{"title":"Isostatic gravity map of Mountain Pass and vicinity, California and Nevada","authors":"D. Ponce, K. Denton","doi":"10.3133/sim3412a","DOIUrl":"https://doi.org/10.3133/sim3412a","url":null,"abstract":"","PeriodicalId":36283,"journal":{"name":"U.S. Geological Survey Scientific Investigations Map","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69293647","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
CR–CO–LN–01–14 39.2750272 106.346184 3236 3 2.73 0.9999 0 0.2766 25.271 970±22 7.07±0.16 47.40±1.25 6.70±0.23 20.66±0.48 2.32 21.29±0.57 2.66 1.03 CR–CO–LN–02–14 39.2748902 106.347121 3030 3 2.73 0.9999 0 0.2783 41.551 1,475±26 6.59±0.12 44.20±1.16 6.71±0.21 19.45±0.35 1.78 20.04±0.53 2.65 1.03 CR–CO–LN–03–14 39.2760246 106.348754 3030 3 2.73 0.9999 0 0.2791 30.354 977±33 5.98±0.20 40.80±1.27 6.82±0.31 17.81±0.60 3.36 18.68±0.59 3.14 1.05 Cblk–3509–1 -------0.2808 -4±01 --------CR–CO–HR–06–11 39.3550122 106.370884 3248 3 2.73 0.9996 0 0.2697 15.703 539±15 6.14±0.17 44.60±1.93 7.26±0.37 15.96±0.44 2.73 17.85±0.78 4.37 1.12 CR–CO–LN–01–11 39.3415053 106.368624 3236 3 2.73 0.9999 0 0.2875 27.647 978±24 6.76±0.17 46.00±1.65 6.80±0.30 17.63±0.45 2.52 18.50±0.67 3.62 1.05 CR–CO–LN–02–11 39.3209233 106.340185 3036 3 2.73 0.9995 0 0.2801 19.716 815±14 7.69±0.14 51.40±1.41 6.68±0.22 22.17±0.39 1.78 22.83±0.63 2.77 1.03 CR–CO–LN–03–11 39.3231251 106.341468 3036 3 2.73 0.9995 0 0.2825 20.025 1,119±21 10.50±0.20 69.20±2.19 6.59±0.24 29.55±0.56 1.91 30.04±0.97 3.21 1.02 CR–CO–LN–04–11 39.33184 106.354525 3067 3 2.73 0.9998 0 0.2818 39.845 1,358±21 6.40±0.10 43.00±1.18 6.72±0.21 18.52±0.29 1.57 19.14±0.53 2.77 1.03 CR–CO–LN–05–11 39.3305518 106.35682 3064 3 2.73 0.9992 0 0.2842 24.561 763±21 5.87±0.16 39.10±1.30 6.66±0.29 17.12±0.48 2.79 17.58±0.59 3.36 1.03 Cblk–3436–2 -------0.2876 -5±1 --------Cblk–3436–1 -------0.2828 -4±1 --------Blank sample measured for instrument calibration. Table 1. Be and Al cosmogenic radionuclide sample data and age analyses. Sampling was carried out following established procedures outlined in Gosse and Phillips (2001). This included recording elevation, latitude, longitude, and topographic shielding data for each sample location, which accounts for any hindrance to Be and Al production from the surrounding skyline. Ages of samples were calculated using the CRONUS-Earth online calculator V.2.2 following the time-invariant scaling model of Lal (1991) and Stone (2000). Uncertainties are reported at the 1 sigma (σ) (±9 percent external uncertainty; Balco and others, 2008). Consistent with past studies within the region, no corrections for erosion or snow cover were applied, which allows for comparison with previous Be chronologies reported for the upper Arkansas River valley and central Colorado (Guido and others, 2007; Briner, 2009; Ward and others, 2009; Young and others, 2011) when adjustments for production rates are made. 39° 39°30'
{"title":"Geologic map of the Leadville North 7.5’ quadrangle, Eagle and Lake Counties, Colorado","authors":"C. A. Ruleman, T. Brandt, M. Caffee, B. Goehring","doi":"10.3133/sim3400","DOIUrl":"https://doi.org/10.3133/sim3400","url":null,"abstract":"CR–CO–LN–01–14 39.2750272 106.346184 3236 3 2.73 0.9999 0 0.2766 25.271 970±22 7.07±0.16 47.40±1.25 6.70±0.23 20.66±0.48 2.32 21.29±0.57 2.66 1.03 CR–CO–LN–02–14 39.2748902 106.347121 3030 3 2.73 0.9999 0 0.2783 41.551 1,475±26 6.59±0.12 44.20±1.16 6.71±0.21 19.45±0.35 1.78 20.04±0.53 2.65 1.03 CR–CO–LN–03–14 39.2760246 106.348754 3030 3 2.73 0.9999 0 0.2791 30.354 977±33 5.98±0.20 40.80±1.27 6.82±0.31 17.81±0.60 3.36 18.68±0.59 3.14 1.05 Cblk–3509–1 -------0.2808 -4±01 --------CR–CO–HR–06–11 39.3550122 106.370884 3248 3 2.73 0.9996 0 0.2697 15.703 539±15 6.14±0.17 