{"pageNumber":"28","pageRowStart":"675","pageSize":"25","recordCount":16443,"records":[{"id":70242711,"text":"pp1837C - 2023 - Determining three-dimensional hydrologic processes in the eastern Snake River Plain aquifer using geochemical mass-balance modeling, Idaho National Laboratory, eastern Idaho, with contributions by Treinen, K.C.","interactions":[],"lastModifiedDate":"2023-04-17T11:04:59.33674","indexId":"pp1837C","displayToPublicDate":"2023-04-14T06:48:18","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":331,"text":"Professional Paper","code":"PP","onlineIssn":"2330-7102","printIssn":"1044-9612","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1837","chapter":"C","displayTitle":"Determining Three-Dimensional Hydrologic Processes in the Eastern Snake River Plain Aquifer Using Geochemical Mass-Balance Modeling, Idaho National Laboratory, Eastern Idaho","title":"Determining three-dimensional hydrologic processes in the eastern Snake River Plain aquifer using geochemical mass-balance modeling, Idaho National Laboratory, eastern Idaho, with contributions by Treinen, K.C.","docAbstract":"

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

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

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

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

","tableOfContents":"","publishedDate":"2023-04-14","noUsgsAuthors":false,"publicationDate":"2023-04-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Rattray, Gordon W. 0000-0002-1690-3218 grattray@usgs.gov","orcid":"https://orcid.org/0000-0002-1690-3218","contributorId":2521,"corporation":false,"usgs":true,"family":"Rattray","given":"Gordon","email":"grattray@usgs.gov","middleInitial":"W.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":869457,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70242682,"text":"ofr20231026 - 2023 - Assessment of riparian vegetation patterns and change downstream from Glen Canyon Dam from 2014 to 2019","interactions":[],"lastModifiedDate":"2026-02-11T21:04:06.498805","indexId":"ofr20231026","displayToPublicDate":"2023-04-13T12:02:15","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-1026","displayTitle":"Assessment of Riparian Vegetation Patterns and Change Downstream from Glen Canyon Dam from 2014 to 2019","title":"Assessment of riparian vegetation patterns and change downstream from Glen Canyon Dam from 2014 to 2019","docAbstract":"

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

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231026","collaboration":"Prepared in cooperation with the Bureau of Reclamation Glen Canyon Adaptive Management Program","usgsCitation":"Palmquist, E.C., Butterfield, B.J., and Ralston, B.E., 2023, Assessment of riparian vegetation patterns and change downstream from Glen Canyon Dam from 2014 to 2019: U.S. Geological Survey Open-File Report 2023–1026, 55 p., https://doi.org/10.3133/ofr20231026.","productDescription":"Report: vii, 55 p.; Data Release","numberOfPages":"55","onlineOnly":"Y","ipdsId":"IP-132835","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":499774,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114661.htm","linkFileType":{"id":5,"text":"html"}},{"id":415675,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1026/images"},{"id":415674,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1026/ofr20231026.pdf","text":"Report","size":"5 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":415673,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1026/covrthb.jpg"},{"id":415672,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9KEHY2S","text":"Riparian vegetation data downstream of Glen Canyon Dam in Glen Canyon National Recreation Area and Grand Canyon National Park, AZ from 2014 to 2019","description":"Palmquist, E.C., Butterfield, B.J., and Ralston, B.E., 2022, Riparian vegetation data downstream of Glen Canyon Dam in Glen Canyon National Recreation Area and Grand Canyon National Park, AZ from 2014 to 2019: U.S. Geological Survey data release, https://doi.org/10.5066/P9KEHY2S."}],"country":"United States","state":"Arizona","otherGeospatial":"Glen Canyon Dam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -114.06028247701303,\n 36.94784441270309\n ],\n [\n -114.06028247701303,\n 35.55756259875736\n ],\n [\n -111.24899178190306,\n 35.55756259875736\n ],\n [\n -111.24899178190306,\n 36.94784441270309\n ],\n [\n -114.06028247701303,\n 36.94784441270309\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"
Southwest Biological Science Center
U.S. Geological Survey
2255 N. Gemini Drive
Flagstaff, AZ 86001
","tableOfContents":"","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2023-04-13","noUsgsAuthors":false,"publicationDate":"2023-04-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Palmquist, Emily C. 0000-0003-1069-2154 epalmquist@usgs.gov","orcid":"https://orcid.org/0000-0003-1069-2154","contributorId":5669,"corporation":false,"usgs":true,"family":"Palmquist","given":"Emily","email":"epalmquist@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":869339,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Butterfield, Bradley J.","contributorId":18096,"corporation":false,"usgs":true,"family":"Butterfield","given":"Bradley J.","affiliations":[],"preferred":false,"id":869340,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ralston, Barbara E. 0000-0001-9991-8994 bralston@usgs.gov","orcid":"https://orcid.org/0000-0001-9991-8994","contributorId":606,"corporation":false,"usgs":true,"family":"Ralston","given":"Barbara","email":"bralston@usgs.gov","middleInitial":"E.","affiliations":[{"id":501,"text":"Office of Science Quality and Integrity","active":true,"usgs":true}],"preferred":false,"id":869341,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70243034,"text":"70243034 - 2023 - Data integration reveals dynamic and systematic patterns of breeding habitat use by a threatened shorebird","interactions":[],"lastModifiedDate":"2023-04-27T12:06:00.830801","indexId":"70243034","displayToPublicDate":"2023-04-13T07:01:48","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Data integration reveals dynamic and systematic patterns of breeding habitat use by a threatened shorebird","docAbstract":"

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

","language":"English","publisher":"Nature","doi":"10.1038/s41598-023-32886-w","usgsCitation":"Ellis, K.S., Anteau, M.J., MacDonald, G.J., Swift, R.J., Ring, M., Toy, D.L., Sherfy, M.H., and Post van der Burg, M., 2023, Data integration reveals dynamic and systematic patterns of breeding habitat use by a threatened shorebird: Scientific Reports, v. 13, 6087, 12 p., https://doi.org/10.1038/s41598-023-32886-w.","productDescription":"6087, 12 p.","ipdsId":"IP-143601","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":443865,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-023-32886-w","text":"Publisher Index Page"},{"id":435376,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9KWK13B","text":"USGS data release","linkHelpText":"Piping plover nesting habitat distribution maps for the U.S. Prairie Pothole Region, 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Article"},"seriesTitle":{"id":5686,"text":"Fisheries Magazine","active":true,"publicationSubtype":{"id":10}},"title":"Climate change risks to freshwater subsistence fisheries in Arctic Alaska: Insights and uncertainty from broad whitefish Coregonus nasus","docAbstract":"

Arctic freshwater ecosystems and fish populations are largely shaped by seasonal and long-term watershed hydrology. In this paper, we hypothesize how changing air temperature and precipitation will alter freeze and thaw processes, hydrology, and instream habitat to assess potential indirect effects, such as the change to the foraging and behavioral ecology, on Arctic fishes, using Broad Whitefish Coregonus nasus as an indicator species. Climate change is expected to continue to alter hydrologic pathways, flow regimes, and, therefore, habitat suitability, connectivity, and availability for fishes. Warming and lengthening of the growing season will likely increase fish growth rates; however, the exceedance of threshold stream temperatures will likely increase physiological stress and alter life histories. We expect these changes to have mixed effects on Arctic subsistence fishes and fisheries. Management and conservation approaches focused on preserving the processes that create heterogeneity in aquatic habitats, genes, and communities will help maintain the resilience of Broad Whitefish and other important subsistence fisheries. Long-term effects are uncertain, so filling scientific knowledge gaps, such as identifying important habitats or increasing knowledge of abiotic variables in priority watersheds, is key to understanding and potentially mitigating likely impacts to Arctic fishes in a rapidly changing landscape.

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Fifteen participants who work in a wide range of job functions associated with southern California postfire hazards were selected using purposive sampling for unstructured interviews about useful characteristics and needs for postfire debris-flow inundation hazard assessments. The interview guide was developed by a team of social and physical scientists following best practices for engaging with users. The guide focused on target information that could influence ongoing or not-yet-initiated research on debris-flow physics and hazard assessment methodology. Following standard methods for user needs assessment, the audio from the unstructured interviews was recorded, transcribed, and analyzed using a thematic coding scheme. Participants reported engaging with postfire debris-flow inundation as one of multiple postfire hazards and their information needs reflect this breadth. Most participants were from organizations with life and property mandates, and this focused their concerns on where debris-flow inundation could impact people’s physical safety, the ability of populations to egress, and damage to property. Common comments included, (1) the need to interpret inundation hazard assessments in the context of forecast rainfall—which are typically associated with different timeframes, 15 and 60 minutes, respectively; (2) the need to provide multiple scenarios in a hazard assessment to show how the hazard changes under different external factors such as varying rainfall intensity; and (3) the tension between fully reflecting all sources of uncertainty in identifying impacted areas and a high level of precision needed to determine evacuation zones in order to reduce evacuation fatigue. Participants saw utility in both low-resolution hazard assessments over large areas and fine-resolution targeted assessments over small areas, noting that the identification of target areas could pose an ethical challenge because some areas might be prioritized over others. Participants were concerned about the hazard posed by the continuum of postfire hydrologic hazards, including hyperconcentrated flows. Finally, participants recognized that the shrinking time window between the end of fire season and the start of the wet season in southern California makes the production, interpretation, and use of rapid postfire debris-flow inundation hazard assessments both important and challenging.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231025","programNote":"Landslide Hazards Program","usgsCitation":"Barnhart, K.R., Romero, V.Y., and Clifford, K.R., 2023, User needs assessment for postfire debris-flow inundation hazard products: U.S. Geological Survey Open-File Report 2023–1025, 25 p., https://doi.org/10.3133/ofr20231025.","productDescription":"vi, 25 p.","numberOfPages":"25","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-140742","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":415140,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1025/coverthb.jpg"},{"id":415144,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1025/images/"},{"id":415143,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1025/ofr20231025.XML"},{"id":421028,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231025/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2023-1025"},{"id":415141,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1025/ofr20231025.pdf","text":"Report","size":"1.11 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1025"}],"country":"United States","state":"California","city":"Montecito","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -119.70234862012427,\n 34.497719835273585\n ],\n [\n -119.70234862012427,\n 34.41216398408224\n ],\n [\n -119.52439809003698,\n 34.41216398408224\n ],\n [\n -119.52439809003698,\n 34.497719835273585\n ],\n [\n -119.70234862012427,\n 34.497719835273585\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

Director, Geologic Hazards Science Center
U.S. Geological Survey
1711 Illinois Street
Golden, Colorado 80401

Contact Pubs Warehouse

","tableOfContents":"","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"publishedDate":"2023-04-06","noUsgsAuthors":false,"publicationDate":"2023-04-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Barnhart, Katherine R. 0000-0001-5682-455X","orcid":"https://orcid.org/0000-0001-5682-455X","contributorId":257870,"corporation":false,"usgs":true,"family":"Barnhart","given":"Katherine","email":"","middleInitial":"R.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":868489,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Romero, Veronica 0000-0002-8124-4386","orcid":"https://orcid.org/0000-0002-8124-4386","contributorId":302660,"corporation":false,"usgs":true,"family":"Romero","given":"Veronica","email":"","affiliations":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":868490,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Clifford, Katherine R. 0000-0002-1385-8765","orcid":"https://orcid.org/0000-0002-1385-8765","contributorId":303904,"corporation":false,"usgs":false,"family":"Clifford","given":"Katherine","email":"","middleInitial":"R.","affiliations":[{"id":38977,"text":"University of Colorado at Boulder","active":true,"usgs":false}],"preferred":false,"id":868491,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70241874,"text":"fs20233012 - 2023 - U.S. Geological Survey and Blackfeet Water Department Hydrologic Assessment of the Blackfeet Indian Reservation, Montana","interactions":[],"lastModifiedDate":"2026-02-06T21:58:06.716158","indexId":"fs20233012","displayToPublicDate":"2023-04-03T15:12:20","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-3012","displayTitle":"U.S. Geological Survey and Blackfeet Water Department Hydrologic Assessment of the Blackfeet Indian Reservation, Montana","title":"U.S. Geological Survey and Blackfeet Water Department Hydrologic Assessment of the Blackfeet Indian Reservation, Montana","docAbstract":"

The Blackfeet Nation seeks an increased scientific understanding of the water resources within the Blackfeet Indian Reservation of northwestern Montana. Hydrologic information is needed to better inform water-management decisions as the Blackfeet Nation implements the Blackfeet Water Rights Compact, initiates new water-use projects, and improves the Blackfeet Irrigation Project.

