Semi-quantitative mussel surveys, conducted by the U.S. Geological Survey and the Delaware Riverkeeper Network in cooperation with The Nature Conservancy, were completed in the vicinity of the Columbia Dam, on the Paulins Kill, New Jersey, in August 2017 in order to document the mussel species composition and relative abundance prior to removal of the dam. Surveys were conducted from the Brugler Road Bridge downriver approximately 2,000 meters (m) to the Columbia Dam and downriver from the dam about 300 m to 75 m upriver from the confluence of the Paulins Kill with the Delaware River. Sixteen sections (average length=175 m) were surveyed by personnel snorkeling or SCUBA diving; 13 sections were upriver from the dam, and 3 were downriver from the dam. Mussels, as they were encountered by surveyors, were removed from the sediment, immediately identified to species, and replaced in their original collection locations. Habitat data were collected for each surveyed section. Upriver and downriver from the dam, river margins with dense vegetation were examined for mussels by personnel using snorkels in transects (approximately 25 meters) perpendicular to river flow every 50 m on both sides of the river. Only two species were found upriver from the dam, and those were present in relatively low numbers. Catch per unit effort is reported here within parentheses as the average across upriver sections in number of mussels per person hour of survey time: 42 Elliptio complanata (2.6) and 1 Pyganodon cataracta (0.1) were found upriver from the dam. No mussels were found in the dense vegetation either upriver or downriver of the dam by surveyors using snorkels. Significantly higher species richness and mussel catch per unit effort were found downriver from the dam than upriver, including 106 E. complanta (32.5), 27 Utterbackiana implicata (8.2), 1 Alasmidonta undulata (0.4), 2 Lampsilis cariosa (0.5), 6 Lampsilis radiata (2.1), 4 P. cataracta (1.1), and 1 Strophitus undulatus (0.4). The average habitat assessment score did not differ upriver and downriver from the dam.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181074","collaboration":"Prepared in cooperation with The Nature Conservancy","usgsCitation":"Galbraith, H.S., Blakeslee, C.J., Cole, J.C., and Silldorff, E.L., 2018, Freshwater mussel survey for the Columbia Dam removal, Paulins Kill, New Jersey: U.S. Geological Survey Open-File Report 2018–1074, 7 p., https://doi.org/10.3133/ofr20181074.","productDescription":"v, 7 p.","numberOfPages":"18","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-094047","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":354676,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1074/ofr20181074.pdf","text":"Report","size":"9.40 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1074"},{"id":354675,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1074/coverthb.jpg"}],"country":"United States","state":"New Jersey","otherGeospatial":"Columbia Dam, Paulins Kill","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.0889778137207,\n 40.9203876084737\n ],\n [\n -75.06837844848633,\n 40.9203876084737\n ],\n [\n -75.06837844848633,\n 40.937896253014145\n ],\n [\n -75.0889778137207,\n 40.937896253014145\n ],\n [\n -75.0889778137207,\n 40.9203876084737\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Eastern Ecological Science Center
U.S. Geological Survey
11649 Leetown Road
Kearneysville, WV 25430
Frequent occurrence of intermediate forms and poor knowledge on the variability of characters have caused some difficulties in the taxonomy of Trapa in Japan. Thus I made a preliminary analysis on the variation of nuts collected from 21 populations in Southwestern Japan. Attention was paid to some morphometrical characters of the nut and development of lower spines or “pseudohorns.” Each population usually contained different forms of nuts. Among them, however, several entities could be recognized based on the shape of nut as follows. 1) Two-spined form: This included nuts of middle size (width 30–50 mm) and ones of big size (width over 45 mm). In case of the former ones, the nuts with pseudohorns of varying degree of development usually occurred together within one population and even on a single plant. I propose to treat them as one taxon, Trapa japonica, sensu OHWI (1965), without inventing varieties. But at the same time, it was remarkable that the tendency of development of pseudohorns was apparently different from population to population. The bigger ones included two types, that is, one without pseudohorns and the other with pseudohorns. The former one may be identified as T. bispinosa ROXB., but the latter one has not been described in literature. 2) Four-spined form: The nuts of small size (width of about 20 mm) were well definable and thought to be T. incisa SIEB. et ZUCC. The nuts of bigger size showed some variations with respect to their size and/or stoutness of lower spines. The big ones (width over 45 mm) may be treated as one taxon, T. natans or its variety. The nuts of middle size have been named T. natans var. pumila NAKANO. But so far as present materials were concerned, its entity seemed dubious. They might be immature nuts of bigger ones. The different patterns of variation among populations were ascribed to genetic differentiation. Predominance of self-pollination and isolation of habitats were thought to promote genetic isolation and preservation of genetic variations which occurred in each population. But the possibility of hybridization cannot be excluded.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181075","usgsCitation":"Kadono, Yasuro, 2018, A preliminary study of variation of Trapa in Japan (translated into English from the Japanese by V. Chintu Lai): U.S. Geological Survey Open-File Report 2018–1075, 16 p., https://doi.org/10.3133/ofr20181075. [The translation was edited by Nancy B. Rybicki. The article was originally published in Japanese with English summary as Kadono, Y., 1987, A preliminary study of variation of Trapa in Japan: Acta Phytotaxonomica et Geobotanica, v. 38 (September), p. 199–210, https://doi.org/10.18942/bunruichiri.KJ00002992255.]","productDescription":"14 p.","numberOfPages":"16","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-086527","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":354294,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1075/coverthb.jpg"},{"id":354295,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1075/ofr20181075.pdf","text":"Report","size":"769 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1075","linkHelpText":"- Open File Report of the Japanese language paper by Y. Kadono, and translated by Vince Lai that describes Trapa (water chestnut)."}],"country":"Japan","publicComments":"Open File Report of the Japanese language paper by Y. Kadono, and translated by Vince Lai that describes Trapa (water chestnut).","contact":"Director, Earth System Processes Division
U.S. Geological Survey
411 National Center
12201 Sunrise Valley Drive
Reston, VA 20192
This report was written as a collaborative effort between the U.S. Geological Survey, SilvaCarbon, and Wageningen University with funding provided by the U.S. Agency for International Development and the European Space Agency, respectively, to address a pressing need for enhanced result-based monitoring and evaluation of delivered capacity-building activities. For this report, the capacity-building activities delivered by capacity-building providers (referred to as “providers” hereafter) during 2011–15 (the study period) to support countries in building measurement, reporting, and verification (MRV) systems for reducing emissions from deforestation and forest degradation (REDD+) were assessed and evaluated.
Summarizing capacity-building activities and outcomes across multiple providers was challenging. Many of the providers did not have information readily available, which precluded them from participating in this study despite the usefulness of their information. This issue led to a key proposed future action: Capacity-building providers could establish a central repository within the Global Forestry Observation Initiative (GFOI; http://www.gfoi.org/) where data from past, current, and future activities of all capacity-building providers could be stored. The repository could be maintained in a manner to continually learn from previous lessons.
Although various providers monitored and evaluated the success of their capacity-building activities, such evaluations only assessed the success of immediate outcomes and not the overarching outcomes and impacts of activities implemented by multiple providers. Good monitoring and evaluation should continuously monitor and periodically evaluate all factors affecting the outcomes of a provided capacity-building activity.
The absence of a methodology to produce quantitative evidence of a causal link between multiple capacity-building activities delivered and successful outcomes left only a plausible association. A previous publication argued that plausible association, although not a precise measurement of cause and effect, was a realistic tool. Our review of the available literature on this subject did not find another similar assessment to assess capacity-building activities for supporting the countries in building MRV system for REDD+.
Four countries from the main forested regions of Africa, the Americas, and Asia were chosen as subjects for this report based on the length of time SilvaCarbon and other providers have provided capacity-building activities toward MRV system for REDD+: Colombia (the Americas), the Democratic Republic of the Congo (DRC; Africa), Peru (the Americas), and the Republic of the Philippines (referred to as “the Philippines” hereafter; Asia).
Several providers were contacted for information to include in this report, but, because of various constraints, only SilvaCarbon, the Food and Agriculture Organization of the United Nations (FAO), and the World Wildlife Fund (WWF) participated in this study. These three providers supported various targeted capacity-building activities through-out Africa, the Americas, and Asia, including the following: technical workshops at national and regional levels (referred to as “workshops” hereafter), hands on training, study tours, technical details by experts, technical consultation between providers and recipients, sponsorship for travel, organizing network meetings, developing sampling protocols, assessing deforestation and degradation drivers, estimating carbon stock and flow, designing monitoring systems for multiple uses, promoting public-private partnerships to scale up investments on MRV system for REDD+, and assisting with the design of national forest monitoring systems.
Their activities were planned in coordination with key partners in each country and region and with the support and assistance of other providers. Note that several other organizations and institutions assisted the providers to deliver capacity-building activities, including Boston University, Conservation International, Stanford University, University of Maryland, and Wageningen University & Research.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181031","collaboration":"Prepared in cooperation with Wageningen University, the U.S. Agency for International Development, the U.S. Department of State, and the European Space Agency ","usgsCitation":"Peneva-Reed, E.I., and Romijn, J.E, 2018, Assessment of capacity-building activities for forest measurement, reporting, and verification, 2011–15: U.S. Geological Survey Open-File Report 2018–1031, 35 p., https://doi.org/10.3133/ofr20181031. ","productDescription":"v, 35 p.","numberOfPages":"46","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-088895","costCenters":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"links":[{"id":354567,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1031/ofr20181031.pdf","text":"Report","size":"1.07 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1031"},{"id":354566,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1031/coverthb.jpg"}],"contact":"Director, U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
**September 28, 2018: The purpose of a USGS Open-file report (OFR) is dissemination of information that must be released immediately to fill a public need or information that is not sufficiently refined to warrant publication in one of the other USGS series. As part of that refinement process, an error was discovered in one of the input data sets of the Rio Grande Transboundary Integrated Hydrologic Model (RGTIHM) that this OFR was based upon. The error involved the assignment of storage properties to “phantom cells.”
Phantom cells are required for most variants of MODFLOW that use a structured finite-difference grid when individual stratigraphic layers are represented as separate layers. Using phantom cells is a common practice that allows separate model layers to be maintained without having to combine stratigraphic layers into equivalent model layers or to use an unstructured grid. Typically, phantom cell horizontal hydraulic conductivities and storage properties are set to a small number and vertical hydraulic conductivities are set to a number large enough to allow vertical flow between the vertically adjacent layers.
In the RGTIHM, the specific storage properties of the phantom cells for the upper (RGTIHM layers 3 and 4), middle (RGTIHM layers 5 and 6), and lower (RGTIHM layers 7 and 8) members of the Santa Fe Group were inadvertently assigned a value of 1 feet-1. The revision of these specific storage values to a small number (1.0 x 10-09 feet-1) required additional trial-and-error model calibration and a new sensitivity analysis. After calibration, the overall model fit remained similar to the fit described in the OFR, but the fit for many individual features such as project water available for diversions at the American Canal and Acequia Madre improved due to the reduction in flow coming from lower layers. Overall, there is still an average net depletion of groundwater flow, and the conclusions of the report are not changed. The revised average annual groundwater flow depletion simulated for the period 1953-2014 is -1,480 acre-feet/year for the entire model region, and -3,660 acre-feet/year for the portion of the model in the United States. The final version of the model will be the basis of the USGS Scientific Investigations Report that will supersede this OFR. An updated Model Archive of RGTIHM is available upon request to the USGS California Water Science Center.
The corrected version of the model WAS the basis for the USGS Scientific Investigations Report that SUPERSEDED this Open-File Report.**
Changes in population, agricultural development and practices (including shifts to more water-intensive crops), and climate variability are increasing demands on available water resources, particularly groundwater, in one of the most productive agricultural regions in the Southwest—the Rincon and Mesilla Valley parts of Rio Grande Valley, Doña Ana and Sierra Counties, New Mexico, and El Paso County, Texas. The goal of this study was to produce an integrated hydrological simulation model to help evaluate water-management strategies, including conjunctive use of surface water and groundwater for historical conditions, and to support long-term planning for the Rio Grande Project. This report describes model construction and applications by the U.S. Geological Survey, working in cooperation and collaboration with the Bureau of Reclamation.
