Hurricane Irma skirted the northern coasts of the U.S. Virgin Islands and Puerto Rico, with maximum sustained winds of 185 miles per hour (mi/h) on September 6, 2017. The hurricane first made landfall in Florida near Cudjoe Key, in the lower Florida Keys, with maximum sustained winds of 130 mi/h on September 10, 2017. The hurricane made a second Florida landfall on Marco Island, Florida, with maximum sustained winds of 115 mi/h on September 10, 2017. The U.S. Geological Survey (USGS), in cooperation with Federal Emergency Management Agency, deployed a temporary monitoring network of water-level and barometric pressure sensors at 249 locations along the Puerto Rico, Florida, Georgia, and South Carolina coasts to record the timing, areal extent, and magnitude of hurricane storm tide and coastal flooding generated by the hurricane. Immediately following the passage of Hurricane Irma, the sensors were retrieved, and the data were disseminated on the USGS Flood Event Viewer (https://stn.wim.usgs.gov/FEV/#IrmaSeptember2017). The storm-tide peak data values were verified by comparing data from hydrologic recorders and nearby high-water marks (HWMs). Following the hurricane, 508 independent HWM locations were flagged and surveyed relative to the North American Vertical Datum of 1988, National Geodetic Vertical Datum of 1929, or a local datum along the southeastern U.S. coast, and to Puerto Rico Vertical Datum of 2002 in Puerto Rico. Most HWMs were in Florida because of the path of the hurricane. The data from the Hurricane Irma storm-tide network are available on a provisional basis in tab-delimited, American Standard Code for Information Interchange (ASCII) format and Network Common Data Form (NetCDF) format by site for each sensor by using the USGS Flood Event Viewer.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191013","collaboration":"Prepared in cooperation with the Federal Emergency Management Agency","usgsCitation":"Byrne, M.J., Sr., and Dickman, M.R., 2019, Monitoring storm tide and flooding from Hurricane Irma along the U.S. Virgin Islands, Puerto Rico, and the Southeastern United States, September 2017 (ver. 1.1, July 2019): U.S. Geological Survey Open-File Report 2019–1013, 35 p., https://doi.org/10.3133/ofr20191013.","productDescription":"vi, 35 p.","numberOfPages":"46","onlineOnly":"N","ipdsId":"IP-095711","costCenters":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":365693,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1013/ofr20191013.pdf","text":"Report","size":"9.26 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019–1013"},{"id":365694,"rank":2,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2019/1013/versionHist.txt","text":"Version History","size":"1.00 kB","linkFileType":{"id":2,"text":"txt"},"description":"OFR 2019–1013 Version History"},{"id":365697,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1013/coverthb2.jpg"}],"country":"United States","otherGeospatial":"Puerto Rico, U.S. Virgin Islands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.9892578125,\n 24.00632619875113\n ],\n [\n -79.4970703125,\n 24.00632619875113\n ],\n [\n -79.4970703125,\n 32.0639555946604\n ],\n [\n -88.9892578125,\n 32.0639555946604\n ],\n [\n -88.9892578125,\n 24.00632619875113\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -68.02734375,\n 16.04581345375217\n ],\n [\n -63.45703124999999,\n 16.04581345375217\n ],\n [\n -63.45703124999999,\n 20.96143961409684\n ],\n [\n -68.02734375,\n 20.96143961409684\n ],\n [\n -68.02734375,\n 16.04581345375217\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: April 16, 2019; Version 1.1: July 25, 2019 ","contact":"Director, Caribbean-Florida Water Science Center
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Evidence is presented that Diodon holocanthus is a circumtropical swarm (not a hybrid swarm because the individuals are not hybrids). Some individuals are so different
from one another in both color and morphology that they appear to be different species. Thirty undersea and aquarium photographs from different global localities are provided to demonstrate the variability. The worldwide distribution is achieved by the juvenile that has been found more than 1,000 km offshore as large as 90 mm SL. How can it feed on zooplankton with jaws and dentition designed to crush shelled invertebrates? We believe it draws the prey into the mouth with the same mechanism that it uses to expand its body when threatened; the water with prey is diverted to the pharyngeal cavity, then released from the gill opening on each side. Larger juveniles may seek concentrations of zooplankton for feeding, perhaps collectively. A confirming experiment in an aquarium is advised. Aggregations of pelagic juveniles have been observed at the surface outside barrier reefs and found inshore the following morning, indicating that settlement took place at night to minimize predation. The juveniles soon disperse to inshore habitats of mangrove and sea grass to coral reef. The hybrid Diodon holocanthusx D. hystrix from South Africa is illustrated. The narrative for the present research on D. holocanthus is presented chronologically to show how increasing evidence failed to support the multitude of apparent new species of Diodon, leading to the conclusion of a swarm.
Many streams are experiencing increased average temperatures due to anthropogenic activity and climate change. As a result, surface water temperature regulation is critical for preserving a diverse stream fish species assemblage. The development of temperature regulations has generally been based on laboratory measurements of individual species' thermal tolerances rather than community response to temperature in the field, despite multiple limitations of using laboratory data for this purpose. Using field data to develop temperature regulations may avoid some of the limitations of laboratory data, but the use of field data comes with additional challenges that prevent its widespread adoption. We used Wyoming stream fish assemblages as a case study to examine the feasibility of addressing the limitations of field and laboratory data through a hybrid approach that integrates both types of data to classify species into thermal guilds that can potentially inform regulatory standards. We identified coldwater, coolwater, and warmwater classes of sites with modeled mean August temperatures of <15.5, 15.5–19.9, and >19.9°C, respectively. We used species' associations with these temperature classes to place species into site‐groups. Finally, we used standardized laboratory measures of species' upper acute and chronic thermal tolerances to identify and reclassify species with unusual thermal distributions. Through this process we classified species into five thermal guilds that may be useful for surface water temperature regulation in Wyoming. Our approach addresses the limitations identified for field and laboratory data and demonstrates a framework that could be used for incorporating multiple types of data to develop temperature standards.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/tafs.10169","usgsCitation":"Mandeville, C.P., Rahel, F.J., Patterson, L.S., and Walters, A.W., 2019, Integrating fish assemblage data, modeled stream temperatures, and thermal tolerance metrics to develop thermal guilds for water temperature regulation: Wyoming case study: Transactions of the American Fisheries Society, v. 148, no. 4, p. 739-754, https://doi.org/10.1002/tafs.10169.","productDescription":"15 p.","startPage":"739","endPage":"754","ipdsId":"IP-098236","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":379546,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.0498046875,\n 40.88029480552824\n ],\n [\n -104.0185546875,\n 40.88029480552824\n ],\n [\n -104.0185546875,\n 44.933696389694674\n ],\n [\n -111.0498046875,\n 44.933696389694674\n ],\n [\n -111.0498046875,\n 40.88029480552824\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"148","issue":"4","noUsgsAuthors":false,"publicationDate":"2019-05-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Mandeville, Caitlin P. 0000-0002-1361-607X","orcid":"https://orcid.org/0000-0002-1361-607X","contributorId":243378,"corporation":false,"usgs":false,"family":"Mandeville","given":"Caitlin","email":"","middleInitial":"P.","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":802164,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rahel, Frank J.","contributorId":171824,"corporation":false,"usgs":false,"family":"Rahel","given":"Frank","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":802165,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Patterson, Lindsay S.","contributorId":243379,"corporation":false,"usgs":false,"family":"Patterson","given":"Lindsay","email":"","middleInitial":"S.","affiliations":[{"id":48707,"text":"Wyoming Dept of Environmental Quality","active":true,"usgs":false}],"preferred":false,"id":802166,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Walters, Annika W. 0000-0002-8638-6682 awalters@usgs.gov","orcid":"https://orcid.org/0000-0002-8638-6682","contributorId":4190,"corporation":false,"usgs":true,"family":"Walters","given":"Annika","email":"awalters@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":802167,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70217883,"text":"70217883 - 2019 - A framework for characterising and evaluating the effectiveness of environmental modelling","interactions":[],"lastModifiedDate":"2021-02-09T13:22:03.223877","indexId":"70217883","displayToPublicDate":"2019-04-13T07:20:32","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1551,"text":"Environmental Modelling and Software","active":true,"publicationSubtype":{"id":10}},"title":"A framework for characterising and evaluating the effectiveness of environmental modelling","docAbstract":"Environmental modelling is transitioning from the traditional paradigm that focuses on the model and its quantitative performance to a more holistic paradigm that recognises successful model-based outcomes are closely tied to undertaking modelling as a social process, not just as a technical procedure. This paper redefines evaluation as a multi-dimensional and multi-perspective concept, and proposes a more complete framework for identifying and measuring the effectiveness of modelling that serves the new paradigm. Under this framework, evaluation considers a broader set of success criteria, and emphasises the importance of contextual factors in determining the relevance and outcome of the criteria. These evaluation criteria are grouped into eight categories: project efficiency, model accessibility, credibility, saliency, legitimacy, satisfaction, application, and impact. Evaluation should be part of an iterative and adaptive process that attempts to improve model-based outcomes and foster pathways to better futures.