The U.S. Geological Survey and the Blackfeet Water Department began cooperating in 2019 to design and implement a hydrologic data-collection program. The program is being implemented in phases that include discrete and continuous discharge measurements of streams and canals, installation, operation of streamgages, groundwater-level monitoring, and database management. Data collected will be used to characterize current hydrologic conditions on the reservation and will act as a baseline for comparison as Blackfeet Nation water projects are implemented.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20233012","collaboration":"Prepared in cooperation with the Blackfeet Water Department","usgsCitation":"Lawlor, S.M., Caldwell, R.R., Bartos, T.T., and Price, B., 2023, U.S. Geological Survey and Blackfeet Water Department Hydrologic Assessment of the Blackfeet Indian Reservation, Montana: U.S. Geological Survey Fact Sheet 2023–3012, 4 p., https://doi.org/10.3133/fs20233012.","productDescription":"Report: 4 p.; Dataset","numberOfPages":"4","onlineOnly":"Y","ipdsId":"IP-141394","costCenters":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"links":[{"id":414914,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2023/3012/coverthb2.jpg"},{"id":414918,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2023/3012/images"},{"id":414919,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":415102,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/fs20233012/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":499662,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114650.htm","linkFileType":{"id":5,"text":"html"}},{"id":414917,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2023/3012/fs20233012.XML","text":"Report","linkFileType":{"id":8,"text":"xml"}},{"id":414916,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2023/3012/fs20233012.pdf","text":"Report","size":"2.78 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2023–3012"}],"country":"United States","state":"Montana","otherGeospatial":"Blackfeet Indian Reservation","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -113.92382337824559,\n 49.00115786005651\n ],\n [\n -113.92382337824559,\n 47.9492225969058\n ],\n [\n -111.72750252269083,\n 47.9492225969058\n ],\n [\n -111.72750252269083,\n 49.00115786005651\n ],\n [\n -113.92382337824559,\n 49.00115786005651\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

Director, Wyoming-Montana Water Science Center
U.S. Geological Survey
3162 Bozeman Avenue
Helena, MT 59601

Contact Pubs Warehouse

","tableOfContents":"","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2023-04-03","noUsgsAuthors":false,"publicationDate":"2023-04-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Lawlor, Sean M. 0000-0001-5988-7548 slawlor@usgs.gov","orcid":"https://orcid.org/0000-0001-5988-7548","contributorId":1895,"corporation":false,"usgs":true,"family":"Lawlor","given":"Sean","email":"slawlor@usgs.gov","middleInitial":"M.","affiliations":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"preferred":true,"id":868028,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Caldwell, Rodney R. 0000-0002-2588-715X caldwell@usgs.gov","orcid":"https://orcid.org/0000-0002-2588-715X","contributorId":2577,"corporation":false,"usgs":true,"family":"Caldwell","given":"Rodney","email":"caldwell@usgs.gov","middleInitial":"R.","affiliations":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"preferred":true,"id":868029,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bartos, Timothy T. 0000-0003-1803-4375 ttbartos@usgs.gov","orcid":"https://orcid.org/0000-0003-1803-4375","contributorId":1826,"corporation":false,"usgs":true,"family":"Bartos","given":"Timothy","email":"ttbartos@usgs.gov","middleInitial":"T.","affiliations":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"preferred":true,"id":868030,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Price, Brett baprice@usgs.gov","contributorId":303758,"corporation":false,"usgs":true,"family":"Price","given":"Brett","email":"baprice@usgs.gov","affiliations":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"preferred":true,"id":868031,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70246314,"text":"70246314 - 2023 - Flood-frequency analysis in the Midwest: Addressing potential nonstationarity of annual peak-flow records","interactions":[],"lastModifiedDate":"2023-07-19T15:37:03.166943","indexId":"70246314","displayToPublicDate":"2023-04-01T10:32:41","publicationYear":"2023","noYear":false,"publicationType":{"id":25,"text":"Newsletter"},"publicationSubtype":{"id":30,"text":"Newsletter"},"seriesTitle":{"id":16356,"text":"AASHTO Hydrolink","active":true,"publicationSubtype":{"id":30}},"title":"Flood-frequency analysis in the Midwest: Addressing potential nonstationarity of annual peak-flow records","docAbstract":"Flood-frequency analysis is essential in numerous water-resource management applications, including critical structure design and flood-plain mapping. A basic assumption within Bulletin 17C [1], the standardized guidelines for conducting flood-frequency analysis, is that basins without major hydrologic alterations, such as regulation or urbanization, exhibit stationary statistical properties of the distribution of annual peak streamflow. That is, the mean, variance, and skew are constant over time and the peak-flow record is a representative sample of the population of future floods [1]. In recent decades, better understanding of long-term climatic persistence and concerns about climate and land-use change have caused the assumption of stationarity in peak-flow records to be reexamined [2, 3, 4, 5]. Under nonstationary conditions, the long-term distributional properties (mean, variance, and/or skew) of peak-flow series change one or more times, either gradually or abruptly. Nonstationarities may be attributed to one source, but are often a result of a mixture of drivers, making detection and attribution of nonstationarities challenging [6, 7, 8]. Failure to incorporate observed trends and abrupt changes into flood-frequency analysis may result in a poor representation of the true flood risk. Bulletin 17C currently offers no guidance on how to account for nonstationarities when estimating floods and acknowledges the benefit additional flood frequency studies that incorporate changing climate or basin characteristics into the analysis would provide[1].","language":"English","publisher":"American Association of State Highway and Transportation Officials","usgsCitation":"Marti, M.K., Ryberg, K.R., and Levin, S., 2023, Flood-frequency analysis in the Midwest: Addressing potential nonstationarity of annual peak-flow records: AASHTO Hydrolink, no. 22, p. 9-11.","productDescription":"3 p.","startPage":"9","endPage":"11","ipdsId":"IP-146874","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":419153,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":419152,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://transportation.org/design/technical-committees/hydrology-and-hydraulics/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","otherGeospatial":"Midwest","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -80.63079880812552,\n 39.981338894898926\n ],\n [\n -80.305088787779,\n 42.407786545262155\n ],\n [\n -82.78313999112669,\n 41.8642895150752\n ],\n [\n -81.94361722979289,\n 43.7411297751668\n ],\n [\n -84.57946169161875,\n 46.783497345807575\n ],\n [\n -88.02687384801146,\n 48.18911170131872\n ],\n [\n -90.78141289084317,\n 48.05054435475736\n ],\n [\n -94.73142386151744,\n 48.96813415136279\n ],\n [\n -96.0701137437052,\n 49.34965225487991\n ],\n [\n -118.36279683132679,\n 49.044880788818546\n ],\n [\n -114.80117084034327,\n 34.5056159266112\n ],\n [\n -106.83709671015015,\n 33.4475379407086\n ],\n [\n -89.0414291409545,\n 33.06253925797563\n ],\n [\n -81.8240905040015,\n 37.13731159053141\n ],\n [\n -80.63079880812552,\n 39.981338894898926\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","issue":"22","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Marti, Mackenzie K. 0000-0001-8817-4969 mmarti@usgs.gov","orcid":"https://orcid.org/0000-0001-8817-4969","contributorId":289738,"corporation":false,"usgs":true,"family":"Marti","given":"Mackenzie","email":"mmarti@usgs.gov","middleInitial":"K.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":876790,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ryberg, Karen R. 0000-0002-9834-2046 kryberg@usgs.gov","orcid":"https://orcid.org/0000-0002-9834-2046","contributorId":1172,"corporation":false,"usgs":true,"family":"Ryberg","given":"Karen","email":"kryberg@usgs.gov","middleInitial":"R.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":876791,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Levin, Sara B. 0000-0002-2448-3129","orcid":"https://orcid.org/0000-0002-2448-3129","contributorId":209947,"corporation":false,"usgs":true,"family":"Levin","given":"Sara B.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":876792,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70242968,"text":"70242968 - 2023 - Dynamics of streamflow permanence in a headwater network: Insights from catchment-scale model simulations","interactions":[],"lastModifiedDate":"2023-04-25T11:53:37.989298","indexId":"70242968","displayToPublicDate":"2023-04-01T06:47:45","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Dynamics of streamflow permanence in a headwater network: Insights from catchment-scale model simulations","docAbstract":"

The hillslope and channel dynamics that govern streamflow permanence in headwater systems have important implications for ecosystem functioning and downstream water quality. Recent advancements in process-based, semi-distributed hydrologic models that build upon empirical studies of streamflow permanence in well-monitored headwater catchments show promise for characterizing the dynamics of streamflow permanence in headwater systems. However, few process-based models consider the continuum of hillslope-stream network connectivity as a control on streamflow permanence in headwater systems. The objective of this study was to expand a process-based, catchment-scale hydrologic model to better understand the spatiotemporal dynamics of headwater streamflow permanence and to identify controls of streamflow expansion and contraction in a headwater network. Further, we aimed to develop an approach that enhanced the fidelity of model simulations, yet required little additional data, with the intent that the model might be later transferred to catchments with limited long-term and spatially explicit measurements. This approach facilitated network-scale estimates of the controls of streamflow expansion and contraction, albeit with higher degrees of uncertainty in individual reaches due to data constraints. Our model simulated that streamflow permanence was highly dynamic in first-order reaches with steep slopes and variable contributing areas. The simulated stream network length ranged from nearly 98±2% of the geomorphic channel extent during wet periods to nearly 50±10% during dry periods. The model identified a discharge threshold of approximately 1 mm d−1, above which the rate of streamflow expansion decreases by nearly an order of magnitude, indicating a lack of sensitivity of streamflow expansion to hydrologic forcing during high-flow periods. Overall, we demonstrate that process-based, catchment-scale models offer important insights on the controls of streamflow permanence, despite uncertainties and limitations of the model. We encourage researchers to increase data collection efforts and develop benchmarks to better evaluate such models.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2023.129422","usgsCitation":"Mahoney, D.T., Christensen, J., Golden, H., Lane, C., Evenson, G., White, E., Fritz, K., D’Amico, E., Barton, C.D., Williamson, T.N., Sena, K., and Agouridis, C., 2023, Dynamics of streamflow permanence in a headwater network: Insights from catchment-scale model simulations: Journal of Hydrology, v. 620, no. 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Rehabilitation of large Anthropocene rivers requires engagement of diverse stakeholders across a broad range of sociopolitical boundaries. Competing objectives often constrain options for ecological restoration of large rivers whereas fewer competing objectives may exist in a subset of tributaries. Further, tributaries contribute toward building a “portfolio” of river ecosystem assets through physical and biological processes that may present opportunities to enhance the resilience of large river fishes. Our goal is to review roles of tributaries in enhancing mainstem large river fish populations. We present case histories from two greatly altered and distinct large-river tributary systems that highlight how tributaries contribute four portfolio assets to support large-river fish populations: 1) habitat diversity, 2) connectivity, 3) ecological asynchrony, and 4) density-dependent processes. Finally, we identify future research directions to advance our understanding of tributary roles and inform conservation actions. In the Missouri River United States, we focus on conservation efforts for the state endangered lake sturgeon, which inhabits large rivers and tributaries in the Midwest and Eastern United States. In the Colorado River, Grand Canyon United States, we focus on conservation efforts for recovery of the federally threatened humpback chub. In the Missouri River, habitat diversity focused on physical habitats such as substrate for reproduction, and deep-water habitats for refuge, whereas augmenting habitat diversity for Colorado River fishes focused on managing populations in tributaries with minimally impaired thermal and flow regimes. Connectivity enhancements in the Missouri River focused on increasing habitat accessibility that may require removal of physical structures like low-head dams; whereas in the Colorado River, the lack of connectivity may benefit native fishes as the disconnection provides refuge from non-native fish predation. Hydrologic variability among tributaries was present in both systems, likely underscoring ecological asynchrony. These case studies also described density dependent processes that could influence success of restoration actions. Although actions to restore populations varied by river system, these examples show that these four portfolio assets can help guide restoration activities across a diverse range of mainstem rivers and their tributaries. Using these assets as a guide, we suggest these can be transferable to other large river-tributary systems.

","language":"English","publisher":"Frontiers","doi":"10.3389/fenvs.2023.1151315","usgsCitation":"Bouska, K.L., Healy, B.D., Moore, M.J., Dunn, C.G., Spurgeon, J.J., and Paukert, C.P., 2023, Diverse portfolios: Investing in tributaries for restoration of large river fishes in the Anthropocene: Frontiers in Environmental Science, v. 11, 1151315, 18 p., https://doi.org/10.3389/fenvs.2023.1151315.","productDescription":"1151315, 18 p.","ipdsId":"IP-149017","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":444048,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fenvs.2023.1151315","text":"Publisher Index Page"},{"id":416046,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","noUsgsAuthors":false,"publicationDate":"2023-03-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Bouska, Kristen L. 0000-0002-4115-2313 kbouska@usgs.gov","orcid":"https://orcid.org/0000-0002-4115-2313","contributorId":178005,"corporation":false,"usgs":true,"family":"Bouska","given":"Kristen","email":"kbouska@usgs.gov","middleInitial":"L.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":869951,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Healy, Brian D. 0000-0002-4402-638X","orcid":"https://orcid.org/0000-0002-4402-638X","contributorId":304257,"corporation":false,"usgs":true,"family":"Healy","given":"Brian","middleInitial":"D.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":869952,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moore, Michael J. 0000-0002-5495-7049","orcid":"https://orcid.org/0000-0002-5495-7049","contributorId":304258,"corporation":false,"usgs":true,"family":"Moore","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":869953,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dunn, Corey Garland 0000-0002-7102-2165","orcid":"https://orcid.org/0000-0002-7102-2165","contributorId":288691,"corporation":false,"usgs":true,"family":"Dunn","given":"Corey","email":"","middleInitial":"Garland","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":869954,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Spurgeon, Jonathan J. 0000-0002-6888-5867","orcid":"https://orcid.org/0000-0002-6888-5867","contributorId":304259,"corporation":false,"usgs":true,"family":"Spurgeon","given":"Jonathan","middleInitial":"J.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":869955,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Paukert, Craig P. 0000-0002-9369-8545","orcid":"https://orcid.org/0000-0002-9369-8545","contributorId":245524,"corporation":false,"usgs":true,"family":"Paukert","given":"Craig","middleInitial":"P.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":869956,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70251080,"text":"70251080 - 2023 - A framework for estimating global river discharge from the Surface Water and Ocean Topography satellite mission","interactions":[],"lastModifiedDate":"2024-01-21T22:20:07.018816","indexId":"70251080","displayToPublicDate":"2023-03-27T16:18:03","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"A framework for estimating global river discharge from the Surface Water and Ocean Topography satellite mission","docAbstract":"

The Surface Water and Ocean Topography (SWOT) mission will vastly expand measurements of global rivers, providing critical new data sets for both gaged and ungaged basins. SWOT discharge products (available approximately 1 year after launch) will provide discharge for all river that reaches wider than 100 m. In this paper, we describe how SWOT discharge produced and archived by the US and French space agencies will be computed from measurements of river water surface elevation, width, and slope and ancillary data, along with expected discharge accuracy. We present for the first time a complete estimate of the SWOT discharge uncertainty budget, with separate terms for random (standard error) and systematic (bias) uncertainty components in river discharge time series. We expect that discharge uncertainty will be less than 30% for two-thirds of global reaches and will be dominated by bias. Separate river discharge estimates will combine both SWOT and in situ data; these “gage-constrained” discharge estimates can be expected to have lower systematic uncertainty. Temporal variations in river discharge time series will be dominated by random error and are expected to be estimated within 15% for nearly all reaches, allowing accurate inference of event flow dynamics globally, including in ungaged basins. We believe this level of accuracy lays the groundwork for SWOT to enable breakthroughs in global hydrologic science.

