Naturally occurring gas hydrates may contribute to a positive feedback for global warming because they sequester large amounts of the potent greenhouse gas methane in ice-like deposits that could be destabilized by increasing ocean/atmospheric temperatures. Most hydrates occur within marine sediments; gas liberated during the decomposition of seafloor hydrates or originating with other methane pools can feed methane emissions at cold seeps. Regardless of the origin of seep methane, all previous measurements of methane emitted from seeps have shown it to have a unique fossil radiocarbon signature, contrasting with other sources of marine methane. Here we present the concentration and natural radiocarbon content of methane dissolved in the water column from the seafloor to the sea surface at seep fields along the US Atlantic and Pacific margins. For shallower water columns, where the seafloor is not within the hydrate stability zone, we do document seep CH4 in some surface-water samples. However, measurements in deeper water columns along the US Atlantic margin reveal no evidence of seep CH4 reaching surface waters when the water-column depth is greater than 430 ± 90 m. Gas hydrates exist only at water depths greater than ~550 m in this region, suggesting that the source of methane escaping to the atmosphere is not from hydrate decomposition.
","language":"English","publisher":"Nature Publications","doi":"10.1038/s41561-022-01044-8","usgsCitation":"Joung, D., Ruppel, C.D., Southon, J.R., Weber, T.S., and Kessler, J.D., 2022, Negligible atmospheric release of methane from decomposing hydrates in mid-latitude oceans: Nature Geoscience, v. 15, p. 885-891, https://doi.org/10.1038/s41561-022-01044-8.","productDescription":"7 p.","startPage":"885","endPage":"891","ipdsId":"IP-137535","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":408475,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina, Oregon, Virginia, Washington","otherGeospatial":"mid-Atlantic Bight, Pacific Northwest","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75,\n 35\n ],\n [\n -74.4,\n 35\n ],\n [\n -74.4,\n 38\n ],\n [\n -75,\n 38\n ],\n [\n -75,\n 35\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -128.8916015625,\n 45\n ],\n [\n -122,\n 45\n ],\n [\n -122,\n 49\n ],\n [\n -128.8916015625,\n 49\n ],\n [\n -128.8916015625,\n 45\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"15","noUsgsAuthors":false,"publicationDate":"2022-10-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Joung, DongJoo","contributorId":298022,"corporation":false,"usgs":false,"family":"Joung","given":"DongJoo","email":"","affiliations":[{"id":64483,"text":"University of Rochester and Pusan National University","active":true,"usgs":false}],"preferred":false,"id":854883,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ruppel, Carolyn D. 0000-0003-2284-6632 cruppel@usgs.gov","orcid":"https://orcid.org/0000-0003-2284-6632","contributorId":195778,"corporation":false,"usgs":true,"family":"Ruppel","given":"Carolyn","email":"cruppel@usgs.gov","middleInitial":"D.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":854884,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Southon, John R.","contributorId":201538,"corporation":false,"usgs":false,"family":"Southon","given":"John","email":"","middleInitial":"R.","affiliations":[{"id":36191,"text":"Keck Carbon Cycle AMS Laboratory, Department of Earth System Science, University of California Irvine, Irvine, California, USA.","active":true,"usgs":false}],"preferred":false,"id":854885,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Weber, Thomas S.","contributorId":198207,"corporation":false,"usgs":false,"family":"Weber","given":"Thomas","middleInitial":"S.","affiliations":[{"id":18105,"text":"University of New Hampshire, Durham","active":true,"usgs":false}],"preferred":false,"id":854886,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kessler, John D. 0000-0003-1097-6800","orcid":"https://orcid.org/0000-0003-1097-6800","contributorId":184241,"corporation":false,"usgs":false,"family":"Kessler","given":"John","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":854887,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70237654,"text":"70237654 - 2022 - Simulation experiments comparing nonstationary design-flood adjustments based on observed annual peak flows in the conterminous United States","interactions":[],"lastModifiedDate":"2023-11-08T16:36:31.345339","indexId":"70237654","displayToPublicDate":"2022-10-17T07:17:18","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5836,"text":"Journal of Hydrology X","onlineIssn":"2589-9155","active":true,"publicationSubtype":{"id":10}},"title":"Simulation experiments comparing nonstationary design-flood adjustments based on observed annual peak flows in the conterminous United States","docAbstract":"While nonstationary flood frequency analysis (NSFFA) methods have proliferated, few studies have rigorously compared them for modeling changes in both the central tendency and variability of annual peak-flow series, also known as the annual maximum series (AMS), in hydrologically diverse areas. Through Monte Carlo experiments, we appraise five methods for updating estimates of 10- and 100-year floods at gauged sites using synthetic records based on sample moments and change trajectories of observed AMS in the conterminous United States (CONUS). We compare two methods that consider changes in both central tendency and variability - a Gamma generalized linear model estimated with weighted least squares and the Generalized Additive Model for Location, Scale, Shape (GAMLSS) - with a distribution-free approach (quantile regression), and baseline cases assuming stationarity or only changes in central tendency.
‘Trend-space’ plots identify realistic AMS changes for which modeling trends in both central tendency and variability were warranted based on fractional root mean squared errors (fRMSE). They also reveal statistical properties of AMS under which NSFFA models perform especially well or poorly. For instance, quantile regression performed especially well (poorly) under strong negative (positive) skewness. Although the nonstationary LP3 distribution accommodates most AMS with trends well, the sensitivity of NSFFA model performance to different sample moments and trends suggests the need for more flexibility in prescribing design-flood adjustments in the CONUS. A follow-up comparison of regional NSFFA models pooling at-site AMS would further illuminate NSFFA guidance, especially for AMS with properties less conducive to NSFFA modeling, such as positive skewness and increasing variability.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.hydroa.2021.100115","usgsCitation":"Hecht, J., Barth, N.A., Ryberg, K.R., and Gregory, A., 2022, Simulation experiments comparing nonstationary design-flood adjustments based on observed annual peak flows in the conterminous United States: Journal of Hydrology X, v. 17, 100115, 24 p., https://doi.org/10.1016/j.hydroa.2021.100115.","productDescription":"100115, 24 p.","ipdsId":"IP-129280","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true},{"id":37273,"text":"Advanced Research Computing (ARC)","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":446110,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.hydroa.2021.100115","text":"Publisher Index Page"},{"id":435655,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9PVRCDS","text":"USGS data release","linkHelpText":"Data for simulation experiments comparing nonstationary design-flood adjustments based on observed annual peak flows in the conterminous United States"},{"id":408467,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -128.32031249999997,\n 24.5271348225978\n ],\n [\n -65.91796875,\n 24.5271348225978\n ],\n [\n -65.91796875,\n 50.958426723359935\n ],\n [\n -128.32031249999997,\n 50.958426723359935\n ],\n [\n -128.32031249999997,\n 24.5271348225978\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"17","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hecht, Jory Seth","contributorId":298019,"corporation":false,"usgs":true,"family":"Hecht","given":"Jory Seth","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":854875,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barth, Nancy A. 0000-0002-7060-8244 nabarth@usgs.gov","orcid":"https://orcid.org/0000-0002-7060-8244","contributorId":298020,"corporation":false,"usgs":true,"family":"Barth","given":"Nancy","email":"nabarth@usgs.gov","middleInitial":"A.","affiliations":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"preferred":true,"id":854876,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ryberg, Karen R. 0000-0002-9834-2046 kryberg@usgs.gov","orcid":"https://orcid.org/0000-0002-9834-2046","contributorId":1172,"corporation":false,"usgs":true,"family":"Ryberg","given":"Karen","email":"kryberg@usgs.gov","middleInitial":"R.