{"pageNumber":"561","pageRowStart":"14000","pageSize":"25","recordCount":46856,"records":[{"id":70056139,"text":"sir20125208 - 2013 - Evaluation of intake efficiencies and associated sediment-concentration errors in US D-77 bag-type and US D-96-type depth-integrating suspended-sediment samplers","interactions":[],"lastModifiedDate":"2018-03-21T15:48:11","indexId":"sir20125208","displayToPublicDate":"2013-11-21T09:29:00","publicationYear":"2013","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":"2012-5208","title":"Evaluation of intake efficiencies and associated sediment-concentration errors in US D-77 bag-type and US D-96-type depth-integrating suspended-sediment samplers","docAbstract":"Accurate measurements of suspended-sediment concentration require suspended-sediment samplers to operate isokinetically, within an intake-efficiency range of 1.0 ± 0.10, where intake efficiency is defined as the ratio of the velocity of the water through the sampler intake to the local ambient stream velocity. Local ambient stream velocity is defined as the velocity of the water in the river at the location of the nozzle, unaffected by the presence of the sampler. Results from Federal Interagency Sedimentation Project (FISP) laboratory experiments published in the early 1940s show that when the intake efficiency is less than 1.0, suspended-sediment samplers tend to oversample sediment relative to water, leading to potentially large positive biases in suspended-sediment concentration that are positively correlated with grain size. Conversely, these experiments show that, when the intake efficiency is greater than 1.0, suspended‑sediment samplers tend to undersample sediment relative to water, leading to smaller negative biases in suspended-sediment concentration that become slightly more negative as grain size increases.\n\nThe majority of FISP sampler development and testing since the early 1990s has been conducted under highly uniform flow conditions via flume and slack-water tow tests, with relatively little work conducted under the greater levels of turbulence that exist in actual rivers. Additionally, all of this recent work has been focused on the hydraulic characteristics and intake efficiencies of these samplers, with no field investigations conducted on the accuracy of the suspended-sediment data collected with these samplers. When depth-integrating suspended-sediment samplers are deployed under the more nonuniform and turbulent conditions that exist in rivers, multiple factors may contribute to departures from isokinetic sampling, thus introducing errors into the suspended-sediment data collected by these samplers that may not be predictable on the basis of flume and tow tests alone.\n\nThis study has three interrelated goals. First, the intake efficiencies of the older US D-77 bag-type and newer, FISP-approved US D-96-type1 depth-integrating suspended‑sediment samplers are evaluated at multiple cross‑sections under a range of actual-river conditions. The intake efficiencies measured in these actual-river tests are then compared to those previously measured in flume and tow tests. Second, other physical effects, mainly water temperature and the duration of sampling at a vertical, are examined to determine whether these effects can help explain observed differences in intake efficiency both between the two types of samplers and between the laboratory and field tests. Third, the signs and magnitudes of the likely errors in suspendedsand concentration in measurements made with both types of samplers are predicted based the intake efficiencies of these two types of depth-integrating samplers. Using the relative difference in isokinetic sampling observed between the US D-77 bag-type and D-96-type samplers during river tests, measured differences in suspended-sediment concentration in a variety of size classes were evaluated between paired equal-discharge-increment (EDI) and equal-width-increment (EWI) measurements made with these two types of samplers to determine whether these differences in concentration are consistent with the differences in concentrations expected on the basis of the 1940s FISP laboratory experiments. In addition, sequential single-vertical depth-integrated samples were collected (concurrent with velocity measurements) with the US D-96-type bag sampler and two different rigidcontainer samplers to evaluate whether the predicted errors in suspended-sand concentrations measured with the US D-96- type sampler are consistent with those expected on the basis of the 1940s FISP laboratory experiments.\n\nResults from our study indicate that the intake efficiency of the US D-96-type sampler is superior to that of the US D-77 bag-type sampler under actual-river conditions, with overall performance of the US D-96-type sampler being closer to, yet still typically below, the FISP-acceptable range of isokinetic operation. These results are in contrast to the results from FISP-conducted flume tests that showed that both the US D-77 bag-type and US D-96-type samplers sampled isokinetically in the laboratory. Results from our study indicate that the single largest problem with the behavior of both the US D-77 bag-type and the US D-96-type samplers under actual‑river conditions is that both samplers are prone to large time‑dependent decreases in intake efficiency as sampling duration increases. In the case of the US D-96-type sampler, this problem may be at least partially overcome by shortening the duration of sampling (or, instead, perhaps by a simple design improvement); in the case of the US D-77 bag-type sampler, although shortening the sampling duration improves the intake efficiency, it does not bring it into agreement with the FISP‑accepted range of isokinetic operation.\n\nThe predicted errors in suspended-sand concentration in EDI or EWI measurements made with the US-96-type sampler are much smaller than those associated with EDI or EWI measurements made with the US D-77 bag-type sampler, especially when the results are corrected for the effects of water temperature and sampling duration. The bias in the concentration in each size class measured using the US D-77 bag-type relative to the concentration measured using the US D-96-type sampler behaves in a manner consistent with that expected on the basis of the observed differences in intake efficiency between the two samplers in conjunction with the results from the 1940s FISP laboratory experiments. In addition, the bias in the concentration in each size class measured using the US D-96‑type sampler relative to the concentration measured using the truly isokinetic rigid-container samplers is in excellent agreement with that predicted on the basis of the 1940s FISP laboratory experiments. Because suspended-sediment samplers can respond differently between laboratory and field conditions, actual-river tests such as those in this study should be conducted when models of suspended-sediment samplers are changed from one type to another during the course of long-term monitoring programs. Otherwise, potential large differences in the suspended-sediment data collected by different types of samplers would lead to large step changes in sediment loads that may be misinterpreted as real, when, in fact, they are associated with the change in suspended‑sediment sampling equipment.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125208","issn":"2328-0328","usgsCitation":"Sabol, T., and Topping, D.J., 2013, Evaluation of intake efficiencies and associated sediment-concentration errors in US D-77 bag-type and US D-96-type depth-integrating suspended-sediment samplers: U.S. Geological Survey Scientific Investigations Report 2012-5208, viii, 88 p., https://doi.org/10.3133/sir20125208.","productDescription":"viii, 88 p.","numberOfPages":"100","ipdsId":"IP-027819","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":279306,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20125208.jpg"},{"id":279305,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5208/pdf/sir2012-5208.pdf"},{"id":279302,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5208/"}],"projection":"North America Albers Equal Area","datum":"North American Datum of 1983","country":"United States","state":"Arizona;Nevada;Utah","otherGeospatial":"Grand Canyon;Marble Canyon","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -114.5,35.5 ], [ -114.5,37.5 ], [ -111.0,37.5 ], [ -111.0,35.5 ], [ -114.5,35.5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"528f53c9e4b0660d392bed6c","contributors":{"authors":[{"text":"Sabol, Thomas A.","contributorId":67186,"corporation":false,"usgs":true,"family":"Sabol","given":"Thomas A.","affiliations":[],"preferred":false,"id":486324,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Topping, David J. 0000-0002-2104-4577 dtopping@usgs.gov","orcid":"https://orcid.org/0000-0002-2104-4577","contributorId":715,"corporation":false,"usgs":true,"family":"Topping","given":"David","email":"dtopping@usgs.gov","middleInitial":"J.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":false,"id":486323,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70048894,"text":"ofr20131261 - 2013 - Landscape consequences of natural gas extraction in Sullivan and Wyoming Counties, Pennsylvania, 2004–2010","interactions":[],"lastModifiedDate":"2016-08-19T18:07:33","indexId":"ofr20131261","displayToPublicDate":"2013-11-21T08:30:00","publicationYear":"2013","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":"2013-1261","title":"Landscape consequences of natural gas extraction in Sullivan and Wyoming Counties, Pennsylvania, 2004–2010","docAbstract":"<p>Increased demands for cleaner burning energy, coupled with the relatively recent technological advances in accessing unconventional hydrocarbon-rich geologic formations, have led to an intense effort to find and extract natural gas from various underground sources around the country. One of these sources, the Marcellus Shale, located in the Allegheny Plateau, is currently undergoing extensive drilling and production. The technology used to extract gas in the Marcellus Shale is known as hydraulic fracturing and has garnered much attention because of its use of large amounts of fresh water, its use of proprietary fluids for the hydraulic-fracturing process, its potential to release contaminants into the environment, and its potential effect on water resources. Nonetheless, development of natural gas extraction wells in the Marcellus Shale is only part of the overall natural gas story in this area of Pennsylvania. Conventional natural gas wells, which sometimes use the same technique, are commonly located in the same general area as the Marcellus Shale and are frequently developed in clusters across the landscape. The combined effects of these two natural gas extraction methods create potentially serious patterns of disturbance on the landscape. This document quantifies the landscape changes and consequences of natural gas extraction for Sullivan County and Wyoming County in Pennsylvania between 2004 and 2010. Patterns of landscape disturbance related to natural gas extraction activities were collected and digitized using National Agriculture Imagery Program (NAIP) imagery for 2004, 2005/2006, 2008, and 2010. The disturbance patterns were then used to measure changes in land cover and land use using the National Land Cover Database (NLCD) of 2001. A series of landscape metrics is also used to quantify these changes and is included in this publication.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131261","usgsCitation":"Slonecker, T.E., Milheim, L., Roig-Silva, C.M., and Malizia, A.R., 2013, Landscape consequences of natural gas extraction in Sullivan and Wyoming Counties, Pennsylvania, 2004–2010: U.S. Geological Survey Open-File Report 2013-1261, v, 34 p., https://doi.org/10.3133/ofr20131261.","productDescription":"v, 34 p.","numberOfPages":"39","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-042856","costCenters":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"links":[{"id":279303,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131261.jpg"},{"id":279298,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1261/pdf/of2013-1261.pdf","text":"Report","size":"4.65 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,{"id":70049027,"text":"ofr20131263 - 2013 - Landscape consequences of natural gas extraction in Armstrong and Indiana Counties, Pennsylvania, 2004–2010","interactions":[],"lastModifiedDate":"2016-08-19T18:05:36","indexId":"ofr20131263","displayToPublicDate":"2013-11-21T08:29:00","publicationYear":"2013","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":"2013-1263","title":"Landscape consequences of natural gas extraction in Armstrong and Indiana Counties, Pennsylvania, 2004–2010","docAbstract":"<p>Increased demands for cleaner burning energy, coupled with the relatively recent technological advances in accessing unconventional hydrocarbon-rich geologic formations, have led to an intense effort to find and extract natural gas from various underground sources around the country. One of these sources, the Marcellus Shale, located in the Allegheny Plateau, is currently undergoing extensive drilling and production. The technology used to extract gas in the Marcellus Shale is known as hydraulic fracturing and has garnered much attention because of its use of large amounts of fresh water, its use of proprietary fluids for the hydraulic-fracturing process, its potential to release contaminants into the environment, and its potential effect on water resources. Nonetheless, development of natural gas extraction wells in the Marcellus Shale is only part of the overall natural gas story in this area of Pennsylvania. Conventional natural gas wells are commonly located in the same general area as the Marcellus Shale and are frequently developed in clusters across the landscape. The combined effects of these two natural gas extraction methods create potentially serious patterns of disturbance on the landscape. This document quantifies the landscape changes and consequences of natural gas extraction for Armstrong County and Indiana County in Pennsylvania between 2004 and 2010. Patterns of landscape disturbance related to natural gas extraction activities were collected and digitized using National Agriculture Imagery Program (NAIP) imagery for 2004, 2005/2006, 2008, and 2010. The disturbance patterns were then used to measure changes in land cover and land use using the National Land Cover Database (NLCD) of 2001. A series of landscape metrics is also used to quantify these changes and is included in this publication.