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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 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.
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This dataset includes the audio-magnetotelluric (AMT) sounding data collected in 2009 in and near the San Luis Basin, New Mexico. The U.S. Geological Survey conducted a series of multidisciplinary studies, including AMT surveys, in the San Luis Basin to improve understanding of the hydrogeology of the Santa Fe Group and the nature of the sedimentary deposits comprising the principal groundwater aquifers of the Rio Grande rift. The shallow unconfined and the deeper confined Santa Fe Group aquifers in the San Luis Basin are the main sources of municipal water for the region. The population of the San Luis Basin region is growing rapidly and water shortfalls could have serious consequences. Future growth and land management...
Categories: Data; Types: Downloadable, Map Service, OGC WFS Layer, OGC WMS Layer, Shapefile; Tags: AMT, Cerro, Cerro De La Olla, GGGSC, GPS measurement, All tags...
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There is a need to understand how alteration of physical processes on the Rio Grande River have impacted aquatic biota and their habitats, and a need to predict potential future effects of climate change on biotic resources in order to prescribe research and management activities that will enhance conservation of aquatic species. We propose a project with the goal of developing monitoring recommendations and identifying research needs for aquatic ecological resources in the Big Bend region of the Rio Grande. This goal will be targeted by synthesizing and analyzing available data and literature for aquatic species in the project region. In particular, we will work to develop time series of abundance and population...
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This project had two primary goals: 1) To develop a process for integrating data from multiple sources to improve predictions of climate impacts for wildlife species; and 2) To provide data on climate and related hydrological change, fire behavior under future climates, and species’ distributions for use by researchers and resource managers.We present within this report the process used to integrate species niche models, fire simulations, and vulnerability assessment methods and provide species’ reports that summarize the results of this work. Species niche model analysis provides information on species’ distributions under three climate scenarios and time periods. Niche model analysis allows us to estimate the...
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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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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) 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 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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This dataset contains monthly pumping rates for municipal and industrial (MnI) wells in New Mexico within the Rio Grande Transboundary Integrated Hydrologic Model (RGTIHM) that were not included in other pumping rate datasets. In RGTIHM, these wells are considered the New Mexico Office of the State Engineer MnI (NMOSE_MnI) group. Monthly pumping rates are presented in units of cubic feet per day for the period from March 1940 through December 2014.
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These data represent 2 years of plant clipping data in areas with elk plus bison and areas of elk only in the San Luis Valley of Colorado, USA from 2006-2008. Clipping plots were measured (clipped) in meadow sites, herbaceous riparian sites, and willow communities. We clipped 1/4 m2 (meter-squared) rings inside and outside of 1-m2 grazing cages, as well as within large ungulate exclosures that were 0.04 ha (hectares) in size.
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The U.S. Geological Survey Precipitation-Runoff Modeling System (PRMS) was used to assess the effects of changing climate and land disturbance on seasonal streamflow in the Rio Grande Headwaters (RGHW) region. Three applications of PRMS in the RGHW were used to simulate 1) baseline effects of climate (see RGHW-PRMS_baseline_input.zip), 2) effects of bark-beetle induced tree mortality (see RGHW-PRMS_BB_input.zip), and 3) effects of wildfire (see RGHW-PRMS_fire_input.zip), on components of the hydrologic cycle by hydrologic response unit (HRU) and subsequent seasonal streamflow runoff from April through September for water years 1980 through 2017. PRMS input files (control, climate-by-hru, data, parameter, dynamic...
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In regulated rivers of the southwest, reduced flooding and the invasion of tamarisk contributes to accumulation of greater fuel loads and increased riparian fire frequency. As a result, some desert riparian areas, historically considered barriers to wildfire, have been converted into pathways for wildfire spread. Fire-smart management strategies are needed to protect sensitive riparian species and reduce fire risk from increased fire frequency due to interactions of climate change, tamarisk invasion, and tamarisk beetle activity. Fire niche simulations will be used to project impacts of fire frequency and climate change, which can be used to highlight areas of the Desert LCC where Southwestern Willow Flycatcher,...
Categories: Data, Project; Types: Map Service, OGC WFS Layer, OGC WMS Layer, OGC WMS Service; Tags: 2014, AZ-01, AZ-02, AZ-03, AZ-04, All tags...
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We are providing geospatial data layers of climate, fire, biome and predicted species distributions for download at our project website. Links to presentations, data descriptions and zip files containing data layers can be found here. Over the next few months, we will continue to upload webinars and new training tutorials that demonstrate the application of these datasets to new questions and species. Climate and environmental data can readily be used to generate new models for additional species or other applications to describe habitats and future conditions within New Mexico. Initial fire model output is available as raster images and tabulated values that can be used in analyses of wildfire risk or hazardous...
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Fire type predicted for the 2080-2100 period in the Rio Grande area with five classes: 1) shrub vegetation with torching flames; 2) shrub vegetation without torching flames; 3) forest with torching flames; 4) forest without torching flames; 5) grass or non-vegetation. 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...
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This dataset contains monthly pumping rates for municipal and industrial (MnI) wells in the Mexico portion of the Rio Grande Transboundary Integrated Hydrologic Model (RGTIHM). Monthly pumping rates are presented in units of cubic feet per day for the period from March 1940 through December 2014.
