Malheur Lake is the largest lake in the endorheic Harney Basin in southeastern Oregon. Since the 1990s, Malheur Lake—which averages depths of about 1 meter—has been in a degraded, turbid state lacking submergent and emergent vegetation. The goals of this study were to identify the major sources of sediment and nutrients to Malheur Lake to determine the importance of managing nutrients for lake restoration. Discrete water samples were analyzed for nutrient (total phosphorus, total nitrogen, orthophosphate, nitrate+nitrite, and ammonia) and suspended-sediment concentrations, and additional parameters including chlorophyll-a and phytoplankton biomass were measured in lake samples. Lake area fluctuated from a minimum of 3,300 hectares (ha) to a maximum of 11,300 ha in water years 2019 and 2020. In water year 2019, inflow from the tributaries created a 1,400-hectare area in the lake with low turbidity that persisted for multiple months. Land-use practices and water diversions along the tributaries affected the hydrographs and nutrient and suspended-sediment concentrations reaching the lake. As lake area increased, storage of sediment-associated constituents in the water column increased in excess of external loads because of resuspension. In 2019, 69 percent of the increase in suspended-sediment storage in the water column was attributed to internal resuspension and 31 percent was from external loading. Sediment was deposited as lake area decreased, and water-column storage decreased even as positive external loading continued. The internal resuspension, deposition, and external loading of suspended sediment likely is decreasing topographic heterogeneity in the lake. Concentrations of total phosphorus and orthophosphate are substantially higher than in the 1980s, and the lake is eutrophic. Phytoplankton in the lake was light limited in 2019–20, and restoration actions that prioritize vegetation establishment would reduce bioavailable nutrients for phytoplankton while increasing light in the water column.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235098","usgsCitation":"Smith, C.D., and Wood, T.M., 2023, Implications of water, sediment, and nutrient budgets for the restoration of a shallow, turbid lake in semiarid southeastern Oregon: U.S. Geological Survey Scientific Investigations Report 2023–5098, 31 p., https://doi.org/10.3133/sir20235098.","productDescription":"Report: viii, 31 p.; 2 Data Releases","onlineOnly":"Y","ipdsId":"IP-136413","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":501065,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115406.htm","linkFileType":{"id":5,"text":"html"}},{"id":420867,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P92ZBWJ5","text":"USGS data release","description":"USGS data release","linkHelpText":"Phytoplankton data for Malheur Lake, Oregon, 2018–2020"},{"id":420864,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5098/Images"},{"id":420861,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5098/coverthb.jpg"},{"id":420862,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5098/sir20235098.pdf","text":"Report","size":"3.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5098"},{"id":420863,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235098/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2023-5098"},{"id":420865,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5098/sir20235098.XML"},{"id":420866,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P96VJVRQ","text":"USGS data release","description":"USGS data release","linkHelpText":"Stage-volume-area table for Malheur Lake, Oregon, 2021"}],"country":"United States","state":"Oregon","otherGeospatial":"Malheur Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -119.58577782962396,\n 43.67074885904847\n ],\n [\n -119.58577782962396,\n 42.85909953384322\n ],\n [\n -118.17464011814371,\n 42.85909953384322\n ],\n [\n -118.17464011814371,\n 43.67074885904847\n ],\n [\n -119.58577782962396,\n 43.67074885904847\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Oregon Water Science Center
U.S. Geological Survey
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The Federal Clean Water Act stipulates that States adopt water-quality standards to protect and enhance the quality of water in those States and to protect water quality through the creation of planning documents and discharge permits. Critical low-flow values, including the 4-day, 3-year low-flow frequency (4Q3) and harmonic mean streamflows, are necessary for developing those planning documents and permits. The U.S. Geological Survey computed the 4Q3 and adjusted harmonic mean streamflows using data from 96 streamgages on perennial streams, and regression equations were developed for the estimation of these parameters at ungaged, perennial streams in the State of New Mexico using weighted least-squares regression and readily accessed basin and climatic characteristics. Six equations were developed for the 4Q3 statistic, and five equations were developed for the adjusted harmonic mean statistic. Separate equations were developed for sites located in basins with mean elevations equal to or greater than 8,000 feet above the National Geodetic Vertical Datum of 1929 (except where noted as the North American Vertical Datum of 1988), as well as for sites on streams that are tributary to the San Juan River. Pseudo R-squared values ranged from 0.53 to 0.87 (4Q3) and adjusted R-squared values ranged from 0.69 to 0.89 (adjusted harmonic mean). For sites in basins with mean elevations of less than 8,000 feet above the National Geodetic Vertical Datum of 1929 (except where noted as the North American Vertical Datum of 1988), equations were developed based on contributing drainage area size. Drainage area, mean basin elevation, basinwide mean annual precipitation, and mean basin slope were found to have relations to the 4Q3; drainage area, mean basin elevation, basinwide mean annual precipitation, mean basin slope, and mean basinwide precipitation for the winter period, defined as the months of October through April, were found to have relations to the adjusted harmonic mean. Comparison to previous 4Q3 regression equations using fit statistics indicate an overall improvement in performance.
Director, New Mexico Water Science Center
U.S. Geological Survey
6700 Edith Blvd. NE
Albuquerque, NM 87113
Samples of oil-field water (oil wells, injectate, disposal ponds) and groundwater near selected oil and gas fields in southern California were analyzed for dissolved organic carbon (DOC) concentration and by optical spectroscopic techniques (i.e., absorbance and fluorescence) to assess whether these measurements can be used to distinguish between oil-field water (Oil Field), native groundwater (WGnat), and native groundwater mixed with oil-field water from surface (WGsurf) or subsurface sources (WGsub), and if so whether commonly reported optical measurements can be used as a screening tool to identify such water. Concentrations of DOC were significantly (p < 0.0001) higher (67 to 2934 mg C L−1) in oil-field water compared to native groundwater samples (<5.0 mg C L−1). Individual optical properties varied by water category and frequently overlapped. However, multivariate statistical analysis showed that when evaluated in combination, 10 optical properties were determined by discriminant analysis to be significant (p < 0.05) in distinguishing among water categories. Principal component analysis of those 10 optical properties showed that these properties can be used to successfully distinguish Oil Field samples from WGnat, WGsurf, and WGsub even when mixing fractions are low (approximately 10 %).
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2023.166970","usgsCitation":"Hansen, A., Kraus, T.E., Landon, M.K., and McMahon, P.B., 2023, Spectral characterization of dissolved organic matter in groundwater to assess mixing with oil-field water near selected oil fields, southern California: Science of the Total Environment, v. 905, 166970, 13 p., https://doi.org/10.1016/j.scitotenv.2023.166970.","productDescription":"166970, 13 p.","ipdsId":"IP-117786","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":442070,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2023.166970","text":"Publisher Index Page"},{"id":425566,"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 -118.38583234532425,\n 33.579820141579305\n ],\n [\n -118.38583234532425,\n 36.78462762816734\n ],\n [\n -121.18734601719926,\n 36.78462762816734\n ],\n [\n -121.18734601719926,\n 33.579820141579305\n ],\n [\n -118.38583234532425,\n 33.579820141579305\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"905","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hansen, Angela 0000-0003-0938-7611 anhansen@usgs.gov","orcid":"https://orcid.org/0000-0003-0938-7611","contributorId":171551,"corporation":false,"usgs":true,"family":"Hansen","given":"Angela","email":"anhansen@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":894580,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kraus, Tamara E. C. 0000-0002-5187-8644 tkraus@usgs.gov","orcid":"https://orcid.org/0000-0002-5187-8644","contributorId":147560,"corporation":false,"usgs":true,"family":"Kraus","given":"Tamara","email":"tkraus@usgs.gov","middleInitial":"E. C.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":894581,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Landon, Matthew K. 0000-0002-5766-0494 landon@usgs.gov","orcid":"https://orcid.org/0000-0002-5766-0494","contributorId":392,"corporation":false,"usgs":true,"family":"Landon","given":"Matthew","email":"landon@usgs.gov","middleInitial":"K.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":894582,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McMahon, Peter B. 0000-0001-7452-2379 pmcmahon@usgs.gov","orcid":"https://orcid.org/0000-0001-7452-2379","contributorId":724,"corporation":false,"usgs":true,"family":"McMahon","given":"Peter","email":"pmcmahon@usgs.gov","middleInitial":"B.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":894583,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70248563,"text":"sir20235091 - 2023 - Groundwater quality in abandoned underground coal mine aquifers across West Virginia","interactions":[],"lastModifiedDate":"2026-03-12T21:14:59.986084","indexId":"sir20235091","displayToPublicDate":"2023-09-15T13:20:00","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-5091","displayTitle":"Groundwater Quality in Abandoned Underground Coal Mine Aquifers Across West Virginia","title":"Groundwater quality in abandoned underground coal mine aquifers across West Virginia","docAbstract":"Abandoned underground coal mine aquifers cover a large part of West Virginia and could supply substantial quantities of water for agricultural, industrial, residential, and public use. Several Federal, State, and academic institutions have studied the availability and quality of water stored in abandoned underground coal mine aquifers for a variety of applications, such as economic development, geothermal energy, aquaculture, and wastewater disposal. However, the spatial and stratigraphic controls on water quality produced from abandoned underground coal mine aquifers are still poorly constrained on a state-wide basis. In response to these knowledge gaps, the U.S. Geological Survey initiated a study, in cooperation with the West Virginia Department of Environmental Protection, to understand the applicability of using existing secondary source data for understanding water quality in abandoned underground coal mine aquifers across the State.
