A 3-year study was undertaken to evaluate the suitability of the available modeling tools for characterizing environmental flows in the middle Verde River watershed of central Arizona, describe riparian vegetation throughout the watershed, and estimate sediment mobilization in the river. Existing data on fish and macroinvertebrates were analyzed in relation to basin characteristics, flow regimes, and microhabitat, and a pilot study was conducted that sampled fish and macroinvertebrates and the microhabitats in which they were found. The sampling for the pilot study took place at five different locations in the middle Verde River watershed. This report presents the results of this 3-year study.
The Northern Arizona Groundwater Flow Model (NARGFM) was found to be capable of predicting long-term changes caused by alteration of regional recharge (such as may result from climate variability) and groundwater pumping in gaining, losing, and dry reaches of the major streams in the middle Verde River watershed. Over the period 1910 to 2006, the model simulated an increase in dry reaches, a small increase in reaches losing discharge to the groundwater aquifer, and a concurrent decrease in reaches gaining discharge from groundwater. Although evaluations of the suitability of using the NARGFM and Basin Characteristic Model to characterize various streamflow intervals showed that smallerscale basin monthly runoff could be estimated adequately at locations of interest, monthly stream-flow estimates were found unsatisfactory for determining environmental flows.
Orthoimagery and Moderate Resolution Imaging Spectroradiometer data were used to quantify stream and riparian vegetation properties related to biotic habitat. The relative abundance of riparian vegetation varied along the main channel of the Verde River. As would be expected, more upland plant species and fewer lowland species were found in the upper-middle section compared to the lower-middle section, and vice-versa. Vegetation changes within the upper-middle and lower-middle reaches are related to differences in climate and hydrology. In general, the riparian vegetation of the middle Verde River watershed is that of a healthy ecosystem’s mixed age, mixed patch structure, likely a result of the mostly unaltered disturbance regime.
The frequency of in-river hydrogeomorphic features (pool, riffle, run) varied along the middle Verde River channel. There was a greater abundance of riffle habitat in the upper-middle reach; the lower-middle reach included more pool habitat. The Oak Creek tributary was more homogenous in geomorphic stream habitat composition than West Clear Creek, where runs dominated the upper reaches and pools dominated many of the lower reaches.
On the basis of the period of record and discharges recorded at 15-minute intervals, five flows were found to reach the gravel-transport threshold. Sediment mobilization computed with flows averaged over daily time steps yielded just three flows that reached the gravel-transport threshold, and monthly averaged flows yielded none. In the middle Verde River watershed, 15-minute data should be used when possible to evaluate sediment transport in the river system.
Data from more than 300 fish surveys conducted from 1992 to 2011 were analyzed using two schemes, one that divided the river into five reaches based on basin characteristics, and a second that divided the river into five reaches based on degree of flow alteration (specifically, diversions). Fish community metrics and assemblage data were used to analyze patterns of species composition and abundance in the two approaches. Overall, native and non-native species were regularly interacting and probably competing for similar resources. Fish abundances were also analyzed in response to floods and other flow metrics. Although the data are limited, native fish abundances increased more rapidly than non-native fish abundances in response to large floods. The basin-characteristic reach analysis showed native fish in greater abundance in the upper-middle reaches of the Verde River watershed and generally decreasing with downstream distance. The median relative abundance of native fish decreased by 50 percent from reach 1 to reach 5. Using the reach scheme based on degree of flow alteration, nondiverted reaches were found to have a greater abundance of native fish than diverted reaches. In heavily diverted reaches, non-native species outnumbered native species.
Fish metrics and stream-flow metrics for the 30, 90, and 365-day periods before collection were computed and the results analyzed statistically. Only abundance of all fish species was associated with the 30-day flow metrics. The 90-day flow metrics were generally positively associated with fish metrics, whereas the 365-day flow metrics had more negative correlations. In particular, significant relations were found between fish metrics and the magnitude and frequency of high flows, including maximum monthly flow, median annual number of high-flow events, and median annual maximum streamflow. Native sucker (Catostomidae) populations tended to decrease in periods of extended base flow, and fish in the non-native sunfish family (Centrarchidae) decreased in periods of flashy, high magnitude flows.
A pilot study surveyed fish at five locations in the upper part of the middle Verde River watershed as a means to measure microhabitat availability and quantify native and non-native fish use of that available microhabitat. Results indicated that native and non-native species exhibit some clear differences in microhabitat use. Although at least some native and non-native fish were found in each velocity, depth, and substrate category, preferential microhabitat use was common. On a percentage basis, non-native species had a strong preference for slow-moving and deeper water with silt and sand substrate, with a secondary preference for faster moving and very shallow water and a coarse gravel substrate. Native species showed a general preference for somewhat faster, moderate depth water over coarse gravel and had no clear secondary preference.
Macroinvertebrate-variables index period, high-flow year, and collection location (upper-middle Verde River, lowermiddle Verde River, or Verde River tributaries) were found to be important explanatory variables in differentiating among community metrics. Overall richness (number of unique taxa), Shannon’s diversity index, and the percent of the most dominant taxa were all highly correlated, but their response to each macroinvertebrate variable was different. The percentage of mayfly (order Ephemeroptera) taxa was significantly higher in Oak Creek and the upper-middle and lower-middle Verde River reaches, locations which have higher flows and more urbanization than other reaches. When community metrics were related to hydrologic metrics, caddisfly (order Trichoptera) populations appeared to increase and mayfly populations to decrease in response to less flashy and more stable streamflows. Conversely, caddisfly populations appeared to decrease and mayfly populations to increase in response to greater flow variability.
Six locations along the Verde River were sampled for macroinvertebrates as part of a pilot study associated with this report—(1) below Granite Creek, (2) near Campbell Ranch, (3) at the U.S. Geological Survey Paulden gage, (4) at the Perkinsville Bridge, (5) at the USGS Clarkdale gage, and (6) near the Reitz Ranch property. A nonmetric multidimensional scaling ordination of macroinvertebrate assemblages showed that the Verde River below Granite Creek site was different from the five other sites and that the Perkinsville Bridge and near Reitz Ranch samples had similar community structure. The near Campbell Ranch and Paulden gage locations had similar microhabitat characteristics, with the exception of riparian cover, yet the assemblage structure was very different. The different community composition at Verde River below Granite Creek was likely due to it having the smallest substrate sizes, lowest velocities, shallowest depths, and most riparian cover of the six sites.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175100","collaboration":"Prepared in cooperation with The Nature Conservancy and Salt River Project","usgsCitation":"Paretti, N.V., Brasher, A.M.D., Pearlstein, S.L., Skow, D.M., Gungle, Bruce, and Garner, B.D., 2018, Preliminary synthesis and assessment of environmental flows in the middle Verde River watershed, Arizona: U.S. Geological Survey Scientific Investigations Report 2017–5100, 104 p., https://doi.org/10.3133/sir20175100.","productDescription":"Report: xii; 104 p.; 3 Tables","numberOfPages":"120","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-084364","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":354141,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5100/sir20175100_table14.csv","text":"Table 14","size":"5 KB","linkFileType":{"id":7,"text":"csv"},"description":"Scientific Investigation Report 2017-5100 Table 12"},{"id":354142,"rank":5,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5100/sir20175100_tables12_14.xlsx","text":"Table 12 and 14","size":"25 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"Scientific Investigation Report 2017-5100 Table 12 and 14 Excel file"},{"id":354139,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5100/sir20175100.pdf","text":"Report","size":"17 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Scientific Investigation Report 2017-5100"},{"id":354138,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5100/coverthb.jpg"},{"id":354140,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5100/sir20175100_table12.csv","text":"Table 12","size":"5 KB","linkFileType":{"id":7,"text":"csv"},"description":"Scientific Investigation Report 2017-5100 Table 12"}],"country":"United States","state":"Arizona","otherGeospatial":"Verde River Watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.5,\n 34.5\n ],\n [\n -112.5,\n 34.5\n ],\n [\n -112.5,\n 35.5\n ],\n [\n -111.5,\n 35.5\n ],\n [\n -111.5,\n 34.5\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
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This study presents a synthesis of century-scale hydroclimate variations in North America for the Common Era (last 2000 years) using new age models of previously published multiple proxy-based paleoclimate data. This North American Hydroclimate Synthesis (NAHS) examines regional hydroclimate patterns and related environmental indicators, including vegetation, lake water elevation, stream flow and runoff, cave drip rates, biological productivity, assemblages of living organisms, and salinity. Centennial-scale hydroclimate anomalies are obtained by iteratively sampling the proxy data on each of thousands of age model realizations and determining the fractions of possible time series indicating that the century-smoothed data was anomalously wet or dry relative to the 100 BCE to 1900 CE mean. Results suggest regionally asynchronous wet and dry periods over multidecadal to centennial timescales and frequent periods of extended regional drought. Most sites indicate drying during previously documented multicentennial periods of warmer Northern Hemisphere temperatures, particularly in the western U.S., central U.S., and Canada. Two widespread droughts were documented by the NAHS: from 50 BCE to 450 CE and from 800 to 1100 CE. Major hydroclimate reorganizations occurred out of sync with Northern Hemisphere temperature variations and widespread wet and dry anomalies occurred during both warm and cool periods. We present a broad assessment of paleoclimate relationships that highlights the potential influences of internal variability and external forcing and supports a prominent role for Pacific and Atlantic Ocean dynamics on century-scale continental hydroclimate.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.gloplacha.2017.12.025","usgsCitation":"Rodysill, J.R., Anderson, L., Cronin, T.M., Jones, M.C., Thompson, R.S., Wahl, D.B., Willard, D.A., Addison, J.A., Alder, J.R., Anderson, K.H., Anderson, L., Barron, J.A., Bernhardt, C.E., Hostetler, S.W., Kehrwald, N.M., Khan, N., Richey, J.N., Starratt, S.W., Strickland, L.E., Toomey, M., Treat, C.C., and Wingard, G.L., 2018, A North American Hydroclimate Synthesis (NAHS) of the Common Era: Global and Planetary Change, v. 162, p. 175-198, https://doi.org/10.1016/j.gloplacha.2017.12.025.","productDescription":"24 p.","startPage":"175","endPage":"198","ipdsId":"IP-089799","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science 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As snow in northern latitudes compacted into ice several kilometers thick, it flowed as glaciers southward across the North American continent. These glaciers extended across the northern United States, dramatically altering the landscape they covered. East of the Rocky Mountains, the ice coalesced into continental glaciers (called the Laurentide Ice Sheet) that at times blanketed much of the north-central and northeastern United States. To the west of the Laurentide Ice Sheet, glaciers formed in the mountains of western Canada and the United States and coalesced into the Cordilleran ice sheet; this relatively smaller ice mass extended into the conterminous United States in the northernmost areas of western Montana, Idaho, and Washington. Throughout the Pleistocene, landscape alteration occurred by (1) glacial erosion of the rocks and sediments; (2) redeposition of the eroded earth materials in a form substantially different from their source rocks, in terms of texture and overall character; and (3) disruption of preexisting drainage patterns by the newly deposited sediments. In many cases, pre-glacial drainage systems (including, for example, the Mississippi River) were rerouted because their older drainage courses became blocked with glacial sediment.
The continental glaciers advanced and retreated many times across those areas. During each ice advance, or glaciation, erosion and deposition occurred, and the landscape was again altered. Through successive glaciations, the landscape and the bedrock surface gradually came to resemble their present configurations. As continental ice sheets receded and the Pleistocene ended, erosion and deposition of sediment (for example in stream valleys) continued to shape the landscape up to the present day (albeit to a lesser extent than during glaciation). The interval of time since the last recession of the glaciers is called the Holocene and, together with the Pleistocene, constitutes the Quaternary Period of geologic time; this publication characterizes the three-dimensional geometry of the Quaternary sediments and the bedrock surface that lies beneath.
The pre-glacial landscape was underlain mostly by weathered bedrock generally similar in nature to that found in many areas of the non-glaciated United States. Glacial erosion and redeposition of earth materials produced a young, mineral-rich soil that formed the basis for the highly productive agricultural economy in the U.S. midcontinent. Extensive buried sands and gravels within the glacial deposits also provided a stimulus to other economic sectors by serving as high-quality aquifers supplying groundwater to the region’s industry and cities. An understanding of the three-dimensional distribution of these glacial sediments has direct utility for addressing various societal issues including groundwater quality and supply, and landscape and soil response to earthquake-induced shaking.
The Quaternary sediment thickness map and bedrock topographic map shown here provide a regional overview and are intended to supplement the more detailed work on which they are based. Detailed mapping is particularly useful in populated areas for site-specific planning. In contrast, regional maps such as these serve to place local, detailed mapping in context; to permit the extrapolation of data into unmapped areas; and to depict large-scale regional geologic features and patterns that are beyond the scope of local, detailed mapping. They also can enhance the reader’s general understanding of the region’s landscape and geologic history and provide a source of information for regional decision making that could benefit by improved predictability of bedrock depth beneath the unconsolidated Quaternary sediments. To enable these maps to be analyzed in conjunction with other types of information, this publication also includes the map data in GIS compatible format.