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":854877,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gregory, Angela 0000-0002-9905-1240","orcid":"https://orcid.org/0000-0002-9905-1240","contributorId":45018,"corporation":false,"usgs":true,"family":"Gregory","given":"Angela","email":"","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":854938,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70238372,"text":"70238372 - 2022 - Hydrologic recovery after wildfire: A framework of approaches, metrics, criteria, trajectories, and timescales","interactions":[],"lastModifiedDate":"2022-11-18T12:36:54.183072","indexId":"70238372","displayToPublicDate":"2022-10-17T06:32:35","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":12968,"text":"Journal of Hydrology and Hydromechanics","active":true,"publicationSubtype":{"id":10}},"title":"Hydrologic recovery after wildfire: A framework of approaches, metrics, criteria, trajectories, and timescales","docAbstract":"Deviations in hydrologic processes due to wildfire can alter streamflows across the hydrograph, spanning peak flows to low flows. Fire-enhanced changes in hydrologic processes, including infiltration, interception, and evapotranspiration, and the resulting streamflow responses can affect water supplies, through effects on the quantity, quality, and timing of water availability. Post-fire shifts in hydrologic processes can also alter the timing and magnitude of floods and debris flows. The duration of hydrologic deviations from a pre-fire condition or function, sometimes termed hydrologic recovery, is a critical concern for land, water, and emergency managers. We reviewed and summarized terminology and approaches for defining and assessing hydrologic recovery after wildfire, focusing on statistical and functional definitions. We critically examined advantages and drawbacks of current recovery assessment methods, outline challenges to determining recovery, and call attention to selected opportunities for advancement of post-fire hydrologic recovery assessment. Selected challenges included hydroclimatic variability, post-fire land management, and spatial and temporal variability. The most promising opportunities for advancing assessment of hydrologic recovery include: (1) combining statistical and functional recovery approaches, (2) using a greater diversity of post-fire observations complemented with hydrologic modeling, and (3) defining optimal assemblages of recovery metrics and criteria for common hydrologic concerns and regions.","language":"English","publisher":"Institute of Hydrology of the Slovak Academy of Sciences","doi":"10.2478/johh-2022-0033","usgsCitation":"Ebel, B., Wagenbrenner, J.W., Kinoshita, A.M., and Bladon, K.D., 2022, Hydrologic recovery after wildfire: A framework of approaches, metrics, criteria, trajectories, and timescales: Journal of Hydrology and Hydromechanics, v. 70, no. 4, p. 388-400, https://doi.org/10.2478/johh-2022-0033.","productDescription":"13 p.","startPage":"388","endPage":"400","ipdsId":"IP-145116","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":446116,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2478/johh-2022-0033","text":"Publisher Index Page"},{"id":409437,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"70","issue":"4","noUsgsAuthors":false,"publicationDate":"2022-11-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Ebel, Brian A. 0000-0002-5413-3963","orcid":"https://orcid.org/0000-0002-5413-3963","contributorId":211845,"corporation":false,"usgs":true,"family":"Ebel","given":"Brian A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":857271,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wagenbrenner, Joseph W. 0000-0003-3317-5141","orcid":"https://orcid.org/0000-0003-3317-5141","contributorId":264444,"corporation":false,"usgs":false,"family":"Wagenbrenner","given":"Joseph","email":"","middleInitial":"W.","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":857272,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kinoshita, Alicia M.","contributorId":245287,"corporation":false,"usgs":false,"family":"Kinoshita","given":"Alicia","email":"","middleInitial":"M.","affiliations":[{"id":49134,"text":"San Diego State University, California","active":true,"usgs":false}],"preferred":false,"id":857273,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bladon, Kevin D.","contributorId":298225,"corporation":false,"usgs":false,"family":"Bladon","given":"Kevin","email":"","middleInitial":"D.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":857274,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70237684,"text":"70237684 - 2022 - Mechanisms and magnitude of dissolved silica release from a New England salt marsh","interactions":[],"lastModifiedDate":"2022-12-15T15:05:12.015569","indexId":"70237684","displayToPublicDate":"2022-10-16T07:19:38","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1007,"text":"Biogeochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Mechanisms and magnitude of dissolved silica release from a New England salt marsh","docAbstract":"Salt marshes are sites of silica (SiO2) cycling and export to adjacent coastal systems, where silica availability can exert an important control over coastal marine primary productivity. Mineral weathering and biologic fixation concentrate silica in these systems; however, the relative contributions of geologic versus biogenic silica dissolution to this export are not known. We collected water samples from the tidal creek of a relatively undisturbed New England (USA) salt marsh over 13 tidal cycles in spring, summer, and fall 2014–2016 to determine patterns of dissolved silica (DSi) concentration in the water entering and leaving the marsh. DSi concentrations in the tidal creek peaked in the summer and were at a minimum in the fall. Additionally, we analyzed DSi concentrations and Ge/Si ratios in marsh porewater and groundwater samples as a tracer of DSi origin. Ge/Si ratios in the porewater, subterranean estuary, and fresh groundwater averaged 6.3 ± 0.31 µmol/mol, which is consistent with production via silicate weathering rather than biogenic silica dissolution. These results highlight a previously unstudied role marsh sediment plays in coastal biogeochemistry by supplying DSi to coastal ecosystems. This marsh exported 1170 mmol DSi m−2 year−1, 85% of which originated from porewater exchange, with minor contributions from brackish groundwater discharge from the subterranean estuary. Examining these values in the context of the other known DSi inputs indicates that coastal marshes provide ~ 75% of the annual silica inputs into the adjacent estuary, Waquoit Bay.
This study characterized the concentration and quality of dissolved organic carbon (DOC) in the McKenzie River, a relatively undeveloped watershed in western Oregon, and its link to forming disinfection by-products (DBPs) in treated drinking water. The study aimed to identify the primary source(s) of DOC in source water for the Eugene Water & Electric Board’s (EWEB) conventional treatment plant on the McKenzie River near river mile 11, upstream of Hayden Bridge. The two classes of regulated compounds examined—trihalomethanes (THMs) and haloacetic acids (HAAs)—form when organic carbon in raw source water reacts with chlorine and (or) bromine during water treatment.
The objectives of the study were to:
Eleven storms were sampled synoptically in upstream-to-downstream fashion to provide a “snapshot” of water quality conditions at four sites on the McKenzie River from Frissell Bridge (6 miles downstream from Trail Bridge Reservoir) to the EWEB water treatment plant at Hayden Bridge and nine contributing tributaries. Storms included late summer and early autumn “first flush” events and late autumn, winter, and spring storms spanning a range in streamflows from 3,000 to 26,000 cubic feet per second as measured in the main stem McKenzie River at the EWEB water intake.
Water samples were analyzed for DOC concentrations and optical properties (fluorescence and ultraviolet absorbance [UVA]) across a range of wavelengths to characterize the quantity and quality of dissolved organic matter (DOM) in the McKenzie River at the drinking water intake and upstream locations. Paired sets of source and finished water samples were collected at the EWEB treatment plant to identify DOC quality parameters in raw source water that might predict DBP concentrations in finished drinking water.
DOC concentrations were relatively low in the McKenzie River (0.4–3 milligrams per liter [mg/L]; average 1.5 mg/L) but much higher in the tributaries. The highest DOC concentrations occurred during “first flush” storms in October 2012 and September 2013; the highest value (16 mg/L) was measured at the 52nd Street stormwater outfall. The average DOC concentration in the lower basin-tributaries was 3.8 mg/L; three middle basin tributaries—Quartz, Gate, and Haagen Creeks, which drain private forestland with less coniferous forest compared with other higher elevation tributaries— had slightly lower average DOC concentrations (2.8 mg/L). These middle-basin watersheds may be important sources of DOC and DBP precursors to the McKenzie River, even more so than the lower basin tributaries, depending on their flows (and loads). This is particularly true after the September 2020 Holiday Farm fire, which burned much of this area.
DOC concentrations increased 68 percent in the McKenzie River between the uppermost reference site at Frissell Bridge and Vida; this includes drainage from Quartz Creek, Blue River Lake and Cougar Reservoir, which all contributed DOC to the main stem. In contrast, the lowermost tributaries draining most of the agricultural and urban land did not have a large effect on DOC in the McKenzie River despite their higher DOC concentrations because of their presumed relatively low streamflows and, consequently, DOC loads. Apart from the continuous flow monitors in the McKenzie River and some tributaries (Blue River and South Fork McKenzie River, and streamflow at Hayden Bridge and Vida, Camp Creek and some other locations), streamflow was not assessed during sample collection for this study. This lack of streamflow data precludes a detailed analysis of loads, which is discussed in the future studies section.
All DBP concentrations in finished drinking water were less than EPA maximum contaminant levels (MCLs) of 0.080 mg/L for the four trihalomethanes (THM4) and 0.060 mg/L for five haloacetic acids (HAA5). During the 11 storm sampling events the maximum summed concentrations were about 0.040 mg/L for both THM4 and HAA5. Compliance monitoring samples, collected separately by EWEB, yielded some higher concentrations—0.046 mg/L THM4 and 0.047 HAA5—during the December 2012 storm. The corresponding benchmark quotient (BQ) values, which indicate how close a measured DBP concentration is to the MCL, were 0.58 and 0.78, respectively, for THM4 and HAA5. Compared with a similar 2007–08 McKenzie River study that did not target storm events, concentrations of THM4 and HAA5 in finished water were 68 percent and 33 percent higher, respectively, during the current study.
