Approximately 2 million California residents depend on groundwater from domestic wells for their drinking-water supply. The State of California, in collaboration with the U.S. Geological Survey, created the Groundwater Ambient Monitoring and Assessment Program Priority Basin Project (GAMA-PBP) to assess the quality of groundwater used for domestic supply throughout the state and determine regional vulnerabilities to drinking-water resources. Many rural households in the northern Sierra Nevada foothills (hereafter referred to as “the foothills”) use domestic wells that pump water from fractured-bedrock aquifers. In the foothills, complicated and varied regional bedrock geology can cause substantial variation in groundwater chemistry and quality over relatively short distances. This factsheet presents findings from the GAMA-PBP assessment that highlight influences of geologic factors on groundwater quality in the foothills.
{"title":"Geologic influences on the quality of groundwater used for domestic supply in the northern Sierra Nevada Foothills","authors":"Zeno F. Levy, M. Fram","doi":"10.3133/FS20213013","DOIUrl":"https://doi.org/10.3133/FS20213013","url":null,"abstract":"Approximately 2 million California residents depend on groundwater from domestic wells for their drinking-water supply. The State of California, in collaboration with the U.S. Geological Survey, created the Groundwater Ambient Monitoring and Assessment Program Priority Basin Project (GAMA-PBP) to assess the quality of groundwater used for domestic supply throughout the state and determine regional vulnerabilities to drinking-water resources. Many rural households in the northern Sierra Nevada foothills (hereafter referred to as “the foothills”) use domestic wells that pump water from fractured-bedrock aquifers. In the foothills, complicated and varied regional bedrock geology can cause substantial variation in groundwater chemistry and quality over relatively short distances. This factsheet presents findings from the GAMA-PBP assessment that highlight influences of geologic factors on groundwater quality in the foothills.","PeriodicalId":36286,"journal":{"name":"U.S. Geological Survey Fact Sheet","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69285406","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 Proximity Visualization Tool is a simple lightweight tool that can be placed on web pages that allows users to identify non-native species near Department of Interior lands. The tool works by accessing the more than 400 million species occurrence records in the Biodiversity Information Serving Our Nation (BISON) database using the BISON Application Programming Interface (API). The tool sends user-defined spatial and species selections to the BISON API, and the BISON API returns instances of non-native species near protected areas (U.S. Geological Survey Gap Analysis Project, 2018) within the selected spatial boundary. The tool is available from the BISON Examples page (htt ps://bison .usgs.gov/ examples.html). EXPLANATION
{"title":"Visualizing proximity of non-native species to protected areas of the United States—A proximity visualization tool for BISON","authors":"Travis J. Harrison, E. Hlavacek, Jennifer Dieck","doi":"10.3133/fs20213027","DOIUrl":"https://doi.org/10.3133/fs20213027","url":null,"abstract":"The Proximity Visualization Tool is a simple lightweight tool that can be placed on web pages that allows users to identify non-native species near Department of Interior lands. The tool works by accessing the more than 400 million species occurrence records in the Biodiversity Information Serving Our Nation (BISON) database using the BISON Application Programming Interface (API). The tool sends user-defined spatial and species selections to the BISON API, and the BISON API returns instances of non-native species near protected areas (U.S. Geological Survey Gap Analysis Project, 2018) within the selected spatial boundary. The tool is available from the BISON Examples page (htt ps://bison .usgs.gov/ examples.html). EXPLANATION","PeriodicalId":36286,"journal":{"name":"U.S. Geological Survey Fact Sheet","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69285583","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":"Using satellite imagery to estimate consumptive water use from irrigated lands in the Milk River Basin, United States and Canada","authors":"Roy Sando, M. Friedrichs, G. Senay","doi":"10.3133/fs20213042","DOIUrl":"https://doi.org/10.3133/fs20213042","url":null,"abstract":"","PeriodicalId":36286,"journal":{"name":"U.S. Geological Survey Fact Sheet","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69285818","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":"Hydrologic conditions in Kansas, water year 2020","authors":"Chantelle Davis","doi":"10.3133/fs20213045","DOIUrl":"https://doi.org/10.3133/fs20213045","url":null,"abstract":"","PeriodicalId":36286,"journal":{"name":"U.S. Geological Survey Fact Sheet","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69285896","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 ShBOQ-1 geochemical reference material is relevant to studies of the organic geochemistry and mineralogy of petroleum source rocks containing high concentrations of carbonate minerals and organic sulfur-rich, oil-prone marine organic matter. ShBOQ-1 is geochemically and mineralogically similar to the lower part of the Upper Cretaceous Eagle Ford Shale.