Results from the calculation of net alkalinity indicated that Upper Pennsylvanian coal beds primarily produce net acidic waters and Lower Pennsylvanian coal beds primarily produce net alkaline waters. Multivariate statistical analysis of elemental data supports the conclusion that abandoned underground coal mine aquifers in the northern part of the State generally produce poor water quality and abandoned underground coal mine aquifers in southern West Virginia primarily produce good water quality. These results substantiate the potential benefits of leveraging abandoned underground coal mine aquifers as a multifaceted resource in West Virginia and can be used as a reconnaissance tool for water managers to characterize abandoned underground coal mine aquifers on a local scale.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235091","collaboration":"Prepared in cooperation with the West Virginia Department of Environmental Protection","usgsCitation":"McAdoo, M.A., Connock, G.T., and Kozar, M.D., 2023, Groundwater quality in abandoned underground coal mine aquifers across West Virginia: U.S. Geological Survey Scientific Investigations Report 2023–5091, 31 p., https://doi.org/10.3133/sir20235091.","productDescription":"Report: vii, 28 p.; Data Release","numberOfPages":"28","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-139239","costCenters":[{"id":37280,"text":"Virginia and West Virginia Water Science Center ","active":true,"usgs":true}],"links":[{"id":501057,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115401.htm","linkFileType":{"id":5,"text":"html"}},{"id":420842,"rank":6,"type":{"id":30,"text":"Data 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Virginia\",\"nation\":\"USA \"}}]}","contact":"Director, Virginia and West Virginia Water Science Center
U.S. Geological Survey
1730 East Parham Road
Richmond, VA 23228
This report summarizes an updated inventory of glaciers and perennial snowfields of the conterminous United States. The inventory is based on interpretation of mostly aerial imagery provided by the National Agricultural I magery Program, US Department of Agriculture, with some satellite imagery in places where aerial imagery was not suitable. The inventory includes all perennial snow and ice features ≥ 0.01 km2. Due to aerial survey schedules and seasonal snow cover, imageries acquired over a number of years were required. The earliest date is 2013 and the latest is 2020, but more than 73 % of the outlines were acquired from 2015 imagery. The inventory is compiled as shapefiles within a geographic information system that includes feature classification, area, and location. The inventory identified 1331 (366.52 ± 14.34 km2) glaciers, 1176 (31.01 ± 9.30 km2) perennial snowfields, and 35 (3.57 km2 ± no uncertainty) buried-ice features. The data including both the shapefiles and tabulated results are publicly available at https://doi.org/10.15760/geology-data.03 (Fountain and Glenn, 2022).
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University","active":true,"usgs":false}],"preferred":false,"id":885974,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McNeil, Christopher J. 0000-0003-4170-0428 cmcneil@usgs.gov","orcid":"https://orcid.org/0000-0003-4170-0428","contributorId":5803,"corporation":false,"usgs":true,"family":"McNeil","given":"Christopher J.","email":"cmcneil@usgs.gov","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":885975,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70250012,"text":"70250012 - 2023 - Stocking fish in inland waters: Opportunities and risks for sustainable food systems","interactions":[],"lastModifiedDate":"2023-11-14T12:43:11.951223","indexId":"70250012","displayToPublicDate":"2023-09-15T06:41:52","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1659,"text":"Fisheries Management and Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Stocking fish in inland waters: Opportunities and risks for sustainable food systems","docAbstract":"Stocking is one of the foremost tools in the inland fisheries management toolbox, but it comes with both opportunities and risks. Stocking is often used as compensation for depleted wild populations, particularly where recruitment processes have been disrupted, but it can introduce disease, disrupt community structures, reduce genetic integrity, and cause conflicts between fishery stakeholders. Despite its widespread use, examples of effective stocking for food fisheries in inland waters are sparse in the peer-reviewed literature. Nevertheless, it is well established that stocking is frequently used to maintain fish yield, so there is a need to conduct the practice in a robust manner that minimises the potential risks. This paper serves as the front matter for a special section of Fisheries Management and Ecology focused on fresh waters feeding the world, which resulted from two panel sessions, one focused on aquaculture and one focused on stocking, hosted by the international InFish research network (https://infish.org/). The paper highlights current practices of fish stock enhancement in inland waters for food, examines potential synergies and interactions of stock enhancement programmes with aquaculture, and provides an outline framework for responsible management of fish stock enhancement.
Blue carbon, a convenient term to encompass the climate mitigation value of coastal carbon dynamics, has received global policy attention and growing datasets to support management actions. Carbon stock assessments in mangroves, seagrass, and tidal marshes document significant carbon storage in soils. Models illustrate significant downward fluxes of carbon dioxide and limited methane emissions, making tidal wetland preservation and restoration notably potent for carbon dioxide removal (CDR). Natural variation in different carbon stocks and fluxes has led to prioritization efforts to characterize coastal lands across physical and biological gradients. However, a larger concern beyond upscaling carbon dynamics is the resilience of these stocks and fluxes with global changes. Data-informed models have greatly improved our assessments of the vulnerability of soil and biomass stocks, greenhouse gas (GHG) balance, and spatial extents. Accelerated sea-level rise is increasingly concerning, but its impacts vary by resilience context, as very few coastal lands are without direct human impact. As the landscape context has changed, blue carbon fluxes have also shifted in terms of importance and distribution. New incentives for tidal ecosystem management are expanding boundaries to include algal carbon and tidal transport of alkalinity, which bring additional co-benefits to coastal waters. Using examples from the conterminous USA on blue carbon stocks, radiative balance, and extent, this chapter explores timelines of physical and biogeochemical stressors and their application to past, current, and future climate mitigation functions of coastal ecosystems.
