{"pageNumber":"641","pageRowStart":"16000","pageSize":"25","recordCount":40807,"records":[{"id":70047810,"text":"70047810 - 2013 - Forecasting the effects of coastal protection and restoration projects on wetland morphology in coastal Louisiana under multiple environmental uncertainty scenarios","interactions":[],"lastModifiedDate":"2019-06-05T14:53:28","indexId":"70047810","displayToPublicDate":"2013-08-23T14:13:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2220,"text":"Journal of Coastal Research","active":true,"publicationSubtype":{"id":10}},"title":"Forecasting the effects of coastal protection and restoration projects on wetland morphology in coastal Louisiana under multiple environmental uncertainty scenarios","docAbstract":"Few landscape scale models have assessed the effects of coastal protection and restoration projects on wetland morphology while taking into account important uncertainties in environmental factors such as sea-level rise (SLR) and subsidence. In support of Louisiana's 2012 Coastal Master Plan, we developed a spatially explicit wetland morphology model and coupled it with other predictive models. The model is capable of predicting effects of protection and restoration projects on wetland area, landscape configuration, surface elevation, and soil organic carbon (SOC) storage under multiple environmental uncertainty scenarios. These uncertainty scenarios included variability in parameters such as eustatic SLR (ESLR), subsidence rate, and Mississippi River discharge. Models were run for a 2010–2060 simulation period. Model results suggest that under a “future-without-action” condition (FWOA), coastal Louisiana is at risk of losing between 2118 and 4677 km<sup>2</sup> of land over the next 50 years, but with protection and restoration projects proposed in the Master Plan, between 40% and 75% of that loss could be mitigated. Moreover, model results indicate that under a FWOA condition, SOC storage (to a depth of 1 m) could decrease by between 108 and 250 million metric tons, a loss of 12% to 30% of the total coastwide SOC, but with the Master Plan implemented, between 35% and 74% of the SOC loss could be offset. Long-term maintenance of project effects was best attained in areas of low SLR and subsidence, with a sediment source to support marsh accretion. Our findings suggest that despite the efficacy of restoration projects in mitigating losses in certain areas, net loss of wetlands in coastal Louisiana is likely to continue. Model results suggest certain areas may eventually be lost regardless of proposed restoration investment, and, as such, other techniques and strategies of adaptation may have to be utilized in these areas.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Coastal Research","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Coastal Restoration and Research Foundation","doi":"10.2112/SI_67_3","usgsCitation":"Couvillion, B.R., Steyer, G.D., Wang, H., Beck, H.J., and Rybczyk, J.M., 2013, Forecasting the effects of coastal protection and restoration projects on wetland morphology in coastal Louisiana under multiple environmental uncertainty scenarios: Journal of Coastal Research, p. 29-50, https://doi.org/10.2112/SI_67_3.","productDescription":"23 p.","startPage":"29","endPage":"50","numberOfPages":"23","ipdsId":"IP-042243","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"links":[{"id":276965,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.2112/SI_67_3"},{"id":276968,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -94.0434,28.9254 ], [ -94.0434,30.8191 ], [ -88.8162,30.8191 ], [ -88.8162,28.9254 ], [ -94.0434,28.9254 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5218765ee4b0e27b926cc665","contributors":{"authors":[{"text":"Couvillion, Brady R. 0000-0001-5323-1687 couvillionb@usgs.gov","orcid":"https://orcid.org/0000-0001-5323-1687","contributorId":3829,"corporation":false,"usgs":true,"family":"Couvillion","given":"Brady","email":"couvillionb@usgs.gov","middleInitial":"R.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":false,"id":483020,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Steyer, Gregory D. 0000-0001-7231-0110 steyerg@usgs.gov","orcid":"https://orcid.org/0000-0001-7231-0110","contributorId":2856,"corporation":false,"usgs":true,"family":"Steyer","given":"Gregory","email":"steyerg@usgs.gov","middleInitial":"D.","affiliations":[{"id":5064,"text":"Southeast Regional Director's Office","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":5062,"text":"Office of the Chief Scientist for Ecosystems","active":true,"usgs":true}],"preferred":true,"id":483019,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wang, Hongqing 0000-0002-2977-7732 wangh@usgs.gov","orcid":"https://orcid.org/0000-0002-2977-7732","contributorId":4421,"corporation":false,"usgs":true,"family":"Wang","given":"Hongqing","email":"wangh@usgs.gov","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":false,"id":483021,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Beck, Holly J. 0000-0002-0567-9329 hbeck@usgs.gov","orcid":"https://orcid.org/0000-0002-0567-9329","contributorId":5454,"corporation":false,"usgs":true,"family":"Beck","given":"Holly","email":"hbeck@usgs.gov","middleInitial":"J.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":483022,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rybczyk, John M.","contributorId":89794,"corporation":false,"usgs":true,"family":"Rybczyk","given":"John","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":483023,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70047776,"text":"fs20133053 - 2013 - The 3D Elevation Program: summary for Idaho","interactions":[],"lastModifiedDate":"2016-08-17T16:10:36","indexId":"fs20133053","displayToPublicDate":"2013-08-23T08:33:00","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":"2013-3053","title":"The 3D Elevation Program: summary for Idaho","docAbstract":"<p>Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the State of Idaho, elevation data are critical for agriculture and precision farming, natural resources conservation, infrastructure and construction management, geologic resource assessment and hazard mitigation, flood risk management, forest resources management, and other business uses. Today, high-quality light detection and ranging (lidar) data are the sources for creating elevation models and other elevation datasets. Federal, State, and local agencies work in partnership to (1) replace data, on a national basis, that are (on average) 30 years old and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of State and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data. The new 3D Elevation Program (3DEP) initiative, managed by the U.S. Geological Survey (USGS), responds to the growing need for high-quality topographic data and a wide range of other three-dimensional representations of the Nation&rsquo;s natural and constructed features. The Idaho LiDAR Consortium provides statewide collaboration and data sharing mechanisms that can be used as a resource by State and Federal partners implementing the 3DEP initiative.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20133053","usgsCitation":"Carswell, W., 2013, The 3D Elevation Program: summary for Idaho: U.S. Geological Survey Fact Sheet 2013-3053, 2 p., https://doi.org/10.3133/fs20133053.","productDescription":"2 p.","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"links":[{"id":276928,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20133053.gif"},{"id":276926,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2013/3053/"},{"id":276927,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2013/3053/pdf/fs2013-3053.pdf","text":"Report","size":"225 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,{"id":70047769,"text":"fs20133052 - 2013 - The 3D Elevation Program: summary for Virginia","interactions":[],"lastModifiedDate":"2016-08-17T16:11:45","indexId":"fs20133052","displayToPublicDate":"2013-08-22T14:41:00","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":"2013-3052","title":"The 3D Elevation Program: summary for Virginia","docAbstract":"<p>Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the Commonwealth of Virginia, elevation data are critical for urban and regional planning, natural resources conservation, flood risk management, agriculture and precision farming, resource mining, infrastructure and construction management, and other business uses. Today, high-quality light detection and ranging (lidar) data are the sources for creating elevation models and other elevation datasets. Federal, State, and local agencies work in partnership to (1) replace data, on a national basis, that are (on average) 30 years old and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of State and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data. The new 3D Elevation Program (3DEP) initiative, managed by the U.S. Geological Survey (USGS), responds to the growing need for high-quality topographic data and a wide range of other three-dimensional representations of the Nation&rsquo;s natural and constructed features.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20133052","usgsCitation":"Carswell, W., 2013, The 3D Elevation Program: summary for Virginia: U.S. Geological Survey Fact Sheet 2013-3052, 2 p., https://doi.org/10.3133/fs20133052.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"links":[{"id":276909,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20133052.jpg"},{"id":276907,"type":{"id":15,"text":"Index 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,{"id":70047766,"text":"sir20135089 - 2013 - Method to support Total Maximum Daily Load development using hydrologic alteration as a surrogate to address aquatic life impairment in New Jersey streams","interactions":[],"lastModifiedDate":"2018-11-01T12:06:18","indexId":"sir20135089","displayToPublicDate":"2013-08-22T13:36:00","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":"2013-5089","title":"Method to support Total Maximum Daily Load development using hydrologic alteration as a surrogate to address aquatic life impairment in New Jersey streams","docAbstract":"<p>More than 300 ambient monitoring sites in New Jersey have been identified by the New Jersey Department of Environmental Protection (NJDEP) in its integrated water-quality monitoring and assessment report (that is, the 305(b) Report on general water quality and 303(d) List of waters that do not support their designated uses) as being impaired with respect to aquatic life; however, no unambiguous stressors (for example, nutrients or bacteria) have been identified. Because of the indeterminate nature of the broad range of possible impairments, surrogate measures that more holistically encapsulate the full suite of potential environmental stressors need to be developed. Streamflow alteration resulting from anthropogenic changes in the landscape is one such surrogate. For example, increases in impervious surface cover (ISC) commonly cause increases in surface runoff, which can result in “flashy” hydrology and other changes in the stream corridor that are associated with streamflow alteration. The NJDEP has indicated that methodologies to support a hydrologically based Total Maximum Daily Load (hydro-TMDL) need to be developed in order to identify hydrologic targets that represent a minimal percent deviation from a baseline condition (“minimally altered”) as a surrogate measure to meet criteria in support of designated&nbsp;uses.</p><p>The primary objective of this study was to develop an applicable hydro-TMDL approach to address aquatic-life impairments associated with hydrologic alteration for New Jersey streams. The U.S. Geological Survey, in cooperation with the NJDEP, identified 51 non- to moderately impaired gaged streamflow sites in the Raritan River Basin for evaluation. Quantile regression (QR) analysis was used to compare flow and precipitation records and identify baseline hydrographs at 37 of these sites. At sites without an appropriately long period of record (POR) or where a baseline hydrograph could not be identified with QR, a rainfall-runoff model was used to develop simulated baseline hydrographs. The hydro-TMDL approach provided an opportunity to evaluate proportional differences in flow attributes between observed and baseline hydrographs and to develop complementary flow-ecology response relations at a subset of Raritan River Basin sites where available flow and ecological information&nbsp;overlapped.</p><p>The New Jersey Stream Classification Tool (NJSCT) was used to determine the stream class of all 51 study sites by using either an observed or a simulated baseline hydrograph. Two New Jersey stream classes (A and C) were evaluated to help characterize the unique hydrology of the Raritan River Basin. In general, class C streams (1.99–40.7&nbsp;square miles) had smaller drainage areas than class A streams (0.7–785&nbsp;square miles). Many of the non-impaired and moderately impaired class A and C streams in the Raritan River Basin were found to have significant hydrologic alteration as indicated by numerous flow values that fell outside the established 25th-to-75th- and the more conservative 40th-to-60th-percentile boundaries. However, percent deviations for the class C streams (defined as moderately stable streams with moderately high base-flow contributions) were, in general, much larger than those for the class A streams (defined as semiflashy streams characterized by moderately low base flow). The greater deviations for class C streams in the hydro-TMDL assessments likely resulted from comparisons that were based solely on simulated baseline hydrographs, which were developed without considering any anthropogenic influences in the basin. In contrast, comparisons for many of the class A streams were made by using an observed baseline, which already includes an implicit level of ISC and other human influences on the&nbsp;landscape.</p><p>By using the hydro-TMDL approach, numerous flow deviations were identified that were indicative of streams that are highly regulated by reservoirs or dams, streams that are affected by increasing amounts of surface runoff resulting from ISC, and streams that are affected by water abstraction (that is, groundwater or surface-water withdrawals used for agricultural and human supply). Eight of the reservoir- and (or) dam-affected sites showed flow deviations that are indicative of flow-managed systems. For example, indices that account for the timing and magnitude of high and low flows were often found to fall outside the 25th-to-75th-percentile range. In general, at regulated class C streams, annual summer low flows are arriving later and tend to be lower, and high flows are arriving earlier with higher magnitudes of longer duration. At class A streams, high and low flows are arriving later with an overall increase in discharge with respect to the prereservoir baseline&nbsp;conditions.