Five centuries of reconstructed streamflow in Athabasca River Basin, Canada: Non-stationarity and teleconnection to climate patterns
Given the challenge to estimate representative long-term natural variability of streamflow from limited observed data, a hierarchical, multilevel Bayesian regression (HBR) was developed to reconstruct the 1489–2006 annual streamflow data at six Athabasca River Basin (ARB) gauging stations based on 1...
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Online Access: | http://hdl.handle.net/10852/82226 http://urn.nb.no/URN:NBN:no-85124 https://doi.org/10.1016/j.scitotenv.2020.141330 |
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ftoslouniv:oai:www.duo.uio.no:10852/82226 2023-05-15T15:26:03+02:00 Five centuries of reconstructed streamflow in Athabasca River Basin, Canada: Non-stationarity and teleconnection to climate patterns Wu, Yenan Gan, Thian Yew She, Yuntong Xu, Chong-Yu Yan, Haibin 2020-12-28T15:41:03Z http://hdl.handle.net/10852/82226 http://urn.nb.no/URN:NBN:no-85124 https://doi.org/10.1016/j.scitotenv.2020.141330 EN eng http://urn.nb.no/URN:NBN:no-85124 Wu, Yenan Gan, Thian Yew She, Yuntong Xu, Chong-Yu Yan, Haibin . Five centuries of reconstructed streamflow in Athabasca River Basin, Canada: Non-stationarity and teleconnection to climate patterns. Science of the Total Environment. 2020, 746 http://hdl.handle.net/10852/82226 1863580 info:ofi/fmt:kev:mtx:ctx&ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Science of the Total Environment&rft.volume=746&rft.spage=&rft.date=2020 Science of the Total Environment 746 https://doi.org/10.1016/j.scitotenv.2020.141330 URN:NBN:no-85124 Fulltext https://www.duo.uio.no/bitstream/handle/10852/82226/2/WU%2BYenan_preprint.pdf 0048-9697 Journal article Tidsskriftartikkel SubmittedVersion 2020 ftoslouniv https://doi.org/10.1016/j.scitotenv.2020.141330 2021-01-20T23:30:59Z Given the challenge to estimate representative long-term natural variability of streamflow from limited observed data, a hierarchical, multilevel Bayesian regression (HBR) was developed to reconstruct the 1489–2006 annual streamflow data at six Athabasca River Basin (ARB) gauging stations based on 14 tree ring chronologies. Seven nested models were developed to maximize the applications of available tree ring predictors. Based on results of goodness-of-fit tests, the HBR developed was skillful and reliable in reconstructing the streamflow of ARB. From five centuries of reconstructed streamflow for ARB, five or six abrupt change points are detected. The streamflow time series obtained from a backward moving, 46-year window for six gauging sites in ARB vary significantly over five centuries (1489–2006) and at times could exceed the 90% and/or 95% confidence intervals, denoting significant non-stationarities. Apparently changes in the mean state and the lag-1 autocorrelation of reconstructed streamflow across the gauging sites can be similar or radically different from each other. These nonstationary features imply that the default stationary assumption is not applicable in ARB. Further, the reconstructed streamflow shows statistically significant oscillations at interannual, interdecadal and multidecadal time scales and are teleconnected to climate patterns such as El Niño Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO) and Atlantic Multi-decadal Oscillation (AMO). A composite analysis shows that La Niña (El Niño), cold (warm) PDO, and cold (warm) AMO events are typically associated with increased (decreased) streamflow anomalies of ARB. The reconstructed streamflow data provides us the full range of streamflow variability and recurrence characteristics of extremes spanned over five centuries from which it is useful for us to evaluate and manage the current water systems of ARB more effectively and a better risk analysis of future droughts of ARB. Article in Journal/Newspaper Athabasca River Universitet i Oslo: Digitale utgivelser ved UiO (DUO) Athabasca River Canada Pacific Science of The Total Environment 746 141330 |
institution |
Open Polar |
collection |
Universitet i Oslo: Digitale utgivelser ved UiO (DUO) |
op_collection_id |
ftoslouniv |
language |
English |
description |
