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TwitterThis data release contains data used to develop models and maps that estimate the occurrence of lithium in groundwater used as drinking water throughout the conterminous United States. An extreme gradient boosting model was developed to estimate the most probable lithium concentration category (≤4, >4 to ≤10, >10 to ≤30 or >30 µg/L). The model uses lithium concentration data from wells located throughout the conterminous United States and predictor variables that are available as geospatial data. The model is included in this data release in the zipped folder named Model_Archive and was used to produce maps that are also included in this data release. The model input data (predictor variables) that were used to make the maps are within a zipped folder (Map_Input_Data.zip) that contains 20 tif-raster files, one for each model predictor variable. The map probability estimates that are outputs from the model are in a zipped folder (Map_Output_Data.zip) that contains 10 tif-raster files, two model estimate maps for each of the lithium concentration categories and the category with the highest probability for public supply well depths and domestic supply well depths.
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TwitterThe Dynamic Surface Water Extent MODIS (DSWEmod) surface water maps for the conterminous United States were used for a study conducted by the U.S. Geological Survey (USGS) Patterns in the Landscape - Analyses of Cause and Effect (PLACE) team quantifying seasonal and annual surface water trends within Environmental Protection Agency (EPA) Level I and Level III Ecoregions (Omernik, 1987) across the U.S. from 2003 through 2019. The overarching objectives of this study were to, (i) generate the monthly DSWEmod maps for the conterminous United States, (ii) review the spatial and temporal dynamics of surface water extent across ecoregions, and (iii) compare surface water area trends to streamgage discharge trends to determine where and how well different approaches to measuring water dynamics align. The DSWEmod model classifies the landscape (i.e., each 250-meter Moderate Resolution Imaging Spectroradiometer, or MODIS, pixel) into different classes of surface water based on quantified levels of confidence, including, (i) high-confidence surface water (class 1), (ii) moderate-confidence surface water (class 2), (iii) potential wetland (class 3), and (iv) low-confidence water/wetland (class 4), as well as a not-water class (class 0) and a no-data class (class 9). The confidence level is based on thresholds within various water- and vegetation-based indices. The level of confidence is based on how many, and, which index thresholds are met. Only high-confidence surface water (class 1) was considered in this study. This data release includes a vector shapefile consisting of 85 polygons, delineating EPA Level III Ecoregions for the conterminous United States. For each Level III Ecoregion, we include attributes identifying, (i) their respective Level I Ecoregion name and identification number, (ii) quantified seasonal and overall mean water area, (iii) comparisons with U.S. Geological Survey (USGS) National Water Information System (NWIS) streamgage discharge trends, (iv) mean surface water extent statistics (mean, minimum, maximum, standard deviation, coefficient of variation, percent of ecoregion), and (v) seasonal and overall results from the Mann-Kendall statistical analysis. An associated manuscript describes the methodology, results, and conclusions from this study.
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TwitterMembers from the U.S. Geological Survey (USGS) Patterns in the Landscape - Analyses of Cause and Effect (PLACE) team are releasing monthly surface water maps for the conterminous United States (U.S.) from 2003 through 2019 as 250-meter resolution geoTIFF files. The maps were produced using the Dynamic Surface Water Extent (DSWE) algorithm applied to daily Moderate Resolution Imaging Spectroradiometer (MODIS) imagery (DSWEmod) (Soulard et al., 2021) - see associated items. The DSWEmod model classifies the landscape (i.e., each MODIS pixel) into different classes of surface water based on quantified levels of confidence, including, i) high-confidence surface water (class 1), ii) moderate-confidence surface water (class 2), iii) potential wetland (class 3), and iv) low-confidence water/wetland (class 4), as well as a not-water class (class 0) and a no-data class (class 9). This data release consists of a Parent Directory and 18 Child Items. The Parent Directory includes a zipped folder housing the complete monthly DSWEmod surface water maps for the conterminous United States from 2003 through 2019 represented in 17 multiband images, equating to one image for each year from 2003 through 2019. Each annual image – available as separate Child Items (n = 17) – consists of 12 bands, where each band value from 1-12 represents sequential months from January (Band 1) to December (Band 12). Such a structure allows for a user to download either the full time-series of DSWEmod products or a user-specified set of years. The DSWEmod surface water maps were used for a study conducted by the PLACE team quantifying seasonal and annual surface water trends within Environmental Protection Agency (EPA) Level I and Level III Ecoregions (Omernik, 1987) across the U.S. from 2003 through 2019. The results from this study are also being released as a Child Item - Surface Water Trends for the Conterminous United States using monthly DSWEmod Surface Water Maps, 2003–2019. This portion of the data release includes a vector shapefile consisting of 85 polygons, delineating EPA Level III Ecoregions for the conterminous United States. For each Level III Ecoregion, we include attributes identifying, (i) their respective Level I Ecoregion name and identification number, (ii) quantified seasonal and overall mean water area, (iii) comparisons with U.S. Geological Survey (USGS) National Water Information System (NWIS) streamgage discharge trends, (iv) mean surface water extent statistics (mean, minimum, maximum, standard deviation, coefficient of variation, percent of ecoregion), and (v) seasonal and overall results from the Mann-Kendall statistical analysis. An associated manuscript describes the methodology, results, and conclusions from this study.