</p><p>The drainage basins of eight of the study sites had large values of ISC (&gt;10 percent), most likely as a result of expanding urban development. In general, the magnitude and frequency of high flows at class A and C sites with high ISC are increasing and were commonly found to fall outside the 25th-to-75th-percentile range. Additionally, magnitudes of low flows are becoming lower and, although the timing of high flows was highly variable, low-flow events appeared to be arriving earlier than would be expected under normal low-flow conditions. Three of the study sites appeared to be affected by hydrologic changes associated with water abstraction. At these sites, the timing of flows appeared to be altered. For example, low flows tended to arrive earlier and high flows arrived later at two of the three sites. Additionally, the magnitude and duration of low flows were commonly less than the 25th-percentile value and the duration of high flows appeared to&nbsp;increase.</p><p>A reduced set of hydrologic and ecological variables was used to develop univariate and multivariate flow-ecology response models for the aquatic-invertebrate assemblage. Many hydrologic variables accounting for the duration, magnitude, frequency, and timing of flows were significantly correlated with ecological response. Multiple linear regression (MLR) models were developed to provide a more holistic evaluation of the combined effects of hydrologic alteration and to identify models with two or three hydrologic variables that account for a significant proportion of the variability in invertebrate-assemblage condition as represented by assemblage metric scores. MLR models, derived on the basis of hydrologic attributes, accounted for 35 to 75 percent of the variability in assemblage&nbsp;condition.</p><p>The hydro-TMDL method developed herein for non- to moderately impaired Raritan River Basin streams utilizes a “surrogate” approach in place of the traditional “pollutant of concern” approach commonly used for TMDL development. Managers can use the results obtained by using the hydro-TMDL method to offset the effects of impervious-surface runoff and altered streamflow and to implement measures designed to achieve the necessary load reductions for the “pollutant of concern” (that is, percentage deviations of stream-class-specific flow-index values outside the established 25th-to-75th-percentile range). In this case, such deviations could represent all or a subset of the altered flow indices that prevent the stream from meeting designated aquatic-life criteria. This hydro-TMDL uses a reference, or attainment stream approach for developing the TMDL endpoint. That is, either observed or simulated baseline hydrographs were selected as appropriate reference conditions on the basis of results of QR analysis and watershed modeling procedures, respectively. For any stream in the Raritan River Basin evaluated as part of this study, the hydro-TMDL can be expressed as the greatest amount of deviation in flow a stream can exhibit without violating the stream’s designated aquatic-life criteria. Use of this surrogate approach is appropriate because flows that fall outside the established percentile ranges are ultimately a function of many anthropogenic modifications of the landscape, including the amount of stormwater runoff generated from impervious surfaces within a given basin, the presence of manmade structures designed to retain or divert water, the magnitude of ground- and surface-water abstraction, and the presence of water-supply processes implemented to support human needs. In addition, the stream-type-specific flow indices used as the basis for the hydro-TMDL approach are useful for representing the hydrologic conditions of class A and C streams/basins because they incorporate the full spectrum of flow conditions (very low to very high) that occur in the stream system over a long period of time, as well as those flow properties that change as a result of seasonal&nbsp;variation.</p><p>Ultimately, an estimate of the maximum percentage flow reduction that could be allowed will be needed to address the aquatic-life impairments in many of the study streams in the Raritan River Basin and will be necessary for identifying appropriate target flow conditions for hydro-TMDL implementation. As described in this report, a target flow value equal to the 25th- or 75th-percentile flow rate could be selected as the point useful for setting specific hydrologic targets. This selection, however, is a management decision that could vary depending on the designated use of the stream or other regulatory factors (for example, water-supply protection, trout production, antidegradation policies, or special protection designations). In New Jersey streams where no unambiguous stressors can be identified, State monitoring agencies, such as the NJDEP, could choose to require the implementation of a flow-based TMDL that not only supports designated uses, but meets the regulatory requirements under the Clean Water Act, and represents a balance between water supply intended to meet human needs and the conservation of ecosystem&nbsp;integrity.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135089","collaboration":"Prepared in cooperation with the New Jersey Department of Environmental Protection","usgsCitation":"Kennen, J., Riskin, M.L., Reilly, P.A., and Colarullo, S.J., 2013, Method to support Total Maximum Daily Load development using hydrologic alteration as a surrogate to address aquatic life impairment in New Jersey streams: U.S. Geological Survey Scientific Investigations Report 2013-5089, viii, 86 p., https://doi.org/10.3133/sir20135089.","productDescription":"viii, 86 p.","numberOfPages":"98","onlineOnly":"Y","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":276906,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135089.png"},{"id":276904,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5089/","text":"Index Page","linkFileType":{"id":5,"text":"html"}},{"id":276905,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5089/pdf/sir2013-5089.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"New Jersey","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -75.25,\n              40\n            ],\n            [\n              -74.25,\n              40\n            ],\n            [\n              -74.25,\n              41\n            ],\n            [\n              -75.25,\n              41\n            ],\n            [\n              -75.25,\n              40\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"521724dae4b043bae8d2e5a9","contributors":{"authors":[{"text":"Kennen, Jonathan G. 0000-0002-5426-4445 jgkennen@usgs.gov","orcid":"https://orcid.org/0000-0002-5426-4445","contributorId":574,"corporation":false,"usgs":true,"family":"Kennen","given":"Jonathan G.","email":"jgkennen@usgs.gov","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":482925,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Riskin, Melissa L. 0000-0001-6499-3775 mriskin@usgs.gov","orcid":"https://orcid.org/0000-0001-6499-3775","contributorId":654,"corporation":false,"usgs":true,"family":"Riskin","given":"Melissa","email":"mriskin@usgs.gov","middleInitial":"L.","affiliations":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":482928,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reilly, Pamela A. 0000-0002-2937-4490 jankowsk@usgs.gov","orcid":"https://orcid.org/0000-0002-2937-4490","contributorId":653,"corporation":false,"usgs":true,"family":"Reilly","given":"Pamela","email":"jankowsk@usgs.gov","middleInitial":"A.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":482927,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Colarullo, Susan J. 0000-0003-4504-0068 colarull@usgs.gov","orcid":"https://orcid.org/0000-0003-4504-0068","contributorId":652,"corporation":false,"usgs":true,"family":"Colarullo","given":"Susan","email":"colarull@usgs.gov","middleInitial":"J.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":482926,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70047763,"text":"sir20135091 - 2013 - A deposit model for magmatic iron-titanium-oxide deposits related to Proterozoic massif anorthosite plutonic suites","interactions":[{"subject":{"id":70047763,"text":"sir20135091 - 2013 - A deposit model for magmatic iron-titanium-oxide deposits related to Proterozoic massif anorthosite plutonic suites","indexId":"sir20135091","publicationYear":"2013","noYear":false,"title":"A deposit model for magmatic iron-titanium-oxide deposits related to Proterozoic massif anorthosite plutonic suites"},"predicate":"SUPERSEDED_BY","object":{"id":70116317,"text":"sir20105070K - 2013 - A deposit model for magmatic iron-titanium-oxide deposits related to Proterozoic massif anorthosite plutonic suite","indexId":"sir20105070K","publicationYear":"2013","noYear":false,"chapter":"K","title":"A deposit model for magmatic iron-titanium-oxide deposits related to Proterozoic massif anorthosite plutonic suite"},"id":1}],"supersededBy":{"id":70116317,"text":"sir20105070K - 2013 - A deposit model for magmatic iron-titanium-oxide deposits related to Proterozoic massif anorthosite plutonic suite","indexId":"sir20105070K","publicationYear":"2013","noYear":false,"title":"A deposit model for magmatic iron-titanium-oxide deposits related to Proterozoic massif anorthosite plutonic suite"},"lastModifiedDate":"2018-11-26T09:35:39","indexId":"sir20135091","displayToPublicDate":"2013-08-22T11:55:07","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":"2013-5091","title":"A deposit model for magmatic iron-titanium-oxide deposits related to Proterozoic massif anorthosite plutonic suites","docAbstract":"This descriptive model for magmatic iron-titanium-oxide (Fe-Ti-oxide) deposits hosted by Proterozoic age massif-type anorthosite and related rock types presents their geological, mineralogical, geochemical, and geoenvironmental attributes. Although these Proterozoic rocks are found worldwide, the majority of known deposits are found within exposed rocks of the Grenville Province, stretching from southwestern United States through eastern Canada; its extension into Norway is termed the Rogaland Anorthosite Province. This type of Fe-Ti-oxide deposit dominated by ilmenite rarely contains more than 300 million tons of ore, with between 10- to 45-percent titanium dioxide (TiO<sub>2</sub>), 32- to 45-percent iron oxide (FeO), and less than 0.2-percent vanadium (V).  The origin of these typically discordant ore deposits remains as enigmatic as the magmatic evolution of their host rocks. The deposits clearly have a magmatic origin, hosted by an age-constrained unique suite of rocks that likely are the consequence of a particular combination of tectonic circumstances, rather than any a priori temporal control. Principal ore minerals are ilmenite and hemo-ilmenite (ilmenite with extensive hematite exsolution lamellae); occurrences of titanomagnetite, magnetite, and apatite that are related to this deposit type are currently of less economic importance. Ore-mineral paragenesis is somewhat obscured by complicated solid solution and oxidation behavior within the Fe-Ti-oxide system. Anorthosite suites hosting these deposits require an extensive history of voluminous plagioclase crystallization to develop plagioclase-melt diapirs with entrained Fe-Ti-rich melt rising from the base of the lithosphere to mid- and upper-crustal levels. Timing and style of oxide mineralization are related to magmatic and dynamic evolution of these diapiric systems and to development and movement of oxide cumulates and related melts.  Active mines have developed large open pits with extensive waste-rock piles, but because of the nature of the ore and waste rock, the major environmental impacts documented at the mine sites are reported to be waste disposal issues and somewhat degraded water quality.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135091","usgsCitation":"Woodruff, L.G., Nicholson, S.W., and Fey, D.L., 2013, A deposit model for magmatic iron-titanium-oxide deposits related to Proterozoic massif anorthosite plutonic suites: U.S. Geological Survey Scientific Investigations Report 2013-5091, vii, 47 p., https://doi.org/10.3133/sir20135091.","productDescription":"vii, 47 p.","numberOfPages":"58","onlineOnly":"Y","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":276898,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135091.gif"},{"id":276897,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5091/"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"521724cfe4b043bae8d2e59d","contributors":{"authors":[{"text":"Woodruff, Laurel G. 0000-0002-2514-9923 woodruff@usgs.gov","orcid":"https://orcid.org/0000-0002-2514-9923","contributorId":2224,"corporation":false,"usgs":true,"family":"Woodruff","given":"Laurel","email":"woodruff@usgs.gov","middleInitial":"G.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":482920,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nicholson, Suzanne W. 0000-0002-9365-1894 swnich@usgs.gov","orcid":"https://orcid.org/0000-0002-9365-1894","contributorId":880,"corporation":false,"usgs":true,"family":"Nicholson","given":"Suzanne","email":"swnich@usgs.gov","middleInitial":"W.","affiliations":[],"preferred":true,"id":482919,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fey, David L. dfey@usgs.gov","contributorId":713,"corporation":false,"usgs":true,"family":"Fey","given":"David","email":"dfey@usgs.gov","middleInitial":"L.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":482918,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70047757,"text":"70047757 - 2013 - Hybrid modeling of spatial continuity for application to numerical inverse problems","interactions":[],"lastModifiedDate":"2013-08-22T10:02:03","indexId":"70047757","displayToPublicDate":"2013-08-22T09:56:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1551,"text":"Environmental Modelling and Software","active":true,"publicationSubtype":{"id":10}},"title":"Hybrid modeling of spatial continuity for application to numerical inverse problems","docAbstract":"A novel two-step modeling approach is presented to obtain optimal starting values and geostatistical constraints for numerical inverse problems otherwise characterized by spatially-limited field data. First, a type of unsupervised neural network, called the self-organizing map (SOM), is trained to recognize nonlinear relations among environmental variables (covariates) occurring at various scales. The values of these variables are then estimated at random locations across the model domain by iterative minimization of SOM topographic error vectors. Cross-validation is used to ensure unbiasedness and compute prediction uncertainty for select subsets of the data. Second, analytical functions are fit to experimental variograms derived from original plus resampled SOM estimates producing model variograms. Sequential Gaussian simulation is used to evaluate spatial uncertainty associated with the analytical functions and probable range for constraining variables. The hybrid modeling of spatial continuity is demonstrated using spatially-limited hydrologic measurements at different scales in Brazil: (1) physical soil properties (sand, silt, clay, hydraulic conductivity) in the 42 km<sup>2</sup> Vargem de Caldas basin; (2) well yield and electrical conductivity of groundwater in the 132 km<sup>2</sup> fractured crystalline aquifer; and (3) specific capacity, hydraulic head, and major ions in a 100,000 km<sup>2</sup> transboundary fractured-basalt aquifer. These results illustrate the benefits of exploiting nonlinear relations among sparse and disparate data sets for modeling spatial continuity, but the actual application of these spatial data to improve numerical inverse modeling requires testing.