Given the challenge to estimate representative long-term natural variability of streamflow from limited observed data, a hierarchical, multilevel Bayesian regression (HBR) was developed to reconstruct the 1489–2006 annual streamflow data at six Athabasca River Basin (ARB) gauging stations based on 14 tree ring chronologies. Seven nested models were developed to maximize the applications of available tree ring predictors. Based on results of goodness-of-fit tests, the HBR developed was skillful and reliable in reconstructing the streamflow of ARB. From five centuries of reconstructed streamflow for ARB, five or six abrupt change points are detected. The streamflow time series obtained from a backward moving, 46-year window for six gauging sites in ARB vary significantly over five centuries (1489–2006) and at times could exceed the 90% and/or 95% confidence intervals, denoting significant non-stationarities. Apparently changes in the mean state and the lag-1 autocorrelation of reconstructed streamflow across the gauging sites can be similar or radically different from each other. These nonstationary features imply that the default stationary assumption is not applicable in ARB. Further, the reconstructed streamflow shows statistically significant oscillations at interannual, interdecadal and multidecadal time scales and are teleconnected to climate patterns such as El Niño Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO) and Atlantic Multi-decadal Oscillation (AMO). A composite analysis shows that La Niña (El Niño), cold (warm) PDO, and cold (warm) AMO events are typically associated with increased (decreased) streamflow anomalies of ARB. The reconstructed streamflow data provides us the full range of streamflow variability and recurrence characteristics of extremes spanned over five centuries from which it is useful for us to evaluate and manage the current water systems of ARB more effectively and a better risk analysis of future droughts of ARB. |
format |
Article in Journal/Newspaper |
author |
Wu, Yenan Gan, Thian Yew She, Yuntong Xu, Chong-Yu Yan, Haibin |
spellingShingle |
Wu, Yenan Gan, Thian Yew She, Yuntong Xu, Chong-Yu Yan, Haibin Five centuries of reconstructed streamflow in Athabasca River Basin, Canada: Non-stationarity and teleconnection to climate patterns |
author_facet |
Wu, Yenan Gan, Thian Yew She, Yuntong Xu, Chong-Yu Yan, Haibin |
author_sort |
Wu, Yenan |
title |
Five centuries of reconstructed streamflow in Athabasca River Basin, Canada: Non-stationarity and teleconnection to climate patterns |
title_short |
Five centuries of reconstructed streamflow in Athabasca River Basin, Canada: Non-stationarity and teleconnection to climate patterns |
title_full |
Five centuries of reconstructed streamflow in Athabasca River Basin, Canada: Non-stationarity and teleconnection to climate patterns |
title_fullStr |
Five centuries of reconstructed streamflow in Athabasca River Basin, Canada: Non-stationarity and teleconnection to climate patterns |
title_full_unstemmed |
Five centuries of reconstructed streamflow in Athabasca River Basin, Canada: Non-stationarity and teleconnection to climate patterns |
title_sort |
five centuries of reconstructed streamflow in athabasca river basin, canada: non-stationarity and teleconnection to climate patterns |
publishDate |
2020 |
url |
http://hdl.handle.net/10852/82226 http://urn.nb.no/URN:NBN:no-85124 https://doi.org/10.1016/j.scitotenv.2020.141330 |
geographic |
Athabasca River Canada Pacific |
geographic_facet |
Athabasca River Canada Pacific |
genre |
Athabasca River |
genre_facet |
Athabasca River |
op_source |
0048-9697 |
op_relation |
http://urn.nb.no/URN:NBN:no-85124 Wu, Yenan Gan, Thian Yew She, Yuntong Xu, Chong-Yu Yan, Haibin . Five centuries of reconstructed streamflow in Athabasca River Basin, Canada: Non-stationarity and teleconnection to climate patterns. Science of the Total Environment. 2020, 746 http://hdl.handle.net/10852/82226 1863580 info:ofi/fmt:kev:mtx:ctx&ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Science of the Total Environment&rft.volume=746&rft.spage=&rft.date=2020 Science of the Total Environment 746 https://doi.org/10.1016/j.scitotenv.2020.141330 URN:NBN:no-85124 Fulltext https://www.duo.uio.no/bitstream/handle/10852/82226/2/WU%2BYenan_preprint.pdf |
op_doi |
https://doi.org/10.1016/j.scitotenv.2020.141330 |
container_title |
Science of The Total Environment |
container_volume |
746 |
container_start_page |
141330 |
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1766356608586088448 |