Bangladesh is one of the world's most vulnerable regions to floods, which kill and displace a huge number of people each year. Floods also destroy homes and damage agricultural land, which is the main source of income for most people. An early warning system that provides adequate time for people to vacate can help communities to plan their activities to reduce the impact of floods, including harvesting early, moving livestock to safety, protecting fish ponds with nets, and stocking food and other essentials on high ground.
One of the main issue in flood forecasting in Bangladesh is estimating upstream transboundary river levels beyond the country's borders. The Institute of Water Modelling (IWM) in Bangladesh has developed a satellite-based flood forecasting system that does not rely on rain gauge data and provides long-range flood forecasts. This system uses JASON-2 satellite data to track the river levels of the Ganges and Brahmaputra rivers more than 600 miles upstream of Bangladesh.
The JASON-2 flood forecasting system uses a combination of satellite observations, river gauges, and newly developed hydraulic modelling techniques (HEC-RAS model) to provide 8-day flood forecasts of water levels for several water stations (improving on the previous 5-day flood forecast system). It is updated with new model runs and measurements daily. A radar altimeter on JASON-2 measures the precise distance between the satellite and the river surface at points where the satellite path passes on the stream. The new system is equipped with a user-friendly and robust platform for the real-time operation and flood forecasting. Web pages based on Google maps provide an improved graphical presentation of forecasting results for use in the preparation of flood warnings. A web page optimized for use on mobile phone devices completes the new system. We feel that the forecast modules we have developed are complete set of templates for a comprehensive flood forecasting system for Bangladesh.
The work flow in the system is as follows:
Work flow of the system
The JASON-2 flood forecasting system has the potential to warn thousands of residents in selected flood-prone regions. The project goal is to consistently reach rural communities in Bangladesh long-range flood forecasts (up to 8-days). Farmers and fishermen live in constant fear of losing homes and livelihoods and can easily lose a year's worth of income in a single flood. Flood victims have said that a flood warning system that sends out advance notice of floods would help them to reduce some of the worst impacts of rising water levels. The flood JASON-2 flood forecast system has the potential to save lives and property, thereby also improving quality of life.
The forecasting platform will require initial funding for network improvements, hardware acquisition, and specialist forecast platform software, and backup facilities, among other things. However, in the long run, the flood forecasting system can be made sustainable through active communal effort using public-private partnerships.
Taking it forward: Project Implementation
The project goal is to have the JASON-2 system officially adopted by the Flood Forecasting and Warning Centre (FFWC), which is the focal point for flood forecasting and warning in Bangladesh FFWC, and other stakeholder. Preliminary discussions with government and non-government organizations have been positive. The Bangladesh Water Development Board, FFWC, and Water Resources Planning Organization have agreed to incorporate the forecasts into their official flood forecast website in the future, after improvement of its performance. After viewing the web-GIS portal, representatives from the Bangladesh Agricultural Research Council, Department of Agricultural Extension, and others have agreed to establish institutional cooperation and start disseminating flood information to villagers. Key partners for project implementation are: the FFWC, Ministry of Disaster Management and Relief, Ministry of Agriculture, Bangladesh Meteorological Department, Department of Disaster Management, and Department of Agricultural Extension.
The forecasting system can be scaled up to include more virtual stations from more satellites and to cover influential rivers such as the Gorai, Dholeshwari, Arial Khan, Korotoa, and Teesta. IWM would also like to obtain finer resolution satellite data (both temporal and spatial) so that smaller rivers could be included in the system.