Mature oil fields potentially contain multiple fluid migration pathways toward protected groundwater (total dissolved solids, TDS, in nonexempted aquifer <10,000 mg/L) because of their extensive development histories. Time-series data for water use, fluid pressures, oil-well construction, and geochemistry from the South Belridge and Lost Hills mature oil fields in California are used to explore the roles of injection/production of oil-field water and well-integrity issues in fluid migration. Injection/production of oil-field water modified hydraulic gradients in both oil fields, resulting in chemical transport from deeper groundwater and hydrocarbon-reservoir systems to aquifers in the oil fields. Those aquifers are used for water supply outside the oil-field boundaries. Oil wells drilled before 1976 can be fluid migration pathways because a relatively large percentage of them have >10 m of uncemented annulus that straddles oil-well casing damage and/or the base of groundwater with TDS <10,000 mg/L. The risk of groundwater-quality degradation is higher when wells with those risk factors occur in areas with upward hydraulic gradients created by positive net injection, groundwater withdrawals, or combinations of these variables. The complex changes in hydrologic conditions and groundwater chemistry likely would not have been discovered in the absence of years to decades of monitoring data for groundwater elevations and chemistry, and installation of monitoring wells in areas with overlapping risk factors. Important monitoring concepts based on results from this and other studies include monitoring hydrocarbon-reservoir and groundwater systems at multiple spatiotemporal scales and maintaining transparency and accessibility of data and analyses. This analysis focuses on two California oil fields, but the methods used and processes affecting fluid migration could be relevant in other oil fields where substantial injection/production of oil-field water occurs and oil-well integrity is of concern.
Contamination from acid mine drainage affects ecosystems and usability of groundwater for domestic and municipal purposes. The Captain Jack Superfund Site outside of Ward, Boulder County, Colorado, USA, hosts a draining mine adit that was remediated through emplacement of a hydraulic bulkhead to preclude acid mine drainage from entering nearby Lefthand Creek. During impoundment of water within the mine workings in 2020, a diverse and novel dataset of stable isotopes of water, sulfate, and carbon (δ2H, δ18OH2O, δ18OSO4, δ34S, δ13CDIC), rare earth elements, and environmental tracers (noble gases and tritium) were collected to understand groundwater recharge and mixing, mechanisms of sulfide oxidation and water-rock interaction, and the influence of remediation on the hydrologic and geochemical system. Water isotopes indicate that groundwater distal from the mine workings has seasonally variable recharge sources whereas water within the workings has a distinctive composition with minimal temporal variability. Sulfate isotopes indicate that sulfide oxidation occurs both within the mine workings and in adjacent igneous dikes, and that sulfide oxidation may occur under suboxic conditions with ferric iron as the oxidant. Carbon isotopes track the neutralization of acidic waters and the carbon mass budget of the system. Rare earth elements corroborate stable isotopes in indicating groundwater compartmentalization, and additionally illustrate enhanced mineral weathering in the mine workings. Environmental tracers indicate mixing of modern and pre-modern groundwater and inform timelines that active remediation may be needed. Together these datasets provide a useful template for similar investigations of abandoned mine sites where physical mixing processes, sources of solute loading, or remediation timeframes are of importance.
A range of hydrologic responses can be observed in steep, recently burned terrain, which makes predicting the spatial distribution of large debris flows challenging. Studies from rainfall-induced landslides in unburned areas show evidence of hydroclimatic tuning of landslide triggering, such that the spatial distribution of events is best predicted by the observed rainfall anomaly relative to climatic norms rather than by absolute rainfall. In this paper, we test whether the spatial distribution of debris flows in response to rainfall can be similarly predicted by rainfall anomaly. The 520 km2 Dolan Fire burn scar in Monterey County, California, USA, spans a sharp hydroclimatic gradient and experienced a widespread storm in January 2021 that triggered floods and debris flows, providing a natural experiment in which to test this hypothesis. In this study, we use remote and field methods to map debris-flow response and examine its spatial heterogeneity. Together with rainfall data, our mapping reveals that the observed anomalies in peak 15-min rainfall intensity (I15) relative to the intensity of the 1-yr return interval storm predict debris-flow occurrence better than the absolute peak I15. Our findings indicate that debris-flow processes and threshold rainfall required for debris-flow initiation may be tuned to local hydroclimate.
","conferenceTitle":"8th International Conference on Debris Flow Hazard Mitigation","conferenceDate":"June 26-29, 2023","conferenceLocation":"Turin, Italy","language":"English","publisher":"EDP Sciences","doi":"10.1051/e3sconf/202341504003","usgsCitation":"Cavagnaro, D.B., McCoy, S., Thomas, M.A., Kostelnik, J., and Lindsay, D.N., 2023, The spatial distribution of debris flows in relation to observed rainfall anomalies: Insights from the Dolan Fire, California, 8th International Conference on Debris Flow Hazard Mitigation, v. 415, Turin, Italy, June 26-29, 2023, 04003, 4 p., https://doi.org/10.1051/e3sconf/202341504003.","productDescription":"04003, 4 p.","ipdsId":"IP-142506","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":442361,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1051/e3sconf/202341504003","text":"Publisher Index Page"},{"id":420912,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Dolan fire","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.7,\n 36.3\n ],\n [\n -121.7,\n 35.9\n ],\n [\n -121.2,\n 35.9\n ],\n [\n -121.2,\n 36.3\n ],\n [\n -121.7,\n 36.3\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"415","noUsgsAuthors":false,"publicationDate":"2023-08-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Cavagnaro, David B.","contributorId":267181,"corporation":false,"usgs":false,"family":"Cavagnaro","given":"David","email":"","middleInitial":"B.","affiliations":[{"id":16686,"text":"University of Nevada, Reno","active":true,"usgs":false}],"preferred":false,"id":883279,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCoy, Scott W.","contributorId":267182,"corporation":false,"usgs":false,"family":"McCoy","given":"Scott W.","affiliations":[{"id":16686,"text":"University of Nevada, Reno","active":true,"usgs":false}],"preferred":false,"id":883280,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thomas, Matthew A. 0000-0002-9828-5539 matthewthomas@usgs.gov","orcid":"https://orcid.org/0000-0002-9828-5539","contributorId":200616,"corporation":false,"usgs":true,"family":"Thomas","given":"Matthew","email":"matthewthomas@usgs.gov","middleInitial":"A.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":883281,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kostelnik, Jaime 0000-0002-1817-5461","orcid":"https://orcid.org/0000-0002-1817-5461","contributorId":300717,"corporation":false,"usgs":true,"family":"Kostelnik","given":"Jaime","email":"","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":883282,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lindsay, Donald N.","contributorId":216337,"corporation":false,"usgs":false,"family":"Lindsay","given":"Donald","email":"","middleInitial":"N.","affiliations":[{"id":12640,"text":"California Geological Survey","active":true,"usgs":false}],"preferred":false,"id":883283,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70247841,"text":"70247841 - 2023 - Assessing environmental change associated with early Eocene hyperthermals in the Atlantic Coastal Plain, USA","interactions":[],"lastModifiedDate":"2023-08-22T12:08:00.858115","indexId":"70247841","displayToPublicDate":"2023-08-17T07:06:14","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1250,"text":"Climate of the Past","active":true,"publicationSubtype":{"id":10}},"title":"Assessing environmental change associated with early Eocene hyperthermals in the Atlantic Coastal Plain, USA","docAbstract":"Eocene transient global warming events (hyperthermals) can provide insight into a future warmer world. While much research has focused on the Paleocene–Eocene Thermal Maximum (PETM), hyperthermals of a smaller magnitude can be used to characterize climatic responses over different magnitudes of forcing. This study identifies two events, namely the Eocene Thermal Maximum 2 (ETM2 and H2), in shallow marine sediments of the Eocene-aged Salisbury Embayment of Maryland, based on magnetostratigraphy, calcareous nannofossil, and dinocyst biostratigraphy, as well as the recognition of negative stable carbon isotope excursions (CIEs) in biogenic calcite. We assess local environmental change in the Salisbury Embayment, utilizing clay mineralogy, marine palynology, δ18O of biogenic calcite, and biomarker paleothermometry (TEX86). Paleotemperature proxies show broad agreement between surface water and bottom water temperature changes. However, the timing of the warming does not correspond to the CIE of the ETM2 as expected from other records, and the highest values are observed during H2, suggesting factors in addition to pCO2 forcing have influenced temperature changes in the region. The ETM2 interval exhibits a shift in clay mineralogy from smectite-dominated facies to illite-rich facies, suggesting hydroclimatic changes but with a rather dampened weathering response relative to that of the PETM in the same region. Organic walled dinoflagellate cyst assemblages show large fluctuations throughout the studied section, none of which seem systematically related to CIE warming. These observations are contrary to the typical tight correspondence between climate change and assemblages across the PETM, regionally and globally, and ETM2 in the Arctic Ocean. The data do indicate very warm and (seasonally) stratified conditions, likely salinity-driven, across H2. The absence of evidence for strong perturbations in local hydrology and nutrient supply during ETM2 and H2, compared to the PETM, is consistent with the less extreme forcing and the warmer pre-event baseline, as well as the non-linear response in hydroclimates to greenhouse forcing.
Despite increasing wildfires, few studies have investigated seasonal water quality responses to wildfire characteristics (e.g., burn severity) across a large number of lakes. We monitored 30 total lakes (15 burned, 15 control) monthly following the Greenwood Fire in Minnesota, USA, a lake-rich region with historically prevalent wildfire. We found increases in median concentrations of total nitrogen (68%), total phosphorus (70%), dissolved organic carbon (127%), total suspended solids (71%), and reduced water clarity (48%) and pH (0.45) in burned lakes. Post-wildfire responses in drainage lakes were often persistent or cumulative throughout the open-water season, compared to isolated lakes. Total phosphorus (TP) increased linearly with watershed high-severity burns, and shoreline high-severity burns explained more variation in TP than lake morphometry and watershed variables. Post-wildfire chlorophyll-a responses were nonsignificant and inconsistent, possibly due to light limitation. Our results suggest that increasing wildfires have significant potential to affect water quality of inland lakes.
