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JDR Vol.4 No.1 pp. 12-23
doi: 10.20965/jdr.2009.p0012
(2009)

Review:

Assessing Climate Change Impact on Water Resources in the Tone River Basin, Japan, Using Super-High-Resolution Atmospheric Model Output

Kaoru Takara*, Sunmin Kim*, Yasuto Tachikawa**,
and Eiichi Nakakita*

*Disaster Prevention Research Institute (DPRI), Kyoto University
Gokasho, Uji, Kyoto 611-0011, Japan

**Hydrology and Water Resources Engineering Laboratory, Department of Urban and Environmental Engineering, Kyoto University, C1, Nishikyo-ku, Kyoto 615-8540, Japan

Received:
October 6, 2008
Accepted:
January 5, 2009
Published:
February 1, 2009
Keywords:
climate change, AGCM20, SPI, water resources, Tone River Basin
Abstract

We examined the potential impact of climate change on Tokyo metropolitan water resources in the Tone River basin using output from a super-high-resolution global atmospheric general circulation model, AGCM20, having 20-km spatial resolution and 1-hour temporal resolution. AGCM20 is run on the Earth Simulator and being developed under the Japanese government’s Kakushin21 program. AGCM20 has an advantage in simulating orographic rainfall and frontal rain bands, so we used its output to analyze Tone River basin water resources. The basin covers 16,840 km2 and the main channel is 322 km long from its source to the Pacific Ocean. AGCM20 outputs hourly precipitation and daily variables such as snowfall, rainfall, snowmelt, evaporation, and transpiration for a present period, 1979-1998, and a projected period, 2075-2094. A comparison of these two periods showed that snow-related variables will decrease and all others will increase. Based on a comparison of ordered daily precipitation curves (ODPC) between AGCM20 and the Automated Meteorological Data Acquisition System (AMeDAS), a high-resolution Japan Meteorological Agency (JMA) surface observation network, we corrected AGCM20 precipitation data bias, and calculated the standardized precipitation index (SPI) drought indicator. The SPI for less than 6 months does not show noticeable variations under climate change, but the yearly SPI predicts more frequent dry conditions, indicating increased future vulnerability to subtle droughts.

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