220 results — topic: Field Methods & Monitoring

Dataset

UAV Imagery of Marmot Burrows in Colorado

UAV flights were conducted between August 26, 2024, and September 1, 2024, at and around the Rocky Mountain Biological Laboratory in the East River Valley, Gothic, Colorado, USA (38°57′ N, 106°59′ W; approximately 2900 m elevation). The study area included marmot colonies located in two core zones,

Duporge, Isla2026DOI: 10.6084/m9.figshare.29114009
Dataset

Meteorological and Soil Data from Ecohydrology Sensor Towers at Pump House and Snodgrass Mountain in East River Watershed, Colorado, 2019-2025

This data package includes hourly meteorological and soil sensor data at eight ecohydrology monitoring sites in East River Watershed, Colorado as part of the Watershed Function Scientific Focus Area (WFSFA) research led by Lawrence Berkeley National Lab (LBNL). Four field sites were located on the h

Wu, Yuxin, Chou, Chunwei, Beutler, Curtis2026DOI: 10.15485/3007697Cited 1 times
Dataset

UAV Imagery of Marmot Burrows in Colorado

UAV flights were conducted between August 26, 2024, and September 1, 2024, at and around the Rocky Mountain Biological Laboratory in the East River Valley, Gothic, Colorado, USA (38°57′ N, 106°59′ W; approximately 2900 m elevation). The study area included marmot colonies located in two core zones,

Duporge, Isla2026DOI: 10.6084/m9.figshare.29114009.v1
Dataset

CHESS 2025: Leaf Area Index (LAI) for meadow, shrub, tree, and understory vegetation

This dataset contains Leaf Area Index (LAI) measurements made as part of the Colorado Headwaters Ecological Spectroscopy Study (CHESS) during June and July of 2025. Data were collected in the Upper Gunnison Basin, Colorado, across three study domains: the Upper East River (CRBU), Almont Triangle (AL

Todorov *, Sophia, Worsham *, H. Marshall, Breckheimer, Ian2026DOI: 10.15485/3022242
Dataset

SOS: Terrestrial Scanning Lidar L1 Upwind East Tower Raw Point Clouds. Version 1.0

Raw point clouds from the terrestrial scanning lidar #1 (L1) that was deployed on the upwind east flux tower near Crested Butte, Colorado for the SOS (Sublimation of Snow) campaign. The raw point clouds provide information about the distribution of blowing snow particles in the air in addition to va

Gutmann, E., Lundquist, J.2026DOI: 10.26023/1y3p-hsyz-0a09
Dataset

SOS: Terrestrial Scanning Lidar L2 Upwind East Tower Raw Point Clouds. Version 1.0

Raw point clouds from the terrestrial scanning lidar #2 (L2) that was deployed on the upwind east flux tower near Crested Butte, Colorado for the SOS (Sublimation of Snow) campaign. The raw point clouds provide information about the distribution of blowing snow particles in the air in addition to va

Gutmann, E., Lundquist, J.2026DOI: 10.26023/g9c5-pz82-ns0r
Dataset

SOS: Terrestrial Scanning Lidar L3 Upwind West Tower Raw Point Clouds. Version 1.0

Raw point clouds from the terrestrial scanning lidar #3 (L3) that was deployed on the upwind west flux tower near Crested Butte, Colorado for the SOS (Sublimation of Snow) campaign. The raw point clouds provide information about the distribution of blowing snow particles in the air in addition to va

Gutmann, E., Lundquist, J.2026DOI: 10.26023/gm9s-br2k-6a00
Dataset

SOS: Terrestrial Scanning Lidar L4 Upwind West Tower Raw Point Clouds. Version 1.0

Raw point clouds from the terrestrial scanning lidar #4 (L4) that was deployed on the upwind west flux tower near Crested Butte, Colorado for the SOS (Sublimation of Snow) campaign. The raw point clouds provide information about the distribution of blowing snow particles in the air in addition to va

Gutmann, E., Lundquist, J.2026DOI: 10.26023/h4ay-wsa3-ct0x
Dataset

SOS: Terrestrial Scanning Lidar L6 Downwind Tower Raw Point Clouds. Version 1.0

Raw point clouds from the terrestrial scanning lidar #6 (L6) that was deployed on the downwind flux tower near Crested Butte, Colorado for the SOS (Sublimation of Snow) campaign. The raw point clouds provide information about the distribution of blowing snow particles in the air in addition to valua

Gutmann, E., Lundquist, J.2026DOI: 10.26023/s2vd-jm09-a514
Dataset

SOS: Terrestrial Scanning Lidar L5 Downwind Tower Raw Point Clouds. Version 1.0

Raw point clouds from the terrestrial scanning lidar #5 (L5) that was deployed on the downwind flux tower near Crested Butte, Colorado for the SOS (Sublimation of Snow) campaign. The raw point clouds provide information about the distribution of blowing snow particles in the air in addition to valua