","largerWorkTitle":"Climate change and estuaries","language":"English","publisher":"CRC Press","usgsCitation":"Windham-Myers, L., 2023, Blue carbon in a changing climate and a changing context, chap. of Climate change and estuaries, p. 203-214.","productDescription":"12 p.","startPage":"203","endPage":"214","ipdsId":"IP-144897","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":421025,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":421024,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.taylorfrancis.com/chapters/edit/10.1201/9781003126096-12/blue-carbon-changing-climate-changing-context-lisamarie-windham-myers?context=ubx&refId=09c63ae2-147c-4d3e-a44e-e123f1046fc4","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"editors":[{"text":"Kennish, Michael J.","contributorId":111903,"corporation":false,"usgs":true,"family":"Kennish","given":"Michael","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":883743,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Paerl, Hans W.","contributorId":172724,"corporation":false,"usgs":false,"family":"Paerl","given":"Hans","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":883744,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Crosswell, Joseph","contributorId":217003,"corporation":false,"usgs":false,"family":"Crosswell","given":"Joseph","email":"","affiliations":[{"id":36909,"text":"CSIRO","active":true,"usgs":false}],"preferred":false,"id":883745,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Windham-Myers, Lisamarie 0000-0003-0281-9581 lwindham-myers@usgs.gov","orcid":"https://orcid.org/0000-0003-0281-9581","contributorId":2449,"corporation":false,"usgs":true,"family":"Windham-Myers","given":"Lisamarie","email":"lwindham-myers@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":883711,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70248449,"text":"70248449 - 2023 - Multi-decadal erosion rates from glacierized watersheds on Mount Baker, Washington, USA, reveal topographic, climatic, and lithologic controls on sediment yields","interactions":[],"lastModifiedDate":"2023-09-13T19:15:08.088286","indexId":"70248449","displayToPublicDate":"2023-09-13T13:51:42","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1801,"text":"Geomorphology","active":true,"publicationSubtype":{"id":10}},"title":"Multi-decadal erosion rates from glacierized watersheds on Mount Baker, Washington, USA, reveal topographic, climatic, and lithologic controls on sediment yields","docAbstract":"Understanding land surface change in and sediment export out of proglacial landscapes is critical for understanding geohazard and flood risks over engineering timescales and characterizing landscape evolution over geomorphic timescales. We used automated Structure from Motion software to process historical aerial photographs and, with modern lidar data, generated a high-resolution DEM time series with coverage over 10 glacierized watersheds on Mount Baker, Washington, USA for the time period between 1947 and 2015. We measured basin-wide sediment yields and sediment redistribution on hillslopes and in stream channels. Slopes within most measured erosion sites are above theoretical and observed debris-flow thresholds. We observed significant erosion of hillslopes and limited deposition on hillslopes and in stream channels. Sediment delivery ratios during time periods with net erosion averaged 0.73. We determined, consistent with previous field observations, that debris flows originating from moraines are a primary erosion mechanism in proglacial zones on Mount Baker. Time series measurements indicate that temporal variability in erosion rates is associated with climate oscillations, with higher erosion rates during cooler-wetter periods. Basin-wide sediment yield is positively correlated with lithology (r2 = 0.54), hillslope angle (r2 = 0.52), drainage area (r2 = 0.82), and negatively correlated with stream channel slope (r2 = 0.67). Topographic differences between high and low yielding basins indicate that spatial variability in erosion on Mount Baker is sensitive to Pleistocene and Holocene glacial and volcanic activity. Specific sediment yields in six basins averaged 4600 ton/km2/yr, consistent with global measurements in glacierized catchments. Specific sediment yield decreased with increasing basin area, with total loads in the downstream main stem Nooksack River estimated between 480 and 820 ton/km2/yr. Proglacial sediment yields account for between 18 and 32 % of total sediment load in the main stem Nooksack River and exceed contributions by bluff and terrace erosion, which account for between 8 and 13 % of total load. Our findings indicate that erosion in glacierized basins is sensitive to decadal climate oscillations and that high proglacial sediment yields provide an important contribution to river systems downstream, particularly in catchments where upland topography and lithology is favorable.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.geomorph.2023.108805","usgsCitation":"Schwat, E., Istanbulluoglu, E., Horner-Devine, A., Anderson, S.W., Knuth, F., and Shean, D., 2023, Multi-decadal erosion rates from glacierized watersheds on Mount Baker, Washington, USA, reveal topographic, climatic, and lithologic controls on sediment yields: Geomorphology, v. 438, 108805, 17 p., https://doi.org/10.1016/j.geomorph.2023.108805.","productDescription":"108805, 17 p.","ipdsId":"IP-152751","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":442107,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.geomorph.2023.108805","text":"Publisher Index Page"},{"id":420774,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Koma Kulshan, Mount Baker","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.85505311805078,\n 48.71738721735028\n ],\n [\n -121.8138912926704,\n 48.69120451475976\n ],\n [\n -121.72859208826776,\n 48.669266019808475\n ],\n [\n -121.67503212271245,\n 48.72229495768988\n ],\n [\n -121.6804873043895,\n 48.74224816877816\n ],\n [\n -121.66610546178667,\n 48.77461439590772\n ],\n [\n -121.7603313271151,\n 48.82361440118996\n ],\n [\n -121.86298792776248,\n 48.840916292756305\n ],\n [\n -121.92101122378057,\n 48.82034922330564\n ],\n [\n -121.94729528095108,\n 48.77134602689094\n ],\n [\n -121.91357233967562,\n 48.74061295759708\n ],\n [\n -121.85505311805078,\n 48.71738721735028\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"438","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Schwat, Eli","contributorId":299744,"corporation":false,"usgs":false,"family":"Schwat","given":"Eli","email":"","affiliations":[],"preferred":false,"id":882951,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Istanbulluoglu, Erkan 0000-0001-9453-4676","orcid":"https://orcid.org/0000-0001-9453-4676","contributorId":295348,"corporation":false,"usgs":false,"family":"Istanbulluoglu","given":"Erkan","email":"","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":882952,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Horner-Devine, Alex 0000-0003-2323-7150","orcid":"https://orcid.org/0000-0003-2323-7150","contributorId":295351,"corporation":false,"usgs":false,"family":"Horner-Devine","given":"Alex","email":"","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":882953,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Anderson, Scott W. 0000-0003-1678-5204 swanderson@usgs.gov","orcid":"https://orcid.org/0000-0003-1678-5204","contributorId":196687,"corporation":false,"usgs":true,"family":"Anderson","given":"Scott","email":"swanderson@usgs.gov","middleInitial":"W.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":882954,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Knuth, Friedrich","contributorId":299741,"corporation":false,"usgs":false,"family":"Knuth","given":"Friedrich","email":"","affiliations":[],"preferred":false,"id":882955,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Shean, David","contributorId":299742,"corporation":false,"usgs":false,"family":"Shean","given":"David","affiliations":[],"preferred":false,"id":882956,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70248439,"text":"70248439 - 2023 - Identifying sources of antibiotic resistance genes in the environment using the microbial Find, Inform, and Test framework","interactions":[],"lastModifiedDate":"2023-09-13T18:44:22.909442","indexId":"70248439","displayToPublicDate":"2023-09-13T13:33:43","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1702,"text":"Frontiers in Microbiology","onlineIssn":"1664-302X","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Identifying sources of antibiotic resistance genes in the environment using the microbial Find, Inform, and Test framework","title":"Identifying sources of antibiotic resistance genes in the environment using the microbial Find, Inform, and Test framework","docAbstract":"Introduction: Antimicrobial resistance (AMR) is an increasing public health concern for humans, animals, and the environment. However, the contributions of spatially distributed sources of AMR in the environment are not well defined.
Methods: To identify the sources of environmental AMR, the novel microbial Find, Inform, and Test (FIT) model was applied to a panel of five antibiotic resistance-associated genes (ARGs), namely, erm(B), tet(W), qnrA, sul1, and intI1, quantified from riverbed sediment and surface water from a mixed-use region.
Results: A one standard deviation increase in the modeled contributions of elevated AMR from bovine sources or land-applied waste sources [land application of biosolids, sludge, and industrial wastewater (i.e., food processing) and domestic (i.e., municipal and septage)] was associated with 34–80% and 33–77% increases in the relative abundances of the ARGs in riverbed sediment and surface water, respectively. Sources influenced environmental AMR at overland distances of up to 13 km.
Discussion: Our study corroborates previous evidence of offsite migration of microbial pollution from bovine sources and newly suggests offsite migration from land-applied waste. With FIT, we estimated the distance-based influence range overland and downstream around sources to model the impact these sources may have on AMR at unsampled sites. This modeling supports targeted monitoring of AMR from sources for future exposure and risk mitigation efforts.
