oklahoma, 1980–2015 (ver. 1.1, June 2025): U.S. Geological Survey Scientific Investigations Report 2021–5003, 85 p., https://doi.org/10.3133/sir20215003.","productDescription":"Report: xi, 85 p.; Data Release","numberOfPages":"102","onlineOnly":"Y","ipdsId":"IP-117037","costCenters":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":494144,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_111244.htm","linkFileType":{"id":5,"text":"html"}},{"id":490592,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2021/5003/VersionHistory.txt","linkFileType":{"id":2,"text":"txt"}},{"id":384305,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5003/sir20215003.pdf","text":"Report","size":"28.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5003"},{"id":384306,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P927IAO1","text":"USGS data release","description":"USGS Data Release","linkHelpText":"MODFLOW-NWT model used in simulation of groundwater availability in the Salt Fork Red River aquifer, southwestern Oklahoma, 1980–2015"},{"id":384304,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5003/coverthb1.jpg"}],"country":"United States","state":"Oklahoma","otherGeospatial":"Salt Fork Red River Aquifer","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -99.9810791015625,\n 34.025347738147936\n ],\n [\n -97.97882080078125,\n 34.025347738147936\n ],\n [\n -97.97882080078125,\n 35.01425155045957\n ],\n [\n -99.9810791015625,\n 35.01425155045957\n ],\n [\n -99.9810791015625,\n 34.025347738147936\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: March 15, 2021; Version 1.1: June 13, 2025","contact":"

Director, Oklahoma-Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, Texas 78754-4501

Contact Us- USGS Publications Warehouse

","tableOfContents":"","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2021-03-15","revisedDate":"2025-06-13","noUsgsAuthors":false,"publicationDate":"2021-03-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Smith, S. Jerrod 0000-0002-9379-8167 sjsmith@usgs.gov","orcid":"https://orcid.org/0000-0002-9379-8167","contributorId":981,"corporation":false,"usgs":true,"family":"Smith","given":"S.","email":"sjsmith@usgs.gov","middleInitial":"Jerrod","affiliations":[{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true}],"preferred":true,"id":811826,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ellis, John H. 0000-0001-7161-3136 jellis@usgs.gov","orcid":"https://orcid.org/0000-0001-7161-3136","contributorId":177759,"corporation":false,"usgs":true,"family":"Ellis","given":"John","email":"jellis@usgs.gov","middleInitial":"H.","affiliations":[],"preferred":false,"id":811827,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Paizis, Nicole 0000-0003-3037-2668","orcid":"https://orcid.org/0000-0003-3037-2668","contributorId":255116,"corporation":false,"usgs":true,"family":"Paizis","given":"Nicole","email":"","affiliations":[{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true}],"preferred":true,"id":811828,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Becker, Carol 0000-0001-6652-4542 cjbecker@usgs.gov","orcid":"https://orcid.org/0000-0001-6652-4542","contributorId":2489,"corporation":false,"usgs":true,"family":"Becker","given":"Carol","email":"cjbecker@usgs.gov","affiliations":[{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true}],"preferred":true,"id":811829,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wagner, Derrick L.","contributorId":177762,"corporation":false,"usgs":false,"family":"Wagner","given":"Derrick L.","affiliations":[],"preferred":false,"id":811830,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Correll, Jessica S. 0000-0000-0000-0001","orcid":"https://orcid.org/0000-0000-0000-0001","contributorId":37253,"corporation":false,"usgs":true,"family":"Correll","given":"Jessica","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":811831,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hernandez, R. Jacob","contributorId":255117,"corporation":false,"usgs":false,"family":"Hernandez","given":"R.","email":"","middleInitial":"Jacob","affiliations":[],"preferred":false,"id":811832,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70219184,"text":"70219184 - 2021 - Rapid strain release on the Bear River fault zone, Utah–Wyoming—The impact of preexisting structure on the rupture behavior of a new normal fault","interactions":[],"lastModifiedDate":"2021-03-30T12:44:59.505994","indexId":"70219184","displayToPublicDate":"2021-03-15T07:39:55","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3525,"text":"Tectonophysics","active":true,"publicationSubtype":{"id":10}},"title":"Rapid strain release on the Bear River fault zone, Utah–Wyoming—The impact of preexisting structure on the rupture behavior of a new normal fault","docAbstract":"

Earthquake clustering (grouping in space and time) is a widely observed mode of strain release in the upper crust, although this behavior on individual faults is a departure from classic elastic rebound theory. In this study, we consider factors responsible for a cluster of earthquakes on the Bear River fault zone (BRF), a recently activated, 44-km-long normal fault on the eastern margin of Basin and Range extension in the Rocky Mountains. The entire surface-rupturing history of the BRF, as gleaned from paleoseismic and geomorphic observations, began only 4500 years ago and consists of at least three large events. Rupture of the BRF is spatially complex and is clearly conditioned by preexisting structure. In particular, where the south end of the fault intersects older thrust faults and upturned strata along the south-dipping flank of the Precambrian basement-cored Uinta arch, the main trace ends abruptly in a set of orthogonal splays that accommodate down-dropping of a large hanging-wall graben against the arch. We hypothesize that the geomechanically strong Uinta arch crustal block impeded the development of the BRF and, over time, enabled a significant accumulation of elastic strain energy, eventually giving rise to a pulse of strain release in the mid- to late Holocene. We surmise that variations in fault strength, both in space and time, is a cause of earthquake clustering on the BRF and on other faults that are structurally and tectonically immature. The first two earthquakes on the BRF occurred during the same period of time as a regional cluster of earthquakes in the Middle Rocky Mountains, suggesting that isolated faults in this slowly extending region interact through widespread changes in stress conditions.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.tecto.2021.228819","usgsCitation":"Hecker, S., Schwartz, D.P., and DeLong, S.B., 2021, Rapid strain release on the Bear River fault zone, Utah–Wyoming—The impact of preexisting structure on the rupture behavior of a new normal fault: Tectonophysics, v. 808, 228819, 18 p., https://doi.org/10.1016/j.tecto.2021.228819.","productDescription":"228819, 18 p.","ipdsId":"IP-121753","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":453083,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.tecto.2021.228819","text":"Publisher Index Page"},{"id":384757,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Utah, Wyoming","otherGeospatial":"Bear River fault zone","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.9833984375,\n 39.605688178320804\n ],\n [\n -109.3798828125,\n 39.605688178320804\n ],\n [\n -109.3798828125,\n 43.929549935614595\n ],\n [\n -112.9833984375,\n 43.929549935614595\n ],\n [\n -112.9833984375,\n 39.605688178320804\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"808","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hecker, Suzanne 0000-0002-5054-372X","orcid":"https://orcid.org/0000-0002-5054-372X","contributorId":205568,"corporation":false,"usgs":true,"family":"Hecker","given":"Suzanne","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":813146,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schwartz, David P. 0000-0001-5193-9200 dschwartz@usgs.gov","orcid":"https://orcid.org/0000-0001-5193-9200","contributorId":1940,"corporation":false,"usgs":true,"family":"Schwartz","given":"David","email":"dschwartz@usgs.gov","middleInitial":"P.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":813147,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DeLong, Stephen B. 0000-0002-0945-2172 sdelong@usgs.gov","orcid":"https://orcid.org/0000-0002-0945-2172","contributorId":5240,"corporation":false,"usgs":true,"family":"DeLong","given":"Stephen","email":"sdelong@usgs.gov","middleInitial":"B.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":813148,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70219910,"text":"70219910 - 2021 - The evolving perceptual model of streamflow generation at the Panola Mountain Research Watershed","interactions":[],"lastModifiedDate":"2021-04-19T11:51:47.992809","indexId":"70219910","displayToPublicDate":"2021-03-15T06:56:10","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"The evolving perceptual model of streamflow generation at the Panola Mountain Research Watershed","docAbstract":"

The Panola Mountain Research Watershed (PMRW) is a 41‐hectare forested catchment within the Piedmont Province of the Southeastern United States. Observations, experimentation, and numerical modelling have been conducted at Panola over the past 35 years. But to date, these studies have not been fully incorporated into a more comprehensive synthesis. Here we describe the evolving perceptual understanding of streamflow generation mechanisms at the PMRW. We show how the long‐term study has enabled insights that were initially unforeseen but are also unachievable in short‐term studies. In particular, we discuss how the accumulation of field evidence, detailed site characterization, and modelling enabled a priori hypotheses to be formed, later rejected, and then further refined through repeated field campaigns. The extensive characterization of the soil and bedrock provided robust process insights not otherwise achievable from hydrometric measurements and numerical modelling alone. We focus on two major aspects of streamflow generation: the role of hillslopes (and their connection to the riparian zone) and the role of catchment storage in controlling fluxes and transit times of water in the catchment. Finally, we present location‐independent hypotheses based on our findings at PMRW and suggest ways to assess the representativeness of PMRW in the broader context of headwater watersheds.

