Japan Geoscience Union Meeting 2015

Presentation information

Oral

Symbol H (Human Geosciences) » H-SC Social Earth Sciences & Civil/Urban System Sciences

[H-SC24] Human environment and disaster risk

Sun. May 24, 2015 4:15 PM - 6:00 PM 101B (1F)

Convener:*Tatsuto Aoki(School of Regional Development Studies, Kanazawa University), Yasuhiro Suzuki(Nagoya University), Mamoru Koarai(Survey Department, College of Land, Infrastructure, Transport and Tourism), Toshihiko Sugai(Department of Natural Environmental Studies, Institute of Environmental Studies, Graduate School of Frontier Science, The University of Tokyo), Hiroshi Une(Geospacial Information Authority of Japan), Yoichi Nakamura(Department of Earth Sciences, Utsunomiya University), Jun Matsumoto(Deaprtment of Geography, Tokyo Metropolitan University), Shintaro Goto(Department of Environmental Systems Faculty of GEO-Environmental Science Rissho University), Keitarou Hara(Faculty of Informatics, Tokyo University of Information Sciences), Chair:Tatsuto Aoki(School of Regional Development Studies, Kanazawa University)

5:15 PM - 5:30 PM

[HSC24-05] Investigation of Inundation Prediction Method Linked with Real-Time Precipitation Information

*Motohiro HONMA1 (1.DPRI, Kyoto University)

Keywords:inundation prediction, weather warning, hazard map, evacuation judgement

1. Introduction
In order to guard oneself from an inundation damage, a citizen has to receive precipitation information and judge the need of evacuation by oneself. However, it is difficult for citizens to comprehend a flood risk from precipitation information because the precipitation information actually provided at the time of heavy rainfall doesn't link with a flood hazard map. In this study, I try to develop the inundation prediction map that a citizen can remind the inundation situation easily from the precipitation information and/or heavy rain warning by making the inundation prediction dataset linked with the precipitation information to be provided at the time of a heavy rain.

2. Method
The method of this study composes of 4 steps, (1) setting on the precipitation scenarios, (2) runoff / inundation analysis, (3) categorization of the weather information assumed to be issued at each precipitation scenario, (4) making of the inundation prediction map according to weather information and/or precipitation.
In setting on the precipitation scenarios, I set several rain duration (1, 2, 3, 6, 12, 24, 48 hours), and several precipitations on the basis of occurrence probability (1/30, 1/50, 1/100, 1/200). A conventional inundation prediction map often assumes the uniform distribution of precipitation. However, in the case of short-period heavy rain, it is the local rain. Therefore, I set several number of the rainfall area, and increased the rain areas sequentially, 5km*5km, 10km*10km, 15km*15km.
I use Rain-Runoff-Inundation (RRI) model developed in Public Works Research Institute as the method of the inundation prediction.
At each precipitation scenario, I categorize weather information assumed to be issued. The high risk precipitation scenarios is extracted in each subregion according to categorized weather information.
In this presentation, I report the result of case study for basin of Katsura-River.