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The profile in this issue describes the Map Section of the Geological Survey Library.
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This report presents two detailed cross sections of the Eocene Green River Formation in the Piceance Basin, northwestern Colorado, constructed from eight detailed measured sections, fourteen core holes, and two rotary holes. The Eocene Green River Formation in the Piceance Basin contains the world’s largest known oil shale deposit with more than 1.5 billion barrels of oil in place. It was deposited in Lake Uinta, a long-lived saline lake that once covered much of the Piceance Basin and the Uinta Basin to the west. The cross sections extend across the northern and eastern margins of the Piceance Basin and are intended to aid in correlating between surface sections and the subsurface in the basin.
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Landsat 5 and moderate resolution imaging spectro-radiometer satellite imagery were used to map the area of inundation of Lake Champlain, which forms part of the border between New York and Vermont, during May 2011. During this month, the lake’s water levels were record high values not observed in the previous 150 years. Lake inundation area determined from the satellite imagery is correlated with lake stage measured at three U.S. Geological Survey lake level gages to provide estimates of lake area at different lake levels (stage/area rating) and also compared with the levels of the high-water marks (HWMs) located on the Vermont side of the lake. The rating developed from the imagery shows a somewhat different relation than a similar stage/area rating developed from a medium-resolution digital elevation model (DEM) of the region. According to the rating derived from the imagery, the lake surface area during the peak lake level increased by about 17 percent above the average or “normal” lake level. By using a comparable rating developed from the DEM, the increase above average is estimated to be about 12 percent. The northern part of the lake (north of Burlington) showed the largest amount of flooding. Based on intersecting the inundation maps with the medium-resolution DEM, lake levels were not uniform around the lake. This is also evident from the lake level gage measurements and HWMs. The gage data indicate differences up to 0.5 feet between the northern and southern end of the lake. Additionally, the gage data show day-to-day and intradaily variation of the same range (0.5 foot). The high-water mark observations show differences up to 2 feet around the lake, with the highest level generally along the south- and west-facing shorelines. The data suggest that during most of May 2011, water levels were slightly higher and less variable in the northern part of the lake. These phenomena may be caused by wind effects as well as proximity to major river inputs to the lake. The inundation areas generated from the imagery generally coincide with flood mapping as estimated by the Federal Emergency Management Agency (FEMA) and shown on its digital flood insurance rate maps. Where areas in the flood inundation map derived from the imagery and the FEMA estimated flooded areas differ substantially, this difference may be due to differences between the flood magnitude at the time of the image and the assumed flood condition used for the FEMA modeling and mapping, wind/storage effects not accounted for by the FEMA modeling, and the resolution of the image compared to the DEM used in the FEMA mapping.
This report synthesizes current (2024) science-based knowledge related to the impacts of climate change on big sagebrush vegetation in Western North America. This effort was conducted through the U.S. Geological Survey working with the Bureau of Land Management as part of multiple science syntheses to aid management agencies developing environmental impacts assessments in response to human-related or caused events. This report reviews the potential impacts climate change may have on sagebrush vegetation and related management decisions. The body of the synthesis introduces the diverse impacts of climate change across the region by first focusing directly on what climate change may entail in terms of altered temperature and precipitation patterns. The report then discusses how these changes could likely affect individual plant species based on experimental results and scale the impacts to species distributions and community composition. The synthesis section ends by surveying efforts to model potential future changes in habitat. The report goes on to link the synthesis conclusions to individual land uses or land management decisions, such as forage resources, restoration or fuel treatment. Finally, the report provides a section that discusses the pros and cons of available datasets that model the potential future of vegetation in the sagebrush region.
The Marble exploration hole 3 is in the northern part of the Tippipah Spring NE 7-1/2 minute quadrangle at the north end of Yucca Valley (fig.1). The collar elevation of the hole is about 5,316 feet and has the approximate Nevada State coordinates of N. 903,093 and E. 674,870. The hole was drilled to determine the physical and chemical properties of the marble within a radius of 200 feet of a point 950 feet below the surface. The exploration hole is 978 feet deep and was drilled from June 12 to July 8, 1959, by Minerals Engineering Co. of Grand Junction, Colorado, using conventional NX coring equiipment and a Portadrill 2,500 drill rig. Water-base bentonitic mud was used as the drilling fluid in the upper part of the hole. Clear water was used after circulation became unrestorable below 200 feet. The hole was cased from surface to 20 feet. The drilling rate during coring ranged from 2.0 to 19.3 minutes per foot and averaged 4.6 minutes per foot (table 1). The core recovered was excellent in quality and quantity. The average core recovery is 92.7 percent (table 2).
Geospatial data describing the topography, natural features, human-built features, and land uses of a particular area or region can come from independent data providers and, therefore, vary in format, data encoding, and geographic coverage. Because of the complexity of the processes and procedures required for unifying these heterogeneous data into a dataset with consistent format, encoding, and coverage, fully automated procedures for data unification do not exist. However, a combination of manual and automated procedures—semi-automated methods—can substantially reduce the time required for data unification while improving accuracy. This report presents three semi-automated data-unification methods in detail. Although these methods are not new in principle, their details are the result of original development work, and they serve as examples that can be reused, adapted, or generalized to provide head starts to future data-unification projects. The format of this report can be used and refined to encourage the publication of future reports and more widespread sharing of semi-automated methods.