","language":"English","publisher":"Wiley","doi":"10.1002/hyp.14127","usgsCitation":"Aulenbach, B.T., Hooper, R.P., van Meerveld, H.J., Burns, D., Freer, J.E., Shanley, J.B., Huntington, T., McDonnell, J.J., and Norman E. Peters, 2021, The evolving perceptual model of streamflow generation at the Panola Mountain Research Watershed: Hydrological Processes, v. 35, no. 4, e14127, 14 p., https://doi.org/10.1002/hyp.14127.","productDescription":"e14127, 14 p.","ipdsId":"IP-125152","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":385149,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Georgia","city":"Atlanta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.78149414062499,\n 33.25706340236547\n ],\n [\n -83.770751953125,\n 33.25706340236547\n ],\n [\n -83.770751953125,\n 34.288991865037524\n ],\n [\n -84.78149414062499,\n 34.288991865037524\n ],\n [\n -84.78149414062499,\n 33.25706340236547\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"35","issue":"4","noUsgsAuthors":false,"publicationDate":"2021-04-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Aulenbach, Brent T. 0000-0003-2863-1288 btaulenb@usgs.gov","orcid":"https://orcid.org/0000-0003-2863-1288","contributorId":3057,"corporation":false,"usgs":true,"family":"Aulenbach","given":"Brent","email":"btaulenb@usgs.gov","middleInitial":"T.","affiliations":[{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":814371,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hooper, Richard P 0000-0002-3329-9622","orcid":"https://orcid.org/0000-0002-3329-9622","contributorId":257488,"corporation":false,"usgs":false,"family":"Hooper","given":"Richard","email":"","middleInitial":"P","affiliations":[{"id":52045,"text":"Tufts University, Department of Civil and Environmental Engineering","active":true,"usgs":false}],"preferred":false,"id":814372,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"van Meerveld, H. J. 0000-0002-7547-3270","orcid":"https://orcid.org/0000-0002-7547-3270","contributorId":257489,"corporation":false,"usgs":false,"family":"van Meerveld","given":"H.","email":"","middleInitial":"J.","affiliations":[{"id":52048,"text":"University of Zurich, Department of Geography","active":true,"usgs":false}],"preferred":false,"id":814373,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Burns, Douglas A. 0000-0001-6516-2869","orcid":"https://orcid.org/0000-0001-6516-2869","contributorId":202943,"corporation":false,"usgs":true,"family":"Burns","given":"Douglas A.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":814374,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Freer, James E. 0000-0001-6388-7890","orcid":"https://orcid.org/0000-0001-6388-7890","contributorId":188139,"corporation":false,"usgs":false,"family":"Freer","given":"James","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":814375,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Shanley, James B. 0000-0002-4234-3437 jshanley@usgs.gov","orcid":"https://orcid.org/0000-0002-4234-3437","contributorId":1953,"corporation":false,"usgs":true,"family":"Shanley","given":"James","email":"jshanley@usgs.gov","middleInitial":"B.","affiliations":[{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":814376,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Huntington, Thomas G. 0000-0002-9427-3530","orcid":"https://orcid.org/0000-0002-9427-3530","contributorId":218737,"corporation":false,"usgs":true,"family":"Huntington","given":"Thomas G.","affiliations":[{"id":371,"text":"Maine Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":814377,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"McDonnell, Jeffery J. 0000-0002-3880-3162","orcid":"https://orcid.org/0000-0002-3880-3162","contributorId":62723,"corporation":false,"usgs":false,"family":"McDonnell","given":"Jeffery","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":814378,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Norman E. Peters 0000-0002-0637-9424","orcid":"https://orcid.org/0000-0002-0637-9424","contributorId":207130,"corporation":false,"usgs":false,"family":"Norman E. Peters","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":814379,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70221418,"text":"70221418 - 2021 - Using bottom trawls to monitor subsurface water clarity in marine ecosystems","interactions":[],"lastModifiedDate":"2021-06-15T11:46:28.05606","indexId":"70221418","displayToPublicDate":"2021-03-15T06:44:29","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3194,"text":"Progress in Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"Using bottom trawls to monitor subsurface water clarity in marine ecosystems","docAbstract":"

Biophysical processes that affect subsurface water clarity play a key role in ecosystem function. However, subsurface water clarity is poorly monitored in marine ecosystems because doing so requires in-situ sampling that is logistically difficult to conduct and sustain. Novel solutions are thus needed to improve monitoring of subsurface water clarity. To that end, we developed a sampling method and data processing algorithm that enable the use of bottom trawl fishing gear as a platform for conducting subsurface water clarity monitoring using trawl-mounted irradiance sensors without disruption to fishing operations. The algorithm applies quality control checks to irradiance measurements and calculates the downwelling diffuse attenuation coefficient, Kd, and optical depth, ζ– apparent optical properties (AOPs) that characterize the rate of decrease in downwelling irradiance and relative irradiance transmission to depth, respectively. We applied our algorithm to irradiance measurements, obtained using bottom-trawl-mounted archival tags equipped with a photodiode collected during NOAA’s Alaska Fisheries Science Center annual summer bottom trawl surveys of the eastern Bering Sea continental shelf from 2004 to 2018. We validated our AOPs by quantitatively comparing surface-weighted Kd from tags to the multi-sensor Kd(490) product from the Ocean Colour Climate Change Initiative project (OC-CCI) and qualitatively evaluating whether tag Kd was consistent with patterns of subsurface chlorophyll-a concentrations predicted by a coupled regional physical-biological model (Bering10K-BESTNPZ). We additionally examined patterns and trends in water clarity in the eastern Bering Sea. Key findings are: 1) water clarity decreased significantly from 2004 to 2018; 2) a recurrent, pycnocline-associated, maximum in Kd occurred over much of the northwestern shelf, putatively due to a subsurface chlorophyll maximum; and 3) a turbid bottom layer (nepheloid layer) was present over a large portion of the eastern Bering Sea shelf. Our study demonstrates that bottom trawls can provide a useful platform for monitoring water clarity, especially when trawling is conducted as part of a systematic stock assessment survey.