Consideration of estimation method of precipitation data for numerical real-time flood forecasting
Extremely dense hydro-meteorological monitoring system is being operated in the Mae Wang basin in northern Thailand by GEOSS. This study aimed at establishing a flood forecasting system with this dataset. It was turned out to be that the parameterization of soil water conditions (SWC) was essential to simulate discharge in tropical river basins. Then to apply this system to other basins, including un-gauged/poor-gauged basins, two alternatives to estimate precipitation data in this basin were considered. One is the use of alternative precipitation datasets, i.e. GSMaP. This dataset was turned out to have a potential for utilizing a basinscale flood forecasting. The other is the reduction of the precipitation observation density. This indicated that the minimum number of rain gauges was specified to 3.
real-time flood forecasting GEOSS SWC parameterization GSMaP observation density
Kenichiro NAKANISHI Kenji TANAKA Daisuke KOMORI Taikan OKI Toshiharu KOJIRI
The University of Tokyo,Komaba,Meguro-ku 153-8505,Japan Kyoto University,#D-1406 Gokasho 611-0011,Japan
国际会议
The Four Conference of Asia Pacific Association of Hydrology and Water Resources(亚太地区水文水资源协会第4届科学大会)
北京
英文
136-142
2008-11-03（万方平台首次上网日期，不代表论文的发表时间）