{"title":"Geochemical and mineralogical properties of Boquillas Shale geochemical reference material ShBOQ-1","authors":"J. Birdwell, S. Wilson","doi":"10.3133/fs20213048","DOIUrl":"https://doi.org/10.3133/fs20213048","url":null,"abstract":"The ShBOQ-1 geochemical reference material is relevant to studies of the organic geochemistry and mineralogy of petroleum source rocks containing high concentrations of carbonate minerals and organic sulfur-rich, oil-prone marine organic matter. ShBOQ-1 is geochemically and mineralogically similar to the lower part of the Upper Cretaceous Eagle Ford Shale.","PeriodicalId":36286,"journal":{"name":"U.S. Geological Survey Fact Sheet","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69285992","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":"Water priorities for the Nation—USGS Integrated Water Science basins","authors":"Mark P. Miller, S. Eberts, L. Sprague","doi":"10.3133/fs20213041","DOIUrl":"https://doi.org/10.3133/fs20213041","url":null,"abstract":"","PeriodicalId":36286,"journal":{"name":"U.S. Geological Survey Fact Sheet","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69285764","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}
Broadband, which is a high-speed, always-on internet connection, is critical to the modern economy and education, as well as to healthcare, public safety, government services, entertainment, and more. However, according to the Federal Communications Commission (FCC), millions of Americans in rural parts of the country currently lack access to broadband. Federal and State agencies have launched initiatives to enhance broadband access in rural America. High-resolution light detection and ranging (lidar) data can play a role in improving maps of broadband accessibility and helping to strengthen the broadband communications network. Lidar underpins signal propagation analyses to determine where broadband signals from communication towers can and cannot reach across the landscape and can be used to determine optimal siting of new towers and cell stations to increase broadband coverage. The 3D Elevation Program (3DEP; see sidebar) is managed by the U.S. Geological Survey in partnership with Federal, State, Tribal, U.S. territorial, and local agencies to acquire consistent lidar coverage for the Nation. Lidar provides high-resolution, very accurate three-dimensional (3D) data representations of constructed and natural features on the Earth’s surface. Bare-earth and digital surface models derived from lidar are used in viewshed analyses for signal propagation studies necessary to identify the optimum locations for cell tower and cell station networks. Viewshed analysis, also known as line-of-sight analysis, determines the visibility of objects or areas from different points of view, such as from the top of a transmission tower (fig. 1). Objects such as buildings, hills, and other features (referred to as clutter in the communications industry) can attenuate or block signals, which reduces the coverage area of a broadband signal transmitter.
宽带是一种高速、永远在线的互联网连接，对现代经济和教育，以及医疗保健、公共安全、政府服务、娱乐等都至关重要。然而，根据联邦通信委员会(FCC)的数据，美国农村地区目前有数百万人无法接入宽带。联邦和州政府机构已经启动了加强美国农村宽带接入的计划。高分辨率光探测和测距(激光雷达)数据可以在改善地图的宽带可及性和帮助加强宽带通信网络方面发挥作用。激光雷达支持信号传播分析，以确定来自通信塔的宽带信号可以到达和不能到达的位置，并可用于确定新塔和蜂窝站的最佳位置，以增加宽带覆盖范围。3D Elevation Program (3DEP);(见侧栏)由美国地质调查局与联邦、州、部落、美国领土和地方机构合作管理，以获得全国一致的激光雷达覆盖范围。激光雷达提供高分辨率，非常精确的三维(3D)数据表示地球表面的建筑和自然特征。从激光雷达获得的裸地和数字表面模型用于信号传播研究的视域分析，这是确定蜂窝塔和蜂窝站网络的最佳位置所必需的。视域分析，也称为视距分析，从不同的角度确定物体或区域的可见性，例如从发射塔的顶部(图1)。建筑物、山丘和其他特征(在通信行业中称为杂波)等物体会衰减或阻挡信号，从而减少宽带信号发射机的覆盖面积。
{"title":"3D Elevation Program supports broadband internet access","authors":"C. Thatcher, V. Lukas","doi":"10.3133/fs20213056","DOIUrl":"https://doi.org/10.3133/fs20213056","url":null,"abstract":"Broadband, which is a high-speed, always-on internet connection, is critical to the modern economy and education, as well as to healthcare, public safety, government services, entertainment, and more. However, according to the Federal Communications Commission (FCC), millions of Americans in rural parts of the country currently lack access to broadband. Federal and State agencies have launched initiatives to enhance broadband access in rural America. High-resolution light detection and ranging (lidar) data can play a role in improving maps of broadband accessibility and helping to strengthen the broadband communications network. Lidar underpins signal propagation analyses to determine where broadband signals from communication towers can and cannot reach across the landscape and can be used to determine optimal siting of new towers and cell stations to increase broadband coverage. The 3D Elevation Program (3DEP; see sidebar) is managed by the U.S. Geological Survey in partnership with Federal, State, Tribal, U.S. territorial, and local agencies to acquire consistent lidar coverage for the Nation. Lidar provides high-resolution, very accurate three-dimensional (3D) data