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021WR031614","usgsCitation":"Durand, M., Gleason, C., Pavelsky, T., Frasson, R., Turmon, M., David, C., Altenau, E., Tebaldi, N., Larnier, K., Monnier, J., Malaterre, P., Oubanas, H., Allen, G.H., Astifan, B., Brinkerhoff, C., Bates, P., Bjerklie, D.M., Coss, S., Dudley, R., Fengolio, L., Garambois, P., Getirana, A., Lin, P., Margulis, S.A., Matte, P., Minear, J., Muhebwa, A., Pan, M., Peters, D.L., Riggs, R., Sikder, S., Simmons, T., Stuurman, C., Taneja, J., Tarpanelli, A., Schulze, K., Tourian, M., and Wang, J., 2023, A framework for estimating global river discharge from the Surface Water and Ocean Topography satellite mission: Water Resources Research, v. 59, no. 4, e2021WR031614, 31 p., https://doi.org/10.1029/2021WR031614.","productDescription":"e2021WR031614, 31 p.","ipdsId":"IP-142706","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":444055,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2021wr031614","text":"Publisher Index Page"},{"id":424667,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"59","issue":"4","noUsgsAuthors":false,"publicationDate":"2023-04-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Durand, Michael","contributorId":331079,"corporation":false,"usgs":false,"family":"Durand","given":"Michael","affiliations":[{"id":36630,"text":"Ohio State University","active":true,"usgs":false}],"preferred":false,"id":892993,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gleason, Colin","contributorId":213715,"corporation":false,"usgs":false,"family":"Gleason","given":"Colin","affiliations":[],"preferred":false,"id":892994,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pavelsky, Tamlin","contributorId":149629,"corporation":false,"usgs":false,"family":"Pavelsky","given":"Tamlin","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":892995,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Frasson, Renato 0000-0003-4299-1730","orcid":"https://orcid.org/0000-0003-4299-1730","contributorId":258827,"corporation":false,"usgs":false,"family":"Frasson","given":"Renato","email":"","affiliations":[{"id":39742,"text":"Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA.","active":true,"usgs":false}],"preferred":false,"id":892996,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Turmon, Michael","contributorId":225055,"corporation":false,"usgs":false,"family":"Turmon","given":"Michael","email":"","affiliations":[{"id":41027,"text":"NASA JPL/CalTech","active":true,"usgs":false}],"preferred":false,"id":892997,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"David, Cedric H.","contributorId":258841,"corporation":false,"usgs":false,"family":"David","given":"Cedric H.","affiliations":[{"id":27151,"text":"Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA","active":true,"usgs":false}],"preferred":false,"id":892998,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Altenau, Elizabeth","contributorId":333510,"corporation":false,"usgs":false,"family":"Altenau","given":"Elizabeth","email":"","affiliations":[{"id":24532,"text":"Department of Geological Sciences, University of North Carolina, Chapel Hill, NC 27599, USA","active":true,"usgs":false}],"preferred":false,"id":892999,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Tebaldi, Nikki","contributorId":333511,"corporation":false,"usgs":false,"family":"Tebaldi","given":"Nikki","email":"","affiliations":[{"id":79905,"text":"Department of Civil and Environmental Engineering, University of Massachusetts Amherst","active":true,"usgs":false}],"preferred":false,"id":893000,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Larnier, Kevin","contributorId":333512,"corporation":false,"usgs":false,"family":"Larnier","given":"Kevin","email":"","affiliations":[{"id":79906,"text":"Space Department, CS Corporation, Toulouse, France","active":true,"usgs":false}],"preferred":false,"id":893001,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Monnier, Jerome","contributorId":258839,"corporation":false,"usgs":false,"family":"Monnier","given":"Jerome","email":"","affiliations":[{"id":52305,"text":"INSA Toulouse - Math. 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Ming","contributorId":333523,"corporation":false,"usgs":false,"family":"Pan","given":"Ming","email":"","affiliations":[{"id":79915,"text":"Center for Western Weather and Water Extremes, Scripps Institution of Oceanography, University of California San Diego, La Jolla, California, USA","active":true,"usgs":false}],"preferred":false,"id":893020,"contributorType":{"id":1,"text":"Authors"},"rank":28},{"text":"Peters, Daniel L.","contributorId":315429,"corporation":false,"usgs":false,"family":"Peters","given":"Daniel","email":"","middleInitial":"L.","affiliations":[{"id":36681,"text":"Environment and Climate Change Canada","active":true,"usgs":false}],"preferred":false,"id":893021,"contributorType":{"id":1,"text":"Authors"},"rank":29},{"text":"Riggs, Ryan","contributorId":333524,"corporation":false,"usgs":false,"family":"Riggs","given":"Ryan","email":"","affiliations":[{"id":79916,"text":"Department of Geography, Texas A&M University, College Station, TX, 77843, USA","active":true,"usgs":false}],"preferred":false,"id":893022,"contributorType":{"id":1,"text":"Authors"},"rank":30},{"text":"Sikder, Safat","contributorId":333525,"corporation":false,"usgs":false,"family":"Sikder","given":"Safat","email":"","affiliations":[{"id":79917,"text":"Department of Geography and Geospatial Sciences, Kansas State University, Manhattan, KS, USA.","active":true,"usgs":false}],"preferred":false,"id":893023,"contributorType":{"id":1,"text":"Authors"},"rank":31},{"text":"Simmons, Travis","contributorId":333526,"corporation":false,"usgs":false,"family":"Simmons","given":"Travis","email":"","affiliations":[{"id":79905,"text":"Department of Civil and Environmental Engineering, University of Massachusetts Amherst","active":true,"usgs":false}],"preferred":false,"id":893024,"contributorType":{"id":1,"text":"Authors"},"rank":32},{"text":"Stuurman, Cassie","contributorId":239994,"corporation":false,"usgs":false,"family":"Stuurman","given":"Cassie","email":"","affiliations":[{"id":36276,"text":"JPL","active":true,"usgs":false}],"preferred":false,"id":893025,"contributorType":{"id":1,"text":"Authors"},"rank":33},{"text":"Taneja, Jay","contributorId":333527,"corporation":false,"usgs":false,"family":"Taneja","given":"Jay","email":"","affiliations":[{"id":79914,"text":"Department of Electrical and Computer Engineering, University of Massachusetts, Amherst , USA","active":true,"usgs":false}],"preferred":false,"id":893026,"contributorType":{"id":1,"text":"Authors"},"rank":34},{"text":"Tarpanelli, Angelica","contributorId":333528,"corporation":false,"usgs":false,"family":"Tarpanelli","given":"Angelica","email":"","affiliations":[{"id":79918,"text":"Research Institute for Geo-Hydrological protection, National Research Council, Via Madonna Alta 126, Perugia, Italy","active":true,"usgs":false}],"preferred":false,"id":893027,"contributorType":{"id":1,"text":"Authors"},"rank":35},{"text":"Schulze, Kerstin","contributorId":333529,"corporation":false,"usgs":false,"family":"Schulze","given":"Kerstin","email":"","affiliations":[{"id":79911,"text":"Department of Geodesy and Geoinformation, University of Bonn, Bonn, Germany","active":true,"usgs":false}],"preferred":false,"id":893028,"contributorType":{"id":1,"text":"Authors"},"rank":36},{"text":"Tourian, Mohammad","contributorId":333530,"corporation":false,"usgs":false,"family":"Tourian","given":"Mohammad","email":"","affiliations":[{"id":79919,"text":"Institute of Geodesy, University of Stuttgart, Germany","active":true,"usgs":false}],"preferred":false,"id":893029,"contributorType":{"id":1,"text":"Authors"},"rank":37},{"text":"Wang, Jida","contributorId":333531,"corporation":false,"usgs":false,"family":"Wang","given":"Jida","email":"","affiliations":[{"id":79917,"text":"Department of Geography and Geospatial Sciences, Kansas State University, Manhattan, KS, USA.","active":true,"usgs":false}],"preferred":false,"id":893030,"contributorType":{"id":1,"text":"Authors"},"rank":38}]}} ,{"id":70242725,"text":"70242725 - 2023 - Uptake of per- and polyfluoroalkyl substances by fish, mussel, and passive samplers in mobile laboratory exposures using groundwater from a contamination plume at a historical fire training area, Cape Cod, Massachusetts","interactions":[],"lastModifiedDate":"2023-04-14T11:55:48.98417","indexId":"70242725","displayToPublicDate":"2023-03-27T06:49:07","publicationYear":"2023","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":"Uptake of per- and polyfluoroalkyl substances by fish, mussel, and passive samplers in mobile laboratory exposures using groundwater from a contamination plume at a historical fire training area, Cape Cod, Massachusetts","docAbstract":"

Aqueous film-forming foams historically were used during fire training activities on Joint Base Cape Cod, Massachusetts, and created an extensive per- and polyfluoroalkyl substances (PFAS) groundwater contamination plume. The potential for PFAS bioconcentration from exposure to the contaminated groundwater, which discharges to surface water bodies, was assessed with mobile-laboratory experiments using groundwater from the contamination plume and a nearby reference location. The on-site continuous-flow 21-day exposures used male and female fathead minnows, freshwater mussels, polar organic chemical integrative samplers (POCIS), and polyethylene tube samplers (PETS) to evaluate biotic and abiotic uptake. The composition of the PFAS-contaminated groundwater was complex and 9 PFAS were detected in the reference groundwater and 17 PFAS were detected in the contaminated groundwater. The summed PFAS concentrations ranged from 120 to 140 ng L–1 in reference groundwater and 6100 to 15,000 ng L–1 in contaminated groundwater. Biotic concentration factors (CFb) for individual PFAS were species, sex, source, and compound-specific and ranged from 2.9 to 1000 L kg–1 in whole-body male fish exposed to contaminated groundwater for 21 days. The fish and mussel CFb generally increased with increasing fluorocarbon chain length and were greater for sulfonates than for carboxylates. The exception was perfluorohexane sulfonate, which deviated from the linear trend and had a 10-fold difference in CFb between sites, possibly because of biotransformation of precursors such as perfluorohexane sulfonamide. Uptake for most PFAS in male fish was linear over time, whereas female fish had bilinear uptake indicated by an initial increase in tissue concentrations followed by a decrease. Uptake of PFAS was less for mussels (maximum CFb = 200) than for fish, and mussel uptake of most PFAS also was bilinear. Although abiotic concentration factors were greater than CFb, and values for POCIS were greater than for PETS, passive samplers were useful for assessing PFAS that potentially bioconcentrate in fish but are present at concentrations below method quantitation limits in water. Passive samplers also accumulate short-chain PFAS that are not bioconcentrated.

","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.2c06500","usgsCitation":"Barber, L., Pickard, H.M., Alvarez, D.A., Becanova, J., Keefe, S.H., LeBlanc, D.R., Lohmann, R., Steevens, J.A., and Vajda, A.M., 2023, Uptake of per- and polyfluoroalkyl substances by fish, mussel, and passive samplers in mobile laboratory exposures using groundwater from a contamination plume at a historical fire training area, Cape Cod, Massachusetts: Environmental Science and Technology, v. 57, no. 14, p. 5544-5557, https://doi.org/10.1021/acs.est.2c06500.","productDescription":"14 p.","startPage":"5544","endPage":"5557","ipdsId":"IP-121897","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":38175,"text":"Toxics Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":444066,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/10116195","text":"External Repository"},{"id":435404,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9LCN0EF","text":"USGS data release","linkHelpText":"Uptake of Per- and Polyfluoroalkyl Substances by Fish, Mussel, and Passive Samplers in Mobile Laboratory Exposures using Groundwater from a Contamination Plume at a Historical Fire Training Area, Cape Cod, Massachusetts - Chemical and Biological Data from August to September 2018"},{"id":415771,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Massachusetts","otherGeospatial":"Cape Cod","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -70.68647141190323,\n 42.211476864603554\n ],\n [\n -70.68647141190323,\n 41.50810472445593\n ],\n [\n -69.8326516793067,\n 41.50810472445593\n ],\n [\n -69.8326516793067,\n 42.211476864603554\n ],\n [\n -70.68647141190323,\n 42.211476864603554\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"57","issue":"14","noUsgsAuthors":false,"publicationDate":"2023-03-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Barber, Larry B. 0000-0002-0561-0831","orcid":"https://orcid.org/0000-0002-0561-0831","contributorId":218953,"corporation":false,"usgs":true,"family":"Barber","given":"Larry B.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":38175,"text":"Toxics Substances Hydrology Program","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":869505,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pickard, Heidi M. 0000-0001-8312-7522","orcid":"https://orcid.org/0000-0001-8312-7522","contributorId":261821,"corporation":false,"usgs":false,"family":"Pickard","given":"Heidi","email":"","middleInitial":"M.","affiliations":[{"id":53027,"text":"Harvard John A. Paulson School of Engineering and Applied Sciences","active":true,"usgs":false}],"preferred":false,"id":869506,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Alvarez, David A. 0000-0002-6918-2709","orcid":"https://orcid.org/0000-0002-6918-2709","contributorId":220763,"corporation":false,"usgs":true,"family":"Alvarez","given":"David","middleInitial":"A.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":869507,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Becanova, Jitka 0000-0002-3091-1054","orcid":"https://orcid.org/0000-0002-3091-1054","contributorId":304148,"corporation":false,"usgs":false,"family":"Becanova","given":"Jitka","email":"","affiliations":[{"id":37391,"text":"University of Rhode Island, Graduate School of Oceanography","active":true,"usgs":false}],"preferred":false,"id":869508,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Keefe, Steffanie H. 0000-0002-3805-6101 shkeefe@usgs.gov","orcid":"https://orcid.org/0000-0002-3805-6101","contributorId":2843,"corporation":false,"usgs":true,"family":"Keefe","given":"Steffanie","email":"shkeefe@usgs.gov","middleInitial":"H.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":869509,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"LeBlanc, Denis R. 0000-0002-4646-2628","orcid":"https://orcid.org/0000-0002-4646-2628","contributorId":219907,"corporation":false,"usgs":true,"family":"LeBlanc","given":"Denis","email":"","middleInitial":"R.","affiliations":[{"id":38175,"text":"Toxics Substances Hydrology Program","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":869510,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lohmann, Rainer 0000-0001-8796-3229","orcid":"https://orcid.org/0000-0001-8796-3229","contributorId":304150,"corporation":false,"usgs":false,"family":"Lohmann","given":"Rainer","email":"","affiliations":[{"id":37391,"text":"University of Rhode Island, Graduate School of Oceanography","active":true,"usgs":false}],"preferred":false,"id":869511,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Steevens, Jeffery A. 0000-0003-3946-1229","orcid":"https://orcid.org/0000-0003-3946-1229","contributorId":207511,"corporation":false,"usgs":true,"family":"Steevens","given":"Jeffery","middleInitial":"A.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":869512,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Vajda, Alan M.","contributorId":156301,"corporation":false,"usgs":false,"family":"Vajda","given":"Alan","email":"","middleInitial":"M.","affiliations":[{"id":6713,"text":"University of Colorado, Boulder CO","active":true,"usgs":false}],"preferred":false,"id":869513,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70241125,"text":"sir20225132 - 2023 - Evaluation of potential stresses and hydrologic conditions driving water-level fluctuations in well ER-5-3-2, Frenchman Flat, southern Nevada","interactions":[],"lastModifiedDate":"2026-02-24T18:04:17.753698","indexId":"sir20225132","displayToPublicDate":"2023-03-22T14:27:54","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-5132","displayTitle":"Evaluation of Potential Stresses and Hydrologic Conditions Driving Water-Level Fluctuations in Well ER-5-3-2, Frenchman Flat, Southern Nevada","title":"Evaluation of potential stresses and hydrologic conditions driving water-level fluctuations in well ER-5-3-2, Frenchman Flat, southern Nevada","docAbstract":"

