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Canopy Density and Canopy Structure Metrics were derived for the San Juan Mountains of Southwest Colorado from Aerial point cloud data at a 1-meter resolution. The aerial Lidar data originated from the ‘CO_Southwest_NRCS_2018’ project prepared by Quantum Spatial for the USGS from a series of flyovers between 2018 and 2019 and were made available in 2021. Canopy Density metrics include Canopy Closure (CC) and Leaf Area Index (LAI). Canopy Structure metrics include total gap area, mean distance to canopy, canopy edginess to the south and canopy edginess to the north.
Canopy Density and Canopy Structure Metrics were derived for the San Juan Mountains of Southwest Colorado from Aerial point cloud data at a 1-meter resolution. The aerial Lidar data originated from the ‘CO_Southwest_NRCS_2018’ project prepared by Quantum Spatial for the USGS from a series of flyovers between 2018 and 2019 and were made available in 2021. Canopy Density metrics include Canopy Closure (CC) and Leaf Area Index (LAI). Canopy Structure metrics include total gap area, mean distance to canopy, canopy edginess to the south and canopy edginess to the north. These Canopy Density and Canopy Structure Metrics were used to partition 100 m grid cells over the same area for a snow melt model called SNOWMODEL....
The Rio Grande is a vital water source for the southwestern States of Colorado, New Mexico, and Texas and for northern Mexico. The river serves as the primary source of water for irrigation in the region, has many environmental and recreational uses, and is used by more than 13 million people including those in the Cities of Albuquerque and Las Cruces, New Mexico; El Paso, Texas; and Ciudad Juárez, Chihuahua, Mexico. However, concern is growing over the increasing gap between water supply and demand in the Upper Rio Grande Basin. As populations increase and agricultural crop patterns change, demands for water are increasing, at the same time the region is undergoing a decrease in supply due to drought and climate...
Categories: Publication;
Types: Citation
This dataset contains projected climate data (precipitation, maximum temperature, minimum temperature) from 27 climate scenarios used as input to the Precipitation-Runoff Modeling System (PRMS), and baseline PRMS simulated streamflow at 63 sites in the Upper Rio Grande Basin under each of the 27 scenarios. Projected climate data, obtained from the USGS South Central Climate Adaptation Science Center (Wooten, 2020), were generated using three general circulation models, run under three emission scenarios (RCP 2.6, RCP 4.5, RCP 8.5), and downscaled using three different methods (delta SD, equidistant quantile mapping, piecewise asynchronous regression). Together, the three models, RCPs, and downscaling methods resulted...
This dataset contains input parameter and data files, as well as output files for simulations before calibration (pre-calibration) and after calibration (post-calibration) of solar radiation and potential evapotranspiration (ET) parameters. Simulated solar radiation and potential ET for nine near-native subbasins and three selected subareas [16, 71, 124] are included for parts of the Upper Rio Grande Basin in Colorado, New Mexico, Texas, and northern Mexico using the Precipitation-Runoff Modeling System (PRMS). Input data include pre-calibration input parameters for the entire Upper Rio Grande Basin developed from the National Hydrologic Model (NHM) parameter database, and model parameters after calibration (post-calibration)...
This dataset contains input parameter and data files, as well as output files for simulations prior to the distribution of parameters from near-native subbasins to uncalibrated hydrologic response units (HRUs) (pre-distribution) and after parameters are distributed to HRUs (post-distribution). Simulated and observed streamflow for sites along the mainstem of the Rio Grande River are included for parts of the Upper Rio Grande Basin in Colorado, New Mexico, Texas, and northern Mexico using the Precipitation-Runoff Modeling System (PRMS). Input data include pre-distribution input parameters for the entire Upper Rio Grande Basin. Pre-distribution parameters used as input to PRMS for step 3 are the post-calibration parameters...