This model, the Rio Grande Transboundary Integrated Hydrologic Model, simulates the most important natural and human components of the hydrologic system, including selected components related to variations in climate, thereby providing a reliable assessment of surface-water and groundwater conditions and processes that can inform water users and help improve planning for future conditions and sustained operations of the Rio Grande Project (RGP) by the Bureau of Reclamation. Model development included a revision of the conceptual model of the flow system, construction of a Transboundary Rio Grande Watershed Model (TRGWM) water-balance model using the Basin Characterization Model (BCM), and construction of an integrated hydrologic flow model with MODFLOW-One-Water Hydrologic Flow Model (referred to as One Water). The hydrologic models were developed for and calibrated to historical conditions of water and land use, and parameters were adjusted so that simulated values closely matched available measurements (calibration). The calibrated model was then used to assess the use and movement of water in the Rincon Valley, Mesilla Basin, and northern part of the Conejos-Médanos Basin, with the entire region referred to as the “Transboundary Rio Grande” or TRG. These tools provide a means to understand hydrologic system response to the evolution of water use in the region, its availability, and potential operational constraints of the RGP.
The conceptual model identified surface-water and groundwater inflows and outflows that included the movement and use of water both in natural and in anthropogenic systems. The groundwater-flow system is characterized by a layered geologic sedimentary sequence combined with the effects of groundwater pumping, operation of the RGP, natural runoff and recharge, and the application of irrigation water at the land surface that is captured and reused in an extensive network of canals and drains as part of the conjunctive use of water in the region.
Historical groundwater-level fluctuations followed a cyclic pattern that were aligned with climate cycles, which collectively resulted in alternating periods of wet or dry years. Periods of drought that persisted for one or more years are associated with low surface-water availability that resulted in higher rates of groundwater-level decline. Rates of groundwater-level decline also increased during periods of agricultural intensification, which necessitated increasing use of groundwater as a source of irrigation water. Agriculture in the area was initially dominated by alfalfa and cotton, but since 1970 more water-intensive pecan orchards and vegetable production have become more common. Groundwater levels substantially declined in subregions where drier climate combined with increased demand, resulting in periods of reduced streamflows.
Most of the groundwater was recharged in the Rio Grande Valley floor, and most of the pumpage and aquifer storage depletion was in Mesilla Basin agricultural subregions. A cyclic imbalance between inflows and outflows resulted in the modeled cyclic depletion (groundwater withdrawals in excess of natural recharge) of the groundwater basin during the 75-year simulation period of 1940–2014. Changes in groundwater storage can vary considerably from year to year, depending on land use, pumpage, and climate conditions. Climatic drivers of wet and dry years can greatly affect all inflows, outflows, and water use. Although streamflow and, to a minor extent, precipitation during inter-decadal wet-year periods replenished the groundwater historically, contemporary water use and storage depletion could have reduced the effects of these major recharge events. The average net groundwater flow-rate deficit for 1953–2014 was estimated to be about 8,990 acre-feet per year.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181091","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Hanson, R.T., Ritchie, A.B., Boyce, S.E., Galanter, A.E., Ferguson, I.A., Flint, L.E., and Henson, W.R., 2018, Rio Grande transboundary integrated hydrologic model and water-availability analysis, New Mexico and Texas, United States, and Northern Chihuahua, Mexico: U.S Geological Survey Open-File Report 2018–1091, 185 p., https://doi.org/10.3133/ofr20181091.","productDescription":"Report: x, 185 p.; Dataset; Data release; Errata","numberOfPages":"200","onlineOnly":"Y","ipdsId":"IP-071162","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":354790,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1091/ofr20181091.pdf","text":"Report","size":"25 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":354791,"rank":2,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.3133/ofr20181091","linkHelpText":"- This Open-File report (OFR) was superseded by USGS Scientific Investigations report (SIR) SIR 2019-5120. The final model archive will be available on the national USGS archive site."},{"id":357946,"rank":4,"type":{"id":12,"text":"Errata"},"url":"https://pubs.usgs.gov/of/2018/1091/erratum.txt","size":"3 KB","linkFileType":{"id":2,"text":"txt"}},{"id":363155,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9J9NYND","linkHelpText":"Digital hydrologic and geospatial data for the Rio Grande transboundary integrated hydrologic model and water-availability analysis, New Mexico and Texas, United States, and Northern Chihuahua, Mexico"},{"id":354795,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1091/coverthb_.jpg"}],"country":"Mexico, United States","state":"New Mexico, Northern Chihuahua, Texas","otherGeospatial":"Rio Grande","publicComments":"This Open-File report (OFR) will be superseded by a USGS Scientific Investigations report (SIR) once the USGS Techniques and Methods report (T&M) documenting the numerical code is published. Once the SIR is released, the final model archive will be available on the national USGS archive site. For the interim archive for this model, please contact CaWSC for directions on downloading 916-278-3026.","contact":"Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
Forster’s terns (Sterna forsteri), historically one of the most numerous colonial-breeding waterbirds in South San Francisco Bay, California, have had recent decreases in the number of nesting colonies and overall breeding population size. The South Bay Salt Pond (SBSP) Restoration Project aims to restore 50–90 percent of former salt evaporation ponds to tidal marsh habitat in South San Francisco Bay. This restoration will remove much of the historical island nesting habitat used by Forster’s terns, American avocets (Recurvirostra americana), and other waterbirds. To address this issue, the SBSP Restoration Project organized the construction of new nesting islands in managed ponds that will not be restored to tidal marsh, thereby providing enduring island nesting habitat for waterbirds. In 2012, 16 new islands were constructed in Pond A16 in the Alviso complex of the Don Edwards San Francisco Bay National Wildlife Refuge, increasing the number of islands in this pond from 4 to 20. However, despite a history of nesting on the four historical islands in Pond A16 before 2012, no Forster’s terns have nested in Pond A16 since the new islands were constructed.
In 2017, we used social attraction measures (decoys and electronic call systems) to attract Forster’s terns to islands within Pond A16 to re-establish nesting colonies. We maintained these systems from March through August 2017. To evaluate the effect of these social attraction measures, we also completed waterbird surveys between April and August, where we recorded the number and location of all Forster’s terns and other waterbirds using Pond A16, and monitored waterbird nests. We compared bird survey and nest monitoring data collected in 2017 to data collected in 2015 and 2016, prior to the implementation of social attraction measures, allowing for direct evaluation of social attraction efforts on Forster’s terns.
To increase the visibility and stakeholder involvement of this project, we engaged in multiple outreach activities, including the development of a project web site (https://apps.usgs.gov/shorebirds/) and educational video (https://www.youtube.com/watch?v=-IaZD0YlAvM&feature=youtu.be); publication of a popular article (http://www.sfestuary.org/estuary-news-caspian-push-and-pull/); and public presentations to relay findings to managers, stakeholders, and the general public.
The relative number of Forster’s terns using Pond A16, after adjusting for the overall South San Francisco Bay breeding population each year, was higher during the nesting period in 2017 (after social attraction was used) than in 2015 and 2016 (before social attraction was used). Furthermore, in 2017, more Forster’s terns were observed in the areas of Pond A16 where decoys and call systems were deployed during the pre-nesting and nesting periods. Although no Forster’s tern nests were recorded in Pond A16 before (2015, 2016) or after (2017) implementation of social attraction measures, bird survey results indicate that Forster’s terns were attracted to areas within Pond A16 where decoys and call systems were deployed, suggesting that terns may have been prospecting for future breeding sites. As social attraction efforts often benefit from multiple years of decoy and call system deployment, these first-year results suggest that continued implementation of social attraction measures could help to re-establish Forster’s tern breeding colonies in Pond A16 and other areas of South San Francisco Bay.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181090","collaboration":"Prepared in cooperation with the San Francisco Bay Bird Observatory","usgsCitation":"Hartman, C.A., Ackerman, J.T., Herzog, M.P., Wang, Y., and Strong, C., 2018, Evaluation of social attraction measures to establish Forster’s tern (Sterna forsteri) nesting colonies for the South Bay Salt Pond Restoration Project, San Francisco Bay, California—2017 annual report: U.S. Geological Survey Open-File Report 2018–1090, 25 p., https://doi.org/10.3133/ofr20181090.","productDescription":"iv, 25 p.","numberOfPages":"33","onlineOnly":"Y","ipdsId":"IP-096847","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":354652,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1090/coverthb2.jpg"},{"id":354653,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1090/ofr20181090.pdf","text":"Report","size":"12.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1090"}],"country":"United States","state":"California","otherGeospatial":"Don Edwards San Francisco Bay National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.15492248535156,\n 37.38379840307495\n ],\n [\n -121.89674377441405,\n 37.38379840307495\n ],\n [\n -121.89674377441405,\n 37.555465068186955\n ],\n [\n -122.15492248535156,\n 37.555465068186955\n ],\n [\n -122.15492248535156,\n 37.38379840307495\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
Streamflow and concentrations of sodium and chloride estimated from records of specific conductance were used to calculate loads of sodium and chloride during water year (WY) 2015 (October 1, 2014, through September 30, 2015) for tributaries to the Scituate Reservoir, Rhode Island. Streamflow and water-quality data used in the study were collected by the U.S. Geological Survey and the Providence Water Supply Board. Streamflow was measured or estimated by the U.S. Geological Survey following standard methods at 23 streamgages; 14 of these streamgages are equipped with instrumentation capable of continuously monitoring water level, specific conductance, and water temperature. Water-quality samples were collected at 36 sampling stations by the Providence Water Supply Board and at 14 continuous-record streamgages by the U.S. Geological Survey during WY 2015 as part of a long-term sampling program; all stations are in the Scituate Reservoir drainage area. Water-quality data collected by the Providence Water Supply Board are summarized by using values of central tendency and are used, in combination with measured (or estimated) streamflows, to calculate loads and yields (loads per unit area) of selected water-quality constituents for WY 2015.
The largest tributary to the reservoir (the Ponaganset River, which was monitored by the U.S. Geological Survey) contributed a mean streamflow of 25 cubic feet per second to the reservoir during WY 2015. For the same time period, annual mean streamflows measured (or estimated) for the other monitoring stations in this study ranged from about 0.38 to about 14 cubic feet per second. Together, tributaries (equipped with instrumentation capable of continuously monitoring specific conductance) transported about 1,500,000 kilograms of sodium and 2,400,000 kilograms of chloride to the Scituate Reservoir during WY 2015; sodium and chloride yields for the tributaries ranged from 8,000 to 54,000 kilograms per square mile and from 12,000 to 91,000 kilograms per square mile, respectively.