Well ER-5-3-2 is part of a well network designed to monitor long-term water levels and radionuclide concentrations downgradient from underground nuclear tests that occurred in Frenchman Flat, an area of the U.S. Department of Energy Nevada National Security Site in southern Nevada. Interpretation of monitoring records for well ER-5-3-2 was confounded by previously unexplained water-level fluctuations in the well hydrograph. This study integrated geologic, hydrologic, and water-chemistry data to evaluate potential stresses and hydrologic conditions that likely affected the well ER-5-3-2 hydrograph. Numerical groundwater models were applied to evaluate four model scenarios: (1) wellbore leakage without recharge, (2) wellbore leakage with recharge, (3) equilibration to vertical heterogeneities between shallow (low transmissivity) and deep (higher transmissivity) carbonate zones, and (4) equilibration to lateral heterogeneities in carbonate rocks.

Meteoric recharge was not the cause of the 21-foot (ft) water-level rise in well ER-5-3-2 from 2001 to 2011 or the 4-ft decline from 2012 to 2016. Based on observed water-level fluctuations in nearby wells, the water-level rise and decline from recharge for these periods was less than 3 and 1 ft, respectively. The lateral-heterogeneity scenario is based on the assumption that the 21-ft water-level rise from 2001 to 2011 was a natural water-level reequilibration following the pumping-induced depressurization of a large volume of high transmissivity and low-storage carbonate rock that is surrounded by low transmissivity and high-storage carbonate rock. The lateral-heterogeneity scenario was discounted because simulated water levels cannot match the well ER-5-3-2 hydrograph. Underground nuclear testing and temperature effects were discounted based on hydraulic connections and water-temperature data.

Wellbore-leakage scenarios are based on the assumption that the water-level rise was sustained from leakage rates required to cause a localized mounding in the carbonate system near well ER-5-3-2, where the carbonate transmissivity is 530 square feet per day. Even though simulated and measured water levels compare favorably for scenarios of wellbore leakage with and without recharge, large volumes (178–184 million gallons) of groundwater from volcanic rocks would be required to leak into the carbonate system, which is not supported by water-chemistry data.

An alternative conceptualization of wellbore leakage is based on the assumption that the 21-ft water-level rise from 2001 to 2011 was sustained by the hydraulic disconnection of well ER-5-3-2 from the carbonate system. The disconnection occurred several months after a constant-rate test in well ER-5-3-2 when carbonate rocks were hydraulically disconnected from the well by either (1) the shifting of sloughed fill in the open hole or (2) the encrusting of carbonate precipitate in the well screen. The hydraulic disconnection effectively sealed the well and caused a 21-ft water-level rise from wellbore leakage during 2001–11. In this case, total wellbore leakage from 2001 to 2011 was about 50 gallons. The 4-ft water-level decline from 2012 to 2016 was conceptualized to have occurred from the slow breaking of the seal and reconnection of the well to the carbonate system. This alternative conceptualization of wellbore leakage was consistent with water-chemistry analyses because the computed wellbore leakage (50 gallons) was small relative to purged volumes (30,000–40,000 gallons) for sampling, and the water chemistry would not be expected to change.

The shallow-deep carbonate scenario provided another explanation for the well ER-5-3-2 hydrograph. This scenario is based on the assumption that well-construction effects and vertical heterogeneity of the carbonate system explain the ER-5-3-2 water-level trend. Well-construction effects are attributed to a temporary clogging of the open interval below the well screen that was opened during pumping events, which affected the hydraulic connection of deep transmissive carbonate rocks to the wellbore. The 21-ft water-level rise from 2001 to 2011 was a natural equilibration to shallow, low-transmissivity carbonate rocks during a period when the lower open interval was clogged. The 4-ft decline from 2012 to 2016 represents equilibration between the shallow and deep intervals, because of a partial unclogging of the connection between the two intervals. The low water levels from 2016 to 2021 resulted from pumping for sampling and an unclogging of the open interval so that the low head in the deep carbonate dominated the water level. Despite potential well-construction effects, from either a wellbore leakage or shallow-deep carbonate scenario, samples collected from well ER-5-3-2 are representative of the carbonate system.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225132","collaboration":"Prepared in cooperation with the U.S. Department of Energy, National Nuclear Security Administration Nevada Site Office, Office of Environmental Management under Interagency Agreement, DE-EM0004969","usgsCitation":"Jackson, T.R., and Frus, R.J., 2023, Evaluation of potential stresses and hydrologic conditions driving water-level fluctuations in well ER-5-3-2, Frenchman Flat, southern Nevada: U.S. Geological Survey Scientific Investigations Report 2022–5132, 35 p., https://doi.org/10.3133/sir20225132.","productDescription":"Report: viii, 35 p.; Data Release","numberOfPages":"35","onlineOnly":"Y","ipdsId":"IP-139917","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":413963,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P95C0NG5","text":"MODFLOW 6 models used to evaluate potential stresses and hydrologic conditions driving water-level fluctuations in well ER-5-3-2, Frenchman Flat, southern Nevada","description":"Jackson, T.R., and Frus, R.J., 2023, MODFLOW 6 models used to evaluate potential stresses and hydrologic conditions driving water-level fluctuations in well ER-5-3-2, Frenchman Flat, southern Nevada: U.S. Geological Survey data release, available at https://doi.org/10.5066/P95C0NG5."},{"id":500485,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114613.htm","linkFileType":{"id":5,"text":"html"}},{"id":413973,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20225132/full"},{"id":413962,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5132/images"},{"id":413961,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5132/sir20225132.xml"},{"id":413960,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5132/sir20225132.pdf","text":"Report","size":"6 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":413959,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5132/covrthb.jpg"}],"country":"United States","state":"Nevada","otherGeospatial":"Frenchman Flat","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -116.05668643871044,\n 36.549912612507626\n ],\n [\n -116.05668643871044,\n 35.84481987187543\n ],\n [\n -115.27945901304658,\n 35.84481987187543\n ],\n [\n -115.27945901304658,\n 36.549912612507626\n ],\n [\n -116.05668643871044,\n 36.549912612507626\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

Director,
Nevada Water Science Center
U.S. Geological Survey
2730 N. Deer Run Road
Carson City, Nevada 89701

","tableOfContents":"","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2023-03-22","noUsgsAuthors":false,"publicationDate":"2023-03-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Jackson, Tracie R. 0000-0001-8553-0323","orcid":"https://orcid.org/0000-0001-8553-0323","contributorId":215365,"corporation":false,"usgs":true,"family":"Jackson","given":"Tracie R.","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866169,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Frus, Rebecca J. 0000-0002-2435-7202","orcid":"https://orcid.org/0000-0002-2435-7202","contributorId":206261,"corporation":false,"usgs":true,"family":"Frus","given":"Rebecca","email":"","middleInitial":"J.","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866170,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70255298,"text":"70255298 - 2023 - Understanding the spatiotemporal distribution of snow refugia in the rain-snow transition zone of north-central Idaho","interactions":[],"lastModifiedDate":"2024-06-14T12:24:56.984299","indexId":"70255298","displayToPublicDate":"2023-03-21T07:19:45","publicationYear":"2023","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":"Understanding the spatiotemporal distribution of snow refugia in the rain-snow transition zone of north-central Idaho","docAbstract":"

Knowledge of snow cover distribution and disappearance dates over a wide range of scales is imperative for understanding hydrological dynamics and for habitat management of wildlife species that rely on snow cover. Identification of snow refugia, or places with relatively late snow disappearance dates (SDDs) compared to surrounding areas, is especially important as climate change alters snow cover timing and duration. The purpose of this study was to increase understanding of snow refugia in complex terrain spanning the rain-snow transition zone at fine spatial and temporal scales. To accomplish this objective, we used remote cameras to provide relatively high temporal and spatial resolution measurements on snowpack conditions. We built linear models to relate SDDs at the monitoring sites to topoclimatic and canopy cover metrics. One model to quantify SDDs included elevation, aspect, and an interaction between canopy cover and cold-air pooling potential. High-elevation, north-facing sites in cold-air pools (CAPs) had the latest SDDs, but isolated lower-elevation points also exhibited relatively late potential SDDs. Importantly, canopy cover had a much stronger effect on SDDs in CAPs than in non-CAPs, indicating that best practices in forest management for snow refugia could vary across microtopography. A second model that included in situ hydroclimate observations (December–February (DJF) temperature and March 1 snow depth) indicated that March 1 snow depth had little impact on SDD at the coldest winter temperatures, and that DJF temperatures had a stronger effect on SDD at lower snow depths, implying that the relative importance of snowfall and temperature could vary across hydroclimatic contexts in their impact on snow refugia. This new understanding of factors influencing snow refugia can guide forest management actions to increase snow retention and inform management of snow-dependent wildlife species in complex terrain.

","language":"English","publisher":"IOPScience","doi":"10.1088/1748-9326/acbb90","usgsCitation":"Strickfaden, K.M., Marshall, A.M., Svancara, L.K., Dugger, K., and Link, T.E., 2023, Understanding the spatiotemporal distribution of snow refugia in the rain-snow transition zone of north-central Idaho: Environmental Research Letters, v. 18, 044014, 11 p., https://doi.org/10.1088/1748-9326/acbb90.","productDescription":"044014, 11 p.","ipdsId":"IP-147918","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":444142,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/1748-9326/acbb90","text":"Publisher Index Page"},{"id":430200,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"18","noUsgsAuthors":false,"publicationDate":"2023-03-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Strickfaden, Kaitlyn M.","contributorId":339386,"corporation":false,"usgs":false,"family":"Strickfaden","given":"Kaitlyn","email":"","middleInitial":"M.","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":904127,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Marshall, Adrienne M.","contributorId":339387,"corporation":false,"usgs":false,"family":"Marshall","given":"Adrienne","email":"","middleInitial":"M.","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":904128,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Svancara, Leona K.","contributorId":339389,"corporation":false,"usgs":false,"family":"Svancara","given":"Leona","email":"","middleInitial":"K.","affiliations":[{"id":36224,"text":"Idaho Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":904129,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dugger, Katie M. 0000-0002-4148-246X cdugger@usgs.gov","orcid":"https://orcid.org/0000-0002-4148-246X","contributorId":4399,"corporation":false,"usgs":true,"family":"Dugger","given":"Katie","email":"cdugger@usgs.gov","middleInitial":"M.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":904130,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Link, Timothy E.","contributorId":339393,"corporation":false,"usgs":false,"family":"Link","given":"Timothy","email":"","middleInitial":"E.","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":904131,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70241616,"text":"70241616 - 2023 - Integrating terrestrial and aquatic ecosystems to constrain estimates of land-atmosphere carbon exchange","interactions":[],"lastModifiedDate":"2023-03-24T11:57:44.122655","indexId":"70241616","displayToPublicDate":"2023-03-21T06:53:25","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2842,"text":"Nature Communications","active":true,"publicationSubtype":{"id":10}},"title":"Integrating terrestrial and aquatic ecosystems to constrain estimates of land-atmosphere carbon exchange","docAbstract":"

In this Perspective, we put forward an integrative framework to improve estimates of land-atmosphere carbon exchange based on the accumulation of carbon in the landscape as constrained by its lateral export through rivers. The framework uses the watershed as the fundamental spatial unit and integrates all terrestrial and aquatic ecosystems as well as their hydrologic carbon exchanges. Application of the framework should help bridge the existing gap between land and atmosphere-based approaches and offers a platform to increase communication and synergy among the terrestrial, aquatic, and atmospheric research communities that is paramount to advance landscape carbon budget assessments.

