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This dataset is based on U.S. Geological Survey (USGS) resource assessments for “undiscovered” natural gas liquid resources, which are resources that have not yet been extensively proven by drilling (USGS 2014). Individual resource assessments describe the amount of petroleum resources in units with similar geologic features. We quantified the density of natural gas liquid resources by adding together the amounts in spatially overlapping assessment units and dividing these totals by polygon areas. Since assessments for geologic areas used in this analysis were completed at various times, the certainty related to these values is likely to vary according to geologic unit. USGS [U.S. Geological Survey]. 2014. Energy...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Arizona,
Colorado,
Colorado headwaters-Plateau,
Nevada,
New Mexico,
This dataset is based on U.S. Geological Survey (USGS) resource assessments for “undiscovered” oil resources, which are resources that have not yet been extensively proven by drilling (USGS 2014). Individual resource assessments describe the amount of petroleum resources in units with similar geologic features. We focused on the amount of undiscovered continuous oil because technological advances have made exploitation of continuous resources increasingly profitable and large amounts remain undeveloped in comparison with conventional resources. We quantified the density of continuous oil resources by adding together the amounts in spatially overlapping assessment units and dividing these totals by polygon areas....
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Arizona,
Colorado,
Colorado headwaters-Plateau,
Nevada,
New Mexico,
Five principal components are used to represent the climate variation in an original set of 12 composite climate variables reflecting complex precipitation and temperature gradients. The dataset provides coverage for future climate (defined as the 2040-2070 normal period) under the RCP4.5 emission scenarios. Climate variables were chosen based on their known influence on local adaptation in plants, and include: mean annual temperature, summer maximum temperature, winter minimum temperature, annual temperature range, temperature seasonality (coefficient of variation in monthly average temperatures), mean annual precipitation, winter precipitation, summer precipitation, proportion of summer precipitation, precipitation...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Arizona,
California,
Colorado,
Colorado Plateau,
Great Basin,
This dataset provides timeseries data on water quality and quantity, as collected or computed from outside sources. The format is many tables with one row per time series observation (1 tab-delimited file per site-variable combination, 1 zip file per site). This compilation of data is intended for use in estimating or interpreting metabolism. Sites were included if they met the initial criteria of having at least 100 dissolved oxygen observations and one of the accepted NWIS site types ('ST','ST-CA','ST-DCH','ST-TS', or 'SP'). This dataset is part of a larger data release of metabolism model inputs and outputs for 356 streams and rivers across the United States (https://doi.org/10.5066/F70864KX). The complete release...
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...
Climate Distance Mapper is an interactive web mapping application designed to facilitate informed seed sourcing decisions and to aid in directing regional seed collections. Implemented as a shiny web application (Chang et al. 2017), Climate Distance Mapper is hosted on the web at: https://usgs-werc-shinytools.shinyapps.io/Climate_Distance_Mapper/. The application is designed to guide restoration seed sourcing in the desert southwest by allowing users to interactively match seed sources with restoration sites climatic differences – in the form of multivariate climate distance values – between restoration sites and the surrounding landscape. Climatic distances are based on a combination of variables likely to influence...
Five principal components are used to represent the climate variation in an original set of 12 composite climate variables reflecting complex precipitation and temperature gradients. The dataset provides coverage for future climate (defined as the 2040-2070 normal period) under the RCP8.5 emission scenarios. Climate variables were chosen based on their known influence on local adaptation in plants, and include: mean annual temperature, summer maximum temperature, winter minimum temperature, annual temperature range, temperature seasonality (coefficient of variation in monthly average temperatures), mean annual precipitation, winter precipitation, summer precipitation, proportion of summer precipitation, precipitation...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Arizona,
California,
Colorado,
Colorado Plateau,
Great Basin,
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.
The RCMAP (Rangeland Condition Monitoring Assessment and Projection) dataset quantifies the percent cover of rangeland components across the western U.S. using Landsat imagery from 1985-2021. The RCMAP product suite consists of nine fractional components: annual herbaceous, bare ground, herbaceous, litter, non-sagebrush shrub, perennial herbaceous, sagebrush, shrub, and tree, in addition to the temporal trends of each component. Several enhancements were made to the RCMAP process relative to prior generations. First, we have trained time-series predictions directly from 331 high-resolution sites collected from 2013-2018 from Assessment, Inventory, and Monitoring (AIM) instead of using the 2016 “base” map as an intermediary....