At the stations where water-quality samples were collected by the Providence Water Supply Board, the medians of the median concentrations were the following: for chloride, 29.5 milligrams per liter; for nitrite, 0.002 milligrams per liter as nitrogen; for nitrate, 0.05 milligrams per liter as nitrogen; for orthophosphate, 0.08 milligrams per liter as phosphate; and for total coliform bacteria and Escherichia coli, 440 and 20 colony forming units per 100 milliliters, respectively. The medians of the median daily loads (and yields) of chloride, nitrite, nitrate, orthophosphate, and total coliform and Escherichia coli bacteria were 170 kilograms per day (79 kilograms per day per square mile), 14 grams per day (5.2 grams per day per square mile), 670 grams per day (190 grams per day per square mile), 640 grams per day (210 grams per day per square mile), 18,000 million colony forming units per day (7,600 million colony forming units per day per square mile), and 1,200 million colony forming units per day (810 million colony forming units per day per square mile), respectively.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181065","collaboration":"Prepared in cooperation with the Providence Water Supply Board","usgsCitation":"Smith, K.P., 2018, Streamflow, water quality, and constituent loads and yields, Scituate Reservoir drainage area, Rhode Island, water year 2015: U.S. Geological Survey Open-File Report 2018–1065, 28 p., https://doi.org/10.3133/ofr20181065.","productDescription":"Report: v, 28 p.; Data release","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-088040","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":354074,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7FJ2FR5","text":"USGS data release","description":"USGS data release","linkHelpText":"Water Quality data from the Providence Water Supply Board for tributary streams to the Scituate Reservoir, water year 2015"},{"id":354073,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1065/ofr20181065.pdf","text":"Report","size":"1.16 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1065"},{"id":354072,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1065/coverthb2.jpg"}],"country":"United States","state":"Rhode Island","otherGeospatial":"Scituate Reservoir","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -71.61334991455077,\n 41.72546174412562\n ],\n [\n -71.59687042236328,\n 41.73571038089891\n ],\n [\n -71.57112121582031,\n 41.75978824099475\n ],\n [\n -71.5481185913086,\n 41.784369074958185\n ],\n [\n -71.5536117553711,\n 41.82173436916421\n ],\n [\n -71.55635833740234,\n 41.83145600892532\n ],\n [\n -71.5536117553711,\n 41.842199261672384\n ],\n [\n -71.55979156494139,\n 41.85652079326776\n ],\n [\n -71.5707778930664,\n 41.862146232018134\n ],\n [\n -71.59000396728514,\n 41.862146232018134\n ],\n [\n -71.60923004150389,\n 41.877485822442324\n ],\n [\n -71.61128997802734,\n 41.907642945005215\n ],\n [\n -71.6421890258789,\n 41.918373400143004\n ],\n [\n -71.66622161865234,\n 41.91173095014917\n ],\n [\n -71.66416168212889,\n 41.886687809812926\n ],\n [\n -71.66622161865234,\n 41.857543637121026\n ],\n [\n -71.67377471923828,\n 41.854986496815044\n ],\n [\n -71.6861343383789,\n 41.8744181988335\n ],\n [\n -71.69265747070311,\n 41.87262868373214\n ],\n [\n -71.70398712158203,\n 41.86674849564142\n ],\n [\n -71.72321319580077,\n 41.88719899247718\n ],\n [\n -71.73282623291016,\n 41.89435512030307\n ],\n [\n -71.75617218017578,\n 41.895888471963744\n ],\n [\n -71.77196502685547,\n 41.88771017105127\n ],\n [\n -71.76578521728516,\n 41.87237303462768\n ],\n [\n -71.77265167236328,\n 41.854986496815044\n ],\n [\n -71.76647186279297,\n 41.83145600892532\n ],\n [\n -71.7685317993164,\n 41.82122266302155\n ],\n [\n -71.76990509033202,\n 41.81457011105642\n ],\n [\n -71.75754547119139,\n 41.79358445913614\n ],\n [\n -71.74655914306639,\n 41.78129698585321\n ],\n [\n -71.7348861694336,\n 41.77464028786307\n ],\n [\n -71.71634674072264,\n 41.771567732673454\n ],\n [\n -71.7033004760742,\n 41.76081263047197\n ],\n [\n -71.69300079345702,\n 41.75620274904767\n ],\n [\n -71.6861343383789,\n 41.74185877811425\n ],\n [\n -71.6744613647461,\n 41.741346434162764\n ],\n [\n -71.6476821899414,\n 41.73775991204249\n ],\n [\n -71.63875579833983,\n 41.727511602285894\n ],\n [\n -71.61334991455077,\n 41.72546174412562\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
In this report, precipitation data from 2002 to 2012 from the hourly gridded Next-Generation Radar (NEXRAD)-based Multisensor Precipitation Estimate (MPE) precipitation product are compared to precipitation data from two rain gage networks—an automated tipping bucket network of 25 rain gages operated by the U.S. Geological Survey (USGS) and 51 rain gages from the volunteer-operated Community Collaborative Rain, Hail, and Snow (CoCoRaHS) network—in and near DuPage County, Illinois, at a daily time step to test for long-term differences in space, time, and distribution. The NEXRAD–MPE data that are used are from the fifty 2.5-mile grid cells overlying the rain gages from the other networks. Because of the challenges of measuring of frozen precipitation, the analysis period is separated between days with or without the chance of freezing conditions. The NEXRAD–MPE and tipping-bucket rain gage precipitation data are adjusted to account for undercatch by multiplying by a previously determined factor of 1.14. Under nonfreezing conditions, the three precipitation datasets are broadly similar in cumulative depth and distribution of daily values when the data are combined spatially across the networks. However, the NEXRAD–MPE data indicate a significant trend relative to both rain gage networks as a function of distance from the NEXRAD radar just south of the study area. During freezing conditions, of the USGS network rain gages only the heated gages were considered, and these gages indicate substantial mean undercatch of 50 and 61 percent compared to the NEXRAD–MPE and the CoCoRaHS gages, respectively. The heated USGS rain gages also indicate substantially lower quantile values during freezing conditions, except during the most extreme (highest) events. Because NEXRAD precipitation products are continually evolving, the report concludes with a discussion of recent changes in those products and their potential for improved precipitation estimation. An appendix provides an analysis of spatially combined NEXRAD–MPE precipitation data as a function of temperature at an hourly time scale and indicates, among other results, that most precipitation in the study area occurs at moderate temperatures of 30 to 74 degrees Fahrenheit. However, when precipitation does occur, its intensity increases with temperature to about 86 degrees Fahrenheit.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181061","collaboration":"Prepared in cooperation with the DuPage County Stormwater Management Department","usgsCitation":"Spies, R.R., Over, T.M., and Ortel, T.W., 2018, Comparison of NEXRAD multisensor precipitation estimates to rain gage observations in and near DuPage County, Illinois, 2002–12: U.S. Geological Survey Open-File Report 2018–1061, 30 p., https://doi.org/10.3133/ofr20181061. ","productDescription":"v, 30 p.","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-057485","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":354281,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1061/coverthb.jpg","text":"Report"},{"id":354282,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1061/ofr20181061.pdf","text":"Report","size":"5.61 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1061"}],"country":"United States","state":"Illinois","county":"DuPage County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.33,\n 41.5833\n ],\n [\n -87.8333,\n 41.5833\n ],\n [\n -87.8333,\n 42.1667\n ],\n [\n -88.33,\n 42.1667\n ],\n [\n -88.33,\n 41.5833\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
405 North Goodwin Avenue
Urbana, IL 61801
Brown bullhead (Ameiurus nebulosus) is a commonly used indicator species for tumor surveys at Great Lakes Areas of Concern. The “fish tumors or other deformities” is one of the beneficial use impairments at the Ashtabula River Area of Concern. In May 2016, 150 brown bullhead were collected in the lower Ashtabula River and 150 were collected in the nearby Conneaut Creek as a reference. Length, weight and external visible abnormalities were documented. Fish were euthanized, and skin lesions and liver tissue preserved for histopathological analyses. Otoliths were collected for age analyses. The percentage of bullhead with raised external lesions on lips, barbels and body surface was 34.7 percent at the Ashtabula River and 23.3 percent at Conneaut Creek. At the Ashtabula River, 26.7 percent of the bullhead collected had skin neoplasms, including papillomas, melanomas and squamous cell carcinomas, whereas at Conneaut Creek 18.6 percent had only papillomas, benign skin tumors. Liver neoplasms were observed in 7.3 percent of the bullhead from the Ashtabula River and 4.7 percent of those from Conneaut Creek. These neoplasms were observed in fish 6 years of age or older at both sites.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181072","usgsCitation":"Blazer, V.S., Walsh, H.L., and Braham, R.P.. 2018 Assessment of skin and liver neoplasms in brown bullhead (Ameiurus nebulosus) collected at the Ashtabula River Area of Concern and associated reference site, Ohio, in 2016: U.S. Geological Survey Open-File Report 2018-1072, 18 p., https://doi.org/10.3133/ofr20181072.","productDescription":"v, 18 p.","numberOfPages":"29","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-094847","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":354298,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1072/ofr20181072.pdf","text":"Report","size":"6.91 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1072"},{"id":354297,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1072/coverthb.jpg"}],"country":"United States","state":"Ohio","otherGeospatial":"Ashtabula River","contact":"Director, Eastern Ecological Science Center
U.S. Geological Survey
11649 Leetown Road
Kearneysville, WV 25430
Operable Unit 2, Area 8, at Naval Base Kitsap, Keyport is the site of a former chrome-plating facility that released metals (primarily chromium and cadmium), chlorinated volatile organic compounds, and petroleum compounds into the local environment. To ensure long-term protectiveness, as stipulated in the Fourth Five-Year Review for the site, Naval Facilities Engineering Command Northwest collaborated with the U.S. Environmental Protection Agency, the Washington State Department of Ecology, and the Suquamish Tribe, to collect data to monitor the contamination left in place and to ensure the site does not pose a risk to human health or the environment. To support these efforts, refined information was needed on the interaction of fresh groundwater with seawater in response to the up-to 13-ft tidal fluctuations at this nearshore site adjacent to Port Orchard Bay. The information was analyzed to meet the primary objective of this investigation, which was to determine the optimal time during the semi-diurnal and the neap-spring tidal cycles to sample groundwater for freshwater contaminants in Area 8 monitoring wells.
Groundwater levels and specific conductance in five monitoring wells, along with marine water-levels (tidal levels) in Port Orchard Bay, were monitored every 15 minutes during a 3-week duration to determine how nearshore groundwater responds to tidal forcing. Time series data were collected from October 24, 2017, to November 16, 2017, a period that included neap and spring tides. Vertical profiles of specific conductance were also measured once in the screened interval of each well prior to instrument deployment to determine if a freshwater/saltwater interface was present in the well during that particular time.
The vertical profiles of specific conductance were measured only one time during an ebbing tide at approximately the top, middle, and bottom of the saturated thickness within the screened interval of each well. The landward-most well, MW8-8, was completely freshwater, while one of the most seaward wells, MW8-9, was completely saline. A distinct saltwater interface was measured in the three other shallow wells (MW8-11, MW8-12, and MW8-14), with the topmost groundwater occurring fresh underlain by higher conductivity water.
Lag times between minimum spring-tide level and minimum groundwater levels in wells ranged from about 2 to 4.5 hours in the less-than 20-ft deep wells screened across the water table, and was about 7 hours for the single 48-ft deep well screened below the water table. Those lag times were surprisingly long considering the wells are all located within 200-ft of the shoreline and the local geology is largely coarse-grained glacial outwash deposits. Various manmade subsurface features, such as slurry walls and backfilled excavations, likely influence and confuse the connectivity between seawater and groundwater.
The specific-conductance time-series data showed clear evidence of substantial saltwater intrusion into the screened intervals of most shallow wells. Unexpectedly, the intrusion was associated with the neap part of the tidal cycle around November 13–16, when relatively low barometric pressure and high southerly winds led to the highest high and low tides measured during the monitoring period. The data consistently indicated that the groundwater had the lowest specific conductance (was least mixed with seawater) during the prior neap tides around October 30, the same period when the shallow groundwater levels were lowest. Although the specific conductance response is somewhat different between wells, the data do suggest that it is the heights of the actual high-high and low-low tides, regardless of whether or not they occur during the neap or spring part of the cycle, that allows seawater intrusion into the nearshore aquifer at Area 8.