","language":"English","publisher":"Nature","doi":"10.1038/s41467-023-37232-2","usgsCitation":"Casas-Ruiz, J., Bodmer, P., Bona, K.A., Butman, D., Couturier, M., Emilson, E.J., Finlay, K., Genet, H., Hayes, D., Karlsson, J., Pare, D., Peng, C., Striegl, R.G., Webb, J., Wei, X., Ziegler, S., and Del Giorgio, P., 2023, Integrating terrestrial and aquatic ecosystems to constrain estimates of land-atmosphere carbon exchange: Nature Communications, v. 14, 1571, 17 p., https://doi.org/10.1038/s41467-023-37232-2.","productDescription":"1571, 17 p.","ipdsId":"IP-146296","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":444145,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41467-023-37232-2","text":"Publisher Index Page"},{"id":414690,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","noUsgsAuthors":false,"publicationDate":"2023-03-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Casas-Ruiz, Joan","contributorId":303397,"corporation":false,"usgs":false,"family":"Casas-Ruiz","given":"Joan","email":"","affiliations":[{"id":65789,"text":"Research Group on Ecology of Inland Waters, Institute of Aquatic Ecology, University of Girona, Girona, Spain","active":true,"usgs":false}],"preferred":false,"id":867499,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bodmer, Pascal","contributorId":303398,"corporation":false,"usgs":false,"family":"Bodmer","given":"Pascal","email":"","affiliations":[{"id":65790,"text":"Groupe de Recherche Interuniversitaire en Limnologie (GRIL), Département des sciences biologiques, Université du Québec à Montréal, Montréal, Québec, Canada","active":true,"usgs":false}],"preferred":false,"id":867500,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bona, Kelly Ann","contributorId":303399,"corporation":false,"usgs":false,"family":"Bona","given":"Kelly","email":"","middleInitial":"Ann","affiliations":[{"id":65791,"text":"Environment and Climate Change Canada, Gatineau, Quebec, Canada","active":true,"usgs":false}],"preferred":false,"id":867501,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Butman, David","contributorId":224754,"corporation":false,"usgs":false,"family":"Butman","given":"David","affiliations":[{"id":16962,"text":"U. Washington","active":true,"usgs":false}],"preferred":false,"id":867502,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Couturier, Mathilde","contributorId":303400,"corporation":false,"usgs":false,"family":"Couturier","given":"Mathilde","email":"","affiliations":[{"id":65790,"text":"Groupe de Recherche Interuniversitaire en Limnologie (GRIL), Département des sciences biologiques, Université du Québec à Montréal, Montréal, Québec, Canada","active":true,"usgs":false}],"preferred":false,"id":867503,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Emilson, Erik J.S.","contributorId":245463,"corporation":false,"usgs":false,"family":"Emilson","given":"Erik","email":"","middleInitial":"J.S.","affiliations":[{"id":49199,"text":"Natural Resources Canada, Canadian Forest ServiceGreat Lakes Forestry Centre, Sault Ste. Marie, Canada","active":true,"usgs":false}],"preferred":false,"id":867504,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Finlay, Kerri","contributorId":289777,"corporation":false,"usgs":false,"family":"Finlay","given":"Kerri","email":"","affiliations":[{"id":27547,"text":"University of Regina","active":true,"usgs":false}],"preferred":false,"id":867505,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Genet, Helene","contributorId":198686,"corporation":false,"usgs":false,"family":"Genet","given":"Helene","email":"","affiliations":[],"preferred":false,"id":867506,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hayes, Daniel B.","contributorId":248252,"corporation":false,"usgs":false,"family":"Hayes","given":"Daniel B.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":867507,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Karlsson, Jan","contributorId":139660,"corporation":false,"usgs":false,"family":"Karlsson","given":"Jan","email":"","affiliations":[{"id":12869,"text":"Dept. of Ecology and Environmental Science, Umeå University, Umeå, Sweden.","active":true,"usgs":false}],"preferred":false,"id":867508,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Pare, David","contributorId":303401,"corporation":false,"usgs":false,"family":"Pare","given":"David","email":"","affiliations":[{"id":65793,"text":"Natural Resources Canada, Québec, Québec, Canada","active":true,"usgs":false}],"preferred":false,"id":867509,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Peng, Changhui","contributorId":197932,"corporation":false,"usgs":false,"family":"Peng","given":"Changhui","email":"","affiliations":[{"id":6613,"text":"Center of CEF/ESCER, Department of Biological Science, University of Quebec at Montreal, Montreal H3C 3P8, Canada","active":true,"usgs":false},{"id":6612,"text":"State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Northwest A&F University, Yangling 712100, China","active":true,"usgs":false}],"preferred":false,"id":867510,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Striegl, Robert G. 0000-0002-8251-4659 rstriegl@usgs.gov","orcid":"https://orcid.org/0000-0002-8251-4659","contributorId":1630,"corporation":false,"usgs":true,"family":"Striegl","given":"Robert","email":"rstriegl@usgs.gov","middleInitial":"G.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":false,"id":867511,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Webb, Jackie","contributorId":293904,"corporation":false,"usgs":false,"family":"Webb","given":"Jackie","email":"","affiliations":[],"preferred":false,"id":867512,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Wei, Xinyuan","contributorId":303402,"corporation":false,"usgs":false,"family":"Wei","given":"Xinyuan","email":"","affiliations":[{"id":65794,"text":"Center for Research on Sustainable Forests, University of Maine, Orono, Maine, USA","active":true,"usgs":false}],"preferred":false,"id":867513,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Ziegler, Sue","contributorId":303403,"corporation":false,"usgs":false,"family":"Ziegler","given":"Sue","email":"","affiliations":[{"id":65796,"text":"Memorial University of Newfoundland, St. John’s, Newfoundland and Labrador, Canada","active":true,"usgs":false}],"preferred":false,"id":867514,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Del Giorgio, Paul","contributorId":211167,"corporation":false,"usgs":false,"family":"Del Giorgio","given":"Paul","email":"","affiliations":[{"id":38187,"text":"Université du Québec à Montréal, Quebec, Montreal, Canada","active":true,"usgs":false}],"preferred":false,"id":867515,"contributorType":{"id":1,"text":"Authors"},"rank":17}]}} ,{"id":70248233,"text":"70248233 - 2023 - Assessing potential effects of climate change on highway-runoff flows and loads in southern New England by using planning-level space-for-time analyses","interactions":[],"lastModifiedDate":"2023-09-05T12:11:07.324945","indexId":"70248233","displayToPublicDate":"2023-03-19T07:06:24","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":16697,"text":"Transportation Research Record, Journal of the Transportation Research Board.","active":true,"publicationSubtype":{"id":10}},"title":"Assessing potential effects of climate change on highway-runoff flows and loads in southern New England by using planning-level space-for-time analyses","docAbstract":"
Transportation agencies need information about the potential effects of climate change on the volume, quality, and treatment of stormwater to mitigate potential effects of runoff on receiving waters. To address these concerns, the U.S. Geological Survey and the Federal Highway Administration used the Coupled Model Intercomparison Project tool and the Stochastic Empirical Loading and Dilution Model to perform space-for-time stormwater quality analyses. This study indicated that spatial variations in precipitation statistics within and adjacent to southern New England are greater than projected climate-related changes for the centroid of this region. A dilution-factor analysis indicated that highway runoff would become a greater proportion of downstream flows if average event volumes or time between event midpoints increase and would become a smaller proportion of downstream flows if event durations increase. Highway-runoff yield analyses for total phosphorus (TP) indicate that uncertainty in water quality statistics results in variations in long-term average yields from about 1.69 to 7.96 times higher than the lowest TP values simulated. In comparison, variations in precipitation statistics cause yield variations that ranged from 1.41 to 1.76 for the different simulated concentrations. An analysis of stormwater treatment indicated that uncertainties in runoff treatment variables are also larger than the magnitude of climate variations. This study does not question the potentially large climate-related changes in hydrologic and hydraulic variables expected to occur in the foreseeable future. It does indicate that uncertainties in the current data and potential effects of land use change on stormwater quality and treatment variables are larger than the projected effects of climate change.
","language":"English","publisher":"Sage","doi":"10.1177/03611981231155183","usgsCitation":"Jeznach, L.C., Granato, G., Sharar-Salgado, D., Jones, S.C., and Imig, D., 2023, Assessing potential effects of climate change on highway-runoff flows and loads in southern New England by using planning-level space-for-time analyses: Transportation Research Record, Journal of the Transportation Research Board., v. 2677, no. 7, p. 570-581, https://doi.org/10.1177/03611981231155183.","productDescription":"12 p.","startPage":"570","endPage":"581","ipdsId":"IP-143447","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":444172,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1177/03611981231155183","text":"Publisher Index Page"},{"id":420466,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Connecticut, Rhode Island, 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Des Moines Water Works (DMWW) is one of the largest water providers in Iowa and as population growth continues, demand for drinking water is increasing. DMWW uses groundwater and surface water as raw water sources to supply the City of Des Moines and surrounding communities. In response to current and future demands, DMWW is in need of a thorough understanding of local groundwater resources, specifically the Des Moines River alluvial aquifer. The Des Moines River alluvial aquifer is hydraulically connected to the Des Moines River and consists of alluvial deposits and glacial outwash sands and gravels. To ensure a sustainable groundwater supply, additional information to better understand and manage groundwater availability within the Des Moines River alluvial aquifer would be beneficial. Beginning in 2018, DMWW partnered with the U.S. Geological Survey to construct a groundwater-flow model to increase understanding of the hydrologic system in the Des Moines area. The model hydrogeologic framework will be enhanced by using multiple geophysical methods of data collection in the Des Moines River, Beaver Creek, and the Des Moines River alluvial aquifer that could provide a better understanding of the geology in the model area.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20233006","usgsCitation":"Thomas, J.C., Spring, M.A., Gruhn, L.R., and Bristow, E.L., 2023, Application of geophysical methods to enhance aquifer characterization and groundwater-flow model development, Des Moines River alluvial aquifer, Des Moines, Iowa, 2022: U.S. Geological Survey Fact Sheet 2023–3006, 4 p., https://doi.org/10.3133/fs20233006.","productDescription":"Report: 4 p.; 2 Data Releases; Dataset","numberOfPages":"4","onlineOnly":"Y","ipdsId":"IP-136349","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":414104,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2023/3006/fs20233006.pdf","text":"Report","size":"2.95 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2023–3006"},{"id":414105,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2023/3006/fs20233006.XML","description":"FS 2023–3006"},{"id":414103,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2023/3006/coverthb2.jpg"},{"id":414112,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://www.usgs.gov/national-hydrography/access-national-hydrography-products","text":"USGS dataset","linkHelpText":"—National Hydrography Dataset— USGS National Hydrography Dataset Best Resolution for Hydrologic Unit 4 – 2001"},{"id":414109,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9B9AVKJ","text":"USGS data release","linkHelpText":"Geophysical data collected in the Des Moines River, Beaver Creek, and the Des Moines River floodplain, Des Moines, Iowa, 2018"},{"id":414110,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9F3CKLC","text":"USGS data release","linkHelpText":"MODFLOW-NWT model used to simulate groundwater levels in the Des Moines River alluvial aquifer near Des Moines, Iowa"},{"id":499566,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114475.htm","linkFileType":{"id":5,"text":"html"}},{"id":414138,"rank":8,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/fs20233006/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":414113,"rank":7,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2023/3006/images"}],"country":"United States","state":"Iowa","city":"Des Moines","otherGeospatial":"Des Moines River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -93.69895287733283,\n 41.66093681949087\n ],\n [\n -93.69895287733283,\n 41.52388190639587\n ],\n [\n -93.51363729010005,\n 41.52388190639587\n ],\n [\n -93.51363729010005,\n 41.66093681949087\n ],\n [\n -93.69895287733283,\n 41.66093681949087\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

Director, Central Midwest Water Science Center
U.S. Geological Survey
405 North Goodwin
Urbana, IL 61801

Contact Pubs Warehouse

","tableOfContents":"","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2023-03-14","noUsgsAuthors":false,"publicationDate":"2023-03-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Thomas, Judith C. 0000-0001-7883-1419 juthomas@usgs.gov","orcid":"https://orcid.org/0000-0001-7883-1419","contributorId":1468,"corporation":false,"usgs":true,"family":"Thomas","given":"Judith","email":"juthomas@usgs.gov","middleInitial":"C.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866417,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Spring, Morgan A. 0000-0002-8781-604X mspring@usgs.gov","orcid":"https://orcid.org/0000-0002-8781-604X","contributorId":303050,"corporation":false,"usgs":true,"family":"Spring","given":"Morgan","email":"mspring@usgs.gov","middleInitial":"A.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866418,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gruhn, Lance R. 0000-0002-7120-3003 lgruhn@usgs.gov","orcid":"https://orcid.org/0000-0002-7120-3003","contributorId":219710,"corporation":false,"usgs":true,"family":"Gruhn","given":"Lance","email":"lgruhn@usgs.gov","middleInitial":"R.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866419,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bristow, Emilia L. 0000-0002-7939-166X ebristow@usgs.gov","orcid":"https://orcid.org/0000-0002-7939-166X","contributorId":214538,"corporation":false,"usgs":true,"family":"Bristow","given":"Emilia L.","email":"ebristow@usgs.gov","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866420,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70241433,"text":"70241433 - 2023 - Exploratory analysis of machine learning techniques in the Nevada geothermal play fairway analysis","interactions":[],"lastModifiedDate":"2023-03-17T12:05:34.434371","indexId":"70241433","displayToPublicDate":"2023-03-14T07:01:19","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1828,"text":"Geothermics","active":true,"publicationSubtype":{"id":10}},"title":"Exploratory analysis of machine learning techniques in the Nevada geothermal play fairway analysis","docAbstract":"