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.pocean.2021.102554","usgsCitation":"Rohan, S.K., Kotwicki, S., Kearney, K.A., Schulien, J.A., Laman, E.A., Cokelet, E.D., Beauchamp, D., Britt, L.L., Aydin, K.Y., and Zador, S.G., 2021, Using bottom trawls to monitor subsurface water clarity in marine ecosystems: Progress in Oceanography, v. 194, 102554, 17 p., https://doi.org/10.1016/j.pocean.2021.102554.","productDescription":"102554, 17 p.","ipdsId":"IP-122124","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":453091,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.pocean.2021.102554","text":"Publisher Index Page"},{"id":386486,"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 \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -167.34375,\n 51.83577752045248\n ],\n [\n -154.68749999999997,\n 51.83577752045248\n ],\n [\n -154.68749999999997,\n 60.930432202923335\n ],\n [\n -167.34375,\n 60.930432202923335\n ],\n [\n -167.34375,\n 51.83577752045248\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"194","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Rohan, Sean K.","contributorId":260255,"corporation":false,"usgs":false,"family":"Rohan","given":"Sean","email":"","middleInitial":"K.","affiliations":[{"id":52548,"text":"National Marine Fisheries Service, Alaska Fisheries Science Center, National Oceanic and Atmospheric Administration, 7600 Sand Point Way NE, Seattle, WA 98115, USA","active":true,"usgs":false}],"preferred":false,"id":817636,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kotwicki, Stan","contributorId":260256,"corporation":false,"usgs":false,"family":"Kotwicki","given":"Stan","email":"","affiliations":[{"id":52548,"text":"National Marine Fisheries Service, Alaska Fisheries Science Center, National Oceanic and Atmospheric Administration, 7600 Sand Point Way NE, Seattle, WA 98115, USA","active":true,"usgs":false}],"preferred":false,"id":817637,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kearney, Kelly A.","contributorId":260257,"corporation":false,"usgs":false,"family":"Kearney","given":"Kelly","email":"","middleInitial":"A.","affiliations":[{"id":52550,"text":"University of Washington, Joint Institute for the Study of the Atmosphere and Oceans, Seattle, WA, USA","active":true,"usgs":false}],"preferred":false,"id":817638,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schulien, Jennifer A 0000-0003-1428-9370","orcid":"https://orcid.org/0000-0003-1428-9370","contributorId":260258,"corporation":false,"usgs":true,"family":"Schulien","given":"Jennifer","email":"","middleInitial":"A","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":817639,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Laman, Edward A.","contributorId":260259,"corporation":false,"usgs":false,"family":"Laman","given":"Edward","email":"","middleInitial":"A.","affiliations":[{"id":52548,"text":"National Marine Fisheries Service, Alaska Fisheries Science Center, National Oceanic and Atmospheric Administration, 7600 Sand Point Way NE, Seattle, WA 98115, USA","active":true,"usgs":false}],"preferred":false,"id":817640,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cokelet, Edward D.","contributorId":260260,"corporation":false,"usgs":false,"family":"Cokelet","given":"Edward","email":"","middleInitial":"D.","affiliations":[{"id":52552,"text":"Pacific Marine Environmental Laboratory, National Oceanic and Atmospheric Administration, 7600 Sand Point Way NE, Seattle, WA 98115, USA","active":true,"usgs":false}],"preferred":false,"id":817641,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Beauchamp, David 0000-0002-3592-8381","orcid":"https://orcid.org/0000-0002-3592-8381","contributorId":217816,"corporation":false,"usgs":true,"family":"Beauchamp","given":"David","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":817642,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Britt, Lyle L.","contributorId":260261,"corporation":false,"usgs":false,"family":"Britt","given":"Lyle","email":"","middleInitial":"L.","affiliations":[{"id":52548,"text":"National Marine Fisheries Service, Alaska Fisheries Science Center, National Oceanic and Atmospheric Administration, 7600 Sand Point Way NE, Seattle, WA 98115, USA","active":true,"usgs":false}],"preferred":false,"id":817643,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Aydin, Kerim Y.","contributorId":260262,"corporation":false,"usgs":false,"family":"Aydin","given":"Kerim","email":"","middleInitial":"Y.","affiliations":[{"id":52548,"text":"National Marine Fisheries Service, Alaska Fisheries Science Center, National Oceanic and Atmospheric Administration, 7600 Sand Point Way NE, Seattle, WA 98115, USA","active":true,"usgs":false}],"preferred":false,"id":817644,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Zador, Stephani G.","contributorId":201047,"corporation":false,"usgs":false,"family":"Zador","given":"Stephani","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":817645,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70223354,"text":"70223354 - 2021 - Landscape level effects of invasive plants and animals on water infiltration through Hawaiian tropical forests","interactions":[],"lastModifiedDate":"2021-08-24T12:41:21.483952","indexId":"70223354","displayToPublicDate":"2021-03-13T07:39:14","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1018,"text":"Biological Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Landscape level effects of invasive plants and animals on water infiltration through Hawaiian tropical forests","docAbstract":"

Watershed degradation due to invasion threatens downstream water flows and associated ecosystem services. While this topic has been studied across landscapes that have undergone invasive-driven state changes (e.g., native forest to invaded grassland), it is less well understood in ecosystems experiencing within-system invasion (e.g. native forest to invaded forest). To address this subject, we conducted an integrated ecological and ecohydrological study in tropical forests impacted by invasive plants and animals. We measured soil infiltration capacity in multiple fenced (i.e., ungulate-free)/unfenced and native/invaded forest site pairs along moisture and substrate age gradients across Hawaii to explore the effects of invasion on hydrological processes within tropical forests. We also characterized forest composition, structure and soil characteristics at these sites to assess the direct and vegetation-mediated impacts of invasive species on infiltration capacity. Our models show that invasive ungulates negatively affect soil infiltration capacity consistently across the wide moisture and substrate age gradients considered. Additionally, several soil characteristics known to be affected by invasive ungulates were associated with local infiltration rates, indicating that the long-term secondary effects of high ungulate densities in tropical forests may be stronger than effects observed in this study. The effect of invasive plants on infiltration was complex and likely to depend on their physiognomy within existing forest community structure. These results provide clear evidence for managers that invasive ungulate control efforts can improve ecohydrological function of mesic and wet forest systems critical to protecting downstream and nearshore resources and maintaining groundwater recharge.