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Environmental Modelling and Software","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2013.01.009","usgsCitation":"Friedel, M.J., and Iwashita, F., 2013, Hybrid modeling of spatial continuity for application to numerical inverse problems: Environmental Modelling and Software, v. 43, p. 60-79, https://doi.org/10.1016/j.envsoft.2013.01.009.","productDescription":"20 p.","startPage":"60","endPage":"79","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":276885,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":276884,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.envsoft.2013.01.009"}],"volume":"43","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"521724dae4b043bae8d2e5a5","contributors":{"authors":[{"text":"Friedel, Michael J. 0000-0002-5060-3999 mfriedel@usgs.gov","orcid":"https://orcid.org/0000-0002-5060-3999","contributorId":595,"corporation":false,"usgs":true,"family":"Friedel","given":"Michael","email":"mfriedel@usgs.gov","middleInitial":"J.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":482903,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Iwashita, Fabio","contributorId":72287,"corporation":false,"usgs":true,"family":"Iwashita","given":"Fabio","email":"","affiliations":[],"preferred":false,"id":482904,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70047718,"text":"fs20133057 - 2013 - The 3D Elevation Program: summary for Washington","interactions":[],"lastModifiedDate":"2016-08-17T16:12:52","indexId":"fs20133057","displayToPublicDate":"2013-08-20T12:47:00","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":"2013-3057","title":"The 3D Elevation Program: summary for Washington","docAbstract":"<p>Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the State of Washington, elevation data are critical for natural resources conservation, agriculture and precision farming, infrastructure and construction management, flood risk management, geologic resource assessment and hazards mitigation, and other business uses. Today, high-density light detection and ranging (lidar) data are the primary sources for deriving elevation models and other datasets. Federal, State, Tribal, and local agencies work in partnership to (1) replace data that are older and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of State and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data.</p>\n<p>The National Enhanced Elevation Assessment evaluated multiple elevation data acquisition options to determine the optimal data quality and data replacement cycle relative to cost to meet the identified requirements of the user community. The evaluation demonstrated that lidar acquisition at quality level 2 for the conterminous United States and quality level 5 interferometric synthetic aperture radar (ifsar) data for Alaska with a 6- to 10-year acquisition cycle provided the highest benefit/cost ratios. The 3D Elevation Program (3DEP) initiative selected an 8-year acquisition cycle for the respective quality levels. 3DEP, managed by the U.S. Geological Survey, the Office of Management and Budget Circular A&ndash;16 lead agency for terrestrial elevation data, responds to the growing need for high-quality topographic data and a wide range of other 3D representations of the Nation&rsquo;s natural and constructed features.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20133057","usgsCitation":"Carswell, W., 2013, The 3D Elevation Program: summary for Washington (Originally posted August 20, 2013; Revised and reposted August 14, 2014, version 1.1): U.S. Geological Survey Fact Sheet 2013-3057, 2 p., https://doi.org/10.3133/fs20133057.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":423,"text":"National Geospatial 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 \"}}]}","edition":"Originally posted August 20, 2013; Revised and reposted August 14, 2014, version 1.1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"521481e2e4b06d85e08fb4cf","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":482797,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70047707,"text":"70047707 - 2013 - The 2011 Mw 7.1 Van (Eastern Turkey) earthquake","interactions":[],"lastModifiedDate":"2013-08-20T08:37:42","indexId":"70047707","displayToPublicDate":"2013-08-20T08:19:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2312,"text":"Journal of Geophysical Research","active":true,"publicationSubtype":{"id":10}},"title":"The 2011 Mw 7.1 Van (Eastern Turkey) earthquake","docAbstract":"We use interferometric synthetic aperture radar (InSAR), body wave seismology, satellite imagery, and field observations to constrain the fault parameters of the M<sub>w</sub> 7.1 2011 Van (Eastern Turkey) reverse-slip earthquake, in the Turkish-Iranian plateau. Distributed slip models from elastic dislocation modeling of the InSAR surface displacements from ENVISAT and COSMO-SkyMed interferograms indicate up to 9 m of reverse and oblique slip on a pair of en echelon NW 40 &deg;–54 &deg; dipping fault planes which have surface extensions projecting to just 10 km north of the city of Van. The slip remained buried and is relatively deep, with a centroid depth of 14 km, and the rupture reaching only within 8–9 km of the surface, consistent with the lack of significant ground rupture. The up-dip extension of this modeled WSW striking fault plane coincides with field observations of weak ground deformation seen on the western of the two fault segments and has a dip consistent with that seen at the surface in fault gouge exposed in Quaternary sediments. No significant coseismic slip is found in the upper 8 km of the crust above the main slip patches, except for a small region on the eastern segment potentially resulting from the M<sub>w</sub> 5.9 aftershock on the same day. We perform extensive resolution tests on the data to confirm the robustness of the observed slip deficit in the shallow crust. We resolve a steep gradient in displacement at the point where the planes of the two fault segments ends are inferred to abut at depth, possibly exerting some structural control on rupture extent.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Geophysical Research","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1002/jgrb.50117","usgsCitation":"Elliot, J., Copley, A.C., Holley, R., Scharer, K.M., and Parsons, B., 2013, The 2011 Mw 7.1 Van (Eastern Turkey) earthquake: Journal of Geophysical Research, v. 118, no. 4, p. 1619-1637, https://doi.org/10.1002/jgrb.50117.","productDescription":"19 p.","startPage":"1619","endPage":"1637","numberOfPages":"19","ipdsId":"IP-038911","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":276789,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":276788,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/jgrb.50117"}],"country":"Turkey","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 33.0,33.0 ], [ 33.0,44.0 ], [ 52.0,44.0 ], [ 52.0,33.0 ], [ 33.0,33.0 ] ] ] } } ] }","volume":"118","issue":"4","noUsgsAuthors":false,"publicationDate":"2013-04-04","publicationStatus":"PW","scienceBaseUri":"521481e2e4b06d85e08fb4cb","contributors":{"authors":[{"text":"Elliot, John R.","contributorId":26612,"corporation":false,"usgs":true,"family":"Elliot","given":"John R.","affiliations":[],"preferred":false,"id":482782,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Copley, Alex C.","contributorId":90630,"corporation":false,"usgs":true,"family":"Copley","given":"Alex","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":482785,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Holley, R.","contributorId":85874,"corporation":false,"usgs":true,"family":"Holley","given":"R.","email":"","affiliations":[],"preferred":false,"id":482784,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Scharer, Katherine M. 0000-0003-2811-2496 kscharer@usgs.gov","orcid":"https://orcid.org/0000-0003-2811-2496","contributorId":3385,"corporation":false,"usgs":true,"family":"Scharer","given":"Katherine","email":"kscharer@usgs.gov","middleInitial":"M.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":482781,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Parsons, Barry","contributorId":56966,"corporation":false,"usgs":true,"family":"Parsons","given":"Barry","affiliations":[],"preferred":false,"id":482783,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70047697,"text":"ofr20131190 - 2013 - Knowledge and understanding of dissolved solids in the Rio Grande–San Acacia, New Mexico, to Fort Quitman, Texas, and plan for future studies and monitoring","interactions":[],"lastModifiedDate":"2013-08-19T15:16:39","indexId":"ofr20131190","displayToPublicDate":"2013-08-19T15:02:00","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":"2013-1190","title":"Knowledge and understanding of dissolved solids in the Rio Grande–San Acacia, New Mexico, to Fort Quitman, Texas, and plan for future studies and monitoring","docAbstract":"Availability of water in the Rio Grande Basin has long been a primary concern for water-resource managers. The transport and delivery of water in the basin have been engineered by using reservoirs, irrigation canals and drains, and transmountain-water diversions to meet the agricultural, residential, and industrial demand. In contrast, despite the widespread recognition of critical water-quality problems, there have been minimal management efforts to improve water quality in the Rio Grande. Of greatest concern is salinization (concentration of dissolved solids approaching 1,000 mg/L), a water-quality problem that has been recognized and researched for more than 100 years because of the potential to limit both agricultural and municipal use. To address the issue of salinization, water-resource managers need to have a clear conceptual understanding of the sources of salinity and the factors that control storage and transport, identify critical knowledge gaps in this conceptual understanding, and develop a research plan to address these gaps and develop a salinity management program. In 2009, the U.S. Geological Survey (USGS) in cooperation with the U.S. Army Corps of Engineers (USACE), New Mexico Interstate Stream Commission (NMISC), and New Mexico Environment Department (NMED) initiated a project to summarize the current state of knowledge regarding the transport of dissolved solids in the Rio Grande between San Acacia, New Mexico, and Fort Quitman, Texas. The primary objective is to provide hydrologic information pertaining to the spatial and temporal variability present in the concentrations and loads of dissolved solids in the Rio Grande, the source-specific budget for the mass of dissolved solids transported along the Rio Grande, and the locations at which dissolved solids enter the Rio Grande. Dissolved-solids concentration data provide a good indicator of the general quality of surface water and provide information on the factors governing salinization within the Rio Grande study area. The pattern in dissolved-solids concentrations along the Rio Grande is one of increasing concentration with increasing distance downstream from Elephant Butte and Caballo Reservoirs. The concentration of dissolved solids in the Rio Grande doubles (approximately 500 to 1,000 mg/L) from below Elephant Butte Reservoir to El Paso and increases by more than a factor of 5 (approximately 500 to 3,200 mg/L) from below Elephant Butte Reservoir to Fort Quitman. Marked increases in the concentration of dissolved solids commonly coincide with contributions from agricultural drains, wastewater-treatment plants, regional groundwater, and upward-flowing saline groundwater.  The greatest factor, from the surface-water system, in controlling dissolved solids in the Rio Grande is the amount of water that is being transported or stored. Annual variation in streamflow is influenced primarily by climate (precipitation and evaporation) and management of Elephant Butte and Caballo Reservoirs (water storage and release cycles). Seasonal variation in streamflow within the Rio Grande study area is generally categorized generally as irrigation (March–September) and nonirrigation (October–February) seasons; with streamflow in the Rio Grande is highest during the irrigation season and lowest during the nonirrigation season. Dissolved-solids loads during the irrigation season decrease between Leasburg and Fort Quitman primarily because of irrigation diversions and losses to the underlying alluvial aquifer. Conversely, dissolved-solids loads during the nonirrigation season increase between Caballo Dam and Fort Quitman primarily because of the inflow of dissolved solids from agricultural drains, wastewater-treatment plants, and groundwater with elevated concentrations of dissolved solids.  Many studies have mass-balance budgets that account for the mass of dissolved solids transported along the Rio Grande. Results from mass-balance budgets developed for dissolved solids indicated that (1) the inflow of saline groundwater, inflow of regional groundwater, and chemical reactions between mineral phases are the primary sources controlling dissolved solids in the Rio Grande, and (2) groundwater pumping and mineral precipitation are causing a net storage of dissolved solids in the Leasburg to El Paso and El Paso to Fort Quitman reaches of the Rio Grande.  Looking forward, multiple water-resource managers from State and local agencies in New Mexico and Texas and Federal agencies formed the Rio Grande Salinity Management Coalition with the goal to reduce the amount of dissolved solids that are transported and stored in the Rio Grande study area. The recommendations for additional monitoring to assist the coalition are as follows:\n-Monitoring: Couple water-quality and streamflow monitoring in the Rio Grande and agricultural drains; perform groundwater-seepage investigations in the Rio Grande and major agricultural drains; nonitor groundwater water-quality conditions in the Mesilla and Hueco Basins.\n-Focused Hydrogeology Studies at Inflow Sources: Map dissolved-solids concentrations in the Rio Grande and underlying alluvial aquifer; perform hydrogeologic characterization of subsurface areas containing unusually high concentrations of dissolved solids. \n-Modeling of Dissolved Solids: Develop models to simulate the transport and storage of dissolved solids in both surface-water and groundwater systems.