We produced ∼3000-year long relative sea-level (RSL) histories for two sites in North Carolina (USA) using foraminifera preserved in new and existing cores of dated salt-marsh sediment. At Cedar Island, RSL rose by ∼2.4 m during the past ∼3000 years compared to ∼3.3 m at Roanoke Island. This spatial difference arises primarily from differential GIA that caused late Holocene RSL rise to be 0.1–0.2 mm/yr faster at Roanoke Island than at Cedar Island. However, a non-linear difference in RSL between the two study regions (particularly from ∼0 CE to ∼1250 CE) indicates that additional local- to regional-scale processes drove centennial-scale RSL change in North Carolina. Therefore, the Cedar Island and Roanoke Island records should be considered as independent of one another. Between-site differences on sub-millennial timescales cannot be adequately explained by non-stationary tides, sediment compaction, or local sediment dynamics. We propose that a period of accelerating RSL rise from ∼600 CE to 1100 CE that is present at Roanoke Island (and other sites north of Cape Hatteras at least as far as Connecticut), but absent at Cedar Island (and other sites south of Cape Hatteras at least as far as northeastern Florida) is a local-to regional-scale effect of dynamic ocean and/or atmospheric circulation.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.quascirev.2017.01.012","usgsCitation":"Kemp, A.C., Kegel, J.J., Culver, S.J., Barber, D.C., Mallinson, D.J., Leorri, E., Bernhardt, C.E., Cahill, N., Riggs, S.R., Woodson, A.L., Mulligan, R.P., and Horton, B.P., 2017, Extended late Holocene relative sea-level histories for North Carolina, USA: Quaternary Science Reviews, v. 160, p. 13-30, https://doi.org/10.1016/j.quascirev.2017.01.012.","productDescription":"18 p.","startPage":"13","endPage":"30","ipdsId":"IP-082692","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":470102,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.quascirev.2017.01.012","text":"Publisher Index Page"},{"id":348618,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina","otherGeospatial":"Cedar Island, Roanoke Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.41540527343749,\n 34.914088616906106\n ],\n [\n -76.2454605102539,\n 34.914088616906106\n ],\n [\n -76.2454605102539,\n 35.03449433167976\n ],\n [\n -76.41540527343749,\n 35.03449433167976\n ],\n [\n -76.41540527343749,\n 34.914088616906106\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.74592590332031,\n 35.801943102768846\n ],\n [\n -75.59761047363281,\n 35.801943102768846\n ],\n [\n -75.59761047363281,\n 35.94688293218141\n ],\n [\n -75.74592590332031,\n 35.94688293218141\n ],\n [\n -75.74592590332031,\n 35.801943102768846\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"160","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a096bb1e4b09af898c94147","contributors":{"authors":[{"text":"Kemp, Andrew C.","contributorId":192892,"corporation":false,"usgs":false,"family":"Kemp","given":"Andrew","email":"","middleInitial":"C.","affiliations":[{"id":6936,"text":"Tufts University","active":true,"usgs":false}],"preferred":false,"id":717794,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kegel, Jessica J.","contributorId":198983,"corporation":false,"usgs":false,"family":"Kegel","given":"Jessica","email":"","middleInitial":"J.","affiliations":[{"id":27911,"text":"East Carolina University Greenville, North Carolina,USA","active":true,"usgs":false}],"preferred":false,"id":717795,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Culver, Stephen J.","contributorId":198984,"corporation":false,"usgs":false,"family":"Culver","given":"Stephen","email":"","middleInitial":"J.","affiliations":[{"id":27911,"text":"East Carolina University Greenville, North Carolina,USA","active":true,"usgs":false}],"preferred":false,"id":717796,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barber, Donald C.","contributorId":198985,"corporation":false,"usgs":false,"family":"Barber","given":"Donald","email":"","middleInitial":"C.","affiliations":[{"id":6651,"text":"Bryn Mawr College, Bryn Mawr, PA","active":true,"usgs":false}],"preferred":false,"id":717797,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mallinson, David J.","contributorId":198986,"corporation":false,"usgs":false,"family":"Mallinson","given":"David","email":"","middleInitial":"J.","affiliations":[{"id":27911,"text":"East Carolina University Greenville, North Carolina,USA","active":true,"usgs":false}],"preferred":false,"id":717798,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Leorri, Eduardo","contributorId":198987,"corporation":false,"usgs":false,"family":"Leorri","given":"Eduardo","email":"","affiliations":[{"id":27911,"text":"East Carolina University Greenville, North Carolina,USA","active":true,"usgs":false}],"preferred":false,"id":717799,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bernhardt, Christopher E. 0000-0003-0082-4731 cbernhardt@usgs.gov","orcid":"https://orcid.org/0000-0003-0082-4731","contributorId":2131,"corporation":false,"usgs":true,"family":"Bernhardt","given":"Christopher","email":"cbernhardt@usgs.gov","middleInitial":"E.","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":717793,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Cahill, Niamh","contributorId":150754,"corporation":false,"usgs":false,"family":"Cahill","given":"Niamh","email":"","affiliations":[{"id":18091,"text":"University College Dublin","active":true,"usgs":false},{"id":6932,"text":"University of Massachusetts, Amherst","active":true,"usgs":false}],"preferred":false,"id":717800,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Riggs, Stanley R.","contributorId":198988,"corporation":false,"usgs":false,"family":"Riggs","given":"Stanley","email":"","middleInitial":"R.","affiliations":[{"id":27911,"text":"East Carolina University Greenville, North Carolina,USA","active":true,"usgs":false}],"preferred":false,"id":717801,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Woodson, Anna L.","contributorId":198989,"corporation":false,"usgs":false,"family":"Woodson","given":"Anna","email":"","middleInitial":"L.","affiliations":[{"id":6651,"text":"Bryn Mawr College, Bryn Mawr, PA","active":true,"usgs":false},{"id":27911,"text":"East Carolina University Greenville, North Carolina,USA","active":true,"usgs":false}],"preferred":false,"id":717802,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Mulligan, Ryan P.","contributorId":194423,"corporation":false,"usgs":false,"family":"Mulligan","given":"Ryan","email":"","middleInitial":"P.","affiliations":[{"id":35723,"text":"Queen's University - Kingston, Ontario","active":true,"usgs":false}],"preferred":false,"id":721687,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Horton, Benjamin P.","contributorId":192807,"corporation":false,"usgs":false,"family":"Horton","given":"Benjamin","email":"","middleInitial":"P.","affiliations":[{"id":12727,"text":"Rutgers University","active":true,"usgs":false},{"id":5110,"text":"Earth Observatory of Singapore, Nanyang Technological University","active":true,"usgs":false}],"preferred":false,"id":721688,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70182161,"text":"ofr20171022 - 2017 - Record-high specific conductance and water temperature in San Francisco Bay during water year 2015","interactions":[],"lastModifiedDate":"2017-10-30T09:38:04","indexId":"ofr20171022","displayToPublicDate":"2017-02-22T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-1022","title":"Record-high specific conductance and water temperature in San Francisco Bay during water year 2015","docAbstract":"The San Francisco estuary is commonly defined to include San Francisco Bay (bay) and the adjacent Sacramento–San Joaquin River Delta (delta). The U.S. Geological Survey (USGS) has operated a high-frequency (15-minute sampling interval) water-quality monitoring network in San Francisco Bay since the late 1980s (Buchanan and others, 2014). This network includes 19 stations at which sustained measurements have been made in the bay; currently, 8 stations are in operation (fig. 1). All eight stations are equipped with specific conductance (which can be related to salinity) and water-temperature sensors. Water quality in the bay constantly changes as ocean tides force seawater in and out of the bay, and river inflows—the most significant coming from the delta—vary on time scales ranging from those associated with storms to multiyear droughts. This monitoring network was designed to observe and characterize some of these changes in the bay across space and over time. The data demonstrate a high degree of variability in both specific conductance and temperature at time scales from tidal to annual and also reveal longer-term changes that are likely to influence overall environmental health in the bay.
In water year (WY) 2015 (October 1, 2014, through September 30, 2015), as in the preceding water year (Downing-Kunz and others, 2015), the high-frequency measurements revealed record-high values of specific conductance and water temperature at several stations during a period of reduced freshwater inflow from the delta and other tributaries because of persistent, severe drought conditions in California. This report briefly summarizes observations for WY 2015 and compares them to previous years that had different levels of freshwater inflow.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171022","issn":"2331-1258 (online)","usgsCitation":"Work, P.A., Downing-Kunz, M.A., and Livsey, D., 2017, Record-high specific conductance and water temperature in San Francisco Bay during water year 2015: U.S. Geological Survey Open-File Report 2017–1022, 4 p., https://doi.org/10.3133/ofr20171022.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"Y","ipdsId":"IP-079162","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":552,"text":"San Francisco Bay-Delta","active":false,"usgs":true}],"links":[{"id":335947,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1022/coverthb.jpg"},{"id":335948,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1022/ofr20171022.pdf","text":"Report","size":"1.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1022"}],"country":"United States","state":"California","otherGeospatial":"Sacramento-San Joaquin River Delta, San Francisco Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.9,\n 37.4\n ],\n [\n -122.5,\n 37.4\n ],\n [\n -122.5,\n 38.1\n ],\n [\n -121.9,\n 38.1\n ],\n [\n -121.9,\n 37.4\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, CA 95819
What has driven changes in land use and land cover in West Africa over the past 40 years? What trends or patterns can be discerned in those changes? To answer these questions, the U.S. Geological Survey West Africa Land Use Dynamics project partnered with the Permanent Interstate Committee for Drought Control in the Sahel and the U.S. Agency for International Development/West Africa to map land use and land cover across the region for three time periods (years): 1975, 2000, and 2013. This cooperative effort has resulted in the publication of a 219-page atlas, “Landscapes of West Africa: A Window on a Changing World.” The atlas uses satellite imagery, maps, and pictures to tell a complex story of landscape change at regional and national scales. It includes a collection of focused studies, some of which raise cause for concern, and others that provide considerable hope.
","language":"English, French","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20173005","usgsCitation":"Cotillon, S.E., 2017, The landscapes of West Africa—40 years of change: U.S. Geological Survey Fact Sheet 2017–3005, 2 p., https://doi.org/10.3133/fs20173005.","productDescription":"2 p.","onlineOnly":"Y","ipdsId":"IP-082370","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":335758,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2017/3005/fs20173005_French.pdf","text":"Report – French","size":"3.07 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2017-3005 French"},{"id":335757,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2017/3005/fs20173005.pdf","text":"Report – English","size":"3.12 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2017-3005 English"},{"id":335751,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2017/3005/coverthb.jpg"}],"otherGeospatial":"West Africa","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 10.41107660211324,\n 2.118513429359794\n ],\n [\n 23.28428565006891,\n 11.810719747300766\n ],\n [\n 25.961560823287215,\n 32.42941470582909\n ],\n [\n 6.142411713899236,\n 37.98242670846139\n ],\n [\n -8.211384638428427,\n 36.27077305284628\n ],\n [\n -18.442986479614405,\n 21.57365946263323\n ],\n [\n -15.922624317482331,\n 9.250741295049338\n ],\n [\n -6.7555044485721965,\n 3.0864107262271716\n ],\n [\n 10.41107660211324,\n 2.118513429359794\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Earth Resources Observation and Science (EROS) Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, South Dakota 57198-0001
This 1:24,000-scale geologic map includes new geologic mapping as well as compilation and revision of previous geologic maps in the area. Field investigations were carried out during 2009–2011 that included mapping and investigations of the geology and hydrology of the Chickasaw National Recreation Area, Oklahoma, west of the map area.
The Fittstown quadrangle is in Pontotoc and Johnston Counties in south-central Oklahoma, which is in the northeastern part of the Arbuckle Mountains. The Arbuckle Mountains are composed of a thick sequence of Paleozoic sedimentary rocks that overlie Lower Cambrian and Precambrian igneous rocks; these latter rocks are not exposed in the quadrangle. From Middle to Late Pennsylvanian time, the Arbuckle Mountains region was folded, faulted, and uplifted. Periods of erosion followed these Pennsylvanian mountain-building events, beveling this region and ultimately developing the current subtle topography that includes hills and incised uplands. The southern and northwestern parts of the Fittstown quadrangle are directly underlain by Lower Ordovician dolomite of the Arbuckle Group that has eroded to form an extensive, stream-incised upland containing the broad, gently southeast-plunging, Pennsylvanian-age Hunton anticline. The northeastern part of the map area is underlain by Middle Ordovician to Pennsylvanian limestone, shale, and sandstone units that predominantly dip northeast and form the northeastern limb of the Hunton anticline; this limb is cut by steeply dipping, northwest-southeast striking faults of the Franks fault zone. This limb and the Franks fault zone define the southwestern margin of the Franks graben, which is underlain by Pennsylvanian rocks in the northeast part of the map area.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3371","usgsCitation":"Lidke, D.J., and Blome, C.D., 2017, Geologic map of the Fittstown 7.5′ quadrangle, Pontotoc and Johnston Counties, Oklahoma: U.S. Geological Survey Scientific Investigations Map 3371, 14 p., 1 sheet, scale 1:24,000, https://doi.org/10.3133/sim3371.","productDescription":"Pamphlet: iv, 14 p.; 1 Sheet: 34.09 x 34.35 inches; Read Me; Spatial Data","numberOfPages":"22","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-073124","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":438453,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F77P8WJN","text":"USGS data release","linkHelpText":"Geologic map of the Fittstown 7 1/2' quadrangle, Pontotoc and Johnston Counties, Oklahoma"},{"id":332521,"rank":4,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3371/sim3371__map.pdf","text":"Map","size":"31.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3371 Map"},{"id":332522,"rank":5,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3371/sim3371__map_geo.pdf","text":"Georeferenced Map","size":"187 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3371 Georeferenced Map"},{"id":332520,"rank":3,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sim/3371/sim3371_ReadMe_v2.txt","text":"Read Me","size":"8.0 kB","linkFileType":{"id":2,"text":"txt"},"description":"SIM 3371 Read Me"},{"id":332523,"rank":6,"type":{"id":23,"text":"Spatial Data"},"url":"https://doi.org/10.5066/F77P8WJN","text":"Data Release","description":"SIM 3371 Data Release"},{"id":332519,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3371/sim3371_pamphlet.pdf","text":"Pamphlet","size":"3.19 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3371 Pamphlet"},{"id":332518,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3371/coverthb_map2.jpg"}],"country":"United States","state":"Oklahoma","county":"Johnson County. Pontotoc County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.75,\n 34.625\n ],\n [\n -96.75,\n 34.5\n ],\n [\n -96.625,\n 34.5\n ],\n [\n -96.625,\n 34.625\n ],\n [\n -96.75,\n 34.625\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Center Director, USGS Geosciences and Environmental Change Science Center
Box 25046, Mail Stop 980
Denver, CO 80225
Extreme space weather events are low-frequency, high-risk phenomena. Estimating their rates of occurrence, as well as their associated uncertainties, is difficult. In this study, we derive statistical estimates and uncertainties for the occurrence rate of an extreme geomagnetic storm on the scale of the Carrington event (or worse) occurring within the next decade. We model the distribution of events as either a power law or lognormal distribution and use (1) Kolmogorov-Smirnov statistic to estimate goodness of fit, (2) bootstrapping to quantify the uncertainty in the estimates, and (3) likelihood ratio tests to assess whether one distribution is preferred over another. Our best estimate for the probability of another extreme geomagnetic event comparable to the Carrington event occurring within the next 10 years is 10.3% 95% confidence interval (CI) [0.9,18.7] for a power law distribution but only 3.0% 95% CI [0.6,9.0] for a lognormal distribution. However, our results depend crucially on (1) how we define an extreme event, (2) the statistical model used to describe how the events are distributed in intensity, (3) the techniques used to infer the model parameters, and (4) the data and duration used for the analysis. We test a major assumption that the data represent time stationary processes and discuss the implications. If the current trends persist, suggesting that we are entering a period of lower activity, our forecasts may represent upper limits rather than best estimates.