","language":"English","publisher":"Springer","doi":"10.1007/s10530-021-02494-8","usgsCitation":"Fortini, L., Leopold, C., Perkins, K., Chadwick, O.A., Yelenik, S.G., Jacobi, J.D., Bishaw, K., and Gregg, M., 2021, Landscape level effects of invasive plants and animals on water infiltration through Hawaiian tropical forests: Biological Invasions, v. 23, p. 2155-2172, https://doi.org/10.1007/s10530-021-02494-8.","productDescription":"18 p.","startPage":"2155","endPage":"2172","ipdsId":"IP-124144","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":388408,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[-155.778234,20.245743],[-155.772734,20.245409],[-155.746893,20.232325],[-155.737004,20.222773],[-155.735822,20.212417],[-155.732704,20.205392],[-155.653966,20.16736],[-155.630382,20.146916],[-155.624565,20.145911],[-155.607797,20.137987],[-155.600909,20.126573],[-155.598033,20.124539],[-155.590923,20.122497],[-155.58168,20.123617],[-155.568368,20.130545],[-155.558933,20.13157],[-155.523661,20.120028],[-155.516795,20.11523],[-155.502561,20.114155],[-155.468211,20.104296],[-155.443957,20.095318],[-155.405459,20.078772],[-155.4024,20.075541],[-155.387578,20.067119],[-155.33021,20.038517],[-155.29548,20.024438],[-155.282629,20.021969],[-155.270316,20.014525],[-155.240933,19.990173],[-155.204486,19.969438],[-155.194593,19.958368],[-155.179939,19.949372],[-155.149215,19.922872],[-155.144394,19.920523],[-155.131235,19.906801],[-155.124618,19.897288],[-155.12175,19.886099],[-155.107541,19.872467],[-155.098716,19.867811],[-155.095032,19.867882],[-155.086341,19.855399],[-155.084357,19.849736],[-155.085674,19.838584],[-155.088979,19.826656],[-155.094414,19.81491],[-155.09207,19.799409],[-155.091216,19.776368],[-155.093517,19.771832],[-155.093387,19.737751],[-155.087118,19.728013],[-155.079426,19.726193],[-155.063972,19.728917],[-155.045382,19.739824],[-155.006423,19.739286],[-154.997278,19.72858],[-154.987168,19.708524],[-154.981102,19.690687],[-154.984718,19.672161],[-154.983778,19.641647],[-154.974342,19.633201],[-154.963933,19.627605],[-154.950359,19.626461],[-154.947874,19.62425],[-154.947718,19.621947],[-154.951014,19.613614],[-154.947106,19.604856],[-154.93394,19.597505],[-154.928205,19.592702],[-154.924422,19.586553],[-154.903542,19.570622],[-154.875,19.556797],[-154.852618,19.549172],[-154.837384,19.538354],[-154.826732,19.537626],[-154.814417,19.53009],[-154.809561,19.522377],[-154.809379,19.519086],[-154.822968,19.48129],[-154.838545,19.463642],[-154.86854,19.438126],[-154.887817,19.426425],[-154.928772,19.397646],[-154.944185,19.381852],[-154.964619,19.365646],[-154.980861,19.349291],[-155.020537,19.331317],[-155.061729,19.316636],[-155.113272,19.290613],[-155.1337,19.276099],[-155.159635,19.268375],[-155.172413,19.26906],[-155.187427,19.266156],[-155.19626,19.261295],[-155.205892,19.260907],[-155.243961,19.271313],[-155.264619,19.274213],[-155.296761,19.266289],[-155.303808,19.261835],[-155.31337,19.250698],[-155.341268,19.234039],[-155.349148,19.217756],[-155.360631,19.20893],[-155.378638,19.202435],[-155.390701,19.201171],[-155.417369,19.187858],[-155.427093,19.179546],[-155.432519,19.170623],[-155.453516,19.151952],[-155.465663,19.146964],[-155.505281,19.137908],[-155.51474,19.132501],[-155.51214,19.128174],[-155.512137,19.124296],[-155.519652,19.117025],[-155.526136,19.115889],[-155.528902,19.11371],[-155.544806,19.091059],[-155.551129,19.08878],[-155.557817,19.08213],[-155.555326,19.069377],[-155.555177,19.053932],[-155.557371,19.046565],[-155.566446,19.032531],[-155.576599,19.027412],[-155.581903,19.02224],[-155.596032,18.998833],[-155.596521,18.980654],[-155.601866,18.971572],[-155.613966,18.970399],[-155.625256,18.961951],[-155.625,18.959934],[-155.638054,18.941723],[-155.658486,18.924835],[-155.672005,18.917466],[-155.681825,18.918694],[-155.687716,18.923358],[-155.690171,18.932195],[-155.693117,18.940542],[-155.726043,18.969437],[-155.763598,18.981837],[-155.806109,19.013967],[-155.853943,19.023762],[-155.88155,19.036644],[-155.884077,19.039266],[-155.886278,19.05576],[-155.903693,19.080777],[-155.908355,19.081138],[-155.921389,19.121183],[-155.917292,19.155963],[-155.903339,19.217792],[-155.90491,19.230147],[-155.902565,19.258427],[-155.895435,19.274639],[-155.890842,19.298905],[-155.887356,19.337101],[-155.888701,19.348031],[-155.898792,19.377984],[-155.913849,19.401107],[-155.909087,19.415455],[-155.921707,19.43055],[-155.924269,19.438794],[-155.925166,19.468081],[-155.922609,19.478611],[-155.924124,19.481406],[-155.930523,19.484921],[-155.935641,19.485628],[-155.936403,19.481905],[-155.939145,19.481577],[-155.95149,19.486649],[-155.952897,19.488805],[-155.953663,19.510003],[-155.960457,19.546612],[-155.962264,19.551779],[-155.965211,19.554745],[-155.96935,19.555963],[-155.970969,19.586328],[-155.978206,19.608159],[-155.997728,19.642816],[-156.028982,19.650098],[-156.032928,19.653905],[-156.034994,19.65936],[-156.033326,19.66923],[-156.027427,19.672154],[-156.029281,19.678908],[-156.036079,19.690252],[-156.04796,19.698938],[-156.051652,19.703649],[-156.052485,19.718667],[-156.064364,19.730766],[-156.05722,19.742536],[-156.052315,19.756836],[-156.049651,19.780452],[-156.021732,19.8022],[-156.006267,19.81758],[-155.982821,19.845651],[-155.976651,19.85053],[-155.964817,19.855183],[-155.949251,19.857034],[-155.945297,19.853443],[-155.940311,19.852305],[-155.925843,19.858928],[-155.926938,19.870221],[-155.92549,19.875],[-155.915662,19.887126],[-155.901987,19.912081],[-155.894099,19.923135],[-155.894474,19.926927],[-155.892533,19.932162],[-155.866919,19.954172],[-155.856588,19.968885],[-155.840708,19.976952],[-155.838692,19.975527],[-155.835312,19.976078],[-155.831948,19.982775],[-155.828965,19.995542],[-155.825473,20.025944],[-155.828182,20.035424],[-155.850385,20.062506],[-155.866931,20.078652],[-155.88419,20.10675],[-155.899149,20.145728],[-155.906035,20.205157],[-155.901452,20.235787],[-155.890663,20.25524],[-155.882631,20.263026],[-155.873921,20.267744],[-155.853293,20.271548],[-155.811459,20.26032],[-155.783242,20.246395],[-155.778234,20.245743]]],[[[-157.789581,21.438396],[-157.789734,21.437679],[-157.789276,21.435833],[-157.790543,21.434313],[-157.791718,21.434881],[-157.793045,21.43391],[-157.793167,21.43574],[-157.791565,21.43651],[-157.791779,21.437752],[-157.793289,21.437658],[-157.791779,21.438435],[-157.791092,21.438442],[-157.790741,21.43874],[-157.789581,21.438396]]],[[[-160.125,21.95909],[-160.122262,21.962881],[-160.112746,21.995245],[-160.09645,22.001489],[-160.072123,22.003334],[-160.058543,21.99638],[-160.051992,21.983681],[-160.052729,21.980321],[-160.056336,21.977939],[-160.060549,21.976729],[-160.063349,21.978354],[-160.065811,21.976562],[-160.078393,21.955153],[-160.085787,21.927295],[-160.080012,21.910808],[-160.079065,21.89608],[-160.098897,21.884711],[-160.124283,21.876789],[-160.147609,21.872814],[-160.16162,21.864746],[-160.174796,21.846923],[-160.189782,21.82245],[-160.205211,21.789053],[-160.200427,21