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131190","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers, New Mexico Interstate Stream Commission, and New Mexico Environment Department","usgsCitation":"Moyer, D., Anderholm, S.K., Hogan, J., Phillips, F.M., Hibbs, B.J., Witcher, J.C., Matherne, A.M., and Falk, S.E., 2013, Knowledge and understanding of dissolved solids in the Rio Grande–San Acacia, New Mexico, to Fort Quitman, Texas, and plan for future studies and monitoring: U.S. Geological Survey Open-File Report 2013-1190, vii, 55 p., https://doi.org/10.3133/ofr20131190.","productDescription":"vii, 55 p.","numberOfPages":"67","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":276776,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1190/"},{"id":276777,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1190/pdf/ofr2013-1190.pdf"},{"id":276779,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131190.gif"}],"country":"Mexico;United States","state":"New Mexico;Texas","otherGeospatial":"Rio Grande Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -108,31 ], [ -108,34.15 ], [ -105.15,34.15 ], [ -105.15,31 ], [ -108,31 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52136df9e4b0b08f4461988f","contributors":{"authors":[{"text":"Moyer, Douglas 0000-0001-6330-478X dlmoyer@usgs.gov","orcid":"https://orcid.org/0000-0001-6330-478X","contributorId":2670,"corporation":false,"usgs":true,"family":"Moyer","given":"Douglas","email":"dlmoyer@usgs.gov","affiliations":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"preferred":false,"id":482745,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderholm, Scott K.","contributorId":94270,"corporation":false,"usgs":true,"family":"Anderholm","given":"Scott","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":482749,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hogan, James F.","contributorId":30533,"corporation":false,"usgs":true,"family":"Hogan","given":"James F.","affiliations":[],"preferred":false,"id":482746,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Phillips, Fred M.","contributorId":57957,"corporation":false,"usgs":true,"family":"Phillips","given":"Fred","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":482748,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hibbs, Barry J.","contributorId":55327,"corporation":false,"usgs":true,"family":"Hibbs","given":"Barry","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":482747,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Witcher, James C.","contributorId":99456,"corporation":false,"usgs":true,"family":"Witcher","given":"James","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":482750,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Matherne, Anne Marie 0000-0002-5873-2226 matherne@usgs.gov","orcid":"https://orcid.org/0000-0002-5873-2226","contributorId":303,"corporation":false,"usgs":true,"family":"Matherne","given":"Anne","email":"matherne@usgs.gov","middleInitial":"Marie","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":482743,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Falk, Sarah E. sefalk@usgs.gov","contributorId":1056,"corporation":false,"usgs":true,"family":"Falk","given":"Sarah","email":"sefalk@usgs.gov","middleInitial":"E.","affiliations":[],"preferred":true,"id":482744,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70047693,"text":"sir20135140 - 2013 - Monitoring to assess progress toward meeting the total maximum daily load for phosphorus in the Assabet River, Massachusetts: phosphorus loads, 2008 through 2010","interactions":[],"lastModifiedDate":"2013-10-30T13:23:10","indexId":"sir20135140","displayToPublicDate":"2013-08-19T14:18:00","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":"2013-5140","title":"Monitoring to assess progress toward meeting the total maximum daily load for phosphorus in the Assabet River, Massachusetts: phosphorus loads, 2008 through 2010","docAbstract":"Wastewater discharges to the Assabet River contribute substantial amounts of phosphorus, which support accumulations of nuisance aquatic plants that are most evident in the river’s impounded reaches during the growing season. To restore the Assabet River’s water quality and aesthetics, the U.S. Environmental Protection Agency required the major wastewater-treatment plants in the drainage basin to reduce the amount of phosphorus discharged to the river by 2012. From October 2008 to December 2010, the U.S. Geological Survey, in cooperation with the Massachusetts Department of Environmental Protection and in support of the requirements of the Total Maximum Daily Load for Phosphorus, collected weekly flow-proportional, composite samples for analysis of concentrations of total phosphorus and orthophosphorus upstream and downstream from each of the Assabet River’s two largest impoundments: Hudson and Ben Smith. The purpose of this monitoring effort was to evaluate conditions in the river before enhanced treatment-plant technologies had effected reductions in phosphorus loads, thereby defining baseline conditions for comparison with conditions following the mandated load reductions. The locations of sampling sites with respect to the impoundments enabled examination of the impoundments’ effects on phosphorus sequestration and on the transformation of phosphorus between particulate and dissolved forms. The study evaluated the differences between loads upstream and downstream from the impoundments throughout the sampling period and compared differences during two seasonal periods of relevance to aquatic plants: April 1 through October 31, the growing season, and November 1 through March 31, the nongrowing season, when existing permit limits allowed average monthly wastewater-treatment-plant-effluent concentrations of 0.75 milligram per liter (growing season) or 1.0 milligram per liter (nongrowing season) for total phosphorus. At the four sampling sites during the growing season, median weekly total phosphorus loads ranged from 110 to 190 kilograms (kg) and median weekly orthophosphorus loads ranged from 17 to 41 kg. During the nongrowing season, median weekly total phosphorus loads ranged from 240 to 280 kg and median weekly orthophosphorus loads ranged from 56 to 66 kg.\n\nDuring periods of low and moderate streamflow, estimated loads of total phosphorus upstream from the Hudson impoundment generally exceeded those downstream during the same sampling periods throughout the study; orthophosphorus loads downstream from the impoundment were typically larger than those upstream. When storm runoff substantially increased the streamflow, loads of total phosphorus and orthophosphorus both tended to be larger downstream than upstream.\n\nAt the Ben Smith impoundment, both total phosphorus and orthophosphorus loads were generally larger downstream than upstream during low and moderate streamflow, but the differences were not as pronounced as they were at the Hudson impoundment. High flows were also associated with substantially larger total phosphorus and orthophosphorus loads downstream than those entering the impoundment from upstream.\n\nIn comparing periods of growing- and nongrowing-season loads, the same patterns of loads entering and leaving were observed at both impoundments. That is, at the Hudson impoundment, total phosphorus loads entering the impoundment were greater than those leaving it, and orthophosphorus loads leaving the impoundment were greater than those entering it. At the Ben Smith impoundment, both total phosphorus and orthophosphorus loads leaving the impoundment were greater than those entering it. However, the loads were greater during the nongrowing seasons than during the growing seasons, and the net differences between upstream and downstream loads were about the same.\n\nThe results indicate that some of the particulate fraction of the total phosphorus loads is sequestered in the Hudson impoundment, where particulate phosphorus probably undergoes some physical and biogeochemical transformations to the dissolved form orthophosphorus. The orthophosphorus may be taken up by aquatic plants or transported out of the impoundments. The results for the Ben Smith impoundment are less clear and suggest net export of total phosphorus and orthophosphorus. Differences between results from the two impoundments may be attributable in part to differences in their sizes, morphology, unmonitored tributaries, riparian land use, and processes within the impoundments that have not been quantified for this study.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135140","collaboration":"Prepared in cooperation with the Massachusetts Department of Environmental Protection","usgsCitation":"Zimmerman, M.J., and Savoie, J., 2013, Monitoring to assess progress toward meeting the total maximum daily load for phosphorus in the Assabet River, Massachusetts: phosphorus loads, 2008 through 2010: U.S. Geological Survey Scientific Investigations Report 2013-5140, viii, 41 p., https://doi.org/10.3133/sir20135140.","productDescription":"viii, 41 p.","numberOfPages":"53","temporalStart":"2008-01-01","temporalEnd":"2010-12-31","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":276764,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135140.PNG"},{"id":276762,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5140/"},{"id":276763,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5140/pdf/sir2013-5140.pdf"}],"country":"United States","state":"Massachusetts","otherGeospatial":"Assabet River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -71.618499,42.345676 ], [ -71.618499,42.472816 ], [ -71.357709,42.472816 ], [ -71.357709,42.345676 ], [ -71.618499,42.345676 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52136dfae4b0b08f44619897","contributors":{"authors":[{"text":"Zimmerman, Marc J. mzimmerm@usgs.gov","contributorId":3245,"corporation":false,"usgs":true,"family":"Zimmerman","given":"Marc","email":"mzimmerm@usgs.gov","middleInitial":"J.","affiliations":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"preferred":true,"id":482730,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Savoie, Jennifer G.","contributorId":52218,"corporation":false,"usgs":true,"family":"Savoie","given":"Jennifer G.","affiliations":[],"preferred":false,"id":482731,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70047659,"text":"70047659 - 2013 - Response of global soil consumption of atmospheric methane to changes in atmospheric climate and nitrogen deposition","interactions":[],"lastModifiedDate":"2013-10-23T14:29:03","indexId":"70047659","displayToPublicDate":"2013-08-16T13:41:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1836,"text":"Global Biogeochemical Cycles","active":true,"publicationSubtype":{"id":10}},"title":"Response of global soil consumption of atmospheric methane to changes in atmospheric climate and nitrogen deposition","docAbstract":"Soil consumption of atmospheric methane plays an important secondary role in regulating the atmospheric CH<sub>4</sub> budget, next to the dominant loss mechanism involving reaction with the hydroxyl radical (OH). Here we used a process-based biogeochemistry model to quantify soil consumption during the 20th and 21st centuries. We estimated that global soils consumed 32–36 Tg CH<sub>4</sub> yr<sup>−1</sup> during the 1990s. Natural ecosystems accounted for 84% of the total consumption, and agricultural ecosystems only consumed 5 Tg CH<sub>4</sub> yr<sup>−1</sup> in our estimations. During the twentieth century, the consumption rates increased at 0.03–0.20 Tg CH<sub>4</sub> yr<sup>−2</sup> with seasonal amplitudes increasing from 1.44 to 3.13 Tg CH<sub>4</sub> month<sup>−1</sup>. Deserts, shrublands, and xeric woodlands were the largest sinks. Atmospheric CH<sub>4</sub> concentrations and soil moisture exerted significant effects on the soil consumption while nitrogen deposition had a moderate effect. During the 21st century, the consumption is predicted to increase at 0.05-1.0 Tg CH<sub>4</sub> yr<sup>−2</sup>, and total consumption will reach 45–140 Tg CH<sub>4</sub> yr<sup>−1</sup> at the end of the 2090s, varying under different future climate scenarios. Dry areas will persist as sinks, boreal ecosystems will become stronger sinks, mainly due to increasing soil temperatures. Nitrogen deposition will modestly reduce the future sink strength at the global scale. When we incorporated the estimated global soil consumption into our chemical transport model simulations, we found that nitrogen deposition suppressed the total methane sink by 26 Tg during the period 1998–2004, resulting in 6.6 ppb higher atmospheric CH<sub>4</sub> mixing ratios compared to without considering nitrogen deposition effects. On average, a cumulative increase of every 1 Tg soil CH<sub>4</sub> consumption decreased atmospheric CH<sub>4</sub> mixing ratios by 0.26 ppb during the period 1998–2004.