Play fairway analysis (PFA) is commonly used to generate geothermal potential maps and guide exploration studies, with a particular focus on locating and characterizing blind geothermal systems. This study evaluates the application of machine learning techniques to PFA in the Great Basin region of Nevada. Following the evaluation of various techniques, we identified two approaches to PFA that produced promising results, 1) supervised Bayesian probabilistic neural networks to generate geothermal potential maps with confidence intervals, and 2) unsupervised principal component analysis paired with k-means clustering to generate both cluster maps to help identify spatial patterns, as well as new combined feature inputs. We applied these techniques to perform a comparative analysis between two principal sets of geological and geophysical features related to permeability and heat and a set of positive (known geothermal resources) and negative training sites (known drill sites with unsuitable geothermal conditions). We found that these methods constrain previously unrecognized feature controls on geothermal favorability, many of which are spatially organized within the extent of cluster groups and the major structural-hydrologic domains of the study area. Furthermore, we utilized exploratory unsupervised modeling to highlight spatial relationships between input data and predictive output results of our supervised modeling. Finally, we demonstrate how our models compare to the previous Nevada PFA and how the rapid insights these machine learning techniques offer may support future assessments of both known and undiscovered blind geothermal systems in the Great Basin region of Nevada and beyond.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.geothermics.2023.102693","usgsCitation":"Smith, C.M., Faulds, J., Brown, S.C., Coolbaugh, M., DeAngelo, J., Glen, J.M., Burns, E.R., Siler, D.L., Treitel, S., Mlawsky, E., Fehler, M., Gu, C., and Ayling, B.F., 2023, Exploratory analysis of machine learning techniques in the Nevada geothermal play fairway analysis: Geothermics, v. 111, 102693, 21 p., https://doi.org/10.1016/j.geothermics.2023.102693.","productDescription":"102693, 21 p.","ipdsId":"IP-145803","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":444214,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.osti.gov/biblio/1999607","text":"Publisher Index Page"},{"id":414334,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -120.08429216037908,\n 42.0233321964142\n ],\n [\n -120.08429216037908,\n 38.470780571367555\n ],\n [\n -114.02241339577863,\n 38.470780571367555\n ],\n [\n -114.02241339577863,\n 42.0233321964142\n ],\n [\n -120.08429216037908,\n 42.0233321964142\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"111","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Smith, Connor M.","contributorId":237894,"corporation":false,"usgs":false,"family":"Smith","given":"Connor","email":"","middleInitial":"M.","affiliations":[{"id":6689,"text":"Nevada Bureau of Mines and Geology","active":true,"usgs":false}],"preferred":false,"id":866828,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Faulds, James E.","contributorId":252834,"corporation":false,"usgs":false,"family":"Faulds","given":"James 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Chen","contributorId":237896,"corporation":false,"usgs":false,"family":"Gu","given":"Chen","email":"","affiliations":[{"id":12444,"text":"Massachusetts Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":866839,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Ayling, Bridget F.","contributorId":237899,"corporation":false,"usgs":false,"family":"Ayling","given":"Bridget","email":"","middleInitial":"F.","affiliations":[{"id":6689,"text":"Nevada Bureau of Mines and Geology","active":true,"usgs":false}],"preferred":false,"id":866840,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70241179,"text":"70241179 - 2023 - A call for strategic water-quality monitoring to advance assessment and prediction of wildfire impacts on water supplies","interactions":[],"lastModifiedDate":"2023-03-16T15:08:56.24279","indexId":"70241179","displayToPublicDate":"2023-03-13T06:50:17","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7170,"text":"Frontiers in Water","active":true,"publicationSubtype":{"id":10}},"title":"A call for strategic water-quality monitoring to advance assessment and prediction of wildfire impacts on water supplies","docAbstract":"

Wildfires pose a risk to water supplies in the western U.S. and many other parts of the world, due to the potential for degradation of water quality. However, a lack of adequate data hinders prediction and assessment of post-wildfire impacts and recovery. The dearth of such data is related to lack of funding for monitoring extreme events and the challenge of measuring the outsized hydrologic and erosive response after wildfire. Assessment and prediction of post-wildfire surface water quality would be strengthened by the strategic monitoring of key parameters, and the selection of sampling locations based on the following criteria: (1) streamgage with pre-wildfire data; (2) ability to install equipment that can measure water quality at high temporal resolution, with a focus on storm sampling; (3) minimum of 10% drainage area burned at moderate to high severity; (4) lack of major water management; (5) high-frequency precipitation; and (6) availability of pre-wildfire water-quality data and (or) water-quality data from a comparable unburned basin. Water-quality data focused on parameters that are critical to human and (or) ecosystem health, relevant to water-treatment processes and drinking-water quality, and (or) inform the role of precipitation and discharge on flow paths and water quality are most useful. We discuss strategic post-wildfire water-quality monitoring and identify opportunities for advancing assessment and prediction. Improved estimates of the magnitude, timing, and duration of post-wildfire effects on water quality would aid the water resources community prepare for and mitigate against impacts to water supplies.

","language":"English","publisher":"Frontiers Media","doi":"10.3389/frwa.2023.1144225","usgsCitation":"Murphy, S.F., Alpers, C.N., Anderson, C.W., Banta, J.R., Blake, J., Carpenter, K.D., Clark, G.D., Clow, D.W., Hempel, L.A., Martin, D., Meador, M.R., Mendez, G., Mueller-Solger, A., Stewart, M.A., Payne, S.E., Peterman-Phipps, C.L., and Ebel, B., 2023, A call for strategic water-quality monitoring to advance assessment and prediction of wildfire impacts on water supplies: Frontiers in Water, v. 5, 1144225, 9 p., https://doi.org/10.3389/frwa.2023.1144225.","productDescription":"1144225, 9 p.","ipdsId":"IP-147614","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":444230,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/frwa.2023.1144225","text":"Publisher Index Page"},{"id":414084,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5","noUsgsAuthors":false,"publicationDate":"2023-03-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Murphy, Sheila F. 0000-0002-5481-3635 sfmurphy@usgs.gov","orcid":"https://orcid.org/0000-0002-5481-3635","contributorId":1854,"corporation":false,"usgs":true,"family":"Murphy","given":"Sheila","email":"sfmurphy@usgs.gov","middleInitial":"F.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":866351,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Alpers, Charles N. 0000-0001-6945-7365 cnalpers@usgs.gov","orcid":"https://orcid.org/0000-0001-6945-7365","contributorId":411,"corporation":false,"usgs":true,"family":"Alpers","given":"Charles","email":"cnalpers@usgs.gov","middleInitial":"N.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866352,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anderson, Chauncey W. 0000-0002-1016-3781 chauncey@usgs.gov","orcid":"https://orcid.org/0000-0002-1016-3781","contributorId":140160,"corporation":false,"usgs":true,"family":"Anderson","given":"Chauncey","email":"chauncey@usgs.gov","middleInitial":"W.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866353,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Banta, John R. 0000-0002-2226-7270","orcid":"https://orcid.org/0000-0002-2226-7270","contributorId":222710,"corporation":false,"usgs":true,"family":"Banta","given":"John","email":"","middleInitial":"R.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866354,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Blake, Johanna 0000-0003-4667-0096","orcid":"https://orcid.org/0000-0003-4667-0096","contributorId":217272,"corporation":false,"usgs":true,"family":"Blake","given":"Johanna","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866355,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Carpenter, Kurt D. 0000-0002-6231-8335 kdcar@usgs.gov","orcid":"https://orcid.org/0000-0002-6231-8335","contributorId":127442,"corporation":false,"usgs":true,"family":"Carpenter","given":"Kurt","email":"kdcar@usgs.gov","middleInitial":"D.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866356,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Clark, Gregory D. 0000-0003-0066-8193 gmclark@usgs.gov","orcid":"https://orcid.org/0000-0003-0066-8193","contributorId":224364,"corporation":false,"usgs":true,"family":"Clark","given":"Gregory","email":"gmclark@usgs.gov","middleInitial":"D.","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866357,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Clow, David W. 0000-0001-6183-4824 dwclow@usgs.gov","orcid":"https://orcid.org/0000-0001-6183-4824","contributorId":1671,"corporation":false,"usgs":true,"family":"Clow","given":"David","email":"dwclow@usgs.gov","middleInitial":"W.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866358,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hempel, Laura A. 0000-0001-5020-6056","orcid":"https://orcid.org/0000-0001-5020-6056","contributorId":224286,"corporation":false,"usgs":true,"family":"Hempel","given":"Laura","email":"","middleInitial":"A.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866359,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Martin, Deborah A. 0000-0001-8237-0838","orcid":"https://orcid.org/0000-0001-8237-0838","contributorId":244709,"corporation":false,"usgs":true,"family":"Martin","given":"Deborah A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":866360,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Meador, Michael R. 0000-0001-5956-3340 mrmeador@usgs.gov","orcid":"https://orcid.org/0000-0001-5956-3340","contributorId":219878,"corporation":false,"usgs":true,"family":"Meador","given":"Michael","email":"mrmeador@usgs.gov","middleInitial":"R.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":866361,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Mendez, Gregory 0000-0002-9955-3726 gomendez@usgs.gov","orcid":"https://orcid.org/0000-0002-9955-3726","contributorId":139098,"corporation":false,"usgs":true,"family":"Mendez","given":"Gregory","email":"gomendez@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866362,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Mueller-Solger, Anke 0000-0002-2469-4284 amueller-solger@usgs.gov","orcid":"https://orcid.org/0000-0002-2469-4284","contributorId":178275,"corporation":false,"usgs":true,"family":"Mueller-Solger","given":"Anke","email":"amueller-solger@usgs.gov","affiliations":[],"preferred":true,"id":866363,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Stewart, Marc A. 0000-0003-1140-6316 mastewar@usgs.gov","orcid":"https://orcid.org/0000-0003-1140-6316","contributorId":2277,"corporation":false,"usgs":true,"family":"Stewart","given":"Marc","email":"mastewar@usgs.gov","middleInitial":"A.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866364,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Payne, Sean E. 0000-0003-1836-1886 spayne@usgs.gov","orcid":"https://orcid.org/0000-0003-1836-1886","contributorId":292581,"corporation":false,"usgs":true,"family":"Payne","given":"Sean","email":"spayne@usgs.gov","middleInitial":"E.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866365,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Peterman-Phipps, Cara L. 0000-0003-1822-2552","orcid":"https://orcid.org/0000-0003-1822-2552","contributorId":259166,"corporation":false,"usgs":true,"family":"Peterman-Phipps","given":"Cara","email":"","middleInitial":"L.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":866366,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Ebel, Brian A. 0000-0002-5413-3963","orcid":"https://orcid.org/0000-0002-5413-3963","contributorId":211845,"corporation":false,"usgs":true,"family":"Ebel","given":"Brian A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":866367,"contributorType":{"id":1,"text":"Authors"},"rank":17}]}} ,{"id":70241154,"text":"70241154 - 2023 - Adjusting design floods for urbanization across groundwater-dominated watersheds of Long Island, NY","interactions":[],"lastModifiedDate":"2023-03-14T11:38:49.467965","indexId":"70241154","displayToPublicDate":"2023-03-12T06:36:13","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Adjusting design floods for urbanization across groundwater-dominated watersheds of Long Island, NY","docAbstract":"

