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Assessment on annual precipitation change in the headwater source of the middle route of China’s South to North Water Diversion Project

  • Yiming Hu
  • Zhongmin LiangEmail author
  • Lihua Xiong
  • Long Sun
  • Kai Wang
  • Jing Yang
  • Jun Wang
  • Binquan Li
Original Paper
  • 30 Downloads

Abstract

The Danjiangkou (DJK) reservoir is the source of the middle route of China’s South to North Water Diversion Project (MRCSNWDP). The precipitation in DJK basin has been observed to be a decreasing trend, which inevitably has a negative impact on the water resources management and planning in the MRCSNWDP. In this paper, the four varying-parameter probability distribution function models called as GEV-1, GEV-2, PE3-1, and PE3-2 were firstly proposed to assess the DJK annual precipitation change at the level of quantile, then the Bayesian method was used to quantify the uncertainty of such assessment results, finally the equivalent reliability (ER) method was applied to calculate the return level of DJK annual precipitation corresponding to the different return periods and different length of planning periods. Results indicated that quantiles of DJK annual precipitation with the given non-exceedance probabilities of 0.01, 0.02, 0.05, and 0.1 experienced an obvious decreasing trend in the observed period, and in the future, the quantile of annual precipitation was expected to become less. The ER-based estimation of the return level of DJK annual precipitation corresponding to the return period of 10, 20, 50, and 100 years over the next few decades showed that such return level with a given return period would decrease but its uncertainty would increase with the length of planning period increasing. These could bring great challenges to the water resource management and planning of the MRCSNWDP.

Notes

Funding information

This study was supported by the National Natural Science Foundation of China (51709073), the Natural Science Foundation of Jiangsu Province (BK20170878), China Postdoctoral Science Foundation (2017M620188, 2018T110437), and the Open Research Fund Program of State Key Laboratory of Water Resources and Hydropower Engineering Science (2016SWG02).

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Copyright information

© Springer-Verlag GmbH Austria, part of Springer Nature 2019

Authors and Affiliations

  • Yiming Hu
    • 1
    • 2
  • Zhongmin Liang
    • 2
    Email author
  • Lihua Xiong
    • 1
  • Long Sun
    • 2
    • 3
  • Kai Wang
    • 4
  • Jing Yang
    • 2
  • Jun Wang
    • 2
  • Binquan Li
    • 2
  1. 1.State Key Laboratory of Water Resources and Hydropower Engineering ScienceWuhan UniversityWuhanChina
  2. 2.College of Hydrology and Water ResourcesHohai UniversityNanjingChina
  3. 3.Information Center (Hydrology Monitor and Forecast Center)Ministry of Water ResourcesBeijingChina
  4. 4.Huaihe River CommissionBengbuChina

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