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Global Biogeochemical Cycles","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Geophysical Union","doi":"10.1002/gbc.20057","usgsCitation":"Zhuang, Q., Chen, M., Xu, K., Tang, J., Saikawa, E., Lu, Y., Melillo, J.M., Prinn, R.G., and McGuire, A., 2013, Response of global soil consumption of atmospheric methane to changes in atmospheric climate and nitrogen deposition: Global Biogeochemical Cycles, v. 27, no. 3, p. 650-663, https://doi.org/10.1002/gbc.20057.","productDescription":"14 p.","startPage":"650","endPage":"663","numberOfPages":"14","ipdsId":"IP-042134","costCenters":[{"id":108,"text":"Alaska Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"links":[{"id":473596,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/gbc.20057","text":"Publisher Index Page"},{"id":276699,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":276697,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/gbc.20057"}],"volume":"27","issue":"3","noUsgsAuthors":false,"publicationDate":"2013-08-09","publicationStatus":"PW","scienceBaseUri":"520f3bebe4b0fc50304bc490","contributors":{"authors":[{"text":"Zhuang, Qianlai","contributorId":101975,"corporation":false,"usgs":true,"family":"Zhuang","given":"Qianlai","affiliations":[],"preferred":false,"id":482660,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chen, Min","contributorId":56140,"corporation":false,"usgs":true,"family":"Chen","given":"Min","email":"","affiliations":[],"preferred":false,"id":482655,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Xu, Kai","contributorId":23426,"corporation":false,"usgs":true,"family":"Xu","given":"Kai","email":"","affiliations":[],"preferred":false,"id":482653,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tang, Jinyun","contributorId":88257,"corporation":false,"usgs":true,"family":"Tang","given":"Jinyun","email":"","affiliations":[],"preferred":false,"id":482659,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Saikawa, Eri","contributorId":69454,"corporation":false,"usgs":true,"family":"Saikawa","given":"Eri","email":"","affiliations":[],"preferred":false,"id":482657,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lu, Yanyu","contributorId":51190,"corporation":false,"usgs":true,"family":"Lu","given":"Yanyu","email":"","affiliations":[],"preferred":false,"id":482654,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Melillo, Jerry M.","contributorId":87847,"corporation":false,"usgs":false,"family":"Melillo","given":"Jerry","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":482658,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Prinn, Ronald G.","contributorId":69046,"corporation":false,"usgs":true,"family":"Prinn","given":"Ronald","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":482656,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"McGuire, A. David","contributorId":18494,"corporation":false,"usgs":true,"family":"McGuire","given":"A. David","affiliations":[],"preferred":false,"id":482652,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70047655,"text":"70047655 - 2013 - Flow variation and substrate type affect dislodgement of the freshwater polychaete, <i>Manayunkia speciosa</i>","interactions":[],"lastModifiedDate":"2013-08-16T13:50:31","indexId":"70047655","displayToPublicDate":"2013-08-16T13:39:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1699,"text":"Freshwater Science","active":true,"publicationSubtype":{"id":10}},"title":"Flow variation and substrate type affect dislodgement of the freshwater polychaete, <i>Manayunkia speciosa</i>","docAbstract":"We quantified microscale flow forces and their ability to entrain the freshwater polychaete, Manayunkia speciosa, the intermediate host for 2 myxozoan parasites (Ceratomyxa shasta and Parvicapsula minibicornis) that cause substantial mortalities in salmonid fishes in the Pacific Northwest. In a laboratory flume, we measured the shear stress associated with 2 mean flow velocities and 3 substrates and quantified associated dislodgement of polychaetes, evaluated survivorship of dislodged polychaetes, and observed behavioral responses of the polychaetes in response to increased flow. We used a generalized linear mixed model to estimate the probability of polychaete dislodgement for treatment combinations of velocity (mean flow velocity  =  55 cm/s with a shear velocity  =  3 cm/s, mean flow velocity  =  140 cm/s with a shear velocity  =  5 cm/s) and substrate type (depositional sediments and analogs of rock faces and the filamentous alga, Cladophora). Few polychaetes were dislodged at shear velocities <3 cm/s on any substrate. Above this level of shear, probability of dislodgement was strongly affected by both substrate type and velocity. After accounting for substrate, odds of dislodgement were 8× greater at the higher flow. After accounting for velocity, probability of dislodgement was greatest from fine sediments, intermediate from rock faces, and negligible from Cladophora. Survivorship of dislodged polychaetes was high. Polychaetes exhibited a variety of behaviors for avoiding increases in flow, including extrusion of mucus, burrowing into sediments, and movement to lower-flow microhabitats. Our findings suggest that polychaete populations probably exhibit high resilience to flow-mediated disturbances.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Freshwater Science","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"The Society for Freshwater Science","doi":"10.1899/12-140.1","usgsCitation":"Malakauskas, D.M., Wilson, S.J., Wilzbach, M.A., and Som, N.A., 2013, Flow variation and substrate type affect dislodgement of the freshwater polychaete, <i>Manayunkia speciosa</i>: Freshwater Science, v. 32, no. 3, p. 862-873, https://doi.org/10.1899/12-140.1.","productDescription":"12 p.","startPage":"862","endPage":"873","numberOfPages":"12","ipdsId":"IP-040986","costCenters":[{"id":150,"text":"California Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"links":[{"id":276700,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":276698,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1899/12-140.1"}],"country":"United States","state":"California","otherGeospatial":"Klamath River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.58947,41.837985 ], [ -122.58947,41.8622 ], [ -122.551101,41.8622 ], [ -122.551101,41.837985 ], [ -122.58947,41.837985 ] ] ] } } ] }","volume":"32","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"520f3be9e4b0fc50304bc480","contributors":{"authors":[{"text":"Malakauskas, David M.","contributorId":43247,"corporation":false,"usgs":true,"family":"Malakauskas","given":"David","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":482641,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wilson, Sarah J.","contributorId":37238,"corporation":false,"usgs":true,"family":"Wilson","given":"Sarah","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":482640,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wilzbach, Margaret A.","contributorId":76981,"corporation":false,"usgs":true,"family":"Wilzbach","given":"Margaret","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":482642,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Som, Nicholas A.","contributorId":36039,"corporation":false,"usgs":true,"family":"Som","given":"Nicholas","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":482639,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70047647,"text":"ofr20131229 - 2013 - Review of a model to assess stranding of juvenile salmon by ship wakes along the Lower Columbia River, Oregon and Washington","interactions":[],"lastModifiedDate":"2013-08-16T11:13:18","indexId":"ofr20131229","displayToPublicDate":"2013-08-16T11:05:00","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":"2013-1229","title":"Review of a model to assess stranding of juvenile salmon by ship wakes along the Lower Columbia River, Oregon and Washington","docAbstract":"Long period wake waves from deep draft vessels have been shown to strand small fish, particularly juvenile Chinook salmon Oncorhynchus tschawytcha, in the lower Columbia River (LCR). The U.S. Army Corps of Engineers is responsible for maintaining the shipping channel in the LCR and recently conducted dredging operations to deepen the shipping channel from an authorized depth of 40 feet(ft) to an authorized depth of 43 ft (in areas where rapid shoaling was expected, dredging operations were used to increase the channel depth to 48 ft). A model was developed to estimate stranding probabilities for juvenile salmon under the 40- and 43-ft channel scenarios, to determine if channel deepening was going to affect wake stranding (Assessment of potential stranding of juvenile salmon by ship wakes along the Lower Columbia River under scenarios of ship traffic and channel depth: Report prepared for the Portland District U.S. Army Corps of Engineers, Portland, Oregon). The U.S. Army Corps of Engineers funded the U.S. Geological Survey to review this model. A total of 30 review questions were provided to guide the review process, and these questions are addressed in this report. In general, we determined that the analyses by Pearson (2011) were appropriate given the data available. We did identify two areas where additional information could have been provided: (1) a more thorough description of model diagnostics and model selection would have been useful for the reader to better understand the model framework; and (2) model uncertainty should have been explicitly described and reported in the document. Stranding probability estimates between the 40- and 43-ft channel depths were minimally different under most of the scenarios that were examined by Pearson (2011), and a discussion of the effects of uncertainty given these minimal differences would have been useful. Ultimately, however, a stochastic (or simulation) model would provide the best opportunity to illustrate uncertainty within a given set of model predictions, but such an approach would require a substantial amount of additional data collection. Several review questions focused on the accuracy and precision of the model estimates, but we were unable to address these questions because of the limited data that currently exists regarding wake stranding in the LCR. Additional field studies will be required to validate findings from Pearson (2011), if concerns regarding accuracy and precision remain a priority. Although the Pearson (2011) model provided a useful examination of stranding under pre-construction and post-construction conditions, future research will be required to better understand the effects of wake stranding on juvenile salmonids throughout the entire LCR. If additional information on wake stranding is desired in the future, the following topics may be of interest: (1) spatial examination of wake stranding throughout the entire LCR; (2) additional evaluation of juvenile salmonid behavior and population dynamics; (3) assessing and integrating predicted changes in ship development; and (4) assessing and integrating predicted changes in climate on environmental factors known to cause stranding.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131229","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Kock, T.J., Plumb, J.M., and Adams, N.S., 2013, Review of a model to assess stranding of juvenile salmon by ship wakes along the Lower Columbia River, Oregon and Washington: U.S. Geological Survey Open-File Report 2013-1229, iv, 20 p., https://doi.org/10.3133/ofr20131229.","productDescription":"iv, 20 p.","numberOfPages":"28","onlineOnly":"Y","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":276680,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131229.jpg"},{"id":276678,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1229/"},{"id":276679,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1229/pdf/ofr20131229.pdf"}],"country":"United States","state":"Oregon;Washington","otherGeospatial":"Columbia River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.1739,45.5391 ], [ -124.1739,48.9995 ], [ -117.6306,48.9995 ], [ -117.6306,45.5391 ], [ -124.1739,45.5391 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"520f3bece4b0fc50304bc494","contributors":{"authors":[{"text":"Kock, Tobias J. 0000-0001-8976-0230 tkock@usgs.gov","orcid":"https://orcid.org/0000-0001-8976-0230","contributorId":3038,"corporation":false,"usgs":true,"family":"Kock","given":"Tobias","email":"tkock@usgs.gov","middleInitial":"J.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":482625,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Plumb, John M. 0000-0003-4255-1612 jplumb@usgs.gov","orcid":"https://orcid.org/0000-0003-4255-1612","contributorId":3569,"corporation":false,"usgs":true,"family":"Plumb","given":"John","email":"jplumb@usgs.gov","middleInitial":"M.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":482627,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Adams, Noah S. 0000-0002-8354-0293 nadams@usgs.gov","orcid":"https://orcid.org/0000-0002-8354-0293","contributorId":3521,"corporation":false,"usgs":true,"family":"Adams","given":"Noah","email":"nadams@usgs.gov","middleInitial":"S.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":482626,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70047638,"text":"70047638 - 2013 - Clarity versus complexity: land-use modeling as a practical tool for decision-makers","interactions":[],"lastModifiedDate":"2018-03-13T15:41:08","indexId":"70047638","displayToPublicDate":"2013-08-16T08:14:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2258,"text":"Journal of Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Clarity versus complexity: land-use modeling as a practical tool for decision-makers","docAbstract":"The last decade has seen a remarkable increase in the number of modeling tools available to examine future land-use and land-cover (LULC) change. Integrated modeling frameworks, agent-based models, cellular automata approaches, and other modeling techniques have substantially improved the representation of complex LULC systems, with each method using a different strategy to address complexity. However, despite the development of new and better modeling tools, the use of these tools is limited for actual planning, decision-making, or policy-making purposes. LULC modelers have become very adept at creating tools for modeling LULC change, but complicated models and lack of transparency limit their utility for decision-makers. The complicated nature of many LULC models also makes it impractical or even impossible to perform a rigorous analysis of modeling uncertainty. This paper provides a review of land-cover modeling approaches and the issues causes by the complicated nature of models, and provides suggestions to facilitate the increased use of LULC models by decision-makers and other stakeholders. The utility of LULC models themselves can be improved by 1) providing model code and documentation, 2) through the use of scenario frameworks to frame overall uncertainties, 3) improving methods for generalizing key LULC processes most important to stakeholders, and 4) adopting more rigorous standards for validating models and quantifying uncertainty. Communication with decision-makers and other stakeholders can be improved by increasing stakeholder participation in all stages of the modeling process, increasing the transparency of model structure and uncertainties, and developing user-friendly decision-support systems to bridge the link between LULC science and policy. By considering these options, LULC science will be better positioned to support decision-makers and increase real-world application of LULC modeling results.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Environmental Management","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.jenvman.2013.07.027","usgsCitation":"Sohl, T.L., and Claggett, P.R., 2013, Clarity versus complexity: land-use modeling as a practical tool for decision-makers: Journal of Environmental Management, v. 129, p. 235-243, https://doi.org/10.1016/j.jenvman.2013.07.027.","productDescription":"9 p.","startPage":"235","endPage":"243","ipdsId":"IP-042214","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":276664,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":276663,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.jenvman.2013.07.027"}],"volume":"129","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"520f3be8e4b0fc50304bc47c","contributors":{"authors":[{"text":"Sohl, Terry L. 0000-0002-9771-4231 sohl@usgs.gov","orcid":"https://orcid.org/0000-0002-9771-4231","contributorId":648,"corporation":false,"usgs":true,"family":"Sohl","given":"Terry","email":"sohl@usgs.gov","middleInitial":"L.","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":482607,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Claggett, Peter R. 0000-0002-5335-2857 pclaggett@usgs.gov","orcid":"https://orcid.org/0000-0002-5335-2857","contributorId":176287,"corporation":false,"usgs":true,"family":"Claggett","given":"Peter","email":"pclaggett@usgs.gov","middleInitial":"R.