At present, Bangladesh has a flood forecasting lead time of only 3 days or so. There is demand for a forecasting lead time of a month to a season. The primary objectives of this paper are to study the variability and predictability of seasonal flooding in Bangladesh, as revealed by large-scale predictors of the climate across the watersheds. To explore the source of predictability, accessible Bangladesh hydrological indicators are related to large-scale oceanic variability and to large-scale atmospheric circulation patterns predicted by general circulation models (GCMs).Correlation analyses between the flood-affected area (FAA) for July-September and tropical sea-surface temperature (SST) indicate connections to tropical Pacific and Indian Ocean SSTs, at a short lead time of a month or so. These are related to El Nino-southern oscillation (ENSO). Correlations between the SSTs of the preceding October-December and the July-September FAA are weaker but notable. Forecasts of the FAA using the leading principal components (PCs) of SST were made, which provided good skill with a lead time of a month or so. The streamflows and rainfall observed in Bangladesh have been added to these prediction models. Finally, the SST PCs were replaced with PCs of GCM prediction fields (precipitation). The prediction models at short lead time that were constructed for FAA were of generally similar levels of skill to that for SST. This is encouraging, as it suggests that linkages with SST can be successfully recovered in a physical model of the climate system in Bangladesh.This study concludes that seasonal flood prediction in Bangladesh is possible from the unusually warm or cold SST in parts of the tropics. This predictability can be enhanced with the information achievable from monitoring the downstream streamflows (which are generated mainly from upstream rainfall conditions) in advance of the flooding season. Finally, this study recommends formalizing a regional cooperation among the countries in the principal co-basin areas of the Gan.aes-Brahmaputra-Meghna to achieve this goal. Copyright (c) 2006 John Wiley & Sons, Ltd.
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