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USGS researchers with the Patterns in the Landscape – Analyses of Cause and Effect (PLACE) project are releasing a collection of high-frequency surface water map composites derived from daily Moderate Resolution Imaging Spectroradiometer (MODIS) imagery. Using Google Earth Engine, the team developed customized image processing steps and adapted the Dynamic Surface Water Extent (DSWE) to generate surface water map composites in California for 2003-2019 at a 250-m pixel resolution. Daily maps were merged to create 6, 3, 2, and 1 composite(s) per month corresponding to approximately 5-day, 10-day, 15-day, and monthly products, respectively. The resulting maps are available as downloadable files for each year. Each file includes 72, 36, 24, or 12 bands that coincide with the number of maps generated in the 5-day, 10-day, 15-day, and monthly products, respectively. The bands are ordered chronologically, with the first band representing the beginning of the calendar year and the last b ...
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TwitterUSA Detailed Water Bodies represents the major lakes, reservoirs, large rivers, lagoons, and estuaries in the United States. To download the data for this layer as a layer package for use in ArcGIS desktop applications, refer to USA Detailed Water Bodies.
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TwitterThis map layer shows areal and linear water features of the United States, Puerto Rico, and the U.S. Virgin Islands. The original file was produced by joining the individual State hydrography layers from the 1:2,000,000- scale Digital Line Graph (DLG) data produced by the USGS. This map layer was formerly distributed as Hydrography Features of the United States. This is a revised version of the January 2003 map layer.
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TwitterThis layer provides the linear water features for geographic display and analysis at regional and national levels. It represents the linear water features (for example, aqueducts, canals, intracoastal waterways, and streams) of the United States. To download the data for this layer as a layer package for use in ArcGIS desktop applications, refer to USA National Atlas Water Feature Lines Rivers and Streams.
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TwitterStatistical analyses and maps representing mean, high, and low water-level conditions in the surface water and groundwater of Miami-Dade County were made by the U.S. Geological Survey, in cooperation with the Miami-Dade County Department of Regulatory and Economic Resources, to help inform decisions necessary for urban planning and development. Sixteen maps were created that show contours of (1) the mean of daily water levels at each site during October and May for the 2000-2009 water years; (2) the 25th, 50th, and 75th percentiles of the daily water levels at each site during October and May and for all months during 2000-2009; and (3) the differences between mean October and May water levels, as well as the differences in the percentiles of water levels for all months, between 1990-1999 and 2000-2009. The 80th, 90th, and 96th percentiles of the annual maximums of daily groundwater levels during 1974-2009 (a 35-year period) were computed to provide an indication of unusually high groundwater-level conditions. These maps and statistics provide a generalized understanding of the variations of water levels in the aquifer, rather than a survey of concurrent water levels. Water-level measurements from 473 sites in Miami-Dade County and surrounding counties were analyzed to generate statistical analyses. The monitored water levels included surface-water levels in canals and wetland areas and groundwater levels in the Biscayne aquifer. Maps were created by importing site coordinates, summary water-level statistics, and completeness of record statistics into a geographic information system, and by interpolating between water levels at monitoring sites in the canals and water levels along the coastline. Raster surfaces were created from these data by using the triangular irregular network interpolation method. The raster surfaces were contoured by using geographic information system software. These contours were imprecise in some areas because the software could not fully evaluate the hydrology given available information; therefore, contours were manually modified where necessary. The ability to evaluate differences in water levels between 1990-1999 and 2000-2009 is limited in some areas because most of the monitoring sites did not have 80 percent complete records for one or both of these periods. The quality of the analyses was limited by (1) deficiencies in spatial coverage; (2) the combination of pre- and post-construction water levels in areas where canals, levees, retention