Document Type

Presentation

Publication Date

8-1-2014

Abstract

Currently, basin-wide flood monitoring and warning systems are being implemented sequentially in river basins of the Philippines, which suffer from severe floods. The Cagayan River basin is among them draining the area of 27,280km2, where five rainfall and water level gauges are installed for the purpose of flood monitoring and warning. Despite the installed monitoring system, an operational flood forecasting model based on physical processes has not been performed for this basin. IFAS, a distributed hydrological model developed by ICHARM, was applied to the Cagayan River basin as a flood forecasting model. One of its notable functions is the capability of using both ground-gauge data and global satellite information, such as topography, land use and rainfall, in the model. In developing countries, hydrological ground observation still remains insufficient. To utilize global satellite information as supplementary information makes it much easier to forecast flood discharge in an insufficiently-gauged river basin. On the other hand, little has been addressed about accuracy validation of global satellite information as input data of the flood forecasting model. Therefore, simulation results utilizing satellite-based rainfall were compared with those with ground rainfall. GSMaP provided by the Japan Aerospace Exploration Agency (JAXA) was applied to the flood forecasting model as a rainfall input. The comparison shows ground rainfall excels at accuracy of quantity, whereas GSMap excels at spatial distribution. In accordance with this result, GSMaP calibrated by the ground rainfall was applied to the IFAS model in order to increase reproducibility of flood discharge. As a result, the study found that simulation with calibrated GSMaP can reproduce river discharge with high accuracy, suggesting that satellite information is applicable to and effective in flood forecasting and warning activities in the Philippines.

Comments

Session R46, Remote Sensing and LiDAR Data: Products relevant to Hydrology

 
 

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