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\"}}]}","contact":"National Cooperative Geologic Mapping Program
U.S. Geological Survey
12201 Sunrise Valley Drive Mail Stop 908
Reston, VA 20192
Fax: (703) 648-6937
Multi-millennial transient simulations of climate changes have a range of important applications, such as for investigating key geologic events and transitions for which high-resolution palaeoenvironmental proxy data are available, or for projecting the long-term impacts of future climate evolution on the performance of geological repositories for the disposal of radioactive wastes. However, due to the high computational requirements of current fully coupled general circulation models (GCMs), long-term simulations can generally only be performed with less complex models and/or at lower spatial resolution. In this study, we present novel longterm “continuous” projections of climate evolution based on the output from GCMs, via the use of a statistical emulator. The emulator is calibrated using ensembles of GCM simulations, which have varying orbital configurations and atmospheric CO2 concentrations and enables a variety of investigations of long-term climate change to be conducted, which would not be possible with other modelling techniques on the same temporal and spatial scales. To illustrate the potential applications, we apply the emulator to the late Pliocene (by modelling surface air temperature – SAT), comparing its results with palaeo-proxy data for a number of global sites, and to the next 200 kyr (thousand years) (by modelling SAT and precipitation). A range of CO2 scenarios are prescribed for each period. During the late Pliocene, we find that emulated SAT varies on an approximately precessional timescale, with evidence of increased obliquity response at times. A comparison of atmospheric CO2 concentration for this period, estimated using the proxy sea surface temperature (SST) data from different sites and emulator results, finds that relatively similar CO2 concentrations are estimated based on sites at lower latitudes, whereas higher-latitude sites show larger discrepancies. In our second illustrative application, spanning the next 200 kyr into the future, we find that SAT oscillations appear to be primarily influenced by obliquity for the first ∼ 120 kyr, whilst eccentricity is relatively low, after which precession plays a more dominant role. Conversely, variations in precipitation over the entire period demonstrate a strong precessional signal. Overall, we find that the emulator provides a useful and powerful tool for rapidly simulating the long-term evolution of climate, both past and future, due to its relatively high spatial resolution and relatively low computational cost. However, there are uncertainties associated with the approach used, including the inability of the emulator to capture deviations from a quasi-stationary response to the forcing, such as transient adjustments of the deep-ocean temperature and circulation, in addition to its limited range of fixed ice sheet configurations and its requirement for prescribed atmospheric CO2 concentrations.
","language":"English","publisher":"European Geosciences Union","doi":"10.5194/cp-2017-57","usgsCitation":"Lord, N.S., Crucifix, M., Lunt, D.J., Thorne, M.C., Bounceur, N., Dowsett, H.J., O’Brien, C.L., and Ridgwell, A., 2017, Emulation of long-term changes in global climate: application to the late Pliocene and future: Climate of the Past, v. 13, p. 1539-1571, https://doi.org/10.5194/cp-2017-57.","productDescription":"33 p.","startPage":"1539","endPage":"1571","ipdsId":"IP-083123","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":469214,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/cp-2017-57","text":"Publisher Index Page"},{"id":355675,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b6fc50ae4b0f5d57878eaea","contributors":{"authors":[{"text":"Lord, Natalie S.","contributorId":206300,"corporation":false,"usgs":false,"family":"Lord","given":"Natalie","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":740007,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Crucifix, Michel","contributorId":206301,"corporation":false,"usgs":false,"family":"Crucifix","given":"Michel","email":"","affiliations":[],"preferred":false,"id":740008,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lunt, Daniel J.","contributorId":101168,"corporation":false,"usgs":true,"family":"Lunt","given":"Daniel","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":740009,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thorne, Mike C.","contributorId":206302,"corporation":false,"usgs":false,"family":"Thorne","given":"Mike","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":740010,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bounceur, Nabila","contributorId":206303,"corporation":false,"usgs":false,"family":"Bounceur","given":"Nabila","email":"","affiliations":[],"preferred":false,"id":740011,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dowsett, Harry J. 0000-0003-1983-7524 hdowsett@usgs.gov","orcid":"https://orcid.org/0000-0003-1983-7524","contributorId":949,"corporation":false,"usgs":true,"family":"Dowsett","given":"Harry","email":"hdowsett@usgs.gov","middleInitial":"J.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":740012,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"O’Brien, Charlotte L.","contributorId":206304,"corporation":false,"usgs":false,"family":"O’Brien","given":"Charlotte","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":740013,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ridgwell, A.","contributorId":192917,"corporation":false,"usgs":false,"family":"Ridgwell","given":"A.","email":"","affiliations":[],"preferred":false,"id":740014,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70190023,"text":"sim3382 - 2017 - Geologic map of the upper Arkansas River valley region, north-central Colorado","interactions":[],"lastModifiedDate":"2018-09-26T16:07:23","indexId":"sim3382","displayToPublicDate":"2018-04-11T14:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3382","title":"Geologic map of the upper Arkansas River valley region, north-central Colorado","docAbstract":"This 1:50,000-scale U.S. Geological Survey geologic map represents a compilation of the most recent geologic studies of the upper Arkansas River valley between Leadville and Salida, Colorado. The valley is structurally controlled by an extensional fault system that forms part of the prominent northern Rio Grande rift, an intra-continental region of crustal extension. This report also incorporates new detailed geologic mapping of previously poorly understood areas within the map area and reinterprets previously studied areas. The mapped region extends into the Proterozoic metamorphic and intrusive rocks in the Sawatch Range west of the valley and the Mosquito Range to the east. Paleozoic rocks are preserved along the crest of the Mosquito Range, but most of them have been eroded from the Sawatch Range. Numerous new isotopic ages better constrain the timing of both Proterozoic intrusive events, Late Cretaceous to early Tertiary intrusive events, and Eocene and Miocene volcanic episodes, including widespread ignimbrite eruptions. The uranium-lead ages document extensive about 1,440-million years (Ma) granitic plutonism mostly north of Buena Vista that produced batholiths that intruded an older suite of about 1,760-Ma metamorphic rocks and about 1,700-Ma plutonic rocks. As a result of extension during the Neogene and possibly latest Paleogene, the graben underlying the valley is filled with thick basin-fill deposits (Dry Union Formation and older sediments), which occupy two sub-basins separated by a bedrock high near the town of Granite. The Dry Union Formation has undergone deep erosion since the late Miocene or early Pliocene. During the Pleistocene, ongoing stream incision by the Arkansas River and its major tributaries has been interrupted by periodic aggradation. From Leadville south to Salida as many as seven mapped alluvial depositional units, that range in age from early to late Pleistocene, record periodic aggradational events along these streams that are commonly associated with deposition of glacial outwash or bouldery glacial-flood deposits. Many previously unrecognized Neogene and Quaternary faults, some of the latter with possible Holocene displacement, have been identified on lidar (light detection and ranging) imagery which covers 59 percent of the map area. This imagery has also permitted more accurate remapping of glacial, fluvial, and mass-movement deposits and aided in the determination of their relative ages. Recently published 10beryllium cosmogenic surface-exposure ages, coupled with our new geologic mapping, have revealed the timing and rates of late Pleistocene deglaciation. Glacial dams that impounded the Arkansas River at Clear Creek and possibly at Pine Creek failed at least three times during the middle and late Pleistocene, resulting in catastrophic floods and deposition of enormous boulders and bouldery alluvium downstream; at least two failures occurred during the late Pleistocene during the Pinedale glaciation.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3382","usgsCitation":"Kellogg, K.S., Shroba, R.R., Ruleman, C.A., Bohannon, R.G., McIntosh, W. C., Premo, W.R., Cosca, M.A., Moscati, R.J., and Brandt, T.R., 2017, Geologic map of the upper Arkansas River valley region, north-central Colorado: U.S. Geological Survey Scientific Investigations Map 3382, pamphlet 70 p., 2 sheets, scale 1:50,000, https://doi.org/10.3133/sim3382.","productDescription":"Report: vi, 70 p.; 4 Sheets; Data Release; Read Me","numberOfPages":"80","onlineOnly":"Y","ipdsId":"IP-078599","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":348012,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F75B00XQ","text":"USGS Data Release","description":"USGS data release","linkHelpText":"Data release for the geologic map of the upper Arkansas River valley region, north-central Colorado"},{"id":351653,"rank":9,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sim/3382/versionHist.txt","size":"4.0 kB","linkFileType":{"id":2,"text":"txt"},"description":"SIM 3382 Version History"},{"id":348008,"rank":7,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sim/3382/sim3382_ReadMe.txt","text":"Read Me","size":"12.0 KB","linkFileType":{"id":2,"text":"txt"},"description":"SIM 3382 Read Me"},{"id":348002,"rank":4,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3382/sim3382_sheet1_hillshade.pdf","text":"Sheet 1, with hillshade—","size":"102 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3382 Sheet 1 with hillshade","linkHelpText":"Geologic map with shaded relief"},{"id":347996,"rank":3,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3382/sim3382_sheet1_georeferenced.pdf","text":"Sheet 1, georeferenced—","size":"335 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3382 Sheet 1 georeferenced","linkHelpText":"Georeferenced geologic map"},{"id":348005,"rank":6,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3382/sim3382_sheet2.pdf","text":"Sheet 2—","size":"1.16 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3382 Sheet 2","linkHelpText":" Correlation and description of map units"},{"id":348004,"rank":5,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3382/sim3382_sheet1_no_hillshade.pdf","text":"Sheet 1, without hillshade—","size":"50.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3382 Sheet 1 without hillshade","linkHelpText":"Geologic map without shaded relief"},{"id":347995,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3382/sim3382.pdf","text":"Report","size":"17.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3382 Report"},{"id":347994,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3382/coverthb2.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Upper Arkansas River Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.5,\n 38.5\n ],\n [\n -105.9,\n 38.5\n ],\n [\n -105.9,\n 39.5\n ],\n [\n -106.5,\n 39.5\n ],\n [\n -106.5,\n 38.5\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Geosciences and Environmental Change Science Center
U.S. Geological Survey
Box 25046, MS-980
Denver, CO 80225-0046
A suite of hydrologic models has been developed for the Apalachicola-Chattahoochee-Flint River Basin (ACFB) as part of the National Water Census, a U.S. Geological Survey research program that focuses on developing new water accounting tools and assessing water availability and use at the regional and national scales. Seven hydrologic models were developed using the Precipitation-Runoff Modeling System (PRMS), a deterministic, distributed-parameter, process-based system that simulates the effects of precipitation, temperature, land cover, and water use on basin hydrology. A coarse-resolution PRMS model was developed for the entire ACFB, and six fine-resolution PRMS models were developed for six subbasins of the ACFB. The coarse-resolution model was loosely coupled with a groundwater model to better assess the effects of water use on streamflow in the lower ACFB, a complex geologic setting with karst features. The PRMS coarse-resolution model was used to provide inputs of recharge to the groundwater model, which in turn provide simulations of groundwater flow that were aggregated with PRMS-based simulations of surface runoff and shallow-subsurface flow. Simulations without the effects of water use were developed for each model for at least the calendar years 1982–2012 with longer periods for the Potato Creek subbasin (1942–2012) and the Spring Creek subbasin (1952–2012). Water-use-affected flows were simulated for 2008–12. Water budget simulations showed heterogeneous distributions of precipitation, actual evapotranspiration, recharge, runoff, and storage change across the ACFB. Streamflow volume differences between no-water-use and water-use simulations were largest along the main stem of the Apalachicola and Chattahoochee River Basins, with streamflow percentage differences largest in the upper Chattahoochee and Flint River Basins and Spring Creek in the lower Flint River Basin. Water-use information at a shorter time step and a fully coupled simulation in the lower ACFB may further improve water availability estimates and hydrologic simulations in the basin.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175133","collaboration":"U.S. Geological Survey National Water Census and Water Availability and Use Science Program","usgsCitation":"LaFontaine, J.H., Jones, L.E., and Painter, J.A., 2017, Simulations of hydrologic response in the Apalachicola-Chattahoochee-Flint River Basin, Southeastern United States: U.S. Geological Survey Scientific Investigations Report 2017–5133, 112 p., https://doi.org/10.3133/sir20175133.","productDescription":"Report: x, 112 p.; Data Release","numberOfPages":"126","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-075742","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":350203,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5133/sir20175133.pdf","text":"Report","size":"32.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5133"},{"id":350251,"rank":4,"type":{"id":7,"text":"Companion Files"},"url":"https://doi.org/10.3133/sir20175141","text":"Scientific Investigations Report 2017-5141","linkHelpText":"- Groundwater-Flow Budget for the Lower Apalachicola-Chattahoochee-Flint River Basin in Southwestern Georgia and Parts of Florida and Alabama, 2008–12"},{"id":350202,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5133/coverthb.jpg"},{"id":350244,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7FJ2F1R","text":"USGS data release","description":"USGS data release","linkHelpText":"Model Input and Output for Hydrologic Simulations of the Apalachicola-Chattahoochee-Flint River Basin using the Precipitation Runoff Modeling System"}],"country":"United States","otherGeospatial":"Apalachicola-Chattahoochee-Flint River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -85.660400390625,\n 29.726222319395504\n ],\n [\n -83.397216796875,\n 29.726222319395504\n ],\n [\n -83.397216796875,\n 34.88593094075317\n ],\n [\n -85.660400390625,\n 34.88593094075317\n ],\n [\n -85.660400390625,\n 29.726222319395504\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, South Atlantic Water Science Center
U.S. Geological Survey
720 Gracern Road
Stephenson Center, Suite 129
Columbia, SC 29210
Fluorine compounds are essential in numerous chemical and manufacturing processes. Fluorspar is the commercial name for fluorite (isometric CaF2), which is the only fluorine mineral that is mined on a large scale. Fluorspar is used directly as a fluxing material and as an additive in different manufacturing processes. It is the source of fluorine in the production of hydrogen fluoride or hydrofluoric acid, which is used as the feedstock for numerous organic and inorganic chemical compounds.
The United States was the world’s leading producer of fluorspar until the mid-1950s. In the mid-1970s, the U.S. fluorspar mining industry began to decline because of foreign competition. By 1982, there was essentially only a single U.S. producer left, and that company ceased mining in 1996. Consumption of fluorspar in the United States peaked in the early 1970s, which was also the peak period of U.S. steel production. Since then, U.S. fluorspar consumption has decreased substantially; the United States has nonetheless increased its imports of downstream fluorine compounds, such as, in order of tonnage imported, hydrofluoric acid, aluminum fluoride, and cryolite. This combination of no U.S. production (until recently) and high levels of consumption has made the United States the world’s leading fluorspar-importing country, in all its various forms.
The number of fluorspar-exporting countries has decreased substantially in recent decades, and, as a result, the United States has become dependent on just a few countries to supply its needs. In 2013, the United States imported the majority of its fluorspar from three countries, which were, in descending order of the amount imported, Mexico, China, and South Africa.
