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Coupling ensemble weather predictions based on TIGGE database with Grid-Xinanjiang model for flood forecast

Bao, H.-J., Zhao, L.-N., He, Y., Li, Z.-J., Wetterhall, F., Cloke, H. L. ORCID: https://orcid.org/0000-0002-1472-868X, Pappenberger, F. and Manful, D. (2011) Coupling ensemble weather predictions based on TIGGE database with Grid-Xinanjiang model for flood forecast. Advances in Geosciences (ADGEO), 29. pp. 61-67. ISSN 1680-7340

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To link to this item DOI: 10.5194/adgeo-29-61-2011

Abstract/Summary

The incorporation of numerical weather predictions (NWP) into a flood forecasting system can increase forecast lead times from a few hours to a few days. A single NWP forecast from a single forecast centre, however, is insufficient as it involves considerable non-predictable uncertainties and lead to a high number of false alarms. The availability of global ensemble numerical weather prediction systems through the THORPEX Interactive Grand Global Ensemble' (TIGGE) offers a new opportunity for flood forecast. The Grid-Xinanjiang distributed hydrological model, which is based on the Xinanjiang model theory and the topographical information of each grid cell extracted from the Digital Elevation Model (DEM), is coupled with ensemble weather predictions based on the TIGGE database (CMC, CMA, ECWMF, UKMO, NCEP) for flood forecast. This paper presents a case study using the coupled flood forecasting model on the Xixian catchment (a drainage area of 8826 km2) located in Henan province, China. A probabilistic discharge is provided as the end product of flood forecast. Results show that the association of the Grid-Xinanjiang model and the TIGGE database gives a promising tool for an early warning of flood events several days ahead.

Item Type:Article
Refereed:Yes
Divisions:Interdisciplinary Research Centres (IDRCs) > Walker Institute
Science > School of Archaeology, Geography and Environmental Science > Earth Systems Science
Science > School of Archaeology, Geography and Environmental Science > Department of Geography and Environmental Science
ID Code:35035
Publisher:Copernicus Publications

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