basins, detention basins, or water-control structures were installed or removed; (3) an inability to address the potential effects of the vertical hydraulic head gradient on water levels in wells of different depths; and (4) an inability to correct for the differences between daily water-level statistics. Contours are dashed in areas where the locations of contours have been approximated because of the uncertainty caused by these limitations. Although the ability of the maps to depict differences in water levels between 1990-1999 and 2000-2009 was limited by missing data, results indicate that near the coast water levels were generally higher in May during 2000-2009 than during 1990-1999; and that inland water levels were generally lower during 2000-2009 than during 1990-1999. Generally, the 25th, 50th, and 75th percentiles of water levels from all months were also higher near the coast and lower inland during 2000–2009 than during 1990-1999. Mean October water levels during 2000-2009 were generally higher than during 1990-1999 in much of western Miami-Dade County, but were lower in a large part of eastern Miami-Dade County.
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TwitterThis is the 2022 version of the Aquifer Risk Map. The 2021 version of the Aquifer Risk Map is available here.This aquifer risk map is developed to fulfill requirements of SB-200 and is intended to help prioritize areas where domestic wells and state small water systems may be accessing raw source groundwater that does not meet primary drinking water standards (maximum contaminant level or MCL). In accordance with SB-200, the risk map is to be made available to the public and is to be updated annually starting January 1, 2021. The Fund Expenditure Plan states the risk map will be used by Water Boards staff to help prioritize areas for available SAFER funding. This is the final 2022 map based upon feedback received from the 2021 map. A summary of methodology updates to the 2022 map can be found here.This map displays raw source groundwater quality risk per square mile section. The water quality data is based on depth-filtered, declustered water quality results from public and domestic supply wells. The process used to create this map is described in the 2022 Aquifer Risk Map Methodology document. Data processing scripts are available on GitHub. Download/export links are provided in this app under the Data Download widget.This draft version was last updated December 1, 2021. Water quality risk: This layer contains summarized water quality risk per square mile section and well point. The section water quality risk is determined by analyzing the long-tern (20-year) section average and the maximum recent (within 5 years) result for all sampled contaminants. These values are compared to the MCL and sections with values above the MCL are “high risk”, sections with values within 80%-100% of the MCL are “medium risk” and sections with values below 80% of the MCL are “low risk”. The specific contaminants above or close to the MCL are listed as well. The water quality data is based on depth-filtered, de-clustered water quality results from public and domestic supply wells.Individual contaminants: This layer shows de-clustered water quality data for arsenic, nitrate, 1,2,3-trichloropropane, uranium, and hexavalent chromium per square mile section. Domestic Well Density: This layer shows the count of domestic well records per square mile. The domestic well density per square mile is based on well completion report data from the Department of Water Resources Online System for Well Completion Reports, with records drilled prior to 1970 removed and records of “destruction” removed.State Small Water Systems: This layer displays point locations for state small water systems based on location data from the Division of Drinking Water.Public Water System Boundaries: This layer displays the approximate service boundaries for public water systems based on location data from the Division of Drinking Water.Reference layers: This layer contains several reference boundaries, including boundaries of CV-SALTS basins with their priority status, Groundwater Sustainability Agency boundaries, census block group boundaries, county boundaries, and groundwater unit boundaries. ArcGIS Web Application
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TwitterWater Resources is one of five science mission areas of the U.S. Geological Survey (USGS). Water Resource's mission is to collect and disseminate reliable, impartial, and timely information that is needed to understand the Nation's water resources. This database contains downloadable water-related spatial data files for exploration and analysis. Resources in this dataset:Resource Title: Maps and GIS Data. File Name: Web Page, url: https://water.usgs.gov/maps.html Downloadable spatial data files for exploration and analysis.