The magnitude and variability of floods have increased for many nontidal streams on Long Island (LI), NY since the mid-20th century. One of the most densely populated regions of the United States, LI has experienced amplified floods in step with increases in impervious land cover, storm, and sanitary sewers that have accompanied urban development. To better understand the drivers of observed flood trends and effects of urbanization, a nonstationary flood frequency analysis is conducted, using historical annual peak flow records from 17 gaged watersheds on LI using conditional moments based on physical covariates from a two-stage sequential robust linear regression procedure. Regression results indicate that urban development and precipitation are significant co-predictors of peak flows for LI watersheds that have undergone rapid development during the available peak flow record. In watersheds with less intense urbanization or that were fully developed before the peak flow record began, precipitation alone was a significant explanatory variable. Long-term baseflow patterns identified using a nonparametric smoother explained some patterns of decreasing peak flows and heteroskedasticity in the peak flow records. Fitting a log-Pearson III distribution with these conditional moments, floods corresponding to a 20% annual exceedance probability (AEP) are up to 80% higher under a nonstationary framework compared with stationary under current watershed conditions, and differ significantly (95% confidence) from stationary estimates for 6 out of 17 watersheds. Larger floods corresponding to 1% AEPs do not differ significantly between nonstationary and stationary estimates at a 95% confidence level. Nonmonotonic trends observed in two watersheds indicate that recent stormwater management practices, such as rerouting stormwater outfalls away from the channel, substantially reduce flood frequency. Reduced nonstationary flood quantile estimates at these two watersheds are 20 to 40% lower than stationary estimates when accounting for changing watershed conditions over time. Across LI, stormwater management and water-table fluctuations have increased peak flow variability, characteristic of a late phase urban adjustment period on LI. Results of this study demonstrate that a nonstationary framework is a necessary step forward toward a regional flood-frequency analysis for LI. This nonstationary framework will allow flood managers to update flood discharge estimates to current conditions that reflect altered relationships between urban cover and climate for more targeted planning of flood control, transportation infrastructure, and management of floodplain ecosystems.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2023.129194","usgsCitation":"Glas, R.L., Hecht, J.S., Simonson, A.E., Gazoorian, C.L., and Schubert, C., 2023, Adjusting design floods for urbanization across groundwater-dominated watersheds of Long Island, NY: Journal of Hydrology, v. 618, 129194, 18 p., https://doi.org/10.1016/j.jhydrol.2023.129194.","productDescription":"129194, 18 p.","ipdsId":"IP-141042","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":444235,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jhydrol.2023.129194","text":"Publisher Index Page"},{"id":414082,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Long Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -74.05858047106763,\n 40.53935289454654\n ],\n [\n -73.5589147395655,\n 40.53100675208171\n ],\n [\n -72.9988498537052,\n 40.622757129246565\n ],\n [\n -72.21915167927318,\n 40.85158231156032\n ],\n [\n -71.88970174641427,\n 41.046499814971185\n ],\n [\n -71.84577508869982,\n 41.12099665045869\n ],\n [\n -72.05442671284345,\n 41.191277217075765\n ],\n [\n -72.26307833698762,\n 41.21193363017932\n ],\n [\n -72.65292742420364,\n 41.129268863301746\n ],\n [\n -73.23495563892061,\n 41.067201851192294\n ],\n [\n -73.70167637713746,\n 40.980209521445886\n ],\n [\n -73.99269048449594,\n 40.83081255180315\n ],\n [\n -74.11348879321068,\n 40.63525879433698\n ],\n [\n -74.05858047106763,\n 40.53935289454654\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"618","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Glas, Robin L. 0000-0002-7394-1667","orcid":"https://orcid.org/0000-0002-7394-1667","contributorId":300625,"corporation":false,"usgs":true,"family":"Glas","given":"Robin","email":"","middleInitial":"L.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866289,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hecht, Jory Seth 0000-0002-9485-3332","orcid":"https://orcid.org/0000-0002-9485-3332","contributorId":257771,"corporation":false,"usgs":true,"family":"Hecht","given":"Jory","email":"","middleInitial":"Seth","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":866290,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Simonson, Amy E. 0000-0001-8468-5382","orcid":"https://orcid.org/0000-0001-8468-5382","contributorId":217671,"corporation":false,"usgs":true,"family":"Simonson","given":"Amy","email":"","middleInitial":"E.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866291,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gazoorian, Christopher L. 0000-0002-5408-6212 cgazoori@usgs.gov","orcid":"https://orcid.org/0000-0002-5408-6212","contributorId":2929,"corporation":false,"usgs":true,"family":"Gazoorian","given":"Christopher","email":"cgazoori@usgs.gov","middleInitial":"L.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866292,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schubert, Christopher 0000-0002-5137-1229 schubert@usgs.gov","orcid":"https://orcid.org/0000-0002-5137-1229","contributorId":138826,"corporation":false,"usgs":true,"family":"Schubert","given":"Christopher","email":"schubert@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":false,"id":866293,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70242934,"text":"70242934 - 2023 - Investigating hydrologic alteration in the Pearl and Pascagoula River basins using rule-based model trees","interactions":[],"lastModifiedDate":"2023-04-24T12:07:47.445858","indexId":"70242934","displayToPublicDate":"2023-03-09T07:04:19","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":14255,"text":"Environmental Software and Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Investigating hydrologic alteration in the Pearl and Pascagoula River basins using rule-based model trees","docAbstract":"

Anthropogenic hydrologic alteration threatens the health of riverine ecosystems. Machine learning algorithms that employ the use of model trees to predict hydrologic alteration are underrepresented in related literature. This study assesses hydrologic alteration in the Pearl and Pascagoula River basins using modeled daily streamflow. Hydrologic alteration was determined by hypothesis testing and the computation of the net change across 60 years. Cubist models were developed for both basins to predict hydrologic alteration and to identify important basin characteristics. Results from net change and the hypothesis test indicated the basins were essentially identical with respect to the amount of hydrologic alteration. Cubist models for the basins successfully made accurate predictions of hydrologic alteration and demonstrated that the importance of basin geomorphology and land cover on alteration differed in both basins. The results of the study demonstrate the feasibility of model trees in assessing hydrologic alteration.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2023.105667","usgsCitation":"Roland, V.L., Crowley-Ornelas, E., and Rodgers, K., 2023, Investigating hydrologic alteration in the Pearl and Pascagoula River basins using rule-based model trees: Environmental Software and Modelling, v. 163, 105667, 10 p., https://doi.org/10.1016/j.envsoft.2023.105667.","productDescription":"105667, 10 p.","ipdsId":"IP-116276","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":444260,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envsoft.2023.105667","text":"Publisher Index Page"},{"id":435420,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9PUMMTV","text":"USGS data release","linkHelpText":"Supporting data and model outputs for hydrologic alteration modeling in the Pearl and Pascagoula river basins"},{"id":416172,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Mississippi","otherGeospatial":"Pascagoula River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -89.80875982614708,\n 32.61000614560781\n ],\n [\n -89.80875982614708,\n 30.154023040111667\n ],\n [\n -88.27367909529212,\n 30.154023040111667\n ],\n [\n -88.27367909529212,\n 32.61000614560781\n ],\n [\n -89.80875982614708,\n 32.61000614560781\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"163","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Roland, Victor L. II 0000-0002-6260-9351 vroland@usgs.gov","orcid":"https://orcid.org/0000-0002-6260-9351","contributorId":212248,"corporation":false,"usgs":true,"family":"Roland","given":"Victor","suffix":"II","email":"vroland@usgs.gov","middleInitial":"L.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":870238,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Crowley-Ornelas, Elena 0000-0002-1823-8485","orcid":"https://orcid.org/0000-0002-1823-8485","contributorId":211970,"corporation":false,"usgs":true,"family":"Crowley-Ornelas","given":"Elena","email":"","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":870239,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rodgers, Kirk D. 0000-0003-4322-2781","orcid":"https://orcid.org/0000-0003-4322-2781","contributorId":203438,"corporation":false,"usgs":true,"family":"Rodgers","given":"Kirk D.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":870334,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70240876,"text":"sir20235016 - 2023 - 2022 drought in New England","interactions":[],"lastModifiedDate":"2026-03-02T22:03:43.63376","indexId":"sir20235016","displayToPublicDate":"2023-03-08T15:50:00","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-5016","displayTitle":"2022 Drought in New England","title":"2022 drought in New England","docAbstract":"

Introduction 

During April through September 2022, much of New England experienced a short but extreme hydrologic drought that was similar to the drought of 2020. By August 2022, Providence, Rhode Island, was declared a Federal disaster area, and New London and Windham counties in Connecticut were declared natural disaster areas. Mandatory water use restrictions were put in place in communities in Connecticut, Massachusetts, New Hampshire, and Rhode Island (Mecray and Borisoff, 2022). Precipitation in many areas of New England fell below normal levels in November 2021 and continued to decline until September 2022, contributing to low streamflows and groundwater levels in the region. U.S. Geological Survey (USGS) streamflow and groundwater conditions from April to September 2022 were used to characterize the hydrologic component of this short-duration drought. Several record low streamflows and groundwater levels were observed across New England, even falling below 2020 levels in parts of southern New England. The severity of this drought varied across New England, and regional and statewide perspectives are presented in this report.

Highlights

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

Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532

","tableOfContents":"","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"publishedDate":"2023-03-08","noUsgsAuthors":false,"publicationDate":"2023-03-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Crozier, Dee-Ann E. 0000-0003-0526-3013","orcid":"https://orcid.org/0000-0003-0526-3013","contributorId":245837,"corporation":false,"usgs":true,"family":"Crozier","given":"Dee-Ann","email":"","middleInitial":"E.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":865132,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lenoir, Jonathan","contributorId":167876,"corporation":false,"usgs":false,"family":"Lenoir","given":"Jonathan","email":"","affiliations":[{"id":24849,"text":"Université de Picardie Jules Verne","active":true,"usgs":false}],"preferred":false,"id":865133,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lombard, Pamela J. 0000-0002-0983-1906","orcid":"https://orcid.org/0000-0002-0983-1906","contributorId":205225,"corporation":false,"usgs":true,"family":"Lombard","given":"Pamela","email":"","middleInitial":"J.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":865134,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70240929,"text":"sir20235002 - 2023 - Hydrologic effects of possible changes in water-supply withdrawals from, and effluent recharge to, the Kirkwood-Cohansey aquifer system, Winslow Township, Camden County, New Jersey","interactions":[],"lastModifiedDate":"2026-02-24T18:09:00.975169","indexId":"sir20235002","displayToPublicDate":"2023-03-07T14:25:00","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-5002","displayTitle":"Hydrologic Effects of Possible Changes in Water-Supply Withdrawals from, and Effluent Recharge to, the Kirkwood-Cohansey aquifer system, Winslow Township, Camden County, New Jersey","title":"Hydrologic effects of possible changes in water-supply withdrawals from, and effluent recharge to, the Kirkwood-Cohansey aquifer system, Winslow Township, Camden County, New Jersey","docAbstract":"

Winslow Township and the Camden County Municipal Utility Authority (CCMUA) developed a plan to shut down the Winslow sewage-treatment facility and associated effluent infiltration facility and transfer the effluent to the CCMUA sewage-treatment facility on the Delaware River in Camden, New Jersey. Winslow Township reduced groundwater withdrawals from the Kirkwood-Cohansey aquifer system to offset groundwater recharge lost with the cessation of effluent infiltration. The U.S. Geological Survey, in cooperation with Winslow Township and the CCMUA, collected data to evaluate conditions prior to cessation of effluent infiltration and installed two continuous-record streamflow-gaging stations. Streamflow measurements also were made at two low-flow partial-record sites, and groundwater levels were measured in 17 wells at high and low water-level periods (May and September 2010). A groundwater-flow model provides estimated changes in base flow of the Great Egg Harbor River under several groundwater-withdrawal and effluent infiltration scenarios.

Water levels were measured in an observation well 480 feet (ft) from the infiltration lagoons during 1971–2010. A downward trend in water levels in the well prior to 1985 is attributed in part to increased impervious surfaces and groundwater withdrawals associated with development in the area that began in the early 1970s. From late 1985 to 2010, there was an upward trend in water levels in the well that is attributed to the construction of nearby effluent infiltration lagoons in 1985 and the increasing rate of effluent infiltration during the period. Recent and historical measurements made at the four surface-water sites were correlated with same-day discharges measured at three nearby index stations to estimate continuous low-flow record at the sites. Effects on base flow caused by reductions in groundwater withdrawals or the cessation of effluent infiltration in Winslow Township could not be ascertained from the available data with the statistical and analysis methods used.

Groundwater discharge to streams (base flow) was simulated with a groundwater-flow model of the Great Egg Harbor and Mullica River Basins. Simulated monthly base flows using 2008–10 withdrawal rates and effluent recharge (Scenario 1) are generally about 1.5 million gallons per day (Mgal/d) greater than simulated base flows using 2003–07 withdrawal rates (Baseline Scenario) because of the 1.57 Mgal/d reduction in average withdrawals by Winslow Township from the Kirkwood-Cohansey aquifer system from 2003–07 to 2008–10. Simulated monthly base flows using 2008–10 withdrawals but without effluent infiltration (Scenario 2) are very similar to, but typically slightly lower than, Baseline Scenario base flows.

Three hypothetical future distributions of groundwater withdrawals from existing Winslow Township wells are simulated, each without effluent infiltration and using the same groundwater withdrawal rate as Scenario 2, but with different hypothetical distributions of withdrawals among existing Winslow Township wells. The Scenario 3 and 4 base flows are greater than the Baseline Scenario base flows in all months, and the Scenario 5 base flows are less than the Baseline Scenario base flows in all months. The simulation results indicate that a reduction in average withdrawals from the Kirkwood-Cohansey aquifer system by 1.57 Mgal/d offsets the reduction of effluent infiltration by about the same rate, resulting in nearly unchanged base flows in the Great Egg Harbor River near Blue Anchor (01410820).

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235002","collaboration":"Prepared in cooperation with the Township of Winslow and the Camden County Municipal Utilities Authority","usgsCitation":"Carleton, G.B., and Pope, D.A., 2023, Hydrologic effects of possible changes in water-supply withdrawals from, and effluent recharge to, the Kirkwood-Cohansey aquifer system, Winslow Township, Camden County, New Jersey: U.S. Geological Survey Scientific Investigations Report 2023–5002, 16 p., https://doi.org/10.3133/sir20235002.","productDescription":"Report: vii, 16 p.; Data Release","numberOfPages":"16","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-057410","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":413542,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7154G0Z","text":"USGS data release","linkHelpText":"MODFLOW-2000 model used to evaluate the effects of possible changes in water-supply withdrawals from, and effluent recharge to, the Kirkwood-Cohansey aquifer system, Winslow Township, Camden County, New Jersey"},{"id":500487,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114441.htm","linkFileType":{"id":5,"text":"html"}},{"id":413541,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5002/images/"},{"id":413538,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5002/sir20235002.pdf","text":"Report","size":"1.58 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5002"},{"id":413537,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5002/coverthb.jpg"},{"id":413539,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235002/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2023-5002"},{"id":413540,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5002/sir20235002.XML"}],"country":"United States","state":"New Jersey","county":"Camden County","otherGeospatial":"Winslow Township","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -75,\n 39.833\n ],\n [\n -75,\n 39.5833\n ],\n [\n -74.833,\n 39.5833\n ],\n [\n -74.833,\n 39.833\n ],\n [\n -75,\n 39.833\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

Director, New Jersey Water Science Center
U.S. Geological Survey
3450 Princeton Pike, Suite 110
Lawrenceville, NJ, 08648

Contact Pubs Warehouse

","tableOfContents":"","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"publishedDate":"2023-03-07","noUsgsAuthors":false,"publicationDate":"2023-03-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Carleton, Glen B. 0000-0002-7666-4407","orcid":"https://orcid.org/0000-0002-7666-4407","contributorId":208415,"corporation":false,"usgs":true,"family":"Carleton","given":"Glen B.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":865337,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pope, Daryll A. 0000-0002-6777-8285 dpope@usgs.gov","orcid":"https://orcid.org/0000-0002-6777-8285","contributorId":208416,"corporation":false,"usgs":true,"family":"Pope","given":"Daryll","email":"dpope@usgs.gov","middleInitial":"A.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":865338,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70243327,"text":"70243327 - 2023 - Hydrologic modeling and river corridor applications of HY_Features concepts","interactions":[],"lastModifiedDate":"2023-05-09T13:35:13.643633","indexId":"70243327","displayToPublicDate":"2023-03-06T08:26:24","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"seriesTitle":{"id":14271,"text":"OGC Public Engineering Report","active":true,"publicationSubtype":{"id":3}},"title":"Hydrologic modeling and river corridor applications of HY_Features concepts","docAbstract":"

The WaterML2: Part 3 - Surface Hydrology Features (HY_Features) Conceptual Model was published by OGC in 2018. This report documents the use of HY_Features concepts in support of two key tasks: (1) local to continental hydrologic modeling; and (2) referencing river corridor data to hydrographic networks. The presented use cases are applicable in hydroscience research and assessments, water resources engineering practices, and drought and flood responses.

