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To assess the status and trends of conditions of surface waters throughout Mississippi, the U.S. Geological Survey, in cooperation with the Mississippi Department of Environmental Quality (MDEQ), summarized concentrations and estimated loads, yields, trends, and spatial and temporal patterns of total nitrogen (TN) and total phosphorus (TP) at 20 stream sites in MDEQ’s ambient water-quality monitoring network and 2 stream sites in the U.S. Geological Survey’s National Water-Quality Assessment Project’s monitoring network.

Comparison of streamflow at the time of water-quality sample collection to flow-duration curves for each site showed that samples were relatively evenly spread over a wide range of flows, indicating that load estimations were representative of a wide range of flows. Relation of streamflow to concentrations of TN and TP varied among sites and land use. Sites with high agriculture land use in the drainage basin tended to have a positive correlation between streamflow and concentration, suggesting influence of event-driven nonpoint-source runoff. Sites near urban (developed) areas tended to have a negative correlation between streamflow and concentration, suggesting chronic point-source influences during low-flow conditions. Sites with high forest land use and lower agriculture and urban (developed) land use showed little to no association between streamflow and concentration.

Seasonal distributions of concentrations of TN and TP also corresponded closely with variations in land use. Sites near urban (developed) land had the highest concentrations in late summer and fall, sites with a high percentage of agricultural land had the highest concentrations in the spring, and sites that were primarily forested or with little developed land did not exhibit substantial changes in concentration across seasons.

Eight sites had statistical likelihoods for upward trends of TN loads, and seven sites had statistical likelihoods for downward trends. Trends in TN loads at six sites were considered “about as likely as not,” meaning that a site has an equal chance of having an upward or downward trend. Trend results of mean annual flow-normalized loads of TP for the period of analysis (2008–18) showed that 16 sites had upward trends, 3 sites had downward trends, and 2 sites were considered “about as likely as not.”

Results from our study were compared to results from existing regional models to assess accuracy of predictions at a local scale. Comparisons of yields predicted from 2012 regional-scale SPAtially Referenced Regressions on Watershed attributes (SPARROW) to results from this study showed the 2012 SPARROW-predicted estimates varied in consistency with results from this study. The 2012 SPARROW-prediction model underestimated TN yields, more often and by a slightly larger degree, more than it overestimated TN yields. The 2012 SPARROW-predicted model tended to underestimate yields at study sites with higher yields. All four sites in the predominantly agricultural area of northwest Mississippi, locally known as the Mississippi Delta, were underestimated by 2012 SPARROW. For TP, yield comparisons at sites with lower yields were consistent, yields at sites with midrange yields tended to be overestimated by SPARROW, and yields at sites with high yields tended to be underestimated by SPARROW. TP yields at four sites in the Mississippi Delta were underestimated by the 2012 SPARROW-predicted model.

Results of select sites from our study were also compared to other published load estimates from an earlier time period to evaluate possible trends. Comparison of TN yields at four sites and TP yields at three sites from the study-derived estimates to estimates made from data spanning 1993–2004 showed decreasing TN yields at all four sites and decreasing TP yields at two of three sites, with increasing yields of TP at the Yazoo River lower site. Also, a third comparison of the TN and TP yields of the Yazoo River lower site of this study to estimates made from data spanning 1996–97 showed decreasing TN yields but similar TP yields. This suggests that TN yields may have decreased over the last 20–30 years, but TP yields remain constant or are increasing.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235003","issn":"ISSN 2328-0328","collaboration":"Prepared in cooperation with the Mississippi Department of Environmental Quality","usgsCitation":"Hicks, M.B., Crain, A.S., and Segrest, N.G., 2023, Status and trends of total nitrogen and total phosphorus concentrations, loads, and yields in streams of Mississippi, water years 2008–18: U.S. Geological Survey Scientific Investigations Report 2023–5003, 77 p., https://doi.org/10.3133/sir20235003.","productDescription":"Report: x, 77 p.; Data Release; Dataset","numberOfPages":"92","onlineOnly":"Y","ipdsId":"IP-130707","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":413300,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9VV2U70","text":"USGS data release","linkHelpText":"Datasets of streamflow, nutrient concentrations, loads 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\"}}]}","contact":"

Director, Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
640 Grassmere Park, Suite 100
Nashville, TN 37211

Contact Pubs Warehouse

","tableOfContents":"","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2023-02-24","noUsgsAuthors":false,"publicationDate":"2023-02-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Hicks, Matthew B. 0000-0001-5516-0296 mhicks@usgs.gov","orcid":"https://orcid.org/0000-0001-5516-0296","contributorId":3778,"corporation":false,"usgs":true,"family":"Hicks","given":"Matthew","email":"mhicks@usgs.gov","middleInitial":"B.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":864853,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Crain, Angela S. 0000-0003-0969-6238 ascrain@usgs.gov","orcid":"https://orcid.org/0000-0003-0969-6238","contributorId":3090,"corporation":false,"usgs":true,"family":"Crain","given":"Angela","email":"ascrain@usgs.gov","middleInitial":"S.","affiliations":[{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true},{"id":354,"text":"Kentucky Water Science Center","active":true,"usgs":true}],"preferred":true,"id":864854,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Segrest, Natalie G.","contributorId":302617,"corporation":false,"usgs":false,"family":"Segrest","given":"Natalie","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":864855,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70240798,"text":"sir20225126 - 2023 - Estimating streamflow for base flow conditions at partial-record streamgaging stations at Acadia National Park, Maine","interactions":[],"lastModifiedDate":"2026-02-24T17:51:19.791819","indexId":"sir20225126","displayToPublicDate":"2023-02-23T12:15:00","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":"2022-5126","displayTitle":"Estimating Streamflow for Base Flow Conditions at Partial-Record Streamgaging Stations at Acadia National Park, Maine","title":"Estimating streamflow for base flow conditions at partial-record streamgaging stations at Acadia National Park, Maine","docAbstract":"

The objective of the work presented in this report is to develop equations that can be used to extend the base flow record at multiple partial-record streamgaging stations at Acadia National Park in eastern coastal Maine based on nearby continuous-record streamgaging stations. Daily mean streamflow values at U.S. Geological Survey continuous-record streamgaging station Otter Creek near Bar Harbor, Maine (station 01022840) had stronger correlations with instantaneous measurements during base flow conditions from 2006 to 2020 at 14 partial-record streamgaging stations at Acadia National Park than the other four continuous-record streamgaging stations tested for use as index stations. Index stations are continuous-record stations on hydrologically similar streams that have the potential to be used to extend the record at the partial-record station. Base flow is that part of streamflow that is sustained primarily by groundwater discharge. It is not attributable to direct precipitation or melting snow. Five of the partial-record stations had strong correlations with Otter Creek (correlation coefficient greater than 0.90) and relatively low root mean square errors (from 0.04 to 0.19). An additional four partial-record stations had fair correlations with Otter Creek (correlation coefficient from 0.79 to 0.9) and relatively low root mean square errors (from 0.05 to 0.19). For these 10 stations, maintenance of variance extension type 1 (MOVE.1) record extension equations computed in this report provide a reasonable method for extending the partial record, estimating summer monthly means and medians, and estimating daily mean streamflow values at these sites on days with no streamflow (discharge) measurements. Four of the partial-record stations have weak correlations (less than 0.78) or high root mean square error values (greater than 9) or both, indicating that record extension techniques are not appropriate for these partial-record stations using currently [2022] available data.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225126","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Lombard, P.J., 2023, Estimating streamflow for base flow conditions at partial-record streamgaging stations at Acadia National Park, Maine: U.S. Geological Survey Scientific Investigations Report 2022–5126, 13 p., https://doi.org/10.3133/sir20225126.","productDescription":"Report: vi, 13 p.; Data Release","numberOfPages":"13","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-143769","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":413317,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ZP8XHG","text":"USGS data release","linkHelpText":"Data and code to support MOVE.1 regression equations for streamflow at partial-record streamgaging stations at Acadia National Park, Maine:"},{"id":413315,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5126/sir20225126.XML"},{"id":413312,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5126/coverthb.jpg"},{"id":413313,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5126/sir20225126.pdf","text":"Report","size":"1.33 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5126"},{"id":413316,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5126/images/"},{"id":413864,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/sir20225126/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2022-5126"},{"id":500481,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114380.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Maine","otherGeospatial":"Acadia National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -68.16726259768689,\n 44.32624433734378\n ],\n [\n -68.17739845831488,\n 44.36973371484888\n ],\n [\n -68.21954229987337,\n 44.38307924264697\n ],\n [\n -68.23981402112935,\n 44.41090441296549\n ],\n [\n -68.28035746364178,\n 44.41928748605292\n ],\n [\n -68.29422758871185,\n 44.406712425764226\n ],\n [\n -68.33050330043281,\n 44.35371506667144\n ],\n [\n -68.38971806515461,\n 44.35562227826236\n ],\n [\n -68.40305472387581,\n 44.31937464393428\n ],\n [\n -68.39025153150348,\n 44.27890346604781\n ],\n [\n -68.3390387620142,\n 44.21661505589944\n ],\n [\n -68.3112985118746,\n 44.217762064180675\n ],\n [\n -68.2883594588743,\n 44.24566571236582\n ],\n [\n -68.30329651664208,\n 44.285396004838105\n ],\n [\n -68.24514868461804,\n 44.281958867796675\n ],\n [\n -68.1982036459197,\n 44.29532438221068\n ],\n [\n -68.16726259768689,\n 44.32662596339111\n ],\n [\n -68.16726259768689,\n 44.32624433734378\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","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":"2023-02-23","noUsgsAuthors":false,"publicationDate":"2023-02-23","publicationStatus":"PW","contributors":{"authors":[{"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":864860,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70240792,"text":"sir20225131 - 2023 - Nutrient and suspended-sediment concentrations, loads, and yields in upper Macoupin Creek, Illinois, 2017–21","interactions":[],"lastModifiedDate":"2026-02-03T21:08:15.22249","indexId":"sir20225131","displayToPublicDate":"2023-02-23T07:16:54","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":"2022-5131","displayTitle":"Nutrient and Suspended-Sediment Concentrations, Loads, and Yields in Upper Macoupin Creek, Illinois, 2017–21","title":"Nutrient and suspended-sediment concentrations, loads, and yields in upper Macoupin Creek, Illinois, 2017–21","docAbstract":"

The U.S. Geological Survey, in cooperation with the Macoupin County Soil and Water Conservation District and the American Farmland Trust, undertook a monitoring effort from 2017 to 2021 in the upper Macoupin Creek watershed. The monitoring effort was to determine and characterize nitrogen, phosphorus, and suspended-sediment concentrations, loads, and yields for a 566.7 square kilometer area of the Macoupin Creek watershed at two locations on upper Macoupin Creek bracketing a segment of the watershed where increased implementation of conservation land-use practices was planned. Two monitoring stations were established, consisting of an upstream site (Macoupin Creek at Highway 108 near Carlinville, Illinois; U.S. Geological Survey streamgage 05586647) and a downstream site (Macoupin Creek at Highway 111 near Summerville, Ill.; U.S. Geological Survey streamgage 05586745). Data collected at these stations included continuous stream discharge and periodic samples for nutrients and suspended sediment. A Weighted Regressions on Time, Discharge, and Season–Kalman model was implemented to estimate daily concentrations for nitrate plus nitrite, total phosphorus, and suspended sediment for both monitoring stations. These daily concentrations were used in conjunction with the continuous stream discharge data to derive estimates of constituent flux, loads, and yields.

