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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.
Categories: Data;
Tags: Caballo Reservoir,
Chihuahua,
El Paso,
Elephant Butte Reservoir,
Las Cruces,
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.
This dataset consists of 102 magnetotelluric (MT) stations collected in 2012-2014 in the Rio Grande Rift and southern Rocky Mountains. The U.S. Geological Survey acquired these data to improve regional conductivity models of the western United States. This work is in support of studies of the effect of lithospheric modification on electrical resistivity structure and tectonic evolution of the western United States.
This dataset consists of 102 magnetotelluric (MT) stations collected in 2012-2014 in the Rio Grande Rift and southern Rocky Mountains. The U.S. Geological Survey acquired these data to improve regional conductivity models of the western United States. This work is in support of studies of the effect of lithospheric modification on electrical resistivity structure and tectonic evolution of the western United States.
This dataset consists of 102 magnetotelluric (MT) stations collected in 2012-2014 in the Rio Grande Rift and southern Rocky Mountains. The U.S. Geological Survey acquired these data to improve regional conductivity models of the western United States. This work is in support of studies of the effect of lithospheric modification on electrical resistivity structure and tectonic evolution of the western United States.
This dataset consists of 102 magnetotelluric (MT) stations collected in 2012-2014 in the Rio Grande Rift and southern Rocky Mountains. The U.S. Geological Survey acquired these data to improve regional conductivity models of the western United States. This work is in support of studies of the effect of lithospheric modification on electrical resistivity structure and tectonic evolution of the western United States.
These data were compiled for a manuscript in which 1) we develop a water temperature model for the major river segments and tributaries of the Colorado River basin, including the Colorado, Green, Yampa, White, and San Juan rivers; 2) we link modeled water temperature to fish population data to predict the probability native and nonnative species will be common in the future in a warming climate; and 3) assess the degree to which dams create thermal discontinuity in summer in river segments across the western US. Per goal #1, we developed a water temperature model using data spanning 1985-2015 that predicts water temperature every 1 mile (1.6-km) in rivers both now and in the future due to the potential influence...
This dataset consists of 102 magnetotelluric (MT) stations collected in 2012-2014 in the Rio Grande Rift and southern Rocky Mountains. The U.S. Geological Survey acquired these data to improve regional conductivity models of the western United States. This work is in support of studies of the effect of lithospheric modification on electrical resistivity structure and tectonic evolution of the western United States.
This dataset consists of 102 magnetotelluric (MT) stations collected in 2012-2014 in the Rio Grande Rift and southern Rocky Mountains. The U.S. Geological Survey acquired these data to improve regional conductivity models of the western United States. This work is in support of studies of the effect of lithospheric modification on electrical resistivity structure and tectonic evolution of the western United States.
This dataset consists of 102 magnetotelluric (MT) stations collected in 2012-2014 in the Rio Grande Rift and southern Rocky Mountains. The U.S. Geological Survey acquired these data to improve regional conductivity models of the western United States. This work is in support of studies of the effect of lithospheric modification on electrical resistivity structure and tectonic evolution of the western United States.
This dataset contains monthly pumping rates for municipal and industrial (MnI) wells in New Mexico within the Rio Grande Transboundary Integrated Hydrologic Model (RGTIHM). In RGTIHM, these wells are considered the Other New Mexico (ONM) group. Monthly pumping rates are presented in units of cubic feet per day for the period from March 1940 through December 2014.
Categories: Data;
Tags: Caballo Reservoir,
Chihuahua,
El Paso,
Elephant Butte Reservoir,
Las Cruces,
These data represent simulated soil temperature and moisture conditions for current climate, and for future climate represented by all available climate models at two time periods during the 21st century. These data were used to: 1) quantify the direction and magnitude of expected changes in several measures of soil temperature and soil moisture, including the key variables used to distinguish the regimes used in the R and R categories; 2) assess how these changes will impact the geographic distribution of soil temperature and moisture regimes; and 3) explore the implications for using R and R categories for estimating future ecosystem resilience and resistance.
This dataset consists of 102 magnetotelluric (MT) stations collected in 2012-2014 in the Rio Grande Rift and southern Rocky Mountains. The U.S. Geological Survey acquired these data to improve regional conductivity models of the western United States. This work is in support of studies of the effect of lithospheric modification on electrical resistivity structure and tectonic evolution of the western United States.