Due to the high dilution rates in the McKenzie River main stem, many of the individual fluorescence excitation-emission measurements were low (<0.1 Raman units) and approached analytical detection limits. Parallel factor analysis (PARAFAC) resulted in a five-component model (C1–C5) that represents five unique organic fluorophores. Components C1, C2, and C3 represent DOM associated with soil-derived, humic-like, more degraded organic matter. In contrast, components C4 and C5 represent “fresher” DOM, derived from terrestrial and aquatic plants, including algae and cyanobacteria that are common in the McKenzie River and its tributaries and reservoirs. The fluorescence data and PARAFAC modeling suggest that most of the DOC in the McKenzie River originated from terrestrial sources (primarily components C1 and C2). The largest increases in DOC in the main stem occurred in the reach upstream of Vida, from inflows by Quartz Creek, Blue River, South Fork McKenzie River, and other tributaries.
Concentrations of DBPs in EWEB’s finished drinking water were positively correlated with DOC concentrations in raw source water (THM4, p<0.05; HAA5, p<0.01) for paired samples collected 12−24 hours apart. DOC concentrations were significantly positively correlated (p<0.001) with laboratory-based fluorescent dissolved organic matter (fDOM) measurements, suggesting fDOM as a useful parameter for monitoring and predicting DOC concentration in surface water and DBP concentrations in finished water.
Of all the PARAFAC components in surface water, C5 had the highest correlations with DBPs in finished water (rho = 0.77–0.84, p<0.01), followed by components C1 and C2 (rho = 0.75 and 0.71, respectively, p<0.01). This C5 carbon is associated with recently produced DOM, possibly from decomposed terrestrial and aquatic vegetation. Model loadings of these three components were considerably higher in the sampled tributaries relative to the main stem McKenzie River, with most of the observed increases in the main stem apparent at Vida. This points to Quartz Creek or other tributaries in the reach between Frissell Bridge and the sampling site near Vida (South Fork McKenzie and Blue Rivers) as potentially key contributors of DOM source material that leads to the production of DBPs in treated drinking water. A limited load analysis showed that the reservoirs contributed 8–37 percent of the instantaneous DOC loads observed at Vida at the time of sampling, which suggests other sources such as Quartz Creek and other streams in the reach between Frissell Bridge and Vida are more important.
Random forest analyses identified PARAFAC components C1 and C5 and fluorescence peaks A, C, M, T and N as the best predictors for HAA5 concentrations in finished drinking water, explaining 62.5 percent of the variation. The best predictors for THM4 were C1, C4 + C5, and peaks T, A, and N, which explained 33 percent of the variation.
Several land cover and vegetation classes were correlated with DOC concentration and other optical measurements. The percentage of evergreen forest in each of the subwatersheds sampled was negatively correlated (p<0.001) with DOC concentration and many optical indicators of DOM quantity: UVA254, fDOM, and all of the fluorescence peaks. In contrast, mixed (deciduous) forest was positively correlated (p<0.001) with DOC, fDOM, UVA254, and several fluorescence peaks, demonstrating the importance of deciduous leaf fall in generating DOC and DBP precursors.
The high level of human activities in the middle and lower portion of the basin—including timber harvesting and road construction on private forestland, agricultural, rural, industrial, and urban development—have resulted in the greatest loss in native coniferous and mixed deciduous forests in the basin. DOC loading from these tributaries and reservoir releases, which contain DOC from terrestrial and aquatic productivity, both enrich the McKenzie River. Concentrations of DOC increased an average of 71 percent (range 30–120 percent) in the McKenzie River between Frissell Bridge, the upstream reference site, and Vida. PARAFAC components C1, C2, and C5—which were correlated with DBPs in finished water—increased, on average, 109–136 percent (range 20–250 percent) in this same Frissell-to-Vida reach. These increases occur from input of tributaries in the middle basin such as Quartz Creek and others, as noted above.
Future monitoring, field, and lab studies can improve our understanding of seasonal and spatial sources of organic carbon contributing DBP precursors to the McKenzie River and allow detection of long-term trends resulting from the recent Holiday Farm Fire, which burned 173,393 acres of forestland, including riparian areas along the main stem, and numerous structures, homes, and outbuildings in September 2020. Future studies could examine DOC fluxes and flushing of carbon from the watershed, investigate the role of precipitation amount and intensity in mobilizing carbon and sediment, and evaluate impacts to aquatic communities and human health as part of a post-fire assessment. Other areas ripe for study include evaluating the impacts of potential temperature increases on carbon sequestration and decomposition in the burned and unburned forests and identifying practices that foster sequestration of carbon in forest soils.
The use of fluorescence sensors such as fDOM to monitor the concentration and composition of raw water supplies may be improved for detection of specific DBP precursors, to provide continuous and real-time information to treatment plant operators. Future studies that monitor DOM amount and quality, and DBP Formation Potential (FP), particularly during storm events, paired with streamflow measurements, as suggested above, could help identify areas that contribute high DOC loads and thus help managers identify the key areas to focus restoration activities. Other studies could examine treatment options for currently regulated DBPs and potentially unregulated compounds, including advanced biological treatments for their removal.
This study was a collaboration between the U.S. Geological Survey (USGS) and EWEB in Eugene, Oregon, with additional funding provided from USGS Cooperative Matching Funds Program.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225010","collaboration":"Prepared in Cooperation with Eugene Water & Electric Board","usgsCitation":"Carpenter, K.D., Kraus, T.E., Hansen, A.M., Downing, B.D., Goldman, J.H., Haynes, J., Donahue, D., and Morgenstern, K., 2022, Sources and characteristics of dissolved organic carbon in the McKenzie River, Oregon, related to the formation of disinfection by-products in treated drinking water: U.S. Geological Survey Scientific Investigations Report 2022–5010, 50 p., https://doi.org/10.3133/sir20225010.","productDescription":"Report: viii, 50 p.; Table","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-117763","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":408395,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9QPSIG3","text":"USGS data release","description":"USGS data release.","linkHelpText":"Absorbance and fluorescence measurements and concentrations of disinfection by-products in source water and finished water in the McKenzie River Basin, Oregon: 2012-2014"},{"id":408366,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2022/5010/sir20225010_table1.1.xlsx","text":"Table 1.1","size":"37 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2022-5010 table 1.1"},{"id":408301,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5010/images"},{"id":408299,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5010/coverthb2.jpg"},{"id":408302,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5010/sir20225010.XML"},{"id":408300,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5010/sir20225010.pdf","text":"Report","size":"4.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5010"},{"id":502297,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113766.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Oregon","otherGeospatial":"McKenzie River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.125,\n 43.8\n ],\n [\n -121.875,\n 43.8\n ],\n [\n -121.875,\n 44.3\n ],\n [\n -123.125,\n 44.3\n ],\n [\n -123.125,\n 43.8\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oregon Water Science Center
U.S. Geological Survey
Oil spills can inflict mortality and injury on bird populations; many of these deaths involve starvation resulting from thermoregulatory costs incurred by oiling of birds’ feathers. However, the fates and responses of sublethally oiled birds are poorly known. Due to this knowledge gap and the potential for birds to die far from the spill site, resource risk and injury assessors need tools to make informed estimates for delayed deaths and lost reproductive capacity in these birds. Focusing on the thermoregulatory cost of oiled feathers, we present a model addressing one facet of the effects of sublethal oiling on birds. Using mallard-like ducks as a model organism, we combined values from previous laboratory studies of oiled birds with a modified version of an existing temperature-influenced avian migration energetics model. Using this model, we examined the potential effects of oiling on general migration patterns, changes in energetic gains required to compensate for oiling, and starvation. We assessed all metrics across multiple oiling severities; we assessed starvation across both oiling severity and body condition. Median estimates for delays in spring migration were one to two months for trace and lightly oiled birds, and we predicted arrested spring migration in moderately oiled birds. Median estimates of required increases in energetic gains to offset costs of increased thermoregulation ranged from 20.3% to 88.6% depending on severity of oiling. We predicted starvation within four weeks for most combinations of oiling severity and body condition at the median predicted minimum wintering temperature of unoiled birds (-4.9°C). However, at the average winter temperature of the southernmost model latitude (10.8°C), we predicted only moderately oiled birds in less-than-excellent body condition had the potential to starve within a four-week time frame. Due to the potential for even trace oiling to delay spring migration and decrease body condition, the thermoregulatory costs of sublethal oiling during spring migration could reduce a bird's reproductive capacity. Future research integrating this initial energetics-based model into a spatially explicit, population scale migration model could provide additional insight into the potential effects of sublethal oiling on reproduction and survival. Such an integrated model could strengthen risk predictions and injury assessments for birds subjected to sublethal oiling.