During the study period, the study area subbasin of the upper Macoupin Creek watershed reduced downstream nitrate and total phosphorus cummulative yields by approximately 54 and 21 percent, respectively; however, the cummulative yield of suspended sediment increased by approximately 10 percent from inputs within the study area. These data indicate that nitrate and phosphorus transport is greater from the upstream subbasin and being diluted in the combined subbasin by lower transport from the study area, whereas suspended sediment is being contributed from the study area reach, presumably through surface runoff and streambank and streambed erosion.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, Va.","doi":"10.3133/sir20225131","collaboration":"Prepared in cooperation with the Macoupin County Soil and Water Conservation District and American Farmland Trust","usgsCitation":"Garcia, L.A., Terrio, P.J., and Manaster, A.E., 2023, Nutrient and suspended-sediment concentrations, loads, and yields in upper Macoupin Creek, Illinois, 2017–21: U.S. Geological Survey Scientific Investigations Report 2022–5131, 17 p., https://doi.org/10.3133/sir20225131.","productDescription":"Report: vii, 17 p.; Data Release; Dataset","numberOfPages":"30","onlineOnly":"Y","ipdsId":"IP-144304","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":413286,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5131/images"},{"id":413285,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5131/sir20225131.XML","text":"Report","linkFileType":{"id":8,"text":"xml"}},{"id":413284,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5131/sir20225131.pdf","text":"Report","size":"2.40 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022–5131"},{"id":499487,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114379.htm","linkFileType":{"id":5,"text":"html"}},{"id":413345,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20225131/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":413289,"rank":6,"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":413283,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5131/coverthb.jpg"},{"id":413288,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P95IC7QS","text":"USGS data release","linkHelpText":"Nutrient and sediment concentrations, loads, and yields in the Upper Macoupin Creek watershed, water years 2018–2021"}],"country":"United States","state":"Illinois","otherGeospatial":"Upper Macoupin Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -90.666,\n 39.5\n ],\n [\n -90.666,\n 39\n ],\n [\n -89.5,\n 39\n ],\n [\n -89.5,\n 39.5\n ],\n [\n -90.666,\n 39.5\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":"2023-02-23","noUsgsAuthors":false,"publicationDate":"2023-02-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Garcia, Luis A. 0000-0002-0999-625X","orcid":"https://orcid.org/0000-0002-0999-625X","contributorId":300713,"corporation":false,"usgs":true,"family":"Garcia","given":"Luis","email":"","middleInitial":"A.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":864850,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Terrio, Paul J. 0000-0002-1515-9570 pjterrio@usgs.gov","orcid":"https://orcid.org/0000-0002-1515-9570","contributorId":3313,"corporation":false,"usgs":true,"family":"Terrio","given":"Paul","email":"pjterrio@usgs.gov","middleInitial":"J.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":864851,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Manaster, Adam E. 0000-0001-8183-4274","orcid":"https://orcid.org/0000-0001-8183-4274","contributorId":215663,"corporation":false,"usgs":true,"family":"Manaster","given":"Adam E.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":864852,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70241812,"text":"70241812 - 2023 - Data summary report: Unregulated contaminants monitoring project","interactions":[],"lastModifiedDate":"2023-03-28T12:11:44.70089","indexId":"70241812","displayToPublicDate":"2023-02-23T07:08:54","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Data summary report: Unregulated contaminants monitoring project","docAbstract":"

The Drinking Water Protection Section of the Minnesota Department of Health conducted reconnaissance monitoring of selected public water systems in Minnesota. Funding was obtained primarily from the Environment and Natural Resources Trust Fund. Sampling was conducted in 2019 and 2021. Laboratory analysis of samples was conducted for a variety of different contaminants of emerging concern (CECs), including selected pharmaceuticals, pesticides, PFAS, wastewater indicators and other parameters chosen for the physical and land use setting surrounding the sampling points. Sampling site and parameter selection were designed with several goals, as follows: Characterize occurrence and distribution of selected CECs in settings where such chemicals are most likely to be present; Determine if any such occurrences represent a public health concern; Compare results from coupled source water and finished (i.e., treated) water samples at public water system sites where such sampling is feasible; Assess if results from geologically vulnerable (sensitive subject to rapid recharge) and geologically non-vulnerable settings differ significantly. 306 samples were collected as part of the study, from three networks of public water systems differentiated on the basis of source water type (i.e., surface water or groundwater) and land use environment (agricultural and wastewater influenced). This report provides a preliminary, qualitative evaluation of the results. Additionally, more rigorous research will be conducted on these water quality data to evaluate the below findings in more detail. High-level findings from this assessment include the following: Very few samples exceeded health-based guidance for CECs; o When this occurred, MDH staff conducted follow up sampling at the system and provided technical advice about managing the situation. Only a fraction of the CECs analyzed were detected; o Of the 522 different CECs analyzed in the water samples, 161 were detected in one or more samples; o Additionally, most detections were at low levels; Among the CEC classes included in the analytical work, pesticides and PFAS were generally detected at a greater frequency than other CECs; o See Executive Summary Figure 1. The ten most commonly detected individual compounds include: o Tribromomethane, or bromoform, (a disinfection by-product) (70% of sites where analyzed); o norgestrel (a pharmaceutical) (69% of sites where analyzed); o lithium (68% of sites where analyzed); o Metolachlor SA (52%), Deethylatrazine (49%), atrazine (45%), and deisopropylatrazine (31%) (pesticides); o PFBA (44%) and PFHxS (27%) (PFAS compounds); and o 5-methyl benzotriazole (29%) (a benzotriazole). Some CECs were detected more frequently in samples collected from surface waters than those collected from groundwater sources; CEC concentrations were generally higher in vulnerable settings compared to nonvulnerable settings; Whether CECs were detected more frequently in the source water or finished water varied by CEC class. For example, o Benzotriazoles and pharmaceuticals were more frequently detected in source water samples than finished water samples; and o Tribromomethane, or bromoform, a common disinfection by-product, was more frequently found in finished water samples than in source water samples. This work prompted a series of programmatic changes and innovations: A response framework was established for helping the program and public water systems manage detections of unregulated CECs in drinking water; Results were forwarded to the program within MDH responsible for developing healthbased guidance in order to nominate specific compounds found in drinking water but for which limited or no risk advice is available; MDH is seeking support from the Clean Water Council to support the establishment of permanent capacity within the Drinking Water Protection Section to continue sampling efforts of this type.

","language":"English","publisher":"Minnesota Department of Health","collaboration":"Minnesota Department of Health, Minnesota Environment and Natural Resources Trust Fund","usgsCitation":"de Lambert, J., Overbo, A., Robertson, S., and Elliott, S.M., 2023, Data summary report: Unregulated contaminants monitoring project, 85 p.","productDescription":"85 p.","ipdsId":"IP-145896","costCenters":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":414813,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":414798,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.health.state.mn.us/communities/environment/water/docs/ucmpreport.pdf"}],"country":"United 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Sarah M. 0000-0002-1414-3024 selliott@usgs.gov","orcid":"https://orcid.org/0000-0002-1414-3024","contributorId":1472,"corporation":false,"usgs":true,"family":"Elliott","given":"Sarah","email":"selliott@usgs.gov","middleInitial":"M.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":867798,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70246686,"text":"70246686 - 2023 - Vulnerability of estuarine systems in the contiguous United States to water quality change under future climate and land-use","interactions":[],"lastModifiedDate":"2023-07-14T11:53:26.020041","indexId":"70246686","displayToPublicDate":"2023-02-23T06:50:39","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5053,"text":"Earth's Future","active":true,"publicationSubtype":{"id":10}},"title":"Vulnerability of estuarine systems in the contiguous United States to water quality change under future climate and land-use","docAbstract":"

Changes in climate and land-use and land-cover (LULC) are expected to influence surface water runoff and nutrient characteristics of estuarine watersheds, but the extent to which estuaries are vulnerable to altered nutrient loading under future conditions is poorly understood. The present work aims to address this gap through the development of a new vulnerability assessment framework that accounts for (a) estuarine exposure to projected changes in total nitrogen (TN) and total phosphorus (TP) loads as a function of LULC and climate change under several scenarios, (b) sensitivity, and (c) adaptive capacity. The framework was applied to 112 estuaries and their contributing watersheds across the contiguous U.S., specifically to look at regional variability in estuarine vulnerability to nutrient loading. Study findings revealed that the largest increases in estuarine nutrient loads are expected in the North and South Atlantic regions and eastern Gulf of Mexico, while the lowest increases are expected in the North and South Pacific regions and the western Gulf of Mexico. However, the North Atlantic and the South Pacific had the highest adaptive capacity, which could potentially counteract the effects of LULC and climate change on nutrient loads. Strong variation in predicted estuarine nutrient loads was observed as a function of climate model projections, while projected LULC changes were more consistently associated with elevated loads. Our findings illustrate the benefits of integrating natural and socio-ecological factors to identify opportunities to develop adaptation plans and policies to mitigate ecological degradation in vitally important estuaries.

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This is a modern, updated version of the widely used diagram featured on the USGS Water Science School. Notably, this new water cycle diagram depicts humans and major categories of human water use as key components of the water cycle, in addition to the key pools and fluxes of the hydrologic cycle. 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Integrated Information Dissemination Division
Water Resource Mission Area
U.S. Geological Survey
1 Gifford Pinchot Drive
Madison, WI 53726
Email: water-science-school@usgs.gov

","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2023-02-22","noUsgsAuthors":false,"publicationDate":"2023-02-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Corson-Dosch, Hayley R. 0000-0001-8695-1584","orcid":"https://orcid.org/0000-0001-8695-1584","contributorId":244707,"corporation":false,"usgs":true,"family":"Corson-Dosch","given":"Hayley","middleInitial":"R.","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":864531,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nell, Cee S. 0000-0003-2218-3971","orcid":"https://orcid.org/0000-0003-2218-3971","contributorId":244705,"corporation":false,"usgs":true,"family":"Nell","given":"Cee","middleInitial":"S.","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":864532,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Volentine, Rachel E. 0000-0002-4837-8075","orcid":"https://orcid.org/0000-0002-4837-8075","contributorId":302488,"corporation":false,"usgs":true,"family":"Volentine","given":"Rachel","email":"","middleInitial":"E.","affiliations":[{"id":37316,"text":"WMA - 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Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":864540,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Read, Emily 0000-0002-9617-9433 eread@usgs.gov","orcid":"https://orcid.org/0000-0002-9617-9433","contributorId":190110,"corporation":false,"usgs":true,"family":"Read","given":"Emily","email":"eread@usgs.gov","affiliations":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true},{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":864541,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70240217,"text":"ofr20221121 - 2023 - Observations of coastal circulation, waves, and sediment transport along West Maui, Hawaiʻi (November 2017– March 2018), and modeling effects of potential watershed restoration on decreasing sediment loads to adjacent coral reefs","interactions":[],"lastModifiedDate":"2023-02-23T11:58:55.644522","indexId":"ofr20221121","displayToPublicDate":"2023-02-22T09:06:04","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-1121","displayTitle":"Observations of Coastal Circulation, Waves, and Sediment Transport Along West Maui, Hawaiʻi (November 2017– March 2018), and Modeling Effects of Potential Watershed Restoration on Decreasing Sediment Loads to Adjacent Coral Reefs","title":"Observations of coastal circulation, waves, and sediment transport along West Maui, Hawaiʻi (November 2017– March 2018), and modeling effects of potential watershed restoration on decreasing sediment loads to adjacent coral reefs","docAbstract":"

Terrestrial sediment discharging from watersheds off West Maui, Hawaiʻi, has been documented as a primary stressor to local coral reefs, causing coral reef health to decline. The U.S. Geological Survey acquired and analyzed physical oceanographic and sedimentologic field data off the coast of West Maui to calibrate and validate physics-based, numerical hydrodynamic and sediment transport models of the study area developed by Deltares. These models simulated terrestrial sediment transport and dispersal from West Maui watersheds into coastal waters and how terrestrial sediment affects nearby coral reefs under different oceanographic forcing and watershed restoration scenarios.

Wave energy and near-bed turbidity are positively correlated in the field observations, illustrating a process not captured by the model simulations in which sediment already deposited on the seabed is resuspended by wave action and subsequently transported by prevailing currents. In the model simulations, large waves during flood events led to a decrease in suspended-sediment concentrations. Notably, however, the model results only consider sediment entering coastal waters from five stream sources and do not simulate sediment already present on the seabed.

The model simulations project that the Honokeana and Māhinahina coral reefs would experience the greatest reduction in sediment impacts from theoretical watershed restoration. Additionally, when large waves coincide with flood events, post-storm sedimentation generally decreases in the nearshore region, but increases in the region offshore of the reefs. The measured and modeled sediment dynamics demonstrate a demarcation between the coral reefs sheltered within embayments (Honolua reef) or behind points (Wahikuli reef) and those along the relatively open coastline between Kapalua and Kāʻanapali (Kapalua, Honokeana, Māhinahina, and Honokōwai reefs). The sheltered sites are affected by terrestrial sediment from single stream mouths, where most sediment is delivered within hours of a flood (rain) event. Once this sediment enters the nearshore, it settles out and remains within the reef area for a prolonged period owing to a lack of wave or current-driven bed shear stress. Thus, the primary effect of sediment on the reefs within these sheltered areas is sedimentation. In contrast, coral reefs along the unsheltered (or “open”) section of coastline (between Kapalua and Kāʻanapali) are more exposed to waves and terrestrial sediment from multiple stream sources. At these reefs, fine-grained terrestrial sediment can rarely settle but instead remains in suspension. Thus, even long after a flood event has occurred, these sites chronically experience light attenuation from suspended sediment.