The Burmese python (Python bivittatus) is now established as a breeding population throughout south Florida, USA. However, the extent of the invasion, and the ecological impacts of this novel apex predator on animal communities are incompletely known, in large part because Burmese pythons (hereafter “pythons”) are extremely cryptic and there has been no efficient way to detect them. Pythons are recently confirmed nest predators of long-legged wading bird breeding colonies (orders Ciconiiformes and Pelecaniformes). Pythons can consume large quantities of prey and may not be recognized as predators by wading birds, therefore they could be a particular threat to colonies. To quantify python occupancy rates at tree islands where wading birds breed, we utilized environmental DNA (eDNA) analysis—a genetic tool which detects shed DNA in water samples and provides high detection probabilities. We fitted multi-scale Bayesian occupancy models to test the prediction that pythons occupy islands with wading bird colonies at higher rates compared to representative control islands containing no breeding birds. Our results suggest that pythons are widely distributed across the central Everglades in proximity to active wading bird colonies. In support of our prediction that pythons are attracted to colonies, site-level python eDNA occupancy rates were higher at wading bird colonies (ψ = 0.88, 95% credible interval [0.59–1.00]) than at the control islands (ψ = 0.42 [0.16–0.80]) in April through June (n = 15 colony-control pairs). We found our water temperature proxy (time of day) to be informative of detection probability, in accordance with other studies demonstrating an effect of temperature on eDNA degradation in occupied samples. Individual sample concentrations ranged from 0.26 to 38.29 copies/μL and we generally detected higher concentrations of python eDNA in colony sites. Continued monitoring of wading bird colonies is warranted to determine the effect pythons are having on populations and investigate putative management activities.
Efforts to restore water quality in Chesapeake Bay and its tributaries often include extensive Best Management Practice (BMP) implementation on agricultural and developed lands. These BMPs include a variety of methods to reduce nutrient and sediment loads, such as cover crops, conservation tillage, urban filtering systems, and other practices.
Estimates of BMP implementation throughout the Chesapeake Bay watershed were provided for each year from 1985 through 2014 by the Chesapeake Bay Program (CBP). This dataset of BMP implementation is a compilation of actions reported by New York, Maryland, Pennsylvania, Delaware, West Virginia, Virginia, and the District of Columbia, and includes a wide array of management activities. Management actions vary among the jurisdictions and generally reflect the typical land use in each region.
The amount of implementation also varies according to different priorities, reporting practices, and special programs within each jurisdiction. For example, extensive cover crop implementation was reported in Maryland whereas Pennsylvania, in general, has lower levels of BMP implementation reported on cropland. Pennsylvania and Maryland have higher levels of infiltration BMPs on developed land compared to those in Virginia.
Conservation tillage BMPs accounted for the majority of reported agricultural BMP implementation in 1985. By 2014, however, a more diverse collection of agricultural BMPs was reported and conservation tillage BMPs accounted for a smaller proportion of overall reported agricultural BMP implementation. After the year 2000, land-use change BMPs, such as land retirement, pasture fencing, and forest buffers, were more commonly reported across the Chesapeake Bay watershed.
Expected changes in nutrient and sediment loads in the Chesapeake Bay watershed due to BMP implementation were estimated by use of specially designed annual scenarios of the CBP Partnership Phase 5.3.2 Watershed Model. Nitrogen loads to streams were estimated to be reduced by 11 percent from 1985 to 2014 due to the implementation of BMPs. Compared with 1985, phosphorus loads were estimated to be 19 percent lower and sediment loads were estimated to be 23 percent lower by 2014 due to the effects of BMPs.
Reductions in total nitrogen from 1985 to 2014 due to BMPs varied spatially across the watershed and were estimated to be as high as 42 percent in areas of the Eastern Shore of the Chesapeake Bay. Reductions in phosphorus and sediment also varied spatially, with the largest reductions occurring in the Potomac watershed upstream of Washington, D.C. and the Eastern Shore of Maryland, according to the CBP model results.
Additional model scenarios were developed to estimate the effect of individual BMP types. The largest estimated reductions in total nitrogen loads on agricultural lands in 2014 were attributed to land retirement, animal waste management systems, and conservation tillage. The largest estimated reductions in total phosphorus loads on agricultural lands were attributed to animal waste management systems, pasture fencing, and phytase feed additives in 2014. The largest estimated reduction in total sediment loads on agricultural lands was attributed to conservation tillage, pasture fencing, and conservation plans.
Dry ponds, wet ponds, and constructed wetlands were reported extensively throughout the watershed. These BMPs accounted for about half of the reduction in nitrogen loads from developed land to streams, half of the phosphorus reduction, and about a third of the sediment reduction.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185171","collaboration":" ","usgsCitation":"Sekellick, A.J., Devereux, O.H., Keisman, J.L.D., Sweeney, J.S., and Blomquist, J.D., 2019, Spatial and temporal patterns of Best Management Practice implementation in the Chesapeake Bay watershed, 1985–2014: U.S. Geological Survey Scientific Investigations Report 2018–5171, 25 p., https://doi.org/10.3133/sir20185171.","productDescription":"vii, 25 p.","numberOfPages":"37","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-084330","costCenters":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"links":[{"id":362890,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9OVU9PX","text":"USGS data release","description":"USGS data release","linkHelpText":"Estimated effect of best management practice implementation on water quality in the Chesapeake Bay watershed from 1985 to 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U.S. Geological Survey
5522 Research Park Drive
Baltimore, MD 21228
The U.S. Geological Survey, in cooperation with the Idaho Department of Environmental Quality, sampled groundwater from 15 wells during spring 2018 near the city of Marsing in rural northwestern Owyhee County, southwestern Idaho. Samples were analyzed for field parameters, nutrients, trace elements, major inorganics, and dissolved gas, including methane. To examine trends in individual wells and in the region, ammonia and nitrate results from the spring 2018 sampling were compared with data collected from 1996 to 2015 by the Idaho Department of Environmental Quality and the Idaho State Department of Agriculture.
Fourteen of the 15 samples collected in 2018 contained arsenic (0.13–33.8 micrograms per liter [μg/L]), with 7 arsenic concentrations greater than the U.S. Environmental Protection Agency (EPA) maximum contaminant level (MCL) of 10 μg/L. Iron (465–4,180 μg/L), manganese (54–693 μg/L), sulfate (300–624 milligrams per liter [mg/L]), and total dissolved solids (511–1,350 mg/L) were detected at concentrations greater than EPA secondary maximum contaminant levels (SMCL) in water-quality samples from 6, 10, 4, and 14 of the 15 wells, respectively. Fourteen of the 15 samples contained ammonia concentrations from 0.12 to 7.34 milligrams per liter (mg/L). Six samples contained nitrate concentrations from 0.08 to 24.6 mg/L, with one sample greater than the EPA MCL of 10 mg/L for drinking water. The presence of both ammonia and nitrate in four samples indicated multiple nutrient and groundwater sources and varying redox states. Ammonia concentrations tended to increase downgradient throughout the study area.