With all the data taken into consideration, the optimal time for sampling the shallow monitoring wells at Area 8 would be centered on a 2–5-hour period following the predicted low-low tide during neap tide, with due consideration of local atmospheric pressure and wind conditions that have the potential to generate tides that can be substantially higher than those predicted from lunar-solar tidal forces. The optimal time for sampling the deeper monitoring wells at Area 8 would be during the 6–8-hour period following a predicted low-low tide, also during the neap tide part of the tidal cycle. The specific time window to sample each well following a low tide can be found in table 5. Those periods are when groundwater in the wells is most fresh and least diluted by seawater intrusion. In addition to timing, consideration should be given to collecting undisturbed samples from the top of the screened interval (or top of the water table if below the top of the interval) to best characterize contaminant concentrations in freshwater. A downhole conductivity probe could be used to identify the saltwater interface, above which would be the ideal depth for sampling.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181082","collaboration":"Prepared in cooperation with the Department of the Navy, Naval Facilities Engineering Command, Northwest","usgsCitation":"Opatz, C.C., and Dinicola, R.S., 2018, Analysis of groundwater response to tidal fluctuations, Operable Unit 2, Area 8, Naval Base Kitsap, Keyport, Washington: U.S. Geological Survey Open-File Report 2018-1082, 20 p., https://doi.org/10.3133/ofr20181082.","productDescription":"Report: iv, 20 p.","onlineOnly":"Y","ipdsId":"IP-095017","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":354378,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1082/coverthb.jpg"},{"id":354379,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1082/ofr20181082.pdf","text":"Report","size":"3.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1082"},{"id":358998,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7JW8D5S","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Groundwater and Tidal Time Series Data, Operable Unit 2, Area 8, Naval Base Kitsap, Keyport, Washington"}],"country":"United States","state":"Washington","city":"Keyport","otherGeospatial":"Naval Base Kitsap","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.64913558959962,\n 47.683072220525\n ],\n [\n -122.59180068969725,\n 47.683072220525\n ],\n [\n -122.59180068969725,\n 47.72627665811123\n ],\n [\n -122.64913558959962,\n 47.72627665811123\n ],\n [\n -122.64913558959962,\n 47.683072220525\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402
Populations of Northern Spotted Owls (Strix occidentalis caurina; hereinafter referred to as Spotted Owl) are declining throughout this subspecies’ geographic range. Evidence indicates that competition with invading populations of Barred Owls (S. varia) has contributed significantly to those declines. A pilot study in California showed that localized removal of Barred Owls coupled with conservation of suitable forest conditions can slow or even reverse population declines of Spotted Owls. It remains unknown, however, whether similar results can be obtained in areas with different forest conditions, greater densities of Barred Owls, and fewer remaining Spotted Owls. During 2015–17, we initiated a before-after-control-impact (BACI) experiment at three study areas in Oregon and Washington to determine if removal of Barred Owls can improve population trends of Spotted Owls. Each study area had at least 20 years of pre-treatment demographic data on Spotted Owls, and represented different forest conditions occupied by the two owl species in the Pacific Northwest. This report describes research accomplishments and preliminary results from the first 2.5 years (March 2015–August 2017) of the planned 5-year experiment.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181086","usgsCitation":"Wiens, J.D., Dugger, K.M., Lesmeister, D.B., Dilione, K.E., and Simon, D.C., 2018, Effects of experimental removal of Barred Owls on population demography of Northern Spotted Owls in Washington and Oregon—2017 progress report: U.S. Geological Survey Open-File Report 2018–1086, 23 p., https://doi.org/10.3133/ofr20181086.","productDescription":"iv, 23 p.","onlineOnly":"Y","ipdsId":"IP-095904","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":354381,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1086/ofr20181086.pdf","text":"Report","size":"2.5","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1086"},{"id":354380,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1086/coverthb.jpg"}],"country":"United 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\"}}]}","contact":"Director, Forest and Rangeland Ecosystem Science Center
U.S. Geological Survey
777 NW 9th St., Suite 400
Corvallis, Oregon 97330
Crab Orchard Lake in southern Illinois is one of the largest and most popular recreational lakes in the state. Construction of the nearly 7,000-acre reservoir in the late 1930s created employment opportunities through the Works Progress Administration, and the lake itself was intended to supply water, control flooding, and provide recreational opportunities for local communities (Stall, 1954). In 1942, the Department of War appropriated or purchased more than 20,000 acres of land around Crab Orchard Lake and constructed the Illinois Ordnance Plant, which manufactured bombs and anti-tank mines during World War II. After the war, an Act of Congress transferred the property to the U.S. Department of the Interior. Crab Orchard National Wildlife Refuge was established on August 5, 1947, for the joint purposes of wildlife conservation, agriculture, recreation, and industry. Production of explosives continued, but new industries also moved onsite. More than 200 tenants have held leases with Crab Orchard National Wildlife Refuge and have operated a variety of manufacturing plants (electrical components, plated metal parts, ink, machined parts, painted products, and boats) on-site. Soils, water, and sediments in several areas of the refuge were contaminated with hazardous substances from handling and disposal methods that are no longer acceptable environmental practice (for example, direct discharge to surface water, use of unlined landfills).
Polychlorinated biphenyl (PCB) contamination at the refuge was identified in the 1970s, and a PCB-based fish-consumption advisory has been in effect since 1988 for Crab Orchard Lake. The present advisory covers common carp (Cyprinus carpio) and channel catfish (Ictalurus punctatus); see Illinois Department of Public Health (2017). Some of the most contaminated areas of the refuge were actively remediated, and natural ecosystem recovery processes are expected to further reduce residual PCB concentrations in the lake. The U.S. Fish and Wildlife Service sought technical support to understand environmental drivers of current (2017) PCB residues in fish tissue and patterns in PCB residues through time to inform the fish-consumption advisory for Crab Orchard Lake. This project is planned in two phases (Tasks 1 and 2); the first phase is included in this report.
When Task 1 and Task 2 are complete, resource managers will have (a) a synthesis of existing literature that characterizes the processes influencing the fate of residual PCBs remaining in systems such as Crab Orchard Lake, (b) a summary of natural PCB attenuation processes for use in risk communication with the public, and (c) a summary of existing data on PCBs in fish tissues from Crab Orchard Lake, including exploratory plots of tissue residues through time. Overall, this project will provide data to help resource managers better understand the ecological and public health consequences of residual PCBs in Crab Orchard Lake.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181006","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Kunz, B.K., Hinck, J.E., Calfee, R.D., Linder, G.L., and Little, E.E., 2017, Science support for evaluating natural recovery of polychlorinated biphenyl concentrations in fish from Crab Orchard Lake, Crab Orchard National Wildlife Refuge, Illinois: U.S. Geological Survey Open-File Report 2018–1006, 20 p., https://doi.org/10.3133/ofr20181006.","productDescription":"vi, 20 p.","numberOfPages":"30","onlineOnly":"Y","ipdsId":"IP-084872","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":353853,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1006/ofr20181006.pdf","text":"Report","size":"10.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018–1006"},{"id":353852,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1006/coverthb2.jpg"}],"country":"United States","state":"Illinois","otherGeospatial":"Crab Orchard Lake, Crab Orchard National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.025,\n 37.6833\n ],\n [\n -89.0083,\n 37.6833\n ],\n [\n -89.0083,\n 37.6958\n ],\n [\n -89.025,\n 37.6958\n ],\n [\n -89.025,\n 37.6833\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Columbia Environmental Research Center
U.S. Geological Survey
4200 New Haven Road
Columbia, MO 65201
Polar bears (Ursus maritimus) in Alaska use the Arctic National Wildlife Refuge (ANWR) for maternal denning. Pregnant bears den in snow banks for more than 3 months in winter during which they give birth to and nurture young. Denning is one of the most vulnerable times in polar bear life history as the family group cannot simply walk away from a disturbance without jeopardizing survival of newly born cubs. The ANWR includes the “1002 Area”, a region recently opened for oil and gas exploration by the U.S. Department of the Interior (DOI). As a part of its mission, the DOI “… protects and manages the Nation's natural resources …” and is therefore responsible for conserving polar bears and encouraging development of energy potential. Because future industrial activities could overlap habitats used by denning polar bears, identifying these habitats can inform the decisions of resource managers tasked to develop resources and protect polar bears. To help inform these efforts, we qualitatively compared the distribution of denning habitat identified by two different methods: previously published habitat from manual interpretation of aerial photographs, and habitat derived by computer interrogation of interferometric synthetic aperture radar (IfSAR) digital terrain models (DTM). Because photograph-interpreted methods depicted denning habitat as a line and IfSAR-derived methods depicted habitat as a polygon, we assessed agreement between the two methods with distance measurements. We found that 77.5 percent of IfSAR-derived denning habitat (79.6 km2 ; 1.2 percent of the 6,837.0 km2 1002 Area) was within 600 m of photograph-interpreted habitat (3,026.9 km), including 53.9 percent within 200 m. This distribution differed from that of randomly distributed points, as only 49.4 percent of these occurred within 600 m of photograph-interpreted habitat, including 18.3 percent within 200 m. Both methods appear to identify the major physiographic features that polar bears might select for denning. IfSAR-derived methods identified habitat at greater frequency beyond major landscape features such as coastal bluffs, river banks and lakeshores, were more likely to identify isolated pockets of putative denning habitat, and were easier to implement than deriving habitat from photograph-interpretive efforts. However, previous research suggests that photograph-interpretation methods may identify denning habitat more correctly than computer interrogation of IfSAR DTMs. Future work should quantify the distribution of IfSAR-derived denning habitat relative to actual landscape features and polar bear maternal dens in the 1002 Area, and investigate the feasibility of habitat identification from finer grained DTMs.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181083","usgsCitation":"Durner, G.M., and Atwood, T.C., 2018, A comparison of photograph-interpreted and IfSAR-derived maps of polar bear denning habitat for the 1002 Area of the Arctic National Wildlife Refuge, Alaska: U.S. Geological Survey Open-File Report 2018–1083, 12 p., https://doi.org/10.3133/ofr20181083.","productDescription":"Report: iv, 12 p.; Data Release","numberOfPages":"20","onlineOnly":"Y","ipdsId":"IP-095475","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":354103,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7DJ5DXT","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Data used to compare photo-interpreted and IfSAR-derived maps of polar bear denning habitat for the 1002 Area of the Arctic National Wildlife Refuge, Alaska, 2006-2016"},{"id":354102,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1083/ofr20181083.pdf","text":"Report","size":"3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1083"},{"id":354101,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1083/coverthb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -146.5,\n 69.5\n ],\n [\n -142,\n 69.5\n ],\n [\n -142,\n 70.25\n ],\n [\n -146.5,\n 70.25\n ],\n [\n -146.5,\n 69.5\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Alaska Science Center
U.S. Geological Survey
4230 University Drive
Anchorage, Alaska 99508
The California Department of Water Resources and Bureau of Reclamation propose new water intake facilities on the Sacramento River in northern California that would convey some of the water for export to areas south of the Sacramento-San Joaquin River Delta (hereinafter referred to as the Delta) through tunnels rather than through the Delta. The collection of water intakes, tunnels, pumping facilities, associated structures, and proposed operations are collectively referred to as California WaterFix. The water intake facilities, hereinafter referred to as the North Delta Diversion (NDD), are proposed to be located on the Sacramento River downstream of the city of Sacramento and upstream of the first major river junction where Sutter Slough branches from the Sacramento River. The NDD can divert a maximum discharge of 9,000 cubic feet per second (ft3 /s) from the Sacramento River, which reduces the amount of Sacramento River inflow into the Delta.
In this report, we conduct four analyses to investigate the effect of the NDD and its proposed operation on survival of juvenile Chinook salmon (Oncorhynchus tshawytscha). All analyses used the results of a Bayesian survival model that allowed us to simulate travel time, migration routing, and survival of juvenile Chinook salmon migrating through the Delta in response to NDD operations, which affected both inflows to the Delta and operation of the Delta Cross Channel (DCC).
For the first analysis, we evaluated the effect of the NDD bypass rules on salmon survival. The NDD bypass rules are a set of operational rule curves designed to provide adaptive levels of fish protection by defining allowable diversion rates as a function of (1) Sacramento River discharge as measured at Freeport, and (2) time of year when endangered runs requiring the most protection are present. We determined that all bypass rule curves except constant low-level pumping (maximum diversion of 900 ft3 /s) could cause a sizeable decrease in survival by as much as 6–10 percentage points. The maximum decrease in survival occurred at an intermediate Sacramento River flow of about 20,000–30,000 ft3 /s. Diversion rates increased rapidly as Sacramento River flows increased from 20,000 ft3 /s to 30,000 ft3 /s, until a maximum diversion rate was reached at 9,000 ft3 /s. Because through-Delta survival increases sharply over this range of Sacramento River flow before beginning to level off with further flow increases, increasing diversion rates over this flow range causes a large decrease in survival relative to no diversion.
For the second analysis, we applied the survival model to 82 years of daily simulated flows under the Proposed Action (PA) and No Action Alternative (NAA). The PA includes operation of the Central Valley Project/State Water Project with implementation of the NDD and its operations prescribed by the NDD bypass rules, whereas the NAA assumes system operations without implementation of the NDD. We also evaluated a “Level 1” (L1) scenario, which was similar to the PA scenario but applied the most protective bypass rule known as Level 1 post-pulse operations. We noted a high probability that survival under the PA scenario was lower than under the NAA scenario, and that travel time was longer under PA relative to NAA in most simulation years. However, the largest survival differences between the PA and NAA scenarios occurred during October–November and May–June. Although bypass rules are less restrictive during these periods, we determined that more frequent use of the DCC under PA led to the largest differences in survival between the two scenarios. Additionally, we noted no difference in median survival decreases between the PA and L1 scenarios, although in some years the L1 scenario had a lower survival decrease than the PA scenario.