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TwitterU.S. Government Workshttps://www.usa.gov/government-works
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Statistical analyses and maps representing mean, high, and low water-level conditions in the surface water and groundwater of Miami-Dade County were made by the U.S. Geological Survey, in cooperation with the Miami-Dade County Department of Regulatory and Economic Resources, to help inform decisions necessary for urban planning and development. Sixteen maps were created that show contours of (1) the mean of daily water levels at each site during October and May for the 2000-2009 water years; (2) the 25th, 50th, and 75th percentiles of the daily water levels at each site during October and May and for all months during 2000-2009; and (3) the differences between mean October and May water levels, as well as the differences in the percentiles of water levels for all months, between 1990-1999 and 2000-2009. The 80th, 90th, and 96th percentiles of the annual maximums of daily groundwater levels during 1974-2009 (a 35-year period) were computed to provide an indication of unusually hig ...
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TwitterIn this dataset we present two maps that estimate the location and population served by domestic wells in the contiguous United States. The first methodology, called the “Block Group Method” or BGM, builds upon the original block-group data from the 1990 census (the last time the U.S. Census queried the population regarding their source of water) by incorporating higher resolution census block data. The second methodology, called the “Road-Enhanced Method” or REM, refines the locations by using a buffer expansion and shrinkage technique along roadways to define areas where domestic wells exist. The fundamental assumption with this method is that houses (and therefore domestic wells) are located near a named road. The results are presented as two nationally consistent domestic-well population datasets. While both methods can be considered valid, the REM map is more precise in locating domestic wells; the REM map had a smaller amount of spatial bias (nearly equal vs biased in type 1 error), total error (10.9% vs 23.7%,), and distance error (2.0 km vs 2.7 km), when comparing the REM and BGM maps to a California calibration map. However, the BGM map is more inclusive of all potential locations for domestic wells. The primary difference in the BGM and the REM is the mapping of low density areas. The REM has a 57% reduction in areas mapped as low density (populations greater than 0 but less than 1 person per km), concentrating populations into denser regions. Therefore, if one is trying to capture all of the potential areas of domestic-well usage, then the BGM map may be more applicable. If location is more imperative, then the REM map is better at identifying areas of the landscape with the highest probability of finding a domestic well. Depending on the purpose of a study, a combination of both maps can be used. For space concerns, the datasets have been divided into two separate geodatabases. The BGM map geodatabase and the REM map database.
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TwitterUSGS groundwater data, information, data, and maps for Georgia. In particular - Figure 2: Surface-water and ground-water data-collection stations in Georgia.
From site: The USGS provides maps, reports, and information to help others meet their needs to manage, develop, and protect America's water, energy, mineral, and land resources. We help find natural resources needed to build tomorrow, and supply scientific understanding needed to help minimize or mitigate the effects of natural hazards and environmental damage caused by human activities. The results of our efforts touch the daily lives of almost every American.
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TwitterThe map graphic image at https://www.sciencebase.gov/catalog/file/get/63140561d34e36012efa2b7f?name=arsenic_map.png illustrates arsenic values, in micrograms per liter, for groundwater samples from about 31,000 wells and springs in 49 states compiled by the United States Geological Survey (USGS). The map graphic illustrates an updated version of figure 1 from Ryker (2001). Cited Reference: Ryker, S.J., Nov. 2001, Mapping arsenic in groundwater-- A real need, but a hard problem: Geotimes Newsmagazine of the Earth Sciences, v. 46 no. 11, p. 34-36 at http://www.agiweb.org/geotimes/nov01/feature_Asmap.html. An excel tabular data file, a txt file, along with a GIS shape file of arsenic concentrations (20,043 samples collected by the USGS) for a subset of the sites shown on the map. Samples were collected between 1973 and 2001 and are provided for download.
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TwitterWaterWatch (http://waterwatch.usgs.gov) is a U.S. Geological Survey (USGS) World Wide Web site that displays maps, graphs, and tables describing real-time, recent, and past streamflow conditions for the United States. The real-time information generally is updated on an hourly basis. WaterWatch provides streamgage-based maps that show the location of more than 3,000 long-term (30 years or more) USGS streamgages; use colors to represent streamflow conditions compared to historical streamflow; feature a point-and-click interface allowing users to retrieve graphs of stream stage (water elevation) and flow; and highlight locations where extreme hydrologic events, such as floods and droughts, are occurring.