The Colorado Plateau structural province features long monoclinal flexures between uplifts and basins that are the major lines of deformation within and marginal to the Plateau. These folds are named, well-known, and have been described as part of several previous tectonic syntheses of the Colorado Plateau (Kelley, 1955; Davis, 1978; 1999). However, no digital data have ever been created that locate these folds in digital map space. This digital dataset compiles mapped locations of monoclinal folds from several geologic maps from the Colorado Plateau, most released only in “paper”, non-vector format. Fold names and their general map trace were guided by regional-scale maps that synthesize the tectonic elements of...
This data release documents proposed updates to geologic inputs (faults) for the upcoming 2023 National Seismic Hazard Model (NSHM). This version (1.0) conveys differences between 2014 NSHM fault sources and those recently released in the earthquake geology inputs for the U.S. National Seismic Hazard Model (NSHM) 2023, version 1.0 data release by Hatem et al. (2021). A notable difference between the 2014 and 2023 datasets is that slip rates are provided at points for 2023 instead of generalized along the entire fault section length as in 2014; consequently, slip rates are not provided for fault sections in the draft 2023 dataset. Geospatial data (shapefile, kml and geojson) are provided in this data release with...
Categories: Data;
Types: Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: Arizona,
California,
Colorado,
Idaho,
Nevada,
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...
This dataset provides early estimates of 2021 exotic annual grasses (EAG) fractional cover predicted on May 3rd. We develop and release EAG fractional cover map with an emphasis on cheatgrass (Bromus tectrorum) but it also includes number of other species, i.e., Bromus arvensis L., Bromus briziformis, Bromus catharticus Vahl, Bromus commutatus, Bromus diandrus, Bromus hordeaceus L., Bromus japonicus, Bromus madritensis L., Bromus racemosus, Bromus rubens L., Bromus secalinus L., Bromus texensis (Shear) Hitchc., and medusahead (Taeniatherum caput-medusae. The dataset was generated leveraging field observations from Bureau of Land Management (BLM) Assessment, Inventory, and Monitoring data (AIM) plots; Harmonized...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Arizona,
California,
Colorado,
Great Basin,
Harmonized Landsat Sentinel,
Across the country, public land managers make hundreds of decisions each year that influence landscapes and ecosystems within the lands they manage. Many of these decisions involve vegetation manipulations known as land treatments. Land treatments include activities such as removal or alteration of plant biomass, seeding burned areas, and herbicide applications. Data on these land treatments historically have been stored at local offices and gathering information across large spatial areas was difficult. These valuable data needed to be centralized and stored for Federal agencies involved in land treatments because these data are useful to land managers for policy and management and to scientists for developing...
These data were released prior to the October 1, 2016 effective date for the USGS’s policy dictating the review, approval, and release of scientific data as referenced in USGS Survey Manual Chapter 502.8 Fundamental Science Practices: Review and Approval of Scientific Data for Release. Estimates of area and aerial extent of land-use categories are an essential component for computing the water budget of the High Plains aquifer. These raster land-use land class data represent yearly simulated future land use for the High Plains from 2009 to 2050 These data were developed using the FOREcasting SCEnarios (FORE-SCE) of future land cover model (Sohl and others, 2007; Sohl and Sayler 2008) for two (A2 and B2) of the...
Estimation of irrigation water use provides essential information for the management and conservation of agricultural water resources. The blue water evapotranspiration (BWET) raster dataset at 30-meter resolution is created to estimate agricultural irrigation water consumption. The dataset contains seasonal total (1 May to 30 September) BWET time series (1986 – 2020) for the croplands across the U.S. High Plains aquifer region. The BWET estimates are generated by integrating an energy-balance ET model (Operational Simplified Surface Energy Balance model) and a water-balance ET model (Vegetation ET model). BWET in croplands reflects crop consumptive use of irrigation water extracted from surface water and groundwater...
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...
Climate change over the past century has altered vegetation community composition and species distributions across rangelands in the western United States. The scale and magnitude of climatic influences are largely unknown. We used fractional component cover data for rangeland functional groups and weather data from the 1985 to 2023 reference period in conjunction with soils and topography data to develop empirical models describing the spatio-temporal variation in component cover. To investigate the ramifications of future change across the western US, we extended models based on historical relationships over the reference period to model landscape effects based on future weather conditions from two emissions scenarios...
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...
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