","language":"English","publisher":"Frontiers Media S.A.","doi":"10.3389/fmicb.2023.1223876","usgsCitation":"Wiesner-Friedman, C., Beattie, R.E., Stewart, J.R., Hristova, K.R., and Serre, M.L., 2023, Identifying sources of antibiotic resistance genes in the environment using the microbial Find, Inform, and Test framework: Frontiers in Microbiology, v. 14, 1223876, 14 p., https://doi.org/10.3389/fmicb.2023.1223876.","productDescription":"1223876, 14 p.","ipdsId":"IP-149826","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":442109,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fmicb.2023.1223876","text":"Publisher Index Page"},{"id":420771,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","county":"Kewaunee County","otherGeospatial":"Ahnapee River, East Twin River, Kewaunee River","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"id\":3073,\"properties\":{\"name\":\"Kewaunee\",\"state\":\"WI\"},\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-87.3761,44.6754],[-87.3774,44.674],[-87.381,44.6636],[-87.3858,44.6545],[-87.3911,44.6473],[-87.3944,44.6442],[-87.3966,44.6378],[-87.4045,44.6302],[-87.4085,44.6257],[-87.4137,44.6235],[-87.4223,44.6145],[-87.4263,44.61],[-87.4341,44.6056],[-87.442,44.6011],[-87.4428,44.5934],[-87.4468,44.5893],[-87.4502,44.5816],[-87.4544,44.5721],[-87.4604,44.5622],[-87.4664,44.555],[-87.4738,44.5455],[-87.476,44.5369],[-87.4761,44.5305],[-87.4796,44.5223],[-87.4851,44.5106],[-87.488,44.4974],[-87.4959,44.4706],[-87.5046,44.4575],[-87.5041,44.4534],[-87.5062,44.4457],[-87.5064,44.4375],[-87.5074,44.4279],[-87.5121,44.4188],[-87.5163,44.408],[-87.5191,44.3998],[-87.5212,44.3907],[-87.5209,44.3816],[-87.5218,44.3734],[-87.5232,44.3688],[-87.5279,44.3602],[-87.5351,44.3521],[-87.5386,44.3422],[-87.5368,44.338],[-87.5408,44.3331],[-87.5454,44.3277],[-87.6445,44.3273],[-87.7665,44.3271],[-87.7655,44.4146],[-87.7646,44.5017],[-87.7643,44.5888],[-87.7628,44.6477],[-87.7582,44.6522],[-87.7555,44.6558],[-87.7547,44.6608],[-87.7507,44.6667],[-87.7435,44.673],[-87.7389,44.6775],[-87.6413,44.6757],[-87.5193,44.6753],[-87.4384,44.6754],[-87.3973,44.6753],[-87.3761,44.6754]]]}}]}","volume":"14","noUsgsAuthors":false,"publicationDate":"2023-09-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Wiesner-Friedman, Corinne","contributorId":329682,"corporation":false,"usgs":false,"family":"Wiesner-Friedman","given":"Corinne","email":"","affiliations":[{"id":13529,"text":"US Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":882931,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beattie, Rachelle Elaine 0000-0002-9648-4948","orcid":"https://orcid.org/0000-0002-9648-4948","contributorId":298312,"corporation":false,"usgs":true,"family":"Beattie","given":"Rachelle","email":"","middleInitial":"Elaine","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":882932,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stewart, Jill R.","contributorId":329683,"corporation":false,"usgs":false,"family":"Stewart","given":"Jill","email":"","middleInitial":"R.","affiliations":[{"id":27051,"text":"University of North Carolina at Chapel Hill","active":true,"usgs":false}],"preferred":false,"id":882933,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hristova, Krassimira R.","contributorId":298313,"corporation":false,"usgs":false,"family":"Hristova","given":"Krassimira","email":"","middleInitial":"R.","affiliations":[{"id":64527,"text":"Marquette University","active":true,"usgs":false}],"preferred":false,"id":882934,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Serre, Marc L.","contributorId":329684,"corporation":false,"usgs":false,"family":"Serre","given":"Marc","email":"","middleInitial":"L.","affiliations":[{"id":27051,"text":"University of North Carolina at Chapel Hill","active":true,"usgs":false}],"preferred":false,"id":882935,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70248075,"text":"70248075 - 2023 - Mercury isotope values in shoreline spiders reveal transfer of aquatic mercury sources to terrestrial food webs","interactions":[],"lastModifiedDate":"2023-10-11T16:01:26.81846","indexId":"70248075","displayToPublicDate":"2023-09-13T09:30:54","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7485,"text":"Environmental Science and Technology Letters","active":true,"publicationSubtype":{"id":10}},"title":"Mercury isotope values in shoreline spiders reveal transfer of aquatic mercury sources to terrestrial food webs","docAbstract":"The transfer of aquatic contaminants, including mercury (Hg), to terrestrial food webs is an often-overlooked exposure pathway to terrestrial animals. While research has implemented the use of shoreline spiders to assess aquatic to terrestrial Hg transfer, it is unclear whether Hg sources, estimated from isotope ratios, can be successfully resolved to inform site assessments and remedy effectiveness. To examine aquatic to terrestrial Hg transfer, we collected shoreline spiders (Tetragnatha spp.) and aquatic insect larvae (suborder Anisoptera) across a mosaic of aquatic and shoreline habitats in the St. Louis River and Bad River, tributaries to Lake Superior. The fraction of industrial Hg in sediments was reflected in the δ202Hg values of aquatic dragonfly larvae and predatory fish, connecting benthic Hg sources to the aquatic food web. Shoreline spiders mirrored these aquatic Hg source signatures with highly positive correlations in δ202Hg between tetragnathids and dragonfly larvae (r2 = 0.90). Further assessment of different spider taxa (i.e., araneids and pisaurids) revealed that differences in prey consumption and foraging strategies resulted in isotope differences, highlighting the importance of spider taxa selection for Hg monitoring efforts.
