Flood Prediction System Using the Global Satellite Map of Precipitation (GSMaP) 6.5: By 2030, implement integrated water resources management at all levels, including through transboundary cooperation as appropriate

6.5.1: Degree of integrated water resources management implementation (0-100)

Many countries in the Asia-Pacific region have suffered from floods caused by typhoons and heavy rains. The severity and frequency of floods are expected to increase with intensification of the hydrological cycle due to global warming.

As one of the most powerful nonstructural measures against flooding, monitoring and warning systems have been implemented in the region, which combine satellite-based global precipitation data such as the Global Satellite Mapping of Precipitation (GSMaP) dataset with ground observations (rain gauges, water-level gauges) thereby improving prediction accuracy of extreme weather events; and strengthening capacities of both governments and communities for pre-and post-disaster actions.

GSMaP provides estimates of precipitation within   river basin areas, which often extend beyond national boundaries. Flood predictions are made using calibrated GSMaP data and river run-off models. Flood warnings are transmitted by mobile phone.

Earth Observation Data Use

  • GSMaP data
  • Rain-gauge data for correction and validation


GSMaP is an hourly global rainfall map provided in near-real-time on a 0.1 degree (about 10 kilometer) grid over a global area (between 60N and 60S latitudes). GSMaP is produced by integrating microwave radiometer data from low Earth orbiting satellites and thermal infrared data from geostationary satellites. Methodologies and systems to calibrate and validate GSMaP data with ground rainfall data have been developed in pilot areas of each country.

The calibrated GSMaP data is used as input data for flood models in the target river basin for flood forecasting. These models include the Integrated Flood Analysis System developed by the International Centre for Water Hazard and Risk Management (ICHARM), and the Water and Energy Budget-Based Distributed Hydrological Model, developed by the University of Tokyo. Target river basins are Jamuna river basin in Bangladesh, Cagayan river basin in  the Philippines, Red-Thai river basin in Vietnam and Indus river basin in Pakistan.

For flood models, satellite-based topographical information (digital elevation model [DEM] or digital surface model [DSM]) obtained from the Advanced Land Observing Satellite (ALOS) is used to make an inundation map in the pilot area as an alternate source of geographic data to those obtained from spot surveys.

Global Satellite Map of Precipitation (GSMaP) Available at: http://sharaku.eorc.jaxa.jp/GSMaP/index.htm

Key Issues and Results

The main outcome is the mitigation of flood damage risk through improvements in flood prediction and through increased early warnings broadcast by mobile phone. The frequent updates to the data and warning systems facilitate longer times for communities to evacuate.

The accuracy of the satellite-based precipitation data is fundamental to the flood prediction reliability and the rain gauge data is absolutely fundamental to the calibration and validation of the satellite data.

Analysis, Status, and Outlook

Flood prediction systems using GSMaP have been implemented in Bangladesh,  the Philippines, Vietnam, and in Pakistan in collaboration with the Asian Development Bank (ADB) and UNESCO.

The goal of these pilots is to increase the number of countries which provide flood prediction systems using GSMaP as an input.

Partners, Contacts, More Information


Dr. Riko Oki, oki.riko@jaxa.jp

Dr. Takuji Kubota, kubota.takuji@jaxa.jp

Mr. Takanori Miyoshi, miyoshi.takanori@jaxa.jp

Mr. Chu Ishida, ishida.chu@jaxa.jp


ADB, UNESCO, ICHARM, University of Tokyo