representations of constructed and natural features on the Earth’s surface. Bare-earth and digital surface models derived from lidar are used in viewshed analyses for signal propagation studies necessary to identify the optimum locations for cell tower and cell station networks. Viewshed analysis, also known as line-of-sight analysis, determines the visibility of objects or areas from different points of view, such as from the top of a transmission tower (fig. 1). Objects such as buildings, hills, and other features (referred to as clutter in the communications industry) can attenuate or block signals, which reduces the coverage area of a broadband signal transmitter.","PeriodicalId":36286,"journal":{"name":"U.S. Geological Survey Fact Sheet","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69286075","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}
D. Houseknecht, T. Mercier, C. J. Schenk, T. Moore, W. Rouse, J. Dumoulin, W. Craddock, R. Lease, P. Botterell, M. Sanders, Rebecca A. Smith, C. Connors, C. P. Garrity, K. Whidden, J. Gooley, J. Counts, J. Long, C. DeVera
The U.S. Geological Survey (USGS) assessed the potential for undiscovered, technically recoverable gas resources in conventional accumulations in Upper Devonian to Lower Cretaceous strata of the western North Slope of Alaska, including adjacent State waters (fig. 1). The western North Slope lies north of the Brooks Range, west of the National Petroleum Reserve−Alaska (NPR−A), and east of the Chukchi Sea. The western North Slope was included in previous assessments of (1) conventional resources of the Cretaceous Nanushuk and Torok Formations in the NPR−A and adjacent areas (Houseknecht and others, 2017) and (2) continuous resources of the entire North Slope (Houseknecht and others, 2012). Thus, rocks considered in this assessment are limited to strata older than the Torok Formation and younger than the acoustic basement (fig. 2). The assessment area contains sparse subsurface data, including three exploration wells (fig. 1) drilled between 1978 and 1982 and about 500 miles (800 kilometers) of vintage (1970−1971) two-dimensional (2D) seismic data. These were supplemented by geologic maps of the western North Slope and adjacent areas (for example, Mull and others, 2000). Additional well and 2D seismic data from the NPR−A and Chukchi Sea were used to construct a more robust geologic framework for the assessment. Using a geology-based assessment methodology, the U.S. Geological Survey estimated a mean of 1,407 billion (1.4 trillion) cubic feet of gas in conventional accumulations in Upper Devonian to Lower Cretaceous strata of the western North Slope, Alaska.
{"title":"Assessment of undiscovered gas resources in Upper Devonian to Lower Cretaceous strata of the western North Slope, Alaska, 2021","authors":"D. Houseknecht, T. Mercier, C. J. Schenk, T. Moore, W. Rouse, J. Dumoulin, W. Craddock, R. Lease, P. Botterell, M. Sanders, Rebecca A. Smith, C. Connors, C. P. Garrity, K. Whidden, J. Gooley, J. Counts, J. Long, C. DeVera","doi":"10.3133/FS20213003","DOIUrl":"https://doi.org/10.3133/FS20213003","url":null,"abstract":"The U.S. Geological Survey (USGS) assessed the potential for undiscovered, technically recoverable gas resources in conventional accumulations in Upper Devonian to Lower Cretaceous strata of the western North Slope of Alaska, including adjacent State waters (fig. 1). The western North Slope lies north of the Brooks Range, west of the National Petroleum Reserve−Alaska (NPR−A), and east of the Chukchi Sea. The western North Slope was included in previous assessments of (1) conventional resources of the Cretaceous Nanushuk and Torok Formations in the NPR−A and adjacent areas (Houseknecht and others, 2017) and (2) continuous resources of the entire North Slope (Houseknecht and others, 2012). Thus, rocks considered in this assessment are limited to strata older than the Torok Formation and younger than the acoustic basement (fig. 2). The assessment area contains sparse subsurface data, including three exploration wells (fig. 1) drilled between 1978 and 1982 and about 500 miles (800 kilometers) of vintage (1970−1971) two-dimensional (2D) seismic data. These were supplemented by geologic maps of the western North Slope and adjacent areas (for example, Mull and others, 2000). Additional well and 2D seismic data from the NPR−A and Chukchi Sea were used to construct a more robust geologic framework for the assessment. Using a geology-based assessment methodology, the U.S. Geological Survey estimated a mean of 1,407 billion (1.4 trillion) cubic feet of gas in conventional accumulations in Upper Devonian to Lower Cretaceous strata of the western North Slope, Alaska.","PeriodicalId":36286,"journal":{"name":"U.S. Geological Survey Fact Sheet","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69285206","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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