","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.estlett.3c00450","usgsCitation":"Janssen, S., Kotalik, C.J., Eagles-Smith, C., Beaubien, G.B., Hoffman, J.C., Peterson, G., Mills, M.A., and Walters, D., 2023, Mercury isotope values in shoreline spiders reveal transfer of aquatic mercury sources to terrestrial food webs: Environmental Science and Technology Letters, v. 10, no. 10, p. 891-896, https://doi.org/10.1021/acs.estlett.3c00450.","productDescription":"6 p.","startPage":"891","endPage":"896","ipdsId":"IP-153126","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":442116,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/10569030","text":"Publisher Index Page"},{"id":435186,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P96HIBA4","text":"USGS data release","linkHelpText":"Assessment of Mercury and Mercury Stable Isotopes in Sediments and Biota from Reservoirs and Remedial Zones within the Saint Louis River, Minnesota"},{"id":420951,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota, Wisconsin","otherGeospatial":"Bad River, Lake Superior, St. Louis River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -91.97319972002215,\n 46.85080995328977\n ],\n [\n -92.3808806574504,\n 46.85080995328977\n ],\n [\n -92.3808806574504,\n 46.607590925287866\n ],\n [\n -91.97319972002215,\n 46.607590925287866\n ],\n [\n -91.97319972002215,\n 46.85080995328977\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -90.76604011941525,\n 46.66037391866578\n ],\n [\n -90.76604011941525,\n 46.56740333938299\n ],\n [\n -90.61257263374692,\n 46.56740333938299\n ],\n [\n -90.61257263374692,\n 46.66037391866578\n ],\n [\n -90.76604011941525,\n 46.66037391866578\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"10","issue":"10","noUsgsAuthors":false,"publicationDate":"2023-09-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Janssen, Sarah E. 0000-0003-4432-3154","orcid":"https://orcid.org/0000-0003-4432-3154","contributorId":210991,"corporation":false,"usgs":true,"family":"Janssen","given":"Sarah E.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":881781,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kotalik, Christopher James 0000-0001-6739-6036","orcid":"https://orcid.org/0000-0001-6739-6036","contributorId":301847,"corporation":false,"usgs":true,"family":"Kotalik","given":"Christopher","email":"","middleInitial":"James","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":881782,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Eagles-Smith, Collin A. 0000-0003-1329-5285","orcid":"https://orcid.org/0000-0003-1329-5285","contributorId":221745,"corporation":false,"usgs":true,"family":"Eagles-Smith","given":"Collin A.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":881783,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Beaubien, Gale B.","contributorId":244596,"corporation":false,"usgs":false,"family":"Beaubien","given":"Gale","email":"","middleInitial":"B.","affiliations":[{"id":37193,"text":"Middle Tennessee State University","active":true,"usgs":false}],"preferred":false,"id":881784,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hoffman, Joel C.","contributorId":84244,"corporation":false,"usgs":false,"family":"Hoffman","given":"Joel","email":"","middleInitial":"C.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":881785,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Peterson, Greg","contributorId":256978,"corporation":false,"usgs":false,"family":"Peterson","given":"Greg","email":"","affiliations":[{"id":40396,"text":"US Environmental Protection Agency, Office of Research and Development","active":true,"usgs":false}],"preferred":false,"id":881786,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Mills, Marc A.","contributorId":141085,"corporation":false,"usgs":false,"family":"Mills","given":"Marc","email":"","middleInitial":"A.","affiliations":[{"id":12772,"text":"USEPA","active":true,"usgs":false}],"preferred":false,"id":881787,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Walters, David 0000-0002-4237-2158","orcid":"https://orcid.org/0000-0002-4237-2158","contributorId":203410,"corporation":false,"usgs":true,"family":"Walters","given":"David","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":881788,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70248906,"text":"70248906 - 2023 - Converting CRP grasslands to cropland, grazing land, or hayland: Effects on breeding bird abundances in the northern Great Plains of the United States","interactions":[],"lastModifiedDate":"2023-09-26T12:22:34.336494","indexId":"70248906","displayToPublicDate":"2023-09-13T07:19:57","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3871,"text":"Global Ecology and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Converting CRP grasslands to cropland, grazing land, or hayland: Effects on breeding bird abundances in the northern Great Plains of the United States","docAbstract":"Recent declines of grassland bird populations in North America are linked to habitat loss and fragmentation associated with agricultural practices. One tool used to conserve soil, water and wildlife habitat on agricultural fields is the U.S. Department of Agriculture’s Conservation Reserve Program (CRP), the largest agricultural conservation program in the United States. Managers and conservationists recognize CRP as an important component of conserving grassland birds in the central portion of the United States. However, recent widespread expiration of CRP contracts could negatively influence grassland bird populations. Few studies have evaluated how former CRP-enrolled fields may function as grassland bird habitat. In this paper, we analyzed data from a long-term (1990–2017) study aimed at comparing grassland bird abundance (24 species) between idled CRP grasslands and fields where the CRP contracts expired. Some of these fields where contracts expired were maintained as pasture or hayland, and others were converted back to cropland. Estimated abundances of most species were considerably higher in idled CRP than in fields with expired CRP contracts. Post-CRP land use also appeared to affect most bird abundances, with lower abundance in grazed grasslands and haylands relative to idled CRP, but higher abundance than cropland. The responses of obligate and facultative grassland specialists to post-CRP management varied among species, with some being negative and some being positive depending on post-CRP land use, which is unsurprising given the variable habitat requirements of grassland birds. Our results have implications for wildlife managers who must design conservation strategies around the land use decisions of private landowners. Our results support the idea of maintaining a mosaic of undisturbed CRP grasslands and post-CRP grasslands that are hayed or grazed, which should guarantee some undisturbed nesting cover in the landscape for some bird species and some disturbed grasslands that may have long-term benefits for other species.
Biodiversity is generally reduced when non-native species invade an ecosystem. Invasive crayfish, Procambarus clarkii, populate California freshwater streams, and in the Santa Monica Mountains (Los Angeles, USA), their introduction has led to trophic cascades due to omnivorous feeding behavior and a rapid rate of population growth. The native California newt, Taricha torosa, possesses a neurotoxin, tetrodotoxin (TTX), that affects freshwater animal behavior. Given P. clarkii has a limited evolutionary history with TTX, we hypothesized that TTX may affect crayfish feeding behaviors. To determine if TTX affects P. clarkii behavior, we measured cumulative movement and various feeding behaviors of P. clarkii exposed to (i) waterborne, ecologically realistic concentrations of TTX (~ 3.0 × 10− 8 moles/L), (ii) an anuran chemical cue to account for intraguild cues, or (iii) a T. torosa chemical cue with quantitated TTX in it (~ 6.2 × 10− 8 moles/L).
We found that the presence of TTX in any form significantly reduced crayfish movement and decreased the amount of food consumed over time. Crayfish responses to the anuran treatment did not significantly differ from controls.
Our laboratory results show that naturally occurring neurotoxin from native California newts limits invasive crayfish foraging and feeding rates, which may play a role in preserving local stream ecosystems by limiting invasive crayfish behaviors that are detrimental to biodiversity.
","language":"English","publisher":"Springer","doi":"10.1186/s12862-023-02162-6","usgsCitation":"Bucciarelli, G.M., Smith, S.J., Choe, J.J., Shin, P.D., Fisher, R., and Kats, L.B., 2023, Native amphibian toxin reduces invasive crayfish feeding with potential benefits to stream biodiversity: BMC Ecological Evolution, v. 23, 51, 10 p., https://doi.org/10.1186/s12862-023-02162-6.","productDescription":"51, 10 p.","ipdsId":"IP-153361","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":442121,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s12862-023-02162-6","text":"Publisher Index Page"},{"id":420942,"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 -119.10835949859933,\n 34.24972494086572\n ],\n [\n -119.10835949859933,\n 33.95419558307488\n ],\n [\n -118.36160958124017,\n 33.95419558307488\n ],\n [\n -118.36160958124017,\n 34.24972494086572\n ],\n [\n -119.10835949859933,\n 34.24972494086572\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"23","noUsgsAuthors":false,"publicationDate":"2023-09-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Bucciarelli, Gary M.","contributorId":209642,"corporation":false,"usgs":false,"family":"Bucciarelli","given":"Gary","email":"","middleInitial":"M.","affiliations":[{"id":13399,"text":"UCLA","active":true,"usgs":false}],"preferred":false,"id":883402,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Sierra J.","contributorId":329828,"corporation":false,"usgs":false,"family":"Smith","given":"Sierra","email":"","middleInitial":"J.","affiliations":[{"id":37949,"text":"Pepperdine University","active":true,"usgs":false}],"preferred":false,"id":883403,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Choe, Justin J.","contributorId":329829,"corporation":false,"usgs":false,"family":"Choe","given":"Justin","email":"","middleInitial":"J.","affiliations":[{"id":37949,"text":"Pepperdine University","active":true,"usgs":false}],"preferred":false,"id":883404,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shin, Phoebe D.","contributorId":329831,"corporation":false,"usgs":false,"family":"Shin","given":"Phoebe","email":"","middleInitial":"D.","affiliations":[{"id":37949,"text":"Pepperdine University","active":true,"usgs":false}],"preferred":false,"id":883405,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fisher, Robert N. 0000-0002-2956-3240","orcid":"https://orcid.org/0000-0002-2956-3240","contributorId":51675,"corporation":false,"usgs":true,"family":"Fisher","given":"Robert N.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":883406,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kats, Lee B.","contributorId":208330,"corporation":false,"usgs":false,"family":"Kats","given":"Lee","email":"","middleInitial":"B.","affiliations":[{"id":37783,"text":"Seaver College, Pepperdine University","active":true,"usgs":false}],"preferred":false,"id":883407,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70248277,"text":"sir20235087 - 2023 - Approaches for assessing flows, concentrations, and loads of highway and urban runoff and receiving-stream stormwater in southern New England with the Stochastic Empirical Loading and Dilution Model (SELDM)","interactions":[],"lastModifiedDate":"2026-03-12T21:08:34.632448","indexId":"sir20235087","displayToPublicDate":"2023-09-12T19:46:00","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-5087","displayTitle":"Approaches for Assessing Flows, Concentrations, and Loads of Highway and Urban Runoff and Receiving-Stream Stormwater in Southern New England With the Stochastic Empirical Loading and Dilution Model (SELDM)","title":"Approaches for assessing flows, concentrations, and loads of highway and urban runoff and receiving-stream stormwater in southern New England with the Stochastic Empirical Loading and Dilution Model (SELDM)","docAbstract":"The Stochastic Empirical Loading and Dilution Model (SELDM) was designed to help quantify the risk of adverse effects of runoff on receiving waters, the potential need for mitigation measures, and the potential effectiveness of such management measures for reducing these risks. SELDM is calibrated using representative hydrological and water-quality input statistics. This report by the U.S. Geological Survey, in cooperation with the Federal Highway Administration and the Connecticut, Massachusetts, and Rhode Island Departments of Transportation, documents approaches for assessing flows, concentrations, and loads of highway- and urban-runoff and receiving-stream stormwater in southern New England with SELDM. In this report, the term “urban runoff” is used to identify stormwater flows from developed areas with impervious fractions ranging from 10 to 100 percent without regard to the U.S. Census Bureau designation for any given location. There are more than 48,000 delineated road-stream crossings in southern New England, but because there are relatively few precipitation, streamflow, and water-quality monitoring sites in this area, methods were needed to simulate conditions at unmonitored sites. This report documents simulation methods, methods for interpreting stochastic model results, sensitivity analyses to identify the most critical variables of concern, and examples demonstrating how simulation results can be used to inform scientific decision-making processes. Results of 7,511 SELDM simulations were used to do the sensitivity analyses and provide information decisionmakers can use to address runoff-quality issues in southern New England and other areas of the Nation.