For the third analysis, we proposed a quantitative approach for developing NDD rule curves (that is, prescribed diversion flows for given inflows) by using the survival model to identify diversion rates that meet a criterion of a having a small probability of exceeding a given decrease in survival. We examined diversion rates that led to a 10% chance of exceeding a given decrease in survival for a range of absolute and relative decreases in survival. To maintain a given constant level of protection across the range of river flows, our analysis indicated that diversions had to increase at a much slower rate with respect to Sacramento River flow relative to the rule curves defined in the NDD bypass table. Additionally, we determined that diversion rates could be higher than under the bypass table rule curves at river flows less than 20,000 ft3 /s, but diversions had to be less than defined by NDD bypass rules at higher flows.
For the fourth analysis, we simulated the effect of “real-time operations” on salmon survival, where bypass flow rates were determined by the presence of juvenile salmon entering the Delta, as indicated by juvenile salmon catch in a rotary screw trap upstream of the Delta. For this analysis, we evaluated NDD operations as defined by the L1 scenario and an additional scenario (Unlimited Pulse Protection [UPP]) that provided protection to an unlimited number of fish pulses. This analysis indicated that the highest catches occurred during flow pulses when daily survival was high, which caused annual survival to be weighted towards periods of high daily survival, resulting in a high annual survival. We determined that the mean annual survival decreased by 1–4 percentage points, and annual survival decreases were more frequently smaller for the UPP scenario. Additionally, because the UPP scenario protected an unlimited number of fish pulses, decreases in daily survival under the UPP scenario were less than under the L1 scenario.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181078","collaboration":"Prepared in cooperation with National Oceanic and Atmospheric Administration, National Marine Fisheries Service","usgsCitation":"Perry, R.W., and Pope, A.C., 2018, Effects of the proposed California WaterFix North Delta Diversion on survival of juvenile Chinook salmon (Oncorhynchus tshawytscha) in the Sacramento-San Joaquin River Delta, northern California: U.S. Geological Survey Open-File Report 2018-1078, 94 p. plus appendixes,\nhttps://doi.org/10.3133/ofr20181078.","productDescription":"Report: x, 94 p.; 11 Appendixes","numberOfPages":"108","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-095992","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":354085,"rank":9,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2018/1078/ofr20181078_appendix07.pdf","text":"Appendix 7","size":"1.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1078 Appendix 7","linkHelpText":"Simulated daily travel time by year, no action alternative compared to level 1 scenarios, 1922-2003"},{"id":354087,"rank":11,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2018/1078/ofr20181078_appendix09.pdf","text":"Appendix 9","size":"2.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1078 Appendix 9","linkHelpText":"Simulated route-specific survival by year, no action alternative compared to level 1 scenarios, 1922-2003"},{"id":354077,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1078/coverthb.jpg"},{"id":354078,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1078/ofr20181078.pdf","text":"Report","size":"18.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1078"},{"id":354079,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2018/1078/ofr20181078_appendix01.pdf","text":"Appendix 1","size":"1.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1078 Appendix 1","linkHelpText":"Simulated daily survival by year, no action alternative compared to proposed action scenarios, 1922-2003"},{"id":354086,"rank":10,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2018/1078/ofr20181078_appendix08.pdf","text":"Appendix 8","size":"2.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1078 Appendix 8","linkHelpText":"Simulated daily routing by year, no action alternative compared to level 1 scenarios, 1922-2003"},{"id":354080,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2018/1078/ofr20181078_appendix02.pdf","text":"Appendix 2","size":"1.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1078 Appendix 2","linkHelpText":"Simulated daily travel time by year, no action alternative compared to proposed action scenarios, 1922-2003"},{"id":354081,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2018/1078/ofr20181078_appendix03.pdf","text":"Appendix 3","size":"2.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1078 Appendix 3","linkHelpText":"Simulated daily routing by year, no action alternative compared to proposed action scenarios, 1922-2003"},{"id":354082,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2018/1078/ofr20181078_appendix04.pdf","text":"Appendix 4","size":"2.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1078 Appendix 4","linkHelpText":"Simulated route-specific survival by year, no action alternative compared to PA scenarios, 1922-2003"},{"id":354083,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2018/1078/ofr20181078_appendix05.pdf","text":"Appendix 5","size":"2.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1078 Appendix 5","linkHelpText":"Simulated route-specific travel time by year, no action alternative compared to PA scenarios, 1922-2003"},{"id":354084,"rank":8,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2018/1078/ofr20181078_appendix06.pdf","text":"Appendix 6","size":"1.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1078 Appendix 6","linkHelpText":"Simulated daily survival by year, no action alternative compared to level 1 scenarios, 1922-2003"},{"id":354088,"rank":12,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2018/1078/ofr20181078_appendix10.pdf","text":"Appendix 10","size":"2.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1078 Appendix 10","linkHelpText":"Simulated route-specific travel time by year, no action alternative compared to level 1 scenarios, 1922-2003"},{"id":354089,"rank":13,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2018/1078/ofr20181078_appendix11.pdf","text":"Appendix 11","size":"2.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1078 Appendix 11","linkHelpText":"North Delta Diversion rule curve optimization"}],"country":"United States","state":"California","otherGeospatial":"Sacramento-San Joaquin River Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.33,\n 37.82\n ],\n [\n -121.33,\n 38.5\n ],\n [\n -121.9167,\n 38.5\n ],\n [\n -121.9167,\n 37.82\n ],\n [\n -121.33,\n 37.82\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115
This is the ninth annual report highlighting U.S. Geological Survey (USGS) science and decision-support activities conducted for the Wyoming Landscape Conservation Initiative (WLCI). The activities address specific management needs identified by WLCI partner agencies. In fiscal year (FY) 2016, there were 26 active USGS WLCI science-based projects. Of these 26 projects, one project was new for FY2016, and three were completed by the end of the fiscal year (though final products were still in preparation or review). USGS WLCI projects were grouped under five categories: (1) Baseline Synthesis, (2) Long-Term Monitoring, (3) Effectiveness Monitoring, (4) Mechanistic Studies of Wildlife, and (5) Data and Information Management. Each of these topic areas is designed to address WLCI management needs: identifying key drivers of change, identifying the condition and distribution of key wildlife species and habitats and of species’ habitat requirements, development of an integrated inventory and monitoring strategy, use of emerging technologies and development and testing of innovative methods for maximizing the efficiency and efficacy of monitoring efforts, evaluating the effectiveness of habitat treatment projects, evaluating the responses of wildlife to development, and developing a data clearinghouse and information management framework to support and provide access to results of most USGS WLCI projects.
In FY2016, we assisted with updating the WLCI Conservation Action Plan and associated databases as part of the Comprehensive Assessment, and we also assisted with the Bureau of Land Management 2015 WLCI annual report. By the end of FY2016, we completed or had nearly completed assessments of WLCI energy and mineral resources and had submitted a manuscript on modeled effects of oil and gas development on wildlife to a peer-reviewed journal. We also initiated a study on the effects of wind energy on wildlife in the WLCI region. A USGS circular on WLCI long-term monitoring was in review at the end of the fiscal year, and seven projects monitoring water and vegetation (including changes in sagebrush cover and patterns of sagebrush mortality) continued through the year. USGS scientists continued many projects in FY2016 that evaluate the effectiveness of habitat conservation actions (including sagebrush, cheatgrass, and aspen habitat treatments) and provide tools in support of mechanistic studies of wildlife. In FY2016, USGS scientists, along with university and State partners, continued work on five focal wildlife species/communities (pygmy rabbits [Brachylagus idahoensis], greater sage grouse , mule deer, sagebrush songbirds, and native fish). In FY2016, the USGS Information Management Team presented information to WLCI scientists on how USGS tools and resources can be used to fulfill the requirements of new USGS policies regarding data release, data management, and data visualization.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181048","usgsCitation":"Bowen, Z.H., Aikens, E., Aldridge, C.L., Anderson, P.J., Assal, T.J., Chalfoun, A.D., Chong, G.W., Eddy-Miller, C.A., Garman, S.L., Germaine, S.S., Homer, C.G., Johnston, A., Kauffman, M.J., Manier, D.J., Melcher, C.P., Miller, K.A., Walters, A.W., Wheeler, J.D., Wieferich, D., Wilson, A.B., Wyckoff, T.B., and Zeigenfuss, L.C., 2018, U.S. Geological Survey science for the Wyoming Landscape Conservation Initiative—2016 annual report: U.S. Geological Survey Open-File Report 2018–1048, 49 p., https://doi.org/10.3133/ofr20181048.","productDescription":"vii, 49 p.","onlineOnly":"Y","ipdsId":"IP-091604","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science 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Fort Collins Science Center
U.S. Geological Survey
2150 Centre Ave., Building C
Fort Collins, CO 80526-8118
Lahars large enough to reach populated areas are a hazard at Mount Adams, a massive volcano in the southern Cascade Range of Washington State (fig. 1). It is considered to be still active and has the potential to erupt again. By definition, lahars are gravity-driven flows of water-saturated mixtures of mud and rock (plus or minus ice, wood, and other debris), which originate from volcanoes and have a variety of potential triggering mechanisms (Vallance, 2000; Vallance and Iverson, 2015). Flowing mixtures can range in fluid consistency from something like a milkshake to something more like wet concrete, and they behave like flash floods, in that they can appear suddenly in river channels with little warning and commonly have boulder- or log-choked flow fronts. Lahars are hazardous because they can flow rapidly in confined valleys (commonly 20–35 miles per hour [mph] or 9–16 meters per second [m/s]), can travel more than 100 miles (mi) (161 kilometers [km]) from a source volcano, and can move with incredible destructive force, carrying multi-ton boulders and logs that can act as battering rams (Pierson, 1998). The biggest threats from lahars to downstream communities are present during eruptive activity, and impacts to communities can be dire. For example, a very large eruption-triggered lahar in Colombia in 1985 surprised and killed more than 20,000 people in a large town located about 45 mi (72 km) downstream and out of sight of the volcano that produced it (Pierson and others, 1990).
Mount Adams, one of the largest volcanoes in the Cascade Range, is a composite stratocone composed primarily of andesite lava flows. It has been the most continuously active volcano within the 480-mi2 Mount Adams volcanic field—a region covering parts of Klickitat, Skamania, Yakima, andLewis Counties and part of the Yakama Nation Reservation in Washington State (Hildreth and Fierstein,1995, 1997). About 500,000 years in age, Mount Adams reached its present size by about 15,000 years ago, primarily through the episodic effusion of lava flows; it has not had a history of major explosive eruptions like Mount St. Helens, its neighbor to the west. Timing of the most recent eruptive activity (recorded by four thin tephra layers) is on the order of 1,000 years ago; the tephras are bracketed by 2,500-year-old and 500-year-old ash layers from Mount St. Helens (Hildreth and Fierstein, 1995, 1997). Mount Adams currently shows no signs of renewed unrest.
Eruptive history does not tell us everything we need to know about hazards at Mount Adams, however, which are fully addressed in the volcano hazard assessment for Mount Adams (W.E. Scott and others, 1995). This volcano has had a long-active hydrothermal system that circulated acidic hydrothermal fluids, formed by the solution of volcanic gases in heated groundwater, through fractures and permeable zones into upper parts of the volcanic cone. Acid sulfate leaching of rocks in the summit area may still be occurring, but chemical and thermal evidence suggests that the main hydrothermal system is no longer active at Mount Adams (Nathenson and Mariner, 2013). However, these rock-weakening chemical reactions have operated long enough to change about 0.4 cubic miles (mi3) (1.7 cubic kilometers [km3]) of the hard lava rock in the volcano’s upper cone to a much weaker clay-rich rock, thus significantly reducing rock strength and thereby slope stability in parts of the cone (Finn and others, 2007). The two largest previous lahars from Mount Adams were triggered by landslides of hydrothermally altered rock from the upper southwestern flank of the cone, and any future large lahars are likely to be triggered by the same mechanism. Mount Rainier also has had extensive hydrothermal alteration of rock in its upper edifice, and it also has a history of large landslides that transform into lahars (K.M. Scott and others, 1995; Vallance and Scott, 1997; Reid and others, 2001).