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131263","usgsCitation":"Slonecker, T.E., Milheim, L., Roig-Silva, C.M., and Malizia, A.R., 2013, Landscape consequences of natural gas extraction in Armstrong and Indiana Counties, Pennsylvania, 2004–2010: U.S. Geological Survey Open-File Report 2013-1263, v, 35 p., https://doi.org/10.3133/ofr20131263.","productDescription":"v, 35 p.","numberOfPages":"40","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-049110","costCenters":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"links":[{"id":279304,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131263.jpg"},{"id":279299,"type":{"id":15,"text":"Index 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croig@usgs.gov","contributorId":4213,"corporation":false,"usgs":true,"family":"Roig-Silva","given":"Coral","email":"croig@usgs.gov","middleInitial":"M.","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":false,"id":486045,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Malizia, Alexander R.","contributorId":83018,"corporation":false,"usgs":true,"family":"Malizia","given":"Alexander","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":486046,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70057382,"text":"70057382 - 2013 - Location-only and use-availability data: analysis methods converge","interactions":[],"lastModifiedDate":"2013-11-22T13:40:17","indexId":"70057382","displayToPublicDate":"2013-11-20T13:34:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2158,"text":"Journal of Animal Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Location-only and use-availability data: analysis methods converge","docAbstract":"This Special Feature arose from a session on a topic of the same name that took place during The Wildlife Society meeting in Kona, Hawaii, from 5 to 10 November, 2011. The purpose of that session and this Special Feature is to compare methods for predictive modelling of species geographical distributions and the modelling of habitat (resource) selection by animals. The predictive modelling of species geographical distributions and the modelling of habitat selection based on the environmental conditions at sites where animals are known to occur are essentially the same problem. Presence-only and used-available data\nboth consist of a sample of locations with known presence of a species or an individual. A separate sample of locations from a study area, with unknown presence (pseudo-absence), is also assumed to exist. The probability or relative probability of presence of a species or individual is modelled and estimated across a certain time implicitly defined by the sampling mechanism, for example, by the time period during which museum specimens or radiotelemetry data were collected. A number of modelling methods have appeared in the literature over the last couple of decades. Many of these methods were made feasible\nby the availability of geographical information systems (GIS), global positioning system (GPS) radiotelemetry and public online data access initiatives (e.g. global biodiversity information facility). The papers in this Special Feature are intended to present the state of the methodological art in their subject area, with particular attention paid to contrasting the advantages and disadvantages of alternative methods of analysis for data.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Animal Ecology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"British Ecologyical Society","doi":"10.1111/1365-2656.12145","usgsCitation":"McDonald, L., Manly, B., Huettmann, F., and Thogmartin, W., 2013, Location-only and use-availability data: analysis methods converge: Journal of Animal Ecology, v. 82, no. 6, p. 1120-1124, https://doi.org/10.1111/1365-2656.12145.","productDescription":"5 p.","startPage":"1120","endPage":"1124","ipdsId":"IP-051603","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":473439,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2656.12145","text":"Publisher Index Page"},{"id":279605,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":279604,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/1365-2656.12145"},{"id":279584,"type":{"id":15,"text":"Index Page"},"url":"https://onlinelibrary.wiley.com/doi/10.1111/1365-2656.12145/abstract"}],"volume":"82","issue":"6","noUsgsAuthors":false,"publicationDate":"2013-10-24","publicationStatus":"PW","scienceBaseUri":"52908b09e4b0bbdcf23f092c","contributors":{"authors":[{"text":"McDonald, Lyman","contributorId":23588,"corporation":false,"usgs":true,"family":"McDonald","given":"Lyman","affiliations":[],"preferred":false,"id":486665,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Manly, Bryan","contributorId":64292,"corporation":false,"usgs":true,"family":"Manly","given":"Bryan","affiliations":[],"preferred":false,"id":486667,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Huettmann, Falk","contributorId":15663,"corporation":false,"usgs":false,"family":"Huettmann","given":"Falk","email":"","affiliations":[],"preferred":false,"id":486664,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thogmartin, Wayne","contributorId":36974,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","affiliations":[],"preferred":false,"id":486666,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70055549,"text":"fs20133075 - 2013 - Water resources of Lafourche Parish, Louisiana","interactions":[],"lastModifiedDate":"2026-06-11T20:23:44.669825","indexId":"fs20133075","displayToPublicDate":"2013-11-20T12:47:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-3075","title":"Water resources of Lafourche Parish, Louisiana","docAbstract":"This fact sheet presents a brief overview of groundwater and surface-water resources in Lafourche Parish, Louisiana. Information on the availability, past and current use trends, and water quality from groundwater and surface-water sources in the parish is discussed. Previously published reports and data stored in the U.S. Geological Survey’s National Water Information System (http://waterdata.usgs.gov/nwis) are the primary sources of the information presented here.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20133075","collaboration":"Prepared in cooperation with the Louisiana Department of Transportation and Development","usgsCitation":"Prakken, L., and Lovelace, J.K., 2013, Water resources of Lafourche Parish, Louisiana: U.S. Geological Survey Fact Sheet 2013-3075, 4 p., https://doi.org/10.3133/fs20133075.","productDescription":"4 p.","numberOfPages":"4","ipdsId":"IP-050772","costCenters":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"links":[{"id":505502,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_99328.htm","linkFileType":{"id":5,"text":"html"}},{"id":279253,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2013/3075/"},{"id":279252,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2013/3075/pdf/fs2013-3075.pdf"},{"id":279254,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20133075.jpg"}],"country":"United States","state":"Louisiana","county":"Lafourche Parish","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -91.0365,28.942 ], [ -91.0365,30.222 ], [ -89.7565,30.222 ], [ -89.7565,28.942 ], [ -91.0365,28.942 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52a64090e4b0a6d6958827b7","contributors":{"authors":[{"text":"Prakken, Lawrence B.","contributorId":73978,"corporation":false,"usgs":true,"family":"Prakken","given":"Lawrence B.","affiliations":[],"preferred":false,"id":486141,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lovelace, John K. 0000-0002-8532-2599 jlovelac@usgs.gov","orcid":"https://orcid.org/0000-0002-8532-2599","contributorId":999,"corporation":false,"usgs":true,"family":"Lovelace","given":"John","email":"jlovelac@usgs.gov","middleInitial":"K.","affiliations":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":486140,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70057791,"text":"70057791 - 2013 - Performance of quantitative vegetation sampling methods across gradients of cover in Great Basin plant communities","interactions":[],"lastModifiedDate":"2013-11-27T12:03:15","indexId":"70057791","displayToPublicDate":"2013-11-20T11:56:26","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3228,"text":"Rangeland Ecology and Management","onlineIssn":"1551-5028","printIssn":"1550-7424","active":true,"publicationSubtype":{"id":10}},"title":"Performance of quantitative vegetation sampling methods across gradients of cover in Great Basin plant communities","docAbstract":"Resource managers and scientists need efficient, reliable methods for quantifying vegetation to conduct basic research, evaluate land management actions, and monitor trends in habitat conditions. We examined three methods for quantifying vegetation in 1-ha plots among different plant communities in the northern Great Basin: photography-based grid-point intercept (GPI), line-point intercept (LPI), and point-quarter (PQ). We also evaluated each method for within-plot subsampling adequacy and effort requirements relative to information gain. We found that, for most functional groups, percent cover measurements collected with the use of LPI, GPI, and PQ methods were strongly correlated. These correlations were even stronger when we used data from the upper canopy only (i.e., top “hit” of pin flags) in LPI to estimate cover. PQ was best at quantifying cover of sparse plants such as shrubs in early successional habitats. As cover of a given functional group decreased within plots, the variance of the cover estimate increased substantially, which required more subsamples per plot (i.e., transect lines, quadrats) to achieve reliable precision. For GPI, we found that that six–nine quadrats per hectare were sufficient to characterize the vegetation in most of the plant communities sampled. All three methods reasonably characterized the vegetation in our plots, and each has advantages depending on characteristics of the vegetation, such as cover or heterogeneity, study goals, precision of measurements required, and efficiency needed.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Rangeland Ecology and Management","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"The Society for Range Management","doi":"10.2111/REM-D-13-00063.1","usgsCitation":"Pilliod, D., and Arkle, R., 2013, Performance of quantitative vegetation sampling methods across gradients of cover in Great Basin plant communities: Rangeland Ecology and Management, v. 66, no. 6, p. 634-647, https://doi.org/10.2111/REM-D-13-00063.1.","productDescription":"14 p.","startPage":"634","endPage":"647","ipdsId":"IP-045275","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":473440,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/10150/642750","text":"External Repository"},{"id":279868,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":279866,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.2111/REM-D-13-00063.1"},{"id":279867,"type":{"id":15,"text":"Index Page"},"url":"https://www.bioone.org/doi/full/10.2111/REM-D-13-00063.1"}],"country":"United States","state":"Idaho;Oregon","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.61,41.99 ], [ -124.61,49.0 ], [ -111.04,49.0 ], [ -111.04,41.99 ], [ -124.61,41.99 ] ] ] } } ] }","volume":"66","issue":"6","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52972290e4b08e44bf670c47","contributors":{"authors":[{"text":"Pilliod, David S.","contributorId":101760,"corporation":false,"usgs":true,"family":"Pilliod","given":"David S.","affiliations":[],"preferred":false,"id":486875,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Arkle, Robert S.","contributorId":55679,"corporation":false,"usgs":true,"family":"Arkle","given":"Robert S.","affiliations":[],"preferred":false,"id":486874,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70055658,"text":"ofr20131172 - 2013 - Borehole-explosion and air-gun data acquired in the 2011 Salton Seismic Imaging Project (SSIP), southern California: description of the survey","interactions":[],"lastModifiedDate":"2013-11-20T11:16:29","indexId":"ofr20131172","displayToPublicDate":"2013-11-20T10:53:00","publicationYear":"2013","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":"2013-1172","title":"Borehole-explosion and air-gun data acquired in the 2011 Salton Seismic Imaging Project (SSIP), southern California: description of the survey","docAbstract":"<p>The Imperial and Coachella Valleys are being formed by active plate-tectonic processes. From the Imperial Valley southward into the Gulf of California, plate motions are rifting the continent apart. In the Coachella Valley, the plates are sliding past one another along the San Andreas and related faults (fig. 1). These processes build the stunning landscapes of the region, but also produce damaging earthquakes.</p>\n<br/>\n<p>Rupture of the southern section of the San Andreas Fault (SAF), from the Coachella Valley to the Mojave Desert, is believed to be the greatest natural hazard that California will face in the near future. With an estimated magnitude between 7.2 and 8.1, such an event would result in violent shaking, loss of life, and disruption of infrastructure (freeways, aqueducts, power, petroleum, and communication lines) that might bring much of southern California to a standstill. As part of the nation’s efforts to avert a catastrophe of this magnitude, a number of projects have been undertaken to more fully understand and mitigate the effects of such an event. The Salton Seismic Imaging Project (SSIP), funded jointly by the National Science Foundation (NSF) and the U.S. Geological Survey (USGS), seeks to understand, through seismic imaging, the structure of the Earth surrounding the SAF, including the sedimentary basins on which cities are built.</p>\n<br/>\n<p>The principal investigators (PIs) of this collaborative project represent the USGS, Virginia Polytechnic Institute and State University (Virginia Tech), California Institute of Technology (Caltech), Scripps Institution of Oceanography (Scripps), University of Nevada, Reno (UNR), and Stanford University.