Methane (CH4) is a potent greenhouse gas and its concentrations have tripled in the atmosphere since the industrial revolution. There is evidence that global warming has increased CH4 emissions from freshwater ecosystems1,2, providing positive feedback to the global climate. Yet for rivers and streams, the controls and the magnitude of CH4 emissions remain highly uncertain3,4. Here we report a spatially explicit global estimate of CH4 emissions from running waters, accounting for 27.9 (16.7–39.7) Tg CH4 per year and roughly equal in magnitude to those of other freshwater systems5,6. Riverine CH4 emissions are not strongly temperature dependent, with low average activation energy (EM = 0.14 eV) compared with that of lakes and wetlands (EM = 0.96 eV)1. By contrast, global patterns of emissions are characterized by large fluxes in high- and low-latitude settings as well as in human-dominated environments. These patterns are explained by edaphic and climate features that are linked to anoxia in and near fluvial habitats, including a high supply of organic matter and water saturation in hydrologically connected soils. Our results highlight the importance of land–water connections in regulating CH4 supply to running waters, which is vulnerable not only to direct human modifications but also to several climate change responses on land.
","language":"English","publisher":"Nature Publications","doi":"10.1038/s41586-023-06344-6","usgsCitation":"Rocher-Ros, G., Stanley, E.H., Loken, L.C., Casson, N.J., Raymond, P.A., Liu, S., Amatulli, G., and Sponseller, R.A., 2023, Global methane emissions from rivers and streams: Nature, v. 621, p. 530-535, https://doi.org/10.1038/s41586-023-06344-6.","productDescription":"6 p.","startPage":"530","endPage":"535","ipdsId":"IP-146294","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":442410,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41586-023-06344-6","text":"Publisher Index Page"},{"id":421888,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"621","noUsgsAuthors":false,"publicationDate":"2023-08-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Rocher-Ros, Gerard","contributorId":329670,"corporation":false,"usgs":false,"family":"Rocher-Ros","given":"Gerard","email":"","affiliations":[{"id":12666,"text":"Swedish University of Agricultural Sciences","active":true,"usgs":false}],"preferred":false,"id":886050,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stanley, Emily H.","contributorId":55725,"corporation":false,"usgs":false,"family":"Stanley","given":"Emily","email":"","middleInitial":"H.","affiliations":[{"id":12951,"text":"Center for Limnology, University of Wisconsin Madison","active":true,"usgs":false}],"preferred":false,"id":886051,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":886052,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Casson, Nora J.","contributorId":169271,"corporation":false,"usgs":false,"family":"Casson","given":"Nora","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":886053,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Raymond, Peter A.","contributorId":172876,"corporation":false,"usgs":false,"family":"Raymond","given":"Peter","email":"","middleInitial":"A.","affiliations":[{"id":17883,"text":"Yale School of Forestry and Environmental Studies, New Haven, CT","active":true,"usgs":false}],"preferred":false,"id":886054,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Liu, Shaoda","contributorId":257246,"corporation":false,"usgs":false,"family":"Liu","given":"Shaoda","email":"","affiliations":[{"id":51989,"text":"Yale School of Forestry and Environmental Studies, 195 Prospect Street, New Haven, CT, USA","active":true,"usgs":false}],"preferred":false,"id":886055,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Amatulli, Giuseppe","contributorId":330856,"corporation":false,"usgs":false,"family":"Amatulli","given":"Giuseppe","email":"","affiliations":[{"id":37550,"text":"Yale University","active":true,"usgs":false}],"preferred":false,"id":886056,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sponseller, Ryan A.","contributorId":329667,"corporation":false,"usgs":false,"family":"Sponseller","given":"Ryan","email":"","middleInitial":"A.","affiliations":[{"id":24847,"text":"Umea University","active":true,"usgs":false}],"preferred":false,"id":886057,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70246691,"text":"sir20235068 - 2023 - Flood-inundation maps for Fourmile Creek at Silver Grove, Kentucky","interactions":[],"lastModifiedDate":"2026-03-09T17:08:29.267739","indexId":"sir20235068","displayToPublicDate":"2023-08-14T09:50:00","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-5068","displayTitle":"Flood-Inundation Maps for Fourmile Creek at Silver Grove, Kentucky","title":"Flood-inundation maps for Fourmile Creek at Silver Grove, Kentucky","docAbstract":"Digital flood-inundation maps for a 3.4-mile reach of Fourmile Creek at Silver Grove, Kentucky, were created by the U.S. Geological Survey (USGS) in cooperation with the City of Silver Grove and the U.S. Army Corps of Engineers Louisville District. Because the City of Silver Grove is subject to flooding from Fourmile Creek and the Ohio River (backwater flooding up Fourmile Creek), a set of flood-inundation maps was created, including maps for each flooding source considered independently and for possible scenarios involving flooding from both sources combined. The flood-inundation maps depict estimates of the areal extent and depth of flooding corresponding to a range of gage heights (gage height is commonly referred to as “stage,” or the water-surface elevation at a streamgage) at the USGS streamgage on Fourmile Creek at Grays Crossing at Silver Grove, Ky. (station number 03238785), and the USGS streamgage on Fourmile Creek at Highway 8 at Silver Grove, Ky. (station number 03238798). Near-real-time stages at these streamgages can be obtained from the USGS National Water Information System at https://waterdata.usgs.gov/. The USGS streamgage on the Ohio River at Cincinnati, Ohio (station number 03255000), is also important in this study because the National Weather Service (NWS) Advanced Hydrologic Prediction Service (AHPS; https://water.weather.gov/ahps/) forecasts flood hydrographs for this site (NWS AHPS site CCNO1). The peak-stage information forecast by the NWS AHPS can be used in conjunction with the maps developed in this study to show predicted areas of flood inundation.
Flood profiles were computed for the Fourmile Creek study reach by means of a one-dimensional, step-backwater hydraulic model (HEC-RAS) developed by the U.S. Army Corps of Engineers. The hydraulic model was calibrated by using the current stage-discharge relation (USGS rating number 1.1) at USGS streamgage 03238785, Fourmile Creek at Grays Crossing at Silver Grove, Ky. The model was then used to compute water-surface profiles for 83 combinations of flood stages on the Ohio River and Fourmile Creek ranging from approximately base flow to greater than a 2-percent annual exceedance probability flood in the model reach. An additional 50 water-surface profiles were computed for backwater-only flooding (from the Ohio River) for flood elevations (referenced to the North American Vertical Datum of 1988 [NAVD 88]) at 1-foot intervals referenced to USGS streamgage 03238798, Fourmile Creek at Highway 8 at Silver Grove, Ky.; these elevations ranged from approximately normal pool (460 ft, NAVD 88) to approximately a 0.2-percent annual exceedance probability flood (509 ft, NAVD 88) on the Ohio River. The computed water-surface profile information was then combined with a digital elevation model derived from light detection and ranging (lidar) data to delineate the approximate flooded areas.
The digital flood-inundation maps are available through the USGS Flood Inundation Mapper application (https://fim.wim.usgs.gov/fim/), which presents map libraries and provides detailed information on flood extent and depths for selected sites. The flood-inundation maps developed in this study, in conjunction with the real-time stage data from the USGS streamgages on Fourmile Creek at Silver Grove, Ky., and forecasted stream stages from the NWS AHPS, are intended to provide information that can help inform the public about potential flooding and provide emergency management personnel with a tool to efficiently manage emergency flood operations, such as evacuations and road closures, and assist in postflood recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235068","collaboration":"Prepared in cooperation with the City of Silver Grove and the U.S. Army Corps of Engineers Louisville District","usgsCitation":"Boldt, J.A., 2023, Flood-inundation maps for Fourmile Creek at Silver Grove, Kentucky: U.S. Geological Survey Scientific Investigations Report 2023–5068, 22 p., https://doi.org/10.3133/sir20235068.","productDescription":"Report: vii, 22 p.; Data Release","numberOfPages":"22","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-130251","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":500949,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115179.htm","linkFileType":{"id":5,"text":"html"}},{"id":418995,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9VJSH7D","text":"USGS data release","linkHelpText":"Geospatial datasets and model for the flood-inundation study of Fourmile Creek at Silver Grove, Kentucky"},{"id":418994,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5068/sir20235068.XML"},{"id":418993,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5068/images/"},{"id":418992,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235068/full","text":"Report","description":"SIR 2023-5068"},{"id":418991,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5068/sir20235068.pdf","text":"Report","size":"5.38 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5068"},{"id":418990,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5068/coverthb.jpg"}],"country":"United States","state":"Kentucky","city":"Silver Grove","otherGeospatial":"Fourmile Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -84.5333,\n 39.1333\n ],\n [\n -84.5333,\n 39.0167\n ],\n [\n -84.3583,\n 39.0167\n ],\n [\n -84.3583,\n 39.1333\n ],\n [\n -84.5333,\n 39.1333\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Ohio-Kentucky-Indiana Water Science Center
U.S. Geological Survey
5957 Lakeside Blvd.
Indianapolis, IN 46278-1996
Water withdrawn from rivers and streams accounts for approximately 80 percent of the public water supply in West Virginia. Localized and (or) seasonal droughts may threaten future water availability in the state, particularly in rural communities located in the headwaters of unregulated watersheds. Monthly water withdrawal data obtained from the West Virginia Department of Environmental Protection’s Large Quantity User program’s regulatory database was used to calculate all-time, seasonal, and monthly 75th quantile withdrawal rates for 109 public water system (PWS) intakes withdrawing from surface waters in West Virginia. A drought-vulnerability assessment value was calculated by comparing PWS withdrawal rates to the 1-day, 10-year hydrologically based streamflow statistic (1Q10) for 71 of the 109 PWS in locations with valid streamflow statistics. Withdrawal rates were evaluated against thresholds representing different levels of drought-related impacts from the West Virginia interagency drought plan and ecological-flow literature. The drought-vulnerability assessment found 33 of 71 PWS have 75th quantile withdrawal rates greater than 100 percent of 1Q10 streamflow. Forty-five of 71 PWS have 75th quantile withdrawal rates more than 10 percent of 1Q10 streamflow, suggesting some level of ecological impairment during severe drought. Additionally, a publicly available, near real-time drought-awareness web tool was created to compare the estimated withdrawal rate for 109 PWS to forecast streamflows from the National Water Model to support decision-making for emergency and water managers.