.786479],[-160.205851,21.779518],[-160.218044,21.783755],[-160.23478,21.795418],[-160.24961,21.815145],[-160.244943,21.848943],[-160.231028,21.886263],[-160.228965,21.889117],[-160.21383,21.899193],[-160.205528,21.907507],[-160.202716,21.912422],[-160.190158,21.923592],[-160.167471,21.932863],[-160.13705,21.948632],[-160.127302,21.955508],[-160.125,21.95909]]],[[[-159.431707,22.220015],[-159.40732,22.230555],[-159.388119,22.223252],[-159.385977,22.220009],[-159.367563,22.214906],[-159.359842,22.214831],[-159.357227,22.217744],[-159.353795,22.217669],[-159.339964,22.208519],[-159.315613,22.186817],[-159.308855,22.155555],[-159.297808,22.149748],[-159.295875,22.144547],[-159.295271,22.13039],[-159.297143,22.113815],[-159.317451,22.080944],[-159.321667,22.063411],[-159.324775,22.05867],[-159.333267,22.054639],[-159.337996,22.046575],[-159.341401,22.028978],[-159.333224,21.973005],[-159.333109,21.964176],[-159.334714,21.961099],[-159.350828,21.950817],[-159.356613,21.939546],[-159.382349,21.924479],[-159.408284,21.897781],[-159.425862,21.884527],[-159.446599,21.871647],[-159.471962,21.88292],[-159.490914,21.888898],[-159.517973,21.890996],[-159.555415,21.891355],[-159.574991,21.896585],[-159.577784,21.900486],[-159.584272,21.899038],[-159.610241,21.898356],[-159.637849,21.917166],[-159.648132,21.93297],[-159.671872,21.957038],[-159.681493,21.960054],[-159.705255,21.963427],[-159.72014,21.970789],[-159.758218,21.980694],[-159.765735,21.986593],[-159.788139,22.018411],[-159.790932,22.031177],[-159.786543,22.06369],[-159.780096,22.072567],[-159.748159,22.100388],[-159.741223,22.115666],[-159.733457,22.142756],[-159.726043,22.152171],[-159.699978,22.165252],[-159.66984,22.170782],[-159.608794,22.207878],[-159.591596,22.219456],[-159.583965,22.22668],[-159.559643,22.229185],[-159.554166,22.228212],[-159.548594,22.226263],[-159.54115,22.216764],[-159.534594,22.219403],[-159.523769,22.217602],[-159.51941,22.215646],[-159.518348,22.211182],[-159.515574,22.208008],[-159.507811,22.205987],[-159.501055,22.211064],[-159.500821,22.225538],[-159.488558,22.23317],[-159.480158,22.232715],[-159.467007,22.226529],[-159.45619,22.228811],[-159.441809,22.226321],[-159.431707,22.220015]]],[[[-157.014553,21.185503],[-156.999108,21.182221],[-156.991318,21.18551],[-156.987768,21.18935],[-156.982343,21.207798],[-156.984464,21.210063],[-156.984032,21.212198],[-156.974002,21.218503],[-156.969064,21.217018],[-156.962847,21.212131],[-156.951654,21.191662],[-156.950808,21.182636],[-156.946159,21.175963],[-156.918248,21.168279],[-156.903466,21.16421],[-156.898174,21.16594],[-156.89613,21.169561],[-156.896537,21.172208],[-156.867944,21.16452],[-156.841592,21.167926],[-156.821944,21.174693],[-156.771495,21.180053],[-156.742231,21.176214],[-156.738341,21.17202],[-156.736648,21.16188],[-156.719386,21.163911],[-156.712696,21.161547],[-156.714158,21.152238],[-156.726033,21.13236],[-156.748932,21.1086],[-156.775995,21.089751],[-156.790815,21.081686],[-156.794136,21.075796],[-156.835351,21.06336],[-156.865795,21.057801],[-156.877137,21.0493],[-156.891946,21.051831],[-156.89517,21.055771],[-156.953719,21.067761],[-157.00295,21.083282],[-157.02617,21.089015],[-157.032045,21.091094],[-157.037667,21.097864],[-157.079696,21.105835],[-157.095373,21.10636],[-157.125,21.1026],[-157.143483,21.096632],[-157.254061,21.090601],[-157.298054,21.096917],[-157.313343,21.105755],[-157.299187,21.132488],[-157.299471,21.135972],[-157.293774,21.146127],[-157.284346,21.157755],[-157.276474,21.163175],[-157.274504,21.162762],[-157.259911,21.174875],[-157.254709,21.181376],[-157.251007,21.190952],[-157.25026,21.207739],[-157.256935,21.215665],[-157.261457,21.217661],[-157.263163,21.220873],[-157.26069,21.225684],[-157.257085,21.227268],[-157.241534,21.220969],[-157.226445,21.220185],[-157.212082,21.221848],[-157.202125,21.219298],[-157.192439,21.207644],[-157.185553,21.205602],[-157.157103,21.200706],[-157.148125,21.200745],[-157.144627,21.202555],[-157.128207,21.201488],[-157.113438,21.197375],[-157.097971,21.198012],[-157.064264,21.189076],[-157.053053,21.188754],[-157.047757,21.190739],[-157.039987,21.190909],[-157.014553,21.185503]]],[[[-156.544169,20.522802],[-156.550016,20.520273],[-156.559994,20.521892],[-156.586238,20.511711],[-156.603844,20.524372],[-156.631143,20.514943],[-156.642347,20.508285],[-156.647464,20.512017],[-156.668809,20.504738],[-156.682939,20.506775],[-156.703673,20.527237],[-156.702265,20.532451],[-156.696662,20.541646],[-156.6801,20.557021],[-156.651567,20.565574],[-156.614598,20.587109],[-156.610734,20.59377],[-156.576871,20.60657],[-156.56714,20.604895],[-156.553604,20.594729],[-156.543034,20.580115],[-156.542808,20.573674],[-156.548909,20.56859],[-156.556021,20.542657],[-156.553018,20.539382],[-156.540189,20.534741],[-156.539643,20.527644],[-156.544169,20.522802]]],[[[-156.612012,21.02477],[-156.612065,21.027273],[-156.606238,21.034371],[-156.592256,21.03288],[-156.580448,21.020172],[-156.562773,21.016167],[-156.549813,21.004939],[-156.546291,21.005082],[-156.528246,20.967757],[-156.518707,20.954662],[-156.512226,20.95128],[-156.510391,20.940358],[-156.507913,20.937886],[-156.49948,20.934577],[-156.495883,20.928005],[-156.493263,20.916011],[-156.481055,20.898199],[-156.474796,20.894546],[-156.422668,20.911631],[-156.386045,20.919563],[-156.374297,20.927616],[-156.370729,20.932669],[-156.352649,20.941414],[-156.345655,20.941596],[-156.342365,20.938737],[-156.332817,20.94645],[-156.324578,20.950184],[-156.307198,20.942739],[-156.286332,20.947701],[-156.275116,20.937361],[-156.263107,20.940888],[-156.242555,20.937838],[-156.230159,20.931936],[-156.230089,20.917864],[-156.226757,20.916677],[-156.222062,20.918309],[-156.217953,20.916573],[-156.216341,20.907035],[-156.173103,20.876926],[-156.170458,20.874605],[-156.166746,20.865646],[-156.132669,20.861369],[-156.129381,20.847513],[-156.115735,20.827301],[-156.100123,20.828502],[-156.090291,20.831872],[-156.059788,20.81054],[-156.033287,20.808246],[-156.003532,20.795545],[-156.002947,20.789418],[-155.987944,20.776552],[-155.984587,20.767496],[-155.986851,20.758577],[-155.985413,20.744245],[-155.987216,20.722717],[-155.991534,20.713654],[-156.00187,20.698064],[-156.01415,20.685681],[-156.020044,20.686857],[-156.030702,20.682452],[-156.040341,20.672719],[-156.043786,20.664902],[-156.053385,20.65432],[-156.059753,20.652044],[-156.081472,20.654387],[-156.089365,20.648519],[-156.120985,20.633685],[-156.129898,20.627523],[-156.142665,20.623605],[-156.144588,20.624032],[-156.148085,20.629067],[-156.156772,20.629639],[-156.169732,20.627358],[-156.173393,20.6241],[-156.184556,20.629719],[-156.192938,20.631769],[-156.210258,20.628518],[-156.225338,20.62294],[-156.236145,20.61595],[-156.265921,20.601629],[-156.284391,20.596488],[-156.288037,20.59203],[-156.293454,20.588783],[-156.302692,20.586199],[-156.322944,20.588273],[-156.351716,20.58697],[-156.359634,20.581977],[-156.370725,20.57876],[-156.377633,20.578427],[-156.415313,20.586099],[-156.417523,