The spatial depiction of modeled lahar inundation zones accompanying this report, shown in two different map perspectives, is intended to augment (not replace) the existing hazard maps for Mount Adams (W.E. Scott and others, 1995; Vallance, 1999). The maps in this report show potential areas of inundation by lahars of different initial volumes, which are determined by a computer model, LAHARZ (Iverson and others, 1998; Schilling, 1998). One map sheet presents LAHARZ-determined inundation areas on a normal plan-view shaded-relief map of the study area; the other gives an oblique perspective of the landscape with raised topography, as if one were viewing the landscape at an angle from an aircraft (Jenny and Patterson, 2007). LAHARZ was developed after the original hazard maps (based only on mapping of geologic deposits) were made. Predicted inundation zones on these maps provide an alternative approach to estimation of areas that could be inundated as lahars of different volumes pass through the valley. However, there is considerable uncertainty in the exact location of the hazard-zone boundaries shown on these maps, as well as on earlier maps.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181013","usgsCitation":"Griswold, J.P., Pierson, T.C., and Bard J.A., 2018, Modeled inundation limits of potential lahars from Mount Adams in the White Salmon River valley, Washington: U.S. Geological Survey Open-File Report 2018–1013, scale 1:75,000, 14 p., https://doi.org/10.3133/ofr20181013.","productDescription":"Sheet: 42.0 x 42.0 inches; Pamphlet: iii, 14 p.","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-078093","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":353953,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1013/ofr20181013_pamphlet.pdf","text":"Pamphlet","size":"18.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1013 Pamphlet"},{"id":353952,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2018/1013/ofr20181013_sheet_.pdf","size":"41 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1013"},{"id":353951,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1013/coverthb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Mount Adams, While Salmon River Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.8333,\n 45.682198608003404\n ],\n [\n -121.25,\n 45.682198608003404\n ],\n [\n -121.25,\n 46.25\n ],\n [\n -121.8333,\n 46.25\n ],\n [\n -121.8333,\n 45.682198608003404\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Volcano Science Center
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Vancouver, WA, 98683
Groundwater is an important source of drinking and irrigation water throughout Idaho, and groundwater quality is monitored by various Federal, State, and local agencies. The historical, multi-agency records of groundwater quality include a valuable dataset that has yet to be compiled or analyzed on a statewide level. The purpose of this study is to combine groundwater-quality data from multiple sources into a single database, to summarize this dataset, and to perform bulk analyses to reveal spatial and temporal patterns of water quality throughout Idaho. Data were retrieved from the Water Quality Portal (https://www.waterqualitydata.us/), the Idaho Department of Environmental Quality, and the Idaho Department of Water Resources. Analyses included counting the number of times a sample location had concentrations above Maximum Contaminant Levels (MCL), performing trends tests, and calculating correlations between water-quality analytes. The water-quality database and the analysis results are available through USGS ScienceBase (https://doi.org/10.5066/F72V2FBG).
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\"}}]}","contact":"Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Road
Boise, Idaho 83702
SBSC Staff,
Southwest Biological Science Center
U.S. Geological Survey
2255 N. Gemini Drive
Flagstaff, AZ 86001
Sand and oil agglomerates (SOAs) form when weathered oil reaches the surf zone and combines with suspended sediments. The presence of large SOAs in the form of thick mats (up to 10 centimeters [cm] in height and up to 10 square meters [m2] in area) and smaller SOAs, sometimes referred to as surface residual balls (SRBs), may lead to the re-oiling of beaches previously affected by an oil spill. A limited number of numerical modeling and field studies exist on the transport and dynamics of centimeter-scale SOAs and their interaction with the sea floor. Numerical models used to study SOAs have relied on shear-stress formulations to predict incipient motion. However, uncertainty exists as to the accuracy of applying these formulations, originally developed for sand grains in a uniformly sorted sediment bed, to larger, nonspherical SOAs. In the current effort, artificial sand and oil agglomerates (aSOAs) created with the size, density, and shape characteristics of SOAs were studied in a small-oscillatory flow tunnel. These experiments expanded the available data on SOA motion and interaction with the sea floor and were used to examine the applicability of shear-stress formulations to predict SOA mobility. Data collected during these two sets of experiments, including photographs, video, and flow velocity, are presented in this report, along with an analysis of shear-stress-based formulations for incipient motion. The results showed that shear-stress thresholds for typical quartz sand predicted the incipient motion of aSOAs with 0.5–1.0-cm diameters, but were inaccurate for aSOAs with larger diameters (>2.5 cm). This finding implies that modified parameterizations of incipient motion may be necessary under certain combinations of aSOA characteristics and environmental conditions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181010","usgsCitation":"Jenkins, R.L., Dalyander, P.S., Penko, Allison, and Long, J.W., 2018, Laboratory observations of artificial sand and oil agglomerates: U.S. Geological Survey Open-File Report 2018–1010, https://doi.org/10.3133/ofr20181010.","productDescription":"HTML","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-079703","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":353721,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1010","text":"Report HTML"},{"id":353720,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1010/coverthb2.jpg"}],"contact":"Director, St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
600 4th Street South
St. Petersburg, FL 33701
Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, CA 95819
San Francisco gartersnakes (Thamnophis sirtalis tetrataenia) are a subspecies of common gartersnakes endemic to the San Francisco Peninsula of northern California. Because of habitat loss and collection for the pet trade, San Francisco gartersnakes were listed as endangered under the precursor to the Federal Endangered Species Act. A population of San Francisco gartersnakes resides at Mindego Ranch, San Mateo County, which is part of the Russian Ridge Open Space Preserve owned and managed by the Midpeninsula Regional Open Space District (MROSD). Because the site contained non-native fishes and American bullfrogs (Lithobates catesbeianus), MROSD implemented management to eliminate or reduce the abundance of these non-native species in 2014. We monitored the population using capture-mark-recapture techniques to document changes in the population during and following management actions. Although drought confounded some aspects of inference about the effects of management, prey and San Francisco gartersnake populations generally increased following draining of Aquatic Feature 3. Continued management of the site to keep invasive aquatic predators from recolonizing or increasing in abundance, as well as vegetation management that promotes heterogeneous grassland/shrubland near wetlands, likely would benefit this population of San Francisco gartersnakes.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181063","collaboration":"Prepared in cooperation with the Midpeninsula Regional Open Space District","usgsCitation":"Kim, R., Halstead, B.J., Wylie, G.D., and Casazza, M.L., 2018, Distribution and demography of San Francisco gartersnakes (Thamnophis sirtalis tetrataenia) at Mindego Ranch, Russian Ridge Open Space Preserve, San Mateo County, California: U.S. Geological Survey Open-File Report 2018-1063, 80 p., https://doi.org/10.3133/ofr20181063.","productDescription":"viii, 80 p.","numberOfPages":"92","onlineOnly":"Y","ipdsId":"IP-093147","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":353746,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1063/coverthb.jpg"},{"id":353747,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1063/ofr20181063.pdf","text":"Report","size":"2.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1063"}],"country":"United States","state":"California","county":"San Mateo","otherGeospatial":"Mindego Ranch, Russian Ridge Open Space Preserve","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.25543022155762,\n 37.2960420634488\n ],\n [\n -122.22109794616699,\n 37.2960420634488\n ],\n [\n -122.22109794616699,\n 37.33065186897204\n ],\n [\n -122.25543022155762,\n 37.33065186897204\n ],\n [\n -122.25543022155762,\n 37.2960420634488\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
The goals of the USA National Phenology Network (USA-NPN, www.usanpn.org) are to advance science, inform decisions, and communicate and connect with the public regarding phenology and species’ responses to environmental variation and climate change. The USA-NPN seeks to advance the science of phenology and facilitate ecosystem stewardship by providing phenological information freely and openly. To accomplish these goals, the USA-NPN National Coordinating Office (NCO) delivers observational data on plant and animal phenology in several formats, including minimally processed status and intensity datasets and derived phenometrics for individual plants, sites, and regions. This document describes the suite of observational data products delivered by the USA National Phenology Network, covering the period 2009–present for the United States and accessible via the Phenology Observation Portal (http://dx.doi.org/10.5066/F78S4N1V) and via an Application Programming Interface. The data described here have been used in diverse research and management applications, including over 30 publications in fields such as remote sensing, plant evolution, and resource management.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181060","usgsCitation":"Rosemartin, A., Denny, E.G., Gerst, K.L., Marsh, R.L., Posthumus, E.E., Crimmins, T.M., and Weltzin, J.F., 2018, USA National Phenology Network observational data documentation: U.S. Geological Survey Open-File Report 2018–1060, 24 p., https://doi.org/10.3133/ofr20181060.","productDescription":"Report: vi, 24 p.; Appendix tables","numberOfPages":"30","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-085279","costCenters":[{"id":433,"text":"National Phenology Network","active":true,"usgs":true}],"links":[{"id":353663,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1060/coverthb.jpg"},{"id":353665,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2018/1060/ofr20181060_appendix1tables.zip","text":"Appendix 1 Tables","size":"67 KB","linkFileType":{"id":6,"text":"zip"},"description":"OFR 2018-1080 Appendix 1"},{"id":353664,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1060/ofr20181060.pdf","text":"Report","size":"1.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1080"}],"contact":"Director,
Ecosystems Mission Area
U.S. Geological Survey
12201 Sunrise Valley Dr., MS 300
Reston, VA 20192
Data from a long-term capture-recapture program were used to assess the status and dynamics of populations of two long-lived, federally endangered catostomids in Upper Klamath Lake, Oregon. Lost River suckers (LRS; Deltistes luxatus) and shortnose suckers (SNS; Chasmistes brevirostris) have been captured and tagged with passive integrated transponder (PIT) tags during their spawning migrations in each year since 1995. In addition, beginning in 2005, individuals that had been previously PIT-tagged were re-encountered on remote underwater antennas deployed throughout sucker spawning areas. Captures and remote encounters during the spawning season in spring 2016 were incorporated into capture-recapture analyses of population dynamics.
Cormack-Jolly-Seber (CJS) open population capture-recapture models were used to estimate annual survival probabilities, and a reverse-time analog of the CJS model was used to estimate recruitment of new individuals into the spawning populations. In addition, data on the size composition of captured fish were examined to provide corroborating evidence of recruitment. Model estimates of survival and recruitment were used to derive estimates of changes in population size over time and to determine the status of the populations through 2015. Separate analyses were done for each species and also for each subpopulation of LRS. Shortnose suckers and one subpopulation of LRS migrate into tributary rivers to spawn, whereas the other LRS subpopulation spawns at groundwater upwelling areas along the eastern shoreline of the lake.
Capture-recapture analyses indicated that with a few exceptions, the survival of males and females in both Lost River sucker subpopulations was high (greater than 0.88) from 1999 to 2015. Survival was notably lower for males from the river in 2000, 2006, and 2012, and for the shoreline areas in 2002. From 2001 to 2015, the abundance of males in the lakeshore spawning subpopulation decreased by at least 64 percent and the abundance of females decreased by at least 56 percent. Capture-recapture models suggested that the abundance of both sexes in the river spawning subpopulation of LRS had increased substantially since 2006; increases were mostly due to large estimated recruitment events in 2006 and 2008. We know that the estimates in 2006 are substantially biased in favor of recruitment because of a sampling issue. We are skeptical of the magnitude of recruitment indicated by the 2008 estimates as well because (1) few small individuals that would indicate the presence of new recruits were captured in that year, and (2) recapture probabilities in recruitment models based on just physical recaptures of fish were lower than desired for robust inferences from capture-recapture models. If we assume instead that little or no recruitment occurred for this subpopulation, the abundance of both sexes in the river spawning subpopulation likely has decreased at rates similar to the rates for the lakeshore spawning subpopulation from 2002 to 2015.
Shortnose suckers experienced lower and more variable annual survival than either LRS subpopulation. Annual survival of both sexes was relatively low in 2003, 2004, 2010, and 2012. In addition, female survival was low in 1999 and 2000 while male survival was low in 2002. Survival estimate precision in early years of the study; however, are poor. Capture-recapture models and size composition data indicate that recruitment of new individuals into the SNS spawning population was trivial from 2001 to 2005. Models indicate that more than 10 percent of the population was new recruits in a number of more recent years. As a result, capture-recapture modeling suggests that the abundance of adult spawning SNS was relatively stable from 2006 to 2010. We are skeptical of the estimated recruitment in 2006 because of the known sampling issue. We also are skeptical of the estimated recruitment in other recent years because few small individuals that would indicate the presence of new recruits were captured in any of those years, and recapture probabilities in recruitment models were low. The best-case scenario for SNS, based on capture-recapture recruitment modeling, indicates that the abundance of males in the spawning population decreased by 78 percent and the abundance of females decreased by 77 percent from 2001 to 2015. Decreases in abundance for both sexes are likely greater than these estimates indicate.