</p>\n<br/>\n<p>SSIP will create images of underground structure and sediments in the Imperial and Coachella Valleys and adjacent mountain ranges to investigate the earthquake hazards posed to cities in this area. Importantly, the images will help determine the underground geometry of the SAF, how deep the sediments are, and how fast earthquake energy can travel through the sediments. All of these factors determine how hard the earth will shake during a major earthquake. If we can improve on our understanding of how and where earthquakes will occur, and how strong their resultant shaking will be, then buildings can be designed or retrofitted accordingly in order to resist damage and collapse, and emergency plans can be adequately prepared. In addition, SSIP will investigate the processes of rifting and magmatism in the Salton Trough in order to better understand this important plate-boundary region. The Salton Trough is a unique rift in that subsidence is accompanied by huge influxes of infilling sediment from the Colorado River. Volcanism that accompanies the subsidence here is muted by these influxes of sediment. The Salton Trough, in the central part of the Imperial Valley, is apparently made up of entirely new crust: young sediment in the upper crust and basaltic intrusive rocks in the mid-to-lower crust (Fuis and others, 1984).</p>\n<br/>\n<p>Similar to the ultrasound and computed tomography (CT) scans performed by the medical industry, seismic imaging is a collection of techniques that enable scientists to obtain a picture of what is underground. The petroleum industry routinely uses these techniques to search for oil and gas at relatively shallow depths; however, the scope of this project demanded that we image as much as 30 km into the Earth’s crust. This project generated and recorded seismic waves, similar to sound waves, which move downward into the Earth and are bent (refracted) or echoed (reflected) back to the surface.</p>\n<br/>\n<p>SSIP acquired data in a series of intersecting lines that cover key areas of the Salton Trough. The sources of sound waves were detonations (shots) in deep boreholes, designed to create energy equivalent to magnitude 1–2 earthquakes. The study region routinely experiences earthquakes of these magnitudes, but earthquakes are not located in such a way as to permit us to create the detailed images we need for earthquake hazard assessment. Air gun bursts, generated in the Salton Sea along extensions of our onshore seismic lines, also were utilized as sound-wave sources. Temporary deployments of portable land seismometers, as well as ocean-bottom seismometers (OBSs) on the floor of the Salton Sea, recorded the energy from the land shots and air gun bursts.</p>\n<br/>\n<p>SSIP is similar to the Los Angeles Regional Seismic Experiments of 1994 and 1999 (LARSE I and II, respectively; Murphy and others, 1996; Fuis and others, 2001). The LARSE surveys demonstrated that the USGS and collaborators can safely and effectively conduct seismic imaging surveys in urban and nonurban areas, on lands owned and/or managed by many different types of agencies and entities. Information was produced that could not have been obtained any other way, and this information was key to changing the leading ideas about earthquake hazards at that time in the Los Angeles region. These surveys produced no significant environmental impact or damage to structures, and they did not trigger earthquakes.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131172","usgsCitation":"Rose, E.J., Fuis, G.S., Stock, J.M., Hole, J.A., Kell, A.M., Kent, G., Driscoll, N.W., Goldman, M., Reusch, A.M., Han, L., Sickler, R.R., Catchings, R.D., Rymer, M.J., Criley, C.J., Scheirer, D., Skinner, S.M., Slayday-Criley, C.J., Murphy, J.M., Jensen, E.G., McClearn, R., Ferguson, A.J., Butcher, L.A., Gardner, M.A., Emmons, I., Loughran, C.L., Svitek, J.R., Bastien, P., Cotton, J.A., Croker, D.S., Harding, A.J., Babcock, J.M., Harder, S.H., and Rosa, C.M., 2013, Borehole-explosion and air-gun data acquired in the 2011 Salton Seismic Imaging Project (SSIP), southern California: description of the survey: U.S. Geological Survey Open-File Report 2013-1172, Report: vi, 84 p.; 8 Appendixes, https://doi.org/10.3133/ofr20131172.","productDescription":"Report: vi, 84 p.; 8 Appendixes","numberOfPages":"92","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-042942","costCenters":[{"id":380,"text":"Menlo ParkCalif. 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 \"}}]}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52a6407be4b0a6d6958826e8","contributors":{"authors":[{"text":"Carswell, William J. Jr. carswell@usgs.gov","contributorId":1787,"corporation":false,"usgs":true,"family":"Carswell","given":"William J.","suffix":"Jr.","email":"carswell@usgs.gov","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":false,"id":486101,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70055716,"text":"sir20135195 - 2013 - Iodine-129 in the eastern Snake River Plain aquifer at and near the Idaho National Laboratory, Idaho, 2010-12","interactions":[],"lastModifiedDate":"2013-11-18T16:26:52","indexId":"sir20135195","displayToPublicDate":"2013-11-18T16:20:00","publicationYear":"2013","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":"2013-5195","title":"Iodine-129 in the eastern Snake River Plain aquifer at and near the Idaho National Laboratory, Idaho, 2010-12","docAbstract":"From 1953 to 1988, approximately 0.941 curies of iodine-129 (<sup>129</sup>I) were contained in wastewater generated at the Idaho National Laboratory (INL) with almost all of this wastewater discharged at or near the Idaho Nuclear Technology and Engineering Center (INTEC). Most of the wastewater containing <sup>129</sup>I was discharged directly into the eastern Snake River Plain (ESRP) aquifer through a deep disposal well until 1984; lesser quantities also were discharged into unlined infiltration ponds or leaked from distribution systems below the INTEC.\n\nDuring 2010–12, the U.S. Geological Survey in cooperation with the U.S. Department of Energy collected groundwater samples for <sup>129</sup>I from 62 wells in the ESRP aquifer to track concentration trends and changes for the carcinogenic radionuclide that has a 15.7 million-year half-life. Concentrations of <sup>129</sup>I in the aquifer ranged from 0.0000013±0.0000005 to 1.02±0.04 picocuries per liter (pCi/L), and generally decreased in wells near the INTEC, relative to previous sampling events. The average concentration of <sup>129</sup>I in groundwater from 15 wells sampled during four different sample periods decreased from 1.15 pCi/L in 1990–91 to 0.173 pCi/L in 2011–12. All but two wells within a 3-mile radius of the INTEC showed decreases in concentration, and all but one sample had concentrations less than the U.S. Environmental Protection Agency maximum contaminant level of 1 pCi/L. These decreases are attributed to the discontinuation of disposal of <sup>129</sup>I in wastewater and to dilution and dispersion in the aquifer. The decreases in <sup>129</sup>I concentrations, in areas around INTEC where concentrations increased between 2003 and 2007, were attributed to less recharge near INTEC either from less flow in the Big Lost River or from less local snowmelt and anthropogenic sources.\n\nAlthough wells near INTEC sampled in 2011–12 showed decreases in <sup>129</sup>I concentrations compared with previously collected data, some wells south and east of the Central Facilities Area, near the site boundary, and south of the INL showed small increases. These slight increases are attributed to variable discharge rates of wastewater that eventually moved to these well locations as a pulse of water from a particular disposal period.\n\nWells sampled for the first time around the Naval Reactors Facility had <sup>129</sup>I concentrations slightly greater than background concentrations in the ESRP aquifer. These concentrations are attributed to possible leakage from landfills at the Naval Reactors Facility or seepage from air emission deposits from INTEC, or both.\n\nIn 2012, the U.S. Geological Survey collected discrete groundwater samples from 25 zones in 11 wells equipped with multilevel monitoring systems to help define the vertical distribution of <sup>129</sup>I in the aquifer. Concentrations ranged from 0.000006±0.000004 to 0.082±0.003 pCi/L. Two new wells completed in 2012 showed variability of up to one order of magnitude of concentrations of <sup>129</sup>I among various zones. Two other wells showed similar concentrations of <sup>129</sup>I in all three zones sampled. Concentrations were well less than the maximum contaminant level in all zones.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135195","collaboration":"Prepared in cooperation with the U.S. Department of Energy","usgsCitation":"Bartholomay, R.C., 2013, Iodine-129 in the eastern Snake River Plain aquifer at and near the Idaho National Laboratory, Idaho, 2010-12: U.S. Geological Survey Scientific Investigations Report 2013-5195, vi, 22 p., https://doi.org/10.3133/sir20135195.","productDescription":"vi, 22 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-044719","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":279154,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135195.jpg"},{"id":279153,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5195/pdf/sir20135195.pdf"},{"id":279152,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5195/"}],"country":"United States","state":"Idaho","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -114.4556,42.0085 ], [ -114.4556,44.4397 ], [ -111.6129,44.4397 ], [ -111.6129,42.0085 ], [ -114.4556,42.0085 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"528b3709e4b031f8c843946e","contributors":{"authors":[{"text":"Bartholomay, Roy C. 0000-0002-4809-9287 rcbarth@usgs.gov","orcid":"https://orcid.org/0000-0002-4809-9287","contributorId":1131,"corporation":false,"usgs":true,"family":"Bartholomay","given":"Roy","email":"rcbarth@usgs.gov","middleInitial":"C.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":486232,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70056175,"text":"70056175 - 2013 - Paleomagnetic contributions to the Klamath Mountains terrane puzzle-a new piece from the Ironside Mountain batholith, northern California","interactions":[],"lastModifiedDate":"2023-05-26T16:13:12.725475","indexId":"70056175","displayToPublicDate":"2013-11-18T15:37:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3525,"text":"Tectonophysics","active":true,"publicationSubtype":{"id":10}},"title":"Paleomagnetic contributions to the Klamath Mountains terrane puzzle-a new piece from the Ironside Mountain batholith, northern California","docAbstract":"We obtained paleomagnetic samples from six sites within the Middle Jurassic Ironside Mountain batholith (~170 Ma), which constitutes the structurally lowest part of the Western Hayfork terrane, in the Klamath Mountains province of northern California and southern Oregon.  Structural attitudes measured in the coeval Hayfork Bally Meta-andesite were used to correct paleomagnetic data from the batholith.  Comparing the corrected paleomagnetic pole with a 170-Ma reference pole for North America indicates 73.5° ± 10.6° of clockwise rotation relative to the craton.  Nearly one-half of this rotation may have occurred before the terrane accreted to the composite Klamath province at ~168 Ma.  No latitudinal displacement of the batholith was detected.","language":"English","publisher":"Elsevier","doi":"10.1016/j.tecto.2013.09.007","usgsCitation":"Mankinen, E.A., Gromme, C.S., and Irwin, W.P., 2013, Paleomagnetic contributions to the Klamath Mountains terrane puzzle-a new piece from the Ironside Mountain batholith, northern California: Tectonophysics, v. 608, p. 401-407, https://doi.org/10.1016/j.tecto.2013.09.007.","productDescription":"6 p.","startPage":"401","endPage":"407","ipdsId":"IP-050598","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":279149,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon, Washington","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.0,40.5 ], [ -124.0,43.0 ], [ -122.5,43.0 ], [ -122.5,40.5 ], [ -124.0,40.5 ] ] ] } } ] }","volume":"608","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"528b370ae4b031f8c8439474","contributors":{"authors":[{"text":"Mankinen, Edward A. 0000-0001-7496-2681 emank@usgs.gov","orcid":"https://orcid.org/0000-0001-7496-2681","contributorId":1054,"corporation":false,"usgs":true,"family":"Mankinen","given":"Edward","email":"emank@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":486397,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gromme, C. Sherman","contributorId":22236,"corporation":false,"usgs":true,"family":"Gromme","given":"C.","email":"","middleInitial":"Sherman","affiliations":[],"preferred":false,"id":486398,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Irwin, W. Porter","contributorId":84262,"corporation":false,"usgs":true,"family":"Irwin","given":"W.","email":"","middleInitial":"Porter","affiliations":[],"preferred":false,"id":486399,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70048946,"text":"sim3270 - 2013 - Water-table and Potentiometric-surface altitudes in the Upper Glacial, Magothy, and Lloyd aquifers beneath Long Island, New York, April-May 2010","interactions":[],"lastModifiedDate":"2013-11-18T15:36:06","indexId":"sim3270","displayToPublicDate":"2013-11-18T14:51:00","publicationYear":"2013","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":"3270","title":"Water-table and Potentiometric-surface altitudes in the Upper Glacial, Magothy, and Lloyd aquifers beneath Long Island, New York, April-May 2010","docAbstract":"The U.S. Geological Survey (USGS), in cooperation with State and local agencies, systematically collects groundwater data at varying measurement frequencies to monitor the hydrologic conditions on Long Island, New York. Each year during April and May, the USGS conducts a synoptic survey of water levels to define the spatial distribution of the water table and potentiometric surfaces within the three main water-bearing units underlying Long Island—the upper glacial, Magothy, and Lloyd aquifers (Smolensky and others, 1989)—and the hydraulically connected Jameco (Soren, 1971) and North Shore aquifers (Stumm, 2001). These data and the maps constructed from them are commonly used in studies of Long Island’s hydrology and are used by water managers and suppliers for aquifer management and planning purposes. Water-level measurements made in 503 monitoring wells, a network of observation and supply wells, and 16 streamgage locations across Long Island during April–May 2010 were used to prepare the maps in this report. Measurements were made by the wetted-tape method to the nearest hundredth of a foot. Water-table and potentiometric-surface altitudes in these aquifers were contoured by using these measurements. The water-table contours were interpreted by using water-level data collected from 16 streamgages, 349 observation wells, and 1 supply well screened in the upper glacial aquifer and (or) shallow Magothy aquifer; the Magothy aquifer’s potentiometric-surface contours were interpreted from measurements at 67 observation wells and 27 supply wells screened in the middle to deep Magothy aquifer and (or) the contiguous and hydraulically connected Jameco aquifer. The Lloyd aquifer’s potentiometric-surface contours were interpreted from measurements at 55 observation wells and 4 supply wells screened in the Lloyd aquifer or the contiguous and hydraulically connected North Shore aquifer. Many of the supply wells are in continuous operation and, therefore, were turned off for a minimum of 24 hours before measurements were made so that the water levels in the wells could recover to the level of the potentiometric head in the surrounding aquifer. Full recovery time at some of these supply wells can exceed 24 hours; therefore, water levels measured at these wells are assumed to be less accurate than those measured at observation wells, which are not pumped (Busciolano, 2002). In this report, all water-level altitudes are referenced to the National Geodetic Vertical Datum of 1929 (NGVD 29). Hydrographs are included on these maps for selected wells that are instrumented with recording equipment. These hydrographs are representative of the 2010 water year1 to show the changes that have occurred throughout that period. The synoptic survey water level measured at the well is included on each hydrograph.