Gutmann, E., Lundquist, J.2026DOI: 10.26023/j4e4-amf7-2g0r
Dataset

Surface underway measurements of partial pressure (or fugacity) of carbon dioxide, salinity and water temperature collected from the sailing vessel HOLCIM during the Vendée Globe 2024 race in the Atlantic Ocean, Pacific Ocean, Indian Ocean from 2024-11-10 to 2025-01-25 (NCEI Accession 0310919)

This dataset includes data collected from the race sailing vessel HOLCIM during the Vendée Globe 2024 race. A flow-through membrane pCO2 sensor is integrated with the SubCTech Ocean pack. The vessel sailed around the world, from and back to Les Sables D'Olonnes (France), sampling in the Atlantic Oce

NCEI2026DOI: 10.25921/h176-tz06
Dataset

Data From: "Warming and snow loss increase reliance on old groundwater in a Colorado River headwater"

This repository contains the data and code associated with the paper titled "Warming and snow loss increase reliance on old groundwater in a Colorado River headwater," published in Nature Geoscience, 2026. This study seeks to answer how various ages of groundwater interact with mountainous streamflo

Erica Siirila-Woodburn, Nicholas Thiros, Michelle Newcomer2026DOI: 10.15485/3013287
Dataset

Data for "Depth of nutrient uptake by deep-rooted plants is regulated by water availability"

The data set consists of strontium (Sr) isotope ratios (87Sr/86Sr), water isotopes, soil cation concentrations, soil water potential sensor data, and results of 87Sr/86Sr mixing model. The plant canopy size files include the dataset of canopy dimension of sagebrush, lupine, and sunflower. The soil a

Langlang Li, John Christensen, Markus Bill2026DOI: 10.15485/2998779Cited 1 times
Dataset

Compilation of actual evapotranspiration and vegetation indices along critical riparian zones on the Navajo Nation from 2013-2023

These data were compiled for monitoring riparian zone trends and changes in the Navajo Nation as part of a study to document riparian ecosystem health and its water use in support of potential restoration efforts. The objective of our study was to monitor the short and medium-term effects on the rip

Pamela L Nagler2025
Dataset

Compilation of actual evapotranspiration and vegetation indices along critical riparian zones on the Navajo Nation from 2013-2023

These data were compiled for monitoring riparian zone trends and changes in the Navajo Nation as part of a study to document riparian ecosystem health and its water use in support of potential restoration efforts. The objective of our study was to monitor the short and medium-term effects on the rip

Pamela L Nagler2025
Dataset

Scripts and data to produce figures for the SVS2 paper submitted to GMD

The Soil, Vegetation, and snow model version 2.0 (SVS2) is a land surface model developed by Environment and Climate Change Canada (ECCC) to be used in the context of land surface prediction. SVS2 is described in a manuscript submitted to GMD (https://egusphere.copernicus.org/preprints/2025/eguspher

Vionnet, Vincent, Leroux, Nicolas, Royer, Alain2025DOI: 10.5281/zenodo.16760831
Dataset

Scripts and data to produce figures for the SVS2 paper submitted to GMD

The Soil, Vegetation, and snow model version 2.0 (SVS2) is a land surface model developed by Environment and Climate Change Canada (ECCC) to be used in the context of land surface prediction. SVS2 is described in a manuscript submitted to GMD (https://egusphere.copernicus.org/preprints/2025/eguspher

Vionnet, Vincent, Leroux, Nicolas, Royer, Alain2025DOI: 10.5281/zenodo.16760830Cited 1 times
Dataset

Scripts and data to produce figures for the SVS2 paper submitted to GMD

The Soil, Vegetation, and snow model version 2.0 (SVS2) is a land surface model developed by Environment and Climate Change Canada (ECCC) to be used in the context of land surface prediction. SVS2 is described in a manuscript submitted to GMD (https://egusphere.copernicus.org/preprints/2025/eguspher

Vionnet, Vincent, Leroux, Nicolas, Royer, Alain2025DOI: 10.5281/zenodo.16782503
Dataset

Colorado Cold-Air Pooling Maps and SNOTEL Station Classifications

This dataset contains maps of cold-air pooling (CAP) across Colorado at 100m resolution (Colorado_100m.nc) and the region surrounding the East River watershed, CO at 30m resolution (EastRiver_30m.nc). Classifications were determined using a Python implementation of the algorithm originally developed

Cramblitt, John, Lundquist, Jessica2025DOI: 10.5281/zenodo.17168089
Document

Reclamation and Exploitation

VER H EAR O F RECLAMATI ON law' s 16 0-acre limi tatio n o n E water d eliveri es to irrigators? H ave you been told tha t this is " pe tty p o liti cal tyra nny," inefficient a nd uneco nom ic? Tha t because o f it the h o usewife p ays m o r e for foo d in the m arke t? T hat it is an o utmoded my