This site requires Cookies enabled in your browser for login.
WaterNet Home
WaterNet
for
pour le
Canada
Menu
WaterNet
Home
GWFO
Home
Master
List
Data
Centre
Collections
X
Defaults
Select All
Websites
X
Global Water Futures Observatories (GWFO) Global Water Futures (GWF) Global Institute for Water Security (GIWS) International Network of Alpine Research Catchment Hydrology
Legacy Research Programs
X
Changing Cold Regions Network (CCRN) Drought Research Initiative (DRI) International Network of Alpine Research Catchment Hydrology (Legacy Site) Improving Processes & Parameterization for Prediction in Cold Regions Hydrology (IP3) The Mackenzie Global Energy and Water Cycle Experiment (GEWEX) Study (MAGS)
Legacy sites
Map
Utilities
X
Account Settings Metadata Editor Record List Alias List Editor
Data Centre
Data Type Editor
. . .
X
Clear
Select All
Advanced Search
Related items loading ...
Fetching Chart ...
Publication Additional Information Download
Publication Type
Journal Article
Authorship
Appels, W. M., Bradford, L., Chun, K. P., Coles, A. E., & Strickert, G.
Title
DIY meteorology: Use of citizen science to monitor snow dynamics in a data-sparse city
Year
2017
Publication Outlet
FACETS 2, 734-753
DOI
https://doi.org/10.1139/facets-2017-0030
Citation
Appels, W. M., Bradford, L., Chun, K. P., Coles, A. E., & Strickert, G. (2017). DIY meteorology: Use of citizen science to monitor snow dynamics in a data-sparse city, FACETS 2, 734-753. https://doi.org/10.1139/facets-2017-0030
Abstract
Cities are under pressure to operate their services effectively and project costs of operations across various timeframes. In high-latitude and high-altitude urban centers, snow management is one of the larger unknowns and has both operational and budgetary limitations. Snowfall and snow depth observations within urban environments are important to plan snow clearing and prepare for the effects of spring runoff on cities’ drainage systems. In-house research functions are expensive, but one way to overcome that expense and still produce effective data is through citizen science. In this paper, we examine the potential to use citizen science for snowfall data collection in urban environments. A group of volunteers measured daily snowfall and snow depth at an urban site in Saskatoon (Canada) during two winters. Reliability was assessed with a statistical consistency analysis and a comparison with other data sets collected around Saskatoon. We found that citizen-science-derived data were more reliable and relevant for many urban management stakeholders. Feedback from the participants demonstrated reflexivity about social learning and a renewed sense of community built around generating reliable and useful data. We conclude that citizen science holds great potential to improve data provision for effective and sustainable city planning and greater social learning benefits overall.
Program Affiliations
GWF: Global Water Futures
Publication Stage
Published
Download Links
https://doi.org/10.1139/facets-2017-0030
© 2026 - WaterNet Version 2026-06-01
Global Water Futures Observatories
Powered by
G W F Net
T-2022-12-05-51atBIWy1dUWGBI53Z51eAtmw Publication 1.0