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3270","collaboration":"Prepared in cooperation with the Nassau County Department of Public Works, New York City Department of Environmental Protection, New York State Department of Environmental Conservation, Suffolk County Department of Health, Services Suffolk County Water Authority, Town of North Hempstead, Town of Shelter Island, and the U.S. Environmental Protection Agency","usgsCitation":"Monti, J., Como, M.D., and Busciolano, R., 2013, Water-table and Potentiometric-surface altitudes in the Upper Glacial, Magothy, and Lloyd aquifers beneath Long Island, New York, April-May 2010: U.S. Geological Survey Scientific Investigations Map 3270, Map text content: 5 p.; 5 Sheets: 72 inches x 34 inches, https://doi.org/10.3133/sim3270.","productDescription":"Map text content: 5 p.; 5 Sheets: 72 inches x 34 inches","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-034294","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":438781,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FRG2Z3","text":"USGS data release","linkHelpText":"Geospatial Dataset of Water-Table and Potentiometric-Surface Altitudes in the Upper Glacial, Magothy, and Lloyd Aquifers of Long Island, New York, April-May 2010"},{"id":279144,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3270/pdf/sim3270_s3p.pdf"},{"id":279145,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3270/pdf/sim3270_s4p.pdf"},{"id":279146,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3270/pdf/sim3270_monti_Map_text_content.pdf"},{"id":279147,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim3270.PNG"},{"id":279142,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3270/pdf/sim3270_s1p.pdf"},{"id":279143,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3270/pdf/sim3270_s2p.pdf"},{"id":279140,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3270/"}],"country":"United States","state":"New York","otherGeospatial":"Long Island","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -74.0419,40.5418 ], [ -74.0419,41.1408 ], [ -71.8563,41.1408 ], [ -71.8563,40.5418 ], [ -74.0419,40.5418 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"528b370be4b031f8c8439485","contributors":{"authors":[{"text":"Monti, Jack Jr. jmonti@usgs.gov","contributorId":1185,"corporation":false,"usgs":true,"family":"Monti","given":"Jack","suffix":"Jr.","email":"jmonti@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":false,"id":485829,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Como, Michael D. 0000-0002-7911-5390 mcomo@usgs.gov","orcid":"https://orcid.org/0000-0002-7911-5390","contributorId":4651,"corporation":false,"usgs":true,"family":"Como","given":"Michael","email":"mcomo@usgs.gov","middleInitial":"D.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":485830,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Busciolano, Ronald 0000-0002-9257-8453 rjbuscio@usgs.gov","orcid":"https://orcid.org/0000-0002-9257-8453","contributorId":1059,"corporation":false,"usgs":true,"family":"Busciolano","given":"Ronald","email":"rjbuscio@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":false,"id":485828,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70055736,"text":"ofr20131273 - 2013 - Post-fire debris-flow hazard assessment of the area burned by the 2013 Beaver Creek Fire near Hailey, central Idaho","interactions":[],"lastModifiedDate":"2013-11-18T14:35:05","indexId":"ofr20131273","displayToPublicDate":"2013-11-18T11:57:00","publicationYear":"2013","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":"2013-1273","title":"Post-fire debris-flow hazard assessment of the area burned by the 2013 Beaver Creek Fire near Hailey, central Idaho","docAbstract":"A preliminary hazard assessment was developed for debris-flow hazards in the 465 square-kilometer (115,000 acres) area burned by the 2013 Beaver Creek fire near Hailey in central Idaho. The burn area covers all or part of six watersheds and selected basins draining to the Big Wood River and is at risk of substantial post-fire erosion, such as that caused by debris flows. Empirical models derived from statistical evaluation of data collected from recently burned basins throughout the Intermountain Region in Western United States were used to estimate the probability of debris-flow occurrence, potential volume of debris flows, and the combined debris-flow hazard ranking along the drainage network within the burn area and to estimate the same for analyzed drainage basins within the burn area. Input data for the empirical models included topographic parameters, soil characteristics, burn severity, and rainfall totals and intensities for a (1) 2-year-recurrence, 1-hour-duration rainfall, referred to as a 2-year storm (13 mm); (2) 10-year-recurrence, 1-hour-duration rainfall, referred to as a 10-year storm (19 mm); and (3) 25-year-recurrence, 1-hour-duration rainfall, referred to as a 25-year storm (22 mm). Estimated debris-flow probabilities for drainage basins upstream of 130 selected basin outlets ranged from less than 1 to 78 percent with the probabilities increasing with each increase in storm magnitude. Probabilities were high in three of the six watersheds. For the 25-year storm, probabilities were greater than 60 percent for 11 basin outlets and ranged from 50 to 60 percent for an additional 12 basin outlets. Probability estimates for stream segments within the drainage network can vary within a basin. For the 25-year storm, probabilities for stream segments within 33 basins were higher than the basin outlet, emphasizing the importance of evaluating the drainage network as well as basin outlets. Estimated debris-flow volumes for the three modeled storms range from a minimal debris flow volume of 10 cubic meters [m<sup>3</sup>]) to greater than 100,000 m<sup>3</sup>. Estimated debris-flow volumes increased with basin size and distance downstream. For the 25-year storm, estimated debris-flow volumes were greater than 100,000 m<sup>3</sup> for 4 basins and between 50,000 and 100,000 m<sup>3</sup> for 10 basins. The debris-flow hazard rankings did not result in the highest hazard ranking of 5, indicating that none of the basins had a high probability of debris-flow occurrence and a high debris-flow volume estimate. The hazard ranking was 4 for one basin using the 10-year-recurrence storm model and for three basins using the 25-year-recurrence storm model. The maps presented herein may be used to prioritize areas where post-wildfire remediation efforts should take place within the 2- to 3-year period of increased erosional vulnerability.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131273","collaboration":"Prepared in cooperation with Blaine County, Idaho","usgsCitation":"Skinner, K.D., 2013, Post-fire debris-flow hazard assessment of the area burned by the 2013 Beaver Creek Fire near Hailey, central Idaho: U.S. Geological Survey Open-File Report 2013-1273, Report: iv, 12 p.; Table: XLSX file; 9 plates: 24 inches x 31 inches, https://doi.org/10.3133/ofr20131273.","productDescription":"Report: iv, 12 p.; Table: XLSX file; 9 plates: 24 inches x 31 inches","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-052301","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":279139,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131273.PNG"},{"id":279121,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1273/"},{"id":279129,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2013/1273/downloads/ofr2013-1273_table1.xlsx"},{"id":279130,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2013/1273/pdfs/ofr2013-1273_plate1.pdf"},{"id":279131,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2013/1273/pdfs/ofr2013-1273_plate3.pdf"},{"id":279128,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1273/pdfs/ofr2013-1273.pdf"},{"id":279132,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2013/1273/pdfs/ofr2013-1273_plate2.pdf"},{"id":279133,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2013/1273/pdfs/ofr2013-1273_plate4.pdf"},{"id":279134,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2013/1273/pdfs/ofr2013-1273_plate5.pdf"},{"id":279135,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2013/1273/pdfs/ofr2013-1273_plate6.pdf"},{"id":279136,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2013/1273/pdfs/ofr2013-1273_plate7.pdf"},{"id":279137,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2013/1273/pdfs/ofr2013-1273_plate8.pdf"},{"id":279138,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2013/1273/pdfs/ofr2013-1273_plate9.pdf"}],"country":"United States","state":"Idaho","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -114.67495,43.499756 ], [ -114.67495,43.699651 ], [ -114.311371,43.699651 ], [ -114.311371,43.499756 ], [ -114.67495,43.499756 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"528b370ae4b031f8c843947a","contributors":{"authors":[{"text":"Skinner, Kenneth D. 0000-0003-1774-6565 kskinner@usgs.gov","orcid":"https://orcid.org/0000-0003-1774-6565","contributorId":1836,"corporation":false,"usgs":true,"family":"Skinner","given":"Kenneth","email":"kskinner@usgs.gov","middleInitial":"D.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":486256,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70047103,"text":"70047103 - 2013 - Temporal changes and sexual differences in spatial distribution of Burbot in Lake Erie","interactions":[],"lastModifiedDate":"2013-11-15T10:18:01","indexId":"70047103","displayToPublicDate":"2013-11-15T11:46:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Temporal changes and sexual differences in spatial distribution of Burbot in Lake Erie","docAbstract":"We used GIS mapping techniques to examine capture data for Burbot Lota lota from annual gill-net surveys in Canadian waters of Lake Erie during late August and September 1994–2011. Adult males were captured over a larger area (3–17% for ≥20% maximum yearly catch [MYC]) than adult females. More males than females were caught in the gill nets in 14 of the 15 study years. Collectively, these results support a hypothesis of greater activity by adult males during summer, when Burbot are actively feeding. The area of capture contracted by more than 60% (for ≥20% MYC) for both sexes during the time period, which is consistent with the documented decrease of the Burbot population in the lake. The sex ratio (females: males) varied over the time series but declined steadily from 0.97 in 2001 to 0.59 in 2011. The overlap in the capture areas of adult males and females was scale dependent. The depth distribution at which adult Burbot were caught did not change over the time series, and there was no difference in the median depths (about 30 m) at which adult male and female Burbot were caught. The last results are consistent with the Burbot's reliance on coldwater habitats. Additional research is recommended, including telemetry to describe daily and seasonal movements and assessment of gender bias in active and passive capture gear.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Transactions of the American Fisheries Society","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Taylor & Francis","doi":"10.1080/00028487.2013.795191","usgsCitation":"Stapanian, M.A., Witzel, L.D., and Cook, A., 2013, Temporal changes and sexual differences in spatial distribution of Burbot in Lake Erie: Transactions of the American Fisheries Society, v. 142, no. 6, p. 1724-1732, https://doi.org/10.1080/00028487.2013.795191.","productDescription":"9 p.","startPage":"1724","endPage":"1732","numberOfPages":"9","ipdsId":"IP-045137","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":279105,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":279104,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1080/00028487.2013.795191"}],"country":"Canada;United States","otherGeospatial":"Lake Erie","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -80.6803,41.8693 ], [ -80.6803,42.9038 ], [ -78.8183,42.9038 ], [ -78.8183,41.8693 ], [ -80.6803,41.8693 ] ] ] } } ] }","volume":"142","issue":"6","noUsgsAuthors":false,"publicationDate":"2013-11-07","publicationStatus":"PW","scienceBaseUri":"5287425ee4b03b89f6f15080","contributors":{"authors":[{"text":"Stapanian, Martin A. 0000-0001-8173-4273 mstapanian@usgs.gov","orcid":"https://orcid.org/0000-0001-8173-4273","contributorId":3425,"corporation":false,"usgs":true,"family":"Stapanian","given":"Martin","email":"mstapanian@usgs.gov","middleInitial":"A.