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":482608,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70047636,"text":"ofr20131137 - 2013 - Water resources and shale gas/oil production in the Appalachian Basin: critical issues and evolving developments","interactions":[],"lastModifiedDate":"2013-10-30T13:09:01","indexId":"ofr20131137","displayToPublicDate":"2013-08-15T14:20:00","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":"2013-1137","title":"Water resources and shale gas/oil production in the Appalachian Basin: critical issues and evolving developments","docAbstract":"Unconventional natural gas and oil resources in the United States are important components of a national energy program. While the Nation seeks greater energy independence and greener sources of energy, Federal agencies with environmental responsibilities, state and local regulators and water-resource agencies, and citizens throughout areas of unconventional shale gas development have concerns about the environmental effects of high volume hydraulic fracturing (HVHF), including those in the Appalachian Basin in the northeastern United States (fig. 1). Environmental concerns posing critical challenges include the availability and use of surface water and groundwater for hydraulic fracturing; the migration of stray gas and potential effects on overlying aquifers; the potential for flowback, formation fluids, and other wastes to contaminate surface water and groundwater; and the effects from drill pads, roads, and pipeline infrastructure on land disturbance in small watersheds and headwater streams (U.S. Government Printing Office, 2012). Federal, state, regional and local agencies, along with the gas industry, are striving to use the best science and technology to develop these unconventional resources in an environmentally safe manner. Some of these concerns were addressed in U.S. Geological Survey (USGS) Fact Sheet 2009–3032 (Soeder and Kappel, 2009) about potential critical effects on water resources associated with the development of gas extraction from the Marcellus Shale of the Hamilton Group (Ver Straeten and others, 1994). Since that time, (1) the extraction process has evolved, (2) environmental awareness related to high-volume hydraulic fracturing process has increased, (3) state regulations concerning gas well drilling have been modified, and (4) the practices used by industry to obtain, transport, recover, treat, recycle, and ultimately dispose of the spent fluids and solid waste materials have evolved. This report updates and expands on Fact Sheet 2009–3032 and presents new information regarding selected aspects of unconventional shale gas development in the Appalachian Basin (primarily Virginia, West Virginia, Maryland, Pennsylvania, Ohio, and New York). This document was prepared by the USGS, in cooperation with the U.S. Department of Energy, and reviews the evolving technical advances and scientific studies made in the Appalachian Basin between 2009 and the present (2013), addressing past and current issues for oil and gas development in the region.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131137","collaboration":"Prepared in cooperation with the U.S. Department of Energy","usgsCitation":"Kappel, W.M., Williams, J., and Szabo, Z., 2013, Water resources and shale gas/oil production in the Appalachian Basin: critical issues and evolving developments: U.S. Geological Survey Open-File Report 2013-1137, 12 p., https://doi.org/10.3133/ofr20131137.","productDescription":"12 p.","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":276656,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131137.gif"},{"id":276654,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1137/"},{"id":276655,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1137/pdf/ofr2013-1137.pdf"}],"country":"United States","state":"Maryl;New York;Ohio;Pennsylvania;Virginia;West Virginia","otherGeospatial":"Appalachian Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -83.02,37.59 ], [ -83.02,43.14 ], [ -74.38,43.14 ], [ -74.38,37.59 ], [ -83.02,37.59 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"520dea5be4b08494c3cb05bb","contributors":{"authors":[{"text":"Kappel, William M. 0000-0002-2382-9757 wkappel@usgs.gov","orcid":"https://orcid.org/0000-0002-2382-9757","contributorId":1074,"corporation":false,"usgs":true,"family":"Kappel","given":"William","email":"wkappel@usgs.gov","middleInitial":"M.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":482601,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Williams, John H. 0000-0002-6054-6908 jhwillia@usgs.gov","orcid":"https://orcid.org/0000-0002-6054-6908","contributorId":1553,"corporation":false,"usgs":true,"family":"Williams","given":"John","email":"jhwillia@usgs.gov","middleInitial":"H.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":482602,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Szabo, Zoltan 0000-0002-0760-9607 zszabo@usgs.gov","orcid":"https://orcid.org/0000-0002-0760-9607","contributorId":2240,"corporation":false,"usgs":true,"family":"Szabo","given":"Zoltan","email":"zszabo@usgs.gov","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":false,"id":482603,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70047635,"text":"fs20133040 - 2013 - The 3D Elevation Program: summary for Rhode Island","interactions":[],"lastModifiedDate":"2016-08-17T16:14:28","indexId":"fs20133040","displayToPublicDate":"2013-08-15T14:09:00","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":"2013-3040","title":"The 3D Elevation Program: summary for Rhode Island","docAbstract":"<p>Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the State of Rhode Island, elevation data are critical for flood risk management, natural resources conservation, coastal zone management, sea level rise and subsidence, agriculture and precision farming, and other business uses. Today, high-quality light detection and ranging (lidar) data are the sources for creating elevation models and other elevation datasets. Federal, State, and local agencies work in partnership to (1) replace data, on a national basis, that are (on average) 30 years old and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of State and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data. The new 3D Elevation Program (3DEP) initiative (Snyder, 2012a,b), managed by the U.S. Geological Survey (USGS), responds to the growing need for high-quality topographic data and a wide range of other three-dimensional representations of the Nation&rsquo;s natural and constructed features.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20133040","usgsCitation":"Carswell, W., 2013, The 3D Elevation Program: summary for Rhode Island: U.S. Geological Survey Fact Sheet 2013-3040, 2 p., https://doi.org/10.3133/fs20133040.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":423,"text":"National Geospatial 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,{"id":70047628,"text":"ds789 - 2013 - Catalog of earthquake hypocenters at Alaskan volcanoes: January 1 through December 31, 2012","interactions":[],"lastModifiedDate":"2016-09-07T16:51:18","indexId":"ds789","displayToPublicDate":"2013-08-15T12:04:31","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":"789","title":"Catalog of earthquake hypocenters at Alaskan volcanoes: January 1 through December 31, 2012","docAbstract":"<p>Between January 1 and December 31, 2012, the Alaska Volcano Observatory located 4,787 earthquakes, of which 4,211 occurred within 20 kilometers of the 33 volcanoes monitored by a seismograph network. There was significant seismic activity at Iliamna, Kanaga, and Little Sitkin volcanoes in 2012. Instrumentation highlights for this year include the implementation of the Advanced National Seismic System Quake Monitoring System hardware and software in February 2012 and the continuation of the American Recovery and Reinvestment Act work in the summer of 2012. The operational highlight was the removal of Mount Wrangell from the list of monitored volcanoes. This catalog includes hypocenters, magnitudes, and statistics of the earthquakes located in 2012 with the station parameters, velocity models, and other files used to locate these earthquakes.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds789","usgsCitation":"Dixon, J.P., Stihler, S.D., Power, J.A., Haney, M.M., Parker, T., Searcy, C., and Prejean, S., 2013, Catalog of earthquake hypocenters at Alaskan volcanoes: January 1 through December 31, 2012: U.S. Geological Survey Data Series 789, Report: iv, 84 p.; Zip file, https://doi.org/10.3133/ds789.","productDescription":"Report: iv, 84 p.; Zip file","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2012-01-01","temporalEnd":"2012-12-31","costCenters":[{"id":121,"text":"Alaska Volcano Observatory","active":false,"usgs":true}],"links":[{"id":276638,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds789.JPG"},{"id":276637,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/789/2012_AVO_Seismic_Catalog.zip","text":"Seismic Catalog","size":"1.4 MB","linkFileType":{"id":6,"text":"zip"},"description":"Seismic Catalog"},{"id":276636,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/789/pdf/ds789.pdf","text":"Report","size":"6.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":276635,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/789/"}],"country":"United States","state":"Alaska","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -181.82373046875,\n              50.86491125522503\n            ],\n            [\n              -182.120361328125,\n              52.09975692575725\n            ],\n            [\n              -170.33203125,\n              61.33353967329142\n            ],\n            [\n              -153.45703125,\n              65.47650756256367\n            ],\n            [\n              -141.15234374999997,\n              66.26685631430843\n            ],\n            [\n              -141.15234374999997,\n              59.88893689676585\n            ],\n            [\n              -153.8525390625,\n              53.69670647530323\n            ],\n            [\n              -181.82373046875,\n              50.86491125522503\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"520dea57e4b08494c3cb05ab","contributors":{"authors":[{"text":"Dixon, James P. 0000-0002-8478-9971 jpdixon@usgs.gov","orcid":"https://orcid.org/0000-0002-8478-9971","contributorId":3163,"corporation":false,"usgs":true,"family":"Dixon","given":"James","email":"jpdixon@usgs.gov","middleInitial":"P.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":482569,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stihler, Scott D.","contributorId":31373,"corporation":false,"usgs":true,"family":"Stihler","given":"Scott","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":482572,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Power, John A. 0000-0002-7233-4398 jpower@usgs.gov","orcid":"https://orcid.org/0000-0002-7233-4398","contributorId":2768,"corporation":false,"usgs":true,"family":"Power","given":"John","email":"jpower@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":482567,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Haney, Matthew M. mhaney@usgs.gov","contributorId":2943,"corporation":false,"usgs":true,"family":"Haney","given":"Matthew","email":"mhaney@usgs.gov","middleInitial":"M.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":false,"id":482568,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Parker, Tom","contributorId":13520,"corporation":false,"usgs":true,"family":"Parker","given":"Tom","email":"","affiliations":[],"preferred":false,"id":482571,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Searcy, Cheryl 0000-0002-9474-5745 csearcy@usgs.gov","orcid":"https://orcid.org/0000-0002-9474-5745","contributorId":4039,"corporation":false,"usgs":true,"family":"Searcy","given":"Cheryl","email":"csearcy@usgs.gov","affiliations":[],"preferred":true,"id":482570,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Prejean, Stephanie","contributorId":61916,"corporation":false,"usgs":true,"family":"Prejean","given":"Stephanie","affiliations":[],"preferred":false,"id":482573,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70118578,"text":"70118578 - 2013 - Modeling volcano growth on the Island of Hawaii: Deep-water perspectives","interactions":[],"lastModifiedDate":"2020-10-06T00:40:02.381038","indexId":"70118578","displayToPublicDate":"2013-08-14T13:02:10","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"Modeling volcano growth on the Island of Hawaii: Deep-water perspectives","docAbstract":"Recent ocean-bottom geophysical surveys, dredging, and dives, which complement surface data and scientific drilling at the Island of Hawaii, document that evolutionary stages during volcano growth are more diverse than previously described. Based on combining available composition, isotopic age, and geologically constrained volume data for each of the component volcanoes, this overview provides the first integrated models for overall growth of any Hawaiian island. In contrast to prior morphologic models for volcano evolution (preshield, shield, postshield), growth increasingly can be tracked by age and volume (magma supply), defining waxing alkalic, sustained tholeiitic, and waning alkalic stages. Data and estimates for individual volcanoes are used to model changing magma supply during successive compositional stages, to place limits on volcano life spans, and to interpret composite assembly of the island. Volcano volumes vary by an order of magnitude; peak magma supply also varies sizably among edifices but is challenging to quantify because of uncertainty about volcano life spans. Three alternative models are compared: (1) near-constant volcano propagation, (2) near-equal volcano durations, (3) high peak-tholeiite magma supply. These models define inconsistencies with prior geodynamic models, indicate that composite growth at Hawaii peaked ca. 800–400 ka, and demonstrate a lower current rate. Recent age determinations for Kilauea and Kohala define a volcano propagation rate of 8.6 cm/yr that yields plausible inception ages for other volcanoes of the Kea trend. In contrast, a similar propagation rate for the less-constrained Loa trend would require inception of Loihi Seamount in the future and ages that become implausibly large for the older volcanoes. An alternative rate of 10.6 cm/yr for Loa-trend volcanoes is reasonably consistent with ages and volcano spacing, but younger Loa volcanoes are offset from the Kea trend in age-distance plots. Variable magma flux at the Island of Hawaii, and longer-term growth of the Hawaiian chain as discrete islands rather than a continuous ridge, may record pulsed magma flow in the hotspot/plume source.","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES00935.1","usgsCitation":"Lipman, P.W., and Calvert, A.T., 2013, Modeling volcano growth on the Island of Hawaii: Deep-water perspectives: Geosphere, v. 9, no. 5, p. 1348-1383, https://doi.org/10.1130/GES00935.1.","productDescription":"36 