","language":"English","publisher":"AGU Publications","doi":"10.1002/2016SW001470","usgsCitation":"Riley, P., and Love, J.J., 2017, Extreme geomagnetic storms: Probabilistic forecasts and their uncertainties: Space Weather, v. 15, no. 1, p. 53-64, https://doi.org/10.1002/2016SW001470.","productDescription":"12 p.","startPage":"53","endPage":"64","ipdsId":"IP-081721","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":346971,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"15","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-01-10","publicationStatus":"PW","scienceBaseUri":"59e9b996e4b05fe04cd65cba","contributors":{"authors":[{"text":"Riley, Pete","contributorId":145704,"corporation":false,"usgs":false,"family":"Riley","given":"Pete","email":"","affiliations":[{"id":16202,"text":"Predictive Science Inc.","active":true,"usgs":false}],"preferred":false,"id":713249,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Love, Jeffrey J. 0000-0002-3324-0348 jlove@usgs.gov","orcid":"https://orcid.org/0000-0002-3324-0348","contributorId":760,"corporation":false,"usgs":true,"family":"Love","given":"Jeffrey","email":"jlove@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":713250,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70182516,"text":"70182516 - 2016 - A manual to identify sources of fluvial sediment","interactions":[],"lastModifiedDate":"2017-07-25T09:52:55","indexId":"70182516","displayToPublicDate":"2017-02-27T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesNumber":"EPA/600/R-16/210","title":"A manual to identify sources of fluvial sediment","docAbstract":"Sediment is an important pollutant of concern that can degrade and alter aquatic habitat. A sediment budget is an accounting of the sources, storage, and export of sediment over a defined spatial and temporal scale. This manual focuses on field approaches to estimate a sediment budget. We also highlight the sediment fingerprinting approach to attribute sediment to different watershed sources. Determining the sources and sinks of sediment is important in developing strategies to reduce sediment loads to water bodies impaired by sediment. Therefore, this manual can be used when developing a sediment TMDL requiring identification of sediment sources.
The manual takes the user through the seven necessary steps to construct a sediment budget:
Sediment budget construction begins with examining the question(s) being asked and whether a sediment budget is necessary to answer these question(s). If undertaking a sediment budget analysis is a viable option, the next step is to define the spatial scale of the watershed and the time scale needed to answer the question(s). Of course, we understand that monetary constraints play a big role in any decision.
Early in the sediment budget development process, we suggest getting to know your watershed by conducting a reconnaissance and meeting with local stakeholders. The reconnaissance aids in understanding the geomorphic setting of the watershed and potential sources of sediment. Identifying the potential sediment sources early in the design of the sediment budget will help later in deciding which tools are necessary to monitor erosion and/or deposition at these sources. Tools can range from rapid inventories to estimate the sediment budget or quantifying sediment erosion, deposition, and export through more rigorous field monitoring. In either approach, data are gathered and erosion and deposition calculations are determined and compared to the sediment export with a description of the error uncertainty. Findings are presented to local stakeholders and management officials.
Sediment fingerprinting is a technique that apportions the sources of fine-grained sediment in a watershed using tracers or fingerprints. Due to different geologic and anthropogenic histories, the chemical and physical properties of sediment in a watershed may vary and often represent a unique signature (or fingerprint) for each source within the watershed. Fluvial sediment samples (the target sediment) are also collected and exhibit a composite of the source properties that can be apportioned through various statistical techniques. Using an unmixing-model and error analysis, the final apportioned sediment is determined.
","language":"English","publisher":"U.S. Environmental Protection Agency","publisherLocation":"Washington, D.C.","usgsCitation":"Gellis, A.C., Fitzpatrick, F., and Schubauer-Berigan, J., 2016, A manual to identify sources of fluvial sediment, xi, 106 p.","productDescription":"xi, 106 p.","numberOfPages":"117","ipdsId":"IP-078964","costCenters":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":336244,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":336150,"type":{"id":15,"text":"Index Page"},"url":"https://cfpub.epa.gov/si/si_public_record_report.cfm?dirEntryId=335394"}],"publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58b548bde4b01ccd54fddfa4","contributors":{"authors":[{"text":"Gellis, Allen C. 0000-0002-3449-2889 agellis@usgs.gov","orcid":"https://orcid.org/0000-0002-3449-2889","contributorId":172245,"corporation":false,"usgs":true,"family":"Gellis","given":"Allen","email":"agellis@usgs.gov","middleInitial":"C.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":false,"id":671371,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fitzpatrick, Faith A. 0000-0002-9748-7075 fafitzpa@usgs.gov","orcid":"https://orcid.org/0000-0002-9748-7075","contributorId":173463,"corporation":false,"usgs":true,"family":"Fitzpatrick","given":"Faith A.","email":"fafitzpa@usgs.gov","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":false,"id":671372,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schubauer-Berigan, Joseph","contributorId":182408,"corporation":false,"usgs":false,"family":"Schubauer-Berigan","given":"Joseph","email":"","affiliations":[],"preferred":false,"id":671373,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70175252,"text":"sir20165093 - 2016 - Spatial and temporal variation of stream chemistry associated with contrasting geology and land-use patterns in the Chesapeake Bay watershed—Summary of results from Smith Creek, Virginia; Upper Chester River, Maryland; Conewago Creek, Pennsylvania; and Difficult Run, Virginia, 2010–2013","interactions":[],"lastModifiedDate":"2016-11-17T16:24:46","indexId":"sir20165093","displayToPublicDate":"2016-11-17T00:00:00","publicationYear":"2016","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":"2016-5093","title":"Spatial and temporal variation of stream chemistry associated with contrasting geology and land-use patterns in the Chesapeake Bay watershed—Summary of results from Smith Creek, Virginia; Upper Chester River, Maryland; Conewago Creek, Pennsylvania; and Difficult Run, Virginia, 2010–2013","docAbstract":"Despite widespread and ongoing implementation of conservation practices throughout the Chesapeake Bay watershed, water quality continues to be degraded by excess sediment and nutrient inputs. While the Chesapeake Bay Program has developed and maintains a large-scale and long-term monitoring network to detect improvements in water quality throughout the watershed, fewer resources have been allocated for monitoring smaller watersheds, even though water-quality improvements that may result from the implementation of conservation practices are likely to be first detected at smaller watershed scales.
In 2010, the U.S. Geological Survey partnered with the U.S. Environmental Protection Agency and the U.S. Department of Agriculture to initiate water-quality monitoring in four selected small watersheds that were targeted for increased implementation of conservation practices. Smith Creek watershed is an agricultural watershed in the Shenandoah Valley of Virginia that is dominated by cattle and poultry production, and the Upper Chester River watershed is an agricultural watershed on the Eastern Shore of Maryland that is dominated by row-cropping activities. The Conewago Creek watershed is an agricultural watershed in southeastern Pennsylvania that is characterized by mixed agricultural activities. The fourth watershed, Difficult Run, is a suburban watershed in northern Virginia that is dominated by medium density residential development. The objective of this study was to investigate spatial and temporal variations in water chemistry and suspended sediment in these four relatively small watersheds that represent a range of land-use patterns and underlying geology to (1) characterize current water-quality conditions in these watersheds, and (2) identify the dominant sources, sinks, and transport processes in each watershed.
The general study design involved two components. The first included intensive routine water-quality monitoring at an existing streamgage within each study area (including continuous water-quality monitoring as well as discrete water-quality sampling) to develop a detailed understanding of the temporal and hydrologic variability in stream chemistry and sediment transport in each watershed. The second component involved extensive water-quality monitoring at various sites throughout each watershed to develop a detailed understanding of spatial patterns. Both components were used to improve understanding of sources and transport processes affecting stream chemistry, including nutrients and suspended sediments, and their implications for detecting long-term trends related to best management practices. This report summarizes the results of monitoring that was performed from April 2010 through September 2013.
Summaries for each of the four small watersheds are presented below. Each watershed has a more descriptive and detailed section in the report, but these summaries may be particularly useful for some watershed managers and stakeholders desiring slightly less technical detail.
Smith Creek is a 105.39-mi2 watershed within the Shenandoah Valley that drains to the North Fork Shenandoah River. The long-term Smith Creek base-flow index is 72.3 percent, indicating that on average, approximately 72 percent of Smith Creek flow was base flow, which suggests that Smith Creek streamflow is dominated by groundwater discharge rather than stormwater runoff. A series of cluster and principal components analyses demonstrated that the majority of the variability in Smith Creek water quality could be attributed to hydrologic and seasonal variability. Statistically significant positive correlations with flow were observed for turbidity, suspended sediments, total nitrogen, ammonium, orthophosphate, iron, total phosphorus, and the ratio of calcium to magnesium. Statistically significant inverse correlations with flow were observed for specific conductance, magnesium, δ15N of nitrate, pH, bicarbonate, calcium, and δ18O of nitrate. Of particular note, flow and nitrate were not statistically significantly correlated, likely because of the relatively complex concentration-discharge relationship observed in continuous and discrete datasets. Statistically significant seasonal patterns were observed for numerous water-quality constituents: water temperature, turbidity, orthophosphate, total phosphorus, suspended-sediment concentration, and silica were higher during the warm season, but pH, dissolved oxygen, and sulfate were higher during the cool season. Surrogate regression models were developed to compute sediment and nutrient loads in Smith Creek using the continuous water-quality monitors. The mean Smith Creek in-stream sediment load was approximately 6,900 tons per year, with nearly 90 percent of the sediment load over the 3-year study period contributed during the eight largest storm events during that period. The Smith Creek total phosphorus load was approximately 21,000 pounds of phosphorus per year, with the majority of the load contributed during stormflow periods, although a substantial phosphorus load still occurs during base-flow conditions. The Smith Creek total nitrogen load was approximately 400,000 pounds per year, with total nitrogen accumulation less dominated by stormflow contributions (as was the case for sediment and total phosphorus) and strongly affected by base-flow export of nitrogen from the basin.
Extensive water-quality monitoring throughout the Smith Creek watershed revealed how the complex geology and hydrology interacted to result in variable water chemistry. During relatively dry and low base-flow periods, much of the discharge in Smith Creek was contributed by a single dominant spring—Lacey Spring. During wetter base-flow periods, the flows in Smith Creek were largely generated by a mixture of headwater springs and forested mountain tributaries with very different geochemical composition. The headwater springs generally issued from limestone bedrock and were characterized as having relatively high nitrate, specific conductance, calcium, and magnesium, as well as relatively low concentrations of phosphorus, ammonium, iron, and manganese. The undeveloped, high-gradient, forested mountain sites were generally characterized by low ionic strength waters with low nutrient concentrations. Nitrate isotope data from the limestone springs generally were consistent with manure-derived nitrogen sources (such as cattle and poultry), although the possibility of other mixed sources cannot be excluded. Nitrate isotope data from the undeveloped, high-gradient forested mountain sites were more consistent with nitrogen from undisturbed soils, atmospheric deposition, or nitrogen fixation. Regardless of the nitrogen source, oxygen isotope data indicate that the nitrate was largely a result of nitrification. Land-use data indicate that manure sources of nitrogen dominated watershed nitrogen inputs. Phosphorus sources were less well studied. The presence of a single point-source discharge near the town of New Market contributed the majority of the phosphorus to Smith Creek under base-flow conditions, but nonpoint sources of phosphorus dominated the loading to Smith Creek during stormflow periods.
Implementation of conservation practices increased in the Smith Creek watershed during the study period, and even though a broad range of practice types was implemented, the most common practices included stream fencing (for cattle exclusion), the development of nutrient management plans, conservation crop rotation, and the planting of cover crops. While the implementation of these conservation practices is encouraging, results indicate small increases in nitrate concentrations at the streamgage over the last 29 years, concurrent with small decreases in nitrate fluxes. It will likely be years before the cumulative effect of these practices can be detected in the Smith Creek water quality, and the magnitude of the effect of these conservation practices detected in Smith Creek will depend largely on whether nutrient loading (of manure and commercial fertilizer) is reduced over time.
The Upper Chester River watershed includes the 36-square-mile (mi2) watershed area around several nontidal tributaries that drain into the tidal Chester River. The streamgage is on Chesterville Branch, the largest nontidal tributary (approximately 6.12 mi2) and is the site for continuous water-quality monitoring for this project. The base-flow index at Chesterville Branch is about 72 percent and indicates that, as in most of the Coastal Plain, groundwater is the greatest contributor to streamflow. As such, more than 90 percent of the nitrogen in the stream is in the form of nitrate from groundwater. Continuous and discrete data collected at Chesterville Branch show the effects of streamflow and season on water quality. Significantly positive correlations with flow were observed for ammonium, dissolved and total phosphorus, sediment, and turbidity as runoff carried these constituents from the land surface into Chesterville Branch. Other constituents that increased significantly with flow include potassium, sulfate, iron, and manganese, which are likely contributed from near-stream areas and ponds with high organic-matter content. Total nitrogen, pH, and specific conductance, along with chemical constituents associated with groundwater inputs including nitrate, calcium, ratio of calcium to magnesium, silica, bicarbonate, and sodium, were negatively correlated with flow because concentrations of these constituents were diluted by runoff.
Seasonal differences in water chemistry, which are most likely related to increased biologic effects on the uptake and release of chemicals in the stream and near-stream areas, also were observed. Water temperature, orthophosphate, δ15N of nitrate, bicarbonate, sodium, and the ratio of sodium to chloride were higher during the warm season, and dissolved oxygen, total nitrogen, nitrate, magnesium, sulfate, and manganese were higher during the cool season.
