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Tree-ring reconstruction of Lhasa River streamflow reveals 472 years of hydrologic change on southern Tibetan Plateau

Author:
Chen, Feng, Shang, Huaming, Panyushkina, Irina P., Meko, David M., Yu, Shulong, Yuan, Yujiang, Chen, Fahu
Source:
Journal of hydrology 2019 v.572 pp. 169-178
ISSN:
0022-1694
Subject:
El Nino, Juniperus, climate, climate change, dendroclimatology, growth rings, monsoon season, planning, probability, risk reduction, rivers, stream flow, summer, water supply, watersheds, wavelet, China
Abstract:
The Lhasa River is the largest tributary of the Yarlung Zangbo River, provides up to 85% of the water supply for the city of Lhasa, and has a high ecologic and economic importance. Annual streamflow of the Lhasa River is reconstructed from Juniperus tibetica tree rings. The streamflow reconstruction developed for the southern Tibetan Plateau goes back to 1546 CE and has a R2 of 0.485. Spectral and wavelet analysis indicates the existence of decadal (34 and 16 years) and interannual (8.1, 5.7, 4.8, 3.8, 3.5, 3.2, 2.7, 2.3 and 2.1 years) cycles that may reflect climate forcings. Lhasa River streamflow is significantly correlated with precipitation over a vast part of the Yarlung Zangbo River basin, and represents streamflow of the upper Yarlung Zangbo River to a certain extent. Lhasa River variation is linked with large-scale climate circulation features, such as the El Niño-Southern Oscillation (ENSO) and Asian summer monsoon. Some years of abnormally high and low streamflow are related to ENSO events. Based on the reconstruction, the probability that annual streamflow does not exceed a target defined as the instrumental-period mean was lower (48% non-exceedance probability) than during the instrumental period. This study indicates that the instrumental record does not contain the full range of streamflow, especially the lowest streamflow events, and the reconstruction makes up for this shortcoming. Future water resource supply planning based on the instrumental record and streamflow reconstructions will be able to effectively reduce the risks posed by climate change.
Agid:
6327982