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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
The U.S. Geological Survey (USGS) has a long history of working cooperatively with the South Carolina Department of Transportation to develop methods for estimating the magnitude and frequency of floods for rural and urban streams that have minimal to no regulation or tidal influence. As part of those previous investigations, flood-frequency estimates also have been generated for selected streamgages on regulated streams. This report assesses the effects of impoundments on flood-frequency characteristics by comparing annual exceedance probability (AEP) streamflows from pre- and post-regulated (before and after impoundment) periods at 18 long-term USGS streamgages, which is defined as a streamgage with 30 or more years of record, in Georgia, South Carolina, and North Carolina. For an assessment of how differences in such statistics can be influenced by period of record and hydrologic conditions captured in those records, which could be considered as natural variability, AEP streamflows at an additional 18 long-term USGS streamgages that represent unregulated conditions in those three States were computed and compared for the first and last half of those records.
Of the 18 long-term streamgages with pre- and post-regulated periods of record, 17 streamgages had both peak streamflows and daily mean streamflows available. To further assess how impoundments may influence a broader range of streamflow characteristics, The Nature Conservancy’s Indicators of Hydrologic Alteration software was used to compare selected streamflow characteristics generated from daily mean streamflows for pre- and post-regulated periods of record at 16 of those long-term streamgages. For comparison of the natural variability of such streamflow statistics, two periods of record (first half and last half) also were compared at 17 of the 18 long-term streamgages on unregulated streams. The remaining long-term streamgage on an unregulated stream included in this report had only annual peak streamflows and, therefore, was not included in the hydrologic alteration analysis.
In a separate USGS investigation completed in 2023, flood-frequency statistics for the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent AEP streamflows (also known as the 2-, 5-, 10-, 25-, 50-, 100-, 200-, and 500-year recurrence interval streamflows, respectively) were computed for 72 streamgages on regulated streams in Georgia, South Carolina, and North Carolina. Of those 72 streamgages, 29 streamgages were found to be redundant, which is a situation where the drainage basin of one streamgage is contained inside another (nested) and the two basins are of similar size. For the remaining 43 streamgages, 39 had basins where 75 percent or more of the drainage area was above the Fall Line. Those 39 streamgages were included in this investigation to develop regional regression equations that can be used to estimate the flood-frequency statistics at ungaged locations on regulated streams in Georgia, South Carolina, and North Carolina in which 75 percent or more of the drainage basin is located above the Fall Line. The flood-frequency regression equations are functions of drainage area and maximum storage index computed for upstream reservoirs.
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\"}}]}","contact":"Director, South Atlantic Water Science Center
U.S. Geological Survey
1770 Corporate Drive, suite 500
Norcross, GA 30093
Dam removal is used increasingly to restore aquatic ecosystems and remove unnecessary or high-risk infrastructure. As the number of removals increases, there is a growing understanding about the hydrologic, geomorphic, and ecological responses to these removals. Most dam removal studies, however, focus on river and watershed responses to dam removal. The removal of two dams on the Elwha River provided a unique opportunity to characterize the response of nearshore (coastal) ecosystems. We conducted SCUBA surveys between 2011 and 2022 to quantify trajectories of change in a nearshore ecosystem during and after dam removal. We focused on the degree to which the abundances of kelp, benthic invertebrates, and fish changed in response to patterns of sediment fluxes during and after dam removal. Our findings point to two pathways of response depending on the disturbance mechanism and species type. Sites with persistent sediment deposition were characterized by wholesale community changes that did not recover to a before dam removal condition. Instead, the sites were colonized by new species that were largely absent prior to dam removal. Sites that experienced high turbidity but lacked persistent seafloor deposition were primarily characterized by a reduction in the abundance of kelp and other algae during dam removal and a rapid recovery after sediment flux to the nearshore declined. Dam removal influences on invertebrates and fish at these sites were more variable, benefiting some species and disadvantaging others. In addition to dam removal, sea star wasting syndrome and a marine heatwave exerted distinct controls on subtidal communities during the same period. The loss of the predatory sea star Pycnopodia helianthoides was associated with gains in some of its prey species, and kelp community changes reflected regional trends in ocean temperature and kelp abundance. The results presented here have important implications for understanding the response of marine ecosystems to future dam removals and similar sediment perturbation events.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fevo.2023.1233895","usgsCitation":"Rubin, S.P., Foley, M.M., Miller, I.M., Stevens, A.W., Warrick, J.A., Berry, H.D., Elder, N.E., Beirne, M.M., and Gelfenbaum, G., 2023, Nearshore subtidal community response during and after sediment disturbance associated with dam removal: Frontiers in Ecology and Evolution, v. 11, 1233895, 21 p., https://doi.org/10.3389/fevo.2023.1233895.","productDescription":"1233895, 21 p.","ipdsId":"IP-154198","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":442454,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fevo.2023.1233895","text":"Publisher Index Page"},{"id":435228,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9NCE4FE","text":"USGS data 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The paper describes the approach for generating the dataset, provides an initial evaluation, including biases, and indicates how interested users can access the data. The motivation for creating this National Center for Atmospheric Research (NCAR)–U.S. Geological Survey (USGS) collaborative dataset is to provide research and end-user communities with a high-resolution, self-consistent, long-term, continental-scale hydroclimate dataset appropriate for forcing hydrological models and conducting hydroclimate scientific analyses over the conterminous United States. The data are archived and accessible on the USGS Black Pearl tape system and on the NCAR supercomputer Campaign storage system.
","language":"English","publisher":"American Meteorological Society","doi":"10.1175/BAMS-D-21-0326.1","usgsCitation":"Rasmussen, R.M., Chen, F., Liu, C.H., Ikeda, K., Prein, A., Kim, J., Schneider, T., Dai, A., Gochis, D., Dugger, A., Zhang, Y., Jaye, A., Dudhia, J., He, C., Harrold, M., Xue, L., Chen, S., Newman, A., Dougherty, E., Abolafia-Rozenzweig, R., Lybarger, N., Viger, R.J., Lesmes, D.P., Skalak, K., Brakebill, J., Cline, D.W., Dunne, K.A., Rasmussen, K., and Miguez-Macho, G., 2023, CONUS404: The NCAR-USGS 4-km long-term regional hydroclimate reanalysis over the CONUS: Bulletin of the American Meteorological Society, v. 104, no. 8, p. 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Huffington Department of Earth Sciences, Southern Methodist University, Dallas, TX 75275, USA","active":true,"usgs":false}],"preferred":false,"id":883588,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Schneider, T.","contributorId":216061,"corporation":false,"usgs":false,"family":"Schneider","given":"T.","affiliations":[],"preferred":false,"id":883589,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Dai, A.","contributorId":329886,"corporation":false,"usgs":false,"family":"Dai","given":"A.","email":"","affiliations":[{"id":24610,"text":"NCAR","active":true,"usgs":false}],"preferred":false,"id":883590,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Gochis, D.","contributorId":329888,"corporation":false,"usgs":false,"family":"Gochis","given":"D.","affiliations":[{"id":24610,"text":"NCAR","active":true,"usgs":false}],"preferred":false,"id":883591,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Dugger, A.","contributorId":329890,"corporation":false,"usgs":false,"family":"Dugger","given":"A.","email":"","affiliations":[{"id":24610,"text":"NCAR","active":true,"usgs":false}],"preferred":false,"id":883592,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Zhang, Y.","contributorId":274978,"corporation":false,"usgs":false,"family":"Zhang","given":"Y.","affiliations":[{"id":13360,"text":"Auburn University","active":true,"usgs":false}],"preferred":false,"id":883593,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Jaye, A.","contributorId":329892,"corporation":false,"usgs":false,"family":"Jaye","given":"A.","email":"","affiliations":[{"id":24610,"text":"NCAR","active":true,"usgs":false}],"preferred":false,"id":883594,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Dudhia, J.","contributorId":329895,"corporation":false,"usgs":false,"family":"Dudhia","given":"J.","email":"","affiliations":[{"id":24610,"text":"NCAR","active":true,"usgs":false}],"preferred":false,"id":883595,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"He, C.","contributorId":76951,"corporation":false,"usgs":true,"family":"He","given":"C.","email":"","affiliations":[],"preferred":false,"id":883596,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Harrold, M.","contributorId":329899,"corporation":false,"usgs":false,"family":"Harrold","given":"M.","email":"","affiliations":[{"id":24610,"text":"NCAR","active":true,"usgs":false}],"preferred":false,"id":883597,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Xue, L.","contributorId":329901,"corporation":false,"usgs":false,"family":"Xue","given":"L.","affiliations":[{"id":24610,"text":"NCAR","active":true,"usgs":false}],"preferred":false,"id":883598,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Chen, S.","contributorId":7856,"corporation":false,"usgs":true,"family":"Chen","given":"S.","affiliations":[],"preferred":false,"id":883599,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Newman, A.","contributorId":32791,"corporation":false,"usgs":true,"family":"Newman","given":"A.","affiliations":[],"preferred":false,"id":883600,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Dougherty, E.","contributorId":329905,"corporation":false,"usgs":false,"family":"Dougherty","given":"E.","email":"","affiliations":[{"id":24610,"text":"NCAR","active":true,"usgs":false}],"preferred":false,"id":883601,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Abolafia-Rozenzweig, R.","contributorId":329908,"corporation":false,"usgs":false,"family":"Abolafia-Rozenzweig","given":"R.","email":"","affiliations":[{"id":24610,"text":"NCAR","active":true,"usgs":false}],"preferred":false,"id":883602,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Lybarger, N.","contributorId":329911,"corporation":false,"usgs":false,"family":"Lybarger","given":"N.","email":"","affiliations":[{"id":24610,"text":"NCAR","active":true,"usgs":false}],"preferred":false,"id":883603,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Viger, Roland J. 0000-0003-2520-714X rviger@usgs.gov","orcid":"https://orcid.org/0000-0003-2520-714X","contributorId":168799,"corporation":false,"usgs":true,"family":"Viger","given":"Roland","email":"rviger@usgs.gov","middleInitial":"J.