Surrogate-regression models developed by using continuous water-quality data showed that the annual sediment load for the 2013 water year was about 2,600 tons, with more than 90 percent of this sediment contributed during two storms. The total phosphorus load in 2013 was about 13,000 pounds with more than 90 percent contributed during the same two storms as sediment. The load of total nitrogen, 140,000 pounds, accumulated steadily throughout the 2013 water year as nitrate in groundwater continuously discharged into the stream. The same two large storms that contributed 90 percent of the suspended-sediment and total phosphorus load only contributed about 20 percent of the annual total nitrogen load.
Extensive water-quality monitoring of stream base flow throughout the Upper Chester River watershed identified how differences in land use and hydrogeology affected water chemistry. In parts of the watershed with well-drained soil and thick sandy aquifer sediments, concentrations of nitrate and other chemicals associated with fertilizer and lime application increased in streams as agricultural land use increased. More than 90 percent of the nitrogen in streams from these areas was in the form of nitrate, and concentrations ranged from about 5 milligrams per liter (mg/L) to 8 mg/L as nitrogen in the two largest tributaries. Stream nitrate concentrations were about 1 mg/L as nitrogen where soils were more poorly drained, the surficial aquifer sediments were thinner, and forests and wetlands were more widespread than agriculture. Nitrate isotope data were consistent with inorganic fertilizers ± atmospheric deposition and N2 fixation as sources of nitrogen, and with nitrification as the dominant nitrate-forming process. Nitrate reduction was indicated by elevated δ15N and δ18O values in some samples from streams draining watersheds with poorly drained soils. An analysis of land-use data and SPARROW modeling input data attributed almost 90 percent of the nitrogen sources in the Upper Chester River watershed to inorganic fertilizer and fixation of atmospheric nitrogen by legumes, which is in agreement with the isotopic characteristics of nitrate in this watershed. Local sources of manure are limited in this area. Total phosphorus concentrations during base flow ranged from below detection to about 0.2 mg/L. Stream phosphorus concentrations during base flow were generally lower than those measured during storms because most phosphorus transport likely occurs as phosphorus attached to sediment particles during runoff. Because manure is not widely used in this area, the major source of phosphorus is likely fertilizer.
The implementation of conservation practices in the Upper Chester River watershed increased substantially during the study period, with a total implementation of 1,194 U.S. Department of Agriculture-compliant practices. The most frequently used practices were oriented towards nutrient and sediment control, including cover crops, nutrient management planning, conservation crop rotation, conservation tillage, and irrigation management. The current Chesapeake Bay model for this area predicts that implementation of best management practices should result in a 13-percent decrease in overall delivery of nitrogen to the Upper Chester River. Because most nitrogen travels through the groundwater system for years to decades before being discharged to streams, the time period of monitoring was not sufficient to see the effects of these practices on water quality. The magnitude of the effect that may eventually be detected will depend on the degree to which nitrate leaching into the groundwater system is reduced over time. Loadings of phosphorus and sediment are primarily transported during large runoff events and are difficult to control and analyze for trends because of their timing and episodic nature.
Conewago Creek has two primary monitoring locations—one near the middle of the 47-mi2 watershed and the other near the outlet just upstream of the Susquehanna River. The base-flow index was 47.3 percent for 2012–2013, indicating that on average, approximately 53 percent of the streamflow in Conewago Creek exited the watershed as surface flow, which suggests that the stormwater runoff was somewhat greater than groundwater discharge (base flow). A series of cluster and principal components analyses demonstrated that the majority of the variability in the Conewago Creek water quality could be attributed to hydrologic and seasonal variability. Statistically significant positive correlations with flow were observed at both monitoring sites for ammonium, total phosphorus, orthophosphate, iron, and manganese; additionally, at the upstream monitoring station, total nitrogen demonstrated a statistically significant positive correlation with flow. Statistically significant inverse correlations with flow were observed at both sites for water temperature, specific conductance (at the downstream site only), sulfate, chloride, calcium, and magnesium. Statistically significant seasonal patterns were observed for several water-quality constituents. Water temperature, phosphorus (upstream site only), and orthophosphate were higher during the warm season, and nitrate and total nitrogen (upstream site only) were higher during the cool season.
Surrogate regression models were developed to compute sediment and nutrient load in Conewago Creek by using the continuous water-quality monitors and water-quality samples. Conewago Creek sediment load was approximately 9,900 tons in 2012 and approximately 18,900 tons in 2013, with nearly 80 percent of the sediment load in 2013 contributed by the three largest storm events. Annual total nitrogen loads could not be estimated due to poor model performance. The addition of continued monitoring or a continuously recording nitrate sensor could improve estimates of total nitrogen loads. During 2012 and 2013, phosphorus loads in Conewago Creek were approximately 50,000 pounds in each year.
Combining data from one high-flow synoptic sampling with the data from routine sampling revealed how the geology and hydrology interact to result in variable water chemistry throughout the Conewago Creek watershed. The areas above the upstream gage in the headwaters are generally underlain by forested non-carbonate bedrock and are characterized by relatively low nitrate, specific conductance, calcium, and magnesium, as well as relatively low concentrations of phosphorus, ammonium, iron, and manganese. The more developed, agricultural areas below the upstream site were generally characterized by higher ionic strength waters with higher nutrient and metal concentrations. An analysis of land-use data and SPAtially Referenced Regressions On Watershed (SPARROW) modeling data indicates that manure sources of nitrogen dominate the input of nitrogen to the watershed.
Implementation of conservation practices increased in the Conewago Creek watershed during the study period, and while a broad range of practice types were implemented, the most common practices included residue and tillage management, cover crops, nutrient management, terracing, and stream fencing (for animal exclusion or bank restoration). While the implementation of these conservation practices is encouraging, the cumulative effects of these practices probably will not be detected in Conewago Creek water quality for several years. The magnitude of the effects of these conservation practices on water quality in Conewago Creek will depend largely on the extent to which nutrient loading (septic, manure, and commercial fertilizer) and sediment-producing activities are reduced over time.
The Difficult Run watershed is a 57.82-mi2 watershed that drains to the Potomac River. The long-term Difficult Run base-flow index (from 1936 to 2010) was 57.9, indicating that approximately 58 percent of streamflow exited the watershed as base flow and 42 percent as stormflow; however, with continued development and urbanization of the watershed, the base-flow index has decreased to 50 percent during the last 20 years. This base-flow index was less than those of the other watersheds evaluated in this study, likely because the Difficult Run watershed largely is underlain by crystalline piedmont metamorphic rocks and has a greater proportion of impervious urban land cover. A series of cluster and principal components analyses indicated that most of the variability in Difficult Run water quality could be attributed to hydrologic variability and seasonality. Statistically significant positive correlations with flow were observed for turbidity, dissolved oxygen, suspended sediments, ammonium, orthophosphate, iron, and total phosphorus. Statistically significant inverse correlations with flow were observed for water temperature, pH, specific conductance, bicarbonate, calcium, magnesium, nitrate, δ15N of nitrate, and silica. Statistically significant seasonal patterns were observed for numerous water-quality constituents: water temperature, ammonium, orthophosphate, and δ15N of nitrate were higher during the warm season, and dissolved oxygen, nitrate, and manganese were higher during the cool season. Surrogate regression models were developed to compute sediment and nutrient loading rates. The Difficult Run sediment load was approximately 8,000 tons per year, with greater than 95 percent of the sediment load in the 2013 water year contributed by the seven largest storm events. The total phosphorus load in Difficult Run was approximately 14,000 pounds of phosphorus per year, with the majority of the load contributed during stormflow periods. The total nitrogen load in Difficult Run is estimated to have been approximately 140,000 pounds per year, with total nitrogen accumulation less dominated by stormflow contributions than that of phosphorus and strongly affected by base-flow export of nitrogen from the basin.
Extensive water-quality monitoring throughout the Difficult Run watershed revealed relatively uniform generation of flow per unit of watershed area, as well as spatial variation in water quality that is strongly related to land-use activities. Elevated nitrate concentrations were observed in a subset of monitoring sites that are inversely correlated with population density and positively correlated to the septic system density within each subwatershed. The majority of the elevated nitrate concentrations for these sites are hypothesized to be caused by nitrate leaching from septic systems, more so than homeowner fertilizer usage among these subwatersheds that have lower population densities than other parts of the watershed. Nitrate isotope data, temporal patterns in the water-quality data, mass-balance computations, and a separate land-use analysis all generally indicate that leachate from septic systems was the likely source of the elevated nitrate. Another group of water-quality sites have relatively low nitrogen concentrations, are located in areas that are served by city sewer lines, and have experienced stream restoration activities. A final group of sites drained the areas with the highest imperviousness and had strongly elevated specific conductance, chloride, and sodium, which were likely caused by a combination of road salting and other anthropogenic sources draining these urbanized areas in the watershed. A fourth group of sites represents a mixture of water sources and had water quality similar to that at the Difficult Run streamgage. Analysis of the nitrate isotope data generally indicates a broad range of composition indicative of mixed natural and anthropogenic nitrogen sources. Implementation of conservation practices increased in the Difficult Run watershed during the study period, and while a broad range of practice types was implemented, the most common practices included stream restoration. While the implementation of these conservation practices is encouraging, the cumulative effect of these practices probably will not be detected in Difficult Run water quality for several years.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165093","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency Chesapeake Bay Program","usgsCitation":"Hyer, K.E., Denver, J.M., Langland, M.J., Webber, J.S., Böhlke, J.K., Hively, W.D., and Clune, J.W., 2016, Spatial and temporal variation of stream chemistry associated with contrasting geology and land-use patterns in the Chesapeake Bay watershed—Summary of results from Smith Creek, Virginia; Upper Chester River, Maryland; Conewago Creek, Pennsylvania; and Difficult Run, Virginia, 2010–2013: U.S. Geological Survey Scientific Investigations Report 2016–5093, 211 p., https://dx.doi.org/10.3133/sir20165093.","productDescription":"Report: xix, 211 p.","startPage":"1","endPage":"211","numberOfPages":"236","onlineOnly":"N","ipdsId":"IP-067371","costCenters":[{"id":614,"text":"Virginia Water Science 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\"Polygon\"\n},\n\"properties\": {\n\"name\": \"simple chesapeake bay outline\",\n\"shortName\": \"ches_bay\",\n\"code\": \"\",\n\"abbreviation\": \"\",\n\"description\": \"\",\n\"notes\": \"\",\n\"promotedForReuse\": true,\n\"extentType\": \"Custom\"\n},\n\"bbox\": [\n-80.54012471130748,\n36.64642476723632,\n-74.58063054811895,\n42.98721592955874\n]\n}","contact":"Director, Virginia Water Science Center
U.S. Geological Survey
1730 East Parham Road
Richmond, VA 23228
Behavior of coastal systems on time scales ranging from single storm events to years and decades is controlled by both small-scale sediment transport processes and large-scale geologic, oceanographic, and morphologic processes. Improved understanding of coastal behavior at multiple time scales is required for refining models that predict potential erosion hazards and for coastal management planning and decision-making. Here we investigate the primary controls on shoreline response along a geologically-variable barrier island on time scales resolving extreme storms and decadal variations over a period of nearly one century. An empirical orthogonal function analysis is applied to a time series of shoreline positions at Fire Island, NY to identify patterns of shoreline variance along the length of the island. We establish that there are separable patterns of shoreline behavior that represent response to oceanographic forcing as well as patterns that are not explained by this forcing. The dominant shoreline behavior occurs over large length scales in the form of alternating episodes of shoreline retreat and advance, presumably in response to storms cycles. Two secondary responses include long-term response that is correlated to known geologic variations of the island and the other reflects geomorphic patterns with medium length scale. Our study also includes the response to Hurricane Sandy and a period of post-storm recovery. It was expected that the impacts from Hurricane Sandy would disrupt long-term trends and spatial patterns. We found that the response to Sandy at Fire Island is not notable or distinguishable from several other large storms of the prior decade.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.margeo.2016.08.008","usgsCitation":"Hapke, C.J., Plant, N.G., Henderson, R., Schwab, W.C., and Nelson, T., 2016, Decoupling processes and scales of shoreline morphodynamics: Marine Geology, v. 381, p. 42-53, https://doi.org/10.1016/j.margeo.2016.08.008.","productDescription":"12 p.","startPage":"42","endPage":"53","ipdsId":"IP-079791","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":470483,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.margeo.2016.08.008","text":"Publisher Index Page"},{"id":330495,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Fire Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.333333,\n 40.5\n ],\n [\n -73.333333,\n 40.666666\n ],\n [\n -72.666666,\n 40.666666\n ],\n [\n -72.666666,\n 40.5\n ],\n [\n -73.333333,\n 40.5\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"381","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5813125de4b0b5a0c12ab671","chorus":{"doi":"10.1016/j.margeo.2016.08.008","url":"http://dx.doi.org/10.1016/j.margeo.2016.08.008","publisher":"Elsevier BV","authors":"Hapke Cheryl J., Plant Nathaniel G., Henderson Rachel.E., Schwab William C., Nelson Timothy R.","journalName":"Marine Geology","publicationDate":"11/2016"},"contributors":{"authors":[{"text":"Hapke, Cheryl J. 0000-0002-2753-4075 chapke@usgs.gov","orcid":"https://orcid.org/0000-0002-2753-4075","contributorId":2981,"corporation":false,"usgs":true,"family":"Hapke","given":"Cheryl","email":"chapke@usgs.gov","middleInitial":"J.","affiliations":[{"id":6676,"text":"USGS (retired)","active":true,"usgs":false}],"preferred":true,"id":652274,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Plant, Nathaniel G. 0000-0002-5703-5672 nplant@usgs.gov","orcid":"https://orcid.org/0000-0002-5703-5672","contributorId":3503,"corporation":false,"usgs":true,"family":"Plant","given":"Nathaniel","email":"nplant@usgs.gov","middleInitial":"G.","affiliations":[{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":652275,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Henderson, Rachel E. 0000-0001-5810-7941 rhehre@usgs.gov","orcid":"https://orcid.org/0000-0001-5810-7941","contributorId":4934,"corporation":false,"usgs":true,"family":"Henderson","given":"Rachel E.","email":"rhehre@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":652276,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schwab, William C. 0000-0001-9274-5154 bschwab@usgs.gov","orcid":"https://orcid.org/0000-0001-9274-5154","contributorId":417,"corporation":false,"usgs":true,"family":"Schwab","given":"William","email":"bschwab@usgs.gov","middleInitial":"C.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":652277,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nelson, Timothy R. trnelson@usgs.gov","contributorId":176362,"corporation":false,"usgs":true,"family":"Nelson","given":"Timothy R. ","email":"trnelson@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":652278,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70188434,"text":"70188434 - 2016 - Seismic evidence of glacial-age river incision into the Tahaa barrier reef, French Polynesia","interactions":[],"lastModifiedDate":"2017-06-09T14:29:21","indexId":"70188434","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2667,"text":"Marine Geology","active":true,"publicationSubtype":{"id":10}},"title":"Seismic evidence of glacial-age river incision into the Tahaa barrier reef, French Polynesia","docAbstract":"Rivers have long been recognized for their ability to shape reef-bound volcanic islands. On the time-scale of glacial–interglacial sea-level cycles, fluvial incision of exposed barrier reef lagoons may compete with constructional coral growth to shape the coastal geomorphology of ocean islands. However, overprinting of Pleistocene landscapes by Holocene erosion or sedimentation has largely obscured the role lowstand river incision may have played in developing the deep lagoons typical of modern barrier reefs. Here we use high-resolution seismic imagery and core stratigraphy to examine how erosion and/or deposition by upland drainage networks has shaped coastal morphology on Tahaa, a barrier reef-bound island located along the Society Islands hotspot chain in French Polynesia. At Tahaa, we find that many channels, incised into the lagoon floor during Pleistocene sea-level lowstands, are located near the mouths of upstream terrestrial drainages. Steeper antecedent topography appears to have enhanced lowstand fluvial erosion along Tahaa's southwestern coast and maintained a deep pass. During highstands, upland drainages appear to contribute little sediment to refilling accommodation space in the lagoon. Rather, the flushing of fine carbonate sediment out of incised fluvial channels by storms and currents appears to have limited lagoonal infilling and further reinforced development of deep barrier reef lagoons during periods of highstand submersion.