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Acta Meteorologica Sinica

, Volume 26, Issue 1, pp 62–71 | Cite as

Probabilistic flood prediction in the upper Huaihe catchment using TIGGE data

  • Linna Zhao (赵琳娜)
  • Dan Qi (齐 丹)Email author
  • Fuyou Tian (田付友)
  • Hao Wu (吴 昊)
  • Jingyue Di (狄靖月)
  • Zhi Wang (王 志)
  • Aihua Li (李爱华)
Article

Abstract

Based on the precipitation and temperature data obtained from THORPEX (The Observing System Research and Predictability Experiment) Interactive Grand Global Ensemble (TIGGE)-China Meteorological Administration (CMA) archiving center and the raingauge data, the three-layer variable infiltration capacity (VIC-3L) land surface model was employed to carry out probabilistic hydrological forecast experiments over the upper Huaihe River catchment from 20 July to 3 August 2008. The results show that the performance of the ensemble probabilistic prediction from each ensemble prediction system (EPS) is better than that of the deterministic prediction. Especially, the 72-h prediction has been improved obviously. The ensemble spread goes widely with increasing lead time and more observed discharge is bracketed in the 5th-99th quantile. The accuracy of river discharge prediction driven by the European Centre (EC)-EPS is higher than that driven by the CMA-EPS and the US National Centers for Environmental Prediction (NCEP)-EPS, and the grand-ensemble prediction is the best for hydrological prediction using the VIC model. With regard to Wangjiaba station, all predictions made with a single EPS are close to the observation between the 25th and 75th quantile. The onset of the flood ascending and the river discharge thresholds are predicted well, and so is the second rising limb. Nevertheless, the flood recession is not well predicted.

Key words

probabilistic hydrological prediction TIGGE variable infiltration capacity (VIC) model Huaihe River 

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Copyright information

© The Chinese Meteorological Society and Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Linna Zhao (赵琳娜)
    • 1
    • 2
  • Dan Qi (齐 丹)
    • 2
    Email author
  • Fuyou Tian (田付友)
    • 2
  • Hao Wu (吴 昊)
    • 1
    • 2
  • Jingyue Di (狄靖月)
    • 1
    • 2
  • Zhi Wang (王 志)
    • 1
    • 2
  • Aihua Li (李爱华)
    • 3
  1. 1.Public Meteorological Service CenterChina Meteorological AdministrationBeijingChina
  2. 2.National Meteorological CenterChina Meteorological AdministrationBeijingChina
  3. 3.Anhui Weather Modification OfficeAnhui Provincial Meteorological ServiceHefeiChina

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