Categories: Data;
Types: Citation,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Carson National Forest,
Colfax County,
Colorado,
Colorado Plateau,
Dona Ana County,
This data release includes new major and trace element geochemical data acquired by the U.S. Geological Survey (USGS) for igneous rocks in the Cripple Creek district in Colorado. Cripple Creek is among the largest epithermal districts in the world, with more than 800 metric tons (t) Au (>26.4 Moz). The ores are associated spatially, temporally, and genetically with ~34 to 28 Ma alkaline igneous rocks that were emplaced into an 18 km2- diatreme complex and surrounding Proterozoic rocks (Kelley and others, 2020). Igneous rocks associated with Cripple Creek are part of a regionally extensive episode of Oligocene alkaline magmatism that extended southward along the axis of the Rio Grande rift through New Mexico and...
Categories: Data;
Types: Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: Colorado,
Cripple Creek,
Economic Geology,
Economic geology,
Fire Assay,
The High Plains aquifer extends from approximately 32 to 44 degrees north latitude and 96 degrees 30 minutes to 106 degrees west longitude. The aquifer underlies about 175,000 square miles in parts of Colorado, Kansas, Nebraska, New Mexico, Oklahoma, South Dakota, Texas, and Wyoming. This digital dataset consists of a raster of water-level changes for the High Plains aquifer, predevelopment (about 1950) to 2019. It was created using water-level measurements from 2,741 wells measured in both the predevelopment period (about 1950) and in 2019, the latest available static water level measured in 2015 to 2018 from 71 wells in New Mexico and using other published information on water-level change in areas with few water-level...
These data were compiled for a networked field-trial restoration experiment (RestoreNet) that spans the southwestern US, including 21 distributed field sites. The objective of our study was to understand the environmental factors and restoration practices (including seed mixes and soil manipulation) that increase plant establishment and survival to ultimate improve restoration outcomes in dryland environments. These data represent point-in-time plant density and height measurements at our field sites at the time of monitoring. These data were collected at 21 arid and semi-arid sites, located throughout Arizona, Utah, New Mexico, and California. These data were collected by USGS Restoration Assessment and Monitoring...
This child item describes Python code used to estimate average yearly and monthly tourism per 1000 residents within public-supply water service areas. Increases in population due to tourism may impact amounts of water used by public-supply water systems. This data release contains model input datasets, Python code used to develop the tourism information, and output estimates of tourism. This dataset is part of a larger data release using machine learning to predict public supply water use for 12-digit hydrologic units from 2000-2020. Output from this code was used as an input feature in the public supply delivery and water use machine learning models. This page includes the following files: tourism_input_data.zip...
This child item describes a public supply delivery machine learning model that was developed to estimate public-supply deliveries. Publicly supplied water may be delivered to domestic users or to commercial, industrial, institutional, and irrigation (CII) users. This model predicts total, domestic, and CII per capita rates for public-supply water service areas within the conterminous United States for 2009-2020. This child item contains model input datasets, code used to build the delivery machine learning model, and national predictions. This dataset is part of a larger data release using machine learning to predict public-supply water use for 12-digit hydrologic units from 2000-2020. This page includes the following...
This child item describes Python code used to query census data from the TigerWeb Representational State Transfer (REST) services and the U.S. Census Bureau Application Programming Interface (API). These data were needed as input feature variables for a machine learning model to predict public supply water use for the conterminous United States. Census data were retrieved for public-supply water service areas, but the census data collector could be used to retrieve data for other areas of interest. This dataset is part of a larger data release using machine learning to predict public supply water use for 12-digit hydrologic units from 2000-2020. Data retrieved by the census data collector code were used as input...
These data were compiled to demonstrate new predictive mapping approaches and provide comprehensive gridded 30-meter resolution soil property maps for the Colorado River Basin above Hoover Dam. Random forest models related environmental raster layers representing soil forming factors with field samples to render predictive maps that interpolate between sample locations. Maps represented soil pH, texture fractions (sand, silt clay, fine sand, very fine sand), rock, electrical conductivity (ec), gypsum, CaCO3, sodium adsorption ratio (sar), available water capacity (awc), bulk density (dbovendry), erodibility (kwfact), and organic matter (om) at 7 depths (0, 5, 15, 30, 60, 100, and 200 cm) as well as depth to restrictive...
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