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.margeo.2016.04.008","usgsCitation":"Toomey, M., Woodruff, J.D., Ashton, A.D., and Perron, J.T., 2016, Seismic evidence of glacial-age river incision into the Tahaa barrier reef, French Polynesia: Marine Geology, v. 380, p. 284-289, https://doi.org/10.1016/j.margeo.2016.04.008.","productDescription":"6 p.","startPage":"284","endPage":"289","ipdsId":"IP-070030","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":470539,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1016/j.margeo.2016.04.008","text":"External Repository"},{"id":342343,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"French Polynesia","otherGeospatial":"Tahaa barrier reef","volume":"380","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"593bb39fe4b0764e6c60e7b0","contributors":{"authors":[{"text":"Toomey, Michael 0000-0003-0167-9273 mtoomey@usgs.gov","orcid":"https://orcid.org/0000-0003-0167-9273","contributorId":184097,"corporation":false,"usgs":true,"family":"Toomey","given":"Michael","email":"mtoomey@usgs.gov","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":697719,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Woodruff, Jonathan D.","contributorId":192777,"corporation":false,"usgs":false,"family":"Woodruff","given":"Jonathan","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":697720,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ashton, Andrew D.","contributorId":96970,"corporation":false,"usgs":true,"family":"Ashton","given":"Andrew","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":697721,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Perron, J. Taylor","contributorId":184100,"corporation":false,"usgs":false,"family":"Perron","given":"J.","email":"","middleInitial":"Taylor","affiliations":[],"preferred":false,"id":697722,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70175734,"text":"70175734 - 2016 - Analysis of hydrologic and geochemical time-series data at James Cave, Virginia: Implications for epikarst influence on recharge in Appalachian karst aquifers","interactions":[],"lastModifiedDate":"2016-08-31T11:05:08","indexId":"70175734","displayToPublicDate":"2016-08-06T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5198,"text":"Geological Society of America Special Papers ","active":true,"publicationSubtype":{"id":10}},"title":"Analysis of hydrologic and geochemical time-series data at James Cave, Virginia: Implications for epikarst influence on recharge in Appalachian karst aquifers","docAbstract":"The epikarst, which consists of highly weathered rock in the upper vadose zone of exposed karst systems, plays a critical role in determining the hydrologic and geochemical characteristics of recharge to an underlying karst aquifer. This study utilized time series (2007–2014) of hydrologic and geochemical data of drip water collected within James Cave, Virginia, to examine the influence of epikarst on the quantity and quality of recharge in a mature, doline-dominated karst terrain. Results show a strong seasonality of both hydrology and geochemistry of recharge, which has implications for management of karst aquifers in temperate climatic zones. First, recharge (discharge from the epikarst to the underlying aquifer) reaches a maximum between late winter and early spring, with the onset of the recharge season ranging from as early as December to as late as March during the study period. The timing and duration of the recharge season were found to be a function of precipitation in excess of evapotranspiration on a seasonal time scale. Secondly, seasonally variable residence times for water in the epikarst influence rock-water interaction and, hence, the geochemical characteristics of recharge. Overall, results highlight the strong and complex influence that the epikarst has on karst recharge, which requires long-term and high-resolution data sets to accurately understand and quantify.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/2015.2516(15)","usgsCitation":"Eagle, S.D., Orndorff, W., Schwartz, B.F., Doctor, D.H., Gerst, J.D., and Schreiber, M.E., 2016, Analysis of hydrologic and geochemical time-series data at James Cave, Virginia: Implications for epikarst influence on recharge in Appalachian karst aquifers: Geological Society of America Special Papers , v. 516, p. 181-196, https://doi.org/10.1130/2015.2516(15).","productDescription":"16 p.","startPage":"181","endPage":"196","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061917","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":328105,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":326851,"type":{"id":15,"text":"Index Page"},"url":"https://specialpapers.gsapubs.org/content/516/181"}],"country":"United States","state":"Virginia","otherGeospatial":"James Cave","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.87654113769531,\n 37.11707372086296\n ],\n [\n -80.67260742187499,\n 37.2133783531779\n ],\n [\n -80.61698913574219,\n 37.228141500433615\n ],\n [\n -80.59776306152344,\n 37.18821967018367\n ],\n [\n -80.58609008789062,\n 37.18110808791507\n ],\n [\n -80.56755065917969,\n 37.19533058280065\n ],\n [\n -80.52291870117188,\n 37.209003532428646\n ],\n [\n -80.51673889160155,\n 37.19423663983283\n ],\n [\n -80.55450439453125,\n 37.1893137003281\n ],\n [\n -80.56480407714844,\n 37.17563718436526\n ],\n [\n -80.53047180175781,\n 37.14937133266766\n ],\n [\n -80.50575256347656,\n 37.073258333985585\n ],\n [\n -80.72067260742188,\n 36.95318415967938\n ],\n [\n -80.87654113769531,\n 37.11707372086296\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"516","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57c7ffaee4b0f2f0cebfc21c","contributors":{"authors":[{"text":"Eagle, Sarah D.","contributorId":150746,"corporation":false,"usgs":false,"family":"Eagle","given":"Sarah","email":"","middleInitial":"D.","affiliations":[{"id":18089,"text":"Virginia Tech, Dept. of Geosciences","active":true,"usgs":false}],"preferred":false,"id":646235,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Orndorff, William","contributorId":150745,"corporation":false,"usgs":false,"family":"Orndorff","given":"William","email":"","affiliations":[{"id":18088,"text":"Virginia Dept. of Conservation and Recreation","active":true,"usgs":false}],"preferred":false,"id":646236,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schwartz, Benjamin F.","contributorId":150744,"corporation":false,"usgs":false,"family":"Schwartz","given":"Benjamin","email":"","middleInitial":"F.","affiliations":[{"id":18087,"text":"Texas State University, San Marcos","active":true,"usgs":false}],"preferred":false,"id":646237,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Doctor, Daniel H. 0000-0002-8338-9722 dhdoctor@usgs.gov","orcid":"https://orcid.org/0000-0002-8338-9722","contributorId":2037,"corporation":false,"usgs":true,"family":"Doctor","given":"Daniel","email":"dhdoctor@usgs.gov","middleInitial":"H.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":646234,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gerst, Jonathan D.","contributorId":150747,"corporation":false,"usgs":false,"family":"Gerst","given":"Jonathan","email":"","middleInitial":"D.","affiliations":[{"id":18089,"text":"Virginia Tech, Dept. of Geosciences","active":true,"usgs":false}],"preferred":false,"id":646238,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schreiber, Madeline E.","contributorId":138959,"corporation":false,"usgs":false,"family":"Schreiber","given":"Madeline","email":"","middleInitial":"E.","affiliations":[{"id":12594,"text":"Department of Geosciences, Virginia Tech, Blacksburg, VA","active":true,"usgs":false}],"preferred":false,"id":646239,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70174888,"text":"ofr20161118 - 2016 - Near-field receiving water monitoring of trace metals and a benthic community near the Palo Alto Regional Water Quality Control Plant in south San Francisco Bay, California; 2015","interactions":[],"lastModifiedDate":"2023-04-24T20:59:51.652779","indexId":"ofr20161118","displayToPublicDate":"2016-07-22T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-1118","title":"Near-field receiving water monitoring of trace metals and a benthic community near the Palo Alto Regional Water Quality Control Plant in south San Francisco Bay, California; 2015","docAbstract":"Trace-metal concentrations in sediment and in the clam Macoma petalum (formerly reported as Macoma balthica), clam reproductive activity, and benthic macroinvertebrate community structure were investigated in a mudflat 1 kilometer south of the discharge of the Palo Alto Regional Water Quality Control Plant (PARWQCP) in South San Francisco Bay, California. This report includes data collected by U.S. Geological Survey (USGS) scientists for the period from January 2015 to December 2015. These data are appended to long-term datasets extending back to 1974, and serve as the basis for the City of Palo Alto’s Near-Field Receiving Water Monitoring Program, initiated in 1994.
\nFollowing significant reductions in the late 1980s, silver (Ag) and copper (Cu) concentrations in sediment and M. petalum appear to have stabilized. Data for other metals, including chromium (Cr), mercury (Hg), nickel (Ni), selenium (Se), and zinc (Zn), have been collected since 1994. Over this period, concentrations of these elements have remained relatively constant, aside from seasonal variation that is common to all elements. In 2015, concentrations of Ag and Cu in M. petalum varied seasonally in response to a combination of site-specific metal exposures and annual growth and reproduction, as reported previously. Seasonal patterns for other elements, including Cr, Ni, Zn, Hg, and Se, were generally similar in timing and magnitude as those for Ag and Cu. In M. petalum, all observed elements showed annual maxima in January–February and minima in April, except for Zn, which was lowest in December. In sediments, annual maxima also occurred in January–February, and minima were measured in June and September. In 2015, metal concentrations in both sediments and clam tissue were among the lowest on record. This record suggests that regional-scale factors now largely control sedimentary and bioavailable concentrations of Ag and Cu, as well as other elements of regulatory interest, at the Palo Alto site.
\nAnalyses of the benthic community structure at the same mudflat over a 40-year period show that changes in the community have occurred concurrent with reduced concentrations of metals in the sediment and in the tissues of the biosentinel clam, M. petalum, from the same area. Analysis of M. petalum shows increases in reproductive activity concurrent with the decline in metal concentrations in the tissues of this organism. Reproductive activity is presently stable (2015), with almost all animals initiating reproduction in the fall and spawning the following spring. The entire infaunal community has shifted from being dominated by several opportunistic species to a community where the species are more similar in abundance, a pattern that indicates a more stable community that is subjected to fewer stressors. In addition, two of the opportunistic species (Ampelisca abdita and Streblospio benedicti) that brood their young and live on the surface of the sediment in tubes have shown a continual decline in dominance coincident with the decline in metals; both species had short-lived rebounds in abundance in 2008, 2009, and 2010 and showed signs of increasing abundance in 2015. Heteromastus filiformis (a subsurface polychaete worm that lives in the sediment, consumes sediment and organic particles residing in the sediment, and reproduces by laying its eggs on or in the sediment) showed an increase in dominance, concurrent with the decrease in Ag and Cu concentrations, and in the last several years before 2008, showed a stable population. H. filiformis abundance increased slightly in 2011–2012 and returned to pre-2011 abundance in 2015. An unidentified disturbance occurred on the mudflat in early 2008 that resulted in the loss of the benthic animals, except for deep-dwelling animals like M. petalum. However, within two months of this event animals returned to the mudflat. The resilience of the community suggested that the disturbance was not due to a persistent toxin or to anoxia. The reproductive mode of most species present in 2015 is reflective of species that were available either as pelagic larvae or as mobile adults. Although oviparous (live-birth) species were lower in number in this group, the authors hypothesize that these species will return slowly as more species move back into the area. The use of functional ecology was highlighted in the 2015 benthic community data, which showed that the animals that have now returned to the mudflat are those that can respond successfully to a physical, nontoxic disturbance. Today, community data show a mix of species that consume the sediment, or filter feed, have pelagic larvae that must survive landing on the sediment, and those that brood their young. USGS scientists view the 2008 disturbance event as a response by the infaunal community to an episodic natural stressor (possibly sediment accretion or a pulse of freshwater), in contrast to the long-term recovery from metal contamination. We will compare this recovery to the long-term recovery observed after the 1970s when the decline in sediment pollutants was the dominating factor.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161118","collaboration":"Prepared in cooperation with the City of Palo Alto, California","usgsCitation":"Cain, D.J., Thompson, J.K., Crauder, Jeff, Parchaso, Francis, Stewart, Robin, Turner, Mathew, Hornberger, M.I., and Luoma, S.N., 2016, Near-field receiving water monitoring of trace metals and a benthic community near the Palo Alto Regional Water Quality Control Plant in south San Francisco Bay, California; 2015: U.S. Geological Survey Open-File Report 2016–1118, 78 p., https://dx.doi.org/10.3133/ofr20161118.","productDescription":"vii, 78 p.","numberOfPages":"87","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-076608","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":416191,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20231017","text":"Open-File Report 2023-1017","linkHelpText":"- Near-Field Receiving-Water Monitoring of Trace Metals and a Benthic Community Near the Palo Alto Regional Water Quality Control Plant in South San Francisco Bay, California—2020"},{"id":416190,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20211079","text":"Open-File Report 2021-1079","linkHelpText":"- Near-Field Receiving-Water Monitoring of Trace Metals and a Benthic Community Near the Palo Alto Regional Water Quality Control Plant in South San Francisco Bay, California—2019"},{"id":416189,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20191084","text":"Open-File Report 2019-1084","linkHelpText":"- Near-Field Receiving-Water Monitoring of Trace Metals and a Benthic Community Near the Palo Alto Regional Water Quality Control Plant in South San Francisco Bay, California—2018"},{"id":416188,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20181107","text":"Open-File Report 2018-1107","linkHelpText":"- Near-field receiving-water monitoring of trace metals and a benthic community near the Palo Alto Regional Water Quality Control Plant in south San Francisco Bay, California—2017"},{"id":416187,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20171135","text":"Open-File Report 2017-1135","linkHelpText":"- Near-field receiving water monitoring of trace metals and a benthic community near the Palo Alto Regional Water Quality Control Plant in south San Francisco Bay, California; 2016"},{"id":325514,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1118/coverthb.jpg"},{"id":325515,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1118/ofr20161118.pdf","text":"Report","size":"4.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1118"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.14530944824217,\n 37.40452830389465\n ],\n [\n -122.14530944824217,\n 37.52443079581378\n ],\n [\n -121.91871643066406,\n 37.52443079581378\n ],\n [\n -121.91871643066406,\n 37.40452830389465\n ],\n [\n -122.14530944824217,\n 37.40452830389465\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"NRP staff
National Research Program
U.S. Geological Survey
345 Middlefield Road, MS-435
Menlo Park, CA 94025
http://water.usgs.gov/nrp/
Most Atlantic hurricanes form in the Main Development Region between 9°N to 20°N along the northern edge of the Intertropical Convergence Zone (ITCZ). Previous research has suggested that meridional shifts in the ITCZ position on geologic timescales can modulate hurricane activity, but continuous and long-term storm records are needed from multiple sites to assess this hypothesis. Here we present a 3000 year record of intense hurricane strikes in the northern Bahamas (Abaco Island) based on overwash deposits in a coastal sinkhole, which indicates that the ITCZ has likely helped modulate intense hurricane strikes on the western North Atlantic margin on millennial to centennial-scales. The new reconstruction closely matches a previous reconstruction from Puerto Rico, and documents a period of elevated intense hurricane activity on the western North Atlantic margin from 2500 to 1000 years ago when paleo precipitation proxies suggest that the ITCZ occupied a more northern position. Considering that anthropogenic warming is predicted to be focused in the northern hemisphere in the coming century, these results provide a prehistoric analog that an attendant northern ITCZ shift in the future may again return the western North Atlantic margin to an active hurricane interval.