Before the HY_Features conceptual model there was no internationally recognized standard for the design of software and data for the hydroscience and engineering community. This report presents progress towards a logical data model that interprets the abstract HY_Features concepts for use in geospatial workflows, modeling applications, and web data systems that integrate hydrologic data.

The use cases addressed include: (1) hydrologic model control volume definition; (2) hydrologic network connectivity; (3) characterization of catchments with landscape and atmospheric data; (4) river corridor characterization; (5) hydrologic location; and (6) flow network location. Each use case is described briefly along with an analysis of the information requirements. This report presents a summary of the logical model designed to satisfy the needs of these use cases and a summary of updates and changes proposed for HY_Features.

Changes for consideration by the HY_Features Standards Working Group include the following.

  1. Provide more clarity on the inherited properties and associations of features that \"realize\" the catchment and nexus concepts from HY_Features.

  2. Add nexus realization feature types to represent the outlet of catchments that are \"frontal\" (terminate to the ocean or a large waterbody) or \"inland sinks.\"

  3. Add a \"HY_Flowline\" feature as a superclass of HY_Flowpath providing linear referencing on waterbodies that are not catchment realizations.

  4. Add an association or interface to support connection between surface catchments and hydrogeologic units.

","language":"English","publisher":"Open Geospatial Consortium","usgsCitation":"Blodgett, D.L., Johnson, J., Bock, A.R., LeRoy, J.Z., and Wernimont, M.R., 2023, Hydrologic modeling and river corridor applications of HY_Features concepts: OGC Public Engineering Report, HTML Document.","productDescription":"HTML Document","ipdsId":"IP-145176","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":416858,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":416834,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.opengis.net/doc/PER/Hydrofabric-er"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Blodgett, David L. 0000-0001-9489-1710 dblodgett@usgs.gov","orcid":"https://orcid.org/0000-0001-9489-1710","contributorId":3868,"corporation":false,"usgs":true,"family":"Blodgett","given":"David","email":"dblodgett@usgs.gov","middleInitial":"L.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5054,"text":"Office of Water Information","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":872050,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, J. Michael","contributorId":304963,"corporation":false,"usgs":false,"family":"Johnson","given":"J. Michael","affiliations":[{"id":66193,"text":"NOAA-NWS-OWP","active":true,"usgs":false}],"preferred":false,"id":872051,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bock, Andrew R. 0000-0001-7222-6613 abock@usgs.gov","orcid":"https://orcid.org/0000-0001-7222-6613","contributorId":4580,"corporation":false,"usgs":true,"family":"Bock","given":"Andrew","email":"abock@usgs.gov","middleInitial":"R.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":872053,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"LeRoy, Jessica Z. 0000-0003-4035-6872 jzinger@usgs.gov","orcid":"https://orcid.org/0000-0003-4035-6872","contributorId":174534,"corporation":false,"usgs":true,"family":"LeRoy","given":"Jessica","email":"jzinger@usgs.gov","middleInitial":"Z.","affiliations":[{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true},{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":872052,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wernimont, Martin R 0000-0002-2127-8568 mwernimont@usgs.gov","orcid":"https://orcid.org/0000-0002-2127-8568","contributorId":5662,"corporation":false,"usgs":true,"family":"Wernimont","given":"Martin","email":"mwernimont@usgs.gov","middleInitial":"R","affiliations":[{"id":160,"text":"Center for Integrated Data Analytics","active":false,"usgs":true},{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"preferred":true,"id":872054,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70241187,"text":"70241187 - 2023 - A river basin spatial model to quantitively advance understanding of riverine tree response dynamics to water availability and hydrological management","interactions":[],"lastModifiedDate":"2023-03-14T12:19:36.295822","indexId":"70241187","displayToPublicDate":"2023-03-03T07:18:02","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":13457,"text":"The Journal of Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"A river basin spatial model to quantitively advance understanding of riverine tree response dynamics to water availability and hydrological management","docAbstract":"

Ecological condition continues to decline in arid and semi-arid river basins globally due to hydrological over-abstraction combined with changing climatic conditions. Whilst provision of water for the environment has been a primary approach to alleviate ecological decline, how to accurately monitor changes in riverine trees at fine spatial and temporal scales, remains a substantial challenge. This is further complicated by constantly changing water availability across expansive river basins with varying climatic zones. Within, we combine rare, fine-scale, high frequency temporal in-situ field collected data with machine learning and remote sensing, to provide a robust model that enables broadscale monitoring of physiological tree water stress response to environmental changes via actual evapotranspiration (ET). Physiological variation of Eucalyptus camaldulensis (River Red Gum) and E. largiflorens (Black Box) trees across 10 study locations in the southern Murray-Darling Basin, Australia, was captured instantaneously using sap flow sensors, substantially reducing tree response lags encountered by monitoring visual canopy changes. Actual ET measurement of both species was used to bias correct a national spatial ET product where a Random Forest model was trained using continuous timeseries of in-situ data of up to four years. Precise monthly AMLETT (Australia-wide Machine Learning ET for Trees) ET outputs in 30 m pixel resolution from 2012 to 2021, were derived by incorporating additional remote sensing layers such as soil moisture, land surface temperature, radiation and EVI and NDVI in the Random Forest model. Landsat and Sentinal-2 correlation results between in-situ ET and AMLETT ET returned R2 of 0.94 (RMSE 6.63 mm period−1) and 0.92 (RMSE 6.89 mm period−1), respectively. In comparison, correlation between in-situ ET and a national ET product returned R2 of 0.44 (RMSE 34.08 mm period−1) highlighting the need for bias correction to generate accurate absolute ET values. The AMLETT method presented here, enhances environmental management in river basins worldwide. Such robust broadscale monitoring can inform water accounting and importantly, assist decisions on where to prioritize water for the environment to restore and protect key ecological assets and preserve floodplain and riparian ecological function.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.jenvman.2023.117393","usgsCitation":"Doody, T.M., Gao, S., Vervoot, W., Pritchard, J., Davies, M., Nolan, M., and Nagler, P.L., 2023, A river basin spatial model to quantitively advance understanding of riverine tree response dynamics to water availability and hydrological management: The Journal of Environmental Management, v. 332, 117393, 14 p., https://doi.org/10.1016/j.jenvman.2023.117393.","productDescription":"117393, 14 p.","ipdsId":"IP-144919","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":444303,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jenvman.2023.117393","text":"Publisher Index Page"},{"id":414089,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Australia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 140.07757319376452,\n -34.95139605233576\n ],\n [\n 144.51416562293036,\n -34.95139605233576\n ],\n [\n 144.51416562293036,\n -32.46697218892208\n ],\n [\n 140.07757319376452,\n -32.46697218892208\n ],\n [\n 140.07757319376452,\n -34.95139605233576\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"332","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Doody, Tanya M.","contributorId":138691,"corporation":false,"usgs":false,"family":"Doody","given":"Tanya","email":"","middleInitial":"M.","affiliations":[{"id":12494,"text":"CSIRO Land and Water, Australia","active":true,"usgs":false}],"preferred":false,"id":866383,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gao, Sicong","contributorId":303040,"corporation":false,"usgs":false,"family":"Gao","given":"Sicong","email":"","affiliations":[{"id":65623,"text":"CSIRO, Land and Water, Waite Campus, Adelaide, South Australia, Australia; University of Canberra, Canberra, Australian Capital Territory, Australia","active":true,"usgs":false}],"preferred":false,"id":866384,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vervoot, Willem","contributorId":303041,"corporation":false,"usgs":false,"family":"Vervoot","given":"Willem","email":"","affiliations":[{"id":65624,"text":"School of Life and Environmental Sciences, The University of Sydney, Sydney, Australia","active":true,"usgs":false}],"preferred":false,"id":866385,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pritchard, Jodie","contributorId":303042,"corporation":false,"usgs":false,"family":"Pritchard","given":"Jodie","email":"","affiliations":[{"id":65625,"text":"CSIRO, Land and Water, Waite Campus, Adelaide, South Australia, Australia","active":true,"usgs":false}],"preferred":false,"id":866386,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Davies, Michah","contributorId":303043,"corporation":false,"usgs":false,"family":"Davies","given":"Michah","email":"","affiliations":[{"id":65627,"text":"CSIRO, Land and Water, Canberra, Australian Capital Territory, Australia","active":true,"usgs":false}],"preferred":false,"id":866387,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nolan, Martin","contributorId":303044,"corporation":false,"usgs":false,"family":"Nolan","given":"Martin","email":"","affiliations":[{"id":65625,"text":"CSIRO, Land and Water, Waite Campus, Adelaide, South Australia, Australia","active":true,"usgs":false}],"preferred":false,"id":866388,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Nagler, Pamela L. 0000-0003-0674-103X pnagler@usgs.gov","orcid":"https://orcid.org/0000-0003-0674-103X","contributorId":1398,"corporation":false,"usgs":true,"family":"Nagler","given":"Pamela","email":"pnagler@usgs.gov","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":866389,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70244090,"text":"70244090 - 2023 - Unravelling the influence of landscape alteration from flow alteration on benthic macroinvertebrate assemblage response in the Delaware River Basin","interactions":[],"lastModifiedDate":"2023-06-01T14:08:40.055086","indexId":"70244090","displayToPublicDate":"2023-03-01T08:44:05","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1447,"text":"Ecohydrology","active":true,"publicationSubtype":{"id":10}},"title":"Unravelling the influence of landscape alteration from flow alteration on benthic macroinvertebrate assemblage response in the Delaware River Basin","docAbstract":"Quantifying the effects of streamflow alteration on assemblage response is central to understanding the role humans play in shaping aquatic environments. These changes represent a level of complexity that impedes developing quantitative links between flow and ecological response because stream hydrology is strongly intertwined with natural and anthropogenic factors. Better management outcomes require disentangling these linkages. Benthic macroinvertebrate data were combined with GIS-derived natural and anthropogenic basin characteristics to identify factors associated with changes in flow processes and assemblage characteristics. Models linking streamflow metrics and macroinvertebrate response at basin and subregion scales were developed using boosted regression tree (BRT) analysis. Basin-scale BRT analyses revealed that links between macroinvertebrate response and flow metrics were often obscured, whereas more homogeneous subregions were better able to discern relations with flow. Urban land cover was the primary factor accounting for changes in flow characteristics. Elevation, land cover, and high flow frequency were the principal variables driving changes in assemblage structure within subregions. Assemblage metrics and traits were equally useful for building response models and were affected similarly by streamflow alteration. Results indicate that response models should be developed based on upland and coastal subregions. However, when defining subregions, care should be taken to maintain data sufficiency. Developing practical flow-protection standards that support a balance between human water requirements and ecological integrity requires models that reduce uncertainty and identify management-relevant drivers. However, effective management often differs by location and models developed at the subregion level may be more applicable to management and stakeholder interests.","language":"English","publisher":"Wiley","doi":"10.1002/eco.2508","usgsCitation":"Kennen, J., and Cuffney, T.F., 2023, Unravelling the influence of landscape alteration from flow alteration on benthic macroinvertebrate assemblage response in the Delaware River Basin: Ecohydrology, v. 16, no. 2, e2508, 41 p., https://doi.org/10.1002/eco.2508.","productDescription":"e2508, 41 p.","ipdsId":"IP-128360","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":498861,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/eco.2508","text":"Publisher Index Page"},{"id":417646,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Delaware, New Jersey, New York, Pennsylvania","otherGeospatial":"Delaware River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -75.07997541667648,\n 38.70906787639316\n ],\n [\n -74.80531721355018,\n 39.00778043156808\n ],\n [\n -74.33839826823872,\n 40.4450386444411\n ],\n [\n -73.72865705730113,\n 40.994591290300974\n ],\n [\n -73.7835886979261,\n 42.478350475454334\n ],\n [\n -75.40956526042564,\n 42.295772510663625\n ],\n [\n -75.42055158855078,\n 41.8349594674406\n ],\n [\n -76.34340315105082,\n 40.43667721449637\n ],\n [\n -75.78859358073888,\n 39.713504216020766\n ],\n [\n -75.76662092448927,\n 39.578152174338356\n ],\n [\n -75.66225080730156,\n 39.41283383409595\n ],\n [\n -75.50294904948888,\n 39.22584914314203\n ],\n [\n -75.47548322917642,\n 39.042631522344635\n ],\n [\n -75.33266096355176,\n 38.846103881559685\n ],\n [\n -75.07997541667648,\n 38.70906787639316\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"16","issue":"2","noUsgsAuthors":false,"publicationDate":"2023-01-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Kennen, Jonathan G. 0000-0002-5426-4445 jgkennen@usgs.gov","orcid":"https://orcid.org/0000-0002-5426-4445","contributorId":574,"corporation":false,"usgs":true,"family":"Kennen","given":"Jonathan G.","email":"jgkennen@usgs.gov","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":874461,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cuffney, Thomas F. 0000-0003-1164-5560 tcuffney@usgs.gov","orcid":"https://orcid.org/0000-0003-1164-5560","contributorId":517,"corporation":false,"usgs":true,"family":"Cuffney","given":"Thomas","email":"tcuffney@usgs.gov","middleInitial":"F.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":874462,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ]}