The late Pleistocene was a climatically dynamic period, with abrupt shifts between cool-wet and warm-dry conditions. Increased effective precipitation supported large pluvial lakes and long-lived spring ecosystems in valleys and basins throughout the western and southwestern U.S., but the source and seasonality of the increased precipitation are debated. Increases in the proportions of C4/(C4+ C3) grasses in the diets of large grazers have been ascribed both to increases in summer precipitation and lower atmospheric CO2 levels. Here we present stable carbon and oxygen isotope data from tooth enamel of late Pleistocene herbivores recovered from paleowetland deposits at Tule Spring Fossil Beds National Monument in the Las Vegas Valley of southern Nevada, as well as modern herbivores from the surrounding area. We use these data to investigate whether winter or summer precipitation was responsible for driving the relatively wet hydroclimate conditions that prevailed in the region during the late Pleistocene. We also evaluate whether late Pleistocene grass C4/(C4+ C3) was higher than today, and potential drivers of any changes.
Tooth enamel δ18O values for Pleistocene Equus, Bison, and Mammuthus are generally low (average 22.0 ± 0.7‰, 2 s.e., VSMOW) compared to modern equids (27.8 ± 1.5‰), and imply lower water δ18O values (−16.1 ± 0.8‰) than modern precipitation (−10.5‰) or in waters present in active springs and wells in the Las Vegas Valley (−12.9‰), an area dominated by winter precipitation. In contrast, tooth enamel of Camelops (a browser) generally yielded higher δ18O values (23.9 ± 1.1‰), possibly suggesting drought tolerance. Mean δ13C values for the Pleistocene grazers (−6.6 ± 0.7‰, 2 s.e., VPDB) are considerably higher than for modern equids (−9.6 ± 0.4‰) and indicate more consumption of C4 grass (17 ± 5%) than today (4 ± 4%). However, calculated C4 grass consumption in the late Pleistocene is strikingly lower than the proportion of C4 grass taxa currently present in the valley (55–60%). δ13C values in Camelops tooth enamel (−7.7 ± 1.0‰) are interpreted as reflecting moderate consumption (14 ± 8%) of Atriplex (saltbush), a C4 shrub that flourishes in regions with hot, dry summers.
Lower water δ18O values, lower abundance of C4 grasses, and the inferred presence of Atriplex are all consistent with general circulation models for the late Pleistocene that show enhanced delivery of winter precipitation, sourced from the north Pacific, into the interior western U.S. but do not support alternative models that infer enhanced delivery of summer precipitation, sourced from the tropics. In addition, we hypothesize that dietary competition among the diverse and abundant Pleistocene fauna may have driven the grazers analyzed here to feed preferentially on C4 grasses. Dietary partitioning, especially when combined with decreased pCO2 levels during the late Pleistocene, can explain the relatively high δ13C values observed in late Pleistocene grazers in the Las Vegas Valley and elsewhere in the southwestern U.S. without requiring additional summer precipitation. Pleistocene hydroclimate parameters derived from dietary and floral records may need to be reevaluated in the context of the potential effects of dietary preferences and lower pCO2 levels on the stability of C3 vs. C4 plants.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.quascirev.2022.107784","usgsCitation":"Kohn, M.J., Springer, K.B., Pigati, J.S., Reynard, L., Drewicz, A.E., Crevier, J., and Scott, E., 2022, Seasonality of precipitation in the southwestern United States during the late Pleistocene inferred from stable isotopes in herbivore tooth enamel: Quaternary Science Reviews, v. 296, 107784, 21 p., https://doi.org/10.1016/j.quascirev.2022.107784.","productDescription":"107784, 21 p.","ipdsId":"IP-141465","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":446131,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.quascirev.2022.107784","text":"Publisher Index Page"},{"id":435657,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9DBH6V7","text":"USGS data release","linkHelpText":"Data release for Seasonality of precipitation in 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report","interactions":[],"lastModifiedDate":"2022-10-27T16:47:26.966721","indexId":"cir1497","displayToPublicDate":"2022-10-13T12:52:14","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":307,"text":"Circular","code":"CIR","onlineIssn":"2330-5703","printIssn":"1067-084X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1497","displayTitle":"U.S. Geological Survey—Department of the Interior Region 11, Alaska—2021–22 Biennial Science Report","title":"U.S. Geological Survey—Department of the Interior Region 11, Alaska—2021–22 biennial science report","docAbstract":"U.S. Geological Survey (USGS) Mission: The USGS national mission is to monitor, analyze, and predict the current and evolving dynamics of complex human and natural Earth-system interactions, and to deliver actionable information at scales and timeframes relevant to decision-makers. Consistent with the national mission, the USGS in Alaska provides timely and objective scientific information to help address issues and inform management decisions across five inter-connected themes:
The USGS in Alaska consists of approximately 350 scientists and support staff working in three Alaska-based science centers, a Cooperative Research Unit, and USGS centers outside Alaska, with a combined annual science budget of about $60 million. In the last 5 years, USGS research in Alaska has produced many scientific benefits resulting from more than 1,050 publications. Publications relevant to Alaska can be conveniently searched by keyword through the USGS Publications Warehouse at https://pubs.er.usgs.gov/search?q=Alaska.
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Alaska Science Center
U.S. Geological Survey
4210 University Drive
Anchorage, Alaska 99508
The U.S. Geological Survey, in cooperation with the Bureau of Land Management (BLM), continued streamflow data collection in water years 2013–21 to update daily streamflow regressions and annual and semimonthly streamflow statistics initially developed in 2012 for streams designated as “wild,” “scenic,” or “recreational” under the National Wild and Scenic Rivers System in the Owyhee Canyonlands Wilderness in southwestern Idaho. To sustain “outstanding remarkable values” in the Owyhee Canyonlands Wilderness, BLM determined that maintaining specific streamflow conditions in rivers was important for sustaining ecological health, recreational opportunities, and water demands for stock water and irrigation in a region with increased pressure from upstream land development. Streamflow statistics previously developed using regional regressions based on limited number of streamgages and generalized basin characteristics were determined to inaccurately represent hydrologic characteristics in the Owyhee Canyonlands Wilderness.
In this study, updated streamflow regressions and statistics are provided for 11 partial-record sites in the Owyhee Canyonlands Wilderness using 311 additional streamflow measurements. A partial-record Maintenance of Variance Extension, Type 1 (MOVE.1) streamflow regression method was used to relate discrete streamflow measurements collected at partial-record sites with daily mean streamflow at nearby index sites. The updated regressions were used to estimate a synthetic daily mean streamflow record at each partial-record site for the period of record of the selected index site. The computed synthetic streamflow record was then used to determine annual and semimonthly streamflow statistics at each partial-record site. Annual bankfull streamflow statistics were calculated at each partial-record site using the computed bankfull streamflow at the selected index site and the updated streamflow regression.
