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Section 1: Publication
Publication Type
Journal Article
Authorship
Slaughter, A. R., & Razavi, S.
Title
Paleo-hydrologic reconstruction of 400 years of past flows at a weekly time step for major rivers of Western Canada
Year
2020
Publication Outlet
Earth System Science Data, 12(1), 231-243
DOI
ISBN
ISSN
Citation
Slaughter, A. R., & Razavi, S. (2020). Paleo-hydrologic reconstruction of 400 years of past flows at a weekly time step for major rivers of Western Canada. Earth System Science Data, 12(1), 231-243.
https://doi.org/10.5194/essd-12-231-2020
Abstract
The assumption of stationarity in water resources no longer holds, particularly within the context of future climate change. Plausible scenarios of flows that fluctuate outside the envelope of variability of the gauging data are required to assess the robustness of water resource systems to future conditions. This study presents a novel method of generating weekly time step flows based on tree-ring chronology data. Specifically, this method addresses two long-standing challenges with paleo-reconstruction: (i) the typically limited predictive power of tree-ring data at the annual and sub-annual scale and (ii) the inflated short-term persistence in tree-ring time series and improper use of pre-whitening. Unlike the conventional approach, this method establishes relationships between tree-ring chronologies and naturalized flow at a biennial scale to preserve persistence properties and variability of hydrological time series. Biennial flow reconstructions are further disaggregated to weekly flow reconstructions, according to the weekly flow distribution of reference 2-year instrumental periods, identified as periods with broadly similar tree-ring properties to those of every 2-year paleo-period. The Saskatchewan River basin (SaskRB) in Western Canada is selected as a study area, and weekly flows in its four major tributaries are extended back to the year 1600. The study shows that the reconstructed flows properly preserve the statistical properties of the reference flows, particularly in terms of short- to long-term persistence and the structure of variability across timescales. An ensemble approach is presented to represent the uncertainty inherent in the statistical relationships and disaggregation method. The ensemble of reconstructed weekly flows are publicly available for download from
https://doi.org/10.20383/101.0139 (Slaughter and Razavi, 2019).
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