These analyses underscore the importance of understanding how coastal ocean waves and circulation can lead to different sediment dynamics and stressors for coral reefs along the same region of the West Maui coastline. These differing factors indicate that the most effective watershed restoration and mitigation strategies may vary among the different coral reefs and streams. An important next step is to determine how the science of this study can support management goals for these coral reefs: what are target reductions of sedimentation, suspended-sediment concentrations, or the resulting light attenuation? Then, using the coupled hydrodynamic-sediment model, we can examine which watershed restoration scenarios in each stream will best achieve those targets.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221121","collaboration":"Prepared in cooperation with the Deltares Impacts of Extreme Weather Strategic Research Program","programNote":"Coastal and the Marine Hazards and Resources Program","usgsCitation":"Storlazzi, C.D., Cheriton, O.M., Cronin, K.M., van der Heijden, L.H., Winter, G., Rosenberger, K.J., Logan, J.B., and McCall, R.T., 2023, Observations of coastal circulation, waves, and sediment transport along West Maui, Hawaiʻi (November 2017–March 2018), and modeling effects of potential watershed restoration on decreasing sediment loads to adjacent coral reefs: U.S. Geological Survey Open-File Report 2022–1121, 73 p., https://doi.org/10.3133/ofr20221121.","productDescription":"Report: ix, 73 p.; 2 Data Releases","onlineOnly":"Y","ipdsId":"IP-138761","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":412766,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P914LMK2","text":"USGS data release","description":"USGS data release","linkHelpText":"Model parameter input files to compare effects of stream discharge scenarios on sediment deposition and concentrations around coral reefs off west Maui, Hawaii"},{"id":412765,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9DK9O60","text":"USGS data release","description":"USGS data release","linkHelpText":"Time series data of oceanographic conditions from West Maui, Hawaii, 2017-2018 Coral Reef Circulation and Sediment Dynamics Experiment"},{"id":412764,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1121/ofr20221121.pdf","text":"Report","size":"17.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1121"},{"id":412763,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1121/coverthb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"West Maui","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -156.72475140864907,\n 20.922050876041368\n ],\n [\n -156.5888533113449,\n 20.922050876041368\n ],\n [\n -156.5888533113449,\n 21.0514971765583\n ],\n [\n -156.72475140864907,\n 21.0514971765583\n ],\n [\n -156.72475140864907,\n 20.922050876041368\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

Center Director, Pacific Coastal and Marine Science Center
U.S. Geological Survey
2885 Mission Street
Santa Cruz, CA 95060

","tableOfContents":"","publishedDate":"2023-02-22","noUsgsAuthors":false,"publicationDate":"2023-02-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Storlazzi, Curt D. 0000-0001-8057-4490 cstorlazzi@usgs.gov","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":140584,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt","email":"cstorlazzi@usgs.gov","middleInitial":"D.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":863595,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cheriton, Olivia M. 0000-0003-3011-9136 ocheriton@usgs.gov","orcid":"https://orcid.org/0000-0003-3011-9136","contributorId":5476,"corporation":false,"usgs":true,"family":"Cheriton","given":"Olivia M.","email":"ocheriton@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":863596,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cronin, Katherine M. 0000-0003-3011-9136","orcid":"https://orcid.org/0000-0003-3011-9136","contributorId":302141,"corporation":false,"usgs":false,"family":"Cronin","given":"Katherine","email":"","middleInitial":"M.","affiliations":[{"id":36257,"text":"Deltares","active":true,"usgs":false}],"preferred":false,"id":863597,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"van der Heijden, Luuk H.","contributorId":302270,"corporation":false,"usgs":false,"family":"van der Heijden","given":"Luuk","email":"","middleInitial":"H.","affiliations":[{"id":36257,"text":"Deltares","active":true,"usgs":false}],"preferred":false,"id":863598,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Winter, Gundula","contributorId":204988,"corporation":false,"usgs":false,"family":"Winter","given":"Gundula","email":"","affiliations":[],"preferred":false,"id":863599,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rosenberger, Kurt J. 0000-0002-5185-5776 krosenberger@usgs.gov","orcid":"https://orcid.org/0000-0002-5185-5776","contributorId":140453,"corporation":false,"usgs":true,"family":"Rosenberger","given":"Kurt","email":"krosenberger@usgs.gov","middleInitial":"J.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":863600,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Logan, Joshua B. 0000-0002-6191-4119 jlogan@usgs.gov","orcid":"https://orcid.org/0000-0002-6191-4119","contributorId":2335,"corporation":false,"usgs":true,"family":"Logan","given":"Joshua","email":"jlogan@usgs.gov","middleInitial":"B.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":863601,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"McCall, Robert T.","contributorId":148986,"corporation":false,"usgs":false,"family":"McCall","given":"Robert","email":"","middleInitial":"T.","affiliations":[{"id":12474,"text":"Deltares, Netherlands","active":true,"usgs":false}],"preferred":false,"id":863602,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70240838,"text":"70240838 - 2023 - Modeling post-wildfire hydrologic response: Review and future directions for applications of physically based distributed simulation","interactions":[],"lastModifiedDate":"2023-02-24T13:08:09.195827","indexId":"70240838","displayToPublicDate":"2023-02-22T07:04:13","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5053,"text":"Earth's Future","active":true,"publicationSubtype":{"id":10}},"title":"Modeling post-wildfire hydrologic response: Review and future directions for applications of physically based distributed simulation","docAbstract":"

Wildfire is a growing concern as climate shifts. The hydrologic effects of wildfire, which include elevated hazards and changes in water quantity and quality, are increasingly assessed using numerical models. Post-wildfire application of physically based distributed models provides unique insight into the underlying processes that affect water resources after wildfire. This work reviews and synthesizes post-wildfire applications of physically based distributed models by examining the scales and geographic/ecohydrologic distribution of model applications, hydrologic response process representation, model parameterization, and model performance metrics. Highlighted gaps and opportunities for advancing physically based distributed hydrologic response modeling after wildfire include the following: (a) applying models in under-represented geographic (S. America, Africa, Asia) and ecohydrologic regions (arid or dry subhumid climates), (b) incorporating all four major streamflow generation mechanisms (infiltration excess, saturation excess, subsurface storm flow, and groundwater flow), (c) representing integrated vadose zone and saturated zone processes to better capture subsurface streamflow generation, (d) building new remotely sensed model parameterization methods for precipitation interception, infiltration, and overland flow that account for burn severity and recovery, (e) incorporating distributed state variables (e.g., soil moisture, groundwater levels) in model performance assessment, (f) designing model intercomparison studies, including field datasets specifically for post-wildfire model development and validation, (g) linking mechanistic vegetation regrowth models with hydrologic models to improve simulation of process shifts as ecosystems recover, and (h) creating a new community modeling framework to integrate modeling advances across the wildfire science community.

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2022EF003038","usgsCitation":"Ebel, B., Shephard, Z.M., Walvoord, M.A., Murphy, S.F., Partridge, T.F., and Perkins, K., 2023, Modeling post-wildfire hydrologic response: Review and future directions for applications of physically based distributed simulation: Earth's Future, v. 11, e2022EF003038, 23 p., https://doi.org/10.1029/2022EF003038.","productDescription":"e2022EF003038, 23 p.","ipdsId":"IP-142611","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":444393,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2022ef003038","text":"Publisher Index Page"},{"id":413398,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","noUsgsAuthors":false,"publicationDate":"2023-02-22","publicationStatus":"PW","contributors":{"authors":[{"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":865024,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shephard, Zachary M. 0000-0003-2994-3355","orcid":"https://orcid.org/0000-0003-2994-3355","contributorId":222581,"corporation":false,"usgs":true,"family":"Shephard","given":"Zachary","email":"","middleInitial":"M.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":865025,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Walvoord, Michelle A. 0000-0003-4269-8366","orcid":"https://orcid.org/0000-0003-4269-8366","contributorId":211843,"corporation":false,"usgs":true,"family":"Walvoord","given":"Michelle","email":"","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":865026,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":865027,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Partridge, Trevor Fuess 0000-0003-1589-4783","orcid":"https://orcid.org/0000-0003-1589-4783","contributorId":302668,"corporation":false,"usgs":true,"family":"Partridge","given":"Trevor","email":"","middleInitial":"Fuess","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":865028,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Perkins, Kimberlie 0000-0001-8349-447X kperkins@usgs.gov","orcid":"https://orcid.org/0000-0001-8349-447X","contributorId":138544,"corporation":false,"usgs":true,"family":"Perkins","given":"Kimberlie","email":"kperkins@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":865029,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70240752,"text":"fs20233003 - 2023 - Tracking status and trends in seven key indicators of stream health in the Chesapeake Bay watershed","interactions":[],"lastModifiedDate":"2026-02-04T20:31:10.169405","indexId":"fs20233003","displayToPublicDate":"2023-02-21T14:05:00","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-3003","displayTitle":"Tracking Status and Trends in Seven Key Indicators of Stream Health in the Chesapeake Bay Watershed","title":"Tracking status and trends in seven key indicators of stream health in the Chesapeake Bay watershed","docAbstract":"

“The Bay Connects us, the Bay reflects us” writes Tom Horton in the book “Turning the Tide—Saving the Chesapeake Bay”. The Chesapeake Bay watershed contains the largest estuary in the United States. The watershed stretches north to Cooperstown, New York, south to Lynchburg and Virginia Beach, Virginia, west to Pendleton County, West Virginia, and east to Seaford, Delaware, and Scranton, Pennsylvania. The watershed is more than 64,000 square miles that contain 150 major rivers and streams, hereafter referred to collectively as streams, that total more than 100,000 miles in length. The watershed contains thousands of smaller creeks and tributaries, large numbers of plants and animals, and, in 2020, more than 18.4 million people. As changes occur in population, land use, and climate within the watershed, so too do the diversity and health of the Bay's ecosystems.

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U.S. Geological Survey
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","tableOfContents":"","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"publishedDate":"2023-02-21","noUsgsAuthors":false,"publicationDate":"2023-02-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Austin, Samuel H. 0000-0001-5626-023X saustin@usgs.gov","orcid":"https://orcid.org/0000-0001-5626-023X","contributorId":153,"corporation":false,"usgs":true,"family":"Austin","given":"Samuel","email":"saustin@usgs.gov","middleInitial":"H.","affiliations":[{"id":37280,"text":"Virginia and West Virginia Water Science Center ","active":true,"usgs":true}],"preferred":true,"id":864693,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cashman, Matthew J. 0000-0002-6635-4309","orcid":"https://orcid.org/0000-0002-6635-4309","contributorId":203315,"corporation":false,"usgs":true,"family":"Cashman","given":"Matthew","middleInitial":"J.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":864694,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Clune, John W. 0000-0002-3563-1975","orcid":"https://orcid.org/0000-0002-3563-1975","contributorId":205148,"corporation":false,"usgs":true,"family":"Clune","given":"John W.","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":864695,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Colgin, James E. 0000-0003-0519-6738","orcid":"https://orcid.org/0000-0003-0519-6738","contributorId":294621,"corporation":false,"usgs":true,"family":"Colgin","given":"James","email":"","middleInitial":"E.","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":864696,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fanelli, Rosemary M. 0000-0002-0874-1925","orcid":"https://orcid.org/0000-0002-0874-1925","contributorId":206608,"corporation":false,"usgs":true,"family":"Fanelli","given":"Rosemary M.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":864697,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Krause, Kevin P. 0000-0002-0255-7027","orcid":"https://orcid.org/0000-0002-0255-7027","contributorId":218454,"corporation":false,"usgs":true,"family":"Krause","given":"Kevin","email":"","middleInitial":"P.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":864698,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Majcher, Emily H. 0000-0001-7144-6809","orcid":"https://orcid.org/0000-0001-7144-6809","contributorId":203335,"corporation":false,"usgs":true,"family":"Majcher","given":"Emily","middleInitial":"H.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":864699,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Maloney, Kelly O. 0000-0003-2304-0745 kmaloney@usgs.gov","orcid":"https://orcid.org/0000-0003-2304-0745","contributorId":4636,"corporation":false,"usgs":true,"family":"Maloney","given":"Kelly","email":"kmaloney@usgs.gov","middleInitial":"O.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":864700,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Mason, Christopher A. 0000-0001-9001-8244","orcid":"https://orcid.org/0000-0001-9001-8244","contributorId":225681,"corporation":false,"usgs":true,"family":"Mason","given":"Christopher","middleInitial":"A.","affiliations":[{"id":37759,"text":"VA/WV Water Science Center","active":true,"usgs":true}],"preferred":true,"id":864701,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Moyer, Douglas L. 0000-0001-6330-478X dlmoyer@usgs.gov","orcid":"https://orcid.org/0000-0001-6330-478X","contributorId":174389,"corporation":false,"usgs":true,"family":"Moyer","given":"Douglas","email":"dlmoyer@usgs.gov","middleInitial":"L.","affiliations":[{"id":37759,"text":"VA/WV Water Science Center","active":true,"usgs":true}],"preferred":true,"id":864702,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Zimmerman, Tammy M. 0000-0003-0842-6981","orcid":"https://orcid.org/0000-0003-0842-6981","contributorId":219288,"corporation":false,"usgs":true,"family":"Zimmerman","given":"Tammy M.","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":864703,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70240974,"text":"70240974 - 2023 - Vulnerability to climate change of managed stocks in the California Current large marine ecosystem","interactions":[],"lastModifiedDate":"2023-03-03T14:19:06.622212","indexId":"70240974","displayToPublicDate":"2023-02-21T08:13:02","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3912,"text":"Frontiers in Marine Science","onlineIssn":"2296-7745","active":true,"publicationSubtype":{"id":10}},"title":"Vulnerability to climate change of managed stocks in the California Current large marine ecosystem","docAbstract":"

Introduction: Understanding how abundance, productivity and distribution of individual species may respond to climate change is a critical first step towards anticipating alterations in marine ecosystem structure and function, as well as developing strategies to adapt to the full range of potential changes.

