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This dataset contains a thematic [classified] image derived from supervised classification of WorldView-3 satellite imagery. This data release contains a geospatial thematic (raster) image derived from a supervised classification of WorldView-3 satellite imagery obtained during 2020–21. Arundo donax (Arundo cane, giant reed, or Carrizo cane), is an invasive bamboo-like perennial grass most common to riparian areas throughout the southwestern United States. Because it displaces native riparian vegetation, Arundo cane has greatly disrupted the health of riparian ecosystems in the southwestern United States and northern Mexico during the past 50 years. Arundo cane also has created border security problems along the...
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This dataset contains a thematic [classified] image derived from supervised classification of WorldView-3 satellite imagery. This data release contains a geospatial thematic (raster) image derived from a supervised classification of WorldView-3 satellite imagery obtained during 2020–21. Arundo donax (Arundo cane, giant reed, or Carrizo cane), is an invasive bamboo-like perennial grass most common to riparian areas throughout the southwestern United States. Because it displaces native riparian vegetation, Arundo cane has greatly disrupted the health of riparian ecosystems in the southwestern United States and northern Mexico during the past 50 years. Arundo cane also has created border security problems along the...
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These vector contour lines are derived from the 3D Elevation Program using automated and semi-automated processes. They were created to support 1:24,000-scale CONUS and Hawaii, 1:25,000-scale Alaska, and 1:20,000-scale Puerto Rico / US Virgin Island topographic map products, but are also published in this GIS vector format. Contour intervals are assigned by 7.5-minute quadrangle, so this vector dataset is not visually seamless across quadrangle boundaries. The vector lines have elevation attributes (in feet above mean sea level on NAVD88), but this dataset does not carry line symbols or annotation.
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The National Hydrography Dataset (NHD) is a feature-based database that interconnects and uniquely identifies the stream segments or reaches that make up the nation's surface water drainage system. NHD data was originally developed at 1:100,000-scale and exists at that scale for the whole country. This high-resolution NHD, generally developed at 1:24,000/1:12,000 scale, adds detail to the original 1:100,000-scale NHD. (Data for Alaska, Puerto Rico and the Virgin Islands was developed at high-resolution, not 1:100,000 scale.) Local resolution NHD is being developed where partners and data exist. The NHD contains reach codes for networked features, flow direction, names, and centerline representations for areal water...
Tags: Adjuntas, Administrative watershed units, Administrative watershed units, Aguada, Aguadilla, All tags...
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The National Hydrography Dataset (NHD) is a feature-based database that interconnects and uniquely identifies the stream segments or reaches that make up the nation's surface water drainage system. NHD data was originally developed at 1:100,000-scale and exists at that scale for the whole country. This high-resolution NHD, generally developed at 1:24,000/1:12,000 scale, adds detail to the original 1:100,000-scale NHD. (Data for Alaska, Puerto Rico and the Virgin Islands was developed at high-resolution, not 1:100,000 scale.) Local resolution NHD is being developed where partners and data exist. The NHD contains reach codes for networked features, flow direction, names, and centerline representations for areal water...
Tags: Administrative watershed units, Administrative watershed units, Area of Complex Channels, Area to be submerged, Basin, All tags...
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The National Hydrography Dataset (NHD) is a feature-based database that interconnects and uniquely identifies the stream segments or reaches that make up the nation's surface water drainage system. NHD data was originally developed at 1:100,000-scale and exists at that scale for the whole country. This high-resolution NHD, generally developed at 1:24,000/1:12,000 scale, adds detail to the original 1:100,000-scale NHD. (Data for Alaska, Puerto Rico and the Virgin Islands was developed at high-resolution, not 1:100,000 scale.) Local resolution NHD is being developed where partners and data exist. The NHD contains reach codes for networked features, flow direction, names, and centerline representations for areal water...
Tags: Administrative watershed units, Administrative watershed units, Area of Complex Channels, Area to be submerged, Basin, All tags...
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This dataset contains the input files, script, and output files regarding 110 years of daily regulated (observed) and naturalized streamflow (million cubic meters/day) for ten gauge stations in the Rio Grande/Bravo basin. The gauge stations included are at Amistad, Anzalduas, Artesia, Below Presidio, Laredo, Conchos Outlet, Foster Ranch, Laredo, Pecos Outlet, Salado River, and San Juan River.