Geologically, in igneous systems, fluorine is one of a number of elements that are “incompatible.” These incompatible elements become concentrated in the residual magma while the common silicates crystallize upon magma ascent and cooling, leading to relatively high fluorine concentrations in the more evolved or differentiated igneous rocks and in hydrothermal deposits associated with those evolved igneous rocks. In sedimentary rocks, fluorine’s highest concentrations are found in phosphorites because fluorine substitutes for hydroxyl ions in apatite, which leads to fluorine concentrations of, typically, from 2 to 4 weight percent in phosphorites. Because of the presence of fluorine, phosphate fertilizer manufacturers can produce a fluorosilicic acid byproduct. Most deposits mined for fluorine are hydrothermal, however, and consist of fluorine minerals that precipitated from hot water. Magmatic brines and brines from deep within sedimentary basins that have high concentrations of dissolved fluoride are the mineralizing fluids for various types of hydrothermal fluorspar deposits. Relatively dilute hydrothermal fluids that formed in some volcanic rocks can also transport sufficient fluoride to form a high-grade fluorspar deposit. Fluorite has low solubility in a common range of hydrothermal temperatures, particularly from about 160 degrees Celsius (°C) down to 60 °C. The increasing fluorite solubility below 60 °C partly explains why some water with exceptionally high levels of dissolved fluorine are found even at ambient temperatures in evaporitic lake basins in some East African Rift valleys in Kenya and Tanzania. The geologic conditions that led to the high concentrations there are known to exist in a number of other places in the world as well, including, perhaps, places in the Basin and Range province of the United States.
Eight minerals or mineral groups have sufficient fluorine in their structures to be considered as possible ores of the element; they are bastnaesite (also spelled bastnäsite; and other fluorocarbonates), cryolite, sellaite, villiaumite, fluorite, fluorapatite (in phosphorites), various phyllosilicates, and topaz. Fluorite is currently the only mineral that is mined for fluorine, and nomineral except fluorite is likely to become a source of commercially produced fluorine as a primary product as long as supplies from relatively thick and high-grade fluorite deposits continue to be available.
At least seven classes (which include one subclass) of hydrothermal fluorite deposits are recognized; they are classified according to their tectonic and (or) magmatic settings, as follows: (1) carbonatite-related fluorspar deposits; (2) alkaline-intrusion-related fluorspar deposits; (3) alkaline-volcanic-related epithermal fluorspar deposits; (4) Mississippi Valley-type fluorspar deposits (and a subclass of salt-related carbonate-hosted fluorspar deposits); (5) fluorspar deposits related to strongly differentiated granites; (6) subalkaline-volcanic-related epithermal fluospar deposits; and (7) fluorspar deposits that appear to be conformable within tuffaceous limy lacustrine sediments. An eighth class (not hydrothermal) is that of fluorspar deposits concentrated in soils and weathered zones; that is, residual fluorspar deposits. Generally, fluorspar deposits related to strongly differentiated granites have larger tonnages and lower grades than carbonatite-related fluorspar deposits, which, in turn, have larger tonnages and lower grades than fluorspar vein deposits from various other classes.
The United States has a few identified resources of fluorspar, most notably the Klondike II property in the Illinois- Kentucky fluorspar district located about 8 kilometers southwest of Salem, Kentucky, which has a large vein that contains at least 1.6 million metric tons at a grade of 60 percent CaF2 (Feytis, 2009). Additional fluorspar resources of lower grade but larger tonnage have been identified at Hicks Dome in the Illinois-Kentucky fluorspar district and at Lost River near the western tip of the Seward Peninsula in Alaska, along with a couple of dozen smaller, higher grade resources.
Internationally, new mines that either opened before the beginning of 2013 or were scheduled to open soon after that time include the Nui Phao tungsten-fluorspar-bismuth-copper-gold deposit in northern Vietnam; the St. Lawrence project in Newfoundland, Canada, which is located in a well-known fluorspar district; the Bamianshan deposit, which is related to a strongly differentiated granite in northwestern Zhejiang Province, China, near some of that Province’s large, subalkaline-volcanic-related epithermal veins; and the Nokeng project in South Africa, which is also related to a strongly differentiated granite. Other deposits in northwestern Australia, Nevada (United States), Norway, South Africa, and Sweden have been identified and could be put into production within just a few years.
Among undiscovered resources, an interesting possibility might be to produce a fluorine product from evaporitic, high-fluorine, high-pH sodium-carbonate brines like Lake Magadi (Kenya) and Lake Natron (Tanzania) in Africa’s Eastern Rift Valley. In addition, apparently conformable fluorspar deposits in tuffaceous limy lacustrine sediments, such as those in Italy, are likely to occur in similar young alkalic volcanic settings elsewhere in the world.
Modern geophysical and geochemical exploration techniques have typically not been brought to bear in exploration for new fluorspar deposits, although such techniques are likely to be used in future exploration. The tendency for fluorine to dissolve in significant concentrations in water at low temperature allows both surface water and groundwater to be used as sampling media in geochemical exploration. Evolved granite-related fluorspar deposits may be particularly susceptible to geophysical exploration methods because crystalline rocks that form a basement to sedimentary sections can be approximately defined with gravity and magnetic methods, and magnetite-bearing skarns can be directly detected with magnetic surveys.
Environmental considerations of fluorine mining focus especially on drinking water, where high fluorine concentrations can lead to tooth decay; dental and skeletal fluorosis; and bone and cartilage conditions, including genu valgum, which is the crippling bone deformity more commonly known as knock knee. Trace amounts of other elements in fluorspar ores are a concern at some deposits; for example, high beryllium concentrations in alkaline-volcanic-related epithermal deposits or high cadmium concentrations associated with Mississippi Valley-type and salt-related carbonate-hosted fluorspar deposits.
Future research might include testing whether fluorine can be extracted economically from high-pH, sodium-carbonate brines and exploring for new occurrences of apparently conformable fluorspar deposits in tuffaceous limy lacustrine sediments outside of the Latium Region of Italy. Other promising new areas of research could be studies of fluorspar deposit fluid inclusion compositions by quadrupole mass spectrometry, by noble gas mass spectrometry on irradiated fluid inclusions, or by chlorine isotopes, while also measuring the chemistry of the same fluid inclusions either by bulk crush-and-leach methods or by laser ablation-inductively coupled plasma mass spectrometry. Advanced studies of fluid inclusion chemistry could be applied beneficially to some of the enigmatic large epithermal fluorspar veins at various places in the world, where they might determine those deposits’ possible relationships to igneous intrusions, or to dissolved salt, or to heated meteoric water in volcanic sections, or perhaps to all three. This knowledge could help focus new exploration.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Critical mineral resources of the United States—Economic and environmental geology and prospects for future supply","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1802G","isbn":"978-1-4113-3991-0","usgsCitation":"Hayes, T.S., Miller, M.M., Orris, G.J., and Piatak, N.M., 2017, Fluorine, chap. G of Schulz, K.J., DeYoung, J.H., Jr., Seal, R.R., II, and Bradley, D.C., eds., Critical mineral resources of the United States—Economic and environmental geology and prospects for future supply: U.S. Geological Survey Professional Paper 1802, p. G1–G80, https://doi.org/10.3133/pp1802G.","productDescription":"viii, 80 p.","numberOfPages":"92","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-049496","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":334567,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1802/g/coverthb1.jpg"},{"id":334568,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1802/g/pp1802g.pdf","text":"Report","size":"12.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1802 F"}],"contact":"Mineral Resources Program Coordinator
U.S. Geological Survey
913 National Center
Reston, VA 20192
Email: minerals@usgs.gov
https://minerals.usgs.gov
Understanding the factors that affect water quality and the ecological services provided by freshwater ecosystems is an urgent global environmental issue. Predicting how water quality will respond to global changes not only requires water quality data, but also information about the ecological context of individual water bodies across broad spatial extents. Because lake water quality is usually sampled in limited geographic regions, often for limited time periods, assessing the environmental controls of water quality requires compilation of many data sets across broad regions and across time into an integrated database. LAGOS-NE accomplishes this goal for lakes in the northeastern-most 17 US states.
LAGOS-NE contains data for 51 101 lakes and reservoirs larger than 4 ha in 17 lake-rich US states. The database includes 3 data modules for: lake location and physical characteristics for all lakes; ecological context (i.e., the land use, geologic, climatic, and hydrologic setting of lakes) for all lakes; and in situ measurements of lake water quality for a subset of the lakes from the past 3 decades for approximately 2600–12 000 lakes depending on the variable. The database contains approximately 150 000 measures of total phosphorus, 200 000 measures of chlorophyll, and 900 000 measures of Secchi depth. The water quality data were compiled from 87 lake water quality data sets from federal, state, tribal, and non-profit agencies, university researchers, and citizen scientists. This database is one of the largest and most comprehensive databases of its type because it includes both in situ measurements and ecological context data. Because ecological context can be used to study a variety of other questions about lakes, streams, and wetlands, this database can also be used as the foundation for other studies of freshwaters at broad spatial and ecological scales.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/gigascience/gix101","usgsCitation":"Soranno, P.A., Bacon, L.C., Beauchene, M., Bednar, K.E., Bissell, E.G., Boudreau, C.K., Boyer, M.G., Bremigan, M.T., Carpenter, S.R., Carr, J.W., Cheruvelil, K.S., Christel, S.T., Claucherty, M., Collins, S.M., Conroy, J.D., Downing, J.A., Dukett, J., Fergus, C.E., Filstrup, C.T., Funk, C., Gonzalez, M.J., Green, L.T., Gries, C., Halfman, J.D., Hamilton, S.K., Hanson, P.C., Henry, E.N., Herron, E.M., Hockings, C., Jackson, J.R., Jacobson-Hedin, K., Janus, L.L., Jones, W.W., Jones, J., Keson, C.M., King, K.B., Kishbaugh, S.A., Lapierre, J., Lathrop, B., Latimore, J.A., Lee, Y., Lottig, N.R., Lynch, J.A., Matthews, L.J., McDowell, W.H., Moore, K.E., Neff, B., Nelson, S.J., Oliver, S., Pace, M.L., Pierson, D.C., Poisson, A.C., Pollard, A.I., Post, D.M., Reyes, P.O., Rosenberry, D., Roy, K.M., Rudstam, L.G., Sarnelle, O., Schuldt, N.J., Scott, C.E., Skaff, N.K., Smith, N.J., Spinelli, N.R., Stachelek, J.J., Stanley, E.H., Stoddard, J.L., Stopyak, S.B., Stow, C.A., Tallant, J.M., Tan, P., Thorpe, A.P., Vanni, M.J., Wagner, T., Watkins, G., Weathers, K.C., Webster, K.E., White, J., Wilmes, M.K., and Yuan, S., 2017, LAGOS-NE: a multi-scaled geospatial and temporal database of lake ecological context and water quality for thousands of US lakes: GigaScience, v. 6, no. 12, p. 1-22, https://doi.org/10.1093/gigascience/gix101.","productDescription":"22 p.","startPage":"1","endPage":"22","ipdsId":"IP-088165","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":469264,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/gigascience/gix101","text":"Publisher Index Page"},{"id":353287,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Connecticut, Iowa, Illinois, Indiana, Massachusetts, 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Nevada","interactions":[],"lastModifiedDate":"2017-12-04T10:30:46","indexId":"sir20175072","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-5072","title":"Groundwater model of the Great Basin carbonate and alluvial aquifer system version 3.0: Incorporating revisions in southwestern Utah and east central Nevada","docAbstract":"The groundwater model described in this report is a new version of previously published steady-state numerical groundwater flow models of the Great Basin carbonate and alluvial aquifer system, and was developed in conjunction with U.S. Geological Survey studies in Parowan, Pine, and Wah Wah Valleys, Utah. This version of the model is GBCAAS v. 3.0 and supersedes previous versions. The objectives of the model for Parowan Valley were to simulate revised conceptual estimates of recharge and discharge, to estimate simulated aquifer storage properties and the amount of reduction in storage as a result of historical groundwater withdrawals, and to assess reduction in groundwater withdrawals necessary to mitigate groundwater-level declines in the basin. The objectives of the model for the area near Pine and Wah Wah Valleys were to recalibrate the model using new observations of groundwater levels and evapotranspiration of groundwater; to provide new estimates of simulated recharge, hydraulic conductivity, and interbasin flow; and to simulate the effects of proposed groundwater withdrawals on the regional flow system. Meeting these objectives required the addition of 15 transient calibration stress periods and 14 projection stress periods, aquifer storage properties, historical withdrawals in Parowan Valley, and observations of water-level changes in Parowan Valley.
Recharge in Parowan Valley and withdrawal from wells in Parowan Valley and two nearby wells in Cedar City Valley vary for each calibration stress period representing conditions from March 1940 to November 2013. Stresses, including recharge, are the same in each stress period as in the steady-state stress period for all areas outside of Parowan Valley. The model was calibrated to transient conditions only in Parowan Valley. Simulated storage properties outside of Parowan Valley were set the same as the Parowan Valley properties and are not considered calibrated.
Model observations in GBCAAS v. 3.0 are groundwater levels at wells and discharge locations; water-level changes; and discharge to springs, evapotranspiration of groundwater, rivers, and lakes. All observations in the model outside of Parowan Valley are considered to represent steady-state conditions. Composite scaled sensitivities indicate the observations of discharge to rivers and springs provide more information about model parameters in the model focus area than do water-level observations. Water levels and water-level changes, however, provide the only information about specific yield and specific storage parameters and provide more information about recharge and withdrawals in Parowan Valley than any other observation group.
Comparisons of simulated water levels and measured water levels in Parowan Valley indicated that the model fits the overall trend of declining water levels and provides reasonable estimates of long-term reduction in storage and of storage changes from 2012 to 2013. The conceptual and simulated groundwater budgets for Parowan Valley from November 2012 to November 2013 are similar, with recharge of about 20,000 acre-feet and discharge of about 45,000 acre-feet. In the simulation, historical withdrawals averaging about 28,000 acre-feet per year (acre-ft/yr) cause major changes in the groundwater system in Parowan Valley. These changes include the cessation of almost all natural discharge in the valley and the long-term removal of water from storage.