The streamgage-based maps show streamflow conditions for real-time, average daily, and 7-day average streamflow. The real-time streamflow maps highlight flood and high flow conditions. The 7-day average streamflow maps highlight below-normal and drought conditions.
WaterWatch also provides hydrologic unit code (HUC) maps. HUC-based maps are derived from the streamgage-based maps and illustrate streamflow conditions in hydrologic regions. These maps show average streamflow conditions for 1-, 7-, 14-, and 28-day periods, and for monthly average streamflow; highlight regions of low flow or hydrologic drought; and provide historical runoff and streamflow conditions beginning in 1901.
WaterWatch summarizes streamflow conditions in a region (state or hydrologic unit) in terms of the long-term typical condition at streamgages in the region. Summary tables are provided along with time-series plots that depict variations through time. WaterWatch also includes tables of current streamflow information and locations of flooding.
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TwitterThis map shows current flood conditions in the United States using live data from the National Weather Service, including observed flooding locations, river and precipitation forecasts, and flood warning areas. For a map that focuses on more general weather reports and current radar, see our Severe Weather Map.About the dataStream Gauges: This is Esri's Live Stream Gauges layer, symbolized to show only those gauges that are currently at or above flood stage. Click on a gauge to see the current depth, flow rate, and alert level. Five day forecasts from Advanced Hydrologic Prediction Service are shown where available.Population Density: This is Esri's World Population Estimate, which models the likely population of each 250 meter square cell, globally. It provides import context to the map, showing where flooding is likely to have a human impact.Flood Warnings (short and long term): These weather alerts are NOAA Weather Warnings, Watches, and Advisory data provided through the Common Alerting Protocol (CAP) Alert system. The long term warnings (flood warnings) are done on a county basis, while the short term warnings (flash flood and marine warnings) are more spatially precise. 72-hour Precipitation Forecast: This is the Quantitative Precipitation Forecast (QPF) from NOAA's National Digital Forecast Database. By default it shows the predicted total over the next 72 hours, but this forecast can also be viewed in six hour intervals.
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TwitterThe Red River Basin: The International Joint Commission (IJC) of Canada and the United States developed this Esri Web Map Series to provide a structured geographic overview of shared drainage basins that span the Canada-U.S. border. This series was specifically designed to be incorporated into a General Esri Story Map that serves as an introduction to transboundary watersheds, highlighting their geographic, environmental, and hydrological significance.Purpose and UseThe Web Map Series is intended to:Offer a general introduction to shared drainage basins along the Canada-U.S. boundary.Provide a consistent spatial reference for transboundary water governance and policy discussions.Serve as a foundational dataset for broader studies on hydrology, environmental management, and cross-border cooperation.Core Features of the Web Map SeriesThe features included in each Web Map vary by basin but generally include the following:Harmonized Drainage BasinsBased on datasets from the United States Geological Survey (USGS) and Environment and Climate Change Canada (ECCC).Provides a unified representation of drainage basins across the international boundary.Indigenous Communities (as interpreted by federal agencies)Displays Indigenous communities based on datasets from Canadian and U.S. federal agencies.This layer does not represent traditional or historical lands, but rather current federally recognized Indigenous lands.Water Level GaugesIncludes real-time and historical water level monitoring stations.Provides hydrological data critical for flood forecasting, drought assessment, and water resource management.Major Hydrological FeaturesDams and Diversions – Identifies hydropower facilities, flood control structures, and major water diversions impacting shared basins.Rivers and Lakes – Highlights significant hydrologic networks that define transboundary watersheds.Populated Places and Place NamesIncludes official municipalities, towns, and cities within and near the basin boundaries.Features official geographic place names from federal, state, and provincial authorities.Protected AreasDisplays Federal, State, and Provincial Parks within transboundary basins.Highlights protected lands relevant to watershed conservation and ecological management.Significance of the Web Map SeriesThe IJC Web Map Series is designed to serve as a foundational geographic tool for decision-makers, researchers, and the public to better understand the shared hydrological systems of Canada and the United States. By integrating authoritative datasets from both countries, this Web Map Series promotes a standardized approach to visualizing transboundary watersheds, supporting cooperative water resource management and policy development.Important Note: The representation of Indigenous or First Nation lands in this Web Map Series does not indicate traditional or historical territories; rather, it reflects data provided by federal agencies in Canada and the United States.This Web Map Series will continue to evolve as new datasets become available, ensuring that transboundary water governance is supported with the most up-to-date and authoritative geographic information.