","language":"English","publisher":"Nature","doi":"10.1038/srep21728","usgsCitation":"van Hengstrum, P.J., Donnelly, J.P., Fall, P.L., Toomey, M., Albury, N.A., and Kakuk, B., 2016, The intertropical convergence zone modulates intense hurricane strikes on the western North Atlantic margin: Scientific Reports, v. 6, p. 1-10, https://doi.org/10.1038/srep21728.","productDescription":"Article number: 21728; 10 p.","startPage":"1","endPage":"10","ipdsId":"IP-068915","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":470802,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/srep21728","text":"Publisher Index Page"},{"id":342341,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-02-24","publicationStatus":"PW","scienceBaseUri":"593bb3a2e4b0764e6c60e7bd","contributors":{"authors":[{"text":"van Hengstrum, Peter J.","contributorId":192782,"corporation":false,"usgs":false,"family":"van Hengstrum","given":"Peter","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":697730,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Donnelly, Jeffrey P.","contributorId":192783,"corporation":false,"usgs":false,"family":"Donnelly","given":"Jeffrey","email":"","middleInitial":"P.","affiliations":[{"id":6706,"text":"Woods Hole Oceanographic Institution,","active":true,"usgs":false}],"preferred":false,"id":697731,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fall, Patricia L.","contributorId":192784,"corporation":false,"usgs":false,"family":"Fall","given":"Patricia","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":697732,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Toomey, Michael 0000-0003-0167-9273 mtoomey@usgs.gov","orcid":"https://orcid.org/0000-0003-0167-9273","contributorId":184097,"corporation":false,"usgs":true,"family":"Toomey","given":"Michael","email":"mtoomey@usgs.gov","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":697729,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Albury, Nancy A.","contributorId":192785,"corporation":false,"usgs":false,"family":"Albury","given":"Nancy","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":697733,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kakuk, Brian","contributorId":192786,"corporation":false,"usgs":false,"family":"Kakuk","given":"Brian","email":"","affiliations":[],"preferred":false,"id":697734,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70174420,"text":"70174420 - 2016 - Morphodynamics of prograding beaches: A synthesis of seasonal- to century-scale observations of the Columbia River littoral cell","interactions":[],"lastModifiedDate":"2016-07-12T12:46:37","indexId":"70174420","displayToPublicDate":"2016-06-01T02:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2667,"text":"Marine Geology","active":true,"publicationSubtype":{"id":10}},"title":"Morphodynamics of prograding beaches: A synthesis of seasonal- to century-scale observations of the Columbia River littoral cell","docAbstract":"Findings from nearly two decades of research focused on the Columbia River littoral cell (CRLC), a set of rapidly prograding coastal barriers and strand-plains in the U.S. Pacific Northwest, are synthesized to investigate the morphodynamics associated with prograding beaches. Due to a large sediment supply from the Columbia River, the CRLC is the only extensive stretch of shoreline on the U.S. west coast to have advanced significantly seaward during the late Holocene. Since the last Cascadia Subduction Zone (CSZ) earthquake in 1700, with associated co-seismic subsidence and tsunami, much of the CRLC has prograded hundreds of meters. However, the rates of progradation, and the processes most responsible for sediment accumulation, vary depending on time scale and the morphological unit in question. Remarkably, the 20th and early 21st century shoreline change rates were more than double the late prehistoric rates that include recovery from the last major CSZ event, most likely due to an increase in sediment supply resulting from inlet jetty construction. In some locations detailed beach morphology monitoring reveals that at interannual- to decadal-scale the upper shoreface aggraded about 2 cm/yr, subtidal sandbars migrated offshore and decayed while intertidal bars migrated onshore and welded to the shoreline, the shoreline prograded about 4 m/yr, and 1 to 2 new foredune ridges were generated. A detailed meso-scale sediment budget analysis in one location within the littoral cell shows that approximately 100 m3/m/yr accumulated between − 12 m (seaward limit of data) and + 9 m (crest of landward-most foredune). Gradients in alongshore sediment transport, net onshore-directed cross-shore sediment transport within the surf zone, and cross-shore feeding from a shoreface out of equilibrium with forcing conditions are each partially responsible for the significant rates of sediment supplied to the beaches and dunes of the CRLC during the observational period. Direct observations of beach progradation at seasonal- to decadal-scale are put in context of measured or inferred changes over time scales of decades to centuries.
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2016 - Temporal trends and stationarity in annual peak flow and peak-flow timing for selected long-term streamflow-gaging stations in or near Montana through water year 2011: Chapter B in Montana StreamStats","interactions":[{"subject":{"id":70163006,"text":"sir20155019B - 2016 - Temporal trends and stationarity in annual peak flow and peak-flow timing for selected long-term streamflow-gaging stations in or near Montana through water year 2011: Chapter B in Montana StreamStats","indexId":"sir20155019B","publicationYear":"2016","noYear":false,"chapter":"B","title":"Temporal trends and stationarity in annual peak flow and peak-flow timing for selected long-term streamflow-gaging stations in or near Montana through water year 2011: Chapter B in Montana StreamStats"},"predicate":"IS_PART_OF","object":{"id":70169997,"text":"sir20155019 - 2016 - Montana StreamStats","indexId":"sir20155019","publicationYear":"2016","noYear":false,"title":"Montana StreamStats"},"id":1}],"isPartOf":{"id":70169997,"text":"sir20155019 - 2016 - Montana StreamStats","indexId":"sir20155019","publicationYear":"2016","noYear":false,"title":"Montana StreamStats"},"lastModifiedDate":"2018-02-28T16:38:07","indexId":"sir20155019B","displayToPublicDate":"2016-04-05T00:00:00","publicationYear":"2016","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":"2015-5019","chapter":"B","title":"Temporal trends and stationarity in annual peak flow and peak-flow timing for selected long-term streamflow-gaging stations in or near Montana through water year 2011: Chapter B in Montana StreamStats","docAbstract":"
A large-scale study by the U.S. Geological Survey, in cooperation with the Montana Department of Transportation and the Montana Department of Natural Resources and Conservation, was done to investigate general patterns in peak-flow temporal trends and stationarity through water year 2011 for 24 long-term streamflow-gaging stations (hereinafter referred to as gaging stations) in Montana. Hereinafter, all years refer to water years; a water year is the 12-month period from October 1 through September 30 and is designated by the year in which it ends. The primary focus of the study was to identify general patterns in peak-flow temporal trends and stationarity that are relevant to application of peak-flow frequency analyses within a statewide gaging-station network.
\nTemporal trends were analyzed for two hydrologic variables: annual peak flow and peak-flow timing. Annual peak flow is the maximum instantaneous discharge, in cubic feet per second, recorded each year a gaging station was operated. Peak-flow timing is the day of the annual peak flow (hereinafter referred to as day of peak), recorded each year a gaging station was operated.
\nStudy results provide evidence that annual peak flow for most of the long-term gaging stations can be reasonably considered as stationary for application of peak-flow frequency analyses within a statewide gaging station network. Upward trends in annual peak flow during 1930–76 generally were stronger than downward trends during 1967–2011 for most long-term gaging stations. Statistical distributions of annual peak flow generally were similar among three summary time periods (1930–78, 1979–2011, and the entire period of record). However, for two low-elevation gaging stations in eastern Montana (Poplar River at international boundary [gaging station 06178000] and Powder River at Moorhead, Montana [gaging station 06324500]), substantial downward trends in annual peak flow during 1967–2011 were of similar or stronger magnitude than the upward trends during 1930–76, and the annual-peak-flow medians for 1979–2011 were substantially lower than the medians for the entire period of record.
\nFor peak-flow timing for most long-term gaging stations, differences in trends between 1930–76 and 1967–2011 are variable and not particularly strong. Statistical distributions generally are similar among the summary time periods. However, for two high-elevation gaging stations on a Missouri River headwater tributary (Gallatin River near Gallatin Gateway, Montana [gaging station 06043500] and Gallatin River at Logan, Montana [gaging station 06052500]) and for five high-elevation gaging stations in the Yellowstone River Basin (Yellowstone River at Corwin Springs, Montana [gaging station 06191500], Yellowstone River near Livingston, Montana [gaging station 06192500], Clarks Fork Yellowstone River near Belfry, Montana [gaging station 06207500], Clarks Fork Yellowstone River at Edgar, Montana [gaging station 06208500], and Yellowstone River at Billings, Montana [gaging station 06214500]) downward trends in peak-flow timing during 1967–2011 generally were stronger than upward trends during 1930–1976, and day-of-peak medians for 1979–2011 were considerably less than medians for 1930–78. The downward trends in peak-flow timing for 1967–2011 indicate that the timing of annual peak flows changed from later in the year to earlier in the year. For the seven high-elevation gaging stations, the mean change during 1967–2011 was about 13 days (range of 8 to 22 days).
\nFor most of the high-elevation gaging stations in the Missouri River headwaters, Yellowstone River Basin, and Columbia River Basin, there was general correspondence between trend patterns for annual peak flow and trend patterns for peak-flow timing; that is, during periods when there were upward trends in annual peak flow, there generally also were upward trends in peak-flow timing. Conversely, during periods when there were downward trends in annual peak flow, there generally also were downward trends in peak-flow timing.
\nThe two low-elevation gaging stations in eastern Montana (Poplar River at international boundary [gaging station 06178000] and Powder River at Moorhead, Montana [gaging station 06324500]) had considerable changes in annual-peakflow characteristics after the mid-1970s, which might provide evidence of potential nonstationarity in the peak-flow records. The two low-elevation gaging stations that have potential nonstationarity are located in drainage basins that are strongly affected by agricultural activities that potentially affect the hydrologic regimes. Primary agricultural activities that might alter natural hydrologic conditions include construction of small impoundments (primarily for stock-watering purposes) and irrigation diversions. Temporal variability in these activities might contribute to the potential nonstationarity issues. Changes in climatic characteristics after the mid-1970s also possibly contribute to the potential nonstationarity issues. Lack of considerable indication of potential nonstationarity in annual peak flow for the other long-term gaging stations in this study might indicate that climatic changes have been more pronounced with respect to effects on peak flows in low elevation areas in eastern Montana than in areas represented by the other long-term gaging stations. Another possibility is that climatic changes after the mid-1970s are exacerbated in low-elevation areas where small-impoundment development and potential effects of irrigation diversions might be more extensive.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Montana StreamStats (Scientific Investigations Report 2015-5019)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155019B","collaboration":"Prepared in cooperation with the Montana Department of Transportation and Montana Department of Natural Resources and Conservation","usgsCitation":"Sando, S.K., McCarthy, P.M., Sando, Roy, and Dutton, D.M., 2016, Temporal trends and stationarity in annual peak flow and peak-flow timing for selected long-term streamflow-gaging stations in or near Montana through water year 2011: U.S. Geological Survey Scientific Investigations Report 2015–5019–B, 48 p., https://dx.doi.org/10.3133/sir20155019B.","productDescription":"vi, 48 p.","numberOfPages":"58","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-060698","costCenters":[{"id":5050,"text":"WY-MT Water Science 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\"}}]}","contact":"Director, Wyoming-Montana Water Science Center
U.S. Geological Survey
3162 Bozeman Ave
Helena, MT 59601
Erosion following a wildfire is much greater than background erosion in forests because of wildfire-induced changes to soil erodibility and water infiltration. While many previous studies have documented post-wildfire erosion with point and small plot-scale measurements, the spatial distribution of post-fire erosion patterns at the watershed scale remains largely unexplored. In this study lidar surveys were collected periodically in a small, first-order drainage basin over a period of 2 years following a wildfire. The study site was relatively steep with slopes ranging from 17° to > 30°. During the study period, several different types of rain storms occurred on the site including low-intensity frontal storms (2.4 mm h−1) and high-intensity convective thunderstorms (79 mm h−1). These storms were the dominant drivers of erosion. Erosion resulting from dry ravel and debris flows was notably absent at the site. Successive lidar surveys were subtracted from one another to obtain digital maps of topographic change between surveys. The results show an evolution in geomorphic response, such that the erosional response after rain storms was strongly influenced by the previous erosional events and pre-fire site morphology. Hillslope and channel roughness increased over time, and the watershed armored as coarse cobbles and boulders were exposed. The erosional response was spatially nonuniform; shallow erosion from hillslopes (87% of the study area) contributed 3 times more sediment volume than erosion from convergent areas (13% of the study area). However, the total normalized erosion depth (volume/area) was highest in convergent areas. From a detailed understanding of the spatial locations of erosion, we made inferences regarding the processes driving erosion. It appears that hillslope erosion is controlled by rain splash (for detachment) and overland flow (for transport and quasi-channelized erosion), with the sites of highest erosion corresponding to locations with the lowest roughness. By contrast, in convergent areas we found erosion caused by overland flow. Soil erosion was locally interrupted by immobile objects such as boulders, bedrock, or tree trunks, resulting in a patchy erosion network with increasing roughness over time.