Additional streamflow measurements representing a larger range of hydrologic conditions since 2012, reevaluation of index site selection, and updated regression techniques improved streamflow statistic estimates in the Owyhee Canyonlands Wilderness. Regression performance was evaluated based on the coefficient of determination (R2) between the partial-record and index sites, percent bias, and similarity of basin characteristics between the selected index site and the partial-record site. Generally, the updated regressions performed well for partial-record sites with an index site located upstream or downstream on the same stream. Regression performance was degraded and less robust for index sites located farther away from the corresponding partial-record site. Additional streamflow measurements at partial-record sites with few measurements over a small range in hydrologic conditions could improve regression performance and reduce prediction intervals. Furthermore, additional index sites in the Owyhee Canyonlands Wilderness could improve the updated streamflow regressions and statistics.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225095","collaboration":"Prepared in cooperation with the Bureau of Land Management","usgsCitation":"Dudunake, T.J., and Ducar, S.D., 2022, Updated annual and semimonthly streamflow statistics for Wild and Scenic Rivers, Owyhee Canyonlands Wilderness, southwestern Idaho, 2021 (ver. 1.1, May 2024): U.S. Geological Survey Scientific Investigations Report 2022–5095, 31 p., https://doi.org/10.3133/sir20225095.","productDescription":"Report: viii, 31 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-128129","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":408220,"rank":7,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5095/sir20225095.XML"},{"id":408218,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9XSJA24","text":"USGS data release","description":"USGS data release","linkHelpText":"Streamflow regressions and annual and semimonthly exceedance probability statistics for Wild and Scenic Rivers, Owyhee Canyonlands Wilderness, Idaho"},{"id":408217,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5095/sir20225095.pdf","text":"Report","size":"5.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5095"},{"id":408221,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/sir20225095/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2022-5095"},{"id":408219,"rank":6,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5095/images"},{"id":428468,"rank":5,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2022/5095/versionHistory.txt","size":"1 KB","linkFileType":{"id":2,"text":"txt"},"description":"Version History"},{"id":408216,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5095/coverthb2.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Owyhee Canyonlands Wilderness","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.02636718749999,\n 42.00848901572399\n ],\n [\n -114.14794921875,\n 42.00848901572399\n ],\n [\n -114.14794921875,\n 43.50872101129684\n ],\n [\n -117.02636718749999,\n 43.50872101129684\n ],\n [\n -117.02636718749999,\n 42.00848901572399\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Road
Boise, Idaho 83702-4520
This chapter presents a physics-guided recurrent neural network model (PGRNN) for predicting water temperature in lake systems. Standard machine learning (ML) methods, especially deep learning models, often require a large amount of labeled training samples, which are often not available in scientific problems due to the substantial human labor and material costs associated with data collection. ML models have found tremendous success in several commercial applications, e.g., computer vision and natural language processing. The chapter presents PGRNN as a general framework for modeling physical processes in engineering and environmental systems. The proposed PGRNN explicitly incorporates physical laws such as energy conservation or mass conservation. In particular, researchers started pursing this direction by using residual modeling, where an ML model is learned to predict the errors, or residuals, made by a physics-based model. Advanced ML models, especially deep learning models, often require a large amount of training data for tuning model parameters.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Knowledge-guided machine learning: Accelerating discovery using scientific knowledge and data","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Taylor & Francis","doi":"10.1201/9781003143376-16","usgsCitation":"Jia, X., Willard, J., Karpatne, A., Read, J., Zwart, J.A., Steinbach, M., and Kumar, V., 2022, Physics-guided recurrent neural networks for predicting lake water temperature, chap. 16 of Knowledge-guided machine learning: Accelerating discovery using scientific knowledge and data, p. 373-398, https://doi.org/10.1201/9781003143376-16.","productDescription":"26 p.","startPage":"373","endPage":"398","ipdsId":"IP-132700","costCenters":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"links":[{"id":408169,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Jia, Xiaowei 0000-0001-8544-5233","orcid":"https://orcid.org/0000-0001-8544-5233","contributorId":237807,"corporation":false,"usgs":false,"family":"Jia","given":"Xiaowei","email":"","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":854183,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Willard, Jared","contributorId":237808,"corporation":false,"usgs":false,"family":"Willard","given":"Jared","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":854184,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Karpatne, Anuj","contributorId":237810,"corporation":false,"usgs":false,"family":"Karpatne","given":"Anuj","email":"","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":854187,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Read, Jordan 0000-0002-3888-6631","orcid":"https://orcid.org/0000-0002-3888-6631","contributorId":221385,"corporation":false,"usgs":true,"family":"Read","given":"Jordan","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":854188,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zwart, Jacob Aaron 0000-0002-3870-405X","orcid":"https://orcid.org/0000-0002-3870-405X","contributorId":237809,"corporation":false,"usgs":true,"family":"Zwart","given":"Jacob","email":"","middleInitial":"Aaron","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":854189,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Steinbach, Michael","contributorId":237811,"corporation":false,"usgs":false,"family":"Steinbach","given":"Michael","email":"","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":854185,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kumar, Vipin","contributorId":237812,"corporation":false,"usgs":false,"family":"Kumar","given":"Vipin","email":"","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":854186,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70237347,"text":"70237347 - 2022 - Planetary-scale change to the biosphere signalled by global species translocations can be used to identify the Anthropocene","interactions":[],"lastModifiedDate":"2022-10-11T17:10:30.606714","indexId":"70237347","displayToPublicDate":"2022-10-11T11:59:16","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2998,"text":"Palaeontology","active":true,"publicationSubtype":{"id":10}},"title":"Planetary-scale change to the biosphere signalled by global species translocations can be used to identify the Anthropocene","docAbstract":"We examine three distinctive biostratigraphic signatures associated with: hunting and gathering, landscape domestication, and globalisation. All three signatures have significant fossil records of regional importance that can be correlated inter-regionally and help describe the developing pattern of human expansion and appropriation of resources. While none have individual first or last appearances that provide a globally isochronous marker, all three signatures overlap stratigraphically, in that they are part of a continuum of change, with complex regional patterns. Here we show that during the later stages of globalisation, late 19th to 20th century records of species translocations can be used to build an interconnected web of palaeontological correlation with decadal or sub-decadal precision that dovetails with other stratigraphic markers for the Anthropocene. This palaeontological web is also a proxy for accelerating species extinction and of a state shift in the biosphere in the 20th century.","language":"English","publisher":"John Wiley & Sons","doi":"10.1111/pala.12618","usgsCitation":"Williams, M., Leinfelder, R., Barnosky, A.D., Head, M., McCarthy, F.M., Cearreta. Alejandro, Himson, S.J., Holmes, R., Waters, C.N., Zalasiewicz, J., Turner, S., McGann, M., Hadly, E.A., Stegner, M.A., Pilkington, P.M., Kaiser, J., Berrio, J.C., Wilkinson, I.P., Zinke, J., and DeLong, K., 2022, Planetary-scale change to the biosphere signalled by global species translocations can be used to identify the Anthropocene: Palaeontology, v. 65, no. 4, e12618, 25 p., https://doi.org/10.1111/pala.12618.","productDescription":"e12618, 25 p.","ipdsId":"IP-135084","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":446162,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://figshare.com/articles/journal_contribution/Planetary-scale_change_to_the_biosphere_signalled_by_global_species_translocations_can_be_used_to_identify_the_Anthropocene/19625769","text":"Publisher Index Page"},{"id":408168,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"65","issue":"4","noUsgsAuthors":false,"publicationDate":"2022-08-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Williams, Mark","contributorId":214696,"corporation":false,"usgs":false,"family":"Williams","given":"Mark","affiliations":[],"preferred":false,"id":854211,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Leinfelder, Reinhold","contributorId":297457,"corporation":false,"usgs":false,"family":"Leinfelder","given":"Reinhold","email":"","affiliations":[{"id":64399,"text":"Freie University, Berlin, Germany","active":true,"usgs":false}],"preferred":false,"id":854212,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barnosky, Anthony D.","contributorId":197553,"corporation":false,"usgs":false,"family":"Barnosky","given":"Anthony","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":854213,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Head, Martin J","contributorId":297458,"corporation":false,"usgs":false,"family":"Head","given":"Martin J","affiliations":[{"id":64401,"text":"Brock University, Ontario, Canada","active":true,"usgs":false}],"preferred":false,"id":854214,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McCarthy, Francine M G","contributorId":297459,"corporation":false,"usgs":false,"family":"McCarthy","given":"Francine","email":"","middleInitial":"M G","affiliations":[{"id":64401,"text":"Brock University, Ontario, Canada","active":true,"usgs":false}],"preferred":false,"id":854215,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cearreta. 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Estimates were generated using a long short-term memory deep learning model and compared to existing process-based and linear regression models. Model training was optimized for prediction on unmonitored lakes through cross-validation that held out lakes to assess generalizability and estimate error. On the held-out lakes with in situ observations, median lake-specific error was 1.24°C, and the overall root mean squared error was 1.61°C. This dataset increases the number of lakes with daily temperature predictions when compared to existing datasets, as well as substantially improves predictive accuracy compared to a prior empirical model and a debiased process-based approach (2.01°C and 1.79°C median error, respectively).