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":883604,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Lesmes, David P. 0000-0003-1336-3241","orcid":"https://orcid.org/0000-0003-1336-3241","contributorId":228792,"corporation":false,"usgs":true,"family":"Lesmes","given":"David","email":"","middleInitial":"P.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":883605,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Skalak, Katherine 0000-0003-4122-1240 kskalak@usgs.gov","orcid":"https://orcid.org/0000-0003-4122-1240","contributorId":3990,"corporation":false,"usgs":true,"family":"Skalak","given":"Katherine","email":"kskalak@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":883606,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Brakebill, John 0000-0001-9235-6810","orcid":"https://orcid.org/0000-0001-9235-6810","contributorId":211038,"corporation":false,"usgs":true,"family":"Brakebill","given":"John","email":"","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":883608,"contributorType":{"id":1,"text":"Authors"},"rank":25},{"text":"Cline, Donald Walter 0009-0003-9161-9991","orcid":"https://orcid.org/0009-0003-9161-9991","contributorId":329914,"corporation":false,"usgs":true,"family":"Cline","given":"Donald","email":"","middleInitial":"Walter","affiliations":[{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true}],"preferred":true,"id":883607,"contributorType":{"id":1,"text":"Authors"},"rank":26},{"text":"Dunne, Krista A. 0000-0002-1220-6140 kadunne@usgs.gov","orcid":"https://orcid.org/0000-0002-1220-6140","contributorId":203816,"corporation":false,"usgs":true,"family":"Dunne","given":"Krista","email":"kadunne@usgs.gov","middleInitial":"A.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":883609,"contributorType":{"id":1,"text":"Authors"},"rank":27},{"text":"Rasmussen, K.","contributorId":329918,"corporation":false,"usgs":false,"family":"Rasmussen","given":"K.","email":"","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":883610,"contributorType":{"id":1,"text":"Authors"},"rank":28},{"text":"Miguez-Macho, G.","contributorId":329921,"corporation":false,"usgs":false,"family":"Miguez-Macho","given":"G.","affiliations":[{"id":78737,"text":"U. de Santiago de Compestelo, Spain","active":true,"usgs":false}],"preferred":false,"id":883611,"contributorType":{"id":1,"text":"Authors"},"rank":29}]}} ,{"id":70247382,"text":"sir20235083 - 2023 - Evaluation of alternative groundwater-withdrawal scenarios on water levels in Kingsbury Pond, upper Charles River Basin, eastern Massachusetts","interactions":[],"lastModifiedDate":"2026-03-12T20:58:29.716193","indexId":"sir20235083","displayToPublicDate":"2023-07-31T20:00:00","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":"2023-5083","displayTitle":"Evaluation of Alternative Groundwater-Withdrawal Scenarios on Water Levels in Kingsbury Pond, Upper Charles River Basin, Eastern Massachusetts","title":"Evaluation of alternative groundwater-withdrawal scenarios on water levels in Kingsbury Pond, upper Charles River Basin, eastern Massachusetts","docAbstract":"Kingsbury Pond is a glacial kettle pond in the town of Norfolk, Massachusetts, in the Mill River Basin, which is part of the Upper Charles River Basin in eastern Massachusetts. The pond is hydraulically connected to the surrounding groundwater-flow system, and water levels in the pond fluctuate in response to recharge to the aquifer from precipitation and wastewater return flows through septic systems, to withdrawals from the aquifer at nearby wells, and to precipitation directly on the pond surface. Concerns about the effects of withdrawals on water levels in the pond prompted an investigation to better understand the hydrology of Kingsbury Pond and its response to groundwater withdrawals and to determine if withdrawals from wells in Franklin, Mass., can be modified to simultaneously reduce the effect on water levels in the pond and yet meet the water-supply demands of the Town of Franklin.
An existing, transient groundwater-flow model of the Upper Charles River Basin was modified for this study in the area near Kingsbury Pond to improve representation of the hydrologic system near the pond. The mean annual water-level altitude simulated for the pond for nonpumping conditions using the modified model is 136 feet (ft), which falls within the range of likely annual pond-altitude fluctuations of 135 to 140 ft estimated for average hydrologic conditions before the beginning of withdrawals at two nearby wells operated by the Town of Franklin (wells FR–04 and FR–05). The mean annual water-level altitude at the pond decreased by 3.8 ft to 132.2 ft for simulated mean monthly withdrawal rates at all wells within the Upper Charles River Basin from 2010 to 2019 (referred to as the baseline withdrawal condition).
A groundwater management model that links the groundwater-flow model with a mathematical optimization method was developed to evaluate the effects of three alternative groundwater-withdrawal scenarios for the Franklin public-water system on water levels in Kingsbury Pond. In the first scenario, monthly withdrawal rates at wells FR–04 and FR–05 were increased from the baseline withdrawal rates to their maximum authorized rates for all months of the year; all other Franklin wells were specified at their baseline withdrawal rates. This scenario resulted in a mean annual water-level altitude at the pond of 129.3 ft, or a mean annual decline of 6.7 ft compared with nonpumping conditions and a decline of 2.9 ft compared with baseline conditions.
The results of the second scenario showed that water levels in the pond can be increased relative to 2010–19 conditions while meeting Franklin’s 2010–19 monthly water-supply demands if withdrawals at wells FR–04 and FR–05 were shifted to other Franklin wells. In this scenario, monthly withdrawal rates at wells FR–04 and FR–05 were decreased from their baseline rates to one-third their maximum practical rates for all months of the year; increased withdrawal rates at other Franklin wells were determined by the management model. The decrease in withdrawal rates at wells FR–04 and FR–05 resulted in a mean water-level altitude at the pond of 134.1 ft, which was equivalent to a 51 percent increase (improvement) in the mean annual water level of the pond relative to the baseline condition.
A third scenario was done to determine if Franklin’s existing water-supply system has the capacity to meet the mean annual maximum permitted withdrawal rate of the system of 3.45 million gallons per day while maintaining monthly withdrawal rates at wells FR–04 and FR–05 at their 2010–19 rates and water levels in Kingsbury Pond at baseline conditions. The analysis indicated that the capacity of the system cannot meet the increased demand during some months of the year with withdrawal rates at the two wells fixed at their monthly 2010–19 rates; however, the existing system is capable of meeting about 90 percent of the maximum permitted rate (3.10 million gallons per day) by increasing withdrawal rates at other Franklin wells above their 2010–19 rates.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235083","collaboration":"Prepared in cooperation with the Massachusetts Department of Environmental Protection","usgsCitation":"Barlow, P.M., Friesz, P.J., and Barbaro, J.R., 2023, Evaluation of alternative groundwater-withdrawal scenarios on water levels in Kingsbury Pond, upper Charles River Basin, eastern Massachusetts: U.S. Geological Survey Scientific Investigations Report 2023–5083, 36 p., https://doi.org/10.3133/sir20235083.","productDescription":"Report: viii, 36 p.; Data Release","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-141684","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":501046,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115124.htm","linkFileType":{"id":5,"text":"html"}},{"id":419446,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9V49N3R","text":"USGS data release","linkHelpText":"MODFLOW–2000 and management-optimization models used to evaluate alternative groundwater-withdrawal scenarios on water levels in Kingsbury Pond, upper Charles River Basin, eastern Massachusetts"},{"id":419445,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5083/images/"},{"id":419444,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5083/sir20235083.XML"},{"id":419442,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5083/sir20235083.pdf","text":"Report","size":"3.63 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5083"},{"id":419441,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5083/coverthb.jpg"},{"id":419443,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235083/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2023-5083"}],"country":"United States","state":"Massachusetts","otherGeospatial":"Upper Charles River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -71.61642753245717,\n 42.29469041974528\n ],\n [\n -71.61642753245717,\n 41.90357856449015\n ],\n [\n -71.16069045053953,\n 41.90357856449015\n ],\n [\n -71.16069045053953,\n 42.29469041974528\n ],\n [\n -71.61642753245717,\n 42.29469041974528\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
Coastal salt marshes are productive ecosystems that are highly efficient carbon sinks, but there is uncertainty regarding the interactions among climate warming, plant species, and tidal restriction on C cycling.