20.589728],[-156.415746,20.594044],[-156.417799,20.598682],[-156.423141,20.602079],[-156.427708,20.598873],[-156.431872,20.598143],[-156.438385,20.601337],[-156.444242,20.607941],[-156.442884,20.613842],[-156.450651,20.642212],[-156.445894,20.64927],[-156.443673,20.656018],[-156.448656,20.704739],[-156.451038,20.725469],[-156.452895,20.731287],[-156.458438,20.736676],[-156.462242,20.753952],[-156.462058,20.772571],[-156.464043,20.781667],[-156.473562,20.790756],[-156.489496,20.798339],[-156.501688,20.799933],[-156.506026,20.799463],[-156.515994,20.794234],[-156.525215,20.780821],[-156.537752,20.778408],[-156.631794,20.82124],[-156.678634,20.870541],[-156.688969,20.888673],[-156.687804,20.89072],[-156.688132,20.906325],[-156.691334,20.91244],[-156.697418,20.916368],[-156.69989,20.920629],[-156.69411,20.952708],[-156.680905,20.980262],[-156.665514,21.007054],[-156.652419,21.008994],[-156.645966,21.014416],[-156.642592,21.019936],[-156.644167,21.022312],[-156.642809,21.027583],[-156.619581,21.027793],[-156.612012,21.02477]]],[[[-157.010001,20.929757],[-156.989813,20.932127],[-156.971604,20.926254],[-156.937529,20.925274],[-156.91845,20.922546],[-156.897169,20.915395],[-156.837047,20.863575],[-156.825237,20.850731],[-156.809576,20.826036],[-156.808469,20.820396],[-156.809463,20.809169],[-156.817427,20.794606],[-156.838321,20.764575],[-156.846413,20.760201],[-156.851481,20.760069],[-156.869753,20.754701],[-156.890295,20.744855],[-156.909081,20.739533],[-156.949009,20.738997],[-156.96789,20.73508],[-156.984747,20.756677],[-156.994001,20.786671],[-156.988933,20.815496],[-156.991834,20.826603],[-157.006243,20.849603],[-157.010911,20.854476],[-157.054552,20.877219],[-157.059663,20.884634],[-157.061128,20.890635],[-157.062511,20.904385],[-157.05913,20.913407],[-157.035789,20.927078],[-157.025626,20.929528],[-157.010001,20.929757]]],[[[-158.044485,21.306011],[-158.0883,21.2988],[-158.1033,21.2979],[-158.1127,21.3019],[-158.1211,21.3169],[-158.1225,21.3224],[-158.111949,21.326622],[-158.114196,21.331123],[-158.119427,21.334594],[-158.125459,21.330264],[-158.13324,21.359207],[-158.1403,21.3738],[-158.149719,21.385208],[-158.161743,21.396282],[-158.1792,21.4043],[-158.181274,21.409626],[-158.181,21.420868],[-158.182648,21.430073],[-158.192352,21.44804],[-158.205383,21.459793],[-158.219446,21.46978],[-158.233,21.4876],[-158.231171,21.523857],[-158.23175,21.533035],[-158.234314,21.540058],[-158.250671,21.557373],[-158.27951,21.575794],[-158.277679,21.578789],[-158.254425,21.582684],[-158.190704,21.585892],[-158.17,21.5823],[-158.12561,21.586739],[-158.10672,21.596577],[-158.106689,21.603024],[-158.1095,21.6057],[-158.108185,21.607487],[-158.079895,21.628101],[-158.0668,21.6437],[-158.066711,21.65234],[-158.0639,21.6584],[-158.0372,21.6843],[-158.018127,21.699955],[-157.9923,21.708],[-157.98703,21.712494],[-157.968628,21.712704],[-157.947174,21.689568],[-157.939,21.669],[-157.9301,21.6552],[-157.924591,21.651183],[-157.9228,21.6361],[-157.9238,21.6293],[-157.910797,21.611183],[-157.900574,21.605885],[-157.87735,21.575277],[-157.878601,21.560181],[-157.872528,21.557568],[-157.8669,21.5637],[-157.85614,21.560661],[-157.85257,21.557514],[-157.836945,21.529945],[-157.837372,21.512085],[-157.849579,21.509598],[-157.852625,21.499971],[-157.84549,21.466747],[-157.84099,21.459483],[-157.82489,21.455379],[-157.8163,21.4502],[-157.8139,21.4403],[-157.8059,21.4301],[-157.786513,21.415633],[-157.779846,21.417309],[-157.774455,21.421352],[-157.772209,21.431236],[-157.774905,21.453698],[-157.772209,21.457741],[-157.764572,21.461335],[-157.754239,21.461335],[-157.737617,21.459089],[-157.731777,21.455944],[-157.731328,21.444713],[-157.73582,21.438424],[-157.740762,21.424048],[-157.741211,21.414614],[-157.7386,21.4043],[-157.730191,21.401871],[-157.728221,21.402104],[-157.726421,21.402845],[-157.724324,21.403311],[-157.723794,21.40329],[-157.723286,21.403227],[-157.722735,21.403121],[-157.722544,21.403036],[-157.721845,21.401596],[-157.721083,21.399541],[-157.7189,21.3961],[-157.7089,21.3833],[-157.7087,21.3793],[-157.7126,21.3689],[-157.7106,21.3585],[-157.7088,21.3534],[-157.6971,21.3364],[-157.6938,21.3329],[-157.6619,21.3131],[-157.6518,21.3139],[-157.652629,21.308709],[-157.6537,21.302],[-157.6946,21.2739],[-157.6944,21.2665],[-157.7001,21.264],[-157.7097,21.2621],[-157.7139,21.2638],[-157.7142,21.2665],[-157.7114,21.272],[-157.7122,21.2814],[-157.7143,21.2845],[-157.7213,21.2869],[-157.7572,21.278],[-157.765,21.2789],[-157.7782,21.2735],[-157.7931,21.2604],[-157.8096,21.2577],[-157.8211,21.2606],[-157.8241,21.2646],[-157.8253,21.2714],[-157.8319,21.2795],[-157.8457,21.29],[-157.89,21.3065],[-157.894518,21.319632],[-157.898969,21.327391],[-157.90482,21.329172],[-157.918939,21.318615],[-157.917921,21.313781],[-157.913469,21.310983],[-157.910925,21.305768],[-157.952263,21.306531],[-157.950736,21.312509],[-157.951881,21.318742],[-157.967971,21.327986],[-157.973334,21.327426],[-157.989424,21.317984],[-158.0245,21.3093],[-158.044485,21.306011]]]]},\"properties\":{\"name\":\"Hawaii\",\"nation\":\"USA \"}}]}","volume":"23","noUsgsAuthors":false,"publicationDate":"2021-03-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Fortini, Lucas Berio 0000-0002-5781-7295","orcid":"https://orcid.org/0000-0002-5781-7295","contributorId":236984,"corporation":false,"usgs":true,"family":"Fortini","given":"Lucas Berio","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":821841,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Leopold, Christina 0000-0003-0499-3196","orcid":"https://orcid.org/0000-0003-0499-3196","contributorId":178961,"corporation":false,"usgs":false,"family":"Leopold","given":"Christina","affiliations":[],"preferred":false,"id":821842,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Perkins, Kimberlie 0000-0001-8349-447X kperkins@usgs.gov","orcid":"https://orcid.org/0000-0001-8349-447X","contributorId":138544,"corporation":false,"usgs":true,"family":"Perkins","given":"Kimberlie","email":"kperkins@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":821849,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chadwick, Oliver A.","contributorId":88244,"corporation":false,"usgs":false,"family":"Chadwick","given":"Oliver","email":"","middleInitial":"A.","affiliations":[{"id":6710,"text":"University of California, Santa Barbara, CA","active":true,"usgs":false}],"preferred":false,"id":821844,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Yelenik, Stephanie G. 0000-0002-9011-0769","orcid":"https://orcid.org/0000-0002-9011-0769","contributorId":256836,"corporation":false,"usgs":false,"family":"Yelenik","given":"Stephanie","email":"","middleInitial":"G.","affiliations":[{"id":51875,"text":"formerly U.S. Geological Survey; currently Rocky Mountain Research Station, U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":821845,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jacobi, James D. 0000-0003-2313-7862 