The sensitivity analyses indicate the relatively strong effect of input variables on variations in output results. These analyses indicate that highway and urban runoff quality and upstream water-quality statistics that vary considerably from site to site have the greatest effect on simulated results. Further data are needed to improve available water-quality statistics, and because the number of monitored sites will never approach the number of sites of interest for water-quality management, research is needed to identify methods to select statistics for unmonitored sites and quantify the uncertainties in the selection process. Hydrologically, prestorm streamflows with and without zero flows are the most sensitive and therefore the most important hydrologic variables to quantify. Results of analyses also are sensitive to statistics used for simulating structural best management practices.
Although the focus of the report is on data, statistics, simulation methods, and methods to interpret stochastic simulations, the examples in this report provide results that can be used to inform scientific decision-making processes. The results of 441 simulations that provide regional and site-specific highway and urban runoff yields across southern New England can be used for total maximum daily load analyses. The example stormwater load analysis done for 16 tributaries of the Narragansett Bay demonstrates that highway nitrogen loads are a small fraction of stormwater loads (about 3.6 percent), and a much smaller fraction of all nitrogen loads to the bay, primarily because highways have a small footprint on the land. Examples evaluating the potential effectiveness of end-of-pipe treatment indicate that offsite treatment is warranted in developed areas, and land conservation may be an effective mitigation strategy. The results of these analyses are consistent with conclusions from other simulation and monitoring studies.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235087","collaboration":"Prepared in cooperation with the Federal Highway Administration and the Connecticut, Massachusetts, and Rhode Island Departments of Transportation","usgsCitation":"Granato, G.E., Spaetzel, A.B., and Jeznach, L.C., 2023, Approaches for assessing flows, concentrations, and loads of highway and urban runoff and receiving-stream stormwater in southern New England with the Stochastic Empirical Loading and Dilution Model (SELDM): U.S. Geological Survey Scientific Investigations Report 2023–5087, 152 p., https://doi.org/10.3133/sir20235087.","productDescription":"Report: xii, 152 p.; Software Release; 4 Data Releases","numberOfPages":"152","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-133112","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":501050,"rank":12,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115402.htm","linkFileType":{"id":5,"text":"html"}},{"id":420555,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9K0Y7XR","text":"USGS data release","linkHelpText":"Model archive for analysis of the effects of impervious cover on receiving-water quality with the Stochastic Empirical Loading Dilution Model (SELDM)"},{"id":420556,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9CZNIH5","text":"USGS data release","linkHelpText":"Model archive for analysis of flows, concentrations, and loads of highway and urban runoff and receiving-stream stormwater in southern New England with the Stochastic Empirical Loading and Dilution Model (SELDM)"},{"id":420554,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9B02EUZ","text":"USGS data release","linkHelpText":"Model archive for analysis of long-term annual yields of highway and urban runoff in selected areas of California with the Stochastic Empirical Loading Dilution Model (SELDM)"},{"id":420557,"rank":9,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9VK1MCG","text":"USGS data release","linkHelpText":"Basin characteristics and point locations of road crossings in Connecticut, Massachusetts, and Rhode Island for highway-runoff mitigation analyses using the Stochastic Empirical Loading and Dilution Model"},{"id":420548,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5087/coverthb.jpg"},{"id":420549,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5087/sir20235087.pdf","text":"Report","size":"8.64 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5087"},{"id":420552,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5087/images/"},{"id":420887,"rank":11,"type":{"id":35,"text":"Software Release"},"url":"https://doi.org/10.5066/P9PYG7T5","text":"USGS software release","linkHelpText":"- Stochastic Empirical Loading and Dilution Model (SELDM) software archive"},{"id":420551,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5087/sir20235087.XML"},{"id":420553,"rank":10,"type":{"id":35,"text":"Software Release"},"url":"https://doi.org/10.5066/P9XBPIOB","text":"USGS software release","linkHelpText":"- Best management practices statistical estimator (BMPSE) version 1.2.0"},{"id":420550,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235087/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2023-5087"}],"country":"United States","state":"Connecticut, Massachusetts, New Hampshire, Rhode Island, Vermont","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -73.28249194123347,\n 42.97558594616143\n ],\n [\n -73.81823969745555,\n 41.00628384122689\n ],\n [\n -69.72117184187273,\n 40.9949482400483\n ],\n [\n -69.72117184187273,\n 42.97558594616143\n ],\n [\n -73.28249194123347,\n 42.97558594616143\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
Using manufactured baits to attract fish to passive gear is common practice in fisheries management. The most common method is using hoop nets baited with soybean cakes or waste cheese to increase captures of multiple catfish species; however, these techniques are limited to how often bait is added, the type of bait, gear compatibility, and oversaturation of bait during soak time. The U.S. Geological Survey developed a technique to deliver various types of manufactured, pelleted baits over multiple scenarios and traditional passive gears. A floating platform designed with a dispenser can be constructed easily and allows for the automatic application of varying quantities and sizes of bait. Bait platforms can be modified for use in lakes and rivers where water fluctuations are common. Unlike traditional baiting techniques, these platforms can be positioned over or near any type of gear and release bait as many as nine times daily. Programmed release of bait multiple time a day can be useful to target fish activity during specific hours and can allow for sustained application without bait oversaturation or deterioration from long soak times. This report describes the design of a bait delivery platform developed for deployment in the Sandusky River in Ohio for the removal of Ctenopharyngodon idella (Valenciennes, 1844; grass carp) during 2021 and 2022.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm8D2","usgsCitation":"Wamboldt, J.J., 2023, Design and utility of automatous, floating bait delivery platform for applying fish management baits: U.S. Geological Survey Techniques and Methods, book 8, chap. D2, 8 p., https://doi.org/10.3133/tm8D2.","productDescription":"vi, 8 p.","numberOfPages":"18","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-153329","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":420736,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/tm8D2/full","linkFileType":{"id":5,"text":"html"}},{"id":420715,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/tm/08/d02/images/"},{"id":420714,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/tm/08/d02/tm8d2.XML","linkFileType":{"id":8,"text":"xml"}},{"id":420713,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/08/d02/tm8d2.pdf","text":"Report","size":"1.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"TM 8–D2"},{"id":420712,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/08/d02/coverthb.jpg"}],"contact":"Director, Upper Midwest Environmental Sciences Center
U.S. Geological Survey
2630 Fanta Reed Road
La Crosse, Wisconsin 54603