Simulated recharge in Pine Valley of 11,000 acre-ft/yr and in Wah Wah Valley of 3,200 acre-ft/yr is substantially less in GBCAAS v. 3.0 than that simulated by previous model versions. In addition, the valleys have less simulated inflow from and outflow to other hydrographic areas than were simulated by previous model versions. The effects of groundwater development in these valleys, however, are independent of the amount of water recharging in and flowing through the valleys. Groundwater withdrawals in Pine and Wah Wah Valleys will decrease groundwater storage (causing drawdown) until discharge in surrounding areas and mountain springs around the two valleys is reduced by the rate of withdrawal.
The model was used to estimate that reducing withdrawals in Parowan Valley from 35,000 to about 22,000 acre-ft/yr would likely stabilize groundwater levels in the valley if recharge varies as it did from about 1950 to 2012. The model was also used to demonstrate that withdrawals of 15,000 acre-ft/yr from Pine Valley and 6,500 acre-ft/yr from Wah Wah Valley could ultimately cause long-term steady-state water-level declines of about 1,900 feet near the withdrawal wells and of more than 5 feet in an area of about 10,500 square miles. The timing of drawdown and capture and the ultimate amount of drawdown are dependent on the proximity to areas of simulated natural groundwater discharge, simulated transmissivity, and simulated storage properties. The model projections are a representation of possible effects.
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The town of Tortiya was created in the rural northern region of Côte d′Ivoire in the late 1940s to house workers for a new diamond mine. Nearly three decades later, the closure of the industrial-scale diamond mine in 1975 did not diminish the importance of diamond profits to the region's economy, and resulted in the growth of artisanal and small-scale diamond mining (ASM) within the abandoned industrial-scale mining concession. In the early 2000s, the violent conflict that arose in Côte d′Ivoire highlighted the importance of ASM land use to the local economy, but also brought about international concerns that diamond profits were being used to fund the rebellion. In recent years, cashew plantations have expanded exponentially in the region, diversifying economic activity, but also creating the potential for conflict between diamond mining and agricultural land uses. As the government looks to address the future of Tortiya and this potential conflict, a detailed spatio-temporal understanding of the changes in these two land uses over time may assist in informing policymaking. Remotely sensed imagery presents an objective and detailed spatial record of land use/land cover (LULC), and change detection methods can provide quantitative insight regarding regional land cover trends. However, the vastly different scales of ASM and cashew orchards present a unique challenge to comprehensive understanding of land use change in the region. In this study, moderate-scale categories of LULC, including cashew orchards, uncultivated forest, urban space, mining/ bare, and mixed vegetation, were produced through supervised classification of Landsat multispectral imagery from 1984, 1991, 2000, 2007, and 2014. The fine-scale ASM land use was identified through manual interpretation of annually acquired high resolution satellite imagery. Corona imagery was also integrated into the study to extend the temporal duration of the remote sensing record back to the period of industrial-scale mining. These different-scale analyses were then integrated to create a record of 46 years of mining activity and land cover change in Tortiya. While similar in spatial extent, the mining/ bare class in the integrated analysis exhibits a substantially different spatial distribution than in the original classifications. This additional information regarding the locations of ASM activity in the Tortiya area is important from a policy and planning perspective. The results of this study also suggest that LULC classifications of Landsat imagery do not consistently capture areas of ASM in the Côte d′Ivoire landscape.
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pchirico@usgs.gov","orcid":"https://orcid.org/0000-0001-8375-5342","contributorId":195555,"corporation":false,"usgs":true,"family":"Chirico","given":"Peter","email":"pchirico@usgs.gov","middleInitial":"G.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":false,"id":718839,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bergstresser, Sarah E. 0000-0003-0182-5779 sbergstresser@usgs.gov","orcid":"https://orcid.org/0000-0003-0182-5779","contributorId":195556,"corporation":false,"usgs":true,"family":"Bergstresser","given":"Sarah","email":"sbergstresser@usgs.gov","middleInitial":"E.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":718840,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Warner, Timothy A. 0000-0002-0414-9748","orcid":"https://orcid.org/0000-0002-0414-9748","contributorId":195554,"corporation":false,"usgs":false,"family":"Warner","given":"Timothy","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":718841,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70200597,"text":"70200597 - 2017 - Transgressive-regressive cycles in the metalliferous, oil-shale-bearing Heath Formation (Upper Mississippian), central Montana","interactions":[],"lastModifiedDate":"2018-10-24T16:27:54","indexId":"70200597","displayToPublicDate":"2017-11-01T16:27:46","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3481,"text":"Stratigraphy","active":true,"publicationSubtype":{"id":10}},"title":"Transgressive-regressive cycles in the metalliferous, oil-shale-bearing Heath Formation (Upper Mississippian), central Montana","docAbstract":"The Upper Mississippian Heath Formation, which accumulated in the Big Snowy Trough of central Montana, has been known for three decades to contain mudrocks highly enriched in Zn, V, Mo, Ni and other metals, and source rocks for oil. The unit has more recently been recognized as a prospective tight oil play. Here we present petrographic, paleontologic, geochemical, and carbon and sulfur isotope data on seven continuous drill cores spanning ≤146 m of immature to marginally mature strata in order to improve understanding of the depositional setting of the Heath.
The unit consists of five third-order transgressive-regressive cycles (C1–C5 from bottom to top) that were deposited during a fluctuating climatic regime. Cycles comprise thinly interbedded gray to black mudrock and carbonate strata capped by either coal, implying a humid climate (C1, C3 and C4), or gypsum, implying more arid conditions (C2); the upper part of C5 is not preserved in our study area. Mfs (maximum flooding surfaces) in C1, C2, C4, and C5 lie within black mudrock beds ~0.5–3-m thick with >10% TOC (total organic carbon), type I and type II kerogen (determined by programmed pyrolysis), high contents of Zn, V, Mo, and other metals, relatively low values of δ13CTOC and δ34Spyrite, and a limited-diversity fauna of locally abundant, thin-shelled pelecypods (Dunbarella? sp.).
The mfs in C2 is within the Cox Ranch oil shale bed, which is known from previous studies to be metalliferous; new analyses reported here show ≤28 wt % TOC, 5140 ppm Zn, 1910 ppm V, 1590 ppm Mo, and 509 ppm Ni. Strata that contain the mfs of C1, C4, and C5 are shown here for the first time to also have high metal contents, with maximum values of 1030–7340 ppm Zn, 446–1980 ppm V, 72–859 ppm Mo, and 221–452 ppm Ni. Cycle C3, which contains more gray mudrock and carbonate beds than the other cycles, has lower TOC (≤4.2 wt %), lower metals, and mainly type III kerogen. Carbonate beds include normal-marine crinoidal mudstone to packstone and lesser (dolo)mudstone with fenestral fabric, peloids, intraclasts, and a euryhaline fauna. Mid-Chesterian (early Serpukhovian) foraminifers in C3, combined with previously published fossil data, suggest that third-order cycles in the Heath Formation were ~1–2 myr in duration. They formed during a time of active block faulting in the Big Snowy Trough and global cooling linked to Gondwanan glaciation.
Tectonic, climatic, and paleogeographic factors shaped the cycles of the Heath Formation. Faunal and geochemical evidence indicate that conditions were most favorable for marine life during C3. Molybdenum concentrations >100 ppm and organic geochemical data suggest euxinic conditions during deposition of the black mudrock in C2, C4, and C5, but the presence of shell beds (1 mm–6-cm thick) within this mudrock requires bottom water with sufficient oxygen to support life, at least periodically. The apparent conflict between the geochemical and paleontologic observations likely reflects the different time scales of these two environmental proxies: 1000s of yrs vs <1–10s of yrs, respectively.
Metal- and organic-rich strata in the Heath Formation formed by slow, condensed sedimentation from periodically anoxic or euxinic bottom waters in a marine basin. Fossil data indicate that anoxia was episodic, perhaps seasonal and/or linked to longer-duration climate shifts. On a millennial time scale, metal enrichments in the Heath reflect a balance between primary productivity that was high enough for oxygen to be consumed by sinking organic matter and oxic seawater inflow that was strong enough to maintain a supply of metals without compromising anoxia. Organic-rich mudrock in the Heath shares intriguing lithologic and geochemical similarities with mudrock in other Middle to Upper Paleozoic units such as the Devonian-Mississippian Bakken Formation and Pennsylvanian cyclothems (e.g., Excello Shale).
","language":"English","publisher":"Micropress","doi":"10.29041/strat.14.1-4.97-122","usgsCitation":"Dumoulin, J.A., Johnson, C.A., Kelley, K.D., Botterell, P.J., Hackley, P.C., Scott, C., and Slack, J.F., 2017, Transgressive-regressive cycles in the metalliferous, oil-shale-bearing Heath Formation (Upper Mississippian), central Montana: Stratigraphy, v. 14, no. 1-4, p. 97-122, https://doi.org/10.29041/strat.14.1-4.97-122.","productDescription":"26 p.","startPage":"97","endPage":"122","ipdsId":"IP-077939","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":438158,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7668BPP","text":"USGS data release","linkHelpText":"Appendices for Transgressive-regressive cycles in the metalliferous, oil shale-bearing Heath Formation (Upper Mississippian), central Montana"},{"id":358777,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"Heath Formation","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.75,\n 46.75\n ],\n [\n -108.8,\n 46.75\n ],\n [\n -108.8,\n 47\n ],\n [\n -109.75,\n 47\n ],\n [\n -109.75,\n 46.75\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"14","issue":"1-4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-28","publicationStatus":"PW","scienceBaseUri":"5c10aacce4b034bf6a7e5cfd","contributors":{"authors":[{"text":"Dumoulin, Julie A. 0000-0003-1754-1287 dumoulin@usgs.gov","orcid":"https://orcid.org/0000-0003-1754-1287","contributorId":203209,"corporation":false,"usgs":true,"family":"Dumoulin","given":"Julie","email":"dumoulin@usgs.gov","middleInitial":"A.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":749684,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Craig A. 0000-0002-1334-2996 cjohnso@usgs.gov","orcid":"https://orcid.org/0000-0002-1334-2996","contributorId":909,"corporation":false,"usgs":true,"family":"Johnson","given":"Craig","email":"cjohnso@usgs.gov","middleInitial":"A.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science 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pjarboe@usgs.gov","orcid":"https://orcid.org/0000-0001-7140-0915","contributorId":5805,"corporation":false,"usgs":true,"family":"Botterell","given":"Palma","email":"pjarboe@usgs.gov","middleInitial":"J.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":749687,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hackley, Paul C. 0000-0002-5957-2551 phackley@usgs.gov","orcid":"https://orcid.org/0000-0002-5957-2551","contributorId":592,"corporation":false,"usgs":true,"family":"Hackley","given":"Paul","email":"phackley@usgs.gov","middleInitial":"C.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":749688,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Scott, Clint 0000-0003-2778-2711 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,{"id":70193051,"text":"ofr20171135 - 2017 - Near-field receiving water monitoring of trace metals and a benthic community near the Palo Alto Regional Water Quality Control Plant in south San Francisco Bay, California; 2016","interactions":[],"lastModifiedDate":"2023-04-24T21:14:41.275526","indexId":"ofr20171135","displayToPublicDate":"2017-10-30T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-1135","title":"Near-field receiving water monitoring of trace metals and a benthic community near the Palo Alto Regional Water Quality Control Plant in south San Francisco Bay, California; 2016","docAbstract":"Trace-metal concentrations in sediment and in the clam Macoma petalum (formerly reported as Macoma balthica), clam reproductive activity, and benthic macroinvertebrate community structure were investigated in a mudflat 1 kilometer south of the discharge of the Palo Alto Regional Water Quality Control Plant (PARWQCP) in south San Francisco Bay, Calif. This report includes the data collected by U.S. Geological Survey (USGS) scientists for the period January 2014 to December 2016. These append to long-term datasets extending back to 1974. A major focus of the report is an integrated description of the 2016 data within the context of the longer, multi-decadal dataset. This dataset supports the City of Palo Alto’s Near-Field Receiving Water Monitoring Program, initiated in 1994.
Significant reductions in silver and copper concentrations in sediment and M. petalum occurred at the site in the 1980s following the implementation by PARWQCP of advanced wastewater treatment and source control measures. Since the 1990s, concentrations of these elements appear to have stabilized at concentrations somewhat above (silver) or near (copper) regional background concentrations Data for other metals, including chromium (Cr), mercury (Hg), nickel (Ni), selenium (Se), and zinc (Zn), have been collected since 1994. Over this period, concentrations of these elements have remained relatively constant, aside from seasonal variation that is common to all elements. In 2016, concentrations of silver and copper in M. petalum varied seasonally in response to a combination of site-specific metal exposures and annual growth and reproduction, as reported previously. Seasonal patterns for other elements, including Cr, Ni, Zn, Hg, and Se, were generally similar in timing and magnitude as those for Ag and Cu. This record suggests that legacy contamination and regional-scale factors now largely control sedimentary and bioavailable concentrations of silver and copper, as well as other elements of regulatory interest, at the Palo Alto site.
