Snow Depth Datasets for Snodgrass Catchment, Colorado, Water Year 2022-2023

Wang, Lijing; Wang, Chen; Dafflon, Baptiste

doi:10.15485/2572212

Title: Snow Depth Datasets for Snodgrass Catchment, Colorado, Water Year 2022-2023

Dataset
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Abstract

This data package presents snow depths data from distributed temperature probes at 18 locations near Snodgrass catchment, Colorado. These data show that snow melt-out dates are approximately one or two weeks later under evergreen forests compared to other vegetation types even at the same elevation. These data were collected to understand how snowmelt heterogeneity impacts headwater hydrology, including streamflow and groundwater levels. They were also used to compare with process-based model simulations of snow depth to evaluate whether the model accurately represents snowmelt dynamics and their effects on headwater hydrology. Snow_DTPs_locations.csv includes all probes locations and their associated elevation and vegetation types. Snow_Depth_Snodgrass_WY2022_2023.csv includes processed snow depths datasets for Water Year (WY) 2022 and 2023. This dataset also includes a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata and a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type. Several probes have recordings for WY 2021.

Authors:

;

University of Connecticut
Lawrence Berkeley National Laboratory

Publication Date:: Wed Jan 01 04:00:00 UTC 2025

DOE Contract Number:: AC02-05CH11231

Research Org.:: Watershed Function SFA

Sponsoring Org.:: U.S. DOE > Office of Science > Biological and Environmental Research (BER)

Subject:: 54 ENVIRONMENTAL SCIENCES; EARTH SCIENCE > CLIMATE INDICATORS > CRYOSPHERIC INDICATORS > SNOW DEPTH; EARTH SCIENCE > TERRESTRIAL HYDROSPHERE > SNOW/ICE; ESS-DIVE CSV File Formatting Guidelines Reporting Format; ESS-DIVE File Level Metadata Reporting Format; headwater hydrology; snowmelt heterogeneity

OSTI Identifier:: 2572212

DOI:: https://doi.org/10.15485/2572212

Citation Formats


                    Wang, Lijing, Wang, Chen, and Dafflon, Baptiste. Snow Depth Datasets for Snodgrass Catchment, Colorado, Water Year 2022-2023.  United States: N. p., 2025. 
        Web.  doi:10.15485/2572212.

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                    Wang, Lijing, Wang, Chen, & Dafflon, Baptiste. Snow Depth Datasets for Snodgrass Catchment, Colorado, Water Year 2022-2023.  United States.  doi:https://doi.org/10.15485/2572212

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                    Wang, Lijing, Wang, Chen, and Dafflon, Baptiste. 2025.  
"Snow Depth Datasets for Snodgrass Catchment, Colorado, Water Year 2022-2023".  United States.  doi:https://doi.org/10.15485/2572212.  https://www.osti.gov/servlets/purl/2572212. Pub date:Wed Jan 01 04:00:00 UTC 2025

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@article{osti_2572212,

  title        = {Snow Depth Datasets for Snodgrass Catchment, Colorado, Water Year 2022-2023},

  author       = {Wang, Lijing and Wang, Chen and Dafflon, Baptiste},

  abstractNote = {This data package presents snow depths data from distributed temperature probes at 18 locations near Snodgrass catchment, Colorado. These data show that snow melt-out dates are approximately one or two weeks later under evergreen forests compared to other vegetation types even at the same elevation. These data were collected to understand how snowmelt heterogeneity impacts headwater hydrology, including streamflow and groundwater levels. They were also used to compare with process-based model simulations of snow depth to evaluate whether the model accurately represents snowmelt dynamics and their effects on headwater hydrology. Snow_DTPs_locations.csv includes all probes locations and their associated elevation and vegetation types. Snow_Depth_Snodgrass_WY2022_2023.csv includes processed snow depths datasets for Water Year (WY) 2022 and 2023. This dataset also includes a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata and a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type. Several probes have recordings for WY 2021.},

  doi          = {10.15485/2572212},

  journal      = {},

  number       = ,

  volume       = ,

  place        = {United States},

  year         = {Wed Jan 01 04:00:00 UTC 2025},

  month        = {Wed Jan 01 04:00:00 UTC 2025}

}

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DOI: https://doi.org/10.15485/2572212

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