Details:

Journal Title:
Journal of Hydrology
Personal Author:
Wang, Wenzhuo ; Dong, Zengchuan ; Palat Rao, Mukund ; Lall, Upmanu ; Jia, Benyou
Wang, Wenzhuo ; Dong, Zengchuan ; Palat Rao, Mukund ; Lall, Upmanu ; Jia, Benyou Less -
NOAA Program & Office:
NWS (National Weather Service)
Description:
The headwater catchment of the Yellow River Basin (HCYRB) controls 35% of the streamflow of the Yellow River (YR) which faces increasing water shortages. To better understand streamflow variability in the region we require a better understanding of high and low flow characteristics. This study presents a new annual (Nov-Oct) streamflow reconstruction at the Tangnaihai station in the HCYRB for the last two millennia (159–2016 C.E.) using 12 tree-ring chronologies. The nested principal component regression model combined with the stepwise best subset selection method was proposed to improve the temporal length and model skill of reconstruction. The stepwise best subset selection method was presented to select the best principal components subset, instead of a confidence test, based on k-fold cross-validation error and Akaike’s information criteria (AIC). The model assessment results verify that the proposed model exhibits strong reconstruction skills. Besides, the magnitude and duration of both high and low flow periods were analyzed. The results show that (1) the significant high-flow periods are the early 3rd century, circa 300 C.E., early 13th century, 16th century and circa 1900 C.E., while the low-flow periods are the late 5th century and late 15th century; (2) the durations and magnitudes of low-flow periods are longer and larger than high-flow periods and the severities of high-flow periods are greater than low-flow periods. The reconstruction also suggests that a warm climate is more likely accompanied by a high-flow period and low-flow periods are more likely to occur in cold periods associated with the Asian Summer Monsoon and solar activity.
Keywords:
[+]
General Medicine
Source:
Journal of Hydrology, 606, 127387
DOI:
https://doi.org/10.1016/j.jhydrol.2021.127387
ISSN:
0022-1694
Format:
PDF
Publisher:
Elsevier BV
Document Type:
Journal Article
Funding:
Grant no. NA18NWS4620043B
Rights Information:
Accepted Manuscript
Compliance:
Library
Main Document Checksum:
[+]
urn:sha256:a9725d2f2df6f20fc4100f9d122edf156c23db9ca6cf7dcbd65ef88c8ba226f6
Download URL:
https://repository.library.noaa.gov/view/noaa/57813/noaa_57813_DS1.pdf
File Type:

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