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Spring flood reconstruction from continuous and discrete tree ring series
Author(s) -
Boucher Étienne,
Ouarda Taha B. M. J.,
Bégin Yves,
Nicault Antoine
Publication year - 2011
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1029/2010wr010131
Subject(s) - flood myth , dendrochronology , streamflow , hydropower , jackknife resampling , discharge , hydrology (agriculture) , environmental science , robustness (evolution) , climatology , geology , mathematics , statistics , geography , drainage basin , cartography , geotechnical engineering , archaeology , engineering , chemistry , biochemistry , estimator , electrical engineering , gene
This study proposes a method to reconstruct past spring flood discharge from continuous and discrete tree ring chronologies, since both have their respective strengths and weaknesses in northern environments. Ring width or density series provide uninterrupted records that are indirectly linked to regional discharge through a concomitant effect of climate on tree growth and streamflow. Conversely, discrete event chronologies constitute conspicuous records of past high water levels since they are constructed from trees that are directly damaged by the flood. However, the uncertainty of discrete series increases toward the past, and their relationships with spring discharge are often nonlinear. To take advantage of these two sources of information, we introduce a new transfer model technique on the basis of generalized additive model (GAM) theory. The incorporation of discrete predictors and the evaluation of the robustness of the nonlinear relationships are assessed using a jackknife procedure. We exemplify our approach in a reconstruction of May water supplies to the Caniapiscau hydroelectric reservoir in northern Quebec, Canada. We used earlywood density measurements as continuous variables and ice‐scar dates around Lake Montausier in the James Bay area as a discrete variable. Strong calibration (0.57 < 0.61 < 0.75) and validation (0.27 < 0.44 < 0.58) R 2 statistics were obtained, thus highlighting the usefulness of the model. Our reconstruction suggests that, since ∼1965, spring floods have become more intense and variable in comparison with the last 150 years. We argue that a similar procedure can be used in each case where discrete and continuous tree ring proxies are used together to reconstruct past spring floods.