Methods: This study applies the NOAA (National Oceanic and Atmospheric Administration) Fisheries Climate Vulnerability Assessment method to 64 federally-managed species in the California Current Large Marine Ecosystem to assess their vulnerability to climate change, where vulnerability is a function of a species’ exposure to environmental change and its biological sensitivity to a set of environmental conditions, which includes components of its resiliency and adaptive capacity to respond to these new conditions.

Results: Overall, two-thirds of the species were judged to have Moderate or greater vulnerability to climate change, and only one species was anticipated to have a positive response. Species classified as Highly or Very Highly vulnerable share one or more characteristics including: 1) having complex life histories that utilize a wide range of freshwater and marine habitats; 2) having habitat specialization, particularly for areas that are likely to experience increased hypoxia; 3) having long lifespans and low population growth rates; and/or 4) being of high commercial value combined with impacts from non-climate stressors such as anthropogenic habitat degradation. Species with Low or Moderate vulnerability are either habitat generalists, occupy deep-water habitats or are highly mobile and likely to shift their ranges.

Discussion: As climate-related changes intensify, this work provides key information for both scientists and managers as they address the long-term sustainability of fisheries in the region. This information can inform near-term advice for prioritizing species-level data collection and research on climate impacts, help managers to determine when and where a precautionary approach might be warranted, in harvest or other management decisions, and help identify habitats or life history stages that might be especially effective to protect or restore.

","language":"English","publisher":"Frontiers Media","doi":"10.3389/fmars.2023.1103767","usgsCitation":"McClure, M., Haltuch, M.A., Willis-Norton, E., Huff, D.D., Hazen, E.L., Crozier, L.G., Jacox, M.G., Nelson, M.W., Andrews, K.S., Barnett, L.A., Berger, A.M., Beyer, S., Bizzarro, J., Boughton, D.A., Cope, J.M., Carr, M.H., Dewar, H., Dick, E., Emmanis, D., Dunham, J., Gertseva, V., Greene, C.M., Gustafson, R.G., S., H.O., Harvey, C., Henderson, M., Jordan, C.E., Kaplan, I., Lindley, S.T., Mantua, N., Matson, S.E., Monk, M.H., Moyle, P.B., Nicol, C., Pohl, J., Rykaczewski, R.R., Samhouri, J.F., Sogard, S., Tolimieri, N., Wallace, J., Wetzel, C., and Bograd, S.J., 2023, Vulnerability to climate change of managed stocks in the California Current large marine ecosystem: Frontiers in Marine Science, v. 10, 1103767, 21 p., https://doi.org/10.3389/fmars.2023.1103767.","productDescription":"1103767, 21 p.","ipdsId":"IP-148260","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem 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probabilities of late summer surface flow presence in a glaciated mountainous headwater region","interactions":[],"lastModifiedDate":"2023-02-20T22:04:07.85217","indexId":"70240754","displayToPublicDate":"2023-02-20T15:55:10","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Predicting probabilities of late summer surface flow presence in a glaciated mountainous headwater region","docAbstract":"

Accurate mapping of streams that maintain surface flow during annual baseflow periods in mountain headwater streams is important for informing water availability for human consumption and is a fundamental determinant of in-channel conditions for stream-dwelling organisms. Yet accurate mapping that captures local spatial variability and associated local controls on surface flow presence is limited. An empirical random-forest model was developed to predict streamflow permanence (late summer surface-flow presence) for Mount Rainier National Park and the surrounding mountainous area in western Washington, USA. This model was developed to improve upon the existing multi-state, regional-scale probability of stream permanence developed for the greater Pacific Northwest Region (PROSPERPNW). The model was trained on 544 wet/dry observations collected during the late summer, baseflow period from 2018 to 2020 using the crowd-source mobile application, FLOwPER. Final model accuracy was 0.74 with drainage area and covariates describing geology, topography, and land cover as top predictors of streamflow permanence compared to coarser resolution climatic covariates. The prevalence of static covariates over climatic covariates as top ranked important covariates highlights the importance of scale when evaluating controls on streamflow permanence. Cross validation of the model indicates that streamflow permanence probabilities from this model is an improvement over the regional-scale PROSPERPNW model demonstrating the utility of relatively simple, crowd-sourced data to address water resource needs, and that determination of important predictors of streamflow permanence is influenced by the spatial and temporal resolution of analysis.

","language":"English","publisher":"Wiley","doi":"10.1002/hyp.14813","usgsCitation":"Jaeger, K.L., Sando, R., Dunn, S., and Gendaszek, A.S., 2023, Predicting probabilities of late summer surface flow presence in a glaciated mountainous headwater region: Hydrological Processes, v. 37, no. 2, e14813, 20 p., https://doi.org/10.1002/hyp.14813.","productDescription":"e14813, 20 p.","ipdsId":"IP-141066","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true},{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"links":[{"id":444412,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/hyp.14813","text":"Publisher Index Page"},{"id":435442,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P942QL23","text":"USGS data release","linkHelpText":"Supporting data for and predictions from streamflow permanence modeling in Mount Rainier National Park and surrounding area, Washington, 2018-2020"},{"id":413225,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Mt. Rainier National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.91425095542269,\n 47.01752002020956\n ],\n [\n -122.78795134745224,\n 46.62862820386181\n ],\n [\n -122.55339493264981,\n 46.550098584041734\n ],\n [\n -122.65563747243549,\n 46.34497384739839\n ],\n [\n -122.89620815428425,\n 46.09474739160191\n ],\n [\n -122.7909584809756,\n 45.92766699262768\n ],\n [\n -122.74585147812789,\n 45.67282216496895\n ],\n [\n -122.66766600652696,\n 45.61185277936909\n ],\n [\n -122.30380285023114,\n 45.54239311283217\n ],\n [\n -121.81664721948816,\n 45.70223191477319\n ],\n [\n -121.67531194390217,\n 45.68332742209245\n ],\n [\n -121.45879833023858,\n 45.69383070693286\n ],\n [\n -121.1580849779278,\n 45.630781413305954\n ],\n [\n -120.98066410006487,\n 45.679125555918176\n ],\n [\n -121.06185670518839,\n 46.012189334319174\n ],\n [\n -121.07388523928094,\n 46.11234505718508\n ],\n [\n -120.77317188697053,\n 46.28718041984081\n ],\n [\n -120.78219328754065,\n 46.50050734721816\n ],\n [\n -120.60477240967734,\n 46.628693092975396\n ],\n [\n -120.65589367957018,\n 46.69473497860815\n ],\n [\n -120.90548576198775,\n 46.88004533998597\n ],\n [\n -121.37760572511556,\n 47.1445446352175\n ],\n [\n -122.05120363429107,\n 47.246711543948805\n ],\n [\n -122.36695265421739,\n 47.369052224585346\n ],\n [\n -122.54136639855736,\n 47.309956252224225\n ],\n [\n -122.67368027357409,\n 47.14249929055501\n ],\n [\n -122.9052295548532,\n 47.16294919605744\n ],\n [\n -122.91425095542269,\n 47.01752002020956\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"37","issue":"2","noUsgsAuthors":false,"publicationDate":"2023-02-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Jaeger, Kristin L. 0000-0002-1209-8506","orcid":"https://orcid.org/0000-0002-1209-8506","contributorId":206935,"corporation":false,"usgs":true,"family":"Jaeger","given":"Kristin","middleInitial":"L.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":864707,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sando, Roy 0000-0003-0704-6258","orcid":"https://orcid.org/0000-0003-0704-6258","contributorId":3874,"corporation":false,"usgs":true,"family":"Sando","given":"Roy","email":"","affiliations":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"preferred":true,"id":864708,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dunn, Sarah B. 0000-0003-4463-0074","orcid":"https://orcid.org/0000-0003-4463-0074","contributorId":291768,"corporation":false,"usgs":false,"family":"Dunn","given":"Sarah B.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":864709,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gendaszek, Andrew S. 0000-0002-2373-8986 agendasz@usgs.gov","orcid":"https://orcid.org/0000-0002-2373-8986","contributorId":3509,"corporation":false,"usgs":true,"family":"Gendaszek","given":"Andrew","email":"agendasz@usgs.gov","middleInitial":"S.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":864710,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70240844,"text":"70240844 - 2023 - Hydrologic compartmentalization and analytic-element groundwater-flow simulations for a draining mine tunnel","interactions":[],"lastModifiedDate":"2023-02-24T12:37:42.644166","indexId":"70240844","displayToPublicDate":"2023-02-18T06:32:58","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1534,"text":"Environmental Earth Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Hydrologic compartmentalization and analytic-element groundwater-flow simulations for a draining mine tunnel","docAbstract":"

Draining mine tunnels contribute contaminants to groundwater and surface water, but remediation strategies may be hindered as hydrogeologic characterization and modeling of these heterogeneous features generally relies on sparse data sets. The Captain Jack mine site in Colorado, USA, presents a unique data set allowing for temporal evaluation of groundwater connectivity in the vicinity of an abandoned mine, where a hydraulic bulkhead is impounding water within the mine workings. This study applied statistical analysis of system pressure responses to bulkheading and used an analytic-element modeling approach to characterize heterogeneity and groundwater flow. Groundwater-level elevation data collected over a period of 4 years, both prior to and after bulkheading, indicate that the mine workings act as a sink to the local groundwater system. Despite groundwater flow being generally oriented towards the mine workings, there are also large vertical and horizontal hydraulic gradients which persist through time. Although the groundwater system is highly compartmentalized, statistical analysis using Kendall’s Tau indicates correlations between hydraulic head changes in the mine workings and several wells completed in crystalline bedrock, indicating the influence of fracture flow. An analytic-element model was parameterized to account for uncertainty in hydraulic conductivity, recharge, and discharge. Model results reproduced the range of observed hydraulic heads in the mine workings and adjacent igneous dikes but failed to closely simulate hydraulic heads in several wells located distal from the mine workings in granitic bedrock. The modeling approach shows potential promise, however, for conducting preliminary modeling to guide data collection at other similar mine sites.

