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Prediction of summer precipitation in the source region of the Yellow River using sea surface temperature

Yuan, Feifei LU ; Berndtsson, Ronny LU ; Zhang, Linus Tielin LU and Yasuda, Hiroshi (2013) American Geophysical Union, Fall Meeting 2013
Abstract
The source region of the Yellow River contributes about 35% of the total water yield in the Yellow River basin playing an important role in meeting downstream water resources requirements. Thus, it is important to accurately predict the summer precipitation to get better estimation of streamflow for the Yellow River. In this study, the close links between summer precipitation in the source region of the Yellow River and sea surface temperature (SST) in the Pacific Ocean were established for further prediction. Results show that there is a strong lagged significant correlation between SST and summer precipitation. An artificial neural network (ANN) model was used to predict summer precipitation using this correlation with high accuracy.... (More)
The source region of the Yellow River contributes about 35% of the total water yield in the Yellow River basin playing an important role in meeting downstream water resources requirements. Thus, it is important to accurately predict the summer precipitation to get better estimation of streamflow for the Yellow River. In this study, the close links between summer precipitation in the source region of the Yellow River and sea surface temperature (SST) in the Pacific Ocean were established for further prediction. Results show that there is a strong lagged significant correlation between SST and summer precipitation. An artificial neural network (ANN) model was used to predict summer precipitation using this correlation with high accuracy. This indicates that major annual precipitation (during summer season) can be predicted using the suggested approach,and it is an essential part of the development of optimal reservoir planning and operation policies for power generation, water supply, and flood control for the mid and down-stream areas of the Yellow River. (Less)
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author
; ; and
organization
publishing date
type
Contribution to conference
publication status
published
subject
pages
1 pages
conference name
American Geophysical Union, Fall Meeting 2013
conference location
San Fransico, United States
conference dates
2013-12-09 - 2013-12-13
language
English
LU publication?
yes
id
34408799-a81c-46ba-a27c-1de400889b0e
date added to LUP
2019-02-10 01:04:53
date last changed
2019-02-19 08:45:30
@misc{34408799-a81c-46ba-a27c-1de400889b0e,
  abstract     = {The source region of the Yellow River contributes about 35% of the total water yield in the Yellow River basin playing an important role in meeting downstream water resources requirements. Thus, it is important to accurately predict the summer precipitation to get better estimation of streamflow for the Yellow River. In this study, the close links between summer precipitation in the source region of the Yellow River and sea surface temperature (SST) in the Pacific Ocean were established for further prediction. Results show that there is a strong lagged significant correlation between SST and summer precipitation. An artificial neural network (ANN) model was used to predict summer precipitation using this correlation with high accuracy. This indicates that major annual precipitation (during summer season) can be predicted using the suggested approach,and it is an essential part of the development of optimal reservoir planning and operation policies for power generation, water supply, and flood control for the mid and down-stream areas of the Yellow River.},
  author       = {Yuan, Feifei and Berndtsson, Ronny and Zhang, Linus Tielin and Yasuda, Hiroshi},
  language     = {eng},
  month        = {12},
  title        = {Prediction of summer precipitation in the source region of the Yellow River using sea surface temperature},
  year         = {2013},
}