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Burn probability (BP) for Fireline Intensity Class 5 (FIL5) with flame lengths in the range of 2.4-3.7 m predicted for the 2080-2100 period in the Rio Grande area. This raster dataset was generated using: 1) data developed from the 2014 Fire Program Analysis (FPA) system; 2) geospatial Fire Simulation (FSim) system developed by the US Forest Service Missoula Fire Sciences Laboratory to estimate probabilistic components of wildfire risk (Finney et al. 2011); and 3) climate predictions developed using the Multivariate Adaptive Constructed Analogs (MACA) method (Abatzoglou and Brown 2011) which downscaled model output from the GFDL-ESM-2m global climate model of the Coupled Model Inter-Comparison Project 5 for the...
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Burn probability (BP) for Fireline Intensity Class 4 (FIL4) with flame lengths in the range of 1.8-2.4 m predicted for the 2050-2070 period in the Rio Grande area. This raster dataset was generated using: 1) data developed from the 2014 Fire Program Analysis (FPA) system; 2) geospatial Fire Simulation (FSim) system developed by the US Forest Service Missoula Fire Sciences Laboratory to estimate probabilistic components of wildfire risk (Finney et al. 2011); and 3) climate predictions developed using the Multivariate Adaptive Constructed Analogs (MACA) method (Abatzoglou and Brown 2011) which downscaled model output from the GFDL-ESM-2m global climate model of the Coupled Model Inter-Comparison Project 5 for the...
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Burn probability (BP) for Fireline Intensity Class 2 (FIL2) with flame lengths in the range of 0.6-1.2 m predicted for the 2050-2070 period in the Rio Grande area. This raster dataset was generated using: 1) data developed from the 2014 Fire Program Analysis (FPA) system; 2) geospatial Fire Simulation (FSim) system developed by the US Forest Service Missoula Fire Sciences Laboratory to estimate probabilistic components of wildfire risk (Finney et al. 2011); and 3) climate predictions developed using the Multivariate Adaptive Constructed Analogs (MACA) method (Abatzoglou and Brown 2011) which downscaled model output from the GFDL-ESM-2m global climate model of the Coupled Model Inter-Comparison Project 5 for the...
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Burn probability (BP) for Fireline Intensity Class 6 (FIL6) with flame lengths in the range of 3.7-15 m predicted for the 2080-2100 period in the Rio Grande area. This raster dataset was generated using: 1) data developed from the 2014 Fire Program Analysis (FPA) system; 2) geospatial Fire Simulation (FSim) system developed by the US Forest Service Missoula Fire Sciences Laboratory to estimate probabilistic components of wildfire risk (Finney et al. 2011); and 3) climate predictions developed using the Multivariate Adaptive Constructed Analogs (MACA) method (Abatzoglou and Brown 2011) which downscaled model output from the GFDL-ESM-2m global climate model of the Coupled Model Inter-Comparison Project 5 for the 8.5...
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Burn probability (BP) raster dataset predicted for the 2080-2100 period in the Rio Grande area was generated using: 1) data developed from the 2014 Fire Program Analysis (FPA) system; 2) geospatial Fire Simulation (FSim) system developed by the US Forest Service Missoula Fire Sciences Laboratory to estimate probabilistic components of wildfire risk (Finney et al. 2011); and 3) climate predictions developed using the Multivariate Adaptive Constructed Analogs (MACA) method (Abatzoglou and Brown 2011) which downscaled model output from the GFDL-ESM-2m global climate model of the Coupled Model Inter-Comparison Project 5 for the 8.5 Representative Concentration Pathway.
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This part of the Data Release contains the raster representation of the water-level altitude and water-level change maps developed every 5 years from 1980-2015 for the upper Rio Grande Focus Area Study. The input point data used to generate the water-level altitude maps can be found in the "Groundwater level measurement data used to develop water-level altitude maps in the upper Rio Grande Alluvial Basins" child item of this data release. These digital data accompany Houston, N.A., Thomas, J.V., Foster, L.K., Pedraza, D.E., and Welborn, T.L., 2020, Hydrogeologic framework, groundwater-level altitudes, groundwater-level changes, and groundwater-storage changes in selected alluvial basins of the upper Rio Grande...
Types: Map Service, OGC WFS Layer, OGC WMS Layer, OGC WMS Service; Tags: Abiquiu Reservoir, Ahumada, Alamosa, Alamosa County, Alamosa Creek, All tags...
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This point vector dataset represents 10 climate stations used for analysis of annual and seasonal precipitation, analysis of monthly measured reference evapotranspiration, and comparison of simulated potential evapotranspiration with measured reference evapotranspiration within the Rio Grande transboundary integrated hydrologic model and water-availability analysis, New Mexico and Texas, United States, and Northern Chihuahua, Mexico.
