Dataset for the paper entitled ''Reconstructing past hydrology of eastern Canadian boreal catchments using clastic varved sediments and hydro-climatic modelling: 160 years of fluvial inflows''
收藏DataONE2021-03-23 更新2024-06-08 收录
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资源简介:
Analysis of short sediment cores collected in Grand Lake, Labrador, revealed that this lake is an excellent candidate for the preservation of laminated sediments record. The great depth of Grand Lake, the availability of fine sediments along its tributaries, and its important seasonal river inflow have favoured the formation of a 160 years-long clastic varved sequence. Each varve represents one hydrological year. Varve formation is mainly related to spring discharge conditions with contributions from summer and autumn rainfall events. The statistically significant relation between varve parameters and the Naskaupi River discharge observations provided the opportunity to develop local hydrological reconstructions beyond the instrumental period. The combined detrital layer thickness and the particle size (99th percentile) series extracted from each varve yield the strongest correlations with instrumental data (r = 0.68 and 0.75) and have been used to reconstruct Naskaupi River mean and maximum annual discharges, respectively, over the 1856-2016 period. The reconstructed Q-mean series suggest that high Q-mean years occurred during the 1920-1960 period and a slight decrease in Q-mean takes place during the second half of the 20th century. Independent reconstructions based on rainfall-runoff modelling of the watershed from historical reanalysis of global geopotential height fields display a significant correlation with the reconstructed Naskaupi River discharge based on varve physical parameters. The Grand Lake varved sequence contains a regional hydrological signal, as suggested by the statistically significant relation between the combined detrital layer thickness series and the observed Labrador region Q-mean series extracted from five watersheds of different sizes.
创建时间:
2023-12-28