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":481059,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Witzel, Larry D.","contributorId":68642,"corporation":false,"usgs":true,"family":"Witzel","given":"Larry","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":481061,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cook, Andy","contributorId":48473,"corporation":false,"usgs":true,"family":"Cook","given":"Andy","email":"","affiliations":[],"preferred":false,"id":481060,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70055619,"text":"sir20135155 - 2013 - Equations for estimating bankfull channel geometry and discharge for streams in Massachusetts","interactions":[],"lastModifiedDate":"2013-11-14T15:49:49","indexId":"sir20135155","displayToPublicDate":"2013-11-14T15:45:00","publicationYear":"2013","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":"2013-5155","title":"Equations for estimating bankfull channel geometry and discharge for streams in Massachusetts","docAbstract":"Regression equations were developed for estimating bankfull geometry—width, mean depth, cross-sectional area—and discharge for streams in Massachusetts. The equations provide water-resource and conservation managers with methods for estimating bankfull characteristics at specific stream sites in Massachusetts. This information can be used for the adminstration of the Commonwealth of Massachusetts Rivers Protection Act of 1996, which establishes a protected riverfront area extending from the mean annual high-water line corresponding to the elevation of bankfull discharge along each side of a perennial stream. Additionally, information on bankfull channel geometry and discharge are important to Federal, State, and local government agencies and private organizations involved in stream assessment and restoration projects.\n\nRegression equations are based on data from stream surveys at 33 sites (32 streamgages and 1 crest-stage gage operated by the U.S. Geological Survey) in and near Massachusetts. Drainage areas of the 33 sites ranged from 0.60 to 329 square miles (mi2). At 27 of the 33 sites, field data were collected and analyses were done to determine bankfull channel geometry and discharge as part of the present study. For 6 of the 33 sites, data on bankfull channel geometry and discharge were compiled from other studies done by the U.S. Geological Survey, Natural Resources Conservation Service of the U.S. Department of Agriculture, and the Vermont Department of Environmental Conservation. Similar techniques were used for field data collection and analysis for bankfull channel geometry and discharge at all 33 sites. Recurrence intervals of the bankfull discharge, which represent the frequency with which a stream fills its channel, averaged 1.53 years (median value 1.34 years) at the 33 sites. Simple regression equations were developed for bankfull width, mean depth, cross-sectional area, and discharge using drainage area, which is the most significant explanatory variable in estimating these bankfull characteristics. The use of drainage area as an explanatory variable is also the most commonly published method for estimating these bankfull characteristics. Regional curves (graphic plots) of bankfull channel geometry and discharge by drainage area are presented. The regional curves are based on the simple regression equations and can be used to estimate bankfull characteristics from drainage area. Multiple regression analysis, which includes basin characteristics in addition to drainage area, also was used to develop equations. Variability in bankfull width, mean depth, cross-sectional area, and discharge was more fully explained by the multiple regression equations that include mean-basin slope and drainage area than was explained by equations based on drainage area alone. The Massachusetts regional curves and equations developed in this study are similar, in terms of values of slopes and intercepts, to those developed for other parts of the northeastern United States.\n\nLimitations associated with site selection and development of the equations resulted in some constraints for the application of equations and regional curves presented in this report. The curves and equations are applicable to stream sites that have (1) less than about 25 percent of their drainage basin area occupied by urban land use (commercial, industrial, transportation, and high-density residential), (2) little to no streamflow regulation, especially from flood-control structures, (3) drainage basin areas greater than 0.60 mi2 and less than 329 mi2, and (4) a mean basin slope greater than 2.2 percent and less than 23.9 percent. The equations may not be applicable where streams flow through extensive wetlands. The equations also may not apply in areas of Cape Cod and the Islands and the area of southeastern Massachusetts close to Cape Cod with extensive areas of coarse-grained glacial deposits where none of the study sites are located. Regardless of the setting, the regression equations are not intended for use as the sole method of estimating bankfull characteristics; however, they may supplement field identification of the bankfull channel when used in conjunction with field verified bankfull indicators, flood-frequency analysis, or other supporting evidence.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135155","collaboration":"Prepared in cooperation with the Massachusetts Department of Environmental Protection Bureau of Resource Protection Wetlands and Waterways Program and Massachusetts Environmental Trust","usgsCitation":"Bent, G.C., and Waite, A.M., 2013, Equations for estimating bankfull channel geometry and discharge for streams in Massachusetts: U.S. Geological Survey Scientific Investigations Report 2013-5155, vii, 61 p., https://doi.org/10.3133/sir20135155.","productDescription":"vii, 61 p.","numberOfPages":"74","onlineOnly":"N","ipdsId":"IP-009440","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":279091,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135155.jpg"},{"id":279090,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5155/pdf/sir2013-5155.pdf"},{"id":279087,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5155/"}],"country":"United States","state":"Massachusetts","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -73.5081,41.2491 ], [ -73.5081,42.8868 ], [ -69.928,42.8868 ], [ -69.928,41.2491 ], [ -73.5081,41.2491 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52860762e4b00926c218653e","contributors":{"authors":[{"text":"Bent, Gardner C. 0000-0002-5085-3146 gbent@usgs.gov","orcid":"https://orcid.org/0000-0002-5085-3146","contributorId":1864,"corporation":false,"usgs":true,"family":"Bent","given":"Gardner","email":"gbent@usgs.gov","middleInitial":"C.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":486153,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Waite, Andrew M. awaite@usgs.gov","contributorId":2215,"corporation":false,"usgs":true,"family":"Waite","given":"Andrew","email":"awaite@usgs.gov","middleInitial":"M.","affiliations":[],"preferred":true,"id":486154,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70048994,"text":"sir20135133 - 2013 - Hydrogeology and hydrologic conditions of the Northern Atlantic Coastal Plain aquifer System from Long Island, New York, to North Carolina","interactions":[],"lastModifiedDate":"2017-01-17T20:47:58","indexId":"sir20135133","displayToPublicDate":"2013-11-14T15:33:00","publicationYear":"2013","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":"2013-5133","title":"Hydrogeology and hydrologic conditions of the Northern Atlantic Coastal Plain aquifer System from Long Island, New York, to North Carolina","docAbstract":"<p>The seaward-dipping sedimentary wedge that underlies the Northern Atlantic Coastal Plain forms a complex groundwater system. This major source of water provides for public and domestic supply and serves as a vital source of freshwater for industrial and agricultural uses throughout the region. Population increases and land-use and climate changes, however, have led to competing demands for water. The regional response of the aquifer system to these stresses poses regional challenges for water-resources management at the State level because hydrologic effects often extend beyond State boundaries. In response to these challenges, the U.S. Geological Survey Groundwater Resources Program began a regional assessment of the groundwater availability of the Northern Atlantic Coastal Plain aquifer system in 2010.</p>\n<p>The initial phase of this investigation included a refinement of the hydrogeologic framework and an updated hydrologic budget of this aquifer system from the last regional aquifer system assessment completed by the U.S. Geological Survey in the 1980s. Refinements to the hydrogeologic framework include revision of the regional aquifer names to be more consistent with local names in New York, New Jersey, Delaware, Maryland, and Virginia, the primary States included in the study area. Other revisions to the framework include characterization of the aquifers of the regional Potomac aquifer system. The regional Potomac aquifer system is subdivided for this report into two regional aquifers. These aquifers include the single Potomac aquifer in Virginia and two aquifers in Maryland, Delaware, and New Jersey, where the Potomac aquifer system thickens within the Salisbury Embayment. The two regional aquifers making up the Potomac aquifer system include the Potomac-Patapsco aquifer and the underlying Potomac-Patuxent aquifer.</p>\n<p>The Potomac-Patuxent aquifer includes the Lower Potomac-Raritan-Magothy aquifer in southern New Jersey and the Patuxent aquifers in Delaware and Maryland. In northern New Jersey and on Long Island, New York, the PotomacPatuxent aquifer is absent, but the Late Cretaceous fluvialdeltaic aquifer that is laterally equivalent with the upper part of the Potomac Formation now is considered part of the regional Potomac-Patapsco aquifer. This aquifer includes the Middle Potomac-Raritan-Magothy aquifer in New Jersey and the Lloyd aquifer on Long Island.</p>\n<p>The name &ldquo;Upper Potomac aquifer&rdquo; has been removed as part of this regional framework revision. The local aquifer previously considered part of the Upper Potomac aquifer now are part of the regional Magothy aquifer. These units include the Upper Potomac-Raritan-Magothy aquifer in New Jersey, the Magothy aquifers on Long Island, Delaware, and Maryland, and the Virginia Beach aquifer in Virginia.</p>\n<p>Updates to the regional hydrologic budget include revised estimates of aquifer recharge, water use and streamflow data. Inflow to the aquifer system of about 20,000 million gallons per day (Mgal/d) includes 19,600 Mgal/d from recharge from precipitation, 200 Mgal/d of recharge from wastewater via onsite domestic septic systems, and 200 Mgal/d from the release of water from aquifer storage. Outflow from the aquifer system includes groundwater discharge to streams (11,900 Mgal/d), groundwater withdrawals (1,500 Mgal/d), and groundwater discharge to coastal waters (6,600 Mgal/d). A numerical modeling analysis is required to improve this hydrologic budget calculation and to forecast future changes in water levels and aquifer storage caused by groundwater withdrawals, land-use changes, and the effects of climate variability and change.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135133","collaboration":"Groundwater Resources Program","usgsCitation":"Masterson, J.P., Pope, J.P., Monti, Jack, Jr., Nardi, M.R., Finkelstein, J.S., and McCoy, K.J., 2015, Hydrogeology and hydrologic conditions of the Northern Atlantic Coastal Plain aquifer system from Long Island, New York, to North Carolina (ver. 1.1, September 2015): U.S. Geological Survey Scientific Investigations Report 2013–5133, 76 p., https://dx.doi.org/10.3133/sir20135133.","productDescription":"viii, 76 p.","numberOfPages":"88","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-044313","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":308391,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":279088,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5133/pdf/sir20135133.pdf"},{"id":308378,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5133/"}],"country":"United States","state":"Delaware, Maryland, New Jersey, New York, North Carolina, Virginia","otherGeospatial":"Northern Atlantic Coastal Plain","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -78.0,34.0 ], [ -78.0,42.0 ], [ -71.0,42.0 ], [ -71.0,34.0 ], [ -78.0,34.0 ] ] ] } } ] }","edition":"Version 1.0 November 14, 2013; Version 1.1 September 22, 2015","contact":"<p><a href=\"mailto:dc_ma@usgs.gov&quot;\">Office Chief</a><br /> U.S. Geological Survey<br /> New England Water Science Center<br /> Massachusetts-Rhode Island Office<br /> 10 Bearfoot Road<br /> Northborough, MA 01532</p>\n<p>Or visit our Web site at:<br /> <a href=\"http://ma.water.usgs.gov\">http://ma.water.usgs.gov</a></p>","tableOfContents":"<ul>\n<li>\n<p>Abstract</p>\n</li>\n<li>\n<p>Introduction</p>\n</li>\n<li>\n<p>Hydrogeology</p>\n</li>\n<li>\n<p>Hydrologic Conditions</p>\n</li>\n<li>\n<p>Summary and Conclusions</p>\n</li>\n<li>\n<p>References Cited</p>\n</li>\n<li>Appendix</li>\n</ul>","publishedDate":"2013-11-14","revisedDate":"2015-09-18","noUsgsAuthors":false,"publicationDate":"2013-11-14","publicationStatus":"PW","scienceBaseUri":"52860785e4b00926c2186544","contributors":{"authors":[{"text":"Masterson, John P. 0000-0003-3202-4413 jpmaster@usgs.gov","orcid":"https://orcid.org/0000-0003-3202-4413","contributorId":1865,"corporation":false,"usgs":true,"family":"Masterson","given":"John P.","email":"jpmaster@usgs.gov","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":false,"id":485958,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pope, Jason P. 0000-0003-3199-993X jpope@usgs.gov","orcid":"https://orcid.org/0000-0003-3199-993X","contributorId":2044,"corporation":false,"usgs":true,"family":"Pope","given":"Jason","email":"jpope@usgs.gov","middleInitial":"P.","affiliations":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true},{"id":37759,"text":"VA/WV Water Science Center","active":true,"usgs":true}],"preferred":true,"id":485959,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Monti, Jack Jr. jmonti@usgs.gov","contributorId":1185,"corporation":false,"usgs":true,"family":"Monti","given":"Jack","suffix":"Jr.","email":"jmonti@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":false,"id":485955,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nardi, Mark R. 0000-0002-7310-8050 mrnardi@usgs.gov","orcid":"https://orcid.org/0000-0002-7310-8050","contributorId":1859,"corporation":false,"usgs":true,"family":"Nardi","given":"Mark","email":"mrnardi@usgs.gov","middleInitial":"R.