","language":"English","publisher":"American Geophysical Union","publisherLocation":"Richmond, VA","doi":"10.1002/2015JF003600","usgsCitation":"Rengers, F.K., Tucker, G., Moody, J., and Ebel, B., 2016, Illuminating wildfire erosion and deposition patterns with repeat terrestrial lidar: Journal of Geophysical Research F: Earth Surface, v. 121, no. 3, p. 588-608, https://doi.org/10.1002/2015JF003600.","productDescription":"21 p.","startPage":"588","endPage":"608","ipdsId":"IP-068620","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":471157,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015jf003600","text":"Publisher Index Page"},{"id":336854,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.403611,\n 40.030833\n ],\n [\n -105.402222,\n 40.030833\n ],\n [\n -105.402222,\n 40.032222\n ],\n [\n -105.403611,\n 40.032222\n ],\n [\n -105.403611,\n 40.030833\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"121","issue":"3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-11","publicationStatus":"PW","scienceBaseUri":"58be8339e4b014cc3a3a99e5","contributors":{"authors":[{"text":"Rengers, Francis K. 0000-0002-1825-0943 frengers@usgs.gov","orcid":"https://orcid.org/0000-0002-1825-0943","contributorId":150422,"corporation":false,"usgs":true,"family":"Rengers","given":"Francis","email":"frengers@usgs.gov","middleInitial":"K.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":680682,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tucker, G.E.","contributorId":150423,"corporation":false,"usgs":false,"family":"Tucker","given":"G.E.","email":"","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":680683,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moody, J. A.","contributorId":187515,"corporation":false,"usgs":false,"family":"Moody","given":"J. A.","affiliations":[],"preferred":false,"id":680684,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ebel, Brian","contributorId":187516,"corporation":false,"usgs":false,"family":"Ebel","given":"Brian","affiliations":[],"preferred":false,"id":680685,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70178683,"text":"70178683 - 2016 - Rock-avalanche dynamics revealed by large-scale field mapping and seismic signals at a highly mobile avalanche in the West Salt Creek valley, western Colorado","interactions":[],"lastModifiedDate":"2017-03-15T14:51:01","indexId":"70178683","displayToPublicDate":"2016-02-02T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"Rock-avalanche dynamics revealed by large-scale field mapping and seismic signals at a highly mobile avalanche in the West Salt Creek valley, western Colorado","docAbstract":"On 25 May 2014, a rain-on-snow–induced rock avalanche occurred in the West Salt Creek valley on the northern flank of Grand Mesa in western Colorado (United States). The avalanche mobilized from a preexisting rock slide in the Green River Formation and traveled 4.6 km down the confined valley, killing three people. The avalanche was rare for the contiguous United States because of its large size (54.5 Mm3) and high mobility (height/length = 0.14). To understand the avalanche failure sequence, mechanisms, and mobility, we conducted a forensic analysis using large-scale (1:1000) structural mapping and seismic data. We used high-resolution, unmanned aircraft system imagery as a base for field mapping, and analyzed seismic data from 22 broadband stations (distances < 656 km from the rock-slide source area) and one short-period network. We inverted broadband data to derive a time series of forces that the avalanche exerted on the earth and tracked these forces using curves in the avalanche path. Our results revealed that the rock avalanche was a cascade of landslide events, rather than a single massive failure. The sequence began with an early morning landslide/debris flow that started ∼10 h before the main avalanche. The main avalanche lasted ∼3.5 min and traveled at average velocities ranging from 15 to 36 m/s. For at least two hours after the avalanche ceased movement, a central, hummock-rich core continued to move slowly. Since 25 May 2014, numerous shallow landslides, rock slides, and rock falls have created new structures and modified avalanche topography. Mobility of the main avalanche and central core was likely enhanced by valley floor material that liquefied from undrained loading by the overriding avalanche. Although the base was likely at least partially liquefied, our mapping indicates that the overriding avalanche internally deformed predominantly by sliding along discrete shear surfaces in material that was nearly dry and had substantial frictional strength. These results indicate that the West Salt Creek avalanche, and probably other long-traveled avalanches, could be modeled as two layers: a thin, liquefied basal layer, and a thicker and stronger overriding layer.","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES01265.1","usgsCitation":"Coe, J.A., Baum, R.L., Allstadt, K.E., Kochevar, B., Schmitt, R.G., Morgan, M.L., White, J.L., Stratton, B.T., Hayashi, T.A., and Kean, J.W., 2016, Rock-avalanche dynamics revealed by large-scale field mapping and seismic signals at a highly mobile avalanche in the West Salt Creek valley, western Colorado: Geosphere, v. 12, no. 2, p. 607-631, https://doi.org/10.1130/GES01265.1.","productDescription":"25 p.","startPage":"607","endPage":"631","ipdsId":"IP-071133","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":471264,"rank":4,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges01265.1","text":"Publisher Index Page"},{"id":438639,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F74J0C55","text":"USGS data release","linkHelpText":"Map data and Unmanned Aircraft System imagery from the May 25, 2014 West Salt Creek rock avalanche in western Colorado"},{"id":331663,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":337654,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.1130/GES01265.1","text":"Rock-avalanche dynamics revealed by large-scale field mapping and seismic signals at a highly mobile avalanche in the West Salt Creek valley, western Colorado"}],"country":"United States","state":"Colorado","otherGeospatial":"West Salt Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n 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baum@usgs.gov","orcid":"https://orcid.org/0000-0001-5337-1970","contributorId":1288,"corporation":false,"usgs":true,"family":"Baum","given":"Rex","email":"baum@usgs.gov","middleInitial":"L.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":655186,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Allstadt, Kate E. 0000-0003-4977-5248 kallstadt@usgs.gov","orcid":"https://orcid.org/0000-0003-4977-5248","contributorId":167684,"corporation":false,"usgs":true,"family":"Allstadt","given":"Kate","email":"kallstadt@usgs.gov","middleInitial":"E.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":false,"id":655187,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kochevar, Bernard","contributorId":177145,"corporation":false,"usgs":false,"family":"Kochevar","given":"Bernard","email":"","affiliations":[],"preferred":false,"id":655188,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schmitt, Robert G. 0000-0001-8060-1954 rschmitt@usgs.gov","orcid":"https://orcid.org/0000-0001-8060-1954","contributorId":5611,"corporation":false,"usgs":true,"family":"Schmitt","given":"Robert","email":"rschmitt@usgs.gov","middleInitial":"G.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":655189,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Morgan, Matthew L.","contributorId":177280,"corporation":false,"usgs":false,"family":"Morgan","given":"Matthew","email":"","middleInitial":"L.","affiliations":[{"id":12745,"text":"Colorado Geological Survey","active":true,"usgs":false}],"preferred":false,"id":655190,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"White, Jonathan L.","contributorId":177281,"corporation":false,"usgs":false,"family":"White","given":"Jonathan","email":"","middleInitial":"L.","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":655191,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Stratton, Benjamin T.","contributorId":177282,"corporation":false,"usgs":false,"family":"Stratton","given":"Benjamin","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":655192,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hayashi, Timothy A.","contributorId":177283,"corporation":false,"usgs":false,"family":"Hayashi","given":"Timothy","email":"","middleInitial":"A.","affiliations":[{"id":27776,"text":"Mesa County Department of Public Works","active":true,"usgs":false}],"preferred":false,"id":655193,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Kean, Jason W. 0000-0003-3089-0369 jwkean@usgs.gov","orcid":"https://orcid.org/0000-0003-3089-0369","contributorId":1654,"corporation":false,"usgs":true,"family":"Kean","given":"Jason","email":"jwkean@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":655194,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70170615,"text":"70170615 - 2016 - Mercury in fish and macroinvertebrates from New York's streams and rivers: A compendium of data sources","interactions":[],"lastModifiedDate":"2017-04-21T10:39:00","indexId":"70170615","displayToPublicDate":"2016-02-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"seriesTitle":{"id":133,"text":"Report","active":false,"publicationSubtype":{"id":2}},"seriesNumber":"16-07","title":"Mercury in fish and macroinvertebrates from New York's streams and rivers: A compendium of data sources","docAbstract":"The U.S. Geological Survey has compiled a list of existing data sets, from selected sources, containing mercury (Hg) concentration data in fish and macroinvertebrate samples that were collected from flowing waters of New York State from 1970 through 2014. Data sets selected for inclusion in this report were limited to those that contain fish and (or) macroinvertebrate data that were collected across broad areas, cover relatively long time periods, and (or) were collected as part of a broader-scale (e.g. national) study or program. In addition, all data sets listed were collected, processed, and analyzed with documented methods, and contain critical sample information (e.g. fish species, fish size, Hg species) that is needed to analyze and interpret the reported Hg concentration data. Fourteen data sets, all from state or federal agencies, are listed in this report, along with selected descriptive information regarding each data source and data set contents. Together, these 14 data sets contain Hg and related data for more than\r\n7,000 biological samples collected from more than 700 unique stream and river locations between 1970 and 2014.","language":"English","publisher":"New York State Energy Research and Development Authority","usgsCitation":"Riva-Murray, K., and Burns, D.A., 2016, Mercury in fish and macroinvertebrates from New York's streams and rivers: A compendium of data sources: Report 16-07, v, 16 p.","productDescription":"v, 16 p.","numberOfPages":"26","ipdsId":"IP-059881","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":340076,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":340075,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://nyserda.ny.gov/publications"}],"country":"United States","state":"New 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,{"id":70161859,"text":"sir20155133 - 2016 - Application of a Weighted Regression Model for Reporting Nutrient and Sediment Concentrations, Fluxes, and Trends in Concentration and Flux for the Chesapeake Bay Nontidal Water-Quality Monitoring Network, Results Through Water Year 2012","interactions":[],"lastModifiedDate":"2021-07-02T13:50:02.84497","indexId":"sir20155133","displayToPublicDate":"2016-01-13T11:15:00","publicationYear":"2016","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":"2015-5133","title":"Application of a Weighted Regression Model for Reporting Nutrient and Sediment Concentrations, Fluxes, and Trends in Concentration and Flux for the Chesapeake Bay Nontidal Water-Quality Monitoring Network, Results Through Water Year 2012","docAbstract":"In the Chesapeake Bay watershed, estimated fluxes of nutrients and sediment from the bay’s nontidal tributaries into the estuary are the foundation of decision making to meet reductions prescribed by the Chesapeake Bay Total Maximum Daily Load (TMDL) and are often the basis for refining scientific understanding of the watershed-scale processes that influence the delivery of these constituents to the bay. Two regression-based flux and trend estimation models, ESTIMATOR and Weighted Regressions on Time, Discharge, and Season (WRTDS), were compared using data from 80 watersheds in the Chesapeake Bay Nontidal Water-Quality Monitoring Network (CBNTN). The watersheds range in size from 62 to 70,189 square kilometers and record lengths range from 6 to 28 years. ESTIMATOR is a constant-parameter model that estimates trends only in concentration; WRTDS uses variable parameters estimated with weighted regression, and estimates trends in both concentration and flux. WRTDS had greater explanatory power than ESTIMATOR, with the greatest degree of improvement evident for records longer than 25 years (30 stations; improvement in median model R2= 0.06 for total nitrogen, 0.08 for total phosphorus, and 0.05 for sediment) and the least degree of improvement for records of less than 10 years, for which the two models performed nearly equally. Flux bias statistics were comparable or lower (more favorable) for WRTDS for any record length; for 30 stations with records longer than 25 years, the greatest degree of improvement was evident for sediment (decrease of 0.17 in median statistic) and total phosphorus (decrease of 0.05). The overall between-station pattern in concentration trend direction and magnitude for all constituents was roughly similar for both models. A detailed case study revealed that trends in concentration estimated by WRTDS can operationally be viewed as a less-constrained equivalent to trends in concentration estimated by ESTIMATOR. Estimates of annual mean flow-adjusted (ESTIMATOR) and flow-normalized (WRTDS) concentration for years initially constituting the end of a water-quality record showed a similar degree of variability as data for additional years were incrementally added and the initial estimates “aged.” On the basis of the results of this broad comparison of the two models, the U.S. Geological Survey is adopting WRTDS as the primary model for estimating constituent fluxes and trends throughout the CBNTN. Nutrient and sediment flux and trend estimates, based on WRTDS, are summarized narratively and tabulated in appendixes for all stations for which fluxes or trends were reported through water year 2012.
\nWRTDS also was used to explore the sensitivity of flux and trend estimates to three data-quality issues common in many large-scale monitoring networks and evident in some of the CBNTN records. The potential effects of inconsistency in annual sampling effort and inconsistency in storm sampling effort were explored by way of a subsampling experiment using eight of the most densely sampled long-term (1985–2012) stations in the CBNTN as baseline datasets. From each dataset, a set of 10 “design guideline” subsamples was selected, consisting of 12 monthly samples and 8 targeted storm samples per year. The selection was conducted in a manner that preserved the overall intensity of storm sampling in the baseline data. These 10 subsamples were further manipulated to create “heterogeneous” subsamples by removing storm samples prior to 2003. The maximum relative difference between flow-normalized flux estimated in a single year from any of the 10 design guideline subsamples and values estimated in the corresponding year from baseline data was smallest for dissolved inorganic nitrogen (median of 8 stations = 6 percent of baseline estimate), but more appreciable for total phosphorus and sediment (medians of 22 and 32 percent, respectively). The maximum relative difference between flow-normalized flux estimated from from the 10 heterogeneous subsamples and values estimated in the corresponding year from baseline data was more pronounced, with medians for 8 stations of 15, 30, and 53 percent of the corresponding baseline estimates for dissolved inorganic nitrogen, total phosphorus, and sediment, respectively. The worst-case maximum relative differences between flow-normalize flux estimated in a single year from the 10 heterogeneous subsamples and values estimated in the corresponding year from baseline data were 25 percent for dissolved inorganic nitrogen, 37 percent for total phosphorus, and 250 percent for sediment. The results for the heterogeneous subsamples indicate that changes in storm sampling frequency can result in appreciable distortion of estimated trends in flow-normalized flux, especially for total phosphorus and sediment. Trend lines estimated from heterogeneous subsamples tended to converge with the trend lines estimated from baseline data after 2003. In contrast, 2003–12 trends based on subsamples truncated by discarding all data prior to the induced heterogeneity in 2003 showed appreciable biases and differences in slope, relative to the corresponding 2003–12 segment of the trend computed from the design guideline subsamples. Overall, the results indicate that for particulate constituents, load and trend estimates computed using long-term records recently converted to CBNTN design guideline sampling protocols will be most reliable if the trend is computed using the entire record, but reported only for the period that design guideline sampling protocols were followed.