p.","startPage":"1348","endPage":"1383","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":473597,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges00935.1","text":"Publisher Index 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,{"id":70124275,"text":"70124275 - 2013 - Land use planning and wildfire: development policies influence future probability of housing loss","interactions":[],"lastModifiedDate":"2014-09-11T11:36:07","indexId":"70124275","displayToPublicDate":"2013-08-14T11:33:00","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":"Land use planning and wildfire: development policies influence future probability of housing loss","docAbstract":"Increasing numbers of homes are being destroyed by wildfire in the wildland-urban interface. With projections of climate change and housing growth potentially exacerbating the threat of wildfire to homes and property, effective fire-risk reduction alternatives are needed as part of a comprehensive fire management plan. Land use planning represents a shift in traditional thinking from trying to eliminate wildfires, or even increasing resilience to them, toward avoiding exposure to them through the informed placement of new residential structures. For land use planning to be effective, it needs to be based on solid understanding of where and how to locate and arrange new homes. We simulated three scenarios of future residential development and projected landscape-level wildfire risk to residential structures in a rapidly urbanizing, fire-prone region in southern California. We based all future development on an econometric subdivision model, but we varied the emphasis of subdivision decision-making based on three broad and common growth types: infill, expansion, and leapfrog. Simulation results showed that decision-making based on these growth types, when applied locally for subdivision of individual parcels, produced substantial landscape-level differences in pattern, location, and extent of development. These differences in development, in turn, affected the area and proportion of structures at risk from burning in wildfires. Scenarios with lower housing density and larger numbers of small, isolated clusters of development, i.e., resulting from leapfrog development, were generally predicted to have the highest predicted fire risk to the largest proportion of structures in the study area, and infill development was predicted to have the lowest risk. These results suggest that land use planning should be considered an important component to fire risk management and that consistently applied policies based on residential pattern may provide substantial benefits for future risk reduction.","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.0071708","usgsCitation":"Syphard, A.D., Massada, A.B., Butsic, V., and Keeley, J.E., 2013, Land use planning and wildfire: development policies influence future probability of housing loss: PLoS ONE, v. 8, no. 8, e71708; 12 p., https://doi.org/10.1371/journal.pone.0071708.","productDescription":"e71708; 12 p.","numberOfPages":"12","onlineOnly":"Y","ipdsId":"IP-049993","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":473598,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0071708","text":"Publisher Index Page"},{"id":293698,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":293656,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1371/journal.pone.0071708"}],"country":"United States","state":"California","county":"San Diego County","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -117.5959,32.5342 ], [ -117.5959,33.505 ], [ -116.0809,33.505 ], [ -116.0809,32.5342 ], [ -117.5959,32.5342 ] ] ] } } ] }","volume":"8","issue":"8","noUsgsAuthors":false,"publicationDate":"2013-08-14","publicationStatus":"PW","scienceBaseUri":"5412b9afe4b0239f1986ba9c","contributors":{"authors":[{"text":"Syphard, Alexandra D.","contributorId":8977,"corporation":false,"usgs":false,"family":"Syphard","given":"Alexandra","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":500634,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Massada, Avi Bar","contributorId":93744,"corporation":false,"usgs":true,"family":"Massada","given":"Avi","email":"","middleInitial":"Bar","affiliations":[],"preferred":false,"id":500636,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Butsic, Van","contributorId":11524,"corporation":false,"usgs":true,"family":"Butsic","given":"Van","affiliations":[],"preferred":false,"id":500635,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Keeley, Jon E. 0000-0002-4564-6521 jon_keeley@usgs.gov","orcid":"https://orcid.org/0000-0002-4564-6521","contributorId":1268,"corporation":false,"usgs":true,"family":"Keeley","given":"Jon","email":"jon_keeley@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":500633,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70047596,"text":"sir20135139 - 2013 - Relation between organic-wastewater compounds, groundwater geochemistry, and well characteristics for selected wells in Lansing, Michigan","interactions":[],"lastModifiedDate":"2013-08-13T13:04:22","indexId":"sir20135139","displayToPublicDate":"2013-08-13T12:57:00","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":"2013-5139","title":"Relation between organic-wastewater compounds, groundwater geochemistry, and well characteristics for selected wells in Lansing, Michigan","docAbstract":"In 2010, groundwater from 20 Lansing Board of Water and Light (BWL) production wells was tested for 69 organic-wastewater compounds (OWCs). The OWCs detected in one-half of the sampled wells are widely used in industrial and environmental applications and commonly occur in many wastes and stormwater. To identify factors that contribute to the occurrence of these constituents in BWL wells, the U.S. Geological Survey (USGS) interpreted the results of these analyses and related detections of OWCs to local characteristics and groundwater geochemistry.\n\nAnalysis of groundwater-chemistry data collected by the BWL during routine monitoring from 1969 to 2011 indicates that the geochemistry of the BWL wells has changed over time, with the major difference being an increase in sodium and chloride. The concentrations of sodium and chloride were positively correlated to frequency of OWC detections. The BWL wells studied are all completed in the Saginaw aquifer, which consists of water-bearing sandstones of Pennsylvanian age. The Saginaw aquifer is underlain by the Parma-Bayport aquifer, and overlain by the Glacial aquifer. Two possible sources of sodium and chloride were evaluated: basin brines by way of the Parma-Bayport aquifer, and surficial sources by way of the Glacial aquifer. To determine if water from the underlying aquifer had influenced well-water geochemistry over time, the total dissolved solids concentration and changes in major ion concentrations were examined with respect to well depth, age, and pumping rate. To address a possible surficial source of sodium and chloride, 25 well, aquifer, or hydrologic characteristics, and 2 groundwater geochemistry variables that might influence whether, or the rate at which, water from the land surface could reach each well were compared to OWC detections and well chemistry.\n\nThe statistical tests performed during this study, using available variables, indicated that reduced time of travel of water from the land surface to the well opening was significantly correlated with detections of OWCs. No specific well or aquifer characteristic was correlated with OWC detections; however, wells with detections tended to have less modeled confining material thickness (as simulated in the regional groundwater flow model), which is an estimate of the amount of clay or shale between the Glacial and Saginaw aquifers. Additional analyses and collection of other data would be required to more conclusively identify the source and to determine the potential vulnerability of other wells because each BWL well may have a somewhat unique set of characteristics that governs its response to pumping. Therefore, it is possible that a relevant explanatory variable was not included in this analysis. The current patterns of geochemistry, and the relation between these patterns and volume of pumpage for the BWL wells, indicates other wells may be susceptible to OWCs in the future.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135139","collaboration":"Prepared in cooperation with the Tri-County Regional Planning Commission","usgsCitation":"Haack, S.K., and Luukkonen, C.L., 2013, Relation between organic-wastewater compounds, groundwater geochemistry, and well characteristics for selected wells in Lansing, Michigan: U.S. Geological Survey Scientific Investigations Report 2013-5139, v, 36 p., https://doi.org/10.3133/sir20135139.","productDescription":"v, 36 p.","numberOfPages":"46","onlineOnly":"Y","costCenters":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true}],"links":[{"id":276575,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135139.png"},{"id":276573,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5139/"},{"id":276574,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5139/pdf/sir2013-5139_web.pdf"}],"country":"United States","state":"Michigan","county":"Clinton County;Eaton County;Ingham County","city":"Lansing","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -84.701274,42.647483 ], [ -84.701274,42.76988 ], [ -84.417581,42.76988 ], [ -84.417581,42.647483 ], [ -84.701274,42.647483 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"520b81efe4b0d6ca46067db8","contributors":{"authors":[{"text":"Haack, Sheridan K. skhaack@usgs.gov","contributorId":1982,"corporation":false,"usgs":true,"family":"Haack","given":"Sheridan","email":"skhaack@usgs.gov","middleInitial":"K.","affiliations":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true}],"preferred":true,"id":482478,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Luukkonen, Carol L. clluukko@usgs.gov","contributorId":3489,"corporation":false,"usgs":true,"family":"Luukkonen","given":"Carol","email":"clluukko@usgs.gov","middleInitial":"L.","affiliations":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true}],"preferred":true,"id":482479,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70047571,"text":"tm6A46 - 2013 - Documentation of the seawater intrusion (SWI2) package for MODFLOW","interactions":[],"lastModifiedDate":"2013-08-12T11:57:05","indexId":"tm6A46","displayToPublicDate":"2013-08-12T11:50:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"6-A46","title":"Documentation of the seawater intrusion (SWI2) package for MODFLOW","docAbstract":"The SWI2 Package is the latest release of the Seawater Intrusion (SWI) Package for MODFLOW. The SWI2 Package allows three-dimensional vertically integrated variable-density groundwater flow and seawater intrusion in coastal multiaquifer systems to be simulated using MODFLOW-2005. Vertically integrated variable-density groundwater flow is based on the Dupuit approximation in which an aquifer is vertically discretized into zones of differing densities, separated from each other by defined surfaces representing interfaces or density isosurfaces. The numerical approach used in the SWI2 Package does not account for diffusion and dispersion and should not be used where these processes are important. The resulting differential equations are equivalent in form to the groundwater flow equation for uniform-density flow. The approach implemented in the SWI2 Package allows density effects to be incorporated into MODFLOW-2005 through the addition of pseudo-source terms to the groundwater flow equation without the need to solve a separate advective-dispersive transport equation. Vertical and horizontal movement of defined density surfaces is calculated separately using a combination of fluxes calculated through solution of the groundwater flow equation and a simple tip and toe tracking algorithm.\n\nUse of the SWI2 Package in MODFLOW-2005 only requires the addition of a single additional input file and modification of boundary heads to freshwater heads referenced to the top of the aquifer. Fluid density within model layers can be represented using zones of constant density (stratified flow) or continuously varying density (piecewise linear in the vertical direction) in the SWI2 Package. The main advantage of using the SWI2 Package instead of variable-density groundwater flow and dispersive solute transport codes, such as SEAWAT and SUTRA, is that fewer model cells are required for simulations using the SWI2 Package because every aquifer can be represented by a single layer of cells. This reduction in number of required model cells and the elimination of the need to solve the advective-dispersive transport equation results in substantial model run-time savings, which can be large for regional aquifers. The accuracy and use of the SWI2 Package is demonstrated through comparison with existing exact solutions and numerical solutions with SEAWAT. Results for an unconfined aquifer are also presented to demonstrate application of the SWI2 Package to a large-scale regional problem.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Section A: Ground water in Book 6 <i>Modeling Techniques</i>","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm6A46","collaboration":"Groundwater Resources Program; This report is Chapter 46 of Section A: Ground water in Book 6 <i>Modeling Techniques</i>","usgsCitation":"Bakker, M., Schaars, F., Hughes, J.D., Langevin, C.D., and Dausman, A., 2013, Documentation of the seawater intrusion (SWI2) package for MODFLOW: U.S. Geological Survey Techniques and Methods 6-A46, viii, 47 p., https://doi.org/10.3133/tm6A46.","productDescription":"viii, 47 p.","costCenters":[{"id":494,"text":"Office of Groundwater","active":false,"usgs":true}],"links":[{"id":276425,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/tm6a46.gif"},{"id":276409,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/tm/6a46/"},{"id":276411,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/6a46/tm6-a46.pdf"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5209f5dce4b0026c2bc11a9a","contributors":{"authors":[{"text":"Bakker, Mark","contributorId":56137,"corporation":false,"usgs":true,"family":"Bakker","given":"Mark","email":"","affiliations":[],"preferred":false,"id":482430,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schaars, Frans","contributorId":15920,"corporation":false,"usgs":true,"family":"Schaars","given":"Frans","email":"","affiliations":[],"preferred":false,"id":482429,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hughes, Joseph D. 0000-0003-1311-2354 jdhughes@usgs.gov","orcid":"https://orcid.org/0000-0003-1311-2354","contributorId":2492,"corporation":false,"usgs":true,"family":"Hughes","given":"Joseph","email":"jdhughes@usgs.gov","middleInitial":"D.