","language":"English","publisher":"Springer","doi":"10.1007/s12665-023-10797-3","usgsCitation":"Newman, C.P., 2023, Hydrologic compartmentalization and analytic-element groundwater-flow simulations for a draining mine tunnel: Environmental Earth Sciences, v. 82, 117, 14 p., https://doi.org/10.1007/s12665-023-10797-3.","productDescription":"117, 14 p.","ipdsId":"IP-131194","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":435445,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9NVBZXO","text":"USGS data release","linkHelpText":"Analytic-element groundwater-flow model of the Captain Jack Superfund Site, Boulder County, Colorado"},{"id":413393,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -105.718234057508,\n 40.20731895041291\n ],\n [\n -105.718234057508,\n 39.92577764315672\n ],\n [\n -105.21856832600534,\n 39.92577764315672\n ],\n [\n -105.21856832600534,\n 40.20731895041291\n ],\n [\n -105.718234057508,\n 40.20731895041291\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"82","noUsgsAuthors":false,"publicationDate":"2023-02-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Newman, Connor P. 0000-0002-6978-3440","orcid":"https://orcid.org/0000-0002-6978-3440","contributorId":222596,"corporation":false,"usgs":true,"family":"Newman","given":"Connor","email":"","middleInitial":"P.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":865033,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70240815,"text":"70240815 - 2023 - Outlining potential biomarkers of exposure and effect to critical minerals: Nutritionally essential trace elements and the rare earth elements","interactions":[],"lastModifiedDate":"2023-02-23T13:06:15.936835","indexId":"70240815","displayToPublicDate":"2023-02-17T07:05:04","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7597,"text":"Toxics","active":true,"publicationSubtype":{"id":10}},"title":"Outlining potential biomarkers of exposure and effect to critical minerals: Nutritionally essential trace elements and the rare earth elements","docAbstract":"
Emerging and low-carbon technologies and innovations are driving a need for domestic sources, sustainable use, and availability of critical minerals (CMs)—those vital to the national and economic security of the United States. Understanding the known and potential health effects of exposures to such mineral commodities can inform prudent and environmentally responsible handling and harvesting. We review the occurrence, use, predominant exposure pathways, and adverse outcome pathways (AOP) for human and fish receptors of those CMs that are nutritionally essential trace metals (specifically, cobalt, chromium, manganese, nickel, and zinc), as well as the rare earth elements. Biological responses to some elements having comparable biogeochemistry can sometimes be similar. Candidate quantifiable biomarkers for assessing potential AOP are conveyed.
","language":"English","publisher":"MDPI","doi":"10.3390/toxics11020188","usgsCitation":"Jenkins, J., Musgrove, M., and White, S.J., 2023, Outlining potential biomarkers of exposure and effect to critical minerals: Nutritionally essential trace elements and the rare earth elements: Toxics, v. 11, no. 2, 188, 29 p., https://doi.org/10.3390/toxics11020188.","productDescription":"188, 29 p.","ipdsId":"IP-144657","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":444429,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/toxics11020188","text":"Publisher Index Page"},{"id":413342,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","issue":"2","noUsgsAuthors":false,"publicationDate":"2023-02-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Jenkins, Jill 0000-0002-5087-0894","orcid":"https://orcid.org/0000-0002-5087-0894","contributorId":206579,"corporation":false,"usgs":true,"family":"Jenkins","given":"Jill","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":864909,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Musgrove, MaryLynn 0000-0003-1607-3864","orcid":"https://orcid.org/0000-0003-1607-3864","contributorId":223710,"corporation":false,"usgs":true,"family":"Musgrove","given":"MaryLynn","email":"","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":864910,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"White, Sarah Jane 0000-0002-4055-8207","orcid":"https://orcid.org/0000-0002-4055-8207","contributorId":216796,"corporation":false,"usgs":true,"family":"White","given":"Sarah","email":"","middleInitial":"Jane","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":864911,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70240828,"text":"70240828 - 2023 - Building a library of source samples for sediment fingerprinting – Potential and proof of concept","interactions":[],"lastModifiedDate":"2023-02-24T12:46:07.469637","indexId":"70240828","displayToPublicDate":"2023-02-17T06:38:46","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2258,"text":"Journal of Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Building a library of source samples for sediment fingerprinting – Potential and proof of concept","docAbstract":"

Purpose

Sediment fingerprinting of fluvial targets has proven useful to guide conservation management and prioritize sediment sources for Federal and State supported programs in the United States. However, the collection and analysis of source samples can make these studies unaffordable, especially when needed for multiple drainage basins. We investigate the potential use of source samples from a basin with similar physiography (using samples from one of a “pair” to evaluate samples from the other) or combined from multiple basins (a “library”).

Methods

Source samples from eight basins across six ecoregions were harvested from existing, published studies. Individual source samples were fingerprinted using a mixing model derived from source samples from other basins. The ability to identify source category was evaluated both as part of source verification and by classifying source samples as “targets.”

Results

Approximately half of cropland samples were identified as targets, both as pairs and with the multi-basin source dataset, indicating that cropland samples could be shared for basins in similar ecoregions and be combined for larger stream systems. Streambank samples were better identified with the multi-basin analysis relative to the pairs, and those from mixed land-use basins improved this differentiation except for samples from basins with a dominant land-use type. Inconsistent identification of pasture samples highlighted the need for local samples. Inconsistent identification of forest samples indicated that upland- and riparian-forest samples are distinct. Road samples were identified as both sources and targets, and other source types were rarely apportioned as road: these may have the best potential to supplement local source samples. This source-sample library was then used to improve the accuracy of sediment-source apportionment for a previously studied basin.

Conclusion

Ultimately, the source verification process already used in individual basin studies to evaluate the accuracy of sediment-fingerprinting apportionments was useful for determining how to supplement local source samples with those from other basins. This study shows that supplementing local source samples with those from basins with similar physiography has the potential to both improve fingerprinting accuracy and decrease the cost of this type of study.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.jenvman.2023.117254","usgsCitation":"Williamson, T.N., Fitzpatrick, F., and Kreiling, R.M., 2023, Building a library of source samples for sediment fingerprinting – Potential and proof of concept: Journal of Environmental Management, v. 333, 117254, 17 p., https://doi.org/10.1016/j.jenvman.2023.117254.","productDescription":"117254, 17 p.","ipdsId":"IP-144631","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":444434,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jenvman.2023.117254","text":"Publisher Index Page"},{"id":413394,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"333","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Williamson, Tanja N. 0000-0002-7639-8495 tnwillia@usgs.gov","orcid":"https://orcid.org/0000-0002-7639-8495","contributorId":198329,"corporation":false,"usgs":true,"family":"Williamson","given":"Tanja","email":"tnwillia@usgs.gov","middleInitial":"N.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":864979,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fitzpatrick, Faith A. 0000-0002-9748-7075","orcid":"https://orcid.org/0000-0002-9748-7075","contributorId":209444,"corporation":false,"usgs":true,"family":"Fitzpatrick","given":"Faith A.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":864980,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kreiling, Rebecca M. 0000-0002-9295-4156","orcid":"https://orcid.org/0000-0002-9295-4156","contributorId":202193,"corporation":false,"usgs":true,"family":"Kreiling","given":"Rebecca","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":864981,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70240766,"text":"70240766 - 2023 - Waterfowl recently infected with low pathogenic avian influenza exhibit reduced local movement and delayed migration","interactions":[],"lastModifiedDate":"2023-02-22T12:39:50.288986","indexId":"70240766","displayToPublicDate":"2023-02-17T06:35:28","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Waterfowl recently infected with low pathogenic avian influenza exhibit reduced local movement and delayed migration","docAbstract":"

Understanding relationships between infection and wildlife movement patterns is important for predicting pathogen spread, especially for multispecies pathogens and those that can spread to humans and domestic animals, such as avian influenza viruses (AIVs). Although infection with low pathogenic AIVs is generally considered asymptomatic in wild birds, prior work has shown that influenza-infected birds occasionally delay migration and/or reduce local movements relative to their uninfected counterparts. However, most observational research to date has focused on a few species in northern Europe; given that influenza viruses are widespread globally and outbreaks of highly pathogenic strains are increasingly common, it is important to explore influenza–movement relationships across more species and regions. Here, we used telemetry data to investigate relationships between influenza infection and movement behavior in 165 individuals from four species of North American waterfowl that overwinter in California, USA. We studied both large-scale migratory and local overwintering movements and found that relationships between influenza infection and movement patterns varied among species. Northern pintails (Anas acuta) with antibodies to avian influenza, indicating prior infection, made migratory stopovers that averaged 12 days longer than those with no influenza antibodies. In contrast, greater white-fronted geese (Anser albifrons) with antibodies to avian influenza made migratory stopovers that averaged 15 days shorter than those with no antibodies. Canvasbacks (Aythya valisineria) that were actively infected with influenza upon capture in the winter delayed spring migration by an average of 28 days relative to birds that were uninfected at the time of capture. At the local scale, northern pintails and canvasbacks that were actively infected with influenza used areas that were 7.6 and 4.9 times smaller than those of uninfected ducks, respectively, during the period of presumed active influenza infection. We found no evidence for an influence of active influenza infection on local movements of mallards (Anas platyrhynchos). These results suggest that avian influenza can influence waterfowl movements and illustrate that the relationships between avian influenza infection and wild bird movements are context- and species-dependent. More generally, understanding and predicting the spread of multihost pathogens requires studying multiple taxa across space and time.

","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.4432","usgsCitation":"Teitelbaum, C.S., Casazza, M.L., McDuie, F., De La Cruz, S.E., Overton, C.T., Hall, L.A., Matchett, E., Ackerman, J.T., Sullivan, J.D., Ramey, A.M., and Prosser, D., 2023, Waterfowl recently infected with low pathogenic avian influenza exhibit reduced local movement and delayed migration: Ecosphere, v. 14, no. 2, e4432, 16 p., https://doi.org/10.1002/ecs2.4432.","productDescription":"e4432, 16 p.","ipdsId":"IP-144212","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":444436,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.4432","text":"Publisher Index Page"},{"id":435446,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P97NEY5Y","text":"USGS data release","linkHelpText":"Data describing infection status and movement ecology of North American waterfowl"},{"id":413273,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","issue":"2","noUsgsAuthors":false,"publicationDate":"2023-02-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Teitelbaum, Claire S. 0000-0001-5646-3184","orcid":"https://orcid.org/0000-0001-5646-3184","contributorId":255382,"corporation":false,"usgs":false,"family":"Teitelbaum","given":"Claire","email":"","middleInitial":"S.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":864764,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Casazza, Michael L. 0000-0002-5636-735X mike_casazza@usgs.gov","orcid":"https://orcid.org/0000-0002-5636-735X","contributorId":2091,"corporation":false,"usgs":true,"family":"Casazza","given":"Michael","email":"mike_casazza@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":864765,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McDuie, Fiona 0000-0002-1948-5613","orcid":"https://orcid.org/0000-0002-1948-5613","contributorId":222936,"corporation":false,"usgs":true,"family":"McDuie","given":"Fiona","email":"","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":864766,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"De La Cruz, Susan E.W. 0000-0001-6315-0864","orcid":"https://orcid.org/0000-0001-6315-0864","contributorId":202774,"corporation":false,"usgs":true,"family":"De La Cruz","given":"Susan","email":"","middleInitial":"E.W.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":864767,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Overton, Cory T. 0000-0002-5060-7447 coverton@usgs.gov","orcid":"https://orcid.org/0000-0002-5060-7447","contributorId":3262,"corporation":false,"usgs":true,"family":"Overton","given":"Cory","email":"coverton@usgs.gov","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":864768,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hall, Laurie Anne 0000-0001-5822-649X","orcid":"https://orcid.org/0000-0001-5822-649X","contributorId":243313,"corporation":false,"usgs":true,"family":"Hall","given":"Laurie","email":"","middleInitial":"Anne","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":864769,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Matchett, Elliott 0000-0001-5095-2884 ematchett@usgs.gov","orcid":"https://orcid.org/0000-0001-5095-2884","contributorId":5541,"corporation":false,"usgs":true,"family":"Matchett","given":"Elliott","email":"ematchett@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":864770,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ackerman, Joshua T. 0000-0002-3074-8322","orcid":"https://orcid.org/0000-0002-3074-8322","contributorId":202848,"corporation":false,"usgs":true,"family":"Ackerman","given":"Joshua","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":864771,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Sullivan, Jeffery D. 0000-0002-9242-2432","orcid":"https://orcid.org/0000-0002-9242-2432","contributorId":265822,"corporation":false,"usgs":true,"family":"Sullivan","given":"Jeffery","email":"","middleInitial":"D.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":864772,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Ramey, Andrew M. 0000-0002-3601-8400 aramey@usgs.gov","orcid":"https://orcid.org/0000-0002-3601-8400","contributorId":1872,"corporation":false,"usgs":true,"family":"Ramey","given":"Andrew","email":"aramey@usgs.gov","middleInitial":"M.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":864773,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Prosser, Diann 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discriminating between natural and stocked recruitment for inland fisheries","docAbstract":"

Hatchery programmes are frequently used to supplement inland fisheries, yet achieving successful management outcomes often requires information on stocked versus naturally reproduced fish abundance. Parentage-based tagging – genetically assigning offspring to their parents – has potential to be an effective approach for distinguishing stocked and naturally reproduced fish. However, several challenges may limit its application to inland fisheries, including genetic relatedness among populations that can affect identification accuracy and high costs of genotyping large broodstocks. Here, we demonstrate the efficacy of parentage-based tagging based on broodmothers in the Lake Ontario Chinook Salmon fishery, which uses thousands of broodparents and has potential for substantial relatedness between stocked and naturally reproduced fish. Restricting parent sampling to broodmothers reduced costs by two-thirds, was logistically pragmatic, and achieved >95% accuracy in distinguishing stocked from naturally reproduced salmon. Combined, these results highlight the potential wide applicability of parentage-based tagging for assessing stocking programmes in inland waters.