","language":"English","publisher":"Wiley","doi":"10.1002/lol2.10249","usgsCitation":"Willard, J.D., Read, J., Topp, S.N., Hansen, G., and Kumar, V., 2022, Daily surface temperatures for 185,549 lakes in the conterminous United States estimated using deep learning (1980–2020): Limnology & Oceanography: Letters, v. 7, no. 4, p. 287-301, https://doi.org/10.1002/lol2.10249.","productDescription":"15 p.","startPage":"287","endPage":"301","ipdsId":"IP-127157","costCenters":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"links":[{"id":446163,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/lol2.10249","text":"Publisher Index Page"},{"id":435660,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9CEMS0M","text":"USGS data release","linkHelpText":"Daily surface temperature predictions for 185,549 U.S. lakes with associated observations and meteorological 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0000-0003-4434-051X","orcid":"https://orcid.org/0000-0003-4434-051X","contributorId":297456,"corporation":false,"usgs":false,"family":"Willard","given":"Jared","email":"","middleInitial":"D.","affiliations":[{"id":64397,"text":"University of Minnesota Department of Computer Science","active":true,"usgs":false}],"preferred":false,"id":854206,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Read, Jordan 0000-0002-3888-6631","orcid":"https://orcid.org/0000-0002-3888-6631","contributorId":221385,"corporation":false,"usgs":true,"family":"Read","given":"Jordan","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":854207,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Topp, Simon Nemer 0000-0001-7741-5982","orcid":"https://orcid.org/0000-0001-7741-5982","contributorId":268229,"corporation":false,"usgs":true,"family":"Topp","given":"Simon","email":"","middleInitial":"Nemer","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":854208,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hansen, Gretchen J. A.","contributorId":174557,"corporation":false,"usgs":false,"family":"Hansen","given":"Gretchen J. A.","affiliations":[{"id":27469,"text":"Wisconsin Department of Natural Resources, Madison, Wisconsin","active":true,"usgs":false}],"preferred":false,"id":854209,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kumar, Vipin","contributorId":237812,"corporation":false,"usgs":false,"family":"Kumar","given":"Vipin","email":"","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":854210,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70237612,"text":"70237612 - 2022 - Identifying nutrient sources and sinks to the South Platte River and Cherry Creek, Denver, CO, during low-flow conditions in 2019–2020","interactions":[],"lastModifiedDate":"2022-12-15T14:54:03.689933","indexId":"70237612","displayToPublicDate":"2022-10-11T09:53:07","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"title":"Identifying nutrient sources and sinks to the South Platte River and Cherry Creek, Denver, CO, during low-flow conditions in 2019–2020","docAbstract":"Elevated concentrations and loads of nutrients in the South Platte River and Cherry Creek in Denver, Colorado, may have adverse effects on those streams and downstream water bodies, including increased production of algae, eutrophication, and decreased recreational opportunities. This article describes streamflow and concentrations and loads of nutrients for the South Platte River and Cherry Creek in Denver based on data collected during two longitudinal Lagrangian sampling campaigns in low-flow conditions in fall of 2019 and 2020. The results are used to assess sources and sinks of nutrients in the study area and help to establish baseline conditions against which future changes in nutrient concentrations and loads can be assessed. Discharges from Chatfield and Cherry Creek Reservoirs, storm drains, and most tributaries to the South Platte River, and Cherry Creek were generally small sources of streamflow and nutrient loads in both years. The Marcy Gulch, South Platte Water Renewal, and Robert W. Hite wastewater treatment plants were larger sources of streamflow and nutrient loads. The Burlington Ditch was a sink for streamflow and nutrient loads, diverting more than 95% of the South Platte River during the two sampling campaigns. Most other sinks were associated with decreases in streamflow between sampling sites. Golf courses were a potential source of nutrients for Cherry Creek but not for the South Platte River.
","language":"English","publisher":"Wiley","doi":"10.1002/rra.4060","usgsCitation":"Battaglin, W., and Chapin, T.W., 2022, Identifying nutrient sources and sinks to the South Platte River and Cherry Creek, Denver, CO, during low-flow conditions in 2019–2020: River Research and Applications, v. 38, no. 10, p. 1860-1883, https://doi.org/10.1002/rra.4060.","productDescription":"24 p.","startPage":"1860","endPage":"1883","ipdsId":"IP-131828","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":408322,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","city":"Denver","otherGeospatial":"Cherry Creek, South Platte River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.23803710937499,\n 39.35978526869001\n ],\n [\n -103.919677734375,\n 39.35978526869001\n ],\n [\n -103.919677734375,\n 40.66397287638688\n ],\n [\n -105.23803710937499,\n 40.66397287638688\n ],\n [\n -105.23803710937499,\n 39.35978526869001\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"38","issue":"10","noUsgsAuthors":false,"publicationDate":"2022-10-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Battaglin, William A. 0000-0001-7287-7096","orcid":"https://orcid.org/0000-0001-7287-7096","contributorId":204638,"corporation":false,"usgs":true,"family":"Battaglin","given":"William A.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":854652,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chapin, Tanner William 0000-0003-3905-3241","orcid":"https://orcid.org/0000-0003-3905-3241","contributorId":297923,"corporation":false,"usgs":true,"family":"Chapin","given":"Tanner","email":"","middleInitial":"William","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":854653,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70240887,"text":"70240887 - 2022 - Decision support for aquatic restoration based on species-specific responses to disturbance","interactions":[],"lastModifiedDate":"2023-02-28T13:05:03.312497","indexId":"70240887","displayToPublicDate":"2022-10-11T07:02:23","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Decision support for aquatic restoration based on species-specific responses to disturbance","docAbstract":"Disturbances to aquatic habitats are not uniformly distributed within the Great Lakes and acute effects can be strongest in nearshore areas where both landscape and within lake effects can have strong influence. Furthermore, different fish species respond to disturbances in different ways. A means to identify and evaluate locations and extent of disturbances that affect fish is needed throughout the Great Lakes. We used partial Canonical Correspondence Analysis to separate “natural” effects on nearshore assemblages from disturbance effects. Species-specific quadratic models of fish abundance as functions of in-lake disturbance or watershed-derived disturbance were developed separately for each of 35 species and lakewide predictions mapped for Lake Erie. Most responses were unimodal and more species decreased in abundance with increasing watershed disturbance than increased. However, eight species increased in abundance with current in-lake disturbance conditions. Optimum Yellow Perch (Perca flavescens) abundance occurred at in-lake disturbance values less than the gradient mean, but decreased continuously from minimum watershed disturbance to higher values. Bands of optimum in-lake conditions occurred throughout the eastern and western portions of the Lake Erie nearshore zone; some areas were less disturbed than desirable. However, watershed-derived disturbance conditions were generally poor for Yellow Perch throughout the lake. In contrast, optimum Smallmouth Bass (Micropterus dolomieu) abundance occurred at in-lake disturbance values greater than the gradient mean and continuously increased with increasing watershed disturbance. Smallmouth Bass responses to disturbance indicated that most of the nearshore zone was less disturbed than is desirable and were most abundant in areas that the Yellow Perch response indicated were highly disturbed. Mapping counts of species response models that agreed on the disturbance level in each spatial unit of the nearshore zone showed a fine-scale mosaic of areas in which habitat restoration may benefit many or few species. This tool may assist managers in prioritizing conservation and restoration efforts and evaluating environmental conditions that may be improved.