Nutrient trend analysis identified water-quality samples from 2 of the 15 wells with increasing nitrate concentrations from 1999–2018 and 2005–2018. The well with increasing nitrate concentrations from 2005–2018 showed a decreasing trend in ammonia concentrations during the same time period. Groundwater-quality samples from the 13 remaining wells showed no temporal trends. A Regional Kendall test, which evaluates trends at numerous wells across the study area to determine if a consistent trend exists for the area, was done to analyze 539 ammonia concentrations from 91 wells over 20 years (1999–2018) and 591 nitrate concentrations from 107 wells over 23 years (1996–2018). The Regional Kendall Test for ammonia had a tau correlation coefficient of -0.073 with a p-value of 0.072, and nitrate had a tau correlation coefficient of -0.041 with a p-value of 0.198, both indicating no statistically significant trends.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191032","collaboration":"Prepared in cooperation with the Idaho Department of Environmental Quality","usgsCitation":"Skinner, K.D., 2019, Groundwater quality and nutrient trends near Marsing, southwestern Idaho, 2018: U.S. Geological Survey Open-File Report 2019-1032, 23 p., https://doi.org/10.3133/ofr20191032.","productDescription":" iv, 24 p.","numberOfPages":"32","onlineOnly":"Y","ipdsId":"IP-095202","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":362894,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1032/ofr20191032.pdf","text":"Report","size":"27.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1032"},{"id":362893,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1032/coverthb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Marsing","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.94345474243164,\n 43.523410314985455\n ],\n [\n -116.7856979370117,\n 43.523410314985455\n ],\n [\n -116.7856979370117,\n 43.60687218565255\n ],\n [\n -116.94345474243164,\n 43.60687218565255\n ],\n [\n -116.94345474243164,\n 43.523410314985455\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Rd
Boise, Idaho 83702-4520
The goal of this research was to evaluate the impacts of Hurricane Sandy on surface elevation trends in estuarine marshes located across the northeast region of the United States from Virginia to Maine using data from an opportunistic (in other words, not strategic) and collaborative network (from here on, an opportunistic network) of surface elevation table-marker horizon (SET-MH) stations. First, we built a data-base of metadata for 965 individual stations from 96 unique geographical locations that included the location, geomorphic setting, and wetland type for each SET-MH station. The dominant estuarine settings included in the analyses were back-barrier lagoonal marshes and emergent marshes along embayments and tidal tributaries. We then calculated prestorm elevation trends to compare to poststorm elevation measurements to determine the storm impact on each station trend. We hypothesized that the effect of Hurricane Sandy on marsh elevation trends would differ by position relative to landfall (right or left) and distance from landfall in southern New Jersey, as both of these variables influence the presence or absence of storm surge as a result of the physical characteristics of tropical cyclones (in other words, strongest winds typically occur to the right of landfall). Storm surge was spatially less extensive and less deep (~1 meter [m]) in marshes located to the left (in other words, south) of landfall compared to marshes located to the right (in other words, north) of landfall where storm surge covered a larger area and was deeper (3–4 m). About 63 percent of 223 eligible stations had a poststorm trend that was similar to the prestorm trend (in other words, less than ±5 millimeters [mm]), indicating little storm impact on elevation trends at those sites. The remaining 37 percent of stations exhibited significant poststorm deviations from the prestorm trend (in other words, greater than ±5 mm). Of these, stations located to the left of landfall had a significant and greater deviation in their elevation trend, and the deviation was more likely to be positive (elevation gain) compared to marshes located to the right of landfall, which had a significant deviation in their elevation trend that was more likely to be negative (elevation loss). This finding is directly related to storm surge impacts on marsh sediment deposition, where deep storm surge (3–4 m) results in sediment deposition in habitats inland of coastal marshes but less so in the marshes themselves. Substrate compaction by the storm surge over-burden may have contributed to elevation loss, but this was not measured because sufficient marker horizon data were not available for analysis. In contrast, to the left of landfall the wind-driven flooding of sediment laden water pushed into the headwaters of rivers and small bays with an ~1 m surge, and resulted in more prevalent sediment deposition on the marsh surfaces and elevation gain. In general, the findings support previous research showing that the physical characteristics of the storm (for example, wind speed, storm surge height, impact angle of landfall) combined with the local wetland conditions (for example, marsh productivity, groundwater level, tide height) are important factors determining a storm’s impact on soil elevation, and that the soil elevation response can vary widely among multiple wetland sites impacted by the same storm and among different storms for the same wetland site.
The final objective of this project was to create a framework using metadata from the opportunistic network of SET-MH stations that could be used to develop a strategic monitoring network designed to address specific climate change impacts and related phenomena identified by land managers and stakeholders. We evaluated the spatial distribution and density of SET-MH stations in relation to geographic coverage, marsh setting, availability of public land, and historical storm surge footprints and hurricane return intervals in order to identify gaps in our understanding of risk and our ability to assess it. Analyses revealed that the general geographic coverage of SET-MH stations is limited given the low percentage of marsh patches with stations, low density of stations, the clumped distribution of stations, and the often limited and uneven distribution of stations in wetlands with a high historical frequency of hurricane strikes and storm surge impacts. These findings can be used by managers and planners to inform the creation of a strategic monitoring network that can, in turn, inform management and adaptation plans for coastal resources in the region. Final plan designs will need to consider financial and infrastructural support required for station maintenance, as well as data collection and management over the long term.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181142","usgsCitation":"Cahoon, D.R., Olker, J.H., Yeates, A.G., Guntenspergen, G.R., Grace, J.B., Adamowicz, S.C., Anisfeld, S., Baldwin, A.H., Barrett, N., Beckett, L., Benzecry, A., Blum, L.K., Burdick, D.M., Crouch, W., Ekberg, M.C., Fernald, S., Grimes, K.W., Grzyb, J., Hartig, E.K., Kreeger, D.A., Larson, M., Lerberg, S., Lynch, J.C., Maher, N., Maxwell-Doyle, M., Mitchell, L.R., Mora, J., O’Neill, V., Padeletti, A., Prosser, D., Quirk, T., Raposa, K.B., Reay, W.G., Siok, D., Snow, C., Starke, A., Staver, L., Stevenson, J.C., and Turner, V., 2019, Hurricane Sandy impacts on coastal wetland resilience: U.S. Geological Survey Open-File Report 2018–1142, 117 p., https://doi.org/10.3133/ofr20181142.","productDescription":"xii, 117 p.","ipdsId":"IP-089853","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":362852,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1142/ofr20181142.pdf","text":"Report","size":"30.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1142"},{"id":362851,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1142/coverthb1.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 -93.251953125,\n 17.811456088564483\n ],\n [\n -70.9716796875,\n 17.811456088564483\n ],\n [\n -70.9716796875,\n 41.07935114946899\n ],\n [\n -93.251953125,\n 41.07935114946899\n ],\n [\n -93.251953125,\n 17.811456088564483\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Eastern Ecological Science Center
U.S. Geological Survey
12311 Beech Forest Road
Laurel, MD 20708