Analyses of the benthic community structure of a mudflat in south San Francisco Bay over a 40-year period show that changes in the community have occurred concurrent with reduced concentrations of metals in the sediment and in the tissues of the biosentinel clam, M. petalum, from the same area. Analysis of M. petalum shows increases in reproductive activity concurrent with the decline in metal concentrations in the tissues of this organism. Reproductive activity is presently stable (2016), with almost all animals initiating reproduction in the fall and spawning the following spring. The entire infaunal community has shifted from being dominated by several opportunistic species to a community where the species are more similar in abundance, a pattern that indicates a more stable community that is subjected to fewer stressors. In addition, two of the opportunistic species (Ampelisca abdita and Streblospio benedicti) that brood their young and live on the surface of the sediment in tubes have shown a continual decline in dominance coincident with the decline in metals; both species had short-lived rebounds in abundance in 2008, 2009, and 2010 and showed signs of increasing abundance in 2016. Heteromastus filiformis (a subsurface polychaete worm that lives in the sediment, consumes sediment and organic particles residing in the sediment, and reproduces by laying its eggs on or in the sediment) showed a concurrent increase in dominance and, in the last several years before 2008, showed a stable population. H. filiformis abundance increased slightly in 2011–2012 and returned to pre-2011 numbers in 2016. An unidentified disturbance occurred on the mudflat in early 2008 that resulted in the loss of the benthic animals, except for deep-dwelling animals like Macoma petalum. However, within two months of this event animals returned to the mudflat. The resilience of the community suggested that the disturbance was not due to a persistent toxin or anoxia. The reproductive mode of most species present in 2016 is reflective of species that were available either as pelagic larvae or as mobile adults. Although oviparous species were lower in number in this group, the authors hypothesize that these species will return slowly as more species move back into the area. The use of functional ecology was highlighted in the 2016 benthic community data, which showed that the animals that have now returned to the mudflat are those that can respond successfully to a physical, nontoxic disturbance. Today, community data show a mix of species that consume the sediment, or filter feed, have pelagic larvae that must survive landing on the sediment, and those that brood their young. USGS scientists view the 2008 disturbance event as a response by the infaunal community to an episodic natural stressor (possibly sediment accretion or a pulse of freshwater), in contrast to the long-term recovery from metal contamination. We will compare this recovery to the long-term recovery observed after the 1970s when the decline in sediment pollutants was the dominating factor.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171135","collaboration":"Prepared in cooperation with the City of Palo Alto, California","usgsCitation":"Cain, D.J., Thompson, J.K., Parchaso, F., Pearson, S., Stewart, R., Turner, M., Barasch, D., and Luoma, S.N., 2017, Near-field receiving water monitoring of trace metals and a benthic community near the Palo Alto Regional Water Quality Control Plant in south San Francisco Bay, California; 2016: U.S. Geological Survey Open-File Report 2017–1135, 75 p., https://doi.org/10.3133/ofr20171135.","productDescription":"vi, 75 p.","numberOfPages":"82","onlineOnly":"Y","ipdsId":"IP-088104","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":416202,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20231017","text":"Open-File Report 2023-1017","linkHelpText":"- Near-Field Receiving-Water Monitoring of Trace Metals and a Benthic Community Near the Palo Alto Regional Water Quality Control Plant in South San Francisco Bay, California—2020"},{"id":416201,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20211079","text":"Open-File Report 2021-1079","linkHelpText":"- Near-Field Receiving-Water Monitoring of Trace Metals and a Benthic Community Near the Palo Alto Regional Water Quality Control Plant in South San Francisco Bay, California—2019"},{"id":416200,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20191084","text":"Open-File Report 2019-1084","linkHelpText":"- Near-Field Receiving-Water Monitoring of Trace Metals and a Benthic Community Near the Palo Alto Regional Water Quality Control Plant in South San Francisco Bay, California—2018"},{"id":416199,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20181107","text":"Open-File Report 2018-1107","linkHelpText":"- Near-field receiving-water monitoring of trace metals and a benthic community near the Palo Alto Regional Water Quality Control Plant in south San Francisco Bay, California—2017"},{"id":416198,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20161118","text":"Open-File Report 2016-1118","linkHelpText":"- Near-field receiving water monitoring of trace metals and a benthic community near the Palo Alto Regional Water Quality Control Plant in south San Francisco Bay, California; 2015"},{"id":347750,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1135/coverthb_.jpg"},{"id":347751,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1135/ofr.20171135.pdf","text":"Report","size":"4.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1135"}],"country":"United States","state":"California","city":"Palo Alto","otherGeospatial":"south San Francisco bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.16590881347656,\n 37.398528132728615\n ],\n [\n -121.91184997558595,\n 37.398528132728615\n ],\n [\n -121.91184997558595,\n 37.54566616715801\n ],\n [\n -122.16590881347656,\n 37.54566616715801\n ],\n [\n -122.16590881347656,\n 37.398528132728615\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"NRP staff
National Research Program
U.S. Geological Survey
345 Middlefield Road, MS-435
Menlo Park, CA 94025
During 2013, the U.S. Geological Survey (USGS) National Water-Quality Assessment Project (NAWQA), in collaboration with the USGS Columbia Environmental Research Center, the U.S. Environmental Protection Agency (EPA) National Rivers and Streams Assessment (NRSA), and the EPA Office of Pesticide Programs assessed stream quality across the Midwestern United States. This Midwest Stream Quality Assessment (MSQA) simultaneously characterized watershed and stream-reach water-quality stressors along with instream biological conditions, to better understand regional stressor-effects relations. The MSQA design focused on effects from the widespread agriculture in the region and urban development because of their importance as ecological stressors of particular concern to Midwest region resource managers.
A combined random stratified selection and a targeted selection based on land-use data were used to identify and select sites representing gradients in agricultural intensity across the region. During a 14-week period from May through August 2013, 100 sites were selected and sampled 12 times for contaminants, nutrients, and sediment. This 14-week water-quality “index” period culminated with an ecological survey of habitat, periphyton, benthic macroinvertebrates, and fish at all sites. Sediment was collected during the ecological survey for analysis of sediment chemistry and toxicity testing. Of the 100 sites, 50 were selected for the MSQA random stratified group from 154 NRSA sites planned for the region, and the other 50 MSQA sites were selected as targeted sites to more evenly cover agricultural and urban stressor gradients in the study area. Of the 50 targeted sites, 12 were in urbanized watersheds and 21 represented “good” biological conditions or “least disturbed” conditions. The remaining 17 targeted sites were selected to improve coverage of the agricultural intensity gradient or because of historical data collection to provide temporal context for the study.
This report provides a detailed description of the MSQA study components, including surveys of ecological conditions, routine water sampling, deployment of passive polar organic compound integrative samplers, and stream sediment sampling at all sites. Component studies that were completed to provide finer scale temporal data or more extensive analysis at selected sites, included continuous water-quality monitoring, daily pesticide sampling, laboratory and in-stream water toxicity testing efforts, and deployment of passive suspended-sediment samplers.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171073","collaboration":"National Water-Quality Program Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Garrett, J.D., Frey, J.W., Van Metre, P.C., Journey, C.A., Nakagaki, Naomi, Button, D.T., and Howell, L.H., 2017, Design and methods of the Midwest Stream Quality Assessment (MSQA), 2013: U.S. Geological Survey Open-File Report 2017–1073, 59 p., 4 app., https://doi.org/10.3133/ofr20171073.","productDescription":"Report: x, 57 p.; 4 Appendixes","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-075316","costCenters":[{"id":451,"text":"National Water Quality Assessment 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Reach, and Watershed Characteristics of Selected Sites Assessed as Part of the U.S. Geological Survey (USGS) National Water-Quality Assessment (NAWQA) Midwest Stream Quality Assessment (MSQA) in 2013"},{"id":346661,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2017/1073/ofr20171073_appendix3_SampleCounts.xlsx","text":"Appendix 3","size":"50.5 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"Appendix 3","linkHelpText":"- Description of Quality Control Samples"},{"id":346662,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2017/1073/ofr20171073_appendix4_Workplan.xlsx","text":"Appendix 4","size":"27.5 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"Appendix 4","linkHelpText":"- Description of the Sampling Timelines, Matrix, Collection, and Processing for Water, Sediment, and Ecological Samples"}],"country":"United States","state":"Illinois, Indiana, Iowa, Kansas, Kentucky, Michigan, Minnesota, Missouri, Nebraska, 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Many approaches have been developed for measuring or estimating actual evapotranspiration (ETa), and research over many years has led to the development of remote sensing methods that are reliably reproducible and effective in estimating ETa. Several remote sensing methods can be used to estimate ETa at the high spatial resolution of agricultural fields and the large extent of river basins. More complex remote sensing methods apply an analytical approach to ETa estimation using physically based models of varied complexity that require a combination of ground-based and remote sensing data, and are grounded in the theory behind the surface energy balance model. This report, funded through cooperation with the International Joint Commission, provides an overview of selected remote sensing methods used for estimating water consumed through ETa and focuses on Mapping Evapotranspiration at High Resolution with Internalized Calibration (METRIC) and Operational Simplified Surface Energy Balance (SSEBop), two energy balance models for estimating ETa that are currently applied successfully in the United States. The METRIC model can produce maps of ETa at high spatial resolution (30 meters using Landsat data) for specific areas smaller than several hundred square kilometers in extent, an improvement in practice over methods used more generally at larger scales. Many studies validating METRIC estimates of ETa against measurements from lysimeters have shown model accuracies on daily to seasonal time scales ranging from 85 to 95 percent. The METRIC model is accurate, but the greater complexity of METRIC results in greater data requirements, and the internalized calibration of METRIC leads to greater skill required for implementation. In contrast, SSEBop is a simpler model, having reduced data requirements and greater ease of implementation without a substantial loss of accuracy in estimating ETa. The SSEBop model has been used to produce maps of ETa over very large extents (the conterminous United States) using lower spatial resolution (1 kilometer) Moderate Resolution Imaging Spectroradiometer (MODIS) data. Model accuracies ranging from 80 to 95 percent on daily to annual time scales have been shown in numerous studies that validated ETa estimates from SSEBop against eddy covariance measurements. The METRIC and SSEBop models can incorporate low and high spatial resolution data from MODIS and Landsat, but the high spatiotemporal resolution of ETa estimates using Landsat data over large extents takes immense computing power. Cloud computing is providing an opportunity for processing an increasing amount of geospatial “big data” in a decreasing period of time. For example, Google Earth EngineTM has been used to implement METRIC with automated calibration for regional-scale estimates of ETa using Landsat data. The U.S. Geological Survey also is using Google Earth EngineTM to implement SSEBop for estimating ETa in the United States at a continental scale using Landsat data.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175087","collaboration":"Prepared in cooperation with the International Joint Commission","usgsCitation":"McShane, R.R., Driscoll, K.P., and Sando, Roy, 2017, A review of surface energy balance models for estimating actual evapotranspiration with remote sensing at high spatiotemporal resolution over large extents: U.S. Geological Survey Scientific Investigations Report 2017–5087, 19 p., https://doi.org/10.3133/sir20175087.","productDescription":"vi, 19 p.","numberOfPages":"30","onlineOnly":"Y","ipdsId":"IP-083112","costCenters":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"links":[{"id":346073,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5087/coverthb.jpg"},{"id":346074,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5087/sir20175087.pdf","text":"Report","size":"678 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5087"}],"contact":"Director, Wyoming-Montana Water Science Center
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Hurricane Sandy, which made landfall on October 29, 2012, near Atlantic City, New Jersey, had a significant impact on the coastal system along the south shore of Long Island, New York. A record significant wave height of 9.6 meters (m) was measured at wave buoy 44025, approximately 48 kilometers offshore of Fire Island, New York. Surge and runup during the storm resulted in extensive beach and dune erosion and breaching of the Fire Island barrier island system at two locations, including a breach that formed within the Otis Pike Fire Island High Dune Wilderness area on the eastern side of Fire Island.
The U.S. Geological Survey (USGS) has a long history of conducting morphologic change and processes research at Fire Island. One of the primary objectives of the current research effort is to understand the morphologic evolution of the barrier system on a variety of time scales (from storm scale to decade(s) to century). A number of studies that support the project objectives have been published. Prior to Hurricane Sandy, however, little information was available on specific storm-driven change in this region. The USGS received Hurricane Sandy supplemental funding (project GS2–2B: Linking Coastal Processes and Vulnerability, Fire Island, New York, Regional Study) to enhance existing research efforts at Fire Island. The existing research was greatly expanded to include inner continental shelf mapping and investigations of processes of inner shelf sediment transport; beach and dune response and recovery; and observation, analysis, and modeling of the newly formed breach in the Otis Pike High Dune Wilderness area, herein referred to as the wilderness breach. The breach formed at the site of Old Inlet, which was open from 1763 to 1825. The location of the initial island breaching does not directly correspond with topographic lows of the dunes, but instead the breach formed in the location of a cross-island boardwalk that was destroyed during Hurricane Sandy.
From 2013 to November 2015, bathymetric data were collected by the USGS St. Petersburg Coastal and Marine Science Center during three surveys of the breach channel and tidal shoals, and shoreline positions on each side of the breach (also collected by the National Park Service). Additionally, pre-storm topography/bathymetry EAARL–B light detection and ranging (lidar) data were collected by the USGS the day prior to Hurricane Sandy’s landfall. These data serve as a baseline for change analyses during four subsequent periods: June 2013, June 2014, October 2014, and May 2015. The June 2013 single-beam bathymetry data were collected in collaboration with the U.S. Army Corps of Engineers (USACE), using the Lighter Amphibious Resupply Cargo (LARC) vessel, and included the ebb shoal and breach channel. The USGS collected and processed the three additional bathymetric datasets using personal watercraft equipped with single-beam echo sounders and backpack Global Positioning System (GPS) over shallow flood shoals.
Eastern and western breach shorelines were surveyed weekly to monthly beginning on November 6, 2012 (by the National Park Service [NPS], and USGS St. Petersburg Coastal and Marine Science Center), with measurements made every few weeks for the first year and every few months after October 2013. The NPS and researchers from Stony Brook University monitored the breach by collecting field data of the breach channel bathymetry, conducting aerial photographic overflights, and performing water-quality analyses (see http://po.msrc.sunysb.edu/GSB/). The aerial photography collected and rectified by Stony Brook University is used extensively in our morphologic change description to examine changes to breach shorelines (supplementing shoreline data collected in the field), channel width, and orientation. Due to the uncertainties and the variation in survey methods, a rigorous quantitative analysis was not performed. However, average calculations of various breach metrics allow a qualitative analysis of breach development and evolution.