Neonicotinoid insecticide use has increased over the last decade, including as agricultural seed treatments (application of chemical in a coating to the seed prior to planting). In California, multiple crops, including lettuce, can be grown using neonicotinoid treated seeds or receive a direct neonicotinoid soil application (drenching) at planting. Using research plots, this study compared pesticide runoff in four treatments: (1) imidacloprid seed treatment; (2) clothianidin seed treatment; (3) imidacloprid drench and an azoxystrobin seed treatment; and (4) a control with no pesticidal treatment. Neonicotinoid and azoxystrobin concentrations were measured in surface water runoff during six irrigations events in the 2020 growing seasons. Results showed runoff concentrations up to 1308 (±1200) ng L−1 for imidacloprid drench treatment, 431 (±100) ng L−1 for clothianidin seed treatment, 135 (±60) ng L−1 for imidacloprid seed treatment, 13 (±10) ng L−1 for azoxystrobin seed treatment (treatments averaged). The percent of applied mass in runoff over the entire sampling period varied by compound; the imidacloprid seed treatment and drench were similar (0.015 and 0.019%, respectively) to the clothianidin seed treatment (0.036%) while the azoxystrobin seed treatment was much higher (15%). Although the proportion of imidacloprid in runoff was similar for imidacloprid treatments, the mass applied during soil drench was > 4x the amount applied from the imidacloprid seed treatment. Surface soils were collected before planting and at the end of the trial. The neonicotinoids were detected in soil throughout the study and average maximum concentrations were 9–13 ng g−1; azoxystrobin was detected in only two soils at concentrations up to 0.57 ng g−1. These results elucidate the comparative mass runoff resulting from planting treated seed and soil drench applications and highlight the value of additional work to characterize off-site transport from the many commodities that may be utilizing treated seeds.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envpol.2022.120325","usgsCitation":"Woodward, E., Hladik, M.L., Main, A., Cahn, M., Orlando, J., and Teerlink, J., 2022, Comparing imidacloprid, clothianidin, and azoxystrobin runoff from lettuce fields using a soil drench or treated seeds in the Salinas Valley, California: Environmental Pollution, v. 315, 120325, 8 p., https://doi.org/10.1016/j.envpol.2022.120325.","productDescription":"120325, 8 p.","ipdsId":"IP-141733","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":446170,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envpol.2022.120325","text":"Publisher Index Page"},{"id":408325,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Salinas Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.36528015136717,\n 36.42515002455931\n ],\n [\n -121.33575439453126,\n 36.46933726558023\n ],\n [\n -121.61521911621092,\n 36.75594019674357\n ],\n [\n -121.74293518066406,\n 36.75924093413334\n ],\n [\n -121.75529479980467,\n 36.673375615028256\n ],\n [\n -121.6021728515625,\n 36.584106249883554\n ],\n [\n -121.47583007812501,\n 36.47265029399174\n ],\n [\n -121.36528015136717,\n 36.42515002455931\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"315","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Woodward, Emily E. 0000-0001-9196-1349 ewoodward@usgs.gov","orcid":"https://orcid.org/0000-0001-9196-1349","contributorId":177364,"corporation":false,"usgs":true,"family":"Woodward","given":"Emily","email":"ewoodward@usgs.gov","middleInitial":"E.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":854613,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hladik, Michelle L. 0000-0002-0891-2712","orcid":"https://orcid.org/0000-0002-0891-2712","contributorId":221229,"corporation":false,"usgs":true,"family":"Hladik","given":"Michelle","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":854614,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Main, Anson 0000-0001-9539-760X","orcid":"https://orcid.org/0000-0001-9539-760X","contributorId":202852,"corporation":false,"usgs":false,"family":"Main","given":"Anson","email":"","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":854615,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cahn, Michael","contributorId":297909,"corporation":false,"usgs":false,"family":"Cahn","given":"Michael","email":"","affiliations":[{"id":64448,"text":"Univeristy of California ANR","active":true,"usgs":false}],"preferred":false,"id":854616,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Orlando, James 0000-0002-0099-7221","orcid":"https://orcid.org/0000-0002-0099-7221","contributorId":208413,"corporation":false,"usgs":true,"family":"Orlando","given":"James","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":854617,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Teerlink, Jennifer","contributorId":297910,"corporation":false,"usgs":false,"family":"Teerlink","given":"Jennifer","email":"","affiliations":[{"id":40320,"text":"California Department of Pesticide Regulation","active":true,"usgs":false}],"preferred":false,"id":854618,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70256617,"text":"70256617 - 2022 - The Bathy-drone: An autonomous unmanned drone-tethered sonar system","interactions":[],"lastModifiedDate":"2024-08-27T14:37:31.951355","indexId":"70256617","displayToPublicDate":"2022-10-10T09:32:38","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":18351,"text":"Drones","active":true,"publicationSubtype":{"id":10}},"title":"The Bathy-drone: An autonomous unmanned drone-tethered sonar system","docAbstract":"A unique drone-based system for underwater mapping (bathymetry) was developed at the University of Florida. The system, called the “Bathy-drone”, comprises a drone that drags, via a tether, a small vessel on the water surface in a raster pattern. The vessel is equipped with a recreational commercial off-the-shelf (COTS) sonar unit that has down-scan, side-scan, and chirp capabilities and logs GPS-referenced sonar data onboard or transmitted in real time with a telemetry link. Data can then be retrieved post mission and plotted in various ways. The system provides both isobaths and contours of bottom hardness. Extensive testing of the system was conducted on a 5 acre pond located at the University of Florida Plant Science and Education Unit in Citra, FL. Prior to performing scans of the pond, ground-truth data were acquired with an RTK GNSS unit on a pole to precisely measure the location of the bottom at over 300 locations. An assessment of the accuracy and resolution of the system was performed by comparison to the ground-truth data. The pond ground truth had an average depth of 2.30 m while the Bathy-drone measured an average 21.6 cm deeper than the ground truth, repeatable to within 2.6 cm. The results justify integration of RTK and IMU corrections. During testing, it was found that there are numerous advantages of the Bathy-drone system compared to conventional methods including ease of implementation and the ability to initiate surveys from the land by flying the system to the water or placing the platform in the water. The system is also inexpensive, lightweight, and low-volume, thus making transport convenient. The Bathy-drone can collect data at speeds of 0–24 km/h (0–15 mph) and, thus, can be used in waters with swift currents. Additionally, there are no propellers or control surfaces underwater; hence, the vessel does not tend to snag on floating vegetation and can be dragged over sandbars. An area of more than 10 acres was surveyed using the Bathy-drone in one battery charge and in less than 25 min.
","language":"English","publisher":"MDPI","doi":"10.3390/drones6100294","usgsCitation":"Diaz, A.L., Ortega, A.E., Tingle, H., Pulido, A., Cordero, O., Nelson, M., Cocoves, N.E., Shin, J., Carthy, R., Wilkinson, B.E., and Ifju, P.G., 2022, The Bathy-drone: An autonomous unmanned drone-tethered sonar system: Drones, v. 6, no. 10, 294, 19 p., https://doi.org/10.3390/drones6100294.","productDescription":"294, 19 p.","ipdsId":"IP-144387","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":446174,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/drones6100294","text":"Publisher Index Page"},{"id":433196,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","issue":"10","noUsgsAuthors":false,"publicationDate":"2022-10-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Diaz, Antonio L.","contributorId":341377,"corporation":false,"usgs":false,"family":"Diaz","given":"Antonio","email":"","middleInitial":"L.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":908324,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ortega, Andrew E.","contributorId":341378,"corporation":false,"usgs":false,"family":"Ortega","given":"Andrew","email":"","middleInitial":"E.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":908325,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tingle, Henry","contributorId":341379,"corporation":false,"usgs":false,"family":"Tingle","given":"Henry","email":"","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":908326,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pulido, Andres","contributorId":341380,"corporation":false,"usgs":false,"family":"Pulido","given":"Andres","email":"","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":908327,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cordero, Orlando","contributorId":341381,"corporation":false,"usgs":false,"family":"Cordero","given":"Orlando","email":"","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":908328,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nelson, Marisa","contributorId":341382,"corporation":false,"usgs":false,"family":"Nelson","given":"Marisa","email":"","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":908329,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cocoves, Nicholas E.","contributorId":341383,"corporation":false,"usgs":false,"family":"Cocoves","given":"Nicholas","email":"","middleInitial":"E.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":908330,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Shin, Jaejeong","contributorId":341384,"corporation":false,"usgs":false,"family":"Shin","given":"Jaejeong","email":"","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":908331,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Carthy, Raymond 0000-0001-8978-5083","orcid":"https://orcid.org/0000-0001-8978-5083","contributorId":219303,"corporation":false,"usgs":true,"family":"Carthy","given":"Raymond","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":908332,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Wilkinson, Benjamin E.","contributorId":341385,"corporation":false,"usgs":false,"family":"Wilkinson","given":"Benjamin","email":"","middleInitial":"E.