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TwitterThe USGS compiles online access to water-resources data collected at approximately 1.5 million sites in all 50 States, the District of Columbia, Puerto Rico, the Virgin Islands, Guam, American Samoa and the Commonwealth of the Northern Mariana Islands.
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TwitterAttribution-ShareAlike 4.0 (CC BY-SA 4.0)https://creativecommons.org/licenses/by-sa/4.0/
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Authority In the 1963 general session, the Utah State Legislature charged the Division of Water Resources with the responsibility of developing a State Water Plan. This plan is to coordinate and direct the activities of state and federal agencies concerned with Utah’s water resources. As a part of this objective, the Division of Water Resources collects water-related land use data for the entire state. This data includes the types and extent of irrigated crops as well as information concerning phreatophytes, wet/open water areas, dry land agriculture and urban areas. The data produced by the water-related land use program are used for various planning purposes. Some of these include: determining cropland water use, evaluating irrigated land losses and conversion to urban uses, planning for new water development, estimating irrigated acreages for any area, and developing water budgets. Additionally, the data are used by many other state and federal agencies. Previous Methods The land use inventory methods used by the division in conducting water-related land use studies have varied with regard to the procedures used and the precision obtained. During the 1960s and 70s, inventories were prepared using large format vertical-aerial photographs supplemented with field surveys to label boundaries, vegetation types, and other water use information. After identifying crops and labeling photographs, the information was transferred onto a base map and then planimetered or "dot-counted" to determine the acreage. Tables for individual townships and ranges were prepared showing the amount of land in each land use category within each section. Data were then available for use in preparing water budgets. In the early 1980s, the division began updating its methodology for collecting water-related land use data to take advantage of the rapidly growing fields of Remote Sensing and computerized Geographic Information Systems (GIS). For several years during the early 1980’s, the division contracted with the University of Utah Research Institute, Center for Remote Sensing and Cartography (CRSC), to prepare water-related land use inventories. During this period, water-related land use data was obtained by using high altitude color infrared photography and laboratory interpretation, with field checking. In March 1984, several division staff members visited the California Department of Water Resources to observe its methodology for collecting water-related land use data for state water planning purposes. Based on its review of the California methodology and its own experience, the division developed a water-related land use inventory program. This program included the use of 35mm slides, United States Geological Survey (USGS) 7-1/2 minute quadrangle maps, field-mapping using base maps produced from the 35mm photography and a computerized GIS to process, store and retrieve land use data. Areas for survey were first identified from previous land use studies and any other available information. The identified areas were then photographed using an aircraft carrying a high quality 35mm single lens reflex camera mounted to focus along a vertical axis to the earth. Photos were taken between 6,000 and 6,500 feet above the ground using a 24mm lens. This procedure allowed each slide to cover a little more than one square mile with approximately 30 percent overlap on the wide side of the slide and 5 percent on the slide's narrow side. The slides were then indexed according to a flight-line number, slide number, latitude and longitude. All 35mm slides were stored in files at the division offices and cataloged according to township, range and section, and quadrangle map location. Water-related land use areas were then transferred from the slide to USGS 7-1/2 minute quadrangle maps using a standard slide projector with a 100-200mm zoom lens. This step allowed the technician to project the slide onto the back of a quadrangle map. The image showing through the map was adjusted to the map scale with the zoom lens. Field boundaries and other water-use boundaries were then traced on the 7-1/2 minute quadrangle map. Next, a team was sent to use the map in the field to check the boundaries and current year land use field data on the 7-1/2 minute quadrangles. The final step was to digitize and process the field data using ARC/INFO software developed by Environmental Systems Research Institute (ESRI). Starting in 2000 with the land use survey of the Uintah Basin, the division further improved its land use program by using digital data for the purposes of outlining agricultural and other land cover boundaries. The division used satellite data, USGS Digital Orthophoto Quadrangles (DOQs), National Agricultural Imagery Program (NAIP), and other digital