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Overview Research Site Status and Provenance Access and Downloads
Name of Research Project
Related Project
Part
Global Water Futures
Dataset Title
Basin Geometry and Mountain Snowpack Responses to Climate Change: Data, Code, and Figures
Additional Information
GeoNetwork record: www.gwfnet.net/geonetwork/srv/eng/catalog.search#/metadata/6032b57a-0dad-473d-bbf2-42f98b2e3426
Abstract
This dataset contains the code and data files needed to produce the analyses and figures in Shea et al. (2021), doi:10.3389/frwa.2021.604275. The data used in this study are derived from publicly available data sets. These include global elevation data, river basin boundaries, climate normals, automated snow pillows, and manual snow course observations. The Cold Regions Hydrological Model (CRHM, v.05/15/19) was used to produce daily estimates of snowmelt for 50 basins using identical elevation ranges and bands, identical accumulation gradients, and identical climate inputs. Only the hypsometry (area-elevation distribution) was varied for each model run. Analysis of hypsometry, climate inputs, and CRHM outputs is given in a Jupyter notebook running Python 3.7.6.
Purpose
This dataset supports the Global Water Futures project.
Citations
Shea, J., Whitfield, P., Fang, X., Pomeroy, J. (2021). Basin Geometry and Mountain Snowpack Responses to Climate Change: Data, Code, and Figures [Dataset]. Federated Research Data Repository. https://doi.org/10.20383/102.0318 Shea, J. M., Whitfield, P. H., Fang, X., Pomeroy, J. W. (2021). The Role of Basin Geometry in Mountain Snowpack Responses to Climate Change. Front. Water 3: 604275. https://doi.org/10.3389/frwa.2021.604275
Temporal Extent
Begin Date
End Date
1948-01-01
2020-01-01
Geographic Bounding Box
West Boundary Longitude
-123
East Boundary Longitude
-112
North Boundary Latitude
55
South Boundary Latitude
47
Dataset Version
1
Dataset Creation Date
2021-03-18
Status of data collection/production
○ Planned
○ In Progress
○ Abandoned
◉ Complete
Dataset Completion or Abandonment Date
1
Data Update Frequency
○ Continually
○ Daily
○ Weekly
○ Biweekly
○ Monthly
○ Anually
○ As needed
○ Irregular
◉ None planned
○ Unknown
Primary Source of Data
◻ Unknown/Unspecified
◻ Census
◻ Field collected samples
◻ Field experiment
◻ Field observation
◻ Field survey
◻ Human biological samples
◻ Lab experiment
▣ Model simulation
▣ Previously collected
◻ Qualitative (from observations or interviews)
◻ Social survey
◻ Traditional knowledge
◻ Other Source of Data (Please specify in field below)
Data Lineage (if applicable). Please include versions (e.g., input and forcing data, models, and coupling modules; instrument measurements; surveys; sample collections; etc.)
1. Description of methods used for collection/generation of data: Temperature and snow observations (snow course and snow pillow) obtained from government repositories. Elevation data obtained from GLOBE DEM. Model outputs generated by CRHM. Manual snow survey site locations (Government of BC - https://catalogue.data.gov.bc.ca/dataset/9f653102-5627-45a7-bd4c-686e365ee04a ) Manual snow survey site data (Government of BC - https://catalogue.data.gov.bc.ca/dataset/705df46f-e9d6-4124-bc4a-66f54c07b228 ) Snow pillow data (Government of BC - https://aqrt.nrs.gov.bc.ca/Data/ ) Climate Normals (ECCC - https://climate.weather.gc.ca/climate_normals/index_e.html ) Global Land One-kilometer Base Elevation (NOAA - https://doi.org/10.7289/V52R3PMS ) 2. Methods for processing the data: NA 3. Instrument- or software-specific information needed to interpret the data: The version of Python used in this analysis is 3.7.6. Required packages are listed below in the code-specific information section and in the notebook preamble. ----------------------------------------------------------------- CODE-SPECIFIC INFORMATION FOR: BasinHypsometryCRHM-Final.ipynb ----------------------------------------------------------------- 1. Brief description of the code: Jupyter notebook does the following: - calculates and clusters basin hypsometries - assesses the skill of simple linear accumulation gradients and synthetic temperatures against observational data - imports results of the CRHM model runs to assess snow pack and snow melt responses to increased temperatures - produces figures contained in the Shea et al. (2021) publication 2. List required dependencies: CRHM 05/15/19 Python 3.7.6 datetime 4.3 matplotlib 3.1.2 matplotlib-base 3.1.2 pandas 0.25.3 glob2 0.7 scipy 1.3.2 geopandas 0.8.0 scikit-learn 0.22 3. Instructions to install or use the code: Use jupyter notebook to open the code, and ensure that all packages are installed. Outputs from the CRHM model are provided in the data folder, but users can also obtain and run the CRHM model using the .obs files contained in the CRHMobs subfolder. 4. List any required input: Data subfolder. 5. List expected output: To produce figures used in the paper, create a new subfolder called 'Figure' and uncomment the plt.savefig() commands.
Terms of Use
These data are available under a CC BY 4.0 license ( https://creativecommons.org/licenses/by/4.0/legalcode ). The code published with this dataset is available under the GNU General Public License v3.0 ( https://www.gnu.org/licenses/gpl-3.0.en.html ).
Does the data have access restrictions?
▣ No restriction (data is currently open to public)
◻ Limited (data is currently under embargo until publication)
◻ Limited (data involves intellectual property issues related to local or traditional knowledge)
◻ Limited (release of data may cause harm to the environment or to the public)
◻ Limited (pre-existing data has been used and is subject to access restrictions)
◻ Limited (data involves human subjects)
◻ Limited (data is supported by industry partnerships)
◻ Limited (data is supported by government partnerships)
Download Links and Instructions
Download the data from: https://doi.org/10.20383/102.0318
Total Size of all Dataset Files (GB)
0.039
File formats and online databases
◻ Link to online database or web services (e.g., WISKI, ECCC)
◻ Archive files (.zip, .rar, .7z, .tar, .tgz, .tar.gz, etc.)
▣ CSV files (.csv - comma or tab separated value files)
◻ Excel document files (.xlsx, .xls)
▣ Image files (e.g., .tiff, .jpeg, .png, .gif, etc.)
◻ NetCDF files (.netcdf, .nc)
▣ Text files (.txt)
◻ Word document files (.docx, .doc)
▣ Other (Please specify in field below)
Other Data Formats (if applicable)
.shp
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T-2021-06-09-21dykb21xDw0aVRAng0DFOHw Dataset 1.2