44.60±1.93 7.26±0.37 15.96±0.44 2.73 17.85±0.78 4.37 1.12 CR–CO–LN–01–11 39.3415053 106.368624 3236 3 2.73 0.9999 0 0.2875 27.647 978±24 6.76±0.17 46.00±1.65 6.80±0.30 17.63±0.45 2.52 18.50±0.67 3.62 1.05 CR–CO–LN–02–11 39.3209233 106.340185 3036 3 2.73 0.9995 0 0.2801 19.716 815±14 7.69±0.14 51.40±1.41 6.68±0.22 22.17±0.39 1.78 22.83±0.63 2.77 1.03 CR–CO–LN–03–11 39.3231251 106.341468 3036 3 2.73 0.9995 0 0.2825 20.025 1,119±21 10.50±0.20 69.20±2.19 6.59±0.24 29.55±0.56 1.91 30.04±0.97 3.21 1.02 CR–CO–LN–04–11 39.33184 106.354525 3067 3 2.73 0.9998 0 0.2818 39.845 1,358±21 6.40±0.10 43.00±1.18 6.72±0.21 18.52±0.29 1.57 19.14±0.53 2.77 1.03 CR–CO–LN–05–11 39.3305518 106.35682 3064 3 2.73 0.9992 0 0.2842 24.561 763±21 5.87±0.16 39.10±1.30 6.66±0.29 17.12±0.48 2.79 17.58±0.59 3.36 1.03 Cblk–3436–2 -------0.2876 -5±1 --------Cblk–3436–1 -------0.2828 -4±1 --------Blank sample measured for instrument calibration. Table 1. Be and Al cosmogenic radionuclide sample data and age analyses. Sampling was carried out following established procedures outlined in Gosse and Phillips (2001). This included recording elevation, latitude, longitude, and topographic shielding data for each sample location, which accounts for any hindrance to Be and Al production from the surrounding skyline. Ages of samples were calculated using the CRONUS-Earth online calculator V.2.2 following the time-invariant scaling model of Lal (1991) and Stone (2000). Uncertainties are reported at the 1 sigma (σ) (±9 percent external uncertainty; Balco and others, 2008). Consistent with past studies within the region, no corrections for erosion or snow cover were applied, which allows for comparison with previous Be chronologies reported for the upper Arkansas River valley and central Colorado (Guido and others, 2007; Briner, 2009; Ward and others, 2009; Young and others, 2011) when adjustments for production rates are made. 39° 39°30'","PeriodicalId":36283,"journal":{"name":"U.S. Geological Survey Scientific Investigations Map","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69293472","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Clearwater Lake, on the Black River near Piedmont in Reynolds County, Missouri, (fig. 1) was constructed in 1948 and is operated by the U.S. Army Corps of Engineers (USACE) for flood-risk reduction, recreation, and fish and wildlife habitat (U.S. Army Corps of Engineers, [n.d.]). The lake area is about 1,800 acres with about 34 miles of shoreline at the conservation pool elevation of 498 feet (ft). Since the completion of the lake in 1948, sedimentation likely has caused the storage capacity of the lake to decrease gradually. The loss of storage capacity can decrease the effectiveness of the lake to mitigate flooding, and excessive sediment accumulation also can reduce aquatic habitat in some areas of the lake. Many lakes operated by the USACE have periodic bathymetric and sediment surveys to monitor the status of the lake. The U.S. Geological Survey completed one such survey of Clearwater Lake in 2008 during a period of high lake level using bathymetric surveying equipment consisting of a multibeam echosounder (MBES), a singlebeam echosounder, 1/3 arc-second National Elevation Dataset data (used outside the MBES survey extent; https://nationalmap. gov/elevation.html), and the waterline derived from 2008 aerial light detection and ranging (lidar) data (Richards, 2013). In May 2017, the U.S. Geological Survey, in cooperation with the USACE, surveyed the bathymetry of Clearwater Lake to prepare an updated bathymetric map and a surface area and capacity table. The 2008 survey was contrasted with the 2017 survey to document the changes in the bathymetric surface of the lake.