Methanol extractions for chloroethene analyses are conducted on rock samples from seven closely spaced coreholes in a mudstone aquifer that was subject to releases of the nonaqueous phase liquid (NAPL) form of trichloroethene (TCE) between the 1950's and 1990's. Although TCE concentration in the rock matrix over the length of coreholes is dictated by proximity to subhorizontal bedding planefractures, elevated TCE concentrations in the rock matrix are not continuous along the most permeable bedding plane fractures. A complex configuration of subvertical and subhorizontal fractures appears to be responsible for the TCE distribution from prior TCE releases at land surface. Phase partitioning calculations of TCE in the rock matrix show that most TCE is adsorbed to solid surfaces because of the large fraction of organic carbon (foc) in the mudstone. Large TCE content in some cores indicate the likely presence of the NAPL form of TCE in the rock matrix. Using average values of porosity (n) and foc in phase partitioning calculations identifies a number of locations of possible NAPL occurrence in the rock matrix. Samples of mudstone analyzed for n and foc show variability in these properties over several orders of magnitude. Accounting for this variability in phase partitioning calculations identifies a probability of NAPL occurrence, PNAPL. The spatial variability of PNAPL along coreholes identifies a configuration that may be attributed to a TCE source zone that has evolved after emplacement due to NAPL dissolution, adsorption, and matrix diffusion.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jconhyd.2019.04.001","usgsCitation":"Shapiro, A.M., Goode, D.J., Imbrigiotta, T.E., Lorah, M.M., and Tiedeman, C.R., 2019, The complex spatial distribution of trichloroethene and the probability of NAPL occurrence in the rock matrix of a mudstone aquifer: Journal of Contaminant Hydrology, v. 233, 103478; 14 p., https://doi.org/10.1016/j.jconhyd.2019.04.001.","productDescription":"103478; 14 p.","ipdsId":"IP-103048","costCenters":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":467713,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jconhyd.2019.04.001","text":"Publisher Index Page"},{"id":437502,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7P55MD8","text":"USGS data release","linkHelpText":"Concentrations of Chlorinated Ethene Compounds in Rock Core Collected from the Mudstone Underlying the former Naval Air Warfare Center, West Trenton, New Jersey"},{"id":365294,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Jersey","city":"West Trenton","otherGeospatial":"Newark Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.8144268989563,\n 40.268196648437474\n ],\n [\n -74.80998516082764,\n 40.26757447962916\n ],\n [\n -74.80850458145142,\n 40.2704560554525\n ],\n [\n -74.81170177459717,\n 40.272715386988686\n ],\n [\n -74.81320381164551,\n 40.27173307820388\n ],\n [\n -74.8144268989563,\n 40.268196648437474\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"233","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Shapiro, Allen M. 0000-0002-6425-9607 ashapiro@usgs.gov","orcid":"https://orcid.org/0000-0002-6425-9607","contributorId":2164,"corporation":false,"usgs":true,"family":"Shapiro","given":"Allen","email":"ashapiro@usgs.gov","middleInitial":"M.","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":765432,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Goode, Daniel J. 0000-0002-8527-2456 djgoode@usgs.gov","orcid":"https://orcid.org/0000-0002-8527-2456","contributorId":193394,"corporation":false,"usgs":true,"family":"Goode","given":"Daniel","email":"djgoode@usgs.gov","middleInitial":"J.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":false,"id":765433,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Imbrigiotta, Thomas E. 0000-0003-1716-4768 timbrig@usgs.gov","orcid":"https://orcid.org/0000-0003-1716-4768","contributorId":152114,"corporation":false,"usgs":true,"family":"Imbrigiotta","given":"Thomas","email":"timbrig@usgs.gov","middleInitial":"E.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":765434,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lorah, Michelle M. 0000-0002-9236-587X","orcid":"https://orcid.org/0000-0002-9236-587X","contributorId":216751,"corporation":false,"usgs":true,"family":"Lorah","given":"Michelle","email":"","middleInitial":"M.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":765435,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tiedeman, Claire R. 0000-0002-0128-3685 tiedeman@usgs.gov","orcid":"https://orcid.org/0000-0002-0128-3685","contributorId":196777,"corporation":false,"usgs":true,"family":"Tiedeman","given":"Claire","email":"tiedeman@usgs.gov","middleInitial":"R.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":765436,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70227747,"text":"70227747 - 2019 - Louisiana Waterthrush (Parkesia motacilla) survival and site fidelity in an area undergoing shale gas development","interactions":[],"lastModifiedDate":"2022-01-28T15:45:42.288767","indexId":"70227747","displayToPublicDate":"2019-04-09T09:40:31","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3784,"text":"Wilson Journal of Ornithology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Louisiana Waterthrush (Parkesia motacilla) survival and site fidelity in an area undergoing shale gas development","title":"Louisiana Waterthrush (Parkesia motacilla) survival and site fidelity in an area undergoing shale gas development","docAbstract":"We quantified Louisiana Waterthrush (Parkesia motacilla) site fidelity and apparent survival across a 6 year period in an area undergoing shale gas development.Waterthrush initially exhibited high site fidelity that declined over time. At the same time, the number of unpaired males defending territories increased as did natal fidelity. We identified site fidelity factors that influenced if adult males and females returned. More males returned either due to or regardless of amount of shale gas disturbance and lower riparian habitat quality. Females were less likely to return with increased number of breeding attempts. Females in shale gas disturbed areas had a higher number of breeding attempts and lower individual productivity. We saw a general nonsignificant trend in declining apparent survival over time. Overall apparent survival estimates for adult males (0.56) and females (0.44) were similar to those reported for other populations. Apparent survival candidate models suggested weak, positive relationships of increased survival with shale gas territory disturbance, disturbance with year, and year for adult males, and a positive relationship of increased survival with hydraulic fracturing runoff for adult females although regression coefficients overlapped zero for all model-supported covariates implying no statistical significance. Since waterthrush can maintain pair bonds from the previous year and females must pick a nest site within the defended male's territory, there are potential conflicts between factors that influence adult survival and site fidelity that may affect long-term population persistence. Our study adds to previous evidence that shale gas disturbed areas may serve as sink habitats.
","language":"English","publisher":"Wilson Ornithological Society","doi":"10.1676/18-6","usgsCitation":"Frantz, M.W., Wood, P.B., Sheehan, J., and George, G., 2019, Louisiana Waterthrush (Parkesia motacilla) survival and site fidelity in an area undergoing shale gas development: Wilson Journal of Ornithology, v. 13, no. 1, p. 84-95, https://doi.org/10.1676/18-6.","productDescription":"12 p.","startPage":"84","endPage":"95","ipdsId":"IP-090682","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":395062,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"West Virginia","county":"Wetzel County","otherGeospatial":"Lewis Wetzel Wildlife Management Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.71311950683594,\n 39.43407169253772\n ],\n [\n -80.57304382324219,\n 39.43407169253772\n ],\n [\n -80.57304382324219,\n 39.546941396253146\n ],\n [\n -80.71311950683594,\n 39.546941396253146\n ],\n [\n -80.71311950683594,\n 39.43407169253772\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"13","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Frantz, Mack W.","contributorId":272515,"corporation":false,"usgs":false,"family":"Frantz","given":"Mack","email":"","middleInitial":"W.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":832021,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wood, Petra B. 0000-0002-8575-1705 pbwood@usgs.gov","orcid":"https://orcid.org/0000-0002-8575-1705","contributorId":199090,"corporation":false,"usgs":true,"family":"Wood","given":"Petra","email":"pbwood@usgs.gov","middleInitial":"B.