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Supporting Materials for: Advancing Open and Reproducible Water Data Science by Integrating Data Analytics with an Online Data Repository


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Type: Resource
Storage: The size of this resource is 1.6 MB
Created: Oct 11, 2024 at 7:04 p.m. (UTC)
Last updated: Mar 10, 2025 at 1:38 p.m. (UTC)
Published date: Mar 10, 2025 at 1:38 p.m. (UTC)
DOI: 10.4211/hs.7440c7feae1f428d91c1e510d23d3e54
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Sharing Status: Published
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Abstract

This HydroShare resource was created as a demonstration of how a reproducible data science workflow can be created and shared using HydroShare. The hsclient Python Client package for HydroShare is used to show how the content files for the analysis can be managed and shared automatically in HydroShare. The content files include a Jupyter notebook that demonstrates a simple regression analysis to develop a model of annual maximum discharge in the Logan River in northern Utah, USA from annual maximum snow water equivalent data from a snowpack telemetry (SNOTEL) monitoring site located in the watershed. Streamflow data are retrieved from the United States Geological Survey (USGS) National Water Information System using the dataretrieval package. Snow water equivalent data are retrieved from the United States Department of Agriculture Natural Resources Conservation Service (NRCS) SNOTEL system. An additional notebook demonstrates how to use hsclient to retrieve data from HydroShare, load it into a performant data object, and then use the data for visualization and analysis. For a full description of the workflows and technologies used, see the paper linked in the Related Resources section on this page.

Subject Keywords

Coverage

Spatial

Coordinate System/Geographic Projection:
WGS 84 EPSG:4326
Coordinate Units:
Decimal degrees
Place/Area Name:
Logan River Gage, Utah
Longitude
-111.7827°
Latitude
41.7433°

Content

Related Resources

This resource is described by Horsburgh, J. S., Black, S., Castronova, A., Dash, P. K. (2025). Advancing open and reproducible water data science by intgrating data analytics with an online repository, Environmental Modelling & Software, 106422, https://doi.org/10.1016/j.envsoft.2025.106422

Credits

Funding Agencies

This resource was created using funding from the following sources:
Agency Name Award Title Award Number
National Science Foundation Collaborative Research: Elements: Advancing Data Science and Analytics for Water (DSAW) OAC 1931297

How to Cite

Horsburgh, J. S. (2025). Supporting Materials for: Advancing Open and Reproducible Water Data Science by Integrating Data Analytics with an Online Data Repository, HydroShare, https://doi.org/10.4211/hs.7440c7feae1f428d91c1e510d23d3e54

This resource is shared under the Creative Commons Attribution CC BY.

http://creativecommons.org/licenses/by/4.0/
CC-BY

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