Open-top chambers (OTCs) were deployed at two coastal wetlands in Yancheng, China, where native Phragmites australis (Phragmites) and invasive Spartina alterniflora (Spartina) were dominant, respectively. Two study locations were set up in each area based on difference in tidal action. The OTCs achieved an increase of average daytime air temperature of ~ 1.11–1.55 °C. Net ecosystem CO2 exchange (NEE), ecosystem respiration (Reco), CH4 fluxes, aboveground biomass and other abiotic factors were monitored over three years.
Warming reduced the magnitude of the radiative balance of native Phragmites, which was determined to still be a consistent C sink. In contrast, warming or tidal flooding presumably transform the Spartina into a weak C source, because either warming-induced high salinity reduced the magnitude of NEE by 19% or flooding increased CH4 emissions by 789%. Remarkably, native Phragmites affected by tidal restrictions appeared to be a consistent C source with the radiative balance of 7.11–9.64 kg CO2-eq m–2 yr–1 because of a reduction in the magnitude of NEE and increase of CH4 fluxes.
Tidal restrictions that disconnect the tidal hydrologic connection between the ocean and land may transform coastal wetlands from C sinks to C sources. This transformation may potentially be an even greater threat to coastal carbon sequestration than climate warming or invasive plant species in isolation.
","language":"English","publisher":"Springer","doi":"10.1007/s11104-023-06160-x","usgsCitation":"Zhou, P., Ye, S., Xie, L., Krauss, K., Pei, L., Chapman, S.K., Brix, H., Laws, E.A., Yuan, H., Yang, S., Ding, X., and Xie, S., 2023, Tidal restriction likely has greater impact on the carbon sink of coastal wetland than climate warming and invasive plant: Plant and Soil, v. 492, p. 135-156, https://doi.org/10.1007/s11104-023-06160-x.","productDescription":"22 p.","startPage":"135","endPage":"156","ipdsId":"IP-149742","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":499840,"rank":2,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://repository.lsu.edu/enviro_sciences_pubs/237","text":"External Repository"},{"id":419743,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"492","noUsgsAuthors":false,"publicationDate":"2023-07-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Zhou, Pan","contributorId":328390,"corporation":false,"usgs":false,"family":"Zhou","given":"Pan","email":"","affiliations":[{"id":12433,"text":"China University of Geosciences","active":true,"usgs":false}],"preferred":false,"id":880060,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ye, Siyuan","contributorId":146732,"corporation":false,"usgs":false,"family":"Ye","given":"Siyuan","email":"","affiliations":[{"id":16739,"text":"Qingdao Institute of Marine Geology, Shandong Province, China","active":true,"usgs":false}],"preferred":false,"id":880061,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Xie, Liujuan","contributorId":328391,"corporation":false,"usgs":false,"family":"Xie","given":"Liujuan","email":"","affiliations":[{"id":78354,"text":"China Geological Survey","active":true,"usgs":false}],"preferred":false,"id":880062,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Krauss, Ken 0000-0003-2195-0729","orcid":"https://orcid.org/0000-0003-2195-0729","contributorId":223022,"corporation":false,"usgs":true,"family":"Krauss","given":"Ken","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":880063,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pei, Lixin","contributorId":328392,"corporation":false,"usgs":false,"family":"Pei","given":"Lixin","affiliations":[{"id":78354,"text":"China Geological Survey","active":true,"usgs":false}],"preferred":false,"id":880064,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Chapman, Samantha K.","contributorId":303864,"corporation":false,"usgs":false,"family":"Chapman","given":"Samantha","email":"","middleInitial":"K.","affiliations":[{"id":12766,"text":"Villanova University","active":true,"usgs":false}],"preferred":false,"id":880065,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Brix, Hans","contributorId":146735,"corporation":false,"usgs":false,"family":"Brix","given":"Hans","email":"","affiliations":[{"id":13419,"text":"Aarhus University, Denmark","active":true,"usgs":false}],"preferred":false,"id":880066,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Laws, Edward A.","contributorId":328394,"corporation":false,"usgs":false,"family":"Laws","given":"Edward","email":"","middleInitial":"A.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":880067,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Yuan, Hongming","contributorId":173534,"corporation":false,"usgs":false,"family":"Yuan","given":"Hongming","email":"","affiliations":[{"id":27244,"text":"Qingdao Institute of Marine Geology, China","active":true,"usgs":false}],"preferred":false,"id":880068,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Yang, Shixiong","contributorId":328396,"corporation":false,"usgs":false,"family":"Yang","given":"Shixiong","email":"","affiliations":[{"id":78354,"text":"China Geological Survey","active":true,"usgs":false}],"preferred":false,"id":880069,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Ding, Xigui","contributorId":173536,"corporation":false,"usgs":false,"family":"Ding","given":"Xigui","email":"","affiliations":[{"id":27244,"text":"Qingdao Institute of Marine Geology, China","active":true,"usgs":false}],"preferred":false,"id":880070,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Xie, Shucheng","contributorId":328397,"corporation":false,"usgs":false,"family":"Xie","given":"Shucheng","email":"","affiliations":[{"id":12433,"text":"China University of Geosciences","active":true,"usgs":false}],"preferred":false,"id":880071,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70247431,"text":"70247431 - 2023 - Soil salinity and water level interact to generate tipping points in low salinity tidal wetlands responding to climate change","interactions":[],"lastModifiedDate":"2023-10-23T16:01:53.14607","indexId":"70247431","displayToPublicDate":"2023-07-26T07:21:19","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1584,"text":"Estuaries and Coasts","active":true,"publicationSubtype":{"id":10}},"title":"Soil salinity and water level interact to generate tipping points in low salinity tidal wetlands responding to climate change","docAbstract":"Low salinity tidal wetlands (LSTW) are vulnerable to sea level rise and saltwater intrusion, thus their carbon sequestration capacity is threatened. However, the thresholds of rapid changes in carbon dynamics and biogeochemical processes in LSTW due to changes in hydroperiod and salinity regime remain unclear. In this study, we examined the effects of soil porewater salinity and water level on changes in net primary productivity (NPP) and greenhouse gas fluxes [GHG: methane (CH4), nitrous oxide (N2O), and carbon dioxide (CO2)] in LSTW using a wetland biogeochemistry model, Tidal Freshwater Wetland Denitrification and Decomposition (TFW-DNDC). TFW-DNDC was run with a series of combinations of soil salinities (0.1, 0.5, 1, 2, 4, 6, 8, 10 psu) and water levels relative to soil surface (-30, -20, -10, -5, 0, 5, 10, 20, 30 cm) for tidal forest and oligohaline marsh sites along the Savannah River and Waccamaw River, USA. Our results indicate that soil salinity and water level have antagonistic effects on CH4 emissions and synergistic effects on CO2 release. A soil salinity of 2-3 psu is the tipping point for the ecosystem level functional changes (e.g., NPP and CH4 emissions) in LSTW. There are negative and nonlinear responses (NPP and CH4 emission) to soil salinity. Furthermore, a soil water level from 10 cm below to 10 cm above the surface is a critical range in which biogeochemical processes respond strongly to hydrological changes. The presence of nonlinear tipping points in LSTW has large implications for understanding and predicting the effects of climate change on coastal wetland blue carbon storage and ecosystem dynamics.
Brownlee Reservoir is a mercury (Hg)-impaired hydroelectric reservoir that exhibits dynamic hydrological and geochemical conditions and is located within the Hells Canyon Complex in Idaho, USA. Methylmercury (MeHg) contamination in fish is a concern in the reservoir. While MeHg production has historically been attributed to sulfate-reducing bacteria and methanogenic archaea, microorganisms carrying the hgcA gene are taxonomically and metabolically diverse and the major biogeochemical cycles driving mercury (Hg) methylation are not well understood. In this study, Hg speciation and redox-active compounds were measured throughout Brownlee Reservoir across the stratified period in four consecutive years (2016–2019) to identify the location where and redox conditions under which MeHg is produced. Metagenomic sequencing was performed on a subset of samples to characterize the microbial community with hgcA and identify possible links between biogeochemical cycles and MeHg production. Biogeochemical profiles suggested in situ water column Hg methylation was the major source of MeHg. These profiles, combined with genome-resolved metagenomics focused on hgcA-carrying microbes, indicated that MeHg production occurs in this system under nitrate- or manganese-reducing conditions, which were previously thought to preclude Hg-methylation. Using this multidisciplinary approach, we identified the cascading effects of interannual variability in hydrology on the redox status, microbial metabolic strategies, abundance and metabolic diversity of Hg methylators, and ultimately MeHg concentrations throughout the reservoir. This work expands the known conditions conducive to producing MeHg and suggests that the Hg-methylation mitigation efforts by nitrate or manganese amendment may be unsuccessful in some locations.