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This tabular dataset represents monthly flow at 61 surface-water points of diversion used to route flow in the Streamflow-Routing (SFR) Package for MODFLOW-One-Water Hydrologic Flow Model in the Rio Grande Transboundary Integrated Hydrologic Model (RGTIHM). Thirty-one of the 61 diversion points represent surface-water deliveries to combined groundwater and surface-water water balance subregions (WBS), and the remaining 30 diversion points represent diversions to canals and laterals along the surface-water conveyance network. Flow in this tabular dataset is specified monthly at each diversion point as either a rate (volume per time) in cubic feet per day, or as a fractional split from the simulated flow in the upstream...
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This tabular dataset represents the source of monthly flow at 160 stream gages used for surface-water flow and flow-difference observations for the Rio Grande Transboundary Integrated Hydrologic Model (RGTIHM). See the Site_Name attribute in the RGTIHM_Surface_Water_Obs feature class for the location of the stream gages.


map background search result map search result map Fire-smart Southwestern Riparian Landscape Management and Restoration of Native Biodiversity in View of Species of Conservation Concern and the Impacts of Tamarisk Beetles Ecological changes in aquatic communities in the Big Bend reach of the Rio Grande: Synthesis and future monitoring needs 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 Fire type predicted for 2080 to 2100 for Rio Grande study area Final Report: Vulnerability of Riparian Obligate Species in the Rio Grande to the Interactive Effects of Fire, Hydrological Variation and Climate Change Maps and Data: Vulnerability of Riparian Obligate Species in the Rio Grande to the Interactive Effects of Fire, Hydrological Variation and Climate Change Audiomagnetotelluric sounding data, stations 1-9, Taos Plateau Volcanic Field, New Mexico, 2009 RGTIHM CIR Mexico Wells: Municipal and Industrial Monthly Pumping Rates for the Rio Grande transboundary integrated hydrologic model and water-availability analysis, New Mexico and Texas, United States, and Northern Chihuahua, Mexico New Mexico Office of the State Engineer Municipal and Industrial Wells: Municipal and Industrial Monthly Pumping Rates for the Rio Grande transboundary integrated hydrologic model and water-availability analysis, New Mexico and Texas, United States, and Northern Chihuahua, Mexico Other New Mexico Wells: Municipal and Industrial Monthly Pumping Rates for the Rio Grande transboundary integrated hydrologic model and water-availability analysis, New Mexico and Texas, United States, and Northern Chihuahua, Mexico Other New Mexico Wells Data Source: Municipal and Industrial Monthly Pumping Rates for the Rio Grande transboundary integrated hydrologic model and water-availability analysis, New Mexico and Texas, United States, and Northern Chihuahua, Mexico SFR Diversions Table for the Rio Grande transboundary integrated hydrologic model and water-availability analysis, New Mexico and Texas, United States, and Northern Chihuahua, Mexico Surface-Water Flow Observations Table Source for the Rio Grande transboundary integrated hydrologic model and water-availability analysis, New Mexico and Texas, United States, and Northern Chihuahua, Mexico Model input for Precipitation-Runoff Modeling System simulations in the Rio Grande Headwaters, Colorado, for water years 1980 through 2017 Winter herbaceous utilization by elk and bison in the Great Sand Dunes National Park ecosystem of the San Luis Valley, Colorado, 2006 to 2008 Winter herbaceous utilization by elk and bison in the Great Sand Dunes National Park ecosystem of the San Luis Valley, Colorado, 2006 to 2008 Audiomagnetotelluric sounding data, stations 1-9, Taos Plateau Volcanic Field, New Mexico, 2009 Model input for Precipitation-Runoff Modeling System simulations in the Rio Grande Headwaters, Colorado, for water years 1980 through 2017 Ecological changes in aquatic communities in the Big Bend reach of the Rio Grande: Synthesis and future monitoring needs RGTIHM CIR Mexico Wells: Municipal and Industrial Monthly Pumping Rates for the Rio Grande transboundary integrated hydrologic model and water-availability analysis, New Mexico and Texas, United States, and Northern Chihuahua, Mexico New Mexico Office of the State Engineer Municipal and Industrial Wells: Municipal and Industrial Monthly Pumping Rates for the Rio Grande transboundary integrated hydrologic model and water-availability analysis, New Mexico and Texas, United States, and Northern Chihuahua, Mexico Other New Mexico Wells: Municipal and Industrial Monthly Pumping Rates for the Rio Grande transboundary integrated hydrologic model and water-availability analysis, New Mexico and Texas, United States, and Northern Chihuahua, Mexico Other New Mexico Wells Data Source: Municipal and Industrial Monthly Pumping Rates for the Rio Grande transboundary integrated hydrologic model and water-availability analysis, New Mexico and Texas, United States, and Northern Chihuahua, Mexico SFR Diversions Table for the Rio Grande transboundary integrated hydrologic model and water-availability analysis, New Mexico and Texas, United States, and Northern Chihuahua, Mexico Surface-Water Flow Observations Table Source for the Rio Grande transboundary integrated hydrologic model and water-availability analysis, New Mexico and Texas, United States, and Northern Chihuahua, Mexico 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 Fire type predicted for 2080 to 2100 for Rio Grande study area Burn Probability predicted for 2080 to 2100 for Rio Grande study area Final Report: Vulnerability of Riparian Obligate Species in the Rio Grande to the Interactive Effects of Fire, Hydrological Variation and Climate Change Maps and Data: Vulnerability of Riparian Obligate Species in the Rio Grande to the Interactive Effects of Fire, Hydrological Variation and Climate Change Fire-smart Southwestern Riparian Landscape Management and Restoration of Native Biodiversity in View of Species of Conservation Concern and the Impacts of Tamarisk Beetles