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

Research output: Contribution to conferenceAbstract


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.


External organisations
  • Tottori University
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Oceanography, Hydrology, Water Resources
Original languageEnglish
Number of pages1
Publication statusPublished - 2013 Dec 13
Publication categoryResearch
EventAmerican Geophysical Union, Fall Meeting 2013 - San Fransico, United States
Duration: 2013 Dec 92013 Dec 13


ConferenceAmerican Geophysical Union, Fall Meeting 2013
CountryUnited States
CitySan Fransico