Snow water equivalent time-series forecasting in Ontario, Canada, in link to large atmospheric circulations.
The present study applies different time-series models for forecasting daily and monthly snow water equivalent (SWE) data in Ontario, Canada, during 1987-2011. For daily time series, which showed a significant negative trend, four categories of the autoregressive moving-average (ARMA) and ARMA model...
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Online Access: | https://espace.inrs.ca/id/eprint/4280/ https://doi.org/10.1002/hyp.10184 |
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ftinrsquebec:oai:espace.inrs.ca:4280 2023-05-15T17:33:48+02:00 Snow water equivalent time-series forecasting in Ontario, Canada, in link to large atmospheric circulations. Sarhadi, Ali H. Kelly, Richard Modarres, Reza 2014 https://espace.inrs.ca/id/eprint/4280/ https://doi.org/10.1002/hyp.10184 unknown Sarhadi, Ali H., Kelly, Richard et Modarres, Reza (2014). Snow water equivalent time-series forecasting in Ontario, Canada, in link to large atmospheric circulations. Hydrological Processes , vol. 28 , nº 16. p. 4640-4653. DOI:10.1002/hyp.10184 <https://doi.org/10.1002/hyp.10184>. doi:10.1002/hyp.10184 Ontario SARIMAX snow water equivalent time-series forecasting time-trend ARMAX Article Évalué par les pairs 2014 ftinrsquebec https://doi.org/10.1002/hyp.10184 2023-02-10T11:42:56Z The present study applies different time-series models for forecasting daily and monthly snow water equivalent (SWE) data in Ontario, Canada, during 1987-2011. For daily time series, which showed a significant negative trend, four categories of the autoregressive moving-average (ARMA) and ARMA model with exogenous variables (ARMAX) were applied. The North Atlantic Oscillation, Southern Oscillation Index and Pacific/North American Pattern, as large-scale atmospheric anomalies, as well as temperature time series are considered as exogenous variables for ARMAX models. According to the multicriteria performance evaluation, a time-trend ARMAX model demonstrated the best performance for modelling and forecasting daily SWE. Two models, seasonal autoregressive integrated moving average (SARIMA) and SARIMA with exogenous variables (SARIMAX), were also fitted to the monthly SWE time series. The results revealed that the SARIMAX model showed a better performance than the SARIMA model according to multicriteria evaluation. The three nonparametric tests, Wilcoxon, Levene and Kolmogorov-Smirnov for forecasting evaluation demonstrated that the selected time-series models had enough reliability for short-term SWE forecasting in Ontario. The results of this study also demonstrate the importance of incorporating both trend and appropriate exogenous variables for SWE time-series modelling and forecasting. Article in Journal/Newspaper North Atlantic North Atlantic oscillation Institut national de la recherche scientifique, Québec: Espace INRS Canada Pacific Sarima ENVELOPE(29.040,29.040,69.037,69.037) Hydrological Processes 28 16 4640 4653 |
institution |
Open Polar |
collection |
Institut national de la recherche scientifique, Québec: Espace INRS |
op_collection_id |
ftinrsquebec |
language |
unknown |
topic |
Ontario SARIMAX snow water equivalent time-series forecasting time-trend ARMAX |
spellingShingle |
Ontario SARIMAX snow water equivalent time-series forecasting time-trend ARMAX Sarhadi, Ali H. Kelly, Richard Modarres, Reza Snow water equivalent time-series forecasting in Ontario, Canada, in link to large atmospheric circulations. |
topic_facet |
Ontario SARIMAX snow water equivalent time-series forecasting time-trend ARMAX |
description |
The present study applies different time-series models for forecasting daily and monthly snow water equivalent (SWE) data in Ontario, Canada, during 1987-2011. For daily time series, which showed a significant negative trend, four categories of the autoregressive moving-average (ARMA) and ARMA model with exogenous variables (ARMAX) were applied. The North Atlantic Oscillation, Southern Oscillation Index and Pacific/North American Pattern, as large-scale atmospheric anomalies, as well as temperature time series are considered as exogenous variables for ARMAX models. According to the multicriteria performance evaluation, a time-trend ARMAX model demonstrated the best performance for modelling and forecasting daily SWE. Two models, seasonal autoregressive integrated moving average (SARIMA) and SARIMA with exogenous variables (SARIMAX), were also fitted to the monthly SWE time series. The results revealed that the SARIMAX model showed a better performance than the SARIMA model according to multicriteria evaluation. The three nonparametric tests, Wilcoxon, Levene and Kolmogorov-Smirnov for forecasting evaluation demonstrated that the selected time-series models had enough reliability for short-term SWE forecasting in Ontario. The results of this study also demonstrate the importance of incorporating both trend and appropriate exogenous variables for SWE time-series modelling and forecasting. |
format |
Article in Journal/Newspaper |
author |
Sarhadi, Ali H. Kelly, Richard Modarres, Reza |
author_facet |
Sarhadi, Ali H. Kelly, Richard Modarres, Reza |
author_sort |
Sarhadi, Ali H. |
title |
Snow water equivalent time-series forecasting in Ontario, Canada, in link to large atmospheric circulations. |
title_short |
Snow water equivalent time-series forecasting in Ontario, Canada, in link to large atmospheric circulations. |
title_full |
Snow water equivalent time-series forecasting in Ontario, Canada, in link to large atmospheric circulations. |
title_fullStr |
Snow water equivalent time-series forecasting in Ontario, Canada, in link to large atmospheric circulations. |
title_full_unstemmed |
Snow water equivalent time-series forecasting in Ontario, Canada, in link to large atmospheric circulations. |
title_sort |
snow water equivalent time-series forecasting in ontario, canada, in link to large atmospheric circulations. |
publishDate |
2014 |
url |
https://espace.inrs.ca/id/eprint/4280/ https://doi.org/10.1002/hyp.10184 |
long_lat |
ENVELOPE(29.040,29.040,69.037,69.037) |
geographic |
Canada Pacific Sarima |
geographic_facet |
Canada Pacific Sarima |
genre |
North Atlantic North Atlantic oscillation |
genre_facet |
North Atlantic North Atlantic oscillation |
op_relation |
Sarhadi, Ali H., Kelly, Richard et Modarres, Reza (2014). Snow water equivalent time-series forecasting in Ontario, Canada, in link to large atmospheric circulations. Hydrological Processes , vol. 28 , nº 16. p. 4640-4653. DOI:10.1002/hyp.10184 <https://doi.org/10.1002/hyp.10184>. doi:10.1002/hyp.10184 |
op_doi |
https://doi.org/10.1002/hyp.10184 |
container_title |
Hydrological Processes |
container_volume |
28 |
container_issue |
16 |
container_start_page |
4640 |
op_container_end_page |
4653 |
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1766132420044652544 |