","language":"English","publisher":"Wiley","doi":"10.1111/fme.12614","usgsCitation":"Fitzpatrick, K., Overgaard Therkildsen, N., Marcy-Quay, B., Borchardt-Wier, H., and Sethi, S., 2023, Parentage-based tagging using mothers balances accuracy and cost for discriminating between natural and stocked recruitment for inland fisheries: Fisheries Management and Ecology, v. 30, no. 6, p. 592-602, https://doi.org/10.1111/fme.12614.","productDescription":"11 p.","startPage":"592","endPage":"602","ipdsId":"IP-143265","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":498011,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/fme.12614","text":"Publisher Index Page"},{"id":481546,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"New York, Ontario","otherGeospatial":"Credit River, Ganaraska River, Salmon River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -78.35780470076405,\n 44.00588711448293\n ],\n [\n -78.35780470076405,\n 43.938390937821964\n ],\n [\n -78.27054744204773,\n 43.938390937821964\n ],\n [\n -78.27054744204773,\n 44.00588711448293\n ],\n [\n -78.35780470076405,\n 44.00588711448293\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -79.64793103775978,\n 43.56371639011229\n ],\n [\n -79.64793103775978,\n 43.53520511958473\n ],\n [\n -79.57763884041233,\n 43.53520511958473\n ],\n [\n -79.57763884041233,\n 43.56371639011229\n ],\n [\n -79.64793103775978,\n 43.56371639011229\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -76.12853567648116,\n 43.58938347630331\n ],\n [\n -76.12853567648116,\n 43.42078701813762\n ],\n [\n -75.84858907895543,\n 43.42078701813762\n ],\n [\n -75.84858907895543,\n 43.58938347630331\n ],\n [\n -76.12853567648116,\n 43.58938347630331\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"30","issue":"6","noUsgsAuthors":false,"publicationDate":"2023-02-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Fitzpatrick, Kimberly B.","contributorId":350351,"corporation":false,"usgs":false,"family":"Fitzpatrick","given":"Kimberly B.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":925810,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Overgaard Therkildsen, Nina","contributorId":350352,"corporation":false,"usgs":false,"family":"Overgaard Therkildsen","given":"Nina","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":925811,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Marcy-Quay, Benjamin","contributorId":350353,"corporation":false,"usgs":false,"family":"Marcy-Quay","given":"Benjamin","affiliations":[{"id":13253,"text":"University of Vermont","active":true,"usgs":false}],"preferred":false,"id":925812,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Borchardt-Wier, Harmony B.","contributorId":350354,"corporation":false,"usgs":false,"family":"Borchardt-Wier","given":"Harmony B.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":925813,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sethi, Suresh 0000-0002-0053-1827 ssethi@usgs.gov","orcid":"https://orcid.org/0000-0002-0053-1827","contributorId":191424,"corporation":false,"usgs":true,"family":"Sethi","given":"Suresh","email":"ssethi@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":925814,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70240742,"text":"70240742 - 2023 - Metagenomic mapping of cyanobacteria and potential cyanotoxin producing taxa in large rivers of the United States","interactions":[],"lastModifiedDate":"2023-02-17T13:20:13.774667","indexId":"70240742","displayToPublicDate":"2023-02-16T07:18:05","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":"Metagenomic mapping of cyanobacteria and potential cyanotoxin producing taxa in large rivers of the United States","docAbstract":"

Cyanobacteria and cyanotoxin producing cyanobacterial blooms are a trending focus of current research. Many studies focus on bloom events in lentic environments such as lakes or ponds. Comparatively few studies have explored lotic environments and fewer still have examined the cyanobacterial communities and potential cyanotoxin producers during ambient, non-bloom conditions. Here we used a metagenomics-based approach to profile non-bloom microbial communities and cyanobacteria in 12 major U.S. rivers at multiple time points during the summer months of 2019. Our data show that U.S. rivers possess microbial communities that are taxonomically rich, yet largely consistent across geographic location and time. Within these communities, cyanobacteria often comprise significant portions and frequently include multiple species with known cyanotoxin producing strains. We further characterized these potential cyanotoxin producing taxa by deep sequencing amplicons of the microcystin E (mcyE) gene. We found that rivers containing the highest levels of potential cyanotoxin producing cyanobacteria consistently possess taxa with the genetic potential for cyanotoxin production and that, among these taxa, the predominant genus of origin for the mcyE gene is Microcystis. Combined, these data provide a unique perspective on cyanobacteria and potential cyanotoxin producing taxa that exist in large rivers across the U.S. and can be used to better understand the ambient conditions that may precede bloom events in lotic freshwater ecosystems.

","language":"English","publisher":"Nature","doi":"10.1038/s41598-023-29037-6","usgsCitation":"Linz, D., Sienkiewicz, N., Struewing, I., Stelzer, E., Graham, J.L., and Lu, J., 2023, Metagenomic mapping of cyanobacteria and potential cyanotoxin producing taxa in large rivers of the United States: Scientific Reports, v. 13, 2806, 13 p., https://doi.org/10.1038/s41598-023-29037-6.","productDescription":"2806, 13 p.","ipdsId":"IP-137972","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":444442,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-023-29037-6","text":"Publisher Index Page"},{"id":413169,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n 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N.","contributorId":302527,"corporation":false,"usgs":false,"family":"Sienkiewicz","given":"N.","affiliations":[{"id":65484,"text":"USEPA Office of Research and Development","active":true,"usgs":false}],"preferred":false,"id":864602,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Struewing, I.","contributorId":302528,"corporation":false,"usgs":false,"family":"Struewing","given":"I.","email":"","affiliations":[{"id":65484,"text":"USEPA Office of Research and Development","active":true,"usgs":false}],"preferred":false,"id":864603,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stelzer, Erin A. 0000-0001-7645-7603","orcid":"https://orcid.org/0000-0001-7645-7603","contributorId":220549,"corporation":false,"usgs":true,"family":"Stelzer","given":"Erin A.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":864604,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Graham, Jennifer L. 0000-0002-6420-9335 jlgraham@usgs.gov","orcid":"https://orcid.org/0000-0002-6420-9335","contributorId":1769,"corporation":false,"usgs":true,"family":"Graham","given":"Jennifer","email":"jlgraham@usgs.gov","middleInitial":"L.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":864605,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lu, Jingrang","contributorId":288917,"corporation":false,"usgs":false,"family":"Lu","given":"Jingrang","email":"","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":864606,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70240830,"text":"70240830 - 2023 - A framework for prioritizing contaminants in retrospective ecological assessments: Application in the Milwaukee Estuary (Milwaukee, WI)","interactions":[],"lastModifiedDate":"2023-09-06T16:05:41.914019","indexId":"70240830","displayToPublicDate":"2023-02-16T07:11:05","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":13437,"text":"Integrated Environmental Assessment and Management (IEAM)","active":true,"publicationSubtype":{"id":10}},"title":"A framework for prioritizing contaminants in retrospective ecological assessments: Application in the Milwaukee Estuary (Milwaukee, WI)","docAbstract":"

Watersheds are subjected to diverse anthropogenic inputs, exposing aquatic biota to a wide range of chemicals. Detection of multiple, different chemicals can challenge natural resource managers who often have to determine where to allocate potentially limited resources. Here, we describe a weight-of-evidence framework for retrospectively prioritizing aquatic contaminants. To demonstrate framework utility, we used data from 96-h caged fish studies to prioritize chemicals detected in the Milwaukee Estuary (WI, USA; 2017–2018). Across study years, 77/178 targeted chemicals were detected. Chemicals were assigned prioritization scores based on spatial and temporal detection frequency, environmental distribution, environmental fate, ecotoxicological potential, and effect prediction. Chemicals were sorted into priority bins based on the intersection of prioritization score and data availability. Data-limited chemicals represented those that did not have sufficient data to adequately evaluate ecotoxicological potential or environmental fate. Seven compounds (fluoranthene, benzo[a]pyrene, pyrene, atrazine, metolachlor, phenanthrene, and DEET) were identified as high or medium priority and data sufficient and flagged as candidates for further effects-based monitoring studies. Twenty-one compounds were identified as high or medium priority and data limited and flagged as candidates for further ecotoxicological research. Fifteen chemicals were flagged as the lowest priority in the watershed. One of these chemicals (2-methylnaphthalene) displayed no data limitations and was flagged as a definitively low-priority chemical. The remaining chemicals displayed some data limitations and were considered lower-priority compounds (contingent on further ecotoxicological and environmental fate assessments). The remaining 34 compounds were flagged as low or medium priority. Altogether, this prioritization provided a screening-level (non-definitive) assessment that could be used to focus further resource management and risk assessment activities in the Milwaukee Estuary. Furthermore, by providing detailed methodology and a practical example with real experimental data, we demonstrated that the proposed framework represents a transparent and adaptable approach for prioritizing contaminants in freshwater environments. Integr Environ Assess Manag 2023;00:1–21. © 2022 SETAC

","language":"English","publisher":"Wiley","doi":"10.1002/ieam.4725","usgsCitation":"Maloney, E.M., Villeneuve, D.L., Blackewell, B.R., Vitense, K., Corsi, S., Pronschinske, M.A., Jensen, K., and Ankley, G.T., 2023, A framework for prioritizing contaminants in retrospective ecological assessments: Application in the Milwaukee Estuary (Milwaukee, WI): Integrated Environmental Assessment and Management (IEAM), v. 19, no. 5, p. 1276-1296, https://doi.org/10.1002/ieam.4725.","productDescription":"21 p.","startPage":"1276","endPage":"1296","ipdsId":"IP-145582","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":444443,"rank":2,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/10601791","text":"External Repository"},{"id":413399,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","city":"Milwaukee","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -88.24783012360321,\n 43.25798227617699\n ],\n [\n -88.24783012360321,\n 42.86483538384232\n ],\n [\n -87.80856354645815,\n 42.86483538384232\n ],\n [\n -87.80856354645815,\n 43.25798227617699\n ],\n [\n -88.24783012360321,\n 43.25798227617699\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"19","issue":"5","noUsgsAuthors":false,"publicationDate":"2022-12-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Maloney, Erin M","contributorId":302657,"corporation":false,"usgs":false,"family":"Maloney","given":"Erin","email":"","middleInitial":"M","affiliations":[{"id":65526,"text":"SpecPro Professional Services","active":true,"usgs":false}],"preferred":false,"id":864982,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Villeneuve, Daniel L. 0000-0003-2801-0203","orcid":"https://orcid.org/0000-0003-2801-0203","contributorId":197436,"corporation":false,"usgs":false,"family":"Villeneuve","given":"Daniel","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":864983,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Blackewell, Brett R","contributorId":302658,"corporation":false,"usgs":false,"family":"Blackewell","given":"Brett","email":"","middleInitial":"R","affiliations":[{"id":12772,"text":"USEPA","active":true,"usgs":false}],"preferred":false,"id":864984,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vitense, Kelsey","contributorId":195720,"corporation":false,"usgs":false,"family":"Vitense","given":"Kelsey","email":"","affiliations":[],"preferred":false,"id":864985,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Corsi, Steven R. 0000-0003-0583-5536 srcorsi@usgs.gov","orcid":"https://orcid.org/0000-0003-0583-5536","contributorId":172002,"corporation":false,"usgs":true,"family":"Corsi","given":"Steven R.","email":"srcorsi@usgs.gov","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":864986,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pronschinske, Matthew A. 0000-0001-9787-4545 mpronschinske@usgs.gov","orcid":"https://orcid.org/0000-0001-9787-4545","contributorId":295961,"corporation":false,"usgs":true,"family":"Pronschinske","given":"Matthew","email":"mpronschinske@usgs.gov","middleInitial":"A.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":864987,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jensen, Kathleen","contributorId":302659,"corporation":false,"usgs":false,"family":"Jensen","given":"Kathleen","affiliations":[{"id":12772,"text":"USEPA","active":true,"usgs":false}],"preferred":false,"id":864988,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ankley, Gerald T.","contributorId":200659,"corporation":false,"usgs":false,"family":"Ankley","given":"Gerald","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":864989,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70242152,"text":"70242152 - 2023 - Groundwater recharge in northern New England: Meteorological drivers and relations with low streamflow","interactions":[],"lastModifiedDate":"2023-04-10T11:37:58.859573","indexId":"70242152","displayToPublicDate":"2023-02-16T06:33:01","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Groundwater recharge in northern New England: Meteorological drivers and relations with low streamflow","docAbstract":"

Meteorological drivers of groundwater recharge for spring (February–June), fall (October–January), and recharge-year (October–June) recharge seasons were evaluated for northern New England and upstate New York from 1989 to 2018. Monthly groundwater recharge was computed at 21 observation wells by subtracting the water levels at the end of each month from the level of the previous month; only positive monthly values were used to compute seasonal recharge. Precipitation, temperature, sea-level pressure, 500-mb geopotential heights, and various teleconnection indices were tested as explanatory variables for the interannual variability of recharge using random forest machine learning models. Precipitation within recharge seasons was positively correlated with groundwater recharge for most wells in all seasons. In general, whilst groundwater recharge in the study area was generally highest during the months of March and April, October precipitation was an important month for explaining the interannual groundwater recharge variability. This is likely because the variability in recharge in October may be high or low for given years. Sea-level pressure and 500-mb heights were typically inversely correlated with groundwater recharge during the recharge-year and fall recharge seasons, as higher sea-level pressure and heights are usually associated with clearer skies and less precipitation. The North Atlantic Oscillation, Pacific-North American pattern, and Pacific Decadal Oscillation teleconnections affected groundwater recharge differently by well and season. The influence of groundwater recharge on minimum daily streamflows during the subsequent summer/fall was also analysed. Summer precipitation was the most important explanatory variable for study streams whilst groundwater recharge and summer air temperature were significant variables for a few streams.

