Improving gridded snow water equivalent products in British Columbia, Canada: multi-source data fusion by neural network models
Estimates of surface snow water equivalent (SWE) in mixed alpine environments with seasonal melts are particularly difficult in areas of high vegetation density, topographic relief, and snow accumulations. These three confounding factors dominate much of the province of British Columbia (BC), Canada...
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fttriple:oai:gotriple.eu:oai:doaj.org/article:6c87ea785ebf49ef8025a20e4b617f5a 2023-05-15T18:32:19+02:00 Improving gridded snow water equivalent products in British Columbia, Canada: multi-source data fusion by neural network models A. M. Snauffer W. W. Hsieh A. J. Cannon M. A. Schnorbus 2018-03-01 https://doi.org/10.5194/tc-12-891-2018 https://www.the-cryosphere.net/12/891/2018/tc-12-891-2018.pdf https://doaj.org/article/6c87ea785ebf49ef8025a20e4b617f5a en eng Copernicus Publications doi:10.5194/tc-12-891-2018 1994-0416 1994-0424 https://www.the-cryosphere.net/12/891/2018/tc-12-891-2018.pdf https://doaj.org/article/6c87ea785ebf49ef8025a20e4b617f5a undefined The Cryosphere, Vol 12, Pp 891-905 (2018) geo envir Journal Article https://vocabularies.coar-repositories.org/resource_types/c_6501/ 2018 fttriple https://doi.org/10.5194/tc-12-891-2018 2023-01-22T19:25:59Z Estimates of surface snow water equivalent (SWE) in mixed alpine environments with seasonal melts are particularly difficult in areas of high vegetation density, topographic relief, and snow accumulations. These three confounding factors dominate much of the province of British Columbia (BC), Canada. An artificial neural network (ANN) was created using as predictors six gridded SWE products previously evaluated for BC. Relevant spatiotemporal covariates were also included as predictors, and observations from manual snow surveys at stations located throughout BC were used as target data. Mean absolute errors (MAEs) and interannual correlations for April surveys were found using cross-validation. The ANN using the three best-performing SWE products (ANN3) had the lowest mean station MAE across the province. ANN3 outperformed each product as well as product means and multiple linear regression (MLR) models in all of BC's five physiographic regions except for the BC Plains. Subsequent comparisons with predictions generated by the Variable Infiltration Capacity (VIC) hydrologic model found ANN3 to better estimate SWE over the VIC domain and within most regions. The superior performance of ANN3 over the individual products, product means, MLR, and VIC was found to be statistically significant across the province. Article in Journal/Newspaper The Cryosphere Unknown British Columbia ENVELOPE(-125.003,-125.003,54.000,54.000) Canada The Cryosphere 12 3 891 905 |
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geo envir A. M. Snauffer W. W. Hsieh A. J. Cannon M. A. Schnorbus Improving gridded snow water equivalent products in British Columbia, Canada: multi-source data fusion by neural network models |
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geo envir |
description |
Estimates of surface snow water equivalent (SWE) in mixed alpine environments with seasonal melts are particularly difficult in areas of high vegetation density, topographic relief, and snow accumulations. These three confounding factors dominate much of the province of British Columbia (BC), Canada. An artificial neural network (ANN) was created using as predictors six gridded SWE products previously evaluated for BC. Relevant spatiotemporal covariates were also included as predictors, and observations from manual snow surveys at stations located throughout BC were used as target data. Mean absolute errors (MAEs) and interannual correlations for April surveys were found using cross-validation. The ANN using the three best-performing SWE products (ANN3) had the lowest mean station MAE across the province. ANN3 outperformed each product as well as product means and multiple linear regression (MLR) models in all of BC's five physiographic regions except for the BC Plains. Subsequent comparisons with predictions generated by the Variable Infiltration Capacity (VIC) hydrologic model found ANN3 to better estimate SWE over the VIC domain and within most regions. The superior performance of ANN3 over the individual products, product means, MLR, and VIC was found to be statistically significant across the province. |
format |
Article in Journal/Newspaper |
author |
A. M. Snauffer W. W. Hsieh A. J. Cannon M. A. Schnorbus |
author_facet |
A. M. Snauffer W. W. Hsieh A. J. Cannon M. A. Schnorbus |
author_sort |
A. M. Snauffer |
title |
Improving gridded snow water equivalent products in British Columbia, Canada: multi-source data fusion by neural network models |
title_short |
Improving gridded snow water equivalent products in British Columbia, Canada: multi-source data fusion by neural network models |
title_full |
Improving gridded snow water equivalent products in British Columbia, Canada: multi-source data fusion by neural network models |
title_fullStr |
Improving gridded snow water equivalent products in British Columbia, Canada: multi-source data fusion by neural network models |
title_full_unstemmed |
Improving gridded snow water equivalent products in British Columbia, Canada: multi-source data fusion by neural network models |
title_sort |
improving gridded snow water equivalent products in british columbia, canada: multi-source data fusion by neural network models |
publisher |
Copernicus Publications |
publishDate |
2018 |
url |
https://doi.org/10.5194/tc-12-891-2018 https://www.the-cryosphere.net/12/891/2018/tc-12-891-2018.pdf https://doaj.org/article/6c87ea785ebf49ef8025a20e4b617f5a |
long_lat |
ENVELOPE(-125.003,-125.003,54.000,54.000) |
geographic |
British Columbia Canada |
geographic_facet |
British Columbia Canada |
genre |
The Cryosphere |
genre_facet |
The Cryosphere |
op_source |
The Cryosphere, Vol 12, Pp 891-905 (2018) |
op_relation |
doi:10.5194/tc-12-891-2018 1994-0416 1994-0424 https://www.the-cryosphere.net/12/891/2018/tc-12-891-2018.pdf https://doaj.org/article/6c87ea785ebf49ef8025a20e4b617f5a |
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undefined |
op_doi |
https://doi.org/10.5194/tc-12-891-2018 |
container_title |
The Cryosphere |
container_volume |
12 |
container_issue |
3 |
container_start_page |
891 |
op_container_end_page |
905 |
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1766216418147172352 |