A 1-10 day ensemble forecasting scheme for the major river basins of Bangladesh: Forecasting severe floods of 2003-2007

This paper describes a fully automated scheme that has provided calibrated 1–10-day ensemble river discharge forecasts and predictions of severe flooding of the Brahmaputra and Ganges Rivers as they flow into Bangladesh; it has been operational since 2003. The Bangladesh forecasting problem poses unique challenges because of the frequent life-threatening flooding of the country and because of the absence of upstream flow data from India means that the Ganges and Brahmaputra basins must be treated as if they are ungauged. The meteorological–hydrological forecast model is a hydrologic multimodel initialized by NASA and NOAA precipitation products, whose states and fluxes are forecasted forward using calibrated European Centre for Medium-Range Weather Forecasts ensemble prediction system products, and conditionally postprocessed to produce calibrated probabilistic forecasts of river discharge at the entrance points of the Ganges and Brahmaputra into Bangladesh. Forecasts with 1–10-day horizons are presented for the summers of 2003–07. Objective verification shows that the forecast system significantly outperforms both a climatological and persistence forecast at all lead times. All severe flooding events were operationally forecast with significant probability at the 10-day horizon, including the extensive flooding of the Brahmaputra in 2004 and 2007, with the latter providing advanced lead-time warnings for the evacuation of vulnerable residents.

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Author Hopson, Thomas
Webster, Peter
Publisher UCAR/NCAR - Library
Publication Date 2010-06-01T00:00:00
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Topic Category geoscientificInformation
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Metadata Date 2023-08-18T18:59:05.676388
Metadata Record Identifier edu.ucar.opensky::articles:17262
Metadata Language eng; USA
Suggested Citation Hopson, Thomas, Webster, Peter. (2010). A 1-10 day ensemble forecasting scheme for the major river basins of Bangladesh: Forecasting severe floods of 2003-2007. UCAR/NCAR - Library. http://n2t.net/ark:/85065/d76t0nx7. Accessed 15 February 2025.

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