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\"}}]}","volume":"37","issue":"3","noUsgsAuthors":false,"publicationDate":"2023-03-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Crossett, Caitlin","contributorId":304049,"corporation":false,"usgs":false,"family":"Crossett","given":"Caitlin","email":"","affiliations":[{"id":65957,"text":"Department of Geoscience, Hobart and William Smith Colleges, Geneva, NY 14456","active":true,"usgs":false}],"preferred":false,"id":869030,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hodgkins, Glenn A. 0000-0002-4916-5565 gahodgki@usgs.gov","orcid":"https://orcid.org/0000-0002-4916-5565","contributorId":2020,"corporation":false,"usgs":true,"family":"Hodgkins","given":"Glenn","email":"gahodgki@usgs.gov","middleInitial":"A.","affiliations":[{"id":371,"text":"Maine Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":869031,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Menk, Hadley","contributorId":304050,"corporation":false,"usgs":false,"family":"Menk","given":"Hadley","email":"","affiliations":[{"id":65958,"text":"Department of Geography & Sustainable Development, University of St Andrews, St Andrews, Scotland KY16 9AL","active":true,"usgs":false}],"preferred":false,"id":869032,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dupigny-Giroux, Lesley-Ann L. 0000-0002-1992-5607","orcid":"https://orcid.org/0000-0002-1992-5607","contributorId":212158,"corporation":false,"usgs":false,"family":"Dupigny-Giroux","given":"Lesley-Ann","email":"","middleInitial":"L.","affiliations":[{"id":13253,"text":"University of Vermont","active":true,"usgs":false}],"preferred":false,"id":869033,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dudley, Robert W. 0000-0002-0934-0568","orcid":"https://orcid.org/0000-0002-0934-0568","contributorId":220211,"corporation":false,"usgs":true,"family":"Dudley","given":"Robert W.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":869034,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lemcke-Stampone, Mary D. 0000-0001-5445-0267","orcid":"https://orcid.org/0000-0001-5445-0267","contributorId":212160,"corporation":false,"usgs":false,"family":"Lemcke-Stampone","given":"Mary","email":"","middleInitial":"D.","affiliations":[{"id":12667,"text":"University of New Hampshire","active":true,"usgs":false}],"preferred":false,"id":869035,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hammond, John C. 0000-0002-4935-0736","orcid":"https://orcid.org/0000-0002-4935-0736","contributorId":223108,"corporation":false,"usgs":true,"family":"Hammond","given":"John C.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":869036,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70240682,"text":"sir20225051 - 2023 - Generalized additive model estimation of no-flow fractions and L-moments to support flow-duration curve quantile estimation using selected probability distributions for bay and estuary restoration in the Gulf States","interactions":[],"lastModifiedDate":"2026-02-23T19:14:56.874467","indexId":"sir20225051","displayToPublicDate":"2023-02-15T12:00:00","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":"2022-5051","displayTitle":"Generalized Additive Model Estimation of No-Flow Fractions and L-Moments to Support Flow-Duration Curve Quantile Estimation Using Selected Probability Distributions for Bay and Estuary Restoration in the Gulf States","title":"Generalized additive model estimation of no-flow fractions and L-moments to support flow-duration curve quantile estimation using selected probability distributions for bay and estuary restoration in the Gulf States","docAbstract":"

Censored and uncensored generalized additive models (GAMs) were developed using streamflow data from 941 U.S. Geological Survey streamflow-gaging stations (streamgages) to predict decadal statistics of daily streamflow for streams draining to the Gulf of Mexico. The modeled decadal statistics comprise no-flow fractions and L-moments of logarithms of nonzero streamflow for six decades (1950–2009). These statistics represent metrics of decadal flow-duration curves (dFDCs) derived from about 10 million daily mean streamflows. The L-moments comprise the mean, coefficient of L-variation, and the third through fifth L-moment ratios. The GAMs were fit to the statistics from 941 streamgages and 2,750 streamgage-decades by using watershed properties such as basin area and slope, decadal precipitation and temperature, and decadal values of flood storage and urban development percentages. The GAMs then estimated decadal statistics for 9,220 prediction locations (stream reaches) coincident with outlets of level-12 hydrologic unit codes. Both entire dataset (whole model) and leave-one-watershed-out model results are reported. No-flow fractions are censored data, and Tobit extensions to GAMs were used to model ephemeral streamflow conditions. Conversely, uncensored GAMs were used for estimation of the L-moments. The GAMs are shown, by coverage probabilities, to construct reliable 95-percent prediction limits. An example shows how no-flow fractions and L-moments may be used to approximate dFDCs by using selected probability distributions (mathematical formulas) including the asymmetric exponential power, generalized normal, and kappa distributions.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225051","issn":"2328-0328 (online)","collaboration":"Prepared in cooperation with the Gulf Coast Ecosystem Restoration Council","usgsCitation":"Crowley-Ornelas, E.R., Asquith, W.H., and Worland, S.C., 2023, Generalized additive model estimation of no-flow fractions and L-moments to support flow-duration curve quantile estimation using selected probability distributions for bay and estuary restoration in the Gulf States: U.S. Geological Survey Scientific Investigations Report 2022–5051, 35 p., https://doi.org/​10.3133/​sir20225051.","productDescription":"Report: viii, 35 p.; 3 Data Releases; Dataset; Software Release","numberOfPages":"48","onlineOnly":"Y","ipdsId":"IP-111999","costCenters":[{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower 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Director, Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
640 Grassmere Park, Suite 100
Nashville, TN 37211

Contact Pubs Warehouse

","tableOfContents":"","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2023-02-15","noUsgsAuthors":false,"publicationDate":"2023-02-15","publicationStatus":"PW","contributors":{"authors":[{"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":864286,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Asquith, William H. 0000-0002-7400-1861 wasquith@usgs.gov","orcid":"https://orcid.org/0000-0002-7400-1861","contributorId":1007,"corporation":false,"usgs":true,"family":"Asquith","given":"William","email":"wasquith@usgs.gov","middleInitial":"H.","affiliations":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":864287,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Worland, Scott C. 0000-0001-6384-2457 scworland@usgs.gov","orcid":"https://orcid.org/0000-0001-6384-2457","contributorId":5802,"corporation":false,"usgs":true,"family":"Worland","given":"Scott","email":"scworland@usgs.gov","middleInitial":"C.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true}],"preferred":true,"id":864288,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70241542,"text":"70241542 - 2023 - High-frequency time series comparison of Sentinel-1 and Sentinel-2 for open and vegetated water across the United States (2017-2021)","interactions":[],"lastModifiedDate":"2023-03-23T13:55:48.119874","indexId":"70241542","displayToPublicDate":"2023-02-15T08:41:12","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"High-frequency time series comparison of Sentinel-1 and Sentinel-2 for open and vegetated water across the United States (2017-2021)","docAbstract":"

Frequent observations of surface water at fine spatial scales will provide critical data to support the management of aquatic habitat, flood risk and water quality. Sentinel-1 and Sentinel-2 satellites can provide such observations, but algorithms are still needed that perform well across diverse climate and vegetation conditions. We developed surface inundation algorithms for Sentinel-1 and Sentinel-2, respectively, at 12 sites across the conterminous United States (CONUS), covering a total of >536,000 km2 and representing diverse hydrologic and vegetation landscapes. Each scene in the 5-year (2017–2021) time series was classified into open water, vegetated water, and non-water at 20 m resolution using variables from Sentinel-1 and Sentinel-2, as well as variables derived from topographic and weather datasets. The Sentinel-1 algorithm was developed distinct from the Sentinel-2 model to explore if and where the two time series could potentially be integrated into a single high-frequency time series. Within each model, open water and vegetated water (vegetated palustrine, lacustrine, and riverine wetlands) classes were mapped. The models were validated using imagery from WorldView and PlanetScope. Classification accuracy for open water was high across the 5-year period, with an omission and commission error of only 3.1% and 0.9% for the Sentinel-1 algorithm and 3.1% and 0.5% for the Sentinel-2 algorithm, respectively. Vegetated water accuracy was lower, as expected given that the class represents mixed pixels. The Sentinel-2 algorithm showed higher accuracy (10.7% omission and 7.9% commission error) relative to the Sentinel-1 algorithm (28.4% omission and 16.0% commission error). Patterns over time in the proportion of area mapped as open or vegetated water by the Sentinel-1 and Sentinel-2 algorithms were charted and correlated for a subset of all 12 sites. Our results showed that the Sentinel-1 and Sentinel-2 algorithm open water time series can be integrated at all 12 sites to improve the temporal resolution, but sensor-specific differences, such as sensitivity to vegetation structure versus pixel color, complicate the data integration for mixed-pixel, vegetated water. The methods developed here provide inundation at 5-day (Sentinel-2 algorithm) and 12-day (Sentinel-1 algorithm) time steps to improve our understanding of the short- and long-term response of surface water to climate and land use drivers in different ecoregions.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2023.113498","usgsCitation":"Vanderhoof, M.K., Alexander, L., Christensen, J.R., Solvik, K., Nieuwlandt, P.J., and Prentiss, M.A., 2023, High-frequency time series comparison of Sentinel-1 and Sentinel-2 for open and vegetated water across the United States (2017-2021): Remote Sensing of Environment, v. 288, 113498, 28 p., https://doi.org/10.1016/j.rse.2023.113498.","productDescription":"113498, 28 p.","ipdsId":"IP-142670","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":444461,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rse.2023.113498","text":"Publisher Index Page"},{"id":435452,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9RSXQ2U","text":"USGS data release","linkHelpText":"Sentinel-1 and Sentinel-2 based frequency of open and vegetated water across 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Drivers of phytoplankton and zooplankton dynamics vary spatially and temporally in estuaries due to variation in hydrodynamic exchange and residence time, complicating efforts to understand controls on food web productivity. We conducted approximately monthly (2012–2019; n = 74) longitudinal sampling at 10 fixed stations along a freshwater tidal terminal channel in the San Francisco Estuary, California, characterized by seaward to landward gradients in water residence time, turbidity, nutrient concentrations, and plankton community composition. We used multivariate autoregressive state space (MARSS) models to quantify environmental (abiotic) and biotic controls on phytoplankton and mesozooplankton biomass. The importance of specific abiotic drivers (e.g., water temperature, turbidity, nutrients) and trophic interactions differed significantly among hydrodynamic exchange zones with different mean residence times. Abiotic drivers explained more variation in phytoplankton and zooplankton dynamics than a model including only trophic interactions, but individual phytoplankton–zooplankton interactions explained more variation than individual abiotic drivers. Interactions between zooplankton and phytoplankton were strongest in landward reaches with the longest residence times and the highest zooplankton biomass. Interactions between cryptophytes and both copepods and cladocerans were stronger than interactions between bacillariophytes (diatoms) and zooplankton taxa, despite contributing less biovolume in all but the most landward reaches. Our results demonstrate that trophic interactions and their relative strengths vary in a hydrodynamic context, contributing to food web heterogeneity within estuaries at spatial scales smaller than the freshwater to marine transition.