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":832020,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sheehan, James","contributorId":272516,"corporation":false,"usgs":false,"family":"Sheehan","given":"James","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":832022,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"George, Gregory","contributorId":272517,"corporation":false,"usgs":false,"family":"George","given":"Gregory","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":832023,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70220506,"text":"70220506 - 2019 - Stratigraphic occurrences of sub-polar planktic foraminifera in pleistocene sediments on the Lomonosov Ridge, Arctic Ocean","interactions":[],"lastModifiedDate":"2021-05-19T12:10:19.951581","indexId":"70220506","displayToPublicDate":"2019-04-09T07:29:51","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5232,"text":"Frontiers in Earth Science","onlineIssn":"2296-6463","active":true,"publicationSubtype":{"id":10}},"title":"Stratigraphic occurrences of sub-polar planktic foraminifera in pleistocene sediments on the Lomonosov Ridge, Arctic Ocean","docAbstract":"Turborotalita quinqueloba is a species of planktic foraminifera commonly found in the sub-polar North Atlantic along the pathway of Atlantic waters in the Nordic seas and sometimes even in the Arctic Ocean, although its occurrence there remains poorly understood. Existing data show that T. quinqueloba is scarce in Holocene sediments from the central Arctic but abundance levels increase in sediments from the last interglacial period [Marine isotope stage (MIS) 5, 71–120 ka] in cores off the northern coast of Greenland and the southern Mendeleev Ridge. Turborotalita also occurs in earlier Pleistocene interglacials in these regions, with a unique and widespread occurrence of the less known Turborotalita egelida morphotype, proposed as a biostratigraphic marker for MIS 11 (474–374 ka). Here we present results from six new sediment cores, extending from the central to western Lomonosov Ridge, that show a consistent Pleistocene stratigraphy over 575 km. Preliminary semi-quantitative assessments of planktic foraminifer abundance and assemblage composition in two of these records (LOMROG12-7PC and AO16-5PC) reveal two distinct stratigraphic horizons containing Turborotalita in MIS 5. Earlier occurrences in Pleistocene interglacials are recognized, but contain significantly fewer specimens and do not appear to be stratigraphically coeval in the studied sequences. In all instances, the Turborotalita specimens resemble the typical T. quinqueloba morphotype but are smaller (63–125 μm), smooth-walled and lack the final thickened calcite layer common to adults of the species. These results extend the geographical range for T. quinqueloba in MIS 5 sediments of the Arctic Ocean and provide compelling evidence for recurrent invasions during Pleistocene interglacials.","language":"English","publisher":"Frontiers","doi":"10.3389/feart.2019.00071","usgsCitation":"O’Regan, M., Coxall, H., Cronin, T.M., Gyllencreutz, R., Jakobsson, M., Kaboth, S., Lowemark, L., Wiers, S., and West, G., 2019, Stratigraphic occurrences of sub-polar planktic foraminifera in pleistocene sediments on the Lomonosov Ridge, Arctic Ocean: Frontiers in Earth Science, v. 7, 71, 18 p., https://doi.org/10.3389/feart.2019.00071.","productDescription":"71, 18 p.","onlineOnly":"Y","ipdsId":"IP-106073","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":467714,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/feart.2019.00071","text":"Publisher Index Page"},{"id":385702,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Arctic Ocean","volume":"7","noUsgsAuthors":false,"publicationDate":"2019-04-09","publicationStatus":"PW","contributors":{"authors":[{"text":"O’Regan, Matt","contributorId":197135,"corporation":false,"usgs":false,"family":"O’Regan","given":"Matt","email":"","affiliations":[{"id":25421,"text":"Department of Geological Sciences, Stockholm University, Sweden","active":true,"usgs":false}],"preferred":false,"id":815877,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coxall, Helen","contributorId":166866,"corporation":false,"usgs":false,"family":"Coxall","given":"Helen","affiliations":[{"id":24562,"text":"Stockholm University","active":true,"usgs":false}],"preferred":false,"id":815878,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cronin, Thomas M. 0000-0002-2643-0979 tcronin@usgs.gov","orcid":"https://orcid.org/0000-0002-2643-0979","contributorId":2579,"corporation":false,"usgs":true,"family":"Cronin","given":"Thomas","email":"tcronin@usgs.gov","middleInitial":"M.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":815849,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gyllencreutz, Richard","contributorId":179157,"corporation":false,"usgs":false,"family":"Gyllencreutz","given":"Richard","email":"","affiliations":[],"preferred":false,"id":815879,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jakobsson, Martin","contributorId":166854,"corporation":false,"usgs":false,"family":"Jakobsson","given":"Martin","email":"","affiliations":[{"id":24562,"text":"Stockholm University","active":true,"usgs":false}],"preferred":false,"id":815880,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kaboth, Stefanie","contributorId":258170,"corporation":false,"usgs":false,"family":"Kaboth","given":"Stefanie","email":"","affiliations":[],"preferred":false,"id":815881,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lowemark, Ludvig","contributorId":258171,"corporation":false,"usgs":false,"family":"Lowemark","given":"Ludvig","email":"","affiliations":[],"preferred":false,"id":815882,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wiers, Steffen","contributorId":258172,"corporation":false,"usgs":false,"family":"Wiers","given":"Steffen","email":"","affiliations":[],"preferred":false,"id":815883,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"West, Gabriel","contributorId":258085,"corporation":false,"usgs":false,"family":"West","given":"Gabriel","email":"","affiliations":[],"preferred":false,"id":815884,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70204778,"text":"70204778 - 2019 - Coelomic disorders of fishes","interactions":[],"lastModifiedDate":"2021-05-06T13:52:15.488923","indexId":"70204778","displayToPublicDate":"2019-04-08T11:14:10","publicationYear":"2019","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"8","title":"Coelomic disorders of fishes","docAbstract":"Dropsy is a commonly applied term for coelomic distention due to ascites, or the effusion and collection of fluid freely throughout the coelomic cavity. Dropsy, or ascites, is generally a sign of another ongoing disease process, oftentimes one that is multisystemic and impacting coelomic organs and tissues. Dropsy may be caused by a variety of potential etiological agents, both infectious and noninfectious. Stressors such as rapid change in water temperature may predispose fish to bacterial diseases associated with dropsy. Clinically affected fish display coelomic distension of varying degrees of severity. Generally considered a disease syndrome similar to dropsy, affecting specifically Malawi cichlids, a popular group of ornamental fish among aquarium hobbyists. Water belly occurs among salt water pen-reared salmonid fish, including Atlantic salmon, Chinook salmon and rainbow trout. Dietary changes such as reduction of the feeding rate have been reported to improve the condition among affected fish.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Fish diseases and medicine","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"CRC Press","doi":"10.1201/9780429195259","usgsCitation":"Densmore, C., 2019, Coelomic disorders of fishes, chap. 8 of Fish diseases and medicine, p. 174-182, https://doi.org/10.1201/9780429195259.","productDescription":"9 p.","startPage":"174","endPage":"182","ipdsId":"IP-099297","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":467719,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://media.obvsg.at/AC15390036-1001","text":"External Repository"},{"id":366602,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2019-04-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Densmore, Christine L. 0000-0001-6440-0781","orcid":"https://orcid.org/0000-0001-6440-0781","contributorId":204739,"corporation":false,"usgs":true,"family":"Densmore","given":"Christine L.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":768460,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70202903,"text":"sir20195008 - 2019 - Sediment storage and transport in the Nooksack River basin, northwestern Washington, 2006–15","interactions":[],"lastModifiedDate":"2019-05-02T09:56:15","indexId":"sir20195008","displayToPublicDate":"2019-04-08T11:07:35","publicationYear":"2019","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":"2019-5008","displayTitle":"Sediment Storage and Transport in the Nooksack River Basin, Northwestern Washington, 2006–15","title":"Sediment storage and transport in the Nooksack River basin, northwestern Washington, 2006–15","docAbstract":"The Nooksack River is a dynamic gravel-bedded river in northwestern Washington, draining off Mount Baker and the North Cascades into Puget Sound. Working in cooperation with the Whatcom County Flood Control Zone District, the U.S. Geological Survey studied topographic, hydrologic, and climatic data for the Nooksack River basin to document recent changes in sediment storage, long-term bed elevation trends, rates of sediment transport, and factors influencing surficial drainage in order to support ongoing river management. Differences in elevations between topographic and bathymetric surveys in 2005/06 and 2013/15 indicate the active channel aggraded about 1–2 feet locally near the cities of Ferndale and Everson but was primarily stable between them. The active channel upstream of Nugent’s Corner generally incised. Total incision upstream of Nugent’s Corner to Glacier Creek generated 2.3 ± 1.7 million cubic yards of sediment from 2005/06 to 2013 and likely represented a significant source of coarse sediment to the lower mainstem river over that time.