{"title":"Bathymetric contour map, surface area and capacity table, and bathymetric difference map for Clearwater Lake near Piedmont, Missouri, 2017","authors":"Joseph M. Richards, R. Huizinga","doi":"10.3133/sim3409","DOIUrl":"https://doi.org/10.3133/sim3409","url":null,"abstract":"Clearwater Lake, on the Black River near Piedmont in Reynolds County, Missouri, (fig. 1) was constructed in 1948 and is operated by the U.S. Army Corps of Engineers (USACE) for flood-risk reduction, recreation, and fish and wildlife habitat (U.S. Army Corps of Engineers, [n.d.]). The lake area is about 1,800 acres with about 34 miles of shoreline at the conservation pool elevation of 498 feet (ft). Since the completion of the lake in 1948, sedimentation likely has caused the storage capacity of the lake to decrease gradually. The loss of storage capacity can decrease the effectiveness of the lake to mitigate flooding, and excessive sediment accumulation also can reduce aquatic habitat in some areas of the lake. Many lakes operated by the USACE have periodic bathymetric and sediment surveys to monitor the status of the lake. The U.S. Geological Survey completed one such survey of Clearwater Lake in 2008 during a period of high lake level using bathymetric surveying equipment consisting of a multibeam echosounder (MBES), a singlebeam echosounder, 1/3 arc-second National Elevation Dataset data (used outside the MBES survey extent; https://nationalmap. gov/elevation.html), and the waterline derived from 2008 aerial light detection and ranging (lidar) data (Richards, 2013). In May 2017, the U.S. Geological Survey, in cooperation with the USACE, surveyed the bathymetry of Clearwater Lake to prepare an updated bathymetric map and a surface area and capacity table. The 2008 survey was contrasted with the 2017 survey to document the changes in the bathymetric surface of the lake.","PeriodicalId":36283,"journal":{"name":"U.S. Geological Survey Scientific Investigations Map","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69293578","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
K. Turner, Ren A. Thompson, M. Cosca, R. Shroba, Christine F. Chan, L. Morgan
{"title":"Geologic map of the San Antonio Mountain area, northern New Mexico and southern Colorado","authors":"K. Turner, Ren A. Thompson, M. Cosca, R. Shroba, Christine F. Chan, L. Morgan","doi":"10.3133/SIM3417","DOIUrl":"https://doi.org/10.3133/SIM3417","url":null,"abstract":"","PeriodicalId":36283,"journal":{"name":"U.S. Geological Survey Scientific Investigations Map","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69293395","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Geologic map of the Lower Valley quadrangle, Caribou County, Idaho","authors":"H. P. Oberlindacher, R. D. Hovland, Susan T. Miller, J. Evans, Robert J. Miller","doi":"10.3133/sim3215","DOIUrl":"https://doi.org/10.3133/sim3215","url":null,"abstract":".........................................................................................................................................................................","PeriodicalId":36283,"journal":{"name":"U.S. Geological Survey Scientific Investigations Map","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69290338","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Geologic framework and hydrostratigraphy of the Edwards and Trinity aquifers within Hays County, Texas","authors":"Allan K. Clark, Diana E. Pedraza, R. R. Morris","doi":"10.3133/sim3418","DOIUrl":"https://doi.org/10.3133/sim3418","url":null,"abstract":"..........................................................................................................................................................","PeriodicalId":36283,"journal":{"name":"U.S. Geological Survey Scientific Investigations Map","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69293406","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The U.S. Geological Survey, in cooperation with the City of Sioux Falls, South Dakota, began developing a groundwater-fl ow model of the Big Sioux aquifer in 2014 that will enable the City to make more informed water management decisions, such as delineation of areas of the greatest specifi c yield, which is crucial for locating municipal wells. Innovative tools are being evaluated as part of this study that can improve the delineation of the hydrogeologic framework of the aquifer for use in development of a groundwater-fl ow model, and the approach could have transfer value for similar hydrogeologic settings. The fi rst step in developing a groundwater-fl ow model is determining the hydrogeologic framework (vertical and horizontal extents of the aquifer), which typically is determined by interpreting geologic information from drillers’ logs and surfi cial geology maps. However, well and borehole data only provide hydrogeologic information for a single location; conversely, nearly continuous geophysical data are collected along fl ight lines using airborne electromagnetic (AEM) surveys. These electromagnetic data are collected every 3 meters along a fl ight line (on average) and subsequently can be related to hydrogeologic properties. AEM data, coupled with and constrained by well and borehole data, can