This report presents an overview of the data collected and a summary discussion of the observed changes to the breach system and the seasonal wave climatology associated with the breach morphodynamic response.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171116","usgsCitation":"Hapke, C.J., Nelson, T.R., Henderson, R.E., Brenner, O.T., and Miselis, J.L., 2017, Morphologic evolution of the wilderness area breach at Fire Island, New York—2012–15: U.S. Geological Survey Open-File Report 2017–1116, 17 p., https://doi.org/10.3133/ofr20171116.","productDescription":"Report: vi, 17 p.","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-086286","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":345809,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ds1049","text":"Data Series 1049","description":"Data Series 1049","linkHelpText":"- Coastal bathymetry data collected in May 2015 from Fire Island, New York—Wilderness breach and shoreface"},{"id":345808,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ds1034","text":"Data Series 1034","description":"Data Series 1034","linkHelpText":"Bathymetry data collected in October 2014 from Fire Island, New York—The wilderness breach, shoreface, and bay"},{"id":345810,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ds1007","text":"Data Series 1007","description":"Data Series 1007","linkHelpText":"- Coastal bathymetry data collected in June 2014 from Fire Island, New York—The wilderness breach and shoreface"},{"id":345750,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1116/coverthb.jpg"},{"id":345805,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1116/ofr20171116.pdf","text":"Report","size":"21.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1116"},{"id":345806,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ds914","text":"Data Series 914","description":"Data Series 914","linkHelpText":"- Bathymetry of Wilderness Breach at Fire Island, New York from June 2013"},{"id":345807,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7G15Z17","text":"USGS data release","description":"USGS data release","linkHelpText":"Hurricane Sandy Beach Response and Recovery at Fire Island, New York—Shoreline and Beach Profile Data, October 2012 to June 2016"}],"country":"United States","state":"New York","otherGeospatial":"Fire Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.32000732421875,\n 40.6113461833302\n ],\n [\n -72.87574768066406,\n 40.6113461833302\n ],\n [\n -72.87574768066406,\n 40.73581157695217\n ],\n [\n -73.32000732421875,\n 40.73581157695217\n ],\n [\n -73.32000732421875,\n 40.6113461833302\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, St. Petersburg Coastal and Marine Science Center
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Continuous records of discharge and turbidity at a U.S. Geological Survey (USGS) streamgage in the lower Stillaguamish River were paired with discrete measurements of suspended-sediment concentration (SSC) in order to estimate suspended-sediment loads over the water years 2014 and 2015. First, relations between turbidity and SSC were developed and used to translate the continuous turbidity record into a continuous estimate of SSC. Those concentrations were then used to predict suspended-sediment loads based on the current discharge record, reported at daily intervals. Alternative methods were used to in-fill a small number of days with either missing periods of turbidity or discharge records. Uncertainties in our predictions at daily and annual time scales were estimated based on the parameter uncertainties in our turbidity-SSC regressions. Daily loads ranged from as high as 121,000 tons during a large autumn storm to as low as –56 tons, when tidal return flow moved more sediment upstream than river discharge did downstream. Annual suspended-sediment loads for both water years were close to 1.4 ± 0.2 million tons.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171066","usgsCitation":"Anderson, S.W., Curran, C.A., and Grossman, E.E., 2017, Suspended-sediment loads in the lower Stillaguamish River, Snohomish County, Washington, 2014–15: U.S. Geological Survey Open-File Report 2017–1066, 10 p., https://doi.org/10.3133/ofr20171066.","productDescription":"Report: iv, 10 p.; Table","numberOfPages":"10","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-085882","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":344567,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1066/coverthb.jpg"},{"id":344568,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1066/ofr2017.1066.pdf","text":"Report","size":"1.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1066"},{"id":344569,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2017/1066/ofr20171066_table03.xlsx","text":"Table 3","size":"46 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2017-1066"}],"country":"United States","state":"Washington","county":"Snohomish County","otherGeospatial":"Lower Stillaguamish River","contact":"Director,
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Climate change, tectonics, and humans create long- and short-term temporal variations in the supply of suspended sediment to rivers. These signals, generated in upland erosional areas, are filtered by alluvial storage before reaching the basin outlet. We quantified this filter using a random walk model driven by sediment budget data, a power-law distributed probability density function (PDF) to determine how long sediment remains stored, and a constant downstream drift velocity during transport of 157 km/yr. For 25 km of transport, few particles are stored, and the median travel time is 0.2 yr. For 1000 km of transport, nearly all particles are stored, and the median travel time is 2.5 m.y. Both travel-time distributions are power laws. The 1000 km travel-time distribution was then used to filter sinusoidal input signals with periods of 10 yr and 104 yr. The 10 yr signal is delayed by 12.5 times its input period, damped by a factor of 380, and is output as a power law. The 104 yr signal is delayed by 0.15 times its input period, damped by a factor of 3, and the output signal retains its sinusoidal input form (but with a power-law “tail”). Delivery time scales for these two signals are controlled by storage; in-channel transport time is insignificant, and low-frequency signals are transmitted with greater fidelity than high-frequency signals. These signal modifications are essential to consider when evaluating watershed restoration schemes designed to control sediment loading, and where source-area geomorphic processes are inferred from the geologic record.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/G38170.1","usgsCitation":"Pizzuto, J.E., Keeler, J., Skalak, K., and Karwan, D., 2017, Storage filters upland suspended sediment signals delivered from watersheds: Geology, v. 45, no. 2, p. 151-154, https://doi.org/10.1130/G38170.1.","productDescription":"4 p.","startPage":"151","endPage":"154","ipdsId":"IP-081208","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":343977,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"45","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-02-01","publicationStatus":"PW","scienceBaseUri":"596f1e1ee4b0d1f9f0640734","contributors":{"authors":[{"text":"Pizzuto, James E.","contributorId":49424,"corporation":false,"usgs":false,"family":"Pizzuto","given":"James","email":"","middleInitial":"E.","affiliations":[{"id":13220,"text":"The Charles E. Via, Jr. Department of Civil and Environmental Engineering, Virginia Polytechnic Institute and State University","active":true,"usgs":false}],"preferred":false,"id":705310,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Keeler, Jeremy","contributorId":194778,"corporation":false,"usgs":false,"family":"Keeler","given":"Jeremy","email":"","affiliations":[],"preferred":false,"id":705311,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Skalak, Katherine 0000-0003-4122-1240 kskalak@usgs.gov","orcid":"https://orcid.org/0000-0003-4122-1240","contributorId":3990,"corporation":false,"usgs":true,"family":"Skalak","given":"Katherine","email":"kskalak@usgs.gov","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":705309,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Karwan, Diana","contributorId":194779,"corporation":false,"usgs":false,"family":"Karwan","given":"Diana","affiliations":[],"preferred":false,"id":705312,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70188566,"text":"70188566 - 2017 - The role of paleoecology in restoration and resource management—The past as a guide to future decision-making: Review and example from the Greater Everglades Ecosystem, U.S.A","interactions":[],"lastModifiedDate":"2017-06-15T13:12:17","indexId":"70188566","displayToPublicDate":"2017-06-15T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3910,"text":"Frontiers in Ecology and Evolution","onlineIssn":"2296-701X","active":true,"publicationSubtype":{"id":10}},"title":"The role of paleoecology in restoration and resource management—The past as a guide to future decision-making: Review and example from the Greater Everglades Ecosystem, U.S.A","docAbstract":"Resource managers around the world are challenged to develop feasible plans for sustainable conservation and/or restoration of the lands, waters, and wildlife they administer—a challenge made greater by anticipated climate change and associated effects over the next century. Increasingly, paleoecologic and geologic archives are being used to extend the period of record of observed data and provide information on centennial to millennial scale responses to long-term drivers of ecosystem change. The development of paleoecology from an emerging field investigating past environments to a highly relevant applied science is reviewed and general examples of the application of paleoecologic research to resource management questions in diverse habitats and regions are provided. Specific examples of the application of paleoecologic research to the restoration of the Greater Everglades Ecosystem of south Florida (U.S.A) are presented. Conducting valuable scientific research that would benefit resource management decisions, however, is not enough. Scientists and resource managers need to be engaged in collaborative discussions from the beginning of the research process to ensure that management questions are being addressed and that the science reaches the people who will benefit from the information. Paleoecology and related disciplines provide an understanding of how ecosystems and individual species function and change over time in response to both natural and anthropogenic drivers. Information on pre-anthropogenic baseline conditions is provided by paleoecologic research, but it is the detection of long-term trends and cycles that allow resource managers to set realistic goals and targets by moving away from the fixed-point baseline concept to one of dynamic landscapes that anticipates and incorporates an expectation of change into decision-making.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fevo.2017.00011","usgsCitation":"Wingard, G.L., Bernhardt, C.E., and Wachnicka, A., 2017, The role of paleoecology in restoration and resource management—The past as a guide to future decision-making: Review and example from the Greater Everglades Ecosystem, U.S.A: Frontiers in Ecology and Evolution, v. 5, Article 11: 24 p., https://doi.org/10.3389/fevo.2017.00011.","productDescription":"Article 11: 24 p.","ipdsId":"IP-079801","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":469750,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fevo.2017.00011","text":"Publisher Index Page"},{"id":342551,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Greater Everglades Ecosystem","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.5347900390625,\n 24.42214378185897\n ],\n [\n -79.9200439453125,\n 24.42214378185897\n ],\n [\n -79.9200439453125,\n 27.196014383173306\n ],\n [\n -82.5347900390625,\n 27.196014383173306\n ],\n [\n -82.5347900390625,\n 24.42214378185897\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"5","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-03-06","publicationStatus":"PW","scienceBaseUri":"59439c92e4b062508e31a986","contributors":{"authors":[{"text":"Wingard, G. Lynn 0000-0002-3833-5207 lwingard@usgs.gov","orcid":"https://orcid.org/0000-0002-3833-5207","contributorId":605,"corporation":false,"usgs":true,"family":"Wingard","given":"G.","email":"lwingard@usgs.gov","middleInitial":"Lynn","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":698366,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bernhardt, Christopher E. 0000-0003-0082-4731 cbernhardt@usgs.gov","orcid":"https://orcid.org/0000-0003-0082-4731","contributorId":2131,"corporation":false,"usgs":true,"family":"Bernhardt","given":"Christopher","email":"cbernhardt@usgs.gov","middleInitial":"E.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":698367,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wachnicka, Anna","contributorId":15500,"corporation":false,"usgs":true,"family":"Wachnicka","given":"Anna","email":"","affiliations":[],"preferred":false,"id":698368,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70188465,"text":"70188465 - 2017 - Pulsed strain release on the Altyn Tagh fault, northwest China","interactions":[],"lastModifiedDate":"2018-10-24T16:43:47","indexId":"70188465","displayToPublicDate":"2017-06-13T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1427,"text":"Earth and Planetary Science Letters","active":true,"publicationSubtype":{"id":10}},"title":"Pulsed strain release on the Altyn Tagh fault, northwest China","docAbstract":"Earthquake recurrence models assume that major surface-rupturing earthquakes are followed by periods of reduced rupture probability as stress rebuilds. Although purely periodic, time- or slip-predictable rupture models are known to be oversimplifications, a paucity of long records of fault slip clouds understanding of fault behavior and earthquake recurrence over multiple ruptures. Here, we report a 16 kyr history of fault slip—including a pulse of accelerated slip from 6.4 to 6.0 ka—determined using a Monte Carlo analysis of well-dated offset landforms along the central Altyn Tagh strike-slip fault (ATF) in northwest China. This pulse punctuates a median rate of 8.1+1.2/−0.9 mm/a and likely resulted from either a flurry of temporally clustered ∼Mw 7.5 ground-rupturing earthquakes or a single large >Mw 8.2 earthquake. The clustered earthquake scenario implies rapid re-rupture of a fault reach >195 km long and indicates decoupled rates of elastic strain energy accumulation versus dissipation, conceptualized as a crustal stress battery. If the pulse reflects a single event, slip-magnitude scaling implies that it ruptured much of the ATF with slip similar to, or exceeding, the largest documented historical ruptures. Both scenarios indicate fault rupture behavior that deviates from classic time- or slip-predictable models.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.epsl.2016.11.024","usgsCitation":"Gold, R.D., Cowgill, E., Arrowsmith, J.R., and Friedrich, A.M., 2017, Pulsed strain release on the Altyn Tagh fault, northwest China: Earth and Planetary Science Letters, v. 459, p. 291-300, https://doi.org/10.1016/j.epsl.2016.11.024.","productDescription":"10 p.","startPage":"291","endPage":"300","ipdsId":"IP-081268","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":469832,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.epsl.2016.11.024","text":"Publisher Index Page"},{"id":342419,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"China","otherGeospatial":"Altyn Tagh fault","volume":"459","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5940f9b1e4b0764e6c63eaa4","contributors":{"authors":[{"text":"Gold, Ryan D. 0000-0002-4464-6394 rgold@usgs.gov","orcid":"https://orcid.org/0000-0002-4464-6394","contributorId":3883,"corporation":false,"usgs":true,"family":"Gold","given":"Ryan","email":"rgold@usgs.gov","middleInitial":"D.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":697890,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cowgill, Eric","contributorId":192850,"corporation":false,"usgs":false,"family":"Cowgill","given":"Eric","affiliations":[],"preferred":false,"id":697891,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Arrowsmith, J. Ramon","contributorId":80209,"corporation":false,"usgs":false,"family":"Arrowsmith","given":"J.","email":"","middleInitial":"Ramon","affiliations":[{"id":24511,"text":"Arizona State University, Tempe AZ USA 85287","active":true,"usgs":false}],"preferred":false,"id":697892,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Friedrich, Anke M.","contributorId":192852,"corporation":false,"usgs":false,"family":"Friedrich","given":"Anke","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":697916,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70186602,"text":"sir20175025 - 2017 - Evaluation of long-term trends in hydrologic and water-quality conditions, and estimation of water budgets through 2013, Chester County, Pennsylvania","interactions":[],"lastModifiedDate":"2017-07-10T14:14:42","indexId":"sir20175025","displayToPublicDate":"2017-06-02T11:15:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-5025","title":"Evaluation of long-term trends in hydrologic and water-quality conditions, and estimation of water budgets through 2013, Chester County, Pennsylvania","docAbstract":"An evaluation of trends in hydrologic and water quality conditions and estimation of water budgets through 2013 was done by the U.S. Geological Survey in cooperation with the Chester County Water Resources Authority. Long-term hydrologic, meteorologic, and biologic data collected in Chester County, Pennsylvania, which included streamflow, groundwater levels, surface-water quality, biotic integrity, precipitation, and air temperature were analyzed to determine possible trends or changes in hydrologic conditions. Statistically significant trends were determined by applying the Kendall rank correlation test; the magnitudes of the trends were determined using the Sen slope estimator. Water budgets for eight selected watersheds were updated and a new water budget was developed for the Marsh Creek watershed. An average water budget for Chester County was developed using the eight selected watersheds and the new Marsh Creek water budget.