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This dataset contains monthly crop irrigation requirement (CIR) values from March 1940 through 2014 for the 20 virtual land-use units, including the seven canal service units, in the Rio Grande Transboundary Integrated Hydrologic Model (RGTIHM). CIR values are presented in units of feet per day.
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This child page contains the model input and output data used in the model validation process for one Program for Predicting Polluting Particle Passage through Pits, Puddles and Ponds (P8) model during the validation period of the study detailed in the associated Scientific Investigations Report "Comparison of Storm Runoff Models for a Small Watershed in an Urban Metropolitan Area, Albuquerque, New Mexico" (Shephard and Douglas-Mankin, 2020). This model was used to simulate storm runoff in the Hahn Arroyo Watershed, an urbanized watershed with concrete lined channels in the northeastern quadrant of Albuquerque that exhibits flashy, monsoonal-driven storm runoff events. The model is described in detail in the associated...


map background search result map search result map Burn Probability for Fireline Intensity Class 2, predicted for 2050 to 2070 for Rio Grande study area Burn Probability for Fireline Intensity Class 4, predicted for 2050 to 2070 for Rio Grande study area Burn Probability for Fireline Intensity Class 5, predicted for 2080 to 2100 for Rio Grande study area Burn Probability for Fireline Intensity Class 6, predicted for 2080 to 2100 for Rio Grande study area Burn Probability predicted for 2080 to 2100 for Rio Grande study area USGS National Map Index Names (published 20240120) FileGDB USGS National Hydrography Dataset Best Resolution (NHD) for Hydrological Unit (HU) 8 - 13010004 (published 20231219) FileGDB USGS NED 1/3 arc-second Contours for Durango E, Colorado 1 x 1 degree (published 20240112) Shapefile Climate Stations for the Rio Grande transboundary integrated hydrologic model and water-availability analysis, New Mexico and Texas, United States, and Northern Chihuahua, Mexico RGTIHM CIR Groundwater-level altitude and groundwater-level change maps developed for the groundwater component of the upper Rio Grande Focus Area Study P8 Validation Period Input and Output Data USGS US Topo 7.5-minute map for Dog Mountain, CO 2013 USGS US Topo 7.5-minute map for Waverly, CO 2016 USGS US Topo 7.5-minute map for Fajardo, PR 2013 USGS National Hydrography Dataset Best Resolution (NHD) for Hydrological Unit (HU) 4 - 2101 (published 20231213) Shapefile USGS National Hydrography Dataset Best Resolution (NHD) for Hydrological Unit (HU) 8 - 13010001 (published 20231219) GeoPackage Natural and Observed flow at gauging stations from Presidio, Texas, to the outlet of the Rio Grande/Bravo from 1900 to 2011 Arundo donax (Arundo Cane) Image Classification along the Rio Grande in Webb County, Texas, September 26, 2020 Arundo donax (Arundo Cane) Image Classification along the Rio Grande in Webb County, Texas, May 07, 2021 P8 Validation Period Input and Output Data USGS US Topo 7.5-minute map for Dog Mountain, CO 2013 USGS US Topo 7.5-minute map for Waverly, CO 2016 USGS US Topo 7.5-minute map for Fajardo, PR 2013 USGS National Hydrography Dataset Best Resolution (NHD) for Hydrological Unit (HU) 8 - 13010004 (published 20231219) FileGDB USGS National Hydrography Dataset Best Resolution (NHD) for Hydrological Unit (HU) 8 - 13010001 (published 20231219) GeoPackage USGS NED 1/3 arc-second Contours for Durango E, Colorado 1 x 1 degree (published 20240112) Shapefile USGS National Map Index Names (published 20240120) FileGDB USGS National Hydrography Dataset Best Resolution (NHD) for Hydrological Unit (HU) 4 - 2101 (published 20231213) Shapefile Climate Stations for the Rio Grande transboundary integrated hydrologic model and water-availability analysis, New Mexico and Texas, United States, and Northern Chihuahua, Mexico RGTIHM CIR Burn Probability for Fireline Intensity Class 2, predicted for 2050 to 2070 for Rio Grande study area Burn Probability for Fireline Intensity Class 4, predicted for 2050 to 2070 for Rio Grande study area Burn Probability for Fireline Intensity Class 5, predicted for 2080 to 2100 for Rio Grande study area Burn Probability for Fireline Intensity Class 6, predicted for 2080 to 2100 for Rio Grande study area Burn Probability predicted for 2080 to 2100 for Rio Grande study area Groundwater-level altitude and groundwater-level change maps developed for the groundwater component of the upper Rio Grande Focus Area Study Natural and Observed flow at gauging stations from Presidio, Texas, to the outlet of the Rio Grande/Bravo from 1900 to 2011