Despite relatively high survival in most years, we conclude that both species have experienced substantial decreases in the abundance of spawning adults because losses from mortality have not been balanced by recruitment of new individuals. Although capture-recapture data indicate substantial recruitment of new individuals into the spawning populations for SNS and river spawning LRS in some years, size data do not corroborate these estimates. As a result, the status of the endangered sucker populations in Upper Klamath Lake remains distressed, especially for SNS. Our monitoring program provides a robust platform for estimating vital population parameters, evaluating the status of the populations, and assessing the effectiveness of conservation and recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181064","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Hewitt, D.A., Janney, E.C., Hayes, B.S., and Harris, A.C., 2018, Status and trends of adult Lost River (Deltistes luxatus) and shortnose (Chasmistes brevirostris) sucker populations in Upper Klamath Lake, Oregon, 2017: U.S. Geological Survey Open-File Report 2018-1064, 31 p., https://doi.org/10.3133/ofr20181064.","productDescription":"iv, 31 p.","numberOfPages":"40","onlineOnly":"Y","ipdsId":"IP-096959","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":437938,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P97K04NO","text":"USGS data release","linkHelpText":"Status and trends of adult Lost River (Deltistes luxatus) and shortnose (Chasmistes brevirostris) sucker populations in Upper Klamath Lake, Oregon, 2023"},{"id":353417,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1064/coverthb.jpg"},{"id":353418,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1064/ofr20181064.pdf","text":"Report","size":"905 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1064"}],"country":"United States","state":"Oregon","otherGeospatial":"Upper Klamath Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.10067749023438,\n 42.21936476344714\n ],\n [\n -121.79992675781249,\n 42.21936476344714\n ],\n [\n -121.79992675781249,\n 42.61981257367216\n ],\n [\n -122.10067749023438,\n 42.61981257367216\n ],\n [\n -122.10067749023438,\n 42.21936476344714\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115
Seismic hazard assessments that are based on a variety of data and the best available science, coupled with rapid synthesis of real-time information from continuous monitoring networks to guide post-earthquake response, form a solid foundation for effective earthquake loss reduction. With this in mind, the Earthquake Hazards Program (EHP) of the U.S. Geological Survey (USGS) Natural Hazards Mission Area (NHMA) engages in a variety of undertakings, both established and emergent, in order to provide high quality products that enable stakeholders to take action in advance of and in response to earthquakes. Examples include the National Seismic Hazard Model (NSHM), development of tools for improved situational awareness such as earthquake early warning (EEW) and operational earthquake forecasting (OEF), research about induced seismicity, and new efforts to advance comprehensive subduction zone science and monitoring. Geodetic observations provide unique and complementary information directly relevant to advancing many aspects of these efforts (fig. 1). EHP scientists have long leveraged geodetic data for a range of influential studies, and they continue to develop innovative observation and analysis methods that push the boundaries of the field of geodesy as applied to natural hazards research. Given the ongoing, rapid improvement in availability, variety, and precision of geodetic measurements, considering ways to fully utilize this observational resource for earthquake loss reduction is timely and essential. This report presents strategies, and the underlying scientific rationale, by which the EHP could achieve the following outcomes:
A geodesy program that encompasses a balanced mix of activities to sustain missioncritical capabilities, grows new competencies through the continuum of fundamental to applied research, and ensures sufficient resources for these endeavors provides a foundation by which the EHP can be a leader in the application of geodesy to earthquake science. With this in mind the following objectives provide a framework to guide EHP efforts:
Maintaining a vibrant internal research program provides the foundation by which the EHP can remain an effective and trusted source for earthquake science. Exploiting abundant new data sources, evaluating and assimilating the latest science, and pursuing novel avenues of investigation are means to fulfilling the EHP’s core responsibilities and realizing the important scientific advances envisioned by its scientists. Central to the success of such a research program is engaging personnel with a breadth of competencies and a willingness and ability to adapt these to the program’s evolving priorities, enabling current staff to expand their skills and responsibilities, and planning holistically to meet shared workforce needs.
In parallel, collaboration with external partners to support scientific investigations that complement ongoing internal research enables the EHP to strengthen earthquake information products by incorporating alternative perspectives and approaches and to study topics and geographic regions that cannot be adequately covered internally.
With commensurate support from technical staff who possess diverse skills, including engineering, information technology, and proficiency in quantitative analysis combined with basic geophysical knowledge, the EHP can achieve the geodetic outcomes identified in this document.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181037","usgsCitation":"Murray, J.R., Roeloffs, E.A., Brooks, B.A., Langbein, J., Leith, W., Minson, S.E., Svarc, J., and Thatcher, W., 2018, Leveraging geodetic data to reduce losses from earthquakes: U.S. Geological Survey Open-File Report 2018–1037, 34 p., https://doi.org/10.3133/ofr20181037.","productDescription":"vi, 34 p.","numberOfPages":"43","onlineOnly":"Y","ipdsId":"IP-089859","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":353651,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1037/coverthb.jpg"},{"id":353652,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1037/ofr20181037.pdf","text":"Report","size":"2.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1037"}],"contact":"Contact Information, Menlo Park, Calif.
Office—Earthquake Science Center
U.S. Geological Survey
345 Middlefield Road, MS 977
Menlo Park, CA 94025
https://earthquake.usgs.gov/
In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within the 3-nautical-mile limit of California’s State Waters. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data, acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow subsurface geology.
The Offshore of Point Conception map area is in the westernmost part of the Western Transverse Ranges geologic province, which is north of the California Continental Borderland. Significant clockwise rotation—at least 90°—since the early Miocene has been proposed for the Western Transverse Ranges province, and this region is presently undergoing north-south shortening. The offshore part of the map area lies south of the steep south and west flanks of the Santa Ynez Mountains. The crest of the range, which has a maximum elevation of about 340 m in the map area, lies about 5 km north and east of the arcuate shoreline.
The onland part of the coastal zone is remote and sparsely populated. The road to Jalama Beach County Park provides the only public coastal access in the entire map area. North of this county park, the coastal zone is part of Vandenberg Air Force Base. South of Jalama Beach County Park, most of the coastal zone is part of the Cojo-Jalama Ranch, purchased by the Nature Conservancy in December 2017. A relatively small part of the coastal zone in the eastern part of the map area lies within the privately owned Hollister Ranch. The nearest significant commercial centers are Lompoc (population, about 42,000), about 10 km north of the map area, and Goleta (population, about 30,000), about 50 km east of the map area. The Union Pacific railroad tracks run west and northwest along the coast through the entire map area, within a few hundred meters of the shoreline. The map area has a long history of petroleum exploration, and the seafloor notably includes large asphalt mounds and pockmarks that result from petroleum seepage. Several offshore gas and oil fields were discovered, and some were developed, in and on the margin of California’s State Waters.
Much of the shoreline in the Offshore of Point Conception map area is characterized by narrow beaches that have thin sediment cover above bedrock platforms, backed by low (10- to 20-m-high) cliffs that are capped by a coastal terrace. Beaches are subject to wave erosion during winter storms, followed by gradual sediment recovery or accretion in the late spring, summer, and fall months during the gentler wave climate. The map area lies in the west-central part of the Santa Barbara littoral cell, which is characterized by west-to-east transport of sediment from Point Arguello on the northwest to Hueneme and Mugu Canyons on the southeast. Sediment supply to the map area is mainly from relatively small coastal watersheds, including the Jalama Creek–Espada Creek drainage basin (about 63 km2), as well as Cañada del Jolloru, Black Canyon, Wood Canyon, Cañada del Cojo, and Barranca Honda. Coastal-watershed discharge and sediment load are highly variable, characterized by brief large events during major winter storms and long periods of low (or no) flow and minimal sediment load between storms. In recent (recorded) history, the majority of high-discharge, high-sediment-flux events have been associated with El Niño phases of the El Niño–Southern Oscillation climatic pattern.
Following the coastline, the shelf bends to the north and northwest around Point Conception, and the trend of the shelf break changes from about 298° to 241° azimuth. Shelf width ranges from about 5 km south of Point Conception to about 11 km northwest of it; the slope ranges from about 1.0° to 1.2° to about 0.7° south and northwest of Point Conception, respectively. Southwest of Point Conception, the shelf break and upper slope are incised by a 600-m-wide, 20- to 30-m-deep, south-facing trough, one of five heads of the informally named Arguello submarine canyon.
The map area is located at a major biogeographic transition zone between the east-west-trending Santa Barbara Channel region of the Southern California Bight and the northwest-trending central California coast. North of Point Conception, the coast is subjected to high wave exposure from the north, west, and south, as well as consistently strong upwelling that brings cold, nutrient-rich waters to the surface. Southeast of Point Conception, the Santa Barbara Channel is largely protected from strong north swells by Point Conception and from south swells by the Channel Islands; surface waters are warmer, and upwelling is weak and seasonal.