jjacobi@usgs.gov","orcid":"https://orcid.org/0000-0003-2313-7862","contributorId":3705,"corporation":false,"usgs":true,"family":"Jacobi","given":"James","email":"jjacobi@usgs.gov","middleInitial":"D.","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true},{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":true,"id":821846,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bishaw, Kaiena","contributorId":223146,"corporation":false,"usgs":false,"family":"Bishaw","given":"Kaiena","email":"","affiliations":[{"id":13341,"text":"Hawai‘i Cooperative Studies Unit, University of Hawai‘i at Hilo","active":true,"usgs":false}],"preferred":false,"id":821847,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Gregg, Makani","contributorId":223147,"corporation":false,"usgs":false,"family":"Gregg","given":"Makani","email":"","affiliations":[{"id":13341,"text":"Hawai‘i Cooperative Studies Unit, University of Hawai‘i at Hilo","active":true,"usgs":false}],"preferred":false,"id":821848,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70231651,"text":"70231651 - 2021 - Linking altered flow regimes to biological condition: An example using benthic macroinvertebrates in small streams of the Chesapeake Bay watershed","interactions":[],"lastModifiedDate":"2022-05-18T15:38:14.741057","indexId":"70231651","displayToPublicDate":"2021-03-12T10:34:52","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1547,"text":"Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Linking altered flow regimes to biological condition: An example using benthic macroinvertebrates in small streams of the Chesapeake Bay watershed","docAbstract":"

Regionally scaled assessments of hydrologic alteration for small streams and its effects on freshwater taxa are often inhibited by a low number of stream gages. To overcome this limitation, we paired modeled estimates of hydrologic alteration to a benthic macroinvertebrate index of biotic integrity data for 4522 stream reaches across the Chesapeake Bay watershed. Using separate random-forest models, we predicted flow status (inflated, diminished, or indeterminant) for 12 published hydrologic metrics (HMs) that characterize the main components of flow regimes. We used these models to predict each HM status for each stream reach in the watershed, and linked predictions to macroinvertebrate condition samples collected from streams with drainage areas less than 200 km2. Flow alteration was calculated as the number of HMs with inflated or diminished status and ranged from 0 (no HM inflated or diminished) to 12 (all 12 HMs inflated or diminished). When focused solely on the stream condition and flow-alteration relationship, degraded macroinvertebrate condition was, depending on the number of HMs used, 3.8–4.7 times more likely in a flow-altered site; this likelihood was over twofold higher in the urban-focused dataset (8.7–10.8), and was never significant in the agriculture-focused dataset. Logistic regression analysis using the entire dataset showed for every unit increase in flow-alteration intensity, the odds of a degraded condition increased 3.7%. Our results provide an indication of whether altered streamflow is a possible driver of degraded biological conditions, information that could help managers prioritize management actions and lead to more effective restoration efforts.

","language":"English","publisher":"Springer Link","doi":"10.1007/s00267-021-01450-5","usgsCitation":"Maloney, K.O., Carlisle, D.M., Buchanan, C., Rapp, J.L., Austin, S.H., Cashman, M.J., and Young, J.A., 2021, Linking altered flow regimes to biological condition: An example using benthic macroinvertebrates in small streams of the Chesapeake Bay watershed: Environmental Management, v. 67, p. 1171-1185, https://doi.org/10.1007/s00267-021-01450-5.","productDescription":"15 p.","startPage":"1171","endPage":"1185","ipdsId":"IP-121380","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":453098,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s00267-021-01450-5","text":"Publisher Index Page"},{"id":400761,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Chesapeake Bay watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.1904296875,\n 38.41916639395372\n ],\n [\n -75.223388671875,\n 38.64261790634527\n ],\n [\n -75.35522460937499,\n 38.79690830348427\n ],\n [\n -75.498046875,\n 38.87392853923629\n ],\n [\n -75.5419921875,\n 39.0533181067413\n ],\n [\n -75.662841796875,\n 39.30029918615029\n ],\n [\n -75.750732421875,\n 39.70718665682654\n ],\n [\n -75.6298828125,\n 40.052847601823984\n ],\n [\n -75.69580078125,\n 40.07807142745009\n ],\n [\n -75.95947265625,\n 40.052847601823984\n ],\n [\n -76.0693359375,\n 40.069664523297774\n ],\n [\n -76.058349609375,\n 40.18726672309203\n ],\n [\n -75.9375,\n 40.29628651711716\n ],\n [\n -75.91552734375,\n 40.3549167507906\n ],\n [\n -75.89355468749999,\n 40.47202439692057\n ],\n [\n -76.09130859375,\n 40.56389453066509\n ],\n [\n -76.190185546875,\n 40.64730356252251\n ],\n [\n -76.0693359375,\n 40.75557964275589\n ],\n [\n -75.83862304687499,\n 40.871987756697415\n ],\n [\n -75.76171875,\n 40.91351257612758\n ],\n [\n -75.706787109375,\n 40.95501133048621\n ],\n [\n -75.7177734375,\n 41.071069130806414\n ],\n [\n -75.662841796875,\n 41.1455697310095\n ],\n [\n -75.5419921875,\n 41.13729606112276\n ],\n [\n -75.322265625,\n 41.104190944576466\n ],\n [\n -75.377197265625,\n 41.22824901518529\n ],\n [\n -75.377197265625,\n 41.28606238749825\n ],\n [\n -75.377197265625,\n 41.43449030894922\n ],\n [\n -75.399169921875,\n 41.6154423246811\n ],\n [\n -75.34423828125,\n 41.68111756290652\n ],\n [\n -75.2783203125,\n 41.91045347666418\n ],\n [\n -75.38818359375,\n 42.00848901572399\n ],\n [\n -75.377197265625,\n 42.09007006868398\n ],\n [\n -75.223388671875,\n 42.17968819665961\n ],\n [\n -74.970703125,\n 42.26917949243506\n ],\n [\n -74.8388671875,\n 42.32606244456202\n ],\n [\n -74.520263671875,\n 42.415346114253616\n ],\n [\n -74.278564453125,\n 42.54498667313236\n ],\n [\n -74.322509765625,\n 42.64204079304426\n ],\n [\n -74.410400390625,\n 42.80346172417078\n ],\n [\n -74.68505859374999,\n 42.924251753870685\n ],\n [\n -75.069580078125,\n 42.98053954751642\n ],\n [\n -75.38818359375,\n 42.96446257387128\n ],\n [\n -75.684814453125,\n 42.93229601903058\n ],\n [\n -75.9375,\n 42.87596410238256\n ],\n [\n -76.201171875,\n 42.827638636242284\n ],\n [\n -76.26708984375,\n 42.72280375732727\n ],\n [\n -76.2890625,\n 42.601619944327965\n ],\n [\n -76.2890625,\n 42.52069952914966\n ],\n [\n -76.343994140625,\n 42.415346114253616\n ],\n [\n -76.46484375,\n 42.382894009614034\n ],\n [\n -76.640625,\n 42.431565872579185\n ],\n [\n -76.7724609375,\n 42.39912215986002\n ],\n [\n -76.80541992187499,\n 42.24478535602799\n ],\n [\n -76.88232421875,\n 42.285437007491545\n ],\n [\n -76.9482421875,\n 42.415346114253616\n ],\n [\n -77.04711914062499,\n 42.44778143462245\n ],\n [\n -77.14599609375,\n 42.415346114253616\n ],\n [\n -77.2998046875,\n 42.382894009614034\n ],\n [\n -77.222900390625,\n 