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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,
Consumptive use (CU) of water is an important factor for determining water availability and groundwater storage. Many regional stakeholders and water-supply managers in the Upper Rio Grande Basin have indicated CU is of primary concern in their water-management strategies, yet CU data is sparse for this area. This polygon feature class, which represents irrigated acres for 2015, is a geospatial component of the U.S. Geological Survey National Water Census Upper Rio Grande Basin (URGB) focus area study's effort to improve quantification of CU in parts of New Mexico, west Texas, and northern Chihuahua. These digital data accompany Ivahnenko, T.I., Flickinger, A.K., Galanter, A.E., Douglas-Mankin, K.R., Pedraza, D.E.,...
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Abiquiu Reservoir,
Ahumada,
Alamosa,
Alamosa County,
Alamosa Creek,
These data were generated with MAXENT 3.3.3k freeware (Phillips et al. 2011) using climate data and fire probability data for for three time periods: reference (1900-1929), mid-century (2040-2069) and late century (2070-2099), and community occurrence point data extracted from LANDFIRE Environmental Site Potential (ESP). Future time period data are from three global climate models (GCMs): CGCM, GFDL, and HadCM3. In MAXENT, we used the logistic output format (generating presence probabilities between 0 and 1), a random test percentage of 30 (using 70 % of the occurrence points to generate the suitability model and 30 % of the occurrence points to validate it), and a jackknife test to measure variable importance....
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Climate Change,
Drought, Fire and Extreme Weather,
Environmental Suitability Models,
Fire,
LANDFIRE,
This part of the data release contains the water-level measurement data compiled and synthesized from various sources. This collection includes two tables that contain all the water-level measurements that were considered to develop the water-level altitude maps (Input_VisGWDB), and a table of median water-level data that were used to develop the water-level altitude maps (MedianWaterLevelData). 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 Focus Area Study, Colorado, New Mexico, and...
Categories: Data;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Abiquiu Reservoir,
Ahumada,
Alamosa,
Alamosa County,
Alamosa Creek,
These data were generated with MAXENT 3.3.3k freeware (Phillips et al. 2011) using climate data and fire probability data for for three time periods: reference (1900-1929), mid-century (2040-2069) and late century (2070-2099), and community occurrence point data extracted from LANDFIRE Environmental Site Potential (ESP). Future time period data are from three global climate models (GCMs): CGCM, GFDL, and HadCM3. In MAXENT, we used the logistic output format (generating presence probabilities between 0 and 1), a random test percentage of 30 (using 70 % of the occurrence points to generate the suitability model and 30 % of the occurrence points to validate it), and a jackknife test to measure variable importance....
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Climate Change,
Drought, Fire and Extreme Weather,
Environmental Suitability Models,
Fire,
LANDFIRE,
These data were generated with MAXENT 3.3.3k freeware (Phillips et al. 2011) using climate data and fire probability data for for three time periods: reference (1900-1929), mid-century (2040-2069) and late century (2070-2099), and community occurrence point data extracted from LANDFIRE Environmental Site Potential (ESP). Future time period data are from three global climate models (GCMs): CGCM, GFDL, and HadCM3. In MAXENT, we used the logistic output format (generating presence probabilities between 0 and 1), a random test percentage of 30 (using 70 % of the occurrence points to generate the suitability model and 30 % of the occurrence points to validate it), and a jackknife test to measure variable importance....
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Climate Change,
Drought, Fire and Extreme Weather,
Environmental Suitability Models,
Fire,
LANDFIRE,
This Data Release contains various types of hydrologic and geologic data from the Upper Rio Grande Focus Area Study from 1921-2017, including groundwater-level measurement data compiled and synthesized from various sources, water-level altitude and water-level change maps developed from the water-level measurement data every 5 years from 1980-2015, and the horizontal extent of 13 alluvial basins in the Upper Rio Grande Basin
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Abiquiu Reservoir,
Ahumada,
Alamosa,
Alamosa County,
Alamosa Creek,
An extensive archive, estimated to contain more than 3,500 historical (1925–2020) geophysical logs collected in conjunction with past studies conducted by various entities, and more than 2,000 additional donated well and geophysical logs are stored in hard-copy at the Central Texas Branch of the Oklahoma-Texas Water Science Center (OTWSC) located in Austin, Texas. This dataset addresses the need to preserve these records electronically by providing a scanned and indexed collection of 6,058 of these records in Portable Document Format (PDF) along with a public Microsoft Access database and comma-separated values (CSV) text file containing detailed well header information for each record.
Categories: Data;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Anderson,
Andrews,
Angelina,
Aransas,
Archer,
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