Though the importance of Earth's internal climate modes such as the El Niño-Southern Oscillation (ENSO) and the North Atlantic Oscillation (NAO) to regional-scale climate variability is well recognized, the degree to which these oscillations are reflected by spatio-temporal salinity variability over interannual timescales in estuaries is less understood. Here an 11-year continuous salinity monitoring dataset spanning 223 stations across Louisiana's coastal wetlands along the northern Gulf of Mexico is examined with empirical orthogonal function (EOF) analysis to identify dominant modes of interannual variability in the salinity field. The first EOF mode accounts for 72% of the variance in the salinity field and captures a domain-wide pattern where salinities vary in-phase through space in response to local precipitation anomalies occurring in the vicinity of the study area. This local precipitation anomaly is positively correlated with ENSO (Nino3.4 index), consistent with the El Niño – wet (La Niña – dry) precipitation teleconnection that is prevalent throughout the northern Gulf of Mexico coast. The second EOF mode, which accounts for 13% of the variance in the salinity field, is expressed primarily in the marshes across the lower reaches of the Mississippi River deltaic plain (MRDP). EOF2 is anticorrelated with annual Mississippi River discharge anomaly such that salinities in the lower MRDP decrease as discharge increases, pointing to enhanced advection of fresh river plume waters over the shelf into the estuary via estuary-ocean exchange during years of anomalously high river discharge. Mississippi River discharge anomaly is positively correlated with the NAO at a one-year time lag, through a teleconnection with precipitation throughout much of the central region of the Mississippi River drainage basin. Together, these findings indicate that most of the interannual salinity variability across Louisiana's coastal wetlands can be linked to climate variability through teleconnections with precipitation. Incorporating these dynamics into restoration planning, monitoring, and adaptive management efforts may help constrain background environmental variation and better isolate restoration effects.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecss.2023.108487","usgsCitation":"Snedden, G., 2023, ENSO and NAO linkages to interannual salinity variability in north central Gulf of Mexico estuaries through teleconnections with precipitation: Estuarine, Coastal and Shelf Science, v. 293, 108487, 9 p., https://doi.org/10.1016/j.ecss.2023.108487.","productDescription":"108487, 9 p.","ipdsId":"IP-140302","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":420905,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Gulf Coast","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -89.7941680074912,\n 30.932276934300717\n ],\n [\n -93.76673369766087,\n 30.932276934300717\n ],\n [\n -93.76673369766087,\n 28.810632610138626\n ],\n [\n -89.7941680074912,\n 28.810632610138626\n ],\n [\n -89.7941680074912,\n 30.932276934300717\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"293","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Snedden, Gregg 0000-0001-7821-3709","orcid":"https://orcid.org/0000-0001-7821-3709","contributorId":216669,"corporation":false,"usgs":true,"family":"Snedden","given":"Gregg","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":883269,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70248366,"text":"ofr20231063 - 2023 - Summary of the history and research of the U.S. Geological Survey gas hydrate properties laboratory in Menlo Park, California, active from 1993 to 2022","interactions":[],"lastModifiedDate":"2023-09-11T10:52:43.087532","indexId":"ofr20231063","displayToPublicDate":"2023-09-08T15:16:47","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":"2023-1063","displayTitle":"Summary of the History and Research of the U.S. Geological Survey Gas Hydrate Properties Laboratory in Menlo Park, California, Active from 1993 to 2022","title":"Summary of the history and research of the U.S. Geological Survey gas hydrate properties laboratory in Menlo Park, California, active from 1993 to 2022","docAbstract":"The U.S. Geological Survey (USGS) Clathrate Hydrate Properties Project, active from 1993 to 2022 in Menlo Park, California, stemmed from an earlier project on the properties of planetary ices supported by the National Aeronautics and Space Administration’s (NASA’s) Planetary Geology and Geophysics Program. We took a material science approach in both projects, emphasizing chemical purity of samples, having controlled grain size and grain texture, and having verified crystal structures and phase relations. A foundational contribution from our USGS Gas Hydrate Properties Laboratory (GHPL) was in demonstrating the ability to reproducibly create such pure clathrate hydrate samples for study. Clathrate sample synthesis was achieved by heating sieved and weighed pure granular water ice in the presence of cold clathrate-forming gas or liquid. During heating, the ice melts at the grain scale and reacts with the gas to form clathrate. The resulting material has the desired uniformity and purity, with known intergranular porosity; our subsequent measurements showed that these clathrates exhibited the established clathrate structures and phase relations. This novel synthesis method was successful in creating clathrates of pure methane, ethane, propane, carbon dioxide, and multi-component gases. By mixing sand or silt with granular ice, we were also able to make clathrate-sediment aggregates with controlled grain textures. This simple method, adopted by many others in the community, permitted us to measure the physical and chemical properties of well-characterized and well-crystallized clathrates and clathrate/sediment aggregates. At about the same time, we adapted conventional scanning electron microscopy to cryogenic conditions for analysis of grain-scale characteristics of clathrates made in the GHPL as well as those collected from nature by drill core. The uniformity and reproducibility of our samples also allowed us to investigate how clathrates respond to environmental changes in chemistry, temperature, and pressure: we measured chemical exchange rates with dissolved gas species—such as noble gases and chlorofluorocarbons—as well as rates of clathrate dissolution and decomposition. These advances include the first accurate mapping of the conditions that promote the remarkable process of “anomalous preservation” at room pressure, a metastability that offers potential application for low-cost and safe transportation of natural gas from gas fields far from pipelines.
Another advancement stemming from the GHPL was the compaction of as-synthesized porous clathrates to nearly full density by applying external pressure using three different techniques. Compaction allows for high-accuracy measurements of many fundamental physical and chemical properties of these materials, such as elastic wavespeeds and moduli, complete thermal properties, decomposition rates, thermal expansion, and clathrate equations of state. These properties and others, in turn, have helped USGS scientists to interpret geophysical well logs and active geophysical surveys, as well as model the rates of gas production from hydrate deposits in nature.
Studying this class of icy minerals that occur in abundance on Earth and in the outer solar system has been a fascinating laboratory journey. Here, we summarize the history and major findings of the USGS GHPL in Menlo Park, including both in-house research as well as findings from the synergistic collaborations with other agencies and institutes that were key to the success of our laboratory. The Menlo Park GHPL was more formally incorporated within the USGS Gas Hydrates Project, a collaboration among multiple USGS Science Centers, in the early 2000s under the leadership of Deborah Hutchinson, and now under the leadership of Carolyn Ruppel and Timothy Collett.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231063","usgsCitation":"Stern, L.A., and Kirby, S.H., 2023, Summary of the history and research of the U.S. Geological Survey gas hydrate properties laboratory in Menlo Park, California, active from 1993 to 2022: U.S. Geological Survey Open-File Report 2023–1063, 29 p., https://doi.org/10.3133/ofr20231063.","productDescription":"v, 29 p.","numberOfPages":"29","onlineOnly":"Y","ipdsId":"IP-140366","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":420685,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1063/images"},{"id":420683,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1063/ofr20231063.pdf","text":"Report","size":"5 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":420682,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1063/covrthb.jpg"}],"contact":"Earthquake Science Center
U.S. Geological Survey
350 N. Akron Road
Moffett Field, CA 94035
The western U.S. is experiencing increasing rain to snow ratios due to climate change, and scientists are uncertain how changing recharge patterns will affect future groundwater-surface water connection. We examined how watershed topography and streambed hydraulic conductivity impact groundwater age and stream discharge at eight sites along a headwater stream within the Manitou Experimental Forest, CO USA. To do so, we measured: (a) continuous stream and groundwater discharge/level and specific conductivity from April to November 2021; (b) biweekly stream and groundwater chemistry; (c) groundwater chlorofluorocarbons and tritium in spring and fall; (d) streambed hydraulic conductivity; and (e) local slope. We used the chemistry data to calculate fluorite saturation states that were used to inform end-member mixing analysis of streamflow source. We then combined chlorofluorocarbon and tritium data to estimate the age composition of riparian groundwater. Our data suggest that future stream drying is more probable where local slope is steep and streambed hydraulic conductivity is high. In these areas, groundwater source shifted seasonally, as indicated by age increases, and we observed a high fraction of groundwater in streamflow, primarily interflow from adjacent hillslopes. In contrast, where local slope is flat and streambed hydraulic conductivity is low, streamflow is more likely to persist as groundwater age was seasonally constant and buffered by storage in alluvial sediments. Groundwater age and streamflow paired with characterization of watershed topography and subsurface characteristics enabled identification of likely controls on future stream drying patterns.