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":482428,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Langevin, Christian D. 0000-0001-5610-9759 langevin@usgs.gov","orcid":"https://orcid.org/0000-0001-5610-9759","contributorId":1030,"corporation":false,"usgs":true,"family":"Langevin","given":"Christian","email":"langevin@usgs.gov","middleInitial":"D.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":482427,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dausman, Alyssa M.","contributorId":64337,"corporation":false,"usgs":true,"family":"Dausman","given":"Alyssa M.","affiliations":[],"preferred":false,"id":482431,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70047548,"text":"70047548 - 2013 - Modeling steam pressure under martian lava flows","interactions":[],"lastModifiedDate":"2018-11-08T16:11:53","indexId":"70047548","displayToPublicDate":"2013-08-11T17:41:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1963,"text":"Icarus","active":true,"publicationSubtype":{"id":10}},"title":"Modeling steam pressure under martian lava flows","docAbstract":"Rootless cones on Mars are a valuable indicator of past interactions between lava and water. However, the details of the lava–water interactions are not fully understood, limiting the ability to use these features to infer new information about past water on Mars. We have developed a model for the pressurization of a dry layer of porous regolith by melting and boiling ground ice in the shallow subsurface. This model builds on previous models of lava cooling and melting of subsurface ice. We find that for reasonable regolith properties and ice depths of decimeters, explosive pressures can be reached. However, the energy stored within such lags is insufficient to excavate thick flows unless they draw steam from a broader region than the local eruption site. These results indicate that lag pressurization can drive rootless cone formation under favorable circumstances, but in other instances molten fuel–coolant interactions are probably required. We use the model results to consider a range of scenarios for rootless cone formation in Athabasca Valles. Pressure buildup by melting and boiling ice under a desiccated lag is possible in some locations, consistent with the expected distribution of ice implanted from atmospheric water vapor. However, it is uncertain whether such ice has existed in the vicinity of Athabasca Valles in recent history. Plausible alternative sources include surface snow or an aqueous flood shortly before the emplacement of the lava flow.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Icarus","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.icarus.2013.06.036","usgsCitation":"Dundas, C.M., and Keszthelyi, L., 2013, Modeling steam pressure under martian lava flows: Icarus, v. 226, no. 1, p. 1058-1067, https://doi.org/10.1016/j.icarus.2013.06.036.","productDescription":"10 p.","startPage":"1058","endPage":"1067","ipdsId":"IP-044490","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":276287,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":276286,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.icarus.2013.06.036"}],"otherGeospatial":"Mars","volume":"226","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5208a45ce4b0058b906bf5ac","contributors":{"authors":[{"text":"Dundas, Colin M. 0000-0003-2343-7224 cdundas@usgs.gov","orcid":"https://orcid.org/0000-0003-2343-7224","contributorId":2937,"corporation":false,"usgs":true,"family":"Dundas","given":"Colin","email":"cdundas@usgs.gov","middleInitial":"M.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":482360,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Keszthelyi, Laszlo P. 0000-0003-1879-4331 laz@usgs.gov","orcid":"https://orcid.org/0000-0003-1879-4331","contributorId":52802,"corporation":false,"usgs":true,"family":"Keszthelyi","given":"Laszlo P.","email":"laz@usgs.gov","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":482361,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70047538,"text":"ofr20131175 - 2013 - Economic resilience through \"One-Water\" management","interactions":[],"lastModifiedDate":"2013-08-08T15:49:13","indexId":"ofr20131175","displayToPublicDate":"2013-08-08T15:44:00","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":"2013-1175","title":"Economic resilience through \"One-Water\" management","docAbstract":"Disruption of water availability leads to food scarcity and loss of economic opportunity. Development of effective water-resource policies and management strategies could provide resiliance to local economies in the face of water disruptions such as drought, flood, and climate change. To accomplish this, a detailed understanding of human water use and natural water resource availability is needed. A hydrologic model is a computer software system that simulates the movement and use of water in a geographic area. It takes into account all components of the water cycle--“One Water”--and helps estimate water budgets for groundwater, surface water, and landscape features. The U.S. Geological Survey MODFLOW One-Water Integrated Hydrologic Model (MODFLOWOWHM) software and scientific methods can provide water managers and political leaders with hydrologic information they need to help ensure water security and economic resilience.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131175","usgsCitation":"Hanson, R.T., and Schmid, W., 2013, Economic resilience through \"One-Water\" management: U.S. Geological Survey Open-File Report 2013-1175, 2 p., https://doi.org/10.3133/ofr20131175.","productDescription":"2 p.","numberOfPages":"2","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":276247,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131175.jpg"},{"id":276245,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1175/"},{"id":276246,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1175/pdf/ofr20131175.pdf"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5204afd8e4b0403aa62629aa","contributors":{"authors":[{"text":"Hanson, Randall T. 0000-0002-9819-7141 rthanson@usgs.gov","orcid":"https://orcid.org/0000-0002-9819-7141","contributorId":801,"corporation":false,"usgs":true,"family":"Hanson","given":"Randall","email":"rthanson@usgs.gov","middleInitial":"T.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":482301,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schmid, Wolfgang","contributorId":84020,"corporation":false,"usgs":false,"family":"Schmid","given":"Wolfgang","affiliations":[{"id":13040,"text":"Department of Hydrology and Water Resources, University of Arizona","active":true,"usgs":false}],"preferred":false,"id":482302,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70047523,"text":"ds783 - 2013 - Locations and attributes of wind turbines in New Mexico, 2011","interactions":[],"lastModifiedDate":"2013-08-08T12:56:48","indexId":"ds783","displayToPublicDate":"2013-08-08T12:50:00","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":"783","title":"Locations and attributes of wind turbines in New Mexico, 2011","docAbstract":"This dataset represents an update to U.S. Geological Survey Data Series 596. Locations and attributes of wind turbines in New Mexico, 2009 (available at http://pubs.usgs.gov/ds/596/).This updated New Mexico wind turbine Data Series provides geospatial data for all 562 wind turbines established within the State of New Mexico as of June 2011, an increase of 155 wind turbines from 2009.\n\nAttributes specific to each turbine include: turbine location, manufacturer and model, rotor diameter, hub height, rotor height, potential megawatt output, land ownership, county, and development status of wind turbine. Wind energy facility data for each turbine include: facility name, facility power capacity, number of turbines associated with each facility to date, facility developer, facility ownership, and year the facility went online. The locations of turbines are derived from 1-meter true-color aerial photographs produced by the National Agriculture Imagery Program (NAIP); the photographs have a positional accuracy of about &plusmn;5 meters. The locations of turbines constructed during or prior to August 2009 are based on August 2009 NAIP imagery and turbine locations constructed after August 2009 were based June 2011 NAIP imagery. The location of turbines under construction during June 2011 likely will be less accurate than the location of existing turbines.\n\nThis data series contributes to an Online Interactive Energy Atlas developed by the U.S. Geological Survey (http://my.usgs.gov/eerma/). The Energy Atlas synthesizes data on existing and potential energy development in Colorado and New Mexico and includes additional natural resource data layers. This information may be used by decisionmakers to evaluate and compare the potential benefits and tradeoffs associated with different energy development strategies or scenarios. Interactive maps, downloadable data layers, comprehensive metadata, and decision-support tools also are included in the Energy Atlas. The format of the Energy Atlas is designed to facilitate the integration of information about energy with key terrestrial and aquatic resources for evaluating resource values and minimizing risks from energy development.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds783","usgsCitation":"Carr, N.B., Diffendorfer, J.B., Fancher, T.S., Hawkins, S.J., Latysh, N., Leib, K.J., and Matherne, A.M., 2013, Locations and attributes of wind turbines in New Mexico, 2011: U.S. Geological Survey Data Series 783, 3 p.; Downloads Directory, https://doi.org/10.3133/ds783.","productDescription":"3 p.; Downloads Directory","numberOfPages":"3","onlineOnly":"Y","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":276221,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds783.png"},{"id":276220,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/783/downloads/"},{"id":276218,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/783/"},{"id":276219,"type":{"id":1,"text":"Abstract"},"url":"https://pubs.usgs.gov/ds/783/pdf/DS783_abstract-508.pdf"}],"country":"United States","state":"New Mexico","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -109.05,31.33 ], [ -109.05,37.0 ], [ -103.0,37.0 ], [ -103.0,31.33 ], [ -109.05,31.33 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5204afdae4b0403aa62629b2","contributors":{"authors":[{"text":"Carr, Natasha B. 0000-0002-4842-0632 carrn@usgs.gov","orcid":"https://orcid.org/0000-0002-4842-0632","contributorId":1918,"corporation":false,"usgs":true,"family":"Carr","given":"Natasha","email":"carrn@usgs.gov","middleInitial":"B.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":482257,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Diffendorfer, James B.","contributorId":62120,"corporation":false,"usgs":true,"family":"Diffendorfer","given":"James","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":482260,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fancher, Tammy S. 0000-0002-1318-3614 fanchert@usgs.gov","orcid":"https://orcid.org/0000-0002-1318-3614","contributorId":3788,"corporation":false,"usgs":true,"family":"Fancher","given":"Tammy","email":"fanchert@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":482258,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hawkins, Sarah J. 0000-0002-1878-9121 shawkins@usgs.gov","orcid":"https://orcid.org/0000-0002-1878-9121","contributorId":4818,"corporation":false,"usgs":true,"family":"Hawkins","given":"Sarah","email":"shawkins@usgs.gov","middleInitial":"J.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":482259,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Latysh, Natalie 0000-0003-0149-3962 nlatysh@usgs.gov","orcid":"https://orcid.org/0000-0003-0149-3962","contributorId":1356,"corporation":false,"usgs":true,"family":"Latysh","given":"Natalie","email":"nlatysh@usgs.gov","affiliations":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true},{"id":5060,"text":"Data Preservation Program","active":true,"usgs":true}],"preferred":true,"id":482256,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Leib, Kenneth J. 0000-0002-0373-0768 kjleib@usgs.gov","orcid":"https://orcid.org/0000-0002-0373-0768","contributorId":701,"corporation":false,"usgs":true,"family":"Leib","given":"Kenneth","email":"kjleib@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":true,"id":482255,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Matherne, Anne Marie 0000-0002-5873-2226 matherne@usgs.gov","orcid":"https://orcid.org/0000-0002-5873-2226","contributorId":303,"corporation":false,"usgs":true,"family":"Matherne","given":"Anne","email":"matherne@usgs.gov","middleInitial":"Marie","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":482254,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70047522,"text":"ds782 - 2013 - Locations and attributes of wind turbines in Colorado, 2011","interactions":[],"lastModifiedDate":"2013-08-08T12:42:22","indexId":"ds782","displayToPublicDate":"2013-08-08T12:32:00","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":"782","title":"Locations and attributes of wind turbines in Colorado, 2011","docAbstract":"This dataset represents an update to U.S. Geological Survey Data Series 597. Locations and attributes of wind turbines in Colorado, 2009 (available at http://pubs.usgs.gov/ds/597/). This updated Colorado wind turbine Data Series provides geospatial data for all 1,204 wind turbines established within the State of Colorado as of September 2011, an increase of 297 wind turbines from 2009.\n\nAttributes specific to each turbine include: turbine location, manufacturer and model, rotor diameter, hub height, rotor height, potential megawatt output, land ownership, county, and development status of the wind turbine. Wind energy facility data for each turbine include: facility name, facility power capacity, number of turbines associated with each facility to date, facility developer, facility ownership, and year the facility went online. The locations of turbines are derived from 1-meter true-color aerial photographs produced by the National Agriculture Imagery Program (NAIP); the photographs have a positional accuracy of about &plusmn;5 meters. Locations of turbines constructed during or prior to August 2009 are based on August 2009 NAIP imagery and turbine locations constructed after August 2009 were based on September 2011 NAIP imagery. The location of turbines under construction during September 2011 likely will be less accurate than the location of existing turbines.\n\nThis data series contributes to an Online Interactive Energy Atlas developed by the U.S. Geological Survey (http://my.usgs.gov/eerma/). The Energy Atlas synthesizes data on existing and potential energy development in Colorado and New Mexico and includes additional natural resource data layers. This information may be used by decisionmakers to evaluate and compare the potential benefits and tradeoffs associated with different energy development strategies or scenarios. Interactive maps, downloadable data layers, comprehensive metadata, and decision-support tools also are included in the Energy Atlas. 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]}