images in a heads-up digitizing mode for this process. This allowed the division to use multiple technicians for the digitizing process. Digitizing was done as line and polygon files using ArcView 3.2 with a satellite image, DOQ or NAIP image as a background with other layers added for reference. Boundary files were created in logical groups so that the process of edge-matching along quad lines was eliminated and precision increased. Subsequent inventories were digitized in the ArcMap 9.x software versions. Present Methodology Using the latest statewide NAIP Imagery and ArcGIS 10, all boundaries of individual agricultural fields, urban areas, and significant riparian areas are precisely digitized. Once the process of boundary digitizing is done, the polygons are loaded onto tablet PCs. Field crews are then sent to field check the crop and irrigation type for each agricultural polygon and label the shapefiles accordingly. Each tablet PC is attached to a GPS unit for real-time tracking to continuously update the field crew’s location during the field labeling process. This improved process has saved the division much time and money and even greater savings will be realized as the new statewide field boundaries are completed. Once processed and quality checked, the data is filed in the State Geographic Information Database (SGID) maintained by the State Automated Geographic Reference Center (AGRC). Once in the SGID, the data becomes available to the public. At this point, the data is also ready for use in preparing various planning studies. In conducting water-related land use inventories, the division attempts to inventory all lands or areas that consume or evaporate water other than natural precipitation. Areas not inventoried are mainly desert, rangeland and forested areas. Wet/open water areas and dry land agriculture areas are mapped if they are within or border irrigated lands. As a result, the numbers of acres of wet/open water areas and dry land agriculture reported by the division may not represent all such areas in a basin or county. During land use inventories, the division uses 11 hydrologic basins as the basic collection units. County data is obtained from the basin data. The water-related land use data collected statewide covers more than 4.3 million acres of dry and irrigated agricultural land. This represents about 8 percent of the total land area in the state. Due to changes in methodology, improvements in imagery, and upgrades in software and hardware, increasingly more refined inventories have been made in each succeeding year of the Water-Related Land Use Inventory. While this improves the data we report, it also makes comparisons to past years difficult. Making comparisons between datasets is still useful; however, increases or decreases in acres reported should not be construed to represent definite trends or total amounts of change up or down. To estimate such trends or change, more analysis is required.
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TwitterThis digital data set consists of contours for predevelopment water-level elevations for the High Plains aquifer in the central United States. The High Plains aquifer extends from south of 32 degrees to almost 44 degrees north latitude and from 96 degrees 30 minutes to 106 degrees west longitude. The outcrop area covers 174,000 square miles and is present in Colorado, Kansas, Nebraska, New Mexico, Oklahoma, South Dakota, Texas, and Wyoming. This digital data set was created by digitizing the contours for predevelopment water-level elevations from a 1:1,000,000-scale base map created by the U.S. Geological Survey High Plains Regional Aquifer-System Analysis (RASA) project (Gutentag, E.D., Heimes, F.J., Krothe, N.C., Luckey, R.R., and Weeks, J.B., 1984, Geohydrology of the High Plains aquifer in parts of Colorado, Kansas, Nebraska, New Mexico, Oklahoma, South Dakota, Texas, and Wyoming: U.S. Geological Survey Professional Paper 1400-B, 63 p.) The data are not intended for use at scales larger than 1:1,000,000.
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TwitterThis data release contains data used to develop models and maps that estimate the occurrence of lithium in groundwater used as drinking water throughout the conterminous United States. An extreme gradient boosting model was developed to estimate the most probable lithium concentration category (≤4, >4 to ≤10, >10 to ≤30 or >30 µg/L). The model uses lithium concentration data from wells located throughout the conterminous United States and predictor variables that are available as geospatial data. The model is included in this data release in the zipped folder named Model_Archive and was used to produce maps that are also included in this data release. The model input data (predictor variables) that were used to make the maps are within a zipped folder (Map_Input_Data.zip) that contains 20 tif-raster files, one for each model predictor variable. The map probability estimates that are outputs from the model are in a zipped folder (Map_Output_Data.zip) that contains 10 tif-raster files, two model estimate maps for each of the lithium concentration categories and the category with the highest probability for public supply well depths and domestic supply well depths.