","language":"English","publisher":"Nature","doi":"10.1038/s41396-023-01482-1","usgsCitation":"Peterson, B.D., Poulin, B., Krabbenhoft, D.P., Tate, M., Baldwin, A.K., Naymik, J., Gastelecutto, N., and McMahon, K.D., 2023, Metabolically diverse microorganisms mediate methylmercury formation under nitrate-reducing conditions in a dynamic hydroelectric reservoir: International Society for Microbial Ecology Journal, v. 17, p. 1705-1718, https://doi.org/10.1038/s41396-023-01482-1.","productDescription":"14 p.","startPage":"1705","endPage":"1718","ipdsId":"IP-152265","costCenters":[{"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":442645,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41396-023-01482-1","text":"Publisher Index Page"},{"id":419879,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Brownlee Reservoir","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -116.82386599883054,\n 44.927005686412485\n ],\n [\n -117.32902035469117,\n 44.927005686412485\n ],\n [\n -117.32902035469117,\n 44.33306182839914\n ],\n [\n -116.82386599883054,\n 44.33306182839914\n ],\n [\n -116.82386599883054,\n 44.927005686412485\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"17","noUsgsAuthors":false,"publicationDate":"2023-07-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Peterson, Benjamin D.","contributorId":328487,"corporation":false,"usgs":false,"family":"Peterson","given":"Benjamin","email":"","middleInitial":"D.","affiliations":[{"id":16975,"text":"University of California Davis","active":true,"usgs":false}],"preferred":false,"id":880305,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Poulin, Brett A.","contributorId":328488,"corporation":false,"usgs":false,"family":"Poulin","given":"Brett A.","affiliations":[{"id":16975,"text":"University of California Davis","active":true,"usgs":false}],"preferred":false,"id":880306,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Krabbenhoft, David P. 0000-0003-1964-5020 dpkrabbe@usgs.gov","orcid":"https://orcid.org/0000-0003-1964-5020","contributorId":1658,"corporation":false,"usgs":true,"family":"Krabbenhoft","given":"David","email":"dpkrabbe@usgs.gov","middleInitial":"P.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37464,"text":"WMA - 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2023 - Techniques for estimating the magnitude and frequency of peak flows on small streams in Minnesota, excluding the Rainy River Basin, based on data through water year 2019","interactions":[],"lastModifiedDate":"2026-03-13T13:20:17.495243","indexId":"sir20235079","displayToPublicDate":"2023-07-25T10:09:21","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":"2023-5079","displayTitle":"Techniques for Estimating the Magnitude and Frequency of Peak Flows on Small Streams in Minnesota, Excluding the Rainy River Basin, Based on Data Through Water Year 2019","title":"Techniques for estimating the magnitude and frequency of peak flows on small streams in Minnesota, excluding the Rainy River Basin, based on data through water year 2019","docAbstract":"Annual peak-flow data collected at U.S. Geological Survey streamgages in Minnesota and adjacent areas of neighboring states of Iowa and South Dakota were analyzed to develop and update regional regression equations that can be used to estimate the magnitude and frequency of peak streamflow for ungaged streams in Minnesota, excluding the Lake of the Woods-Rainy River Basin upstream from Kenora, Ontario, Canada. Hydraulic engineers use peak-flow frequency estimates to inform designs of bridges, culverts, and dams, and water managers use the estimates for regulation and planning activities. Peak-flow estimates are provided for the 66.7-, 50-, 20-, 10-, 4-, 2-, 1-, and 0.2-percent annual exceedance probabilities (AEPs), which are equivalent to annual flood-frequency recurrence intervals of 1.5-, 2-, 5-, 10-, 25-, 50-, 100-, and 500-years, respectively. The estimates were computed by applying the expected moments algorithm to fit a Pearson Type III distribution to the logarithms of annual peak flows for 298 streamgages based on annual peak-flow data collected through water year 2019. The study area is represented by six hydrologic regions delineated on the basis of a pattern of residuals of statewide regressions, using basin characteristics such as drainage area, main-channel slope, lake area, storage area, and mean annual runoff as explanatory variables. The concept and principles of hydrologic landscape units was used to validate the regions. Residual analysis of the regional regression equations was used to subsequently develop equations relating the peak flow estimates for selected AEPs using 17 characteristics tested as explanatory variables in the regression analysis.
The equations developed in this study can be used to produce AEPs within the six regions and to update equations developed in earlier, similar studies in Minnesota. Furthermore, updating the equations in StreamStats, a web-based geographic information system tool developed by the U.S. Geological Survey, will allow hydraulic engineers and water managers to obtain AEPs and basin characteristics for user-selected locations on streams through an interactive map.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235079","collaboration":"Prepared in cooperation with the Minnesota Department of Transportation","usgsCitation":"Sanocki, C.A., and Levin, S.B., 2023, Techniques for estimating the magnitude and frequency of peak flows on small streams in Minnesota, excluding the Rainy River Basin, based on data through water year 2019: U.S. Geological Survey Scientific Investigations Report 2023–5079, 15 p., https://doi.org/10.3133/sir20235079.","productDescription":"Report: v, 15 p.; 2 Data Releases; Dataset","numberOfPages":"26","onlineOnly":"Y","ipdsId":"IP-127955","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":419307,"rank":7,"type":{"id":39,"text":"HTML 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\"}}]}","contact":"Director, Upper Midwest Water Science Center
U.S. Geological Survey
1 Gifford Pinchot Drive
Madison, WI 53726
Wildfires naturally occur in many landscapes, however they are undergoing rapid regime shifts. Despite the emphasis in the literature on the most severe hydrological responses to wildfire, there remains a knowledge gap on the thresholds of wildfire (i.e. burned area/drainage area ratio, BAR) required to initiate hydrological responses. We investigated hydrological changes in the Russian River Watershed (RRW) in California, a coastal, Mediterranean, drought-prone, wildfire-adapted ecosystem, following ten wildfires that burned 30% of the watershed. Our findings suggest that sub-watersheds of the RRW have not burned beyond an intrinsic, unknown, threshold required to initiate change. Using paired watersheds, we examined spatiotemporal patterns of pre-and-post wildfire hydrology with a rainfall-runoff hydrological model. Even though these successive wildfires burned 1-50% of each sub-watershed (1-30% at moderate/high severity), we found little evidence of wildfire-related shifts in hydrology. As a function of BAR, wildfire imposed limited effects on runoff ratios (runoff/precipitation) and runoff residuals (observations - model simulations). Our findings that post-wildfire runoff enhancements asymptote beyond 30% burn indicate that when a watershed is burned beyond a certain threshold, the magnitude of the hydrologic response no longer increases. Drought and storm conditions explained much of the variability observed in streamflow, whereas wildfire explained only moderate variability in streamflow even when wildfire accounted for >45% BAR. While the BAR in the RRW was sufficiently beyond previously reported minimum disturbance thresholds (>20% burned forest), the lack of hydrological response is attributed to buffering effects of wildfire adaptation and drought factors that are unique to Mediterranean ecoregions.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2022WR034206","usgsCitation":"Newcomer, M.E., Underwood, J.C., Murphy, S.F., Ulrich, C., Schram, T., Maples, S.R., Pena, J., Siirila-Woodburn, E.R., Trotta, M., Jasperse, J., Seymour, D., and Hubbard, S., 2023, Prolonged drought in a northern California coastal region suppresses wildfire impacts on hydrology: Water Resources Research, v. 59, no. 8, e2022WR034206, 23 p., https://doi.org/10.1029/2022WR034206.","productDescription":"e2022WR034206, 23 p.","ipdsId":"IP-147415","costCenters":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"links":[{"id":442702,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2022wr034206","text":"Publisher Index Page"},{"id":419247,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Russian River watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -123.58166191175413,\n 39.66438164966229\n ],\n [\n -123.52362681286694,\n 38.86220749551856\n ],\n [\n -122.91949120418995,\n 38.952501194302044\n ],\n [\n -123.01324021008476,\n 39.6265634050871\n ],\n [\n -123.58166191175413,\n 39.66438164966229\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"59","issue":"8","noUsgsAuthors":false,"publicationDate":"2023-07-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Newcomer, Michelle E.","contributorId":317249,"corporation":false,"usgs":false,"family":"Newcomer","given":"Michelle","email":"","middleInitial":"E.","affiliations":[{"id":68983,"text":"Lawrence Berkeley National Laboratory, Earth & Environmental Sciences Area","active":true,"usgs":false}],"preferred":false,"id":878842,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Underwood, Jennifer C. 0000-0002-2702-0410 jcunder@usgs.gov","orcid":"https://orcid.org/0000-0002-2702-0410","contributorId":294555,"corporation":false,"usgs":true,"family":"Underwood","given":"Jennifer","email":"jcunder@usgs.gov","middleInitial":"C.","affiliations":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":878843,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":878844,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ulrich, Craig","contributorId":317250,"corporation":false,"usgs":false,"family":"Ulrich","given":"Craig","affiliations":[{"id":68983,"text":"Lawrence Berkeley National Laboratory, Earth & Environmental Sciences Area","active":true,"usgs":false}],"preferred":false,"id":878845,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schram, Todd","contributorId":317251,"corporation":false,"usgs":false,"family":"Schram","given":"Todd","email":"","affiliations":[{"id":68984,"text":"Sonoma Water, Santa Rosa, California","active":true,"usgs":false}],"preferred":false,"id":878846,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Maples, Stephen R.","contributorId":317252,"corporation":false,"usgs":false,"family":"Maples","given":"Stephen","email":"","middleInitial":"R.","affiliations":[{"id":68984,"text":"Sonoma Water, Santa Rosa, California","active":true,"usgs":false}],"preferred":false,"id":878847,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pena, Jasquelin","contributorId":317253,"corporation":false,"usgs":false,"family":"Pena","given":"Jasquelin","email":"","affiliations":[{"id":68983,"text":"Lawrence Berkeley National Laboratory, Earth & Environmental Sciences Area","active":true,"usgs":false}],"preferred":false,"id":878848,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Siirila-Woodburn, Erica R.","contributorId":317254,"corporation":false,"usgs":false,"family":"Siirila-Woodburn","given":"Erica","email":"","middleInitial":"R.","affiliations":[{"id":68983,"text":"Lawrence Berkeley National Laboratory, Earth & Environmental Sciences Area","active":true,"usgs":false}],"preferred":false,"id":878849,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Trotta, Marcus","contributorId":317255,"corporation":false,"usgs":false,"family":"Trotta","given":"Marcus","affiliations":[{"id":68984,"text":"Sonoma Water, Santa Rosa, California","active":true,"usgs":false}],"preferred":false,"id":878850,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Jasperse, Jay","contributorId":317256,"corporation":false,"usgs":false,"family":"Jasperse","given":"Jay","affiliations":[{"id":68984,"text":"Sonoma Water, Santa Rosa, California","active":true,"usgs":false}],"preferred":false,"id":878851,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Seymour, Donald","contributorId":317257,"corporation":false,"usgs":false,"family":"Seymour","given":"Donald","affiliations":[{"id":68984,"text":"Sonoma Water, Santa Rosa, California","active":true,"usgs":false}],"preferred":false,"id":878852,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Hubbard, Susan S.","contributorId":317258,"corporation":false,"usgs":false,"family":"Hubbard","given":"Susan S.","affiliations":[{"id":37070,"text":"Oak Ridge National Laboratory","active":true,"usgs":false}],"preferred":false,"id":878853,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70246679,"text":"sir20235042 - 2023 - Selenium hazards in the Salton Sea environment—Summary of current knowledge to inform future wetland management","interactions":[],"lastModifiedDate":"2026-03-06T21:38:07.222047","indexId":"sir20235042","displayToPublicDate":"2023-07-20T14:20:47","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":"2023-5042","displayTitle":"Selenium Hazards in the Salton Sea Environment—Summary of Current Knowledge to Inform Future Wetland Management","title":"Selenium hazards in the Salton Sea environment—Summary of current knowledge to inform future wetland management","docAbstract":"Quaternary marine and continental shales in the western United States are sources of selenium that can be loaded into the aquatic environment through mining, agricultural, and energy production processes. The mobilization of selenium from shales through agricultural irrigation has been recognized since the 1930s; however, discovery of deformities in birds and other wildlife using agricultural habitats during the 1980s spurred studies to determine the extent and effects of the contamination. Through these early studies, researchers determined that biota in the Salton Sea drainage basin was at risk from legacy selenium contamination in the Colorado River watershed.