Seafloor habitats in the broad Santa Barbara Channel region consist of significant amounts of soft, unconsolidated sediment interspersed with isolated areas of rocky habitat that support kelp-forest communities in the nearshore and rocky-reef communities in deeper water. The potential marine benthic habitat types mapped in the Offshore of Point Conception map area are directly related to its Quaternary geologic history, geomorphology, and active sedimentary processes. These potential habitats lie primarily within the Shelf (continental shelf) but also partly within the Flank (basin flank or continental slope) megahabitats. The fairly homogeneous seafloor of sediment and low-relief bedrock provides characteristic habitat for rockfish, groundfish, crabs, shrimp, and other marine benthic organisms. Several areas of smooth sediment form nearshore terraces that have relatively steep, smooth fronts, which are attractive to groundfish. Below the steep shelf break, soft, unconsolidated sediment is interrupted by the heads of several submarine canyons, gullies, and rills, also good potential habitat for rockfish. The map area includes the large (58.3 km2) Point Conception State Marine Reserve.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181024","usgsCitation":"Johnson, S.Y., Dartnell, P., Cochrane, G.R., Hartwell, S.R., Golden, N.E., Kvitek, R.G., and Davenport, C.W. (S.Y. Johnson and S.A. Cochran, eds.), 2018, California State Waters Map Series— Offshore of Point Conception, California: U.S. Geological Survey Open-File Report 2018–1024, pamphlet 36 p., 9 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20181024.","productDescription":"Pamphlet: iv, 36 p.; 9 Sheets: 55.0 x 36.0 inches or smaller; Dataset; Metadata","additionalOnlineFiles":"Y","ipdsId":"IP-082855","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":437940,"rank":23,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7QN64XQ","text":"USGS data release","linkHelpText":"California State Waters Map Series Data Catalog--Offshore of Point Conception, California"},{"id":353525,"rank":9,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2018/1024/ofr20181024_sheet8.pdf","text":"Sheet 8","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1024 Sheet 8","linkHelpText":"Local (Offshore of Point Conception Map Area) and Regional (Offshore from Point Conception to Hueneme Canyon) Shallow-Subsurface Geology and Structure, Santa Barbara Channel, California By Samuel Y. Johnson and Stephen R. Hartwell"},{"id":353524,"rank":8,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2018/1024/ofr20181024_sheet7.pdf","text":"Sheet 7","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1024 Sheet 7","linkHelpText":"Seismic-Reflection Profiles, Offshore of Point Conception Map Area, California By Samuel Y. Johnson and Stephen R. Hartwell"},{"id":353532,"rank":16,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sim3302","text":"Scientific Investigations Map 3302","description":"Scientific Investigations Map 3302","linkHelpText":"California State Waters Map Series—Offshore of Coal Oil Point, California, by Sam Y. Johnson and others."},{"id":353531,"rank":15,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sim3319","text":"Scientific Investigations Map 3319","description":"Scientific Investigations Map 3319","linkHelpText":"California State Waters Map Series—Offshore of Refugio Beach, California, by Sam Y. Johnson and others."},{"id":353530,"rank":14,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20181023","text":"Open-File Report 2018–1023","description":"Open-File Report 2018–1023","linkHelpText":"California State Waters Map Series—Offshore of Gaviota, California, by Sam Y. Johnson and others."},{"id":353528,"rank":12,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7QN64XQ","text":"Data Catalog","linkFileType":{"id":5,"text":"html"},"description":"OFR 2018-1024 Data Catalog","linkHelpText":"The GIS data layers for this map are accessible from “California State Waters Map Series—Offshore of Point Conception, California” which is part of California State Waters Map Series Data Catalog. Each GIS data file is listed with a brief description, a small image, and links to the metadata files and the downloadable data files."},{"id":353526,"rank":10,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2018/1024/ofr20181024_sheet9.pdf","text":"Sheet 9","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1024 Sheet 9","linkHelpText":"Offshore and Onshore Geology and Geomorphology, Offshore of Point Conception Map Area, California By Samuel Y. Johnson, Stephen R. Hartwell, and Clifton W. Davenport"},{"id":353529,"rank":13,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/ds/781/","text":"Data Series 781","description":"Data Series 781","linkHelpText":"California State Waters Map Series Data Catalog"},{"id":353523,"rank":7,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2018/1024/ofr20181024_sheet6.pdf","text":"Sheet 6","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1024 Sheet 6","linkHelpText":"Marine Benthic Habitats from the Coastal and Marine Ecological Classification Standard, Offshore of Point Conception Map Area, California By Guy R. Cochrane, Stephen R. Hartwell, and Samuel Y. Johnson"},{"id":353535,"rank":19,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/sim/3254/","text":"Scientific Investigations Map 3254","description":"Scientific Investigations Map 3254","linkHelpText":"California State Waters Map Series—Offshore of Ventura, California, by Sam Y. Johnson and others."},{"id":353534,"rank":18,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/sim/3261/","text":"Scientific Investigations Map 3261","description":"Scientific Investigations Map 3261","linkHelpText":"California State Waters Map Series—Offshore of Carpinteria, California, by Sam Y. Johnson and others."},{"id":353533,"rank":17,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sim3281","text":"Scientific Investigations Map 3281","description":"Scientific Investigations Map 3281","linkHelpText":"California State Waters Map Series—Offshore of Santa Barbara, California, by Sam Y. 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Johnson and others."},{"id":353527,"rank":11,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1024/ofr20181024_pamphlet.pdf","text":"Pamphlet","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1024 Pamphlet"},{"id":353522,"rank":6,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2018/1024/ofr20181024_sheet5.pdf","text":"Sheet 5","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1024 Sheet 5","linkHelpText":"Seafloor Character, Offshore of Point Conception Map Area, California By Stephen R. Hartwell and Guy R. Cochrane"},{"id":353521,"rank":5,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2018/1024/ofr20181024_sheet4.pdf","text":"Sheet 4","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1024 Sheet 4","linkHelpText":"Data Integration and Visualization, Offshore of Point Conception Map Area, California By Peter Dartnell"},{"id":353520,"rank":4,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2018/1024/ofr20181024_sheet3.pdf","text":"Sheet 3","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1024 Sheet 3","linkHelpText":"Acoustic Backscatter, Offshore of Point Conception Map Area, California By Peter Dartnell and Rikk G. Kvitek"},{"id":353519,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2018/1024/ofr20181024_sheet2.pdf","text":"Sheet 2","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1024 Sheet 2","linkHelpText":"Shaded-Relief Bathymetry, Offshore of Point Conception Map Area, California By Peter Dartnell and Rikk G. Kvitek"},{"id":353518,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2018/1024/ofr20181024_sheet1.pdf","text":"Sheet 1","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1024 Sheet 1","linkHelpText":"Colored Shaded-Relief Bathymetry, Offshore of Point Conception Map Area, California By Peter Dartnell and Rikk G. 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Pacific Coastal & Marine Science Center
U.S. Geological Survey
Pacific Science Center
2885 Mission St.
Santa Cruz, CA 95060
http://walrus.wr.usgs.gov/
In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within the 3-nautical-mile limit of California’s State Waters. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data, acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow subsurface geology.
The map area is in the southern part of the Western Transverse Ranges geologic province, which is north of the California Continental Borderland. Significant clockwise rotation—at least 90°—since the early Miocene has been proposed for the Western Transverse Ranges province, and the region is presently undergoing north-south shortening. The offshore part of the map area lies south of the steep south flank of the Santa Ynez Mountains. The crest of the range, which has a maximum elevation of about 760 m in the map area, lies about 4 km north of the shoreline.
Gaviota is an unincorporated community that has a sparse population (less than 100), and the coastal zone is largely open space that is locally used for cattle grazing. The Union Pacific railroad tracks extend westward along the coast through the entire map area, within a few hundred meters of the shoreline. Highway 101 crosses the eastern part of the map area, also along the coast, then turns north (inland) and travels through Cañada de la Gaviota and Gaviota Pass en route to Buellton. Gaviota State Park lies at the mouth of Cañada de la Gaviota. West of Gaviota, the onland coastal zone is occupied by the Hollister Ranch, a privately owned, gated community that has no public access.
The map area has a long history of petroleum exploration and development. Several offshore gas fields were discovered and were developed by onshore directional drilling in the 1950s and 1960s. Three offshore petroleum platforms were installed in adjacent federal waters in 1976 (platform “Honda”) and 1989 (platforms “Heritage” and “Harmony”). Local offshore and onshore operations were serviced for more than a century by the Gaviota marine terminal, which is currently being decommissioned and will be abandoned in an intended transition to public open space.
The Offshore of Gaviota map area lies within the western Santa Barbara Channel region of the Southern California Bight, and it is somewhat protected from large Pacific swells from the north and northwest by Point Conception and from south and southwest swells by offshore islands and banks. Much of the shoreline in the map area is characterized by narrow beaches that have thin sediment cover, backed by low (10- to 20-m-high) cliffs that are capped by a narrow coastal terrace. Beaches are subject to wave erosion during winter storms, followed by gradual sediment recovery or accretion in the late spring, summer, and fall months during the gentler wave climate.
The map area lies in the western-central part of the Santa Barbara littoral cell, which is characterized by west-to-east transport of sediment from Point Arguello on the northwest to Hueneme and Mugu Canyons on the southeast. Sediment supply to the western and central part of the littoral cell is mainly from relatively small coastal watersheds. In the map area, sediment sources include Cañada de la Gaviota (52 km2), as well as Cañada de la Llegua, Arroyo el Bulito, Cañada de Santa Anita, Cañada de Alegria, Cañada del Agua Caliente, Cañada del Barro, Cañada del Leon, Cañada San Onofre, and many others. Coastal-watershed discharge and sediment load are highly variable, characterized by brief large events during major winter storms and long periods of low (or no) flow and minimal sediment load between storms. In recent (recorded) history, the majority of high-discharge, high-sediment-flux events have been associated with El Niño phases of the El Niño–Southern Oscillation climatic pattern.
Shelf width in the Offshore of Gaviota map area ranges from about 4.3 to 4.7 km, and shelf slopes average about 1.0° to 1.2° but are highly variable because of the presence of the large Gaviota sediment bar. This bar extends southwestward for about 9 km from the mouth of Cañada de la Gaviota to the shelf break, is as wide as 2 km, and is by far the largest shore-attached sediment bar in the Santa Barbara Channel. The shelf is underlain by bedrock and variable amounts (0 to as much as 36 m in the Gaviota bar) of upper Quaternary sediments deposited as sea level fluctuated in the late Pleistocene. The trend of the shelf break changes from about 276° to 236° azimuth over a distance of about 12 km, and it ranges in depth from about 91 m to as shallow as 62 to 73 m where significant shelf-break and upper-slope failure and landsliding has apparently occurred. The shelf break in the western part of the map area is notably embayed by the heads of three large (150- to 300-m-wide) channels that have been referred to as “the Gaviota Canyons” or as “Drake Canyon,” “Sacate Canyon,” and “Alegria Canyon.”
Seafloor habitats in the broad Santa Barbara Channel region consist of significant amounts of soft, unconsolidated sediment interspersed with isolated areas of rocky habitat that support kelp-forest communities in the nearshore and rocky-reef communities in deeper water. The potential marine benthic habitat types mapped in the Offshore of Gaviota map area are directly related to its Quaternary geologic history, geomorphology, and active sedimentary processes. These potential habitats lie primarily within the Shelf (continental shelf) but also partly within the Flank (basin flank or continental slope) megahabitats. The fairly homogeneous seafloor of sediment and low-relief bedrock provides characteristic habitat for rockfish, groundfish, crabs, shrimp, and other marine benthic organisms. Several areas of smooth sediment form nearshore terraces that have relatively steep, smooth fronts, which may be attractive to groundfish. Below the steep shelf break, soft, unconsolidated sediment is interrupted by the heads of several submarine canyons and rills, some bedrock exposures, and small carbonate mounds associated with asphalt mounds and pockmarks, also good potential habitat for rockfish. The map area includes the relatively small (5.2 km2) Kashtayit State Marine Conservation Area, which largely occupies the inner part of the Gaviota sediment bar.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181023","usgsCitation":"Johnson, S.Y., Dartnell, P., Cochrane, G.R., Hartwell, S.R., Golden, N.E., Kvitek, R.G., and Davenport, C.W. (S.Y. Johnson and S.A. Cochran, eds.), 2018, California State Waters Map Series— Offshore of Gaviota, California: U.S. Geological Survey Open-File Report 2018–1023, pamphlet 41 p., 9 sheets, scale 1:24,000, https://doi.org/10.3133/ofr20181023.","productDescription":"Pamphlet: iv, 41 p.; 9 Sheets: 52.0 x 36.0 inches or smaller; Dataset; Metadata","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-082722","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":437941,"rank":23,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7TH8JWJ","text":"USGS data release","linkHelpText":"California State Waters Map Series Data Catalog--Offshore of Gaviota, California"},{"id":399119,"rank":22,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_107161.htm"},{"id":353556,"rank":21,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/of/2018/1023/ofr20181023_metadata.html","text":"Metadata","description":"OFR 2018-1023 Metadata"},{"id":353516,"rank":20,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1023/ofr20181023_pamphlet.pdf","text":"Pamphlet","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1023 Pamphlet"},{"id":353515,"rank":19,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7TH8JWJ","text":"Data Catalog","linkFileType":{"id":5,"text":"html"},"description":"OFR 2018-1023 Data Catalog","linkHelpText":"The GIS data layers for this map are accessible from “California State Waters Map Series—Offshore of Gaviota, California” which is part of California State Waters Map Series Data Catalog. 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Davenport"},{"id":353504,"rank":8,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2018/1023/ofr20181023_sheet8.pdf","text":"Sheet 8","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1023 Sheet 8","linkHelpText":"Local (Offshore of Gaviota Map Area) and Regional (Offshore from Point Conception to Hueneme Canyon) Shallow-Subsurface Geology and Structure, Santa Barbara Channel, California By Samuel Y. Johnson and Stephen R. Hartwell"},{"id":353503,"rank":7,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2018/1023/ofr20181023_sheet7.pdf","text":"Sheet 7","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1023 Sheet 7","linkHelpText":"Seismic-Reflection Profiles, Offshore of Gaviota Map Area, California By Samuel Y. Johnson and Stephen R. Hartwell"},{"id":353502,"rank":6,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2018/1023/ofr20181023_sheet6.pdf","text":"Sheet 6","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1023 Sheet 6","linkHelpText":"Marine Benthic Habitats from the Coastal and Marine Ecological Classification Standard, Offshore of Gaviota Map Area, California By Guy R. Cochrane, Stephen R. Hartwell, and Samuel Y. Johnson"},{"id":353506,"rank":10,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1023/coverthb.jpg"}],"scale":"24000","country":"United States","state":"California","city":"Gaviota","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.3753,\n 34.4056\n ],\n [\n -120.1833,\n 34.4056\n ],\n [\n -120.1833,\n 34.5425\n ],\n [\n -120.3753,\n 34.5425\n ],\n [\n -120.3753,\n 34.4056\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact Information
Pacific Coastal & Marine Science Center
U.S. Geological Survey
Pacific Science Center
2885 Mission St.
Santa Cruz, CA 95060
http://walrus.wr.usgs.gov/