These data include snow depth and snow water equivalence (SWE) for the 2022 and 2023 water years during 16 separate field campaigns. The field area is comprised of 311 surveyed points in, on the perimeter of, and surrounding six forest openings next to Coal Creek off Coal Bank Pass in the San Juan Mountains in Southwest Colorado, USA. These measurements were taken to look at the relationship between snow accumulation and snow melt patterns between forest gaps of various sizes, and forest edges of various sizes (edge of forest gaps). Canopy metrics, including canopy height, total gap area, mean distance to canopy, canopy closure, leaf area index, non-directional edginess, canopy edginess with a southern aspect, and...
Water availability in the upper Rio Grande Basin is dependent on winter and monsoon season precipitation. Consecutive years of drought and above average temperatures have diminished water supply and increased demand for water in this region. The increasing gap between water supply and demand is cause for concern. Climate projections for the southwestern and south central United States suggest that temperatures will continue to increase, affecting seasonal precipitation and water availability. To better manage current water supply and prepare for possible future changes, water managers need projections of future streamflow and landscape conditions that may affect future water supply. The project researchers are...
Categories: Project;
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OGC WMS Layer,
OGC WMS Service;
Tags: 2018,
CASC,
Climate response,
Completed,
Data Visualization & Tools,
The Rio Grande is a vital water source for the southwestern States of Colorado, New Mexico, and Texas and for northern Mexico. Because streamflow in the basin is highly altered, disentangling the impacts of climate change and changes in streamflow due to anthropogenic influences such as dams, diversions, and other forms of water use is difficult. Therefore, a model that simulates naturalized flow (defined as streamflow that would occur in the absence of anthropogenic modifications) was developed to determine to what degree changes in streamflow can be attributed to potential changes in future temperature and precipitation without quantifying future changes in anthropogenic influences. In this study, the calibrated...
The Rio Grande Basin Study (Basin Study) is a stakeholder-led project funded through the U.S. Bureau of Reclamation that is developing climate adaptation strategies to address the growing gap between water supply and demand in the Upper Rio Grande Basin in Colorado, New Mexico, and Texas. The role of the USGS in the Basin Study is to simulate future streamflow using downscaled climate model projection data as input to the Upper Rio Grande Basin Precipitation-Runoff Modeling System (PRMS) (Chavarria and others, 2020). Simulated streamflow for 27 climate scenarios at 63 sites along the mainstem Rio Grande and its tributaries is used as baseline hydrologic response to climate-change emission scenarios and downscaling...
Modeling forest change effects on snow is critical to resource management. However, many models either do not appropriately model canopy structure or cannot represent fine‐scale changes in structure following a disturbance. We applied a 1 m2 resolution energy budget snowpack model at a forested site in New Mexico, USA, affected by a wildfire, using input data from lidar to represent prefire and postfire canopy conditions. Both scenarios were forced with 37 years of equivalent meteorology to simulate the effect of fire‐mediated canopy change on snowpack under varying meteorology. Postfire, the simulated snow distribution was substantially altered, and despite an overall increase in snow, 32% of the field area displayed...
Categories: Publication;
Types: Citation
Accurately modeling the effects of variable forest structure and change on snow distribution and persistence is critical to water resource management. The resolution of many snow models is too coarse to represent heterogeneous canopy structure in forests, and therefore, most models simplify forest effects on snowpack mass and energy budgets. To quantify the loss of snowpack prediction from simplifications of forest canopy-mediated processes, we applied a high-resolution energy balance snowpack model at two forested sites at a fine (1 m2) and coarse (100 m2) spatial resolution. Simulating open and forested areas separately, as is done in many land surface models (LSMs), leads to biases between the coarse and fine-scale...
Categories: Publication;
Types: Citation
This data release contains inputs for and outputs from hydrologic simulations of the Upper Rio Hondo Subbasin, New Mexico using the Precipitation-Runoff Modeling System (PRMS). Input data for the entire Upper Rio Hondo Subbasin were developed, but output data only from the North Fork Eagle Creek subwatershed were used. Input data include parameter files for two PRMS models calibrated to prefire conditions and postfire conditions. Synthetic flow data used to calibrate PRMS for prefire conditions and postfire conditions are also included. Output data include output variable files for four PRMS models: two calibrated models (one for prefire conditions and one for postfire conditions) and two models used for scenarios...