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Much of eastern and south-central Pennsylvania received 5 to 10 inches of rain, and most of the rainfall fell within little more than 6 hours. Southeastern Pennsylvania experienced widespread, substantial flooding, and the city of Philadelphia and surrounding areas were particularly affected by the flooding. U.S. Geological Survey (USGS) streamgages registered peak streamflows of record at 19 locations, and 52 locations experienced top 5 peak streamflows for the period of record and an annual exceedance probability estimate of at least 10 percent. During this September 2021 flood event, USGS personnel made over 60 streamflow measurements at streamgages in Pennsylvania using direct and indirect methods. Many of those streamflow measurements were made to verify or improve the accuracy, extent, or development of new stage-streamflow relations at streamgages operated by the USGS. After the floodwaters receded, USGS personnel identified and documented a total of 338 high-water marks in Pennsylvania, noting such things as their general description, location, height above land surface, and quality. Many of these high-water marks were used to create five flood-documentation maps for selected communities in southeastern Pennsylvania that experienced substantial flooding because of the remnants of Hurricane Ida. Digital datasets of the inundated areas, mapped boundaries, and water depth are available (Stuckey and Conlon, 2023).
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\"}}]}","edition":"Version 1.0: September 7, 2023; Version 1.1: September 28, 2023","contact":"Director, Pennsylvania Water Science Center
U.S. Geological Survey
215 Limekiln Road
New Cumberland, PA 170
Fern Cave in Jackson County, Alabama, is a 15.6-mile-long (25.1-kilometer) cave system, managed by the U.S. Fish and Wildlife Service and Southeastern Cave Conservancy, that has the second highest biodiversity of any cave in the southeastern United States. Groundwater in karst ecosystems is known to be susceptible to impacts from human-induced land-use activities in watersheds that contribute recharge to the groundwater system. To provide the U.S. Fish and Wildlife Service with necessary baseline information on the groundwater flow system in Fern Cave, the U.S. Geological Survey and the Kentucky Geological Survey conducted a series of dye traces during 2019–21 to delineate the watershed recharging the cave system. The dye traces identified two separate streams that flow through the cave and a recharge area of 1.73 square miles (4.48 square kilometers) draining to the cave system. Current land use within the recharge area is dominated by deciduous forest with minimal additional land use types, indicating a low potential for undesirable effects to the cave by anthropogenic sources.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3506","issn":"2329-132X","collaboration":"Prepared in cooperation with Kentucky Geological Survey and U.S. Fish and Wildlife Service","programNote":"Water Availability and Use Science Program","usgsCitation":"Miller, B.V., and Tobin, B., Mapping karst groundwater flow paths and delineating recharge areas for Fern Cave, Alabama, through the use of dye tracing: U.S. Geological Survey Scientific Investigations Map 3506, 2 sheets, https://doi.org/10.3133/sim3506.","productDescription":"2 Sheets: 42.50 x 36.00; Data Releases","numberOfPages":"2","onlineOnly":"Y","ipdsId":"IP-136078","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":420569,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9AE0LQR","text":"USGS Data Release","linkHelpText":"Mapping karst groundwater flow paths and delineating recharge areas for Fern Cave, Alabama through the use of dye tracing"},{"id":420568,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9KZCM54","text":"USGS Data Release","linkHelpText":"National Land Cover Database (NLCD) 2019 Products (ver. 2.0, June 2021)"},{"id":500212,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115246.htm","linkFileType":{"id":5,"text":"html"}},{"id":420571,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://nwis.waterdata.usgs.gov/nwis/wys_rpt?dv_ts_ids=&2629&adr_begin_date=2019-10-01&adr_end_date=2020-09-30&site_no=03574500&agency_cd=USGS","text":"USGS water-year summary 2020","linkHelpText":"03574500 Paint Rock River near Woodville, AL"},{"id":420570,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://nwis.waterdata.usgs.gov/nwis/wys_rpt?dv_ts_ids=&2629&adr_begin_date=2018-10-01&adr_end_date=2019-09-30&site_no=03574500&agency_cd=USGS","text":"USGS water-year summary 2019","linkHelpText":"03574500 Paint Rock River near Woodville, AL"},{"id":420567,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3506/sim3506_sheet_2.pdf","text":"SIM 3506 sheet 2","size":"10.9 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":420572,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3506/coverthb.jpg"},{"id":420566,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3506/sim3506_sheet_1.pdf","text":"SIM 3506 sheet 1","size":"18.3 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Alabama","county":"Jackson County","otherGeospatial":"Fern Cave","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -86.2917,\n 34.7\n ],\n [\n -86.333,\n 34.7\n ],\n [\n -86.333,\n 34.6458\n ],\n [\n -86.2917,\n 34.6458\n ],\n [\n -86.2917,\n 34.7\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
640 Grassmere Park, Suite 100
Nashville, TN 37211
Insufficient water sample volumes can be a limiting factor for detecting species with environmental DNA (eDNA) from aquatic habitats. We compared detections of freshwater mussel (Unionidae) communities using large water sample volumes and dead-end hollow fiber ultrafiltration (D-HFUF or DEUF) with traditional eDNA filtration methods that use relatively small water sample volumes. Unionid species were detected in approximately 50-L D-HFUF eDNA samples with two mitochondrial DNA metabarcoding markers (COI and ND1) and compared to species detection results from eDNA captured from commonly used 1-L samples filtered with polyethersulfone (PES) filters at three lotic sites in Georgia and Missouri. Of the 431,560 COI and 1,035,472 ND1 reads from all environmental samples of both filter types that passed quality control, 95% (410,755 reads) of COI reads and 85% (883,472 reads) of ND1 reads were assigned to a unionid species. Nineteen different freshwater mussel species were detected across all D-HFUF samples, and 11 species were detected across all PES samples. Reads assigned to the genus Elliptio could not be resolved beyond the genus level with either marker. From D-HFUF samples, 15 and 16 mussel species were detected with the COI and ND1 markers, respectively. From PES samples, nine and seven species were detected with the COI and ND1 markers, respectively. More mussel species were detected at each site in D-HFUF samples than in PES samples regardless of whether results from both markers were combined or evaluated separately. Our results demonstrate the merit of further exploration and optimization of D-HFUF for capturing eDNA from high-volume water samples to facilitate detection of unionids and likely other aquatic organisms.
A synoptic water quality study was implemented in Warden Gulch, a headwater stream affected by metals that are contributed by both natural and mining-impacted sources. Warden Gulch is a tributary to Peru Creek (Colorado, USA), where emplacement of a mine tunnel bulkhead and other remedial actions have improved water quality upstream of Warden Gulch. The goal of this study was to identify individual source contributions to Warden Gulch and determine if additional remedial actions were warranted. To this end, trace metal loading was quantified from various sources including an actively draining mine. Although highly concentrated waste streams from mining-impacted sites degrade water quality, natural contributions from unmined areas within the Warden Gulch watershed are the dominant sources of metal loading. Further, some mining-impacted sources are associated with diffuse groundwater inflows that may not be amenable to clean up, due to the diffuse nature of the sources and the associated cost. Mining-impacted sources that are amenable to clean up may therefore represent a small portion of the overall metal loading to Warden Gulch. Remedial measures directed at these sources may not substantially improve the water quality of Peru Creek and the larger Snake River watershed.