\nInconsistencies related to changing laboratory methods were also examined via two manipulative experiments. In the first experiment, increasing and decreasing “stair-step” patterns of changes in censoring level, overall representing a factor-of-five change in the laboratory reporting limit, were artificially imposed on a 27-year record with no censoring and a period-of-record concentration trend of –68.4 percent. Trends estimated on the basis of the manipulated records were broadly similar to the original trend (–63.6 percent for decreasing censoring levels and –70.3 percent for increasing censoring levels), lending a degree of confidence that the survival regression routines upon which WRTDS is based are generally robust to data censoring. The second experiment considered an abrupt disappearance of low-concentration observations of total phosphorus, associated with a laboratory method change and not reflected through censoring, near the middle of a 28-year record. By process of elimination, an upward shift in the estimated flow-normalize concentration trend line around the same time was identified as a likely artifact resulting from the laboratory method change, although a contemporaneous change in watershed processes cannot be ruled out. Decisions as to how to treat records with potential sampling protocol or laboratory methods-related artifacts should be made on a case-by-case basis, and trend results should be appropriately qualified.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155133","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency Chesapeake Bay Program","usgsCitation":"Chanat, J.G., Moyer, D.L., Blomquist, J.D., Hyer, K.E., and Langland, M.J., 2016, Application of a weighted regression model for reporting nutrient and sediment concentrations, fluxes, and trends in concentration and flux for the Chesapeake Bay Nontidal Water-Quality Monitoring Network, results through water year 2012: U.S. Geological Survey Scientific Investigations Report 2015–5133, 76 p., https://dx.doi.org/10.3133/sir20155133.","productDescription":"Report: viii, 74 p.; 5 Appendixes","numberOfPages":"88","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-063310","costCenters":[{"id":614,"text":"Virginia Water Science 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3","size":"452 KB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2015-5133","linkHelpText":"Table 1 - Annual Results"},{"id":314015,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5133/pdf/sir20155133_app3_intro.pdf","text":"Appendix 3","size":"421 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5133","linkHelpText":"Introduction (Table 1 and 2)"},{"id":314014,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5133/pdf/sir20155133_appendix2.pdf","text":"Appendix 2","size":"211 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5133"},{"id":314013,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5133/pdf/sir20155133_appendix1.pdf","text":"Appendix 1","size":"523 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 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U.S. Geological Survey
1730 East Parham Road
Richmond, VA 23228
http://va.water.usgs.gov/
The ONSR is a karst park, containing many springs and caves. The “jewels” of the park are large springs, several of first magnitude, that contribute significantly to the flow and water quality of the Current River and its tributaries. Completion of 1:24,000-scale geologic mapping of the park and surrounding river basin, along with synthesis of published hydrologic data, allows us to examine the spatial relationships between the springs and the geologic framework to develop a conceptual model for genesis of these springs. Based on their similarity to mapped spring conduits, many of the caves in the ONSR are fossil conduit segments. Therefore, geologic control on the evolution of the springs also applies to speleogenesis in this part of the southern Missouri Ozarks.
Large springs occur in the ONSR area because: (1) the Ozark aquifer, from which they rise, is chiefly dolomite affected by solution via various processes over a long time period, (2) Paleozoic hypogenic fluid migration through these rocks exploited and enhanced flow-paths, (3) a consistent and low regional dip of the rocks off of the Salem Plateau (less than 2° to the southeast) allows integration of flow into large groundwater basins with a few discreet outlets, (4) the springs are located where the rivers have cut down into structural highs, allowing access to water from stratigraphic units deeper in the aquifer thus allowing development of springsheds that have volumetrically larger storage than smaller springs higher in the section, and (5) quartz sandstone and bedded chert in the carbonate stratigraphic succession that are locally to regionally continuous, serve as aquitards that locally confine groundwater up dip of the springs creating artesian conditions. This subhorizontal partitioning of the Ozark aquifer allows contributing areas for different springs to overlap, as evidenced by dye traces that cross adjacent groundwater basin boundaries, and possibly contributes to alternate flow routes under different groundwater flow regimes.
A better understanding of the 3-dimensional hydrogeologic framework for the large spring systems in the ONSR allows more precise mapping of the contributing areas for those springs, will guide future studies of groundwater flow paths, and inform development of groundwater resource management strategies for the park.
","largerWorkType":{"id":24,"text":"Conference Paper"},"conferenceTitle":"GSA Annual Meeting","conferenceDate":"2016","conferenceLocation":"Denver, CO ","language":"English","publisher":"Geological Society of America ","doi":"10.1130/abs/2016AM-282679","usgsCitation":"Weary, D.J., and Orndorff, R.C., 2016, Geologic context of large karst springs and caves in the Ozark National Scenic Riverways, Missouri, GSA Annual Meeting, Denver, CO , 2016, https://doi.org/10.1130/abs/2016AM-282679.","ipdsId":"IP-082624","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":336268,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58b548c1e4b01ccd54fddfbe","contributors":{"authors":[{"text":"Weary, David J. 0000-0002-6115-6397 dweary@usgs.gov","orcid":"https://orcid.org/0000-0002-6115-6397","contributorId":545,"corporation":false,"usgs":true,"family":"Weary","given":"David","email":"dweary@usgs.gov","middleInitial":"J.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":671702,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Orndorff, Randall C. 0000-0002-8956-5803 rorndorf@usgs.gov","orcid":"https://orcid.org/0000-0002-8956-5803","contributorId":2739,"corporation":false,"usgs":true,"family":"Orndorff","given":"Randall","email":"rorndorf@usgs.gov","middleInitial":"C.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":501,"text":"Office of Science Quality and Integrity","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":671703,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70159783,"text":"70159783 - 2016 - Effect of antecedent-hydrological conditions on rainfall triggering of debris flows in ash-fall pyroclastic mantled slopes of Campania (southern Italy)","interactions":[],"lastModifiedDate":"2016-09-28T16:29:53","indexId":"70159783","displayToPublicDate":"2015-11-23T10:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2604,"text":"Landslides","active":true,"publicationSubtype":{"id":10}},"title":"Effect of antecedent-hydrological conditions on rainfall triggering of debris flows in ash-fall pyroclastic mantled slopes of Campania (southern Italy)","docAbstract":"Mountainous areas surrounding the Campanian Plain and the Somma-Vesuvius volcano (southern Italy) are among the most risky areas of Italy due to the repeated occurrence of rainfallinduced debris flows along ash-fall pyroclastic soil-mantled slopes. In this geomorphological framework, rainfall patterns, hydrological processes taking place within multi-layered ash-fall pyroclastic deposits and soil antecedent moisture status are the principal factors to be taken into account to assess triggering rainfall conditions and the related hazard. This paper presents the outcomes of an experimental study based on integrated analyses consisting of the reconstruction of physical models of landslides, in situ hydrological monitoring, and hydrological and slope stability modeling, carried out on four representative source areas of debris flows that occurred in May 1998 in the Sarno Mountain Range. The hydrological monitoring was carried out during 2011 using nests of tensiometers and Watermark pressure head sensors and also through a rainfall and air temperature recording station. Time series of measured pressure head were used to calibrate a hydrological numerical model of the pyroclastic soil mantle for 2011, which was re-run for a 12-year period beginning in 2000, given the availability of rainfall and air temperature monitoring data. Such an approach allowed us to reconstruct the regime of pressure head at a daily time scale for a long period, which is representative of about 11 hydrologic years with different meteorological conditions. Based on this simulated time series, average winter and summer hydrological conditions were chosen to carry out hydrological and stability modeling of sample slopes and to identify Intensity- Duration rainfall thresholds by a deterministic approach. Among principal results, the opposing winter and summer antecedent pressure head (soil moisture) conditions were found to exert a significant control on intensity and duration of rainfall triggering events. Going from winter to summer conditions requires a strong increase of intensity and/or duration to induce landslides. The results identify an approach to account for different hazard conditions related to seasonality of hydrological processes inside the ash-fall pyroclastic soil mantle. Moreover, they highlight another important factor of uncertainty that potentially affects rainfall thresholds triggering shallow landslides reconstructed by empirical approaches.
","language":"English","publisher":"Springer","doi":"10.1007/s10346-015-0647-5","usgsCitation":"Napolitano, E., Fusco, F., Baum, R.L., Godt, J.W., and De Vita, P., 2016, Effect of antecedent-hydrological conditions on rainfall triggering of debris flows in ash-fall pyroclastic mantled slopes of Campania (southern Italy): Landslides, v. 13, no. 5, p. 967-983, https://doi.org/10.1007/s10346-015-0647-5.","productDescription":"17 p.","startPage":"967","endPage":"983","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070130","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":311642,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Italy","state":"Campania","otherGeospatial":"Sarno Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 14.616279602050781,\n 40.84550208206526\n ],\n [\n 14.616279602050781,\n 40.89950086329285\n ],\n [\n 14.684257507324219,\n 40.89950086329285\n ],\n [\n 14.684257507324219,\n 40.84550208206526\n ],\n [\n 14.616279602050781,\n 40.84550208206526\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"13","issue":"5","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-11-18","publicationStatus":"PW","scienceBaseUri":"565438a8e4b071e7ea53d490","contributors":{"authors":[{"text":"Napolitano, E.","contributorId":97401,"corporation":false,"usgs":true,"family":"Napolitano","given":"E.","email":"","affiliations":[],"preferred":false,"id":580432,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fusco, F","contributorId":150020,"corporation":false,"usgs":false,"family":"Fusco","given":"F","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":580433,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Baum, Rex L. 0000-0001-5337-1970 baum@usgs.gov","orcid":"https://orcid.org/0000-0001-5337-1970","contributorId":1288,"corporation":false,"usgs":true,"family":"Baum","given":"Rex","email":"baum@usgs.gov","middleInitial":"L.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":580434,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Godt, Jonathan W. 0000-0002-8737-2493 jgodt@usgs.gov","orcid":"https://orcid.org/0000-0002-8737-2493","contributorId":1166,"corporation":false,"usgs":true,"family":"Godt","given":"Jonathan","email":"jgodt@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true}],"preferred":true,"id":580435,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"De Vita, P.","contributorId":26207,"corporation":false,"usgs":true,"family":"De Vita","given":"P.","affiliations":[],"preferred":false,"id":580436,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70005430,"text":"sir20115136 - 2016 - Determination of dilution factors for discharge of aluminum-containing wastes by public water-supply treatment facilities into lakes and reservoirs in Massachusetts","interactions":[],"lastModifiedDate":"2017-03-03T15:28:13","indexId":"sir20115136","displayToPublicDate":"2011-09-16T00:00:00","publicationYear":"2016","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":"2011-5136","title":"Determination of dilution factors for discharge of aluminum-containing wastes by public water-supply treatment facilities into lakes and reservoirs in Massachusetts","docAbstract":"Dilution of aluminum discharged to reservoirs in filter-backwash effluents at water-treatment facilities in Massachusetts was investigated by a field study and computer simulation. Determination of dilution is needed so that permits for discharge ensure compliance with water-quality standards for aquatic life. The U.S. Environmental Protection Agency chronic standard for aluminum, 87 micrograms per liter (μg/L), rather than the acute standard, 750 μg/L, was used in this investigation because the time scales of chronic exposure (days) more nearly match rates of change in reservoir concentrations than do the time scales of acute exposure (hours).
Whereas dilution factors are routinely computed for effluents discharged to streams solely on the basis of flow of the effluent and flow of the receiving stream, dilution determination for effluents discharged to reservoirs is more complex because (1), compared to streams, additional water is available for dilution in reservoirs during low flows as a result of reservoir flushing and storage during higher flows, and (2) aluminum removal in reservoirs occurs by aluminum sedimentation during the residence time of water in the reservoir. Possible resuspension of settled aluminum was not considered in this investigation. An additional concern for setting discharge standards is the substantial concentration of aluminum that can be naturally present in ambient surface waters, usually in association with dissolved organic carbon (DOC), which can bind aluminum and keep it in solution.
A method for dilution determination was developed using a mass-balance equation for aluminum and considering sources of aluminum from groundwater, surface water, and filter-backwash effluents and losses caused by sedimentation, water withdrawal, and spill discharge from the reservoir. The method was applied to 13 reservoirs. Data on aluminum and DOC concentrations in reservoirs and influent water were collected during the fall of 2009. Complete reservoir volume was determined to be available for mixing on the basis of vertical and horizontal aluminum-concentration profiling. Losses caused by settling of aluminum were assumed to be proportional to aluminum concentration and reservoir area. The constant of proportionality, as a function of DOC concentration, was established by simulations in each of five reservoirs that differed in DOC concentration.
In addition to computing dilution factors, the project determined dilution factors that would be protective with the same statistical basis (frequency of exceedance of the chronic standard) as dilutions computed for streams at the 7-day-average 10-year-recurrence annual low flow (the 7Q10). Low-flow dilutions are used for permitting so that receiving waters are protected even at the worst-case flow levels. The low-flow dilution factors that give the same statistical protection are the lowest annual 7-day-average dilution factors with a recurrence of 10 years, termed 7DF10s. Determination of 7DF10 values for reservoirs required that long periods of record be simulated so that dilution statistics could be determined. Dilution statistics were simulated for 13 reservoirs from 1960 to 2004 using U.S. Geological Survey Firm-Yield Estimator software to model reservoir inputs and outputs and present-day values of filter-effluent discharge and aluminum concentration.
Computed settling velocities ranged from 0 centimeters per day (cm/d) at DOC concentrations of 15.5 milligrams per liter (mg/L) to 21.5 cm/d at DOC concentrations of 2.7 mg/L. The 7DF10 values were a function of aluminum effluent discharged. At current (2009) effluent discharge rates, the 7DF10 values varied from 1.8 to 115 among the 13 reservoirs. In most cases, the present-day (2009) discharge resulted in receiving water concentrations that did not exceed the standard at the 7DF10. Exceptions were one reservoir with a very small area and three reservoirs with high concentrations of DOC. Maximum permissible discharges were determined for water-treatment plants by adjusting discharges upward in simulations until the 7DF10 resulted in reservoir concentrations that just met the standard. In terms of aluminum flux, these discharges ranged from 0 to 28 kilograms of aluminum per day.
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\"}}]}","edition":"Version 1.0: Originally posted September 16, 2011; Version 1.1: December 30, 2016","contact":"Director, Massachusetts-Rhode Island Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
(508) 490-5000
http://ma.water.usgs.gov
The U.S. Geological Survey’s (USGS) concept of a national census (or accounting) of water resources has evolved over the last several decades as the Nation has experienced increasing concern over water availability for multiple competing uses. The implementation of a USGS National Water Census was described in the USGS 2007 science strategy document that identified the highest priority science topics for the decade 2007–17. In 2009, the SECURE Water Act (Public Law 111–11, subtitle F) authorized the USGS to create a Water Availability and Use Assessment Program for the Nation, and in 2012, the Department of the Interior WaterSMART initiative provided funding to begin implementation of the USGS National Water Census (NWC).
\nGenerally, the USGS NWC approaches water-availability assessment in terms of a “water budget.” The water-budget approach seeks to better quantify the inflows and outflows of water, as well as the change in storage volume, both nationally and at a regional scale and, by doing so, provides critical information to managers and stakeholders responsible for making water-availability decisions. The NWC has two primary components: Topical Studies and Geographic Focus Area Studies. Topical Studies do research on methods that can provide nationwide estimates of particular water-budget components at the subwatershed scale. Some examples of NWC Topical Studies include estimation of streamflow at ungaged locations; periodic quantification of evapotranspiration; and water use related to development of unconventional oil and gas. These efforts are planned to include additional topics in the future. Geographic Focus Area Studies (FASs) assess water availability and use within a defined geographic area, typically a surface-water drainage basin, to increase the understanding of factors affecting water availability in the region. In the FASs, local stakeholder input helps the USGS identify what components of the water budget are in most need of additional understanding or quantification. Focus Area Studies are planned as 3-year efforts and, typically, three FASs are ongoing in different parts of the country at any given time.