42.54498667313236\n ],\n [\n -77.442626953125,\n 42.69858589169842\n ],\n [\n -77.574462890625,\n 42.60970621339408\n ],\n [\n -77.640380859375,\n 42.48830197960227\n ],\n [\n -77.728271484375,\n 42.439674178149424\n ],\n [\n -77.6513671875,\n 42.31793945446847\n ],\n [\n -77.596435546875,\n 42.22851735620852\n ],\n [\n -77.5634765625,\n 42.09007006868398\n ],\n [\n -77.6953125,\n 41.92680320648791\n ],\n [\n -77.9150390625,\n 41.83682786072714\n ],\n [\n -78.0908203125,\n 41.795888098191426\n ],\n [\n -78.453369140625,\n 41.599013054830216\n ],\n [\n -78.453369140625,\n 41.50857729743935\n ],\n [\n -78.42041015625,\n 41.376808565702355\n ],\n [\n -78.3984375,\n 41.21172151054787\n ],\n [\n -78.519287109375,\n 41.054501963290505\n ],\n [\n -78.541259765625,\n 40.9218144123785\n ],\n [\n -78.409423828125,\n 40.713955826286046\n ],\n [\n -78.299560546875,\n 40.55554790286311\n ],\n [\n -78.343505859375,\n 40.48873742102282\n ],\n [\n -78.475341796875,\n 40.30466538259176\n ],\n [\n -78.64013671875,\n 40.06125658140474\n ],\n [\n -78.826904296875,\n 39.9434364619742\n ],\n [\n -78.848876953125,\n 39.80853604144591\n ],\n [\n -78.85986328125,\n 39.715638134796336\n ],\n [\n -78.99169921875,\n 39.69873414348139\n ],\n [\n -79.046630859375,\n 39.64799732373418\n ],\n [\n -79.266357421875,\n 39.436192999314095\n ],\n [\n -79.420166015625,\n 39.2832938689385\n ],\n [\n -79.354248046875,\n 39.26628442213066\n ],\n [\n -79.266357421875,\n 39.232253141714885\n ],\n [\n -79.2333984375,\n 39.155622393423215\n ],\n [\n -79.244384765625,\n 39.01918369029134\n ],\n [\n -79.27734374999999,\n 38.89103282648846\n ],\n [\n -79.398193359375,\n 38.74551518488265\n ],\n [\n -79.661865234375,\n 38.54816542304656\n ],\n [\n -79.683837890625,\n 38.47079371120379\n ],\n [\n -79.727783203125,\n 38.34165619279595\n ],\n [\n -79.815673828125,\n 38.20365531807149\n ],\n [\n -80.04638671875,\n 38.013476231041935\n ],\n [\n -80.17822265625,\n 37.779398571318765\n ],\n [\n -80.2880859375,\n 37.59682400108367\n ],\n [\n -80.4638671875,\n 37.47485808497102\n ],\n [\n -80.694580078125,\n 37.38761749978395\n ],\n [\n -80.771484375,\n 37.23032838760387\n ],\n [\n -80.57373046875,\n 37.26530995561875\n ],\n [\n -80.44189453125,\n 37.309014074275915\n ],\n [\n -80.255126953125,\n 37.31775185163688\n ],\n [\n -80.013427734375,\n 37.3002752813443\n ],\n [\n -79.8486328125,\n 37.23907530202184\n ],\n [\n -79.771728515625,\n 37.18657859524883\n ],\n [\n -79.6728515625,\n 37.07271048132943\n ],\n [\n -79.541015625,\n 37.09900294387622\n ],\n [\n -79.354248046875,\n 37.142803443716836\n ],\n [\n -79.1455078125,\n 37.10776507118514\n ],\n [\n -79.112548828125,\n 37.055177106660814\n ],\n [\n -78.936767578125,\n 36.932330061503144\n ],\n [\n -78.837890625,\n 36.94111143010769\n ],\n [\n -78.662109375,\n 37.055177106660814\n ],\n [\n -78.486328125,\n 37.03763967977139\n ],\n [\n -78.42041015625,\n 36.94111143010769\n ],\n [\n -78.20068359374999,\n 36.96744946416934\n ],\n [\n -77.904052734375,\n 37.03763967977139\n ],\n [\n -77.750244140625,\n 37.081475648860525\n ],\n [\n -77.53051757812499,\n 37.081475648860525\n ],\n [\n -77.354736328125,\n 37.07271048132943\n ],\n [\n -77.069091796875,\n 37.081475648860525\n ],\n [\n -76.959228515625,\n 37.01132594307015\n ],\n [\n -76.893310546875,\n 36.932330061503144\n ],\n [\n -76.871337890625,\n 36.83566824724438\n ],\n [\n -76.849365234375,\n 36.677230602346214\n ],\n [\n -76.7724609375,\n 36.527294814546245\n ],\n [\n -76.629638671875,\n 36.55377524336089\n ],\n [\n -76.46484375,\n 36.589068371399115\n ],\n [\n -76.35498046875,\n 36.48314061639213\n ],\n [\n -76.256103515625,\n 36.57142382346277\n ],\n [\n -76.190185546875,\n 36.66841891894786\n ],\n [\n -76.0693359375,\n 36.65079252503471\n ],\n [\n -75.9375,\n 36.66841891894786\n ],\n [\n -75.948486328125,\n 36.76529191711624\n ],\n [\n -75.904541015625,\n 37.01132594307015\n ],\n [\n -75.926513671875,\n 37.17782559332976\n ],\n [\n -75.882568359375,\n 37.42252593456307\n ],\n [\n -75.618896484375,\n 37.640334898059486\n ],\n [\n -75.509033203125,\n 37.82280243352756\n ],\n [\n -75.38818359375,\n 38.013476231041935\n ],\n [\n -75.16845703124999,\n 38.272688535980976\n ],\n [\n -75.1904296875,\n 38.41916639395372\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"67","noUsgsAuthors":false,"publicationDate":"2021-03-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Maloney, Kelly O. 0000-0003-2304-0745 kmaloney@usgs.gov","orcid":"https://orcid.org/0000-0003-2304-0745","contributorId":4636,"corporation":false,"usgs":true,"family":"Maloney","given":"Kelly","email":"kmaloney@usgs.gov","middleInitial":"O.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":843233,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carlisle, Daren M. 0000-0002-7367-348X dcarlisle@usgs.gov","orcid":"https://orcid.org/0000-0002-7367-348X","contributorId":513,"corporation":false,"usgs":true,"family":"Carlisle","given":"Daren","email":"dcarlisle@usgs.gov","middleInitial":"M.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true}],"preferred":true,"id":843234,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buchanan, Claire 0000-0001-5627-448X","orcid":"https://orcid.org/0000-0001-5627-448X","contributorId":291854,"corporation":false,"usgs":false,"family":"Buchanan","given":"Claire","email":"","affiliations":[{"id":39005,"text":"ICPRB","active":true,"usgs":false}],"preferred":false,"id":843235,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rapp, Jennifer L. 0000-0003-2253-9886 jrapp@usgs.gov","orcid":"https://orcid.org/0000-0003-2253-9886","contributorId":197342,"corporation":false,"usgs":true,"family":"Rapp","given":"Jennifer","email":"jrapp@usgs.gov","middleInitial":"L.","affiliations":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"preferred":false,"id":843236,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Austin, Samuel H. 0000-0001-5626-023X saustin@usgs.gov","orcid":"https://orcid.org/0000-0001-5626-023X","contributorId":153,"corporation":false,"usgs":true,"family":"Austin","given":"Samuel","email":"saustin@usgs.gov","middleInitial":"H.","affiliations":[{"id":37280,"text":"Virginia and West Virginia Water Science Center ","active":true,"usgs":true}],"preferred":true,"id":843237,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cashman, Matthew J. 0000-0002-6635-4309","orcid":"https://orcid.org/0000-0002-6635-4309","contributorId":203315,"corporation":false,"usgs":true,"family":"Cashman","given":"Matthew","middleInitial":"J.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":843238,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Young, John A. 0000-0002-4500-3673 jyoung@usgs.gov","orcid":"https://orcid.org/0000-0002-4500-3673","contributorId":3777,"corporation":false,"usgs":true,"family":"Young","given":"John","email":"jyoung@usgs.gov","middleInitial":"A.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":843239,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ]}