This data release contains input and output data from hydrologic simulations of naturalized or near-native streamflow conditions in the Upper Rio Grande Basin (URGB) in Colorado, New Mexico, Texas, and northern Mexico by using the Precipitation-Runoff Modeling System (PRMS). The Upper Rio Grande Basin PRMS model was calibrated in a three step process by (1) calibrating solar radiation and potential evapotranspiration parameters by subarea for hydrologic response units (HRU) in the model domain, (2) calibrating streamflow parameters in nine subbasins identified to be “near-native” subbasins, or basins with low anthropogenic disturbance, and (3) distributing calibrated parameters from near-native subbasins to uncalibrated...
Canopy density and canopy structure metrics were derived for the San Juan Mountains of southwest Colorado from aerial point cloud data at a 1-meter (m) resolution. The aerial lidar data originated from the ‘CO_Southwest_NRCS_2018’ project prepared by Quantum Spatial for the U.S. Geological Survey (USGS) from a series of flyovers between 2018 and 2019 and were made available in 2021. Canopy density metrics include Canopy Closure (CC) and Leaf Area Index (LAI). Canopy Structure metrics include total gap area, mean distance to canopy, canopy edginess to the south and canopy edginess to the north. These data were used to partition 100 m grid cells over the same area for a snow melt model called SNOWMODEL. Each grid...
Water availability in the Upper Rio Grande Basin is dependent on winter and monsoon season precipitation. Consecutive years of drought and above average temperatures have diminished water supply and increased demand for water in the southwestern United States. The increasing gap between water supply and demand is cause for concern and climate projections for the southwestern United States suggest that temperatures will continue to increase, affecting seasonal precipitation and water availability potentially widening the water supply and demand gap. To better manage current supply and prepare for possible future changes, water managers need projections of future streamflow and landscape conditions that may affect...
Categories: Publication;
Types: Citation
Water availability in the Upper Rio Grande Basin is dependent on winter and monsoon season precipitation. Consecutive years of drought and above average temperatures have diminished water supply and increased demand for water in the southwestern United States. The increasing gap between water supply and demand is cause for concern and climate projections for the southwestern United States suggest that temperatures will continue to increase, affecting seasonal precipitation and water availability potentially widening the water supply and demand gap. To better manage current supply and prepare for possible future changes, water managers need projections of future streamflow and landscape conditions that may affect...
Categories: Publication;
Types: Citation
This data release contains SnowModel snow evolution simulation output from water years 2022 to 2023 (October 1, 2021, through September 30, 2023) on a 100-meter (m) geospatial grid for a 3 kilometer (km) × 2 km model domain near Coal Creek off Coal Bank Pass in the San Juan Mountains in southwest Colorado, USA. The three quantities simulated for this release were snow water equivalent for the standard model configuration (swe_standard), snow water equivalent for an open canopy model configuration (swe_open), and incoming shortwave radiation for the open canopy model configuration (qsin_open). The simulation used to produce these outputs was forced using meteorology from the National Land Data Assimilation System...
This dataset contains input parameter and data files, as well as output files for simulations prior to (pre-calibration) and after calibration (post-calibration) of streamflow parameters for nine near-native subbasins. Simulated and observed streamflow for nine near-native subbasins are included for parts of the Upper Rio Grande Basin in Colorado, New Mexico, Texas, and northern Mexico using the Precipitation-Runoff Modeling System (PRMS). Input data include pre-calibration input parameters for the entire Upper Rio Grande Basin. Pre-calibrated parameters used as input to PRMS for step 2 are the post-calibration parameters in Step 1-Solar Radiation and Potential ET calibration. Post-calibration model parameters include...
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