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Acta Meteorologica Sinica

, Volume 26, Issue 1, pp 103–111 | Cite as

Early flood warning for Linyi watershed by the GRAPES/XXT model using TIGGE data

  • Jingwen Xu (徐精文)
  • Wanchang Zhang (张万昌)Email author
  • Ziyan Zheng (郑子彦)
  • Meiyan Jiao (娇梅燕)
  • Jing Chen (陈 静)
Article

Abstract

Early and effective flood warning is essential for reducing loss of life and economic damage. Three global ensemble weather prediction systems of the China Meteorological Administration (CMA), the European Centre for Medium-Range Weather Forecasts (ECMWF), and the US National Centers for Environmental Prediction (NCEP) in THORPEX (The Observing System Research and Predictability Experiment) Interactive Grand Global Ensemble (TIGGE) archive are used in this research to drive the Global/Regional Assimilation and PrEdiction System (GRAPES) to produce 6-h lead time forecasts. The output (precipitation, air temperature, humidity, and pressure) in turn drives a hydrological model XXT (the first X stands for Xinanjiang, the second X stands for hybrid, and T stands for TOPMODEL), the hybrid model that combines the TOPMODEL (a topography based hydrological model) and the Xinanjiang model, for a case study of a flood event that lasted from 18 to 20 July 2007 in the Linyi watershed. The results show that rainfall forecasts by GRAPES using TIGGE data from the three forecast centers all underestimate heavy rainfall rates; the rainfall forecast by GRAPES using the data from the NCEP is the closest to the observation while that from the CMA performs the worst. Moreover, the ensemble is not better than individual members for rainfall forecasts. In contrast to corresponding rainfall forecasts, runoff forecasts are much better for all three forecast centers, especially for the NCEP. The results suggest that early flood warning by the GRAPES/XXT model based on TIGGE data is feasible and this provides a new approach to raise preparedness and thus to reduce the socio-economic impact of floods.

Key words

TIGGE GRAPES flood warning XXT rainfall-runoff process 

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Copyright information

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

Authors and Affiliations

  • Jingwen Xu (徐精文)
    • 1
    • 3
  • Wanchang Zhang (张万昌)
    • 2
    Email author
  • Ziyan Zheng (郑子彦)
    • 3
  • Meiyan Jiao (娇梅燕)
    • 4
  • Jing Chen (陈 静)
    • 5
  1. 1.College of Resources and EnvironmentSichuan Agricultural UniversityYaanChina
  2. 2.Center for Earth Observation and Digital EarthChinese Academy of SciencesBeijingChina
  3. 3.Institute of Atmospheric PhysicsChinese Academy of SciencesBeijingChina
  4. 4.China Meteorological AdministrationBeijingChina
  5. 5.National Meteorological CenterCMABeijingChina

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