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia  Water Science Center","active":true,"usgs":true}],"preferred":true,"id":485957,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Finkelstein, Jason S.","contributorId":87055,"corporation":false,"usgs":true,"family":"Finkelstein","given":"Jason S.","affiliations":[],"preferred":false,"id":485960,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McCoy, Kurt J. 0000-0002-9756-8238 kjmccoy@usgs.gov","orcid":"https://orcid.org/0000-0002-9756-8238","contributorId":1391,"corporation":false,"usgs":true,"family":"McCoy","given":"Kurt","email":"kjmccoy@usgs.gov","middleInitial":"J.","affiliations":[{"id":37280,"text":"Virginia and West Virginia Water Science Center ","active":true,"usgs":true}],"preferred":true,"id":485956,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70055876,"text":"70055876 - 2013 - Spatial ecological processes and local factors predict the distribution and abundance of spawning by steelhead (<i>Oncorhynchus mykiss</i>) across a complex riverscape","interactions":[],"lastModifiedDate":"2013-11-14T14:21:40","indexId":"70055876","displayToPublicDate":"2013-11-14T14:13:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Spatial ecological processes and local factors predict the distribution and abundance of spawning by steelhead (<i>Oncorhynchus mykiss</i>) across a complex riverscape","docAbstract":"Processes that influence habitat selection in landscapes involve the interaction of habitat composition and configuration and are particularly important for species with complex life cycles. We assessed the relative influence of landscape spatial processes and local habitat characteristics on patterns in the distribution and abundance of spawning steelhead (Oncorhynchus mykiss), a threatened salmonid fish, across ~15,000 stream km in the John Day River basin, Oregon, USA. We used hurdle regression and a multi-model information theoretic approach to identify the relative importance of covariates representing key aspects of the steelhead life cycle (e.g., site access, spawning habitat quality, juvenile survival) at two spatial scales: within 2-km long survey reaches (local sites) and ecological neighborhoods (5 km) surrounding the local sites. Based on Akaike’s Information Criterion, models that included covariates describing ecological neighborhoods provided the best description of the distribution and abundance of steelhead spawning given the data. Among these covariates, our representation of offspring survival (growing-season-degree-days, °C) had the strongest effect size (7x) relative to other predictors. Predictive performances of model-averaged composite and neighborhood-only models were better than a site-only model based on both occurrence (percentage of sites correctly classified = 0.80±0.03 SD, 0.78±0.02 vs. 0.62±0.05, respectively) and counts (root mean square error = 3.37, 3.93 vs. 5.57, respectively). The importance of both temperature and stream flow for steelhead spawning suggest this species may be highly sensitive to impacts of land and water uses, and to projected climate impacts in the region and that landscape context, complementation, and connectivity will drive how this species responds to future environments.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"PLoS ONE","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0079232","usgsCitation":"Falke, J.A., Dunham, J., Jordan, C.E., McNyset, K., and Reeves, G.H., 2013, Spatial ecological processes and local factors predict the distribution and abundance of spawning by steelhead (<i>Oncorhynchus mykiss</i>) across a complex riverscape: PLoS ONE, v. 8, no. 11, 11 p., https://doi.org/10.1371/journal.pone.0079232.","productDescription":"11 p.","numberOfPages":"11","ipdsId":"IP-049835","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":473445,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0079232","text":"Publisher Index Page"},{"id":279081,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":279080,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1371/journal.pone.0079232"}],"country":"United States","state":"Oregon","otherGeospatial":"John Day River Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -120.5566,44.3714 ], [ -120.5566,45.6675 ], [ -117.9702,45.6675 ], [ -117.9702,44.3714 ], [ -120.5566,44.3714 ] ] ] } } ] }","volume":"8","issue":"11","noUsgsAuthors":false,"publicationDate":"2013-11-12","publicationStatus":"PW","scienceBaseUri":"52860786e4b00926c218654d","contributors":{"authors":[{"text":"Falke, Jeffrey A. 0000-0002-6670-8250 jfalke@usgs.gov","orcid":"https://orcid.org/0000-0002-6670-8250","contributorId":5195,"corporation":false,"usgs":true,"family":"Falke","given":"Jeffrey","email":"jfalke@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":486270,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dunham, Jason B.","contributorId":64791,"corporation":false,"usgs":true,"family":"Dunham","given":"Jason B.","affiliations":[],"preferred":false,"id":486273,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jordan, Christopher E.","contributorId":40116,"corporation":false,"usgs":true,"family":"Jordan","given":"Christopher","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":486271,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McNyset, Kris M.","contributorId":58177,"corporation":false,"usgs":true,"family":"McNyset","given":"Kris M.","affiliations":[],"preferred":false,"id":486272,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Reeves, Gordon H.","contributorId":101521,"corporation":false,"usgs":false,"family":"Reeves","given":"Gordon","email":"","middleInitial":"H.","affiliations":[{"id":527,"text":"Pacific Northwest Research Station","active":false,"usgs":true}],"preferred":false,"id":486274,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70055528,"text":"70055528 - 2013 - Tools and data for meeting America's conservation challenges","interactions":[],"lastModifiedDate":"2018-12-21T13:04:59","indexId":"70055528","displayToPublicDate":"2013-11-14T10:17:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":6,"text":"USGS Unnumbered Series"},"seriesTitle":{"id":362,"text":"General Information Product","active":false,"publicationSubtype":{"id":6}},"seriesNumber":"151","title":"Tools and data for meeting America's conservation challenges","docAbstract":"<p>The Gap Analysis Project (GAP) produces data and tools that help meet critical national challenges such as biodiversity conservation, renewable energy development, climate change adaptation, and infrastructure investment. The GAP is managed by the U.S. Geological Survey, Department of the Interior. GAP supports a wide range of national, State, and local agencies as well as nongovernmental organizations and businesses with scientific tools and data. GAP uses a collaborative approach to do research, analysis, and data development, resulting in a history of cooperation with more than 500 agencies and organizations nationally.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/70055528","collaboration":"Gap Analysis Project","usgsCitation":"Gergely, K.J., and McKerrow, A., 2013, Tools and data for meeting America's conservation challenges: General Information Product 151, 2 p., https://doi.org/10.3133/70055528.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","ipdsId":"IP-035164","costCenters":[{"id":37226,"text":"Core Science Analytics, Synthesis, and Libraries","active":true,"usgs":true},{"id":38315,"text":"GAP Analysis Project","active":true,"usgs":true}],"links":[{"id":279092,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":279023,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/gip/151/"},{"id":279070,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/gip/151/pdf/gip151.pdf"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 144.616667,13.233333 ], [ 144.616667,71.833333 ], [ -64.566667,71.833333 ], [ -64.566667,13.233333 ], [ 144.616667,13.233333 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52860787e4b00926c2186550","contributors":{"authors":[{"text":"Gergely, Kevin J. 0000-0002-4379-2189 gergely@usgs.gov","orcid":"https://orcid.org/0000-0002-4379-2189","contributorId":2706,"corporation":false,"usgs":true,"family":"Gergely","given":"Kevin","email":"gergely@usgs.gov","middleInitial":"J.","affiliations":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":true,"id":486130,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McKerrow, Alexa 0000-0002-8312-2905 amckerrow@usgs.gov","orcid":"https://orcid.org/0000-0002-8312-2905","contributorId":4542,"corporation":false,"usgs":false,"family":"McKerrow","given":"Alexa","email":"amckerrow@usgs.gov","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":486131,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70049018,"text":"ofr20131250 - 2013 - MODIS phenology image service ArcMap toolbox","interactions":[],"lastModifiedDate":"2013-11-13T15:02:31","indexId":"ofr20131250","displayToPublicDate":"2013-11-13T14:59:00","publicationYear":"2013","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":"2013-1250","title":"MODIS phenology image service ArcMap toolbox","docAbstract":"<p>Seasonal change is important to consider when managing conservation areas at landscape scales. The study of such patterns throughout the year is referred to as phenology. Recurring life-cycle events that are initiated and driven by environmental factors include animal migration and plant flowering. Phenological events capture public attention, such as fall color change in deciduous forests, the first flowering in spring, and for those with allergies, the start of the pollen season. These events can affect our daily lives, provide clues to help understand and manage ecosystems, and provide evidence of how climate variability can affect the natural cycle of plants and animals. Phenological observations can be gathered at a range of scales, from plots smaller than an acre to landscapes of hundreds to thousands of acres. Linking these observations to diverse disciplines such as evolutionary biology or climate sciences can help further research in species and ecosystem responses to climate change scenarios at appropriate scales.</p>\n<br/>\n<p>A cooperative study between the National Park Service (NPS), the U.S. Geological Survey (USGS), and the National Aeronautics and Space Administration (NASA) has been exploring how satellite information can be used to summarize phenological patterns observed at the park or landscape scale and how those summaries can be presented to both park managers and visitors. This study specifically addressed seasonal changes in plants, including the onset of growth, photosynthesis in the spring, and the senescence of deciduous vegetation in the fall. The primary objective of the work is to demonstrate that seasonality even in protected areas changes considerably across years. A major challenge is to decouple natural variability from possible trends—directional change that can lead to a permanent and radically different ecosystem state. Trends can be either a gradual degradation of the landscape (often from external influences) or steady improvement (by implementing long-term conservation plans). In either case, it is important to first grasp the magnitude of natural variation so that it is not confused with actual trends.</p>\n<br/>\n<p>This work used existing and freely available remote sensing data, specifically the NASA-funded 250-meter (m) spatial resolution land-surface phenology product for North America. This product is calculated from an annual record of vegetation health observed by NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) instrument. The land-surface phenology product is, in essence, a method to summarize all the observations throughout a year into a few key, ecologically relevant “metrics”.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131250","collaboration":"Prepared in cooperation with the National Park Service and the Great Northern Landscape Conservation Cooperative","usgsCitation":"Talbert, C., Kern, T., Morisette, J., Brown, D., and James, K., 2013, MODIS phenology image service ArcMap toolbox: U.S. Geological Survey Open-File Report 2013-1250, iii, 6 p., https://doi.org/10.3133/ofr20131250.","productDescription":"iii, 6 p.","numberOfPages":"9","onlineOnly":"Y","ipdsId":"IP-045950","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":279059,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131250.jpg"},{"id":279058,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1250/pdf/of2013-1250.pdf"},{"id":279057,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1250/"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52849f61e4b063f258e57461","contributors":{"authors":[{"text":"Talbert, Colin talbertc@usgs.gov","contributorId":4668,"corporation":false,"usgs":true,"family":"Talbert","given":"Colin","email":"talbertc@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":486033,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kern, Tim J. kernt@usgs.gov","contributorId":4454,"corporation":false,"usgs":true,"family":"Kern","given":"Tim J.","email":"kernt@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":486032,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Morisette, Jeff","contributorId":20640,"corporation":false,"usgs":true,"family":"Morisette","given":"Jeff","email":"","affiliations":[],"preferred":false,"id":486034,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brown, Don","contributorId":73490,"corporation":false,"usgs":true,"family":"Brown","given":"Don","email":"","affiliations":[],"preferred":false,"id":486035,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"James, Kevin","contributorId":106787,"corporation":false,"usgs":true,"family":"James","given":"Kevin","email":"","affiliations":[],"preferred":false,"id":486036,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70055547,"text":"sir20135177 - 2013 - Results of repeat bathymetric and velocimetric surveys at the Amelia Earhart Bridge on U.S. Highway 59 over the Missouri River at Atchison, Kansas, 2009-2013","interactions":[],"lastModifiedDate":"2013-11-13T10:10:47","indexId":"sir20135177","displayToPublicDate":"2013-11-13T08:25:00","publicationYear":"2013","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":"2013-5177","title":"Results of repeat bathymetric and velocimetric surveys at the Amelia Earhart Bridge on U.S. Highway 59 over the Missouri River at Atchison, Kansas, 2009-2013","docAbstract":"<p>Bathymetric and velocimetric data were collected six times by the U.S. Geological Survey, in cooperation with the Kansas Department of Transportation, in the vicinity of Amelia Earhart Bridge on U.S. Highway 59 over the Missouri River at Atchison, Kansas. A multibeam echosounder mapping system and an acoustic Doppler current meter were used to obtain channel-bed elevations and depth-averaged velocities for a river reach approximately 2,300 feet long and extending across the active channel of the Missouri River. The bathymetric and velocimetric surveys provide a “snapshot” of the channel conditions at the time of each survey, and document changes to the channel-bed elevations and velocities during the course of construction of a new bridge for U.S. Highway 59 downstream from the Amelia Earhart Bridge.