The Salton Sea and its surrounding managed and unmanaged wetlands provide vital inland habitat and trophic support for diverse assemblages of resident and migratory wildlife, and understanding regional selenium hazards for these trust species is a priority for many Federal and State agencies. The modern Salton Sea is a shallow, landlocked saline lake in Riverside and Imperial Counties (not shown) of California that is sustained by irrigation return and perennial river inflow. Changes in water transfer agreements under the 2003 Quantification Settlement Agreement (QSA) have resulted in reduced irrigation flow, declining lake levels, and the evolution of unmanaged wetlands in areas where drains and rivers no longer reach the Salton Sea. These wetlands provide additional habitat for some species of concern, but their potential to increase selenium hazards for trust species is largely unknown.
From the 1980s to 2020, efforts to document selenium contamination and effects throughout the region have resulted in a considerable amount of selenium data from the Salton Sea and its surrounding drainage basin; however, no long-term (greater than 20 years), consistent sampling program has been established, and all data have been collected by different entities using a variety of protocols and analytical techniques. This lack of coordination has been previously documented in regional management plans and has led to difficulty in reliably assessing selenium hazards in the Salton Sea environment. This report provides a summary of the available disparate selenium information collected from water, sediment, and biota in the Salton Sea region since the 1980s and to identify data gaps that need to be filled to understand the potential effects of selenium on species of concern, including federally endangered desert pupfish (Cyprinodon macularius) and Yuma Ridgway’s Rail (Rallus obsoletus yumanensis; formerly Yuma Clapper Rail, Rallus longirostris yumanensis).
Available data from the Salton Sea drainage basin show that water from the Colorado River has the lowest selenium concentration of all surface water sources. All other surface water flowing into the Salton Sea has elevated selenium concentrations due to evaporation and evapotranspiration that occurs in agricultural fields and associated water delivery infrastructure or leaching of selenium from irrigated farmland soils. The Salton Sea has lower selenium concentrations because of various biogeochemical processes that recycle selenium into the sediment or volatilize it to the atmosphere; however, these mechanisms are not well defined, and it is not clear if selenium cycling will change in response to possible changes in the oxidation state of the Salton Sea bottom waters as water levels decline. Agricultural drains have the highest average selenium concentrations, but few drains have been sampled since changes in irrigation practices have occurred (due to the 2003 QSA). Groundwater selenium concentrations are variable; some wells south of the Salton Sea have selenium concentrations as high as 300 micrograms per liter (µg/L), whereas selenium concentrations are below detection in other wells. Groundwater and surface-water geothermal discharge zones around the margins of the Salton Sea and in unmanaged wetlands have not been studied in detail, and published selenium measurements are not available for these surface features.
Selenium concentrations in the sediment of the Salton Sea drainage basin are highest in wetland particulate organic matter and the Salton Sea lakebed, indicating that removal of selenium from the water to the sediment has been a primary mechanism for keeping selenium concentrations low in the water column. Sediment selenium concentrations in wetlands are lower than in the Salton Sea but higher than inflowing drains and rivers, indicating the lentic wetland sites also may be important sinks for selenium because of biogeochemical processes. Sediment selenium data have not been collected in agricultural drains since changes in irrigation practices occurred (due to the 2003 QSA), and it is unknown if selenium sequestration from the water column has changed in these systems.
We divided biological data into broad taxonomic categories, including primary producers, invertebrates, herpetofauna, mammals, fishes, and birds to facilitate evaluation of selenium concentrations and spatiotemporal trends observed in the Salton Sea. Overall, selenium concentrations were substantially greater in algae samples compared to all vascular plant samples combined. Median selenium concentrations in several invertebrate taxa (Chironomidae, Formicidae, Corixidae, Corbiculidae and Nereididae, and Decapoda) exceeded the maximum suggested dietary threshold of 3.0–4.0 micrograms per gram (µg/g) dry weight (dw) for predators consuming invertebrates in aquatic food webs. The greatest number of samples were collected from fish, and selenium distributions among species and locations showed that the range for most samples was lower than the U.S. Environmental Protection Agency selenium criterion for aquatic life (8.5 µg/g dw whole body, 11.3 µg/g dw fillets). The median selenium concentrations for whole body fish were below the selenium criterion in most locations, except for bairdiella (Bairdiella icistia) from the Salton Sea and irrigation drains, a few individual tilapia spp. (family Cichlidae, including genera Tilapia, Oreochromis, and their hybrids) from the river and river outlets, and several western mosquitofish (Gambusia affinis) and sailfin molly (Poecilia latipinna) from irrigation drain outlets. For avian samples combined among years and locations, median selenium concentrations in livers from all families except waders and Ibis (family Threskiornithidae) were higher than levels expected to cause selenium toxicosis (10–20 µg/g dw), and all median egg concentrations were above or near 6.0 μg/g dw, which is a conservative threshold value for reproductive impairment.
Most knowledge gaps we identified for water, sediment, and biota were interrelated, and the use of integrated approaches to address knowledge gaps can provide greater insight into the drivers behind selenium hazards. Integrated water, sediment, and biota studies could help identify cost-effective management solutions that serve multiple purposes. A comprehensive analysis of the hydrology, biogeochemistry, and food-web processes in wetlands and other habitats can inform predictive models to identify drivers of selenium bioavailability, uptake from the environment and subsequent trophic transfer, ultimately forming the basis for experimental habitat management manipulations to minimize selenium hazards to wildlife. Furthermore, a comprehensive, long-term sampling and analytical laboratory plan would enable comparison of data among different entities that are sampling at the Salton Sea. Such efforts are well suited to help fill knowledge gaps that preclude understanding of selenium hazards and future management options for biota using Salton Sea habitats, including newly formed wetlands throughout the region.
All data compiled for this report are available in two U.S. Geological Survey data releases: Groover and others (2022) for water and sediment samples and De La Cruz and others (2022) for biological samples. The data releases include all publicly available data for selenium concentrations in water, sediment, and biological samples collected in and around the Salton Sea, including the Coachella and Imperial Valleys. The data releases also include previously unpublished data.
Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
Riverbank groundwater discharge faces are spatially extensive areas of preferential seepage that are exposed to air at low river flow. Some conceptual hydrologic models indicate discharge faces represent the spatial convergence of highly variable age and length groundwater flowpaths, while others indicate greater consistency in source groundwater characteristics. Our detailed field investigation of preferential discharge points nested across mainstem riverbank discharge faces was accomplished by: (1) leveraging new temperature-based recursive estimation (extended Kalman Filter) modelling methodology to evaluate seasonal, diurnal, and event-driven groundwater flux patterns, (2) developing a multi-parameter toolkit based on readily measured attributes to classify the general source groundwater flowpath depth and flowpath length scale, and, (3) assessing whether preferential flow points across discharge faces tend to represent common or convergent groundwater sources. Five major groundwater discharge faces were mapped along the Farmington River, CT, United States using thermal infrared imagery. We then installed vertical temperature profilers directly into 39 preferential discharge points for 4.5 months to track vertical discharge flux patterns. Monthly water chemistry was also collected at the discharge points along with one spatial synoptic of stable isotopes of water and dissolved radon gas. We found pervasive evidence of shallow groundwater sources at the upstream discharge faces along a wide valley section with deep bedrock, as primarily evidenced by pronounced diurnal discharge flux patterns. Discharge flux seasonal trends and bank storage transitions during large river flow events provided further indication of shallow, local sources. In contrast, downstream discharge faces associated with near surface cross cutting bedrock exhibited deep and regional source flowpath characteristics such as more stable discharge patterns and temperatures. However, many neighbouring points across discharge faces had similar discharge flux patterns that differed in chloride and radon concentrations, indicating the additional effects of localized flowpath heterogeneity overprinting on larger scale flowpath characteristics.