substantially improve the accuracy of aquifer hydrogeologic framework delineations and result in better groundwater-fl ow models. AEM data were acquired using the Resolve frequency-domain AEM system to map the Big Sioux aquifer in the region of the city of Sioux Falls. The survey acquired more than 870 line-kilometers of AEM data over a total area of about 145 square kilometers, primarily over the fl ood plain of the Big Sioux River between the cities of Dell Rapids and Sioux Falls. The U.S. Geological Survey inverted the survey data to generate resistivity-depth sections that were used in two-dimensional maps and in three-dimensional volumetric visualizations of the Earth resistivity distribution. Contact lines were drawn using a geographic information system to delineate interpreted geologic stratigraphy. The contact lines were converted to points and then interpolated into a raster surface. The methods used to develop elevation and depth maps of the hydrogeologic framework of the Big Sioux aquifer are described herein. The fi nal AEM interpreted aquifer thickness ranged from 0 to 31 meters with an average thickness of 12.8 meters. The estimated total volume of the aquifer was 1,060,000,000 cubic meters based on the assumption that the top of the aquifer is the land-surface elevation. A simple calculation of the volume (length times width times height) of a previous delineation of the aquifer estimated the aquifer volume at 378,000,000 cubic meters; thus, the estimation based on AEM data is more than twice the previous estimate. The depth to top of Sioux Quartzite, which ranged in depth from 0 to 90 meters, also was delineated from the AEM data.
{"title":"Delineation of the hydrogeologic framework of the Big Sioux aquifer near Sioux Falls, South Dakota, using airborne electromagnetic data","authors":"Kristen J. Valseth, G. C. Delzer, C. V. Price","doi":"10.3133/sim3393","DOIUrl":"https://doi.org/10.3133/sim3393","url":null,"abstract":"The U.S. Geological Survey, in cooperation with the City of Sioux Falls, South Dakota, began developing a groundwater-fl ow model of the Big Sioux aquifer in 2014 that will enable the City to make more informed water management decisions, such as delineation of areas of the greatest specifi c yield, which is crucial for locating municipal wells. Innovative tools are being evaluated as part of this study that can improve the delineation of the hydrogeologic framework of the aquifer for use in development of a groundwater-fl ow model, and the approach could have transfer value for similar hydrogeologic settings. The fi rst step in developing a groundwater-fl ow model is determining the hydrogeologic framework (vertical and horizontal extents of the aquifer), which typically is determined by interpreting geologic information from drillers’ logs and surfi cial geology maps. However, well and borehole data only provide hydrogeologic information for a single location; conversely, nearly continuous geophysical data are collected along fl ight lines using airborne electromagnetic (AEM) surveys. These electromagnetic data are collected every 3 meters along a fl ight line (on average) and subsequently can be related to hydrogeologic properties. AEM data, coupled with and constrained by well and borehole data, can substantially improve the accuracy of aquifer hydrogeologic framework delineations and result in better groundwater-fl ow models. AEM data were acquired using the Resolve frequency-domain AEM system to map the Big Sioux aquifer in the region of the city of Sioux Falls. The survey acquired more than 870 line-kilometers of AEM data over a total area of about 145 square kilometers, primarily over the fl ood plain of the Big Sioux River between the cities of Dell Rapids and Sioux Falls. The U.S. Geological Survey inverted the survey data to generate resistivity-depth sections that were used in two-dimensional maps and in three-dimensional volumetric visualizations of the Earth resistivity distribution. Contact lines were drawn using a geographic information system to delineate interpreted geologic stratigraphy. The contact lines were converted to points and then interpolated into a raster surface. The methods used to develop elevation and depth maps of the hydrogeologic framework of the Big Sioux aquifer are described herein. The fi nal AEM interpreted aquifer thickness ranged from 0 to 31 meters with an average thickness of 12.8 meters. The estimated total volume of the aquifer was 1,060,000,000 cubic meters based on the assumption that the top of the aquifer is the land-surface elevation. A simple calculation of the volume (length times width times height) of a previous delineation of the aquifer estimated the aquifer volume at 378,000,000 cubic meters; thus, the estimation based on AEM data is more than twice the previous estimate. The depth to top of Sioux Quartzite, which ranged in depth from 0 to 90 meters, also was delineated from the AEM data.","PeriodicalId":36283,"journal":{"name":"U.S. Geological Survey Scientific Investigations Map","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69292715","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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