</p>\n<br/>\n<p>The baseline survey in June 2009 revealed substantial scour holes existed at the railroad bridge piers upstream from and at pier 10 of the Amelia Earhart Bridge, with mostly uniform flow and velocities throughout the study reach. After the construction of a trestle and cofferdam on the left (eastern) bank downstream from the Amelia Earhart Bridge, a survey on June 2, 2010, revealed scour holes with similar size and shape as the baseline for similar flow conditions, with slightly higher velocities and a more substantial contraction of flow near the bridges than the baseline. Subsequent surveys during flooding conditions in June 2010 and July 2011 revealed substantial scour near the bridges compared to the baseline survey caused by the contraction of flow; however, the larger flood in July 2011 resulted in less scour than in June 2010, partly because the removal of the cofferdam for pier 5 of the new bridge in March 2011 diminished the contraction near the bridges. Generally, the downstream part of the study reach exhibited varying amounts of scour in all of the surveys except the last when compared to the baseline. During the final survey, velocities throughout the study area were the lowest of all the surveys, resulting in overall deposition throughout the reach compared to the baseline survey—despite the presence of the trestle in the final survey.</p>\n<br/>\n<p>The multiple surveys at the Amelia Earhart Bridge document the effects of moderate- to high-flow conditions on scour, compounded by the effects of adding and removing a constriction in the channel. Additional factors such as pier shape and angle of approach flow also were documented.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135177","collaboration":"Prepared in cooperation with the Kansas Department of Transportation","usgsCitation":"Huizinga, R.J., 2013, Results of repeat bathymetric and velocimetric surveys at the Amelia Earhart Bridge on U.S. Highway 59 over the Missouri River at Atchison, Kansas, 2009-2013: U.S. Geological Survey Scientific Investigations Report 2013-5177, vi, 50 p., https://doi.org/10.3133/sir20135177.","productDescription":"vi, 50 p.","numberOfPages":"60","onlineOnly":"Y","ipdsId":"IP-049424","costCenters":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true}],"links":[{"id":279044,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135177.jpg"},{"id":279043,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5177/pdf/sir2013-5177.pdf"},{"id":279042,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5177/"}],"projection":"Universal Transverse Mercator","datum":"North American Datum of 1983","country":"United States","state":"Kansas;Missouri","city":"Atchison;Ks;Winthrop;Mo","otherGeospatial":"Missouri River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -95.121111,39.552778 ], [ -95.121111,39.566667 ], [ -95.103611,39.566667 ], [ -95.103611,39.552778 ], [ -95.121111,39.552778 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52849f71e4b063f258e574ba","contributors":{"authors":[{"text":"Huizinga, Richard J. 0000-0002-2940-2324 huizinga@usgs.gov","orcid":"https://orcid.org/0000-0002-2940-2324","contributorId":2089,"corporation":false,"usgs":true,"family":"Huizinga","given":"Richard","email":"huizinga@usgs.gov","middleInitial":"J.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":486139,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70055531,"text":"fs20133087 - 2013 - Species data: National inventory of range maps and distribution models","interactions":[],"lastModifiedDate":"2018-12-21T13:02:00","indexId":"fs20133087","displayToPublicDate":"2013-11-12T15:36:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-3087","title":"Species data: National inventory of range maps and distribution models","docAbstract":"<p>The Gap Analysis Project (GAP) produces data and tools that help meet critical national challenges such as biodiversity conservation, renewable energy development, climate change adaptation, and infrastructure investment. The GAP species data includes vertebrate range maps and distribution models for the continental United States, as well as Alaska, Hawaii, Puerto Rico, and U.S. Virgin Islands. The vertebrate species include amphibians, birds, mammals, and reptiles. Furthermore, data used to create the distribution models (for example, percent canopy cover, elevation, and so forth) also are available.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20133087","collaboration":"Gap Analysis Project","usgsCitation":"Gergely, K.J., and McKerrow, A., 2013, Species data: National inventory of range maps and distribution models: U.S. Geological Survey Fact Sheet 2013-3087, 1 p., https://doi.org/10.3133/fs20133087.","productDescription":"1 p.","numberOfPages":"1","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-035322","costCenters":[{"id":38315,"text":"GAP Analysis Project","active":true,"usgs":true}],"links":[{"id":279035,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20133087.jpg"},{"id":279026,"type":{"id":15,"text":"Index 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States\"}}]}","edition":"Version 1.0: Originally posted November 12, 2013; Version 1.1: August 29, 2016","contact":"<p>Core Science Analytics and Synthesis<br>U.S. Geological Survey<br>302 National Center <br>Reston, VA 20192</p><p><br><a href=\"http://www.usgs.gov/core_science_systems/csas/index.html \" data-mce-href=\"http://www.usgs.gov/core_science_systems/csas/index.html\">http://www.usgs.gov/core_science_systems/<br>csas/index.html </a><br><a href=\"http://gapanalysis.usgs.gov/\" data-mce-href=\"http://gapanalysis.usgs.gov/\">http://gapanalysis.usgs.gov/</a><br></p>","publishedDate":"2013-11-12","revisedDate":"2016-08-29","noUsgsAuthors":false,"publicationDate":"2013-11-12","publicationStatus":"PW","scienceBaseUri":"53cd639ee4b0b290850feebe","contributors":{"authors":[{"text":"Gergely, Kevin J. 0000-0002-4379-2189 gergely@usgs.gov","orcid":"https://orcid.org/0000-0002-4379-2189","contributorId":2706,"corporation":false,"usgs":true,"family":"Gergely","given":"Kevin","email":"gergely@usgs.gov","middleInitial":"J.","affiliations":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":true,"id":486132,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McKerrow, Alexa 0000-0002-8312-2905 amckerrow@usgs.gov","orcid":"https://orcid.org/0000-0002-8312-2905","contributorId":4542,"corporation":false,"usgs":false,"family":"McKerrow","given":"Alexa","email":"amckerrow@usgs.gov","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":486133,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70049043,"text":"sir20135159 - 2013 - Simulation of climate-change effects on streamflow, lake water budgets, and stream temperature using GSFLOW and SNTEMP, Trout Lake Watershed, Wisconsin","interactions":[],"lastModifiedDate":"2013-11-12T09:35:51","indexId":"sir20135159","displayToPublicDate":"2013-11-12T09:28:00","publicationYear":"2013","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":"2013-5159","title":"Simulation of climate-change effects on streamflow, lake water budgets, and stream temperature using GSFLOW and SNTEMP, Trout Lake Watershed, Wisconsin","docAbstract":"Although groundwater and surface water are considered a single resource, historically hydrologic simulations have not accounted for feedback loops between the groundwater system and other hydrologic processes. These feedbacks include timing and rates of evapotranspiration, surface runoff, soil-zone flow, and interactions with the groundwater system. Simulations that iteratively couple the surface-water and groundwater systems, however, are characterized by long run times and calibration challenges. In this study, calibrated, uncoupled transient surface-water and steady-state groundwater models were used to construct one coupled transient groundwater/surface-water model for the Trout Lake Watershed in north-central Wisconsin, USA. The computer code GSFLOW (Ground-water/Surface-water FLOW) was used to simulate the coupled hydrologic system; a surface-water model represented hydrologic processes in the atmosphere, at land surface, and within the soil-zone, and a groundwater-flow model represented the unsaturated zone, saturated zone, stream, and lake budgets. The coupled GSFLOW model was calibrated by using heads, streamflows, lake levels, actual evapotranspiration rates, solar radiation, and snowpack measurements collected during water years 1998–2007; calibration was performed by using advanced features present in the PEST parameter estimation software suite.\n\nSimulated streamflows from the calibrated GSFLOW model and other basin characteristics were used as input to the one-dimensional SNTEMP (Stream-Network TEMPerature) model to simulate daily stream temperature in selected tributaries in the watershed. The temperature model was calibrated to high-resolution stream temperature time-series data measured in 2002. The calibrated GSFLOW and SNTEMP models were then used to simulate effects of potential climate change for the period extending to the year 2100. An ensemble of climate models and emission scenarios was evaluated. Downscaled climate drivers for the period 2010–2100 showed increases in maximum and minimum temperature over the scenario period. Scenarios of future precipitation did not show a monotonic trend like temperature. Uncertainty in the climate drivers increased over time for both temperature and precipitation.\n\nSeparate calibration of the uncoupled groundwater and surface-water models did not provide a representative initial parameter set for coupled model calibration. A sequentially linked calibration, in which the uncoupled models were linked by means of utility software, provided a starting parameter set suitable for coupled model calibration. Even with sequentially linked calibration, however, transmissivity of the lower part of the aquifer required further adjustment during coupled model calibration to attain reasonable parameter values for evaporation rates off a small seepage lake (a lake with no appreciable surface-water outlets) with a long history of study. The resulting coupled model was well calibrated to most types of observed time-series data used for calibration. Daily stream temperatures measured during 2002 were successfully simulated with SNTEMP; the model fit was acceptable for a range of groundwater inflow rates into the streams.\n\nForecasts of potential climate change scenarios showed growing season length increasing by weeks, and both potential and actual evapotranspiration rates increasing appreciably, in response to increasing air temperature. Simulated actual evapotranspiration rates increased less than simulated potential evapotranspiration rates as a result of water limitation in the root zone during the summer high-evapotranspiration period. The hydrologic-system response to climate change was characterized by a reduction in the importance of the snow-melt pulse and an increase in the importance of fall and winter groundwater recharge. The less dynamic hydrologic regime is likely to result in drier soil conditions in rainfed wetlands and uplands, in contrast to less drying in groundwater-fed systems. Seepage lakes showed larger forecast stage declines related to climate change than did drainage lakes (lakes with outlet streams). Seepage lakes higher in the watershed (nearer to groundwater divides) had less groundwater inflow and thus had larger forecast declines in lake stage; however, ground-water inflow to seepage lakes in general tended to increase as a fraction of the lake budgets with lake-stage decline because inward hydraulic gradients increased. Drainage lakes were characterized by less simulated stage decline as reductions in outlet streamflow of set losses to other water flows. Net groundwater inflow tended to decrease in drainage lakes over the scenario period.\n\nSimulated stream temperatures increased appreciably with climate change. The estimated increase in annual average temperature ranged from approximately 1 to 2 degrees Celsius by 2100 in the stream characterized by a high groundwater inflow rate and 2 to 3 degrees Celsius in the stream with a lower rate. The climate drivers used for the climate-change scenarios had appreciable variation between the General Circulation Model and emission scenario selected; this uncertainty was reflected in hydrologic flow and temperature model results. Thus, as with all forecasts of this type, the results are best considered to approximate potential outcomes of climate change.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135159","collaboration":"Groundwater Resources Program; Climate and Land Use Change Research & Development","usgsCitation":"Hunt, R.J., Walker, J.F., Selbig, W.R., Westenbroek, S.M., and Regan, R.S., 2013, Simulation of climate-change effects on streamflow, lake water budgets, and stream temperature using GSFLOW and SNTEMP, Trout Lake Watershed, Wisconsin: U.S. Geological Survey Scientific Investigations Report 2013-5159, vi, 118 p., https://doi.org/10.3133/sir20135159.","productDescription":"vi, 118 p.","numberOfPages":"128","temporalStart":"1998-01-01","temporalEnd":"2007-12-31","ipdsId":"IP-050362","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":278998,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135159.jpg"},{"id":278996,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5159/"},{"id":278997,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5159/pdf/sir2013-5159.pdf"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Trout Lake Watershed","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -89.733333,45.133333 ], [ -89.733333,46.133333 ], [ -89.533333,46.133333 ], [ -89.533333,45.133333 ], [ -89.733333,45.133333 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52834e08e4b047efbbb47bd3","contributors":{"authors":[{"text":"Hunt, Randall J. 0000-0001-6465-9304 rjhunt@usgs.gov","orcid":"https://orcid.org/0000-0001-6465-9304","contributorId":1129,"corporation":false,"usgs":true,"family":"Hunt","given":"Randall","email":"rjhunt@usgs.gov","middleInitial":"J.