Long-term records of local channel-bed elevation, derived from U.S. Geological Survey streamgage data, show bed-elevation changes of about 1–3 feet. The river bed at most streamgages exhibits long-term trends, with relatively consistent rates of change on the order of 1 foot per decade that persist years to decades. Lagged correlations in bed-elevation trends at all seven streamgages in the North Fork Nooksack and mainstem Nooksack suggest that decadal periods of persistent aggradation and incision originate in the North Fork and translate downstream. The channel-change signal propagates downstream 0.5–2.5 miles per year, with the rate of propagation scaling closely with channel slope. The pattern of incision and aggradation in the North Fork correlates with regional climate, where persistent incision follows extended cold and wet periods, and persistent aggradation follows extended warm and dry periods. Climate-driven variation in coarse-sediment delivery, primarily from the North Fork Nooksack, then appears to be a strong control on long-term vertical channel adjustments at sites downstream. The downstream-translating climate signal generated in the North Fork would account for recently observed aggradation at Everson and Ferndale but not the observed incision in unconfined reaches upstream of Nugent’s Corner from 2005–06 to 2013. This mismatch indicates that understanding how changes in sediment-supply influence those unconfined reaches remains a key uncertainty for predicting future channel change.
Continuous turbidity monitoring integrated with suspended sediment and limited bedload sampling were used to calculate annual sediment loads at five sites in the basin. The sediment load in the lower river at Ferndale ranged from 0.78 to 1.17 million tons per year and averaged 0.97 million tons per year for WYs 2012–17. Suspended sediment made up 93 percent of the load, and bedload made up 7 percent. Most of the fine sediment load of the lower river is supplied from headwaters of the North, Middle, and South Fork Nooksack basins, with relatively little net increase in fine sediment loads in the lower mainstem basin. The three forks supply approximately equal proportions of the lower-river fine sediment load. However, the glacially sourced North and Middle Fork Nooksack basins carry a notably sandier suspended-sediment load than the South Fork Nooksack.
A comparison of monthly streamflow and precipitation trends since 1981 indicate statistically significant increases in total spring precipitation and the number of spring days with measurable precipitation in much of the basin, as well as increases in mean spring river stage near Ferndale. Since no trends in mean spring discharge are observed, the trends in river stage are attributed primarily to observed changes in bed elevation. Changes in bed elevation and precipitation may then both have plausibly impacted field drainage in the lower river below Ferndale.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195008","collaboration":"Prepared in cooperation with the Whatcom County Flood Control Zone District","usgsCitation":"Anderson, S.W., Konrad, C.P., Grossman, E.E., and Curran, C.A., 2019, Sediment storage and transport in the Nooksack River basin, northwestern Washington, 2006–15: U.S. Geological Survey Scientific Investigations Report 2019-5008, 43 p., https://doi.org/10.3133/sir20195008.","productDescription":"vii, 43 p.","onlineOnly":"Y","ipdsId":"IP-097289","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":362810,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5008/sir20195008.pdf","text":"Report","size":"42.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019-5008"},{"id":362809,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5008/coverthb2.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Nooksack River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.64312744140624,\n 48.499317631540286\n ],\n [\n -121.453857421875,\n 48.499317631540286\n ],\n [\n -121.453857421875,\n 48.9991410647952\n ],\n [\n -122.64312744140624,\n 48.9991410647952\n ],\n [\n -122.64312744140624,\n 48.499317631540286\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402
Excess nutrient loading to nearshore environments has been linked to declining water quality and ecosystem health. Macro-algal blooms, eutrophication, and reduction in coral cover have been observed in West Maui, Hawaii, and linked to nutrient inputs from coastal submarine groundwater seeps. Here, we present a forty-year record of nitrogen isotopes (δ15N) of intra-crystalline coral skeletal organic matter in three coral cores collected at this site and evaluate the record in terms of changes in nitrogen sources. Our results show a dramatic increase in coral δ15N values after 1995, corresponding with the implementation of biological nutrient removal at the nearby Lahaina Wastewater Reclamation Facility (LWRF). High δ15N values are known to be strongly indicative of denitrification and sewage effluent, corroborating a previously suggested link between local wastewater injection and degradation of the reef environment. This record demonstrates the power of coral skeletal δ15N as a tool for evaluating nutrient dynamics within coral reef environments.
","language":"English","publisher":"Nature","doi":"10.1038/s41598-019-42013-3","usgsCitation":"Murray, J., Prouty, N.G., Peek, S.E., and Paytan, A., 2019, Coral skeleton δ15N as a tracer of historic nutrient loading to a coral reef in Maui, Hawaii: Scientific Reports, v. 9, p. 1-10, https://doi.org/10.1038/s41598-019-42013-3.","productDescription":"Article number: 5579; 10 p.","startPage":"1","endPage":"10","ipdsId":"IP-090774","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":467729,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-019-42013-3","text":"Publisher Index Page"},{"id":362815,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Maui","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -156.69604539871216,\n 20.932923344761708\n ],\n [\n -156.6832995414734,\n 20.932923344761708\n ],\n [\n -156.6832995414734,\n 20.94877529374215\n ],\n [\n -156.69604539871216,\n 20.94877529374215\n ],\n [\n -156.69604539871216,\n 20.932923344761708\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-04-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Murray, Joseph","contributorId":214650,"corporation":false,"usgs":false,"family":"Murray","given":"Joseph","affiliations":[{"id":17620,"text":"UCSC","active":true,"usgs":false}],"preferred":false,"id":760487,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Prouty, Nancy G. 0000-0002-8922-0688 nprouty@usgs.gov","orcid":"https://orcid.org/0000-0002-8922-0688","contributorId":3350,"corporation":false,"usgs":true,"family":"Prouty","given":"Nancy","email":"nprouty@usgs.gov","middleInitial":"G.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":760486,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Peek, Sara E. 0000-0002-9770-6557 speek@usgs.gov","orcid":"https://orcid.org/0000-0002-9770-6557","contributorId":5341,"corporation":false,"usgs":true,"family":"Peek","given":"Sara","email":"speek@usgs.gov","middleInitial":"E.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":760488,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Paytan, Adina","contributorId":140909,"corporation":false,"usgs":false,"family":"Paytan","given":"Adina","affiliations":[{"id":13611,"text":"Institute of Marine Sciences, University of California, Santa Cruz.","active":true,"usgs":false}],"preferred":false,"id":760489,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70202929,"text":"70202929 - 2019 - Residence time controls on the fate of nitrogen in flow‐through lakebed sediments","interactions":[],"lastModifiedDate":"2019-06-18T11:21:20","indexId":"70202929","displayToPublicDate":"2019-04-05T09:05:27","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2320,"text":"Journal of Geophysical Research: Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Residence time controls on the fate of nitrogen in flow‐through lakebed sediments","docAbstract":"For many glacial lakes with highly permeable sediments, water exchange rates control hydrologic residence times within the sediment‐water interface (SWI) and the removal of reactive compounds such as nitrate, a common pollutant in lakes and groundwater. Here we conducted a series of focused tracer injection experiments in the upper 20 cm of the naturally downwelling SWI in a flow‐through lake on Cape Cod, MA. We systematically varied residence time and reactant controls on nitrate processing, using isotopically labeled 15N nitrate to monitor the effect of these changes on nitrate removal via denitrification. The addition of acetate, a labile carbon compound, triggered the lake SWI to switch from net production to net removal of nitrate. When acetate was combined with increased residence time created by controlled reductions in water flux, we observed a fivefold increase in nitrate removal, a 26‐fold increase in N2 production, and a 42‐fold increase in N2O production. We demonstrate that water residence time is an important control on the fate of nitrate in these lake SWIs and illustrate that seasonal conditions that alter lake exchange rates and variability in lake carbon may predict dynamic nitrate removal across the SWI. Additionally, observed N2O production during the oxic pore water experiments paired with geophysical characterization of the sediment porosity revealed that the lake SWI has less mobile pores occupying upward of 50% of the total porosity volume, which function as reactive microzones for nitrate processing.