\nThe Colorado River Basin (CRB) and the Delaware and Apalachicola-Chattahoochee-Flint (ACF) River Basins were selected by the Department of the Interior for the first round of FASs because of the perceived water shortages in the basins and potential conflicts over water supply and allocations. After gathering input from numerous stakeholders in the CRB, the USGS determined that surface-water resources in the basin were already being closely monitored and that the most important scientific contribution could be made by helping to improve estimates of four water-budget components: evapotranspiration losses, snowpack hydrodynamics, water-use information, and the relative importance of groundwater discharge in supporting streamflow across the basin. The purpose of this fact sheet is to provide a brief summary of the CRB FAS results as the study nears completion. Although some project results are still in the later stages of review and publication, this fact sheet provides an overall description of the work completed and cites the publications in which additional information can be found.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20153080","usgsCitation":"Bruce, B.W., Clow, D.W., Maupin, M.A., Miller, M.P., Senay, G.B., Sexstone, G.A., and Susong, D.D., 2015, U.S. Geological Survey National Water Census—Colorado River Basin Geographic Focus Area Study: U.S. Geological Survey Fact Sheet 2015–3080, 4 p., https://dx.doi.org/10.3133/fs20153080.","productDescription":"4 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070751","costCenters":[{"id":5078,"text":"Southwest Regional Director's Office","active":true,"usgs":true}],"links":[{"id":311749,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2015/3080/fs20153080.pdf","text":"Report","size":"3.90 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2015-3080"},{"id":311748,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2015/3080/coverthb.jpg"}],"country":"United 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National Water Availability and Use
Science Program
U.S. Geological Survey
12201 Sunrise Valley Drive
988 National Center
Reston, VA 20192
http://water.usgs.gov/watercensus/
The U.S. Geological Survey (USGS) has operated a water-quality monitoring network in San Francisco Bay since the late 1980s (Buchanan and others, 2015). This network includes 19 stations in the bay; currently, 8 stations are in operation (fig. 1). All eight stations are equipped with specific conductance (which can be related to salinity) and water-temperature sensors that record measurements at 15-minute intervals. Water quality in the bay constantly changes with the ocean tides and with seasonal and interannual differences in river inflows. Our network was designed to observe and characterize some of these changes in the bay across space and over time. Our data demonstrated a high degree of variability both in specific conductance and temperature at time scales from tidal to annual and also revealed longer term changes that are likely to influence overall environmental health in the bay (San Francisco Estuary Institute, 2014). Figure 1. Locations of fixed water-quality monitoring stations in San Francisco Bay, California, for the 2014 water year (October 1, 2013 to September 30, 2014).
\nIn water year (WY) 2014 (October 1, 2013, through September 30, 2014), our network measured record-high values of specific conductance and water temperature at several stations during a period of very little freshwater inflow from the Sacramento–San Joaquin Delta and other tributaries because of severe drought conditions in California. This report summarizes our observations for WY2014 and compares them to previous years that had different levels of freshwater inflow.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151213","usgsCitation":"Downing-Kunz, M.A., Work, P.A., and Shellenbarger, G.G., 2015, Record-high specific\nconductance and temperature in San Francisco Bay during water year 2014 (ver. 1.1,\nDecember 28, 2015): U.S. Geological Survey Open-File Report 2015–1213, 4 p.","productDescription":"4 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066727","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":552,"text":"San Francisco Bay-Delta","active":false,"usgs":true}],"links":[{"id":311511,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1213/coverthb.jpg"},{"id":313213,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2015/1213/ofr20151213.txt","size":"2 KB","linkFileType":{"id":2,"text":"txt"},"description":"OFR 2015-1213 Version History"},{"id":311512,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1213/ofr20151213.pdf","text":"Report","size":"1.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1213"}],"country":"United States","state":"California","otherGeospatial":"Sacramento–San Joaquin Delta, San Francisco Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.70379638671874,\n 37.933366792504366\n ],\n [\n -121.66534423828125,\n 38.04592811939912\n ],\n [\n -121.75048828124999,\n 38.11943249695316\n ],\n [\n -121.90979003906249,\n 38.151837403006766\n ],\n [\n -122.07183837890625,\n 38.18638677411551\n ],\n [\n -122.178955078125,\n 38.20797181420939\n ],\n [\n -122.26684570312499,\n 38.26621945628273\n ],\n [\n -122.39593505859376,\n 38.26621945628273\n ],\n [\n -122.55249023437501,\n 38.16047628099622\n ],\n [\n -122.61291503906249,\n 37.996162679728116\n ],\n [\n -122.5689697265625,\n 37.861844098370945\n ],\n [\n -122.53326416015624,\n 37.77505678240509\n ],\n [\n -122.45635986328124,\n 37.63815995799935\n ],\n [\n -122.39593505859376,\n 37.51626173528878\n ],\n [\n -122.24761962890625,\n 37.413800350662875\n ],\n [\n -122.06359863281249,\n 37.35487607348372\n ],\n [\n -121.85211181640625,\n 37.38107035775657\n ],\n [\n -121.86035156249999,\n 37.5249753680482\n ],\n [\n -122.03613281249999,\n 37.655557695625056\n ],\n [\n -122.15698242187499,\n 37.81846319511331\n ],\n [\n -122.25585937500001,\n 37.92903406232562\n ],\n [\n -122.25036621093749,\n 37.983174833513395\n ],\n [\n -122.18170166015625,\n 38.00049145082287\n ],\n [\n -121.981201171875,\n 37.996162679728116\n ],\n [\n -121.86584472656251,\n 37.96801944035648\n ],\n [\n -121.75048828124999,\n 37.93553306183642\n ],\n [\n -121.70379638671874,\n 37.933366792504366\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, CA 95819
http://ca.water.usgs.gov
The Yakima River Basin in south-central Washington has a long history of irrigated agriculture and a more recent history of large-scale livestock operations, both of which may contribute nutrients to the groundwater system. Nitrate concentrations in water samples from shallow groundwater wells in the lower Yakima River Basin exceeded the U.S. Environmental Protection Agency drinking-water standard, generating concerns that current applications of fertilizer and animal waste may be exceeding the rate at which plants can uptake nutrients, and thus contributing to groundwater contamination.
\nThe U.S. Geological Survey (USGS) recently completed a regional scale transient three-dimensional groundwater-flow model of the Yakima River Basin using MODFLOW-2000. The model was used with the USGS particle-tracking code MODPATH to generate advective flowpaths and associated travel times. Analyses used particle backtracking in time from September 2001 through 504 monthly stress periods to October 1959 or until pathlines terminated at a model boundary. The particle starting locations were assigned to 1,000 foot square computational model cells containing one or more of the 121 sampling locations with measured nitrate concentrations greater than the U.S. Environmental Protection Agency drinking-water standard for nitrate (10 milligrams per liter [mg/L]). Of the 2,403 particles, the simulated pathlines for 2,080 reached the water table within the 42-year simulation period, thus identifying the predicted recharge areas for those particles. The median horizontal straight-line distance was 13,194 feet between starting and ending locations for these particles and the median time-of-travel for particles that intersected the water table was 984 days. Well to water-table travel times for 75.4 percent of the particles were less than the average travel time of 3,749 days. Predicted recharge locations for all particles, including those that did not reach the water table in 42 years, were between 50 feet and 34 miles horizontal distance from their starting locations, with a median distance of less than 3 miles away.
\nGeneralized groundwater-flow directions in unconsolidated basin-fill deposits were towards the Yakima River, which acts as a local sink for shallow groundwater, and roughly parallel to topographic gradients. Particles backtracked from more shallow aquifer locations traveled shorter distances before reaching the water table than particles from deeper locations. Flowpaths for particles starting at wells completed in the basalt units underlying the basin-fill deposits sometimes were different than for wells with similar lateral locations but more shallow depths. In cases where backtracking particles reached geologic structures simulated as flow barriers, abrupt changes in direction in some particle pathlines suggest significant changes in simulated hydraulic gradients that may not accurately reflect actual conditions. Most groundwater wells sampled had associated zones of contribution within the Toppenish/Benton subbasin between the well and the nearest subbasin margin, but interpretation of these results for any specific well is likely to be complicated by the assumptions and simplifications inherent in the model construction process. Delineated zones of contribution for individual wells are sensitive to the depths assigned to the screened interval of the well, resulting in simulated areal extents of the zones of contribution to a discharging well that are elongated in the direction of groundwater flow.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155149","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Bachmann, M.P., 2015, Particle tracking for selected groundwater wells in the lower Yakima River Basin, Washington: U.S. Geological Survey Scientific Investigations Report 2015-5149, 33 p., https://dx.doi.org/10.3133/sir20155149.","productDescription":"v, 33 p.","numberOfPages":"44","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-066526","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":310287,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5149/coverthb.jpg"},{"id":310288,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5149/sir20155149.pdf","text":"Report","size":"13.5MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5149 Report PDF"}],"country":"United States","state":"Washington","otherGeospatial":"Yakima River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.95947265624999,\n 45.935870621190546\n ],\n [\n -120.95947265624999,\n 46.58529390583601\n ],\n [\n -119.53125,\n 46.58529390583601\n ],\n [\n -119.53125,\n 45.935870621190546\n ],\n [\n -120.95947265624999,\n 45.935870621190546\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402
http://wa.water.usgs.gov
Trace-metal concentrations in sediment and in the clam Macoma petalum (formerly reported as Macoma balthica), clam reproductive activity, and benthic macroinvertebrate community structure were investigated in a mudflat 1 kilometer (km) south of the discharge of the Palo Alto Regional Water Quality Control Plant (PARWQCP) in South San Francisco Bay, Calif. This report includes the data collected by U.S. Geological Survey (USGS) scientists for the period January 2014 to December 2014. These append to long-term datasets extending back to 1974, and serve as the basis for the City of Palo Alto’s Near-Field Receiving Water Monitoring Program, initiated in 1994.
\nFollowing significant reductions in the late 1980s, silver (Ag) and copper (Cu) concentrations in sediment and M. petalum appear to have stabilized. Data for other metals, including chromium (Cr), mercury (Hg), nickel (Ni), selenium (Se), and zinc (Zn), have been collected since 1994. Over this period, concentrations of these elements have remained relatively constant, aside from seasonal variation that is common to all elements. In 2014, concentrations of Ag and Cu in M. petalum varied seasonally in response to a combination of site-specific metal exposures and annual growth and reproduction, as reported previously. Seasonal patterns for other elements, including Cr, Ni, Zn, Hg, and Se, were generally similar in timing and magnitude as those for Ag and Cu. In M. petalum, all observed elements showed annual maxima in January–February and minima in April, except for Zn, which was lowest in December. In sediments, annual maxima also occurred in January–February, and minima were measured in June and September. In 2014, metal concentrations in both sediments and clam tissue were among the lowest on record. This record suggests that regional-scale factors now largely control sedimentary and bioavailable concentrations of Ag and Cu, as well as other elements of regulatory interest, at the Palo Alto site.
\nAnalyses of the benthic community structure of a mudflat in South San Francisco Bay over a 40-year period show that changes in the community have occurred concurrent with reduced concentrations of metals in the sediment and in the tissues of the biosentinel clam, M. petalum, from the same area. Analysis of M. petalum shows increases in reproductive activity concurrent with the decline in metal concentrations in the tissues of this organism. Reproductive activity is presently stable (2014), with almost all animals initiating reproduction in the fall and spawning the following spring. The entire infaunal community has shifted from being dominated by several opportunistic species to a community where the species are more similar in abundance, a pattern that indicates a more stable community that is subjected to fewer stressors. In addition, two of the opportunistic species (Ampelisca abdita and Streblospio benedicti) that brood their young and live on the surface of the sediment in tubes have shown a continual decline in dominance coincident with the decline in metals; both species had short-lived rebounds in abundance in 2008, 2009, and 2010. Heteromastus filiformis (a subsurface polychaete worm that lives in the sediment, consumes sediment and organic particles residing in the sediment, and reproduces by laying its eggs on or in the sediment) showed a concurrent increase in dominance and, in the last several years before 2008, showed a stable population. H. filiformis abundance increased slightly in 2011–2012 and returned to pre-2011 numbers in 2014. An unidentified disturbance occurred on the mudflat in early 2008 that resulted in the loss of the benthic animals, except for deep-dwelling animals like Macoma petalum. However, within two months of this event animals returned to the mudflat. The resilience of the community suggested that the disturbance was not due to a persistent toxin or to anoxia. The reproductive mode of most species present in 2014 is reflective of species that were available either as pelagic larvae or as mobile adults. Although oviparous species were lower in number in this group, the authors hypothesize that these species will return slowly as more species move back into the area. The use of functional ecology was highlighted in the 2014 benthic community data, which showed that the animals that have now returned to the mudflat are those that can respond successfully to a physical, nontoxic disturbance. Today, community data show a mix of species that consume the sediment, or filter feed, have pelagic larvae that must survive landing on the sediment, and those that brood their young. USGS scientists view the 2008 disturbance event as a response by the infaunal community to an episodic natural stressor (possibly sediment accretion or a pulse of freshwater), in contrast to the long-term recovery from metal contamination. We will compare this recovery to the long-term recovery observed after the 1970’s when the decline in sediment pollutants was the dominating factor.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151199","usgsCitation":"Cain, D.J., Thompson, J.K., Crauder, J., Parcheso, F., Stewart, A.R., Kleckner, A.E., Dyke, J., Hornberger, M.I., and Luoma, S.N., 2015, Near-field receiving water monitoring of trace metals and a benthic community near the Palo Alto Regional Water Quality Control Plant in south San Francisco Bay, California: 2014: U.S. Geological Survey Open-File Report 2015-1199, viii, 79 p., https://doi.org/10.3133/ofr20151199.","productDescription":"viii, 79 p.","numberOfPages":"89","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2014-01-01","temporalEnd":"2014-12-31","ipdsId":"IP-068498","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":310004,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1199/ofr20151199.pdf","text":"Report","size":"9.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1199"},{"id":310003,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1199/coverthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.11578369140626,\n 37.43493087364719\n ],\n [\n -122.11578369140626,\n 37.46123344639866\n ],\n [\n -122.09020614624023,\n 37.46123344639866\n ],\n [\n -122.09020614624023,\n 37.43493087364719\n ],\n [\n -122.11578369140626,\n 37.43493087364719\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"NRP staff
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