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":486067,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Walker, John F. jfwalker@usgs.gov","contributorId":1081,"corporation":false,"usgs":true,"family":"Walker","given":"John","email":"jfwalker@usgs.gov","middleInitial":"F.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":486066,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Selbig, William R. 0000-0003-1403-8280 wrselbig@usgs.gov","orcid":"https://orcid.org/0000-0003-1403-8280","contributorId":877,"corporation":false,"usgs":true,"family":"Selbig","given":"William","email":"wrselbig@usgs.gov","middleInitial":"R.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":486065,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Westenbroek, Stephen M. 0000-0002-6284-8643 smwesten@usgs.gov","orcid":"https://orcid.org/0000-0002-6284-8643","contributorId":2210,"corporation":false,"usgs":true,"family":"Westenbroek","given":"Stephen","email":"smwesten@usgs.gov","middleInitial":"M.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":486068,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Regan, R. Steve 0000-0003-4803-8596 rsregan@usgs.gov","orcid":"https://orcid.org/0000-0003-4803-8596","contributorId":2633,"corporation":false,"usgs":true,"family":"Regan","given":"R.","email":"rsregan@usgs.gov","middleInitial":"Steve","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":false,"id":486069,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70049066,"text":"ds709Z - 2013 - Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Kandahar mineral district in Afghanistan","interactions":[{"subject":{"id":70049066,"text":"ds709Z - 2013 - Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Kandahar mineral district in Afghanistan","indexId":"ds709Z","publicationYear":"2013","noYear":false,"chapter":"Z","title":"Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Kandahar mineral district in Afghanistan"},"predicate":"IS_PART_OF","object":{"id":70040370,"text":"ds709 - 2012 - Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan","indexId":"ds709","publicationYear":"2012","noYear":false,"title":"Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan"},"id":1}],"isPartOf":{"id":70040370,"text":"ds709 - 2012 - Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan","indexId":"ds709","publicationYear":"2012","noYear":false,"title":"Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan"},"lastModifiedDate":"2022-12-13T16:47:32.091965","indexId":"ds709Z","displayToPublicDate":"2013-11-11T13:21:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"709","chapter":"Z","title":"Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Kandahar mineral district in Afghanistan","docAbstract":"The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Kandahar mineral district, which has bauxite deposits.\n\nALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA,2006,2007,2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. \n\nThe selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar- elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. Therefore, it was necessary to (1) register the 10-m AVNIR multispectral imagery to a well-controlled Landsat image base, (2) mosaic the individual multispectral images into a single image of the entire area of interest, (3) register each panchromatic image to the registered multispectral image base, and (4) mosaic the individual panchromatic images into a single image of the entire area of interest. The two image- registration steps were facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative- reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band's picture element based on the digital values of all picture elements within a 500-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area- enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands).\n\nAll image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area's local zone (42 for Kandahar) and the WGS84 datum. The final image mosaics were subdivided into eight overlapping tiles or quadrants because of the large size of the target area. The eight image tiles (or quadrants) for the Kandahar area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image. Within the Kandahar study area, two subareas were designated for detailed field investigations (that is, the Obatu-Shela and Sekhab-Zamto Kalay subareas); these subareas were extracted from the area's image mosaic and are provided as separate embedded geotiff images.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan (DS 709)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds709Z","collaboration":"Prepared in cooperation with the U.S. Department of Defense <a href=\"http://tfbso.defense.gov/www/\" target=\"_blank\">Task Force for Business and Stability Operations</a> and the <a href=\"http://www.bgs.ac.uk/AfghanMinerals/\" target=\"_blank\">Afghanistan Geological Survey</a>.","usgsCitation":"Davis, P.A., 2013, Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Kandahar mineral district in Afghanistan: U.S. Geological Survey Data Series 709, Readme; 2 maps: 69.11 x 73.07 inches and 11 x 8.5 inches; 20 Image Files; 20 Metadata Files; 1 Shapefile, https://doi.org/10.3133/ds709Z.","productDescription":"Readme; 2 maps: 69.11 x 73.07 inches and 11 x 8.5 inches; 20 Image Files; 20 Metadata Files; 1 Shapefile","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-051558","costCenters":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"links":[{"id":278986,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds709z.jpg"},{"id":278985,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/709/z/"},{"id":278990,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/z/index_maps/Kandahar_Area-of-Interest_Index_Map.pdf"},{"id":278992,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/ds/709/z/metadata/metadata.html"},{"id":278994,"type":{"id":14,"text":"Image"},"url":"https://pubs.usgs.gov/ds/709/z/image_files/image_files.html"},{"id":278989,"rank":1,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/ds/709/z/1_readme.txt"},{"id":278991,"rank":1,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/z/index_maps/Kandahar_Image_Index_Map.pdf"},{"id":278995,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/709/z/index_maps/index_maps.html"},{"id":278993,"rank":1,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/709/z/shapefiles/shapefiles.html"}],"country":"Afghanistan","otherGeospatial":"Kandahar Mineral District","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 65.416667,31.0 ], [ 65.416667,32.75 ], [ 65.75,32.75 ], [ 65.75,31.0 ], [ 65.416667,31.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5281fc5ee4b08f1425d63da1","contributors":{"authors":[{"text":"Davis, Philip A. pdavis@usgs.gov","contributorId":692,"corporation":false,"usgs":true,"family":"Davis","given":"Philip","email":"pdavis@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":486100,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70048852,"text":"ds769 - 2013 - Topobathymetric model of Mobile Bay, Alabama","interactions":[],"lastModifiedDate":"2017-03-27T15:27:07","indexId":"ds769","displayToPublicDate":"2013-11-08T11:35:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"769","title":"Topobathymetric model of Mobile Bay, Alabama","docAbstract":"Topobathymetric Digital Elevation Models (DEMs) are a merged rendering of both topography (land elevation) and bathymetry (water depth) that provides a seamless elevation product useful for inundation mapping, as well as for other earth science applications, such as the development of sediment-transport, sea-level rise, and storm-surge models. This 1/9-arc-second (approximately 3 meters) resolution model of Mobile Bay, Alabama was developed using multiple topographic and bathymetric datasets, collected on different dates. The topographic data were obtained primarily from the U.S. Geological Survey (USGS) National Elevation Dataset (NED) (http://ned.usgs.gov/) at 1/9-arc-second resolution; USGS Experimental Advanced Airborne Research Lidar (EAARL) data (2 meters) (http://pubs.usgs.gov/ds/400/); and topographic lidar data (2 meters) and Compact Hydrographic Airborne Rapid Total Survey (CHARTS) lidar data (2 meters) from the U.S. Army Corps of Engineers (USACE) (http://www.csc.noaa.gov/digitalcoast/data/coastallidar/). Bathymetry was derived from digital soundings obtained from the National Oceanic and Atmospheric Administration’s (NOAA) National Geophysical Data Center (NGDC) (http://www.ngdc.noaa.gov/mgg/geodas/geodas.html) and from water-penetrating lidar sources, such as EAARL and CHARTS.\n\nMobile Bay is ecologically important as it is the fourth largest estuary in the United States. The Mobile and Tensaw Rivers drain into the bay at the northern end with the bay emptying into the Gulf of Mexico at the southern end. Dauphin Island (a barrier island) and the Fort Morgan Peninsula form the mouth of Mobile Bay. Mobile Bay is 31 miles (50 kilometers) long by a maximum width of 24 miles (39 kilometers) with a total area of 413 square miles (1,070 square kilometers).\n\nThe vertical datum of the Mobile Bay topobathymetric model is the North American Vertical Datum of 1988 (NAVD 88). All the topographic datasets were originally referenced to NAVD 88 and no transformations were made to these input data. The NGDC hydrographic, multibeam, and trackline surveys were transformed from mean low water (MLW) or mean lower low water (MLLW) to NAVD 88 using VDatum (http://vdatum.noaa.gov). VDatum is a tool developed by the National Geodetic Survey (NGS) that performs transformations among tidal, ellipsoid-based, geoid-based, and orthometric datums using calibrated hydrodynamic models. The vertical accuracy of the input topographic data varied depending on the input source. Because the input elevation data were derived primarily from lidar, the vertical accuracy ranges from 6 to 20 centimeters in root mean square error (RMSE).\n\nhe horizontal datum of the Mobile Bay topobathymetric model is the North American Datum of 1983 (NAD 83), geographic coordinates. All the topographic and bathymetric datasets were originally referenced to NAD 83, and no transformations were made to the input data. The bathymetric surveys were downloaded referenced to NAD 83 geographic, and therefore no horizontal transformations were required. The topbathymetric model of Mobile Bay and detailed metadata can be obtained from the USGS Web sites: http://nationalmap.gov/.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds769","usgsCitation":"Danielson, J.J., Brock, J., Howard, D., Gesch, D.B., Bonisteel-Cormier, J.M., and Travers, L.J., 2013, Topobathymetric model of Mobile Bay, Alabama: U.S. Geological Survey Data Series 769, 6 Plates: 38.17 x 33.59 inches; Downloads Directory, https://doi.org/10.3133/ds769.","productDescription":"6 Plates: 38.17 x 33.59 inches; Downloads Directory","ipdsId":"IP-038535","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":278975,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds769.gif"},{"id":278892,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/769/"},{"id":278972,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/769/pdf/mapsheets/ds769_nw-mobilebay-mapsheet.pdf","text":"Sheet 1: Topobathymetric Model of Mobile Bay, Alabama"},{"id":278969,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/769/pdf/mapsheets/ds769_5-SCtr_Mobile_Bay_mapsheet-opt-Aug_12.pdf","text":"Sheet 5: Topobathymetric Model of Mobile Bay, Alabama"},{"id":278970,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/769/pdf/mapsheets/ds769_6-SE_Mobile_Bay_mapsheet-opt-Aug_12.pdf","text":"Sheet 6: Topobathymetric Model of Mobile Bay, Alabama"},{"id":278968,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/769/pdf/mapsheets/ds769_4-SW_Mobile_Bay_mapsheet-opt-Aug_12.pdf","text":"Sheet 4: Topobathymetric Model of Mobile Bay, Alabama"},{"id":278971,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/769/pdf/mapsheets/ds769_nctr-mobilebay-mapsheet.pdf","text":"Sheet 2: Topobathymetric Model of Mobile Bay, Alabama"},{"id":278973,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/769/pdf/mapsheets/ds769_3-NE_Mobile_Bay_mapsheet-opt-Aug_12.pdf","text":"Sheet 3: Topobathymetric Model of Mobile Bay, Alabama"},{"id":278974,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/769/Downloads/"}],"country":"United States","state":"Alabama","otherGeospatial":"Mobile Bay","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -88.230932,30.203506 ], [ -88.230932,30.858225 ], [ -87.80086,30.858225 ], [ -87.80086,30.203506 ], [ -88.230932,30.203506 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"527e0805e4b02d2057dcf1be","contributors":{"authors":[{"text":"Danielson, Jeffrey J. 0000-0003-0907-034X daniels@usgs.gov","orcid":"https://orcid.org/0000-0003-0907-034X","contributorId":3996,"corporation":false,"usgs":true,"family":"Danielson","given":"Jeffrey","email":"daniels@usgs.gov","middleInitial":"J.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":485742,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brock, John 0000-0002-5289-9332 jbrock@usgs.gov","orcid":"https://orcid.org/0000-0002-5289-9332","contributorId":2261,"corporation":false,"usgs":true,"family":"Brock","given":"John","email":"jbrock@usgs.gov","affiliations":[{"id":5061,"text":"National Cooperative Geologic Mapping and Landslide Hazards","active":true,"usgs":true}],"preferred":true,"id":485739,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Howard, Daniel M. 0000-0002-7563-7538","orcid":"https://orcid.org/0000-0002-7563-7538","contributorId":97795,"corporation":false,"usgs":true,"family":"Howard","given":"Daniel M.","affiliations":[],"preferred":false,"id":485744,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gesch, Dean B. 0000-0002-8992-4933 gesch@usgs.gov","orcid":"https://orcid.org/0000-0002-8992-4933","contributorId":2956,"corporation":false,"usgs":true,"family":"Gesch","given":"Dean","email":"gesch@usgs.gov","middleInitial":"B.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":485740,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bonisteel-Cormier, Jamie M.","contributorId":18085,"corporation":false,"usgs":true,"family":"Bonisteel-Cormier","given":"Jamie","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":485743,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Travers, Laurinda J. ltravers@usgs.gov","contributorId":3002,"corporation":false,"usgs":true,"family":"Travers","given":"Laurinda","email":"ltravers@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":true,"id":485741,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
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