JDR Vol.8 No.3 pp. 397-405
doi: 10.20965/jdr.2013.p0397


Impacts of Mid-Rainy Season Rainfall on Runoff into the Chao Phraya River, Thailand

Shunji Kotsuki* and Kenji Tanaka**

*Graduate School of Engineering, Kyoto University, Nishikyo Ward, Kyoto 615-8530, Japan

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

April 23, 2013
May 20, 2013
June 1, 2013
Chao Phraya River, flood, precipitation, soil water content, hydrological land surface model
In Chao Phraya River basin, the runoff at the middle basin (Nakhon Sawan station: C.2 point) is important for the prevention of lower basin floods. Through analyzing 1980 to 2011 runoff and rain gauge data and performing numerical calculations using a hydrological land surface model, this study will describe a condition that causes massive floods at the C.2 point. The main conclusions are the following: (1) In 2011, precipitation exceeding the average by about 40% caused naturalized runoff +125% (+29 billion m3) that in an average year. The massive 2011 flood would have been difficult to prevent even if the operation of the Bhumibol Dam and Sirikit Dam had been appropriate. (2) In 1980, 1995, and 2006, precipitation exceeding the average by about 10% caused naturalized runoff exceeding that of the average year by 50 to 75%. The runoff rate in the Chao Phraya River basin is about 20%, and characteristically a minor increase in precipitation results in a considerable amount of runoff. (3) There are natural flood years, which have higher than average precipitation that causes massive floods, and there are non-natural flood years, which have high precipitation but nomassive floods. In natural flood years, the precipitation in June, July, and August is higher than that in the average years, and the total water storage capacity is brought close to saturation in September. Due to this, in addition to base runoff, surface runoff increases. (4) The coefficient of the determination of observed runoff from August to October is 0.6481 for rainfall from June to August and 0.5276 for rainfall from August to October. Heavy rainfall in June, July and August has the effect of bringing the soil close to saturation, which is a necessary condition for massive flooding. Massive flooding results if this necessary condition is met and there is heavy rainfall in September and October. This finding is also supported by a high coefficient of determination of 0.7260 between rainfall in May, June, July, August, September, and October and naturalized runoff in August, September, and October.
Cite this article as:
S. Kotsuki and K. Tanaka, “Impacts of Mid-Rainy Season Rainfall on Runoff into the Chao Phraya River, Thailand,” J. Disaster Res., Vol.8 No.3, pp. 397-405, 2013.
Data files:
  1. [1] The World Bank, “Thai Flood 2011: Rapid assessment for resilient recoverly and reconstruction planning,” 2012, accessed April 10, 2013]
  2. [2] S. Kure and T. Tebakari, “Hydrological impact of regional climate change in the Chao Phraya River Basin, Thailand,” Hydrological Research Letters, Vol.6, pp. 53-58, 2012.
  3. [3] T. Tebakari, J. Yoshitani, and C. Suvanpimol, “Time-space trend analysis in pan evaporation over Kingdom of Thailand,” J. of Hydrologic Engineering, Vol.10, pp. 205-215, 2005.
  4. [4] T. Homdee, K. Pongput, and S. Kanae, “Impacts of land cover changes on hydrologic responses: a case study of Chi River Basin, Thailand,” Annual J. of Hydraulic Engineering, Vol.55, pp. 31-36, 2011.
  5. [5] P. B. Hunukumbura, and Y. Tachikawa, “River discharge projection under climate change in the Chao Phraya River Basin,” J. of the Meteorological Society of Japan, Vol.90A, pp. 137-150, 2012.
  6. [6] D. Komori et al., “Characteristics of the 2011 Chao Phraya River flood in Central Thailand,” Hydrological Research Letters, Vol.6, pp. 41-46, 2012.
  7. [7] S. Kotsuki and K. Tanaka, “Comparative study of precipitation products through hydrological land surface analysis in Southeast Asian basins,” Hydrological Research Letters (submitted).
  8. [8] GAME-T2 Data Center, 2005, [accessed Mar. 20, 2013]
  9. [9] A. Yatagai, K. Kamiguchi, O. Arakawa, A. Hamada, N. Yasutomi, and A. Kitoh, “APHRODITE: Constructing a Long-term Daily Gridded Precipitation Dataset for Asia based on a Dense Network of Rain Gauges,” Bulletin of American Meteorological Society, BAMS, pp. 1401-1415, 2012.
  10. [10] B. Rudolf, B. Andreas, S. Udo, M. C. Anja, and Z. Markus, “GPCC status Report December 2010,” 2010, [accessed Mar. 20, 2013]
  11. [11] K. Tanaka, “Development of the New Land Surface Scheme SiBUC Commonly Applicable to Basin Water Management and Numerical Weather Prediction Model,” Doctoral Dissertation, Graduate School of Engineering, Kyoto University, pp. 289, 2004.
  12. [12] Y. Hirabayashi, S. Kanae, K. Motoya, K. Masuda, and P. Doll, “A 59-year (1948-2006) global near-surface meteorological data set for land surface models,” Hydrological Research Letters, Vol.2, pp. 36-40, 2008.
  13. [13] K. Onogi et al., “The JRA-25 reanalysis,” J. of the Meteorological Society of Japan, Vol.85, pp. 369-432, 2007.
  14. [14] D. Yamazaki, T. Oki, and S. Kanae, “Deriving a global river network map and sub-grid topographic characteristics from a fineresolution flow direction map,” Hydrology and Earth System Sciences, Vol.13, pp. 2241-2251, 2009.
  15. [15] S. F. Fekete, A. T. K. Tchuente, J. L. Roujean, V. Masson, E. Martin, and P. L. Moigue