","language":"English","publisher":"Wiley","doi":"10.1002/hyp.14939","usgsCitation":"Haynes, A., Briggs, M., Moore, E., Jackson, K., Knighton, J., Rey, D., and Helton, A., 2023, Shallow and local or deep and regional? Inferring source groundwater characteristics across mainstem riverbank discharge faces: Hydrological Processes, v. 37, no. 7, e14939, 19 p., https://doi.org/10.1002/hyp.14939.","productDescription":"e14939, 19 p.","ipdsId":"IP-151076","costCenters":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":442704,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/hyp.14939","text":"Publisher Index Page"},{"id":419349,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Connecticut","otherGeospatial":"Farmington River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -72.716667,\n 41.933\n ],\n [\n -72.8333,\n 41.933\n ],\n [\n -72.8333,\n 41.7833\n ],\n [\n -72.716667,\n 41.7833\n ],\n [\n -72.716667,\n 41.933\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"37","issue":"7","noUsgsAuthors":false,"publicationDate":"2023-07-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Haynes, Adam","contributorId":216657,"corporation":false,"usgs":false,"family":"Haynes","given":"Adam","affiliations":[{"id":36710,"text":"University of Connecticut","active":true,"usgs":false}],"preferred":false,"id":879120,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Briggs, Martin A. 0000-0003-3206-4132","orcid":"https://orcid.org/0000-0003-3206-4132","contributorId":222759,"corporation":false,"usgs":true,"family":"Briggs","given":"Martin A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":879121,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moore, Eric","contributorId":216658,"corporation":false,"usgs":false,"family":"Moore","given":"Eric","affiliations":[{"id":36710,"text":"University of Connecticut","active":true,"usgs":false}],"preferred":false,"id":879122,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jackson, Kevin","contributorId":317715,"corporation":false,"usgs":false,"family":"Jackson","given":"Kevin","affiliations":[{"id":36710,"text":"University of Connecticut","active":true,"usgs":false}],"preferred":false,"id":879123,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Knighton, James","contributorId":317716,"corporation":false,"usgs":false,"family":"Knighton","given":"James","email":"","affiliations":[{"id":36710,"text":"University of Connecticut","active":true,"usgs":false}],"preferred":false,"id":879124,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rey, David M. 0000-0003-2629-365X","orcid":"https://orcid.org/0000-0003-2629-365X","contributorId":211848,"corporation":false,"usgs":true,"family":"Rey","given":"David M.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":879125,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Helton, Ashley","contributorId":219741,"corporation":false,"usgs":false,"family":"Helton","given":"Ashley","affiliations":[{"id":36710,"text":"University of Connecticut","active":true,"usgs":false}],"preferred":false,"id":879126,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70246624,"text":"ofr20231047 - 2023 - Multiple-well monitoring site within the Poso Creek Oil Field, Kern County, California","interactions":[],"lastModifiedDate":"2026-02-11T21:28:50.272733","indexId":"ofr20231047","displayToPublicDate":"2023-07-18T11:37:02","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":"2023-1047","displayTitle":"Multiple-Well Monitoring Site Within the Poso Creek Oil Field, Kern County, California","title":"Multiple-well monitoring site within the Poso Creek Oil Field, Kern County, California","docAbstract":"The Poso Creek Oil Field is one of the many fields selected for regional groundwater mapping and monitoring by the California State Water Resources Control Board as part of the Oil and Gas Regional Monitoring Program (RMP; California State Water Resources Control Board, 2015, 2022b; U.S. Geological Survey, 2022a). The U.S. Geological Survey (USGS), in cooperation with the California State Water Resources Control Board, is evaluating several questions about oil and gas development and groundwater resources in California, including (1) the location of groundwater resources; (2) the proximity of oil and gas operations to groundwater and the geologic materials between them; (3) evidence (or no evidence) of fluids from oil and gas sources in groundwater; and (4) the pathways or processes responsible when fluids from oil and gas sources are present in groundwater (U.S. Geological Survey, 2022a). As part of this evaluation, the USGS installed a multiple-well monitoring site within the administrative boundary of the Poso Creek Oil Field about 12 miles north of Bakersfield, California (fig. 1). Data collected at the Poso Creek multiple-well monitoring site (PCCT) provide information about the geology, hydrology, geophysical properties, and water quality of the aquifer system overlying the oil-bearing zone, thus enhancing understanding of relations between adjacent groundwater and the Poso Creek Oil Field in an area where groundwater data are limited, particularly at different depths in the aquifer. This report presents construction information for the PCCT and initial geohydrologic data collected from the site. Similar sites installed on the east side of the Lost Hills Oil Field and North and South Belridge Oil Fields were described by Everett and others (2020a, b).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231047","collaboration":"Prepared in cooperation with the California State Water Resources Control Board","usgsCitation":"Everett, R.R., McMahon, P.B., Stephens, M.J., Gillespie, J.M., Shepherd, M.M., and Fenton, N.C., 2023, Multiple-well monitoring site within the Poso Creek Oil Field, Kern County, California: U.S. Geological Survey Open-File Report 2023-1047, 11 p., https://doi.org/10.3133/ofr20231047.","productDescription":"11 p.","numberOfPages":"11","onlineOnly":"Y","ipdsId":"IP-143467","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":499783,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114968.htm","linkFileType":{"id":5,"text":"html"}},{"id":418877,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/preview/ofr20231047/full"},{"id":418876,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1047/images"},{"id":418875,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1047/ofr20231047.xml"},{"id":418874,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1047/ofr20231047.pdf","text":"Report","size":"3 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":418873,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1047/covrthb.jpg"}],"country":"United States","state":"California","county":"Kern County","otherGeospatial":"Poso Creek Oil Field","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -119.02751948230053,\n 35.55715768005527\n ],\n [\n -119.02751948230053,\n 35.37156425616723\n ],\n [\n -118.8051417495576,\n 35.37156425616723\n ],\n [\n -118.8051417495576,\n 35.55715768005527\n ],\n [\n -119.02751948230053,\n 35.55715768005527\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
Shifts in the frequency and intensity of high discharge events due to climate change may have important consequences for the hydrology and biogeochemistry of rivers. However, our understanding of event-scale biogeochemical dynamics in large rivers lags that of small streams. To fill this gap, we used high-frequency sensor data collected during four consecutive summers from a main channel and backwater site of the Upper Mississippi River. We identified high discharge events and calculated event concentration-discharge responses for both physical-chemical (nitrate, turbidity, and fluorescent dissolved organic matter) and biological (chlorophyll-a and cyanobacteria) constituents using metrics of hysteresis and slope. We found a range of responses across events, particularly for nitrate. Although fluorescent dissolved organic matter (FDOM) and turbidity exhibited more consistent responses across events, contrasting hysteresis metrics indicated that FDOM was flushed to the river from more distant sources than turbidity. Biological responses (chlorophyll a and cyanobacteria) differed more between sites than physical and chemical constituents. Lastly, we found that the event characteristics best explaining concentration responses differed between sites, with event magnitude more frequently related to responses in the main channel, and antecedent wetness conditions associated with response variation in the backwater. Our results indicate that event responses in large rivers are distinct across the diverse habitats and biogeochemical components of a large floodplain river, which has implications for local and downstream ecosystems as the climate shifts.
As climate changes in coming decades, ponderosa pine forest persistence may be increasingly dictated by their regeneration. Sustained regeneration failure has been predicted for forests of the southwestern US (SWUS) even in absence of stand-replacing wildfire, but regeneration in undisturbed and lightly disturbed forests has been studied infrequently and at a limited number of locations. We characterized 77 ponderosa pine sites in 7 SWUS locations, documented regeneration occurring over the past
Hawaiian coastal wetlands provide important habitat for federally endangered waterbirds and socio-cultural resources for Native Hawaiians. Currently, Hawaiian coastal wetlands are degraded by development, sedimentation, and invasive species and, thus, require restoration. Little is known about their original structure and function due to the large-scale alteration of the lowland landscape since European contact. Here, we used 1) rapid field assessments of hydrology, vegetation, soils, and birds, 2) a comprehensive analysis of endangered bird habitat value, 3) site spatial characteristics, 4) sea-level rise projections for 2050 and 2100 and wetland migration potential, and 5) preferences of the Native Hawaiian community in a GIS site suitability analysis to prioritize restoration of coastal wetlands on the island of Molokaʻi. The site suitability analysis is the first, to our knowledge, to incorporate community preferences, habitat criteria for endangered waterbirds, and sea-level rise into prioritizing wetland sites for restoration. The rapid assessments showed that groundwater is a ubiquitous water source for coastal wetlands. A groundwater-fed, freshwater herbaceous peatland or “coastal fen” not previously described in Hawaiʻi was found adjacent to the coastline at a site being used to grow taro, a staple crop for Native Hawaiians. In traditional ecological knowledge, such a groundwater-fed, agro-ecological system is referred to as a loʻipūnāwai (spring pond). Overall, 39 plant species were found at the 12 sites; 26 of these were wetland species and 11 were native. Soil texture in the wetlands ranged from loamy sands to silt and silty clays and the mean % organic carbon content was 10.93% ± 12.24 (sd). In total, 79 federally endangered waterbirds, 13 Hawaiian coots (‘alae keʻokeʻo; Fulica alai) and 66 Hawaiian stilts (aeʻo; Himantopus mexicanus knudseni), were counted during the rapid field assessments. The site suitability analysis consistently ranked three sites the highest, Kaupapaloʻi o Kaʻamola, Kakahaiʻa National Wildlife Refuge, and ʻŌhiʻapilo Pond, under three different weighting approaches. Site prioritization represents both an actionable plan for coastal wetland restoration and an alternative protocol for restoration decision-making in places such as Hawaiʻi where no pristine “reference” sites exist for comparison.
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