Articles | Volume 12, issue 3
https://doi.org/10.5194/tc-12-891-2018
https://doi.org/10.5194/tc-12-891-2018
Research article
 | 
12 Mar 2018
Research article |  | 12 Mar 2018

Improving gridded snow water equivalent products in British Columbia, Canada: multi-source data fusion by neural network models

Andrew M. Snauffer, William W. Hsieh, Alex J. Cannon, and Markus A. Schnorbus

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Short summary
Estimating winter snowpack throughout British Columbia is challenging due to the complex terrain, thick forests, and high snow accumulations present. This paper describes a way to make better snow estimates by combining publicly available data using machine learning, a branch of artificial intelligence research. These improved estimates will help water resources managers better plan for changes in rivers and lakes fed by spring snowmelt and will aid other research that supports such planning.