","language":"English","publisher":"Wiley","doi":"10.1029/2018JG004741","usgsCitation":"Hampton, T.B., Zarentske, J.P., Briggs, M.A., Singha, K., Harvey, J.W., Day-Lewis, F.D., Dehkordy, F.M., and Lane, J.W., 2019, Residence time controls on the fate of nitrogen in flow‐through lakebed sediments: Journal of Geophysical Research: Biogeosciences, v. 124, no. 3, p. 689-707, https://doi.org/10.1029/2018JG004741.","productDescription":"19 p.","startPage":"689","endPage":"707","ipdsId":"IP-103407","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":467730,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2018jg004741","text":"Publisher Index Page"},{"id":362813,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"124","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-03-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Hampton, Tyler B.","contributorId":210072,"corporation":false,"usgs":false,"family":"Hampton","given":"Tyler","email":"","middleInitial":"B.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":760510,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zarentske, Jay P.","contributorId":214658,"corporation":false,"usgs":false,"family":"Zarentske","given":"Jay","email":"","middleInitial":"P.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":760511,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Briggs, Martin A. 0000-0003-3206-4132 mbriggs@usgs.gov","orcid":"https://orcid.org/0000-0003-3206-4132","contributorId":4114,"corporation":false,"usgs":true,"family":"Briggs","given":"Martin","email":"mbriggs@usgs.gov","middleInitial":"A.","affiliations":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":760509,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Singha, Kamini 0000-0002-0605-3774","orcid":"https://orcid.org/0000-0002-0605-3774","contributorId":191366,"corporation":false,"usgs":false,"family":"Singha","given":"Kamini","email":"","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":760512,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Harvey, Judson W. 0000-0002-2654-9873 jwharvey@usgs.gov","orcid":"https://orcid.org/0000-0002-2654-9873","contributorId":1796,"corporation":false,"usgs":true,"family":"Harvey","given":"Judson","email":"jwharvey@usgs.gov","middleInitial":"W.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":760514,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Day-Lewis, Frederick D. 0000-0003-3526-886X daylewis@usgs.gov","orcid":"https://orcid.org/0000-0003-3526-886X","contributorId":1672,"corporation":false,"usgs":true,"family":"Day-Lewis","given":"Frederick","email":"daylewis@usgs.gov","middleInitial":"D.","affiliations":[{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":760513,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dehkordy, Farzaneh MahmoodPoor","contributorId":214661,"corporation":false,"usgs":false,"family":"Dehkordy","given":"Farzaneh","email":"","middleInitial":"MahmoodPoor","affiliations":[{"id":36710,"text":"University of Connecticut","active":true,"usgs":false}],"preferred":false,"id":760515,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lane, John W. Jr. 0000-0002-3558-243X jwlane@usgs.gov","orcid":"https://orcid.org/0000-0002-3558-243X","contributorId":189168,"corporation":false,"usgs":true,"family":"Lane","given":"John","suffix":"Jr.","email":"jwlane@usgs.gov","middleInitial":"W.","affiliations":[{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true}],"preferred":false,"id":760516,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70202930,"text":"70202930 - 2019 - Wetland-scale mapping of preferential fresh groundwater discharge to the Colorado River","interactions":[],"lastModifiedDate":"2019-09-16T11:55:30","indexId":"70202930","displayToPublicDate":"2019-04-05T09:02:20","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3825,"text":"Groundwater","active":true,"publicationSubtype":{"id":10}},"title":"Wetland-scale mapping of preferential fresh groundwater discharge to the Colorado River","docAbstract":"Quantitative evaluation of groundwater/surface water exchange dynamics is universally challenging in large river systems, because existing methodology often does not yield spatially‐distributed data and is difficult to apply in deeper water. Here we apply a combined near‐surface geophysical and direct groundwater chemical toolkit to refine fresh groundwater discharge estimates to the Colorado River through a 4‐km2 wetland that borders the town of Moab, Utah, USA. Preliminary characterization of raw electromagnetic imaging (EMI) data, collected by kayak and by walking, was used to guide additional direct‐contact electrical measurements and installation of new monitoring wells. Chemical data from the wells strongly supported the EMI spatial characterization of preferential fresh groundwater discharge embedded in natural brine groundwaters and weighted to the southern wetland section. Inversion of the EMI data revealed sub‐meter scale detail regarding bulk electrical conductivity zonation across approximately 15.5 km of transects, collected in only 3 days. This electrical detail indicates processes such as salinization of the unsaturated zone and direct discharge through the Colorado River sediments and a tributary creek bed. Overall, the study contributed to a substantial reduction in fresh groundwater discharge estimates previously made using sparse existing well data and a simplified assumption of diffuse fresh groundwater discharge below the entire wetland. EMI will likely become a widely used tool in systems with natural electrical contrast as groundwater/surface water hydrogeologists continue to recognize the prevalence of preferential groundwater discharge processes.
","language":"English","publisher":"Wiley","doi":"10.1111/gwat.12866","usgsCitation":"Briggs, M.A., Nelson, N.C., Gardner, P.M., Solomon, D.K., Terry, N., and Lane, J.W., 2019, Wetland-scale mapping of preferential fresh groundwater discharge to the Colorado River: Groundwater, v. 57, no. 5, p. 737-748, https://doi.org/10.1111/gwat.12866.","productDescription":"12 p.","startPage":"737","endPage":"748","ipdsId":"IP-104118","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":362812,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"57","issue":"5","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-04-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Briggs, Martin A. 0000-0003-3206-4132 mbriggs@usgs.gov","orcid":"https://orcid.org/0000-0003-3206-4132","contributorId":4114,"corporation":false,"usgs":true,"family":"Briggs","given":"Martin","email":"mbriggs@usgs.gov","middleInitial":"A.","affiliations":[{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":760517,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nelson, Nora C. 0000-0001-8248-2004","orcid":"https://orcid.org/0000-0001-8248-2004","contributorId":207229,"corporation":false,"usgs":true,"family":"Nelson","given":"Nora","email":"","middleInitial":"C.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":760518,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gardner, Philip M. 0000-0003-3005-3587 pgardner@usgs.gov","orcid":"https://orcid.org/0000-0003-3005-3587","contributorId":962,"corporation":false,"usgs":true,"family":"Gardner","given":"Philip","email":"pgardner@usgs.gov","middleInitial":"M.","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true},{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":760519,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Solomon, D. Kip","contributorId":214666,"corporation":false,"usgs":false,"family":"Solomon","given":"D.","email":"","middleInitial":"Kip","affiliations":[{"id":13252,"text":"University of Utah","active":true,"usgs":false}],"preferred":false,"id":760520,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Terry, Neil C. 0000-0002-3965-340X nterry@usgs.gov","orcid":"https://orcid.org/0000-0002-3965-340X","contributorId":192554,"corporation":false,"usgs":true,"family":"Terry","given":"Neil","email":"nterry@usgs.gov","middleInitial":"C.","affiliations":[{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true}],"preferred":true,"id":760521,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lane, John W. Jr. 0000-0002-3558-243X jwlane@usgs.gov","orcid":"https://orcid.org/0000-0002-3558-243X","contributorId":189168,"corporation":false,"usgs":true,"family":"Lane","given":"John","suffix":"Jr.","email":"jwlane@usgs.gov","middleInitial":"W.","affiliations":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true}],"preferred":false,"id":760522,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70202931,"text":"70202931 - 2019 - Multi-scale preferential flow processes in an urban streambed under variable hydraulic conditions","interactions":[],"lastModifiedDate":"2019-04-05T12:54:14","indexId":"70202931","displayToPublicDate":"2019-04-05T08:59:04","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Multi-scale preferential flow processes in an urban streambed under variable hydraulic conditions","docAbstract":"Spatially preferential flow processes occur at nested scales at the sediment-water interface (SWI), due in part to sediment heterogeneities, which may be enhanced in flashy urban streams with heavy road sand influence. However, several factors, including the flow-rate dependence