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":908333,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Ifju, Peter G.","contributorId":341386,"corporation":false,"usgs":false,"family":"Ifju","given":"Peter","email":"","middleInitial":"G.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":908334,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70238000,"text":"70238000 - 2022 - Wave-driven hydrodynamic processes over fringing reefs with varying slopes, depths, and roughness: Implications for coastal protection","interactions":[],"lastModifiedDate":"2022-11-04T11:31:49.381274","indexId":"70238000","displayToPublicDate":"2022-10-09T13:42:11","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7159,"text":"JGR Oceans","active":true,"publicationSubtype":{"id":10}},"title":"Wave-driven hydrodynamic processes over fringing reefs with varying slopes, depths, and roughness: Implications for coastal protection","docAbstract":"Wave breaking on the steep fore-reef slopes of shallow fringing reefs is effective at dissipating incident sea-swell waves prior to reaching reef shorelines. However, wave setup and free infragravity waves generated during the sea-swell breaking process are often the largest contributors to wave-driven water levels at the shoreline. Laboratory flume experiments and a multi-layer phase-resolving nonhydrostatic wave-flow model, which includes a canopy model to predict drag forces generated by roughness elements, were used to investigate the wave-driven water levels on fringing reefs. Though the model is capable of three dimensional simulations, consistent with the laboratory study, a two-dimensional vertical mode was used. In contrast to many previous studies, both the laboratory experiment and the numerical model account for the effects of large bottom roughness. The numerical model reproduced the observations of the wave transformation and runup over both smooth and rough reef profiles. The numerical model was then extended to quantify the influence of reef geometry and compared to simulations of plane beaches lacking a reef. For a set offshore forcing condition, the fore-reef slope controlled wave runup on reef fronted beaches, whereas the beach slope controlled wave runup on plane beaches. As a result, the coastal protection utility of reefs is dependent on these slopes. For our examples, with a fore-reef slope of 1/5 and a 500 m prototype reef flat length, a beach slope of ~1/30 marked the transition between the reef providing runup reduction for steeper beach slopes and enhancing wave runup for milder slopes. Roughness coverage, spacing, dimensions, and drag coefficient were investigated with results indicating the greatest runup reductions were due to tall roughness elements on the reef flat.","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2022JC018857","usgsCitation":"Buckley, M.L., Lowe, R.L., Hansen, J., Dongeren, A.R., Pomeroy, A., Storlazzi, C.D., Rijnsdorp, D., Silva, R.F., Contardo, S., and Green, R., 2022, Wave-driven hydrodynamic processes over fringing reefs with varying slopes, depths, and roughness: Implications for coastal protection: JGR Oceans, v. 127, no. 11, e2022JC018857, 27 p., https://doi.org/10.1029/2022JC018857.","productDescription":"e2022JC018857, 27 p.","ipdsId":"IP-140945","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":446182,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1029/2022jc018857","text":"External Repository"},{"id":409126,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"127","issue":"11","noUsgsAuthors":false,"publicationDate":"2022-11-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Buckley, Mark L. 0000-0002-1909-4831","orcid":"https://orcid.org/0000-0002-1909-4831","contributorId":203481,"corporation":false,"usgs":true,"family":"Buckley","given":"Mark","email":"","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":856512,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lowe, Ryan L.","contributorId":298814,"corporation":false,"usgs":false,"family":"Lowe","given":"Ryan","email":"","middleInitial":"L.","affiliations":[{"id":24588,"text":"The University of Western Australia","active":true,"usgs":false}],"preferred":false,"id":856513,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hansen, Jeff E.","contributorId":298815,"corporation":false,"usgs":false,"family":"Hansen","given":"Jeff E.","affiliations":[{"id":24588,"text":"The University of Western Australia","active":true,"usgs":false}],"preferred":false,"id":856514,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dongeren, Ap R.","contributorId":298816,"corporation":false,"usgs":false,"family":"Dongeren","given":"Ap","email":"","middleInitial":"R.","affiliations":[{"id":36257,"text":"Deltares","active":true,"usgs":false}],"preferred":false,"id":856515,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pomeroy, Andrew","contributorId":298817,"corporation":false,"usgs":false,"family":"Pomeroy","given":"Andrew","affiliations":[{"id":29920,"text":"The University of Melbourne","active":true,"usgs":false}],"preferred":false,"id":856516,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Storlazzi, Curt D. 0000-0001-8057-4490","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":213610,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt","middleInitial":"D.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":856517,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rijnsdorp, Dirk P.","contributorId":298818,"corporation":false,"usgs":false,"family":"Rijnsdorp","given":"Dirk P.","affiliations":[{"id":17614,"text":"Delft University of Technology","active":true,"usgs":false}],"preferred":false,"id":856518,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Silva, Renan F.","contributorId":298819,"corporation":false,"usgs":false,"family":"Silva","given":"Renan","email":"","middleInitial":"F.","affiliations":[{"id":24588,"text":"The University of Western Australia","active":true,"usgs":false}],"preferred":false,"id":856519,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Contardo, Stephanie","contributorId":298820,"corporation":false,"usgs":false,"family":"Contardo","given":"Stephanie","email":"","affiliations":[{"id":64690,"text":"The University of Western Australia and CSIRO","active":true,"usgs":false}],"preferred":false,"id":856520,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Green, Rebecca H.","contributorId":298821,"corporation":false,"usgs":false,"family":"Green","given":"Rebecca H.","affiliations":[{"id":24588,"text":"The University of Western Australia","active":true,"usgs":false}],"preferred":false,"id":856521,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70237980,"text":"70237980 - 2022 - Identifying key stressors driving biological impairment in freshwater streams in the Chesapeake Bay watershed, USA","interactions":[],"lastModifiedDate":"2022-11-02T11:40:22.029965","indexId":"70237980","displayToPublicDate":"2022-10-07T06:37:16","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1547,"text":"Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Identifying key stressors driving biological impairment in freshwater streams in the Chesapeake Bay watershed, USA","docAbstract":"Biological communities in freshwater streams are often impaired by multiple stressors (e.g., flow or water quality) originating from anthropogenic activities such as urbanization, agriculture, or energy extraction. Restoration efforts in the Chesapeake Bay watershed, USA seek to improve biological conditions in 10% of freshwater tributaries and to protect the biological integrity of existing healthy watersheds. To achieve these goals, resource managers need to better understand which stressors are most likely driving biological impairment. Our study addressed this knowledge gap through two approaches: 1) reviewing and synthesizing published multi-stressor studies, and 2) examining 303(d) listed impairments linked to biological impairment as identified by jurisdiction regulatory agencies (the states within the watershed and the District of Columbia). Results identified geomorphology (i.e., physical habitat), salinity, and toxic contaminants as important for explaining variability in benthic community metrics in the literature review. Geomorphology (i.e., physical habitat and sediment), salinity, and nutrients were the most reported stressors in the jurisdictional impairment analysis. Salinity is likely a major stressor in urban and mining settings, whereas geomorphology was commonly reported in agricultural settings. Toxic contaminants, such as pesticides, were rarely measured; more research is needed to quantify the extent of their effects in the region. Flow alteration was also highlighted as an important urban stressor in the literature review but was rarely measured in the literature or reported by jurisdictions as a cause of impairment. These results can be used to prioritize stressor monitoring by managers, and to improve stressor identification methods for identifying causes of biological impairment.
Dissolved organic matter (DOM) and particulate organic matter (POM) can influence biogeochemical processes in aquatic systems. An understanding, however, of the source, composition, and processes driving inland reservoir organic matter (OM) cycling at a regional scale over the long term is currently unexplored. Here, we quantify decadal patterns (> 20 yr) of DOM quantity and composition and POM in 40 reservoirs in the midcontinent United States. We built 184 Random Forest models to identify how the relative influence of watershed characteristics and limnological parameters on OM dynamics may vary over time and in synchrony with hydroclimatic anomalies. The reservoir OM quantity and composition varied nonmonotonically through time and in contrast to lake browning observed in the northern hemisphere. Reservoir DOM composition switched from humic and aromatic during wet summers to aliphatic, potentially autochthonous DOM during particularly prolonged dry summers in the mid-2000s. The shift in reservoir DOM quantity and composition could be attributed to the change in time-varying control of watershed and limnological factors mediated by the hydroclimatic conditions. Watershed control (e.g., percent crops) was predominant during wet summers, while the effect of reservoir morphology (e.g., maximum depth) and water quality parameters (e.g., Secchi depth, chlorophyll a) were evident during dry summers. Thus, future predictions of drier conditions may promote “greening” with negative implications for reservoir water quality and treated drinking water. Considering the nonlinear nature of reservoir OM dynamics and its controls will help to better mitigate water quality issues in these constructed systems increasingly impacted by global changes.