Annual and monthly mean streamflow, base flow, and runoff were analyzed for trends at 10 streamgages. The periods of record at the 10 streamgages ranged from 1961‒2013 to 1988‒2013. The only statistically significant trend for annual mean streamflow was for West Branch Brandywine Creek near Honey Brook, Pa. (01480300) where annual mean streamflow increased 1.6 cubic feet per second (ft3/s) per decade. The greatest increase in monthly mean streamflow was for Brandywine Creek at Chadds Ford, Pa. (01481000) for December; the increase was 47 ft3/s per decade. No statistically significant trends in annual mean base flow or runoff were determined for the 10 streamgages. The greatest increase in monthly mean base flow was for Brandywine Creek at Chadds Ford, Pa. (01481000) for December; the increase was 26 ft3/s per decade.
The magnitude of peaks greater than a base streamflow was analyzed for trends for 12 streamgages. The period of record at the 12 stream gages ranged from 1912‒2012 to 2004–11. Fifty percent of the streamgages showed a small statistically significant increase in peaks greater than the base streamflow. The greatest increase was for Brandywine Creek at Chadds Ford, Pa. (01481000) during 1962‒2012; the increase was 1.8 ft3/s per decade. There were no statistically significant trends in the number of floods equal to or greater than the 2-year recurrence interval flood flow.
Twenty‒one monitoring wells were evaluated for statistically significant trends in annual mean water level, minimum annual water level, maximum annual water level, and annual range in water-level fluctuations. For four wells, a small statistically significant increase in annual mean water level was determined that ranged from 0.16 to 0.7 feet per decade. There was poor or no correlation between annual mean groundwater levels and annual mean streamflow and base flow. No correlation was determined between annual mean groundwater level and annual precipitation. Despite rapid population growth and land-use change since 1950, there appears to have been little or no detrimental effects on groundwater levels in 21 monitoring wells.
Long-term precipitation and temperature data were available from the West Chester (1893‒2013) and Phoenixville, Pa. (1915‒2013) National Oceanic and Atmospheric Administration (NOAA) weather stations. No statistically significant trends in annual mean precipitation or annual mean temperature were determined for either station. Both weather stations had a significant decrease in the number of days per year with precipitation greater than or equal to 0.1 inch. Annual mean minimum and maximum temperatures from the NOAA Southeastern Piedmont Climate Division increased 0.2 degrees Fahrenheit (F) per decade between 1896 and 2014. The number of days with a maximum temperature equal to or greater than 90 degrees F increased at West Chester and decreased at Phoenixville. No statistically significant trend was determined for annual snowfall amounts.
Data from 1974 to 2013 for three stream water-quality monitors in the Brandywine Creek watershed were evaluated. The monitors are on the West Branch Brandywine Creek at Modena, Pa. (01480617), East Branch Brandywine Creek below Downingtown, Pa. (01480870), and Brandywine Creek at Chadds Ford, Pa. (01481000). Statistically significant upward trends were determined for annual mean specific conductance at all three stations, indicating the total dissolved solids load has been increasing. If the current trend continues, the annual mean specific conductance could almost double from 1974 to 2050. The increase in specific conductance likely is due to increases in chloride concentrations, which have been increasing steadily over time at all three stations. No correlation was found between monthly mean specific conductance and monthly mean streamflow or base flow. Statistically significant upward trends in pH were determined for all three stations. Statistically significant upward trends in stream temperature were determined for East Branch Brandywine Creek below Downingtown, Pa. (01480870) and Brandywine Creek at Chadds Ford, Pa. (01481000). The stream water-quality data indicate substantial increases in the minimum daily dissolved oxygen concentrations in the Brandywine Creek over time.
The Chester County Index of Biotic Integrity (CC-IBI) determined for 1998‒2013 was evaluated for the five biological sampling sites collocated with streamgages. CC-IBI scores are based on a 0‒100 scale with higher scores indicating better stream quality. Statistically significant upward trends in the CC-IBI were determined for West Branch Brandywine Creek at Modena, Pa. (01480617) and East Branch Brandywine Creek below Downingtown, Pa. (01480870). No correlation was found between the CC-IBI and streamflow, precipitation, or stream specific conductance, pH, temperature, or dissolved oxygen concentration.
A Chester County average water budget was developed using the nine estimated watershed water budgets. Average precipitation was 48.4 inches, and average streamflow was 21.4 inches. Average runoff and base flow were 8.3 and 13.1 inches, respectively, and average evapotranspiration and estimation of errors was 27.2 inches.\"
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175025","collaboration":"Prepared in cooperation with the Chester County Water Resources Authority","usgsCitation":"Sloto, R.A., and Reif, A.G., 2017, Evaluation of long-term trends in hydrologic and water-quality conditions, and estimation of water budgets through 2013, Chester County, Pennsylvania (ver.1.1, July 2017): U.S. Geological Survey Scientific Investigations Report 2017–5025, 59 p., https://doi.org/10.3133/sir20175025.","productDescription":"vii, 59 p.","numberOfPages":"71","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-064731","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":341981,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5025/sir20175025.pdf","text":"Report","size":"8.49 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 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1.0: Originally posted June 2,2017; Version 1.1: July 10, 2017","contact":"Director, Pennsylvania Water Science Center
U.S. Geological Survey
215 Limekiln Road
New Cumberland, PA 17070
Assessment of water resources at a national scale is critical for understanding their vulnerability to future change in policy and climate. Representation of the spatiotemporal variability in snowmelt processes in continental-scale hydrologic models is critical for assessment of water resource response to continued climate change. Continental-extent hydrologic models such as the U.S. Geological Survey National Hydrologic Model (NHM) represent snowmelt processes through the application of snow depletion curves (SDCs). SDCs relate normalized snow water equivalent (SWE) to normalized snow covered area (SCA) over a snowmelt season for a given modeling unit. SDCs were derived using output from the operational Snow Data Assimilation System (SNODAS) snow model as daily 1-km gridded SWE over the conterminous United States. Daily SNODAS output were aggregated to a predefined watershed-scale geospatial fabric and used to also calculate SCA from October 1, 2004 to September 30, 2013. The spatiotemporal variability in SNODAS output at the watershed scale was evaluated through the spatial distribution of the median and standard deviation for the time period. Representative SDCs for each watershed-scale modeling unit over the conterminous United States (n = 54,104) were selected using a consistent methodology and used to create categories of snowmelt based on SDC shape. The relation of SDC categories to the topographic and climatic variables allow for national-scale categorization of snowmelt processes.
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\"}}]}\n","volume":"53","issue":"3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-04-13","publicationStatus":"PW","scienceBaseUri":"59084922e4b0fc4e448ffd3e","contributors":{"authors":[{"text":"Driscoll, Jessica M. 0000-0003-3097-9603 jdriscoll@usgs.gov","orcid":"https://orcid.org/0000-0003-3097-9603","contributorId":167585,"corporation":false,"usgs":true,"family":"Driscoll","given":"Jessica","email":"jdriscoll@usgs.gov","middleInitial":"M.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":693604,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hay, Lauren E. 0000-0003-3763-4595 lhay@usgs.gov","orcid":"https://orcid.org/0000-0003-3763-4595","contributorId":1287,"corporation":false,"usgs":true,"family":"Hay","given":"Lauren","email":"lhay@usgs.gov","middleInitial":"E.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":693605,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bock, Andrew R. 0000-0001-7222-6613 abock@usgs.gov","orcid":"https://orcid.org/0000-0001-7222-6613","contributorId":4580,"corporation":false,"usgs":true,"family":"Bock","given":"Andrew","email":"abock@usgs.gov","middleInitial":"R.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":693606,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70074784,"text":"sim2932A - 2017 - Geologic map of the northeast flank of Mauna Loa volcano, Island of Hawai'i, Hawaii","interactions":[],"lastModifiedDate":"2024-05-23T22:01:59.158496","indexId":"sim2932A","displayToPublicDate":"2017-05-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2932-A","displayTitle":"Geologic Map of the Northeast Flank of Mauna Loa Volcano, Island of Hawai'i, Hawaii","title":"Geologic map of the northeast flank of Mauna Loa volcano, Island of Hawai'i, Hawaii","docAbstract":"Mauna Loa, the largest volcano on Earth, has erupted 33 times since written descriptions became available in 1832. Some eruptions were preceded by only brief seismic unrest, while others followed several months to a year of increased seismicity.
The majority of the eruptions of Mauna Loa began in the summit area (>12,000-ft elevation; Lockwood and Lipman, 1987); yet the Northeast Rift Zone (NERZ) was the source of eight flank eruptions since 1843 (table 1). This zone extends from the 13,680-ft-high summit towards Hilo (population ~60,000), the second largest city in the State of Hawaii. Although most of the source vents are farther than 30 km away, the 1880 flow from one of the vents extends into Hilo, nearly reaching Hilo Bay. The city is built entirely on flows erupted from the NERZ, most older than that erupted in 1843.
Once underway, Mauna Loa's eruptions can produce lava flows that reach the sea in less than 24 hours, severing roads and utilities in their path. For example, lava flows erupted from the Southwest Rift Zone (SWRZ) in 1950 advanced at an average rate of 9.3 km per hour, and all three lobes reached the ocean within approximately 24 hours (Finch and Macdonald, 1953). The flows near the eruptive vents must have traveled even faster.
In terms of eruption frequency, pre-eruption warning, and rapid flow emplacement, Mauna Loa poses an enormous volcanic-hazard threat to the Island of Hawai‘i. By documenting past activity and by alerting the public and local government officials of our findings, we can anticipate the volcanic hazards and substantially mitigate the risks associated with an eruption of this massive edifice.
From the geologic record, we can deduce several generalized facts about the geologic history of the NERZ. The middle to the uppermost section of the rift zone were more active in the past 4,000 years than the lower part, perhaps due to buttressing of the lower east rift zone by Mauna Kea and Kīlauea volcanoes. The historical flows that erupted on the north flank of the rift zone, which is more vulnerable to inundation, advanced toward Hilo. Lockwood (1990) noted that the vents of historical activity are migrating to the south. The volcano appears to have a self-regulating mechanism that evenly distributes long-term activity across its flanks. The geologic record also supports this notion; the time prior to the historical period (Age Group 1, orange units, pre-A.D. 1843–1,000 yr B.P.; see map sheet 2) is dominated by activity on the south side of the NERZ.
The NERZ trends N. 65° E. and is about 40 km long and 2–4 km wide, narrowing at the summit caldera. It becomes diffuse (6–7 km wide) at its down-rift terminus, at the approximately 3,400-ft elevation. Its constructional crest is marked by low spatter ramparts and by spatter cones as high as 60 m. Subparallel eruptive fissures and ground cracks cut vent deposits and flows in and near the rift crest. Lava typically flows to the north, east, or south, depending on vent location relative to the rift crest.
Encompassing 1,140 km2 of the northeast flank of Mauna Loa from the 10,880-ft elevation to sea level, the map covers the area from Hilo to Volcano on the east and includes the rift zone from Puu Ulaula quadrangle in the southwest to Hilo in the northeast. The distribution of 105 eruptive units (flows)—separated into 15 age groups ranging from more than 30,000 years B.P. to A.D. 1984—are shown, as well as the relations of volcanic and surficial sedimentary deposits. This map incorporates previously reported work published in generalized small-scale maps (Lockwood and Lipman, 1987; Buchanan-Banks, 1993; Lockwood, 1995; and Wolfe and Morris, 1996).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim2932A","usgsCitation":"Trusdell, F.A., and Lockwood, J.P., 2017, Geologic map of the northeast flank of Mauna Loa volcano, Island of Hawai'i, Hawaii: U.S. Geological Survey Scientific Investigations Map 2932–A, pamphlet 25 p., 2 sheets, scale 1:50,000, https://doi.org/10.3133/sim2932A.","productDescription":"Pamphlet: ii, 25 p.; 2 Sheets: 54.66 x 29.17 inches and 46.11 x 28.85 inches; Data Table; Metadata; Read Me; Geospatial Data","ipdsId":"IP-054350","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":429219,"rank":11,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sim2932E","text":"Scientific Investigations Map 2932-E","linkHelpText":"- Geologic Map of the Northwest Flank of Mauna Loa Volcano, Island of Hawai‘i, Hawaii"},{"id":374329,"rank":10,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sim2932C","text":"Scientific Investigations Map 2932-C","linkHelpText":"- Geologic Map of the Southern Flank of Mauna Loa Volcano, Island of Hawai‘i, Hawaii"},{"id":374328,"rank":9,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sim2932B","text":"Scientific Investigations Map 2932-B","linkHelpText":"- Geologic Map of the Central-Southeast Flank of Mauna Loa Volcano, Island of Hawai‘i, Hawaii"},{"id":340642,"rank":7,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sim/2932/a/sim2932a_geospatialdata.zip","text":"Geospatial data","size":"6.6 MB","linkFileType":{"id":6,"text":"zip"},"description":"SIM 2932-A Geospatial data"},{"id":340641,"rank":6,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sim/2932/a/sim2932a_geochemical_data_table_2017.xlsx","text":"Geochemical data table 2017","size":"40 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIM 2932-A Geochemical data table 2017"},{"id":340640,"rank":5,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sim/2932/a/sim2932a_metadata.zip","size":"217 KB","linkFileType":{"id":6,"text":"zip"},"description":"SIM 2932-A Metadata"},{"id":340638,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/2932/a/sim2932a_sheet1.pdf","text":"Sheet 1","size":"20.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 2932-A Sheet 1"},{"id":340637,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/2932/a/sim2932a_pamphlet.pdf","text":"Pamphlet","size":"2.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 2932-A Pamphlet"},{"id":340636,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/2932/a/coverthb.jpg"},{"id":340643,"rank":8,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sim/2932/a/sim2932a_readme.txt","size":"2 KB","linkFileType":{"id":2,"text":"txt"},"description":"SIM 2932-A Readme"},{"id":340639,"rank":4,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/2932/a/sim2932a_sheet2.pdf","text":"Sheet 2","size":"13.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 2932-A Sheet 2"}],"country":"United States","state":"Hawaii","otherGeospatial":"Island of Hawai'i, Mauna Loa Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.5,\n 19.5\n ],\n [\n -154.75,\n 19.5\n ],\n [\n -154.75,\n 19.75\n ],\n [\n -155.5,\n 19.75\n ],\n [\n -155.5,\n 19.5\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact HVO
Volcano Science Center, Hawaiian Volcano Observatory
U.S. Geological Survey
Digital flood-inundation maps were created for a 12.9‑mile reach of Johnson Creek by the U.S. Geological Survey (USGS). The flood-inundation maps depict estimates of water depth and areal extent of flooding from the mouth of Johnson Creek to just upstream of Southeast 174th Avenue in Portland, Oregon. Each flood-inundation map is based on a specific water level and associated streamflow at the USGS streamgage, Johnson Creek at Sycamore, Oregon (14211500), which is located near the upstream boundary of the maps. The maps produced by the USGS, and the forecasted flood hydrographs produced by National Weather Service River Forecast Center can be accessed through the USGS Flood Inundation Mapper Web site (http://wimcloud.usgs.gov/apps/FIM/FloodInundationMapper.html).