","language":"English","publisher":"Wiley","doi":"10.1002/ecm.1567","usgsCitation":"Smits, A.P., Loken, L.C., Van Nieuwenhuyse, E.E., Young, M.J., Stumpner, P., Kammel, L., Burau, J.R., Dahlgren, R.A., Brown, T., Hennessey, A., and Sadro, S., 2023, Hydrodynamics structure plankton communities and interactions in a freshwater tidal estuary: Ecological Monographs, v. 93, no. 2, e1567, 23 p., https://doi.org/10.1002/ecm.1567.","productDescription":"e1567, 23 p.","ipdsId":"IP-136357","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":444467,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecm.1567","text":"Publisher Index Page"},{"id":416649,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -123.71468096588754,\n 39.05037715727204\n ],\n [\n -123.71468096588754,\n 37.12310666336553\n ],\n [\n -120.53001572533375,\n 37.12310666336553\n ],\n [\n -120.53001572533375,\n 39.05037715727204\n ],\n [\n -123.71468096588754,\n 39.05037715727204\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"93","issue":"2","noUsgsAuthors":false,"publicationDate":"2023-03-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Smits, Adrianne P 0000-0001-9967-5419","orcid":"https://orcid.org/0000-0001-9967-5419","contributorId":217759,"corporation":false,"usgs":false,"family":"Smits","given":"Adrianne","email":"","middleInitial":"P","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":871385,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Loken, Luke C. 0000-0003-3194-1498 lloken@usgs.gov","orcid":"https://orcid.org/0000-0003-3194-1498","contributorId":195600,"corporation":false,"usgs":true,"family":"Loken","given":"Luke","email":"lloken@usgs.gov","middleInitial":"C.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":871386,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Van Nieuwenhuyse, Erwin E 0000-0002-9032-2681","orcid":"https://orcid.org/0000-0002-9032-2681","contributorId":269423,"corporation":false,"usgs":false,"family":"Van Nieuwenhuyse","given":"Erwin","email":"","middleInitial":"E","affiliations":[{"id":6736,"text":"Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":871387,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Young, Matthew J. 0000-0001-9306-6866 mjyoung@usgs.gov","orcid":"https://orcid.org/0000-0001-9306-6866","contributorId":206255,"corporation":false,"usgs":true,"family":"Young","given":"Matthew","email":"mjyoung@usgs.gov","middleInitial":"J.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":871388,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stumpner, Paul 0000-0002-0933-7895 pstump@usgs.gov","orcid":"https://orcid.org/0000-0002-0933-7895","contributorId":5667,"corporation":false,"usgs":true,"family":"Stumpner","given":"Paul","email":"pstump@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":871389,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kammel, Leah 0000-0003-4613-0858","orcid":"https://orcid.org/0000-0003-4613-0858","contributorId":211840,"corporation":false,"usgs":true,"family":"Kammel","given":"Leah","email":"","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":871390,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Burau, Jon R. 0000-0002-5196-5035 jrburau@usgs.gov","orcid":"https://orcid.org/0000-0002-5196-5035","contributorId":1500,"corporation":false,"usgs":true,"family":"Burau","given":"Jon","email":"jrburau@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":871391,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Dahlgren, Randy A 0000-0002-8961-875X","orcid":"https://orcid.org/0000-0002-8961-875X","contributorId":269424,"corporation":false,"usgs":false,"family":"Dahlgren","given":"Randy","email":"","middleInitial":"A","affiliations":[{"id":7082,"text":"University of California - Davis","active":true,"usgs":false}],"preferred":false,"id":871392,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Brown, Tiffany","contributorId":304695,"corporation":false,"usgs":false,"family":"Brown","given":"Tiffany","email":"","affiliations":[{"id":37342,"text":"California Department of Water Resources","active":true,"usgs":false}],"preferred":false,"id":871393,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Hennessey, April","contributorId":304696,"corporation":false,"usgs":false,"family":"Hennessey","given":"April","email":"","affiliations":[{"id":6952,"text":"California Department of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":871394,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Sadro, Steven","contributorId":269824,"corporation":false,"usgs":false,"family":"Sadro","given":"Steven","affiliations":[{"id":16975,"text":"University of California Davis","active":true,"usgs":false}],"preferred":false,"id":871395,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70240744,"text":"70240744 - 2023 - In-stream laser diffraction for measuring suspended sediment concentration and particle size distribution in rivers: Insights from field campaigns","interactions":[],"lastModifiedDate":"2023-02-17T12:39:33.140301","indexId":"70240744","displayToPublicDate":"2023-02-15T06:33:55","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":13431,"text":"Journal of Hydraulic Engineering (ASCE)","active":true,"publicationSubtype":{"id":10}},"title":"In-stream laser diffraction for measuring suspended sediment concentration and particle size distribution in rivers: Insights from field campaigns","docAbstract":"

This study evaluates the laser in situ scattering and transmissometry (LISST) instrument LISST-SL2, a laser diffraction instrument for suspended sediment sampling in rivers, with concurrent physical measurements of suspended sediment concentration (SSC) and particle size distribution (PSD) as well as velocity measurements by an acoustic Doppler current profiler (ADCP). We collected 136 LISST-SL2 samples along with 61 physical samples for SSC measurement, of which 24 physical samples included PSD measurement during 2018–2020 from 11 sites in Washington state and Virginia. An effective density is required to convert the measured volumetric SSC by the LISST-SL2 into a reported mass SSC, and by default the LISST-SL2 assumes a value of 2.65  g/mL. From our data set, we computed effective densities (mass SSC/volumetric SSC) that ranged from 0.5 to 5.4  g/mL, with a best-fit value of 2.05  g/mL. Additionally, the LISST-SL2 was not able to measure the finest sediment sizes in suspension, which affects the resulting PSD. Therefore, we propose some adjustments of the LISST-SL2 data with a supporting physical sample to account for these effective density and PSD issues. When doing so, we were able to reduce the root-mean square relative error (RMSRE) to 18% from 117% for SSC, and to 26% from 78% for PSD. LISST-SL2 velocities were generally higher than ADCP velocities with a 21% RMSRE. Our results and guidance will allow for more accurate sampling by the LISST-SL2, which has potential for studying spatial and temporal variation of suspended sediment characteristics in rivers.

","language":"English","publisher":"ASCE","doi":"10.1061/JHEND8.HYENG-13232","usgsCitation":"Ahammad, M., Czuba, J.A., and Curran, C.A., 2023, In-stream laser diffraction for measuring suspended sediment concentration and particle size distribution in rivers: Insights from field campaigns: Journal of Hydraulic Engineering (ASCE), v. 149, no. 2, 13 p., https://doi.org/10.1061/JHEND8.HYENG-13232.","productDescription":"13 p.","ipdsId":"IP-142580","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":444469,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1061/jhend8.hyeng-13232","text":"External Repository"},{"id":435454,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9SPVN51","text":"USGS data release","linkHelpText":"Field data for evaluation of the LISST-SL2, an in-stream particle-size analyzer, at selected rivers in Washington and Virginia, 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ccurran@usgs.gov","orcid":"https://orcid.org/0000-0001-8933-416X","contributorId":1650,"corporation":false,"usgs":true,"family":"Curran","given":"Christopher","email":"ccurran@usgs.gov","middleInitial":"A.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":864670,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70240654,"text":"ofr20231011 - 2023 - The value of scientific information — An overview","interactions":[],"lastModifiedDate":"2023-02-14T17:33:13.350202","indexId":"ofr20231011","displayToPublicDate":"2023-02-14T12:20:00","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-1011","displayTitle":"The Value of Scientific Information—An Overview","title":"The value of scientific information — An overview","docAbstract":"

Introduction

The U.S. Geological Survey (USGS) provides reliable science, data, information, and models (hereafter collectively referred to as “information”) to describe and understand the Earth. This information is used to minimize loss of life and property from natural disasters; manage water, biological, energy, and mineral resources; and enhance and protect quality of life. USGS science informs public and private decisions, operations, and risk management in all major United States economic sectors, as defined by the Bureau of Economic Analysis, and provides critical information for natural resource and natural hazard management and stewardship decisions. Understanding the value of scientific information supports applications of USGS science in land- and water-management decisions, and better informs the public about the return on investment of USGS programs. USGS economists, social scientists, and physical scientists are engaged in collaborative efforts to advance methods to estimate the value of information (VOI) produced by the USGS. These efforts involve collaborating with an international community to develop and refine estimation methods, establish best practices to determine VOI, develop a study repository, and conduct projects to assess the VOI of specific information products and their application. This report focuses on economic valuation conducted by USGS specifically, although the methodology has much broader applicability within the U.S. government, academia, and beyond. Noneconomic valuation techniques for assessing the VOI also exist but are not addressed in this report.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231011","usgsCitation":"Pindilli, E., Chiavacci, S., and Straub, C., 2023, The value of scientific information—An overview: U.S. Geological Survey Open-File Report 2023–1011, 5 p., https://doi.org/10.3133/ofr20231011.","productDescription":"iii, 5 p.","numberOfPages":"5","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-146764","costCenters":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"links":[{"id":412985,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231011/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2023-1011"},{"id":412987,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1011/ofr20231011.XML"},{"id":412950,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1011/ofr20231011.pdf","text":"Report","size":"1.73 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1011"},{"id":412949,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1011/coverthb.jpg"},{"id":412986,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1011/images/"}],"contact":"

Science and Decisions Center
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192

Contact Pubs Warehouse

","tableOfContents":"","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2023-02-14","noUsgsAuthors":false,"publicationDate":"2023-02-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Pindilli, Emily 0000-0002-5101-1266 epindilli@usgs.gov","orcid":"https://orcid.org/0000-0002-5101-1266","contributorId":140262,"corporation":false,"usgs":true,"family":"Pindilli","given":"Emily","email":"epindilli@usgs.gov","affiliations":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"preferred":true,"id":864139,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chiavacci, Scott J. 0000-0003-3579-8377","orcid":"https://orcid.org/0000-0003-3579-8377","contributorId":206161,"corporation":false,"usgs":true,"family":"Chiavacci","given":"Scott","email":"","middleInitial":"J.","affiliations":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"preferred":true,"id":864140,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Straub, Crista L. 0000-0001-7828-3328","orcid":"https://orcid.org/0000-0001-7828-3328","contributorId":219353,"corporation":false,"usgs":true,"family":"Straub","given":"Crista","email":"","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":864141,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70240750,"text":"70240750 - 2023 - Climate-driven mid- to late Holocene hydrologic evolution of arid wetlands documented by strontium, uranium, and oxygen isotopes from Lower Pahranagat Lake, southern Nevada, USA","interactions":[],"lastModifiedDate":"2023-05-25T15:40:53.773785","indexId":"70240750","displayToPublicDate":"2023-02-14T07:13:46","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3218,"text":"Quaternary Research","active":true,"publicationSubtype":{"id":10}},"title":"Climate-driven mid- to late Holocene hydrologic evolution of arid wetlands documented by strontium, uranium, and oxygen isotopes from Lower Pahranagat Lake, southern Nevada, USA","docAbstract":"

Lacustrine carbonates in a 12.4-m-long core from Lower Pahranagat Lake (LPAH), southern Nevada, indicate that radiogenic isotopes of Sr and U (87Sr/86Sr and 234U/238U) preserve evidence of past variations in water sources and evolving hydrologic conditions. Sr and U isotope compositions in LPAH carbonates fall within the range defined by the three primary groundwater sources in Pahranagat Valley and reflect variable mixtures of those sources since the mid-Holocene. Compositions in the oldest sample (5.78 ka) closely match modern compositions of modern discharge from nearby springs, indicating that LPAH water was derived almost exclusively from the local volcanic aquifer. By ca. 5.3–5.2 ka, LPAH water compositions shifted sharply towards isotopic compositions observed in groundwater from the regional carbonate aquifer, indicating a marked increase in surface flow from high-volume springs discharging from the carbonate aquifer to the north. Sediments deposited between 3.08–1.06 ka indicate reduced contributions from the regional aquifer. A comparison of uranium- and oxygen-isotope values in LPAH carbonates suggests that wetter climate conditions favor increased supply from deeper, regional carbonate aquifers compared to drier conditions when contributions from shallower, local volcanic aquifers were more important.

","language":"English","publisher":"Cambridge University Press","doi":"10.1017/qua.2022.72","usgsCitation":"Theissen, K.M., and Paces, J., 2023, Climate-driven mid- to late Holocene hydrologic evolution of arid wetlands documented by strontium, uranium, and oxygen isotopes from Lower Pahranagat Lake, southern Nevada, USA: Quaternary Research, v. 113, p. 52-68, https://doi.org/10.1017/qua.2022.72.","productDescription":"17 p.","startPage":"52","endPage":"68","ipdsId":"IP-141669","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":435455,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P96B7ABG","text":"USGS data release","linkHelpText":"Strontium and uranium isotopic compositions (87Sr/86Sr and 234U/238U) of mid- to late-Holocene lacustrine sediments from Lower Pahranagat Lake, Pahranagat National Wildlife Refuge, Lincoln County, Nevada"},{"id":413168,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","otherGeospatial":"Pahranagat Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -115.43523232398918,\n 37.66375328566663\n ],\n [\n -115.43523232398918,\n 37.05452897208191\n ],\n [\n -114.88855552446904,\n 37.05452897208191\n ],\n [\n -114.88855552446904,\n 37.66375328566663\n ],\n [\n -115.43523232398918,\n 37.66375328566663\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"113","noUsgsAuthors":false,"publicationDate":"2023-02-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Theissen, Kevin M. 0000-0002-6005-4380","orcid":"https://orcid.org/0000-0002-6005-4380","contributorId":298622,"corporation":false,"usgs":false,"family":"Theissen","given":"Kevin","email":"","middleInitial":"M.","affiliations":[{"id":6748,"text":"University of St. Thomas","active":true,"usgs":false}],"preferred":false,"id":864686,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Paces, James B. 0000-0002-9809-8493","orcid":"https://orcid.org/0000-0002-9809-8493","contributorId":118216,"corporation":false,"usgs":true,"family":"Paces","given":"James B.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":864687,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ]}