of preferential hyporheic flow and discrete groundwater discharge zones are commonly overlooked in reach-scale models of groundwater/surface water exchange. Using a series of controlled-head tracer-injection experiments coupled with cm-scale geophysics within the highly reactive upper 30 cm of the hyporheic zone of an urban stream, we quantified the flow dependence of local less-mobile porosity volume, mass-transfer rate coefficient, and the resulting local residence time in the less-mobile pore space at three controlled downward fluid fluxes (0.8, 2, and 3 m/d). Experiments were performed in two adjacent streambed locations, representing different sediment bulk vertical permeability. Less-mobile porosity parameters were generally substantial and similar between the two streambed locations; though a more competent, thin, organic layer at ∼15 cm depth in one location strongly impacted tracer loading, flushing dynamics, and local residence times. Increased downward flux led to (1) a decrease in less-mobile porosity residence time in all experiments, and (2) an increase in less-mobile porosity fraction for most experiments. Additionally, at the larger stream reach-scale, surface electrodes for electrical resistivity measurement were installed along 22 m of the wetted stream channel. These surface electrode measurements were collected during a natural storm flow event, which revealed widespread, short-term, flushing (e.g. <3 h) of the hyporheic zone with stream water, followed by longer-term (e.g. >60 h) flushing of the SWI with riparian zone groundwater. Flow dependence of preferential hyporheic zone flowpaths, like in the controlled tracer experiments, was also observed in these reach-scale electrical resistivity tomography measurements. Our findings reveal that the spatial and temporal dependence of preferential flow processes create highly dynamic SWI conditions that will affect the physical and coupled biogeochemical functions of the SWI in urbanized, sand-impacted streams.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2019.03.022","usgsCitation":"Dehkordy, F.M., Briggs, M.A., Day-Lewis, F.D., Singha, K., Krajnovich, A., Hampton, T.B., Zarnetske, J.P., Scruggs, C.R., and Bagtzoglou, A.C., 2019, Multi-scale preferential flow processes in an urban streambed under variable hydraulic conditions: Journal of Hydrology, v. 573, p. 168-179, https://doi.org/10.1016/j.jhydrol.2019.03.022.","productDescription":"12 p.","startPage":"168","endPage":"179","ipdsId":"IP-104970","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":467731,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jhydrol.2019.03.022","text":"Publisher Index Page"},{"id":362811,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"573","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Dehkordy, Farzaneh MahmoodPoor","contributorId":214661,"corporation":false,"usgs":false,"family":"Dehkordy","given":"Farzaneh","email":"","middleInitial":"MahmoodPoor","affiliations":[{"id":36710,"text":"University of Connecticut","active":true,"usgs":false}],"preferred":false,"id":760524,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Briggs, Martin A. 0000-0003-3206-4132 mbriggs@usgs.gov","orcid":"https://orcid.org/0000-0003-3206-4132","contributorId":4114,"corporation":false,"usgs":true,"family":"Briggs","given":"Martin","email":"mbriggs@usgs.gov","middleInitial":"A.","affiliations":[{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true},{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":760523,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Day-Lewis, Frederick D. 0000-0003-3526-886X daylewis@usgs.gov","orcid":"https://orcid.org/0000-0003-3526-886X","contributorId":1672,"corporation":false,"usgs":true,"family":"Day-Lewis","given":"Frederick","email":"daylewis@usgs.gov","middleInitial":"D.","affiliations":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true}],"preferred":true,"id":760525,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Singha, Kamini 0000-0002-0605-3774","orcid":"https://orcid.org/0000-0002-0605-3774","contributorId":191366,"corporation":false,"usgs":false,"family":"Singha","given":"Kamini","email":"","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":760526,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Krajnovich, Ashton","contributorId":214671,"corporation":false,"usgs":false,"family":"Krajnovich","given":"Ashton","email":"","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":760527,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hampton, Tyler B.","contributorId":210072,"corporation":false,"usgs":false,"family":"Hampton","given":"Tyler","email":"","middleInitial":"B.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":760528,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Zarnetske, Jay P.","contributorId":210073,"corporation":false,"usgs":false,"family":"Zarnetske","given":"Jay","email":"","middleInitial":"P.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":760529,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Scruggs, Courtney R. 0000-0002-1744-3233 cscruggs@usgs.gov","orcid":"https://orcid.org/0000-0002-1744-3233","contributorId":190406,"corporation":false,"usgs":true,"family":"Scruggs","given":"Courtney","email":"cscruggs@usgs.gov","middleInitial":"R.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":760530,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Bagtzoglou, Amvrossios C.","contributorId":211518,"corporation":false,"usgs":false,"family":"Bagtzoglou","given":"Amvrossios","email":"","middleInitial":"C.","affiliations":[{"id":36710,"text":"University of Connecticut","active":true,"usgs":false}],"preferred":false,"id":760531,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70252905,"text":"70252905 - 2019 - Factors affecting 1,2,3-trichloropropane contamination in groundwater in California","interactions":[],"lastModifiedDate":"2025-01-28T15:31:22.559551","indexId":"70252905","displayToPublicDate":"2019-04-05T07:08:51","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":17043,"text":"Science of the Total Envionrment","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Factors Affecting 1,2,3-trichloropropane Contamination in Groundwater in California","title":"Factors affecting 1,2,3-trichloropropane contamination in groundwater in California","docAbstract":"1,2,3-Trichloropropane (1,2,3-TCP) is a volatile organic chemical of eminent concern due to its carcinogenic, mutagenic, and reproductive effects, and its frequent occurrence at concentrations of concern worldwide. In California, 1,2,3-TCP was detected in 6.5% of 1237 wells sampled by the U. S. Geological Survey (USGS). About 8% of domestic wells had a detection of 1,2,3-TCP, compared to 5% of public-supply wells. 1,2,3-TCP was detected in 5.5% of most recent samples from 7787 public-supply well sources of the California State Water Resources Control Board Division of Drinking Water (DDW). Concentrations ranged from <0.005 to 2.7 μg/L. The California maximum contaminant level (MCL) is 0.005 μg/L. Most of the detections occurred in the San Joaquin Valley, where 1,2,3-TCP was detected above the MCL in 16% of USGS sampled wells and 18% of DDW wells. 1,2,3-TCP occurrence and concentrations are related to legacy fumigant use and hydrogeologic factors. Understanding factors affecting 1,2,3-TCP will aid in determining vulnerability and long term persistence in the San Joaquin Valley, which can help focus efforts to manage drinking water resources on the most vulnerable areas and also inform efforts in other areas of the state and worldwide. Widespread occurrence of 1,2,3-TCP is related to nonpoint source agricultural contaminant inputs. High concentrations of 1,2,3-TCP are in young, shallow, oxic groundwater beneath primarily orchard/vineyard crops. These areas are in coarse-grained sediments that promote rapid recharge, related to proximal alluvial fan sediments deposited by large streams that drain glaciated watersheds of the Sierra Nevada. 1,2,3-TCP co-occurs with 1,2-dibromo-3-chloropropane (DBCP) and 1,2-dichloropropane (1,2-DCP) throughout modern age groundwater, indicating its long term persistence with little degradation. The highest concentrations of 1,2,3-TCP were observed at point source cleanup sites in urban areas; depending on the age and source of groundwater to nearby public-supply wells, these areas may see increasing concentrations of 1,2,3-TCP.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2019.03.420","usgsCitation":"Burow, K.R., Floyd, W.D., and Landon, M.K., 2019, Factors affecting 1,2,3-trichloropropane contamination in groundwater in California: Science of the Total Envionrment, v. 672, no. 1 July 2019, p. 324-334, https://doi.org/10.1016/j.scitotenv.2019.03.420.","productDescription":"11 p.","startPage":"324","endPage":"334","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":487474,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2019.03.420","text":"Publisher Index Page"},{"id":427698,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":427783,"rank":2,"type":{"id":42,"text":"Open Access USGS Document"},"url":"https://pubs.usgs.gov/ja/70252905/70252905.pdf","text":"USGS open-access version of article","size":"5 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