Water-surface elevations were computed for Johnson Creek using a combined one-dimensional and two‑dimensional unsteady hydraulic flow model. The model was calibrated using data collected from the flood of December 2015 (including the calculated streamflows at two USGS streamgages on Johnson Creek) and validated with data from the flood of January 2009. Results were typically within 0.6 foot (ft) of recorded or measured water-surface elevations from the December 2015 flood, and within 0.8 ft from the January 2009 flood. Output from the hydraulic model was used to create eight flood inundation maps ranging in stage from 9 to 16 ft. Boundary condition hydrographs were identical in shape to those from the December 2015 flood event, but were scaled up or down to produce the amount of streamflow corresponding to a specific water-surface elevation at the Sycamore streamgage (14211500). Sensitivity analyses using other hydrograph shapes, and a version of the model in which the peak flow is maintained for an extended period of time, showed minimal variation, except for overbank areas near the Foster Floodplain Natural Area.
Simulated water-surface profiles were combined with light detection and ranging (lidar) data collected in 2014 to delineate water-surface extents for each of the eight modeled stages. The availability of flood-inundation maps in conjunction with real-time data from the USGS streamgages along Johnson Creek and forecasted hydrographs from the National Weather Service Northwest River Forecast Center will provide residents of the watershed and emergency management personnel with valuable information that may aid in flood response, including potential evacuations, road closures, and mitigation efforts. In addition, these maps may be used for post-flood recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175024","collaboration":"Prepared in cooperation with the City of Portland Bureau of Environmental Services","usgsCitation":"Stonewall, A.J., and Beal, B.A., 2017, Developing flood-Inundation maps for Johnson Creek, Portland, Oregon: U.S. Geological Survey Scientific Investigations Report 2017–5024, 26 p., https://doi.org/10.3133/sir20175024.","productDescription":"v, 26 p.","onlineOnly":"Y","ipdsId":"IP-080503","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":339976,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F75X273G","text":"USGS data release","description":"USGS data release","linkHelpText":"Flood inundation mapping data for Johnson Creek near Sycamore, Oregon"},{"id":339738,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5024/coverthb.jpg"},{"id":339739,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5024/sir20175024.pdf","text":"Report","size":"9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5024"}],"country":"United States","state":"Oregon","city":"Portland","otherGeospatial":"Johnson Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.655556,\n 45.506944\n ],\n [\n -122.472222,\n 45.506944\n ],\n [\n -122.472222,\n 45.408333\n ],\n [\n -122.655556,\n 45.408333\n ],\n [\n -122.655556,\n 45.506944\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201
http://or.water.usgs.gov
Long-term decadal-scale shoreline change is an important parameter for quantifying the stability of coastal systems. The decadal-scale coastal change is controlled by processes that occur on short time scales (such as storms) and long-term processes (such as prevailing waves). The ability to predict decadal-scale shoreline change is not well established and the fundamental physical processes controlling this change are not well understood. Here we investigate the processes that create large-scale long-term shoreline change along the Outer Banks of North Carolina, an uninterrupted 60 km stretch of coastline, using both observations and a numerical modeling approach. Shoreline positions for a 24-yr period were derived from aerial photographs of the Outer Banks. Analysis of the shoreline position data showed that, although variable, the shoreline eroded an average of 1.5 m/yr throughout this period. The modeling approach uses a three-dimensional hydrodynamics-based numerical model coupled to a spectral wave model and simulates the full 24-yr time period on a spatial grid running on a short (second scale) time-step to compute the sediment transport patterns. The observations and the model results show similar magnitudes (O(105 m3/yr)) and patterns of alongshore sediment fluxes. Both the observed and the modeled alongshore sediment transport rates have more rapid changes at the north of our section due to continuously curving coastline, and possible effects of alongshore variations in shelf bathymetry. The southern section with a relatively uniform orientation, on the other hand, has less rapid transport rate changes. Alongshore gradients of the modeled sediment fluxes are translated into shoreline change rates that have agreement in some locations but vary in others. Differences between observations and model results are potentially influenced by geologic framework processes not included in the model. Both the observations and the model results show higher rates of erosion (∼−1 m/yr) averaged over the northern half of the section as compared to the southern half where the observed and modeled averaged net shoreline changes are smaller (<0.1 m/yr). The model indicates accretion in some shallow embayments, whereas observations indicate erosion in these locations. Further analysis identifies that the magnitude of net alongshore sediment transport is strongly dominated by events associated with high wave energy. However, both big- and small- wave events cause shoreline change of the same order of magnitude because it is the gradients in transport, not the magnitude, that are controlling shoreline change. Results also indicate that alongshore momentum is not a simple balance between wave breaking and bottom stress, but also includes processes of horizontal vortex force, horizontal advection and pressure gradient that contribute to long-term alongshore sediment transport. As a comparison to a more simple approach, an empirical formulation for alongshore sediment transport is used. The empirical estimates capture the effect of the breaking term in the hydrodynamics-based model, however, other processes that are accounted for in the hydrodynamics-based model improve the agreement with the observed alongshore sediment transport.
","language":"English","publisher":"Elsevier","publisherLocation":"New York, NY","doi":"10.1016/j.coastaleng.2016.11.014","usgsCitation":"Safak, I., List, J.H., Warner, J., and Kumar, N., 2017, Observations and 3D hydrodynamics-based modeling of decadal-scale shoreline change along the Outer Banks, North Carolina: Coastal Engineering, v. 120, p. 78-92, https://doi.org/10.1016/j.coastaleng.2016.11.014.","productDescription":"15 p.","startPage":"78","endPage":"92","ipdsId":"IP-071238","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":469939,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hdl.handle.net/1912/8747","text":"External Repository"},{"id":339382,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina","otherGeospatial":"Outer Banks","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.3,\n 35.13\n ],\n [\n -75.07,\n 35.13\n ],\n [\n -75.07,\n 36.45\n ],\n [\n -76.3,\n 36.45\n ],\n [\n -76.3,\n 35.13\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"120","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58e8a540e4b09da6799d639d","contributors":{"authors":[{"text":"Safak, Ilgar 0000-0001-7675-0770 isafak@usgs.gov","orcid":"https://orcid.org/0000-0001-7675-0770","contributorId":5522,"corporation":false,"usgs":true,"family":"Safak","given":"Ilgar","email":"isafak@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":690245,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"List, Jeffrey H. 0000-0001-8594-2491 jlist@usgs.gov","orcid":"https://orcid.org/0000-0001-8594-2491","contributorId":174581,"corporation":false,"usgs":true,"family":"List","given":"Jeffrey","email":"jlist@usgs.gov","middleInitial":"H.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":690247,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Warner, John C. 0000-0002-3734-8903 jcwarner@usgs.gov","orcid":"https://orcid.org/0000-0002-3734-8903","contributorId":2681,"corporation":false,"usgs":true,"family":"Warner","given":"John C.","email":"jcwarner@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":690246,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kumar, Nirnimesh","contributorId":190663,"corporation":false,"usgs":false,"family":"Kumar","given":"Nirnimesh","email":"","affiliations":[],"preferred":false,"id":690248,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70194528,"text":"70194528 - 2017 - Petrology and geochronology of Mesoproterozoic basement of the Mount Rogers area of southwestern Virginia and northwestern North Carolina: Implications for the Precambrian tectonic evolution of the southern Blue Ridge province","interactions":[],"lastModifiedDate":"2017-12-04T11:12:54","indexId":"70194528","displayToPublicDate":"2017-03-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":732,"text":"American Journal of Science","active":true,"publicationSubtype":{"id":10}},"title":"Petrology and geochronology of Mesoproterozoic basement of the Mount Rogers area of southwestern Virginia and northwestern North Carolina: Implications for the Precambrian tectonic evolution of the southern Blue Ridge province","docAbstract":"Results from new geologic mapping, SHRIMP U-Pb geochronology, and petrologic studies indicate that Mesoproterozoic basement in the northern French Broad massif near Mount Rogers consists of multiple, mostly granitic plutons, map- and outcrop-scale xenoliths of pre-existing crustal rocks, and remnants of formerly overlying meta-sedimentary lithologies. Zircon and titanite ages demonstrate that these rocks collectively record nearly 350 m.y. of tectonic evolution including periods of igneous intrusion at ca. 1190 to 1130 Ma (Early Magmatic Suite) and ca. 1075 to 1030 Ma (Late Magmatic Suite) and three episodes of regional metamorphism at ca. 1170 to 1140, 1070 to 1020, and 1000 to 970 Ma. The existence of ca. 1.3 Ga age crust is indicated by (1) orthogranofels of ca. 1.32 Ga age in a map-scale xenolith, (2) inherited zircons of ca. 1.33 to 1.29 Ga age in Early Magmatic Suite plutons, and (3) ca. 1.36 to 1.30 Ga age detrital zircons in meta-sedimentary lithologies. Mineral assemblages developed in amphibolites and granofelses indicate that metamorphism during both Mesoproterozoic episodes occurred at upper amphibolite- to lower granulite-facies conditions. Syn-orogenic Early Magmatic Suite plutons emplaced at ca. 1190 to 1145 Ma are characterized by high-K, variably magnesian, dominantly calc-alkalic compositions, and have trace-element characteristics indicative of continental-arc magmatic origin involving melting of thick continental crust. In contrast, ca. 1140 Ma age quartz syenite displays A-type features indicating derivation from depleted crustal sources with increased mantle input during waning stages of regional contraction. Plutons of the compositionally bimodal Late Magmatic Suite include (1) ca. 1060 Ma meta-granite with geochemical characteristics transitional between silicic rocks of arc systems and post-collisional granites of A-type lineage, and (2) ca. 1055 Ma monzodioritic rocks with A-type compositional characteristics that likely reflect derivation from fertile, mafic sources in the lower crust. Collectively, these data suggest that Mesoproterozoic rocks of the study area preserve evidence of multiple orogenic episodes that likely involved continental-arc development and deformation at ca. 1150 Ma followed by crustal thickening at ca. 1060 Ma. Field relations and geochronologic data indicate that regional uplift and sedimentation occurred at ca. 1100 Ma between the two episodes of overlapping magmatism and orogenesis. The nature and timing of Mesoproterozoic events recorded in basement rocks of the study area illustrate significant differences in the lithologic assemblages and geologic history preserved by Mesoproterozoic basement of the adjacent Shenandoah and French Broad massifs, suggesting that the Blue Ridge massifs occupied different locations within the regional Grenville-age orogen until about 1070 Ma when the effects of Ottawan-age tectonics began to affect both areas. The near ubiquity of Ottawan-age orogenic activity recorded in Mesoproterozoic rocks of the Blue Ridge, other Appalachian inliers such as the New Jersey Highlands, and the Grenville province of Canada, including the Adirondacks, suggests that these formerly disparate terranes were amalgamated to form a common, regional orogen by this time.
","language":"English","publisher":"American Journal of Science","doi":"10.2475/03.2017.01","usgsCitation":"Tollo, R.P., Aleinikoff, J.N., Dickin, A.P., Radwany, M.S., Southworth, C.S., and Fanning, C.M., 2017, Petrology and geochronology of Mesoproterozoic basement of the Mount Rogers area of southwestern Virginia and northwestern North Carolina: Implications for the Precambrian tectonic evolution of the southern Blue Ridge province: American Journal of Science, v. 317, no. 3, p. 251-337, https://doi.org/10.2475/03.2017.01.","productDescription":"87 p.","startPage":"251","endPage":"337","ipdsId":"IP-080746","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":349652,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina, Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.625,\n 36.5\n ],\n [\n -81.25,\n 36.5\n ],\n [\n -81.25,\n 36.75\n ],\n [\n -81.625,\n 36.75\n ],\n [\n -81.625,\n 36.5\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"317","issue":"3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-04-11","publicationStatus":"PW","scienceBaseUri":"5a60fc05e4b06e28e9c238b8","contributors":{"authors":[{"text":"Tollo, Richard P.","contributorId":196682,"corporation":false,"usgs":false,"family":"Tollo","given":"Richard","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":724318,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aleinikoff, John N. 0000-0003-3494-6841 jaleinikoff@usgs.gov","orcid":"https://orcid.org/0000-0003-3494-6841","contributorId":1478,"corporation":false,"usgs":true,"family":"Aleinikoff","given":"John","email":"jaleinikoff@usgs.gov","middleInitial":"N.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":724317,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dickin, Alan P.","contributorId":201096,"corporation":false,"usgs":false,"family":"Dickin","given":"Alan","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":724319,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Radwany, Molly S.","contributorId":201104,"corporation":false,"usgs":false,"family":"Radwany","given":"Molly","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":724320,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Southworth, C. Scott 0000-0002-7976-7807 ssouthwo@usgs.gov","orcid":"https://orcid.org/0000-0002-7976-7807","contributorId":1608,"corporation":false,"usgs":true,"family":"Southworth","given":"C.","email":"ssouthwo@usgs.gov","middleInitial":"Scott","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":724322,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fanning, C. Mark","contributorId":193428,"corporation":false,"usgs":false,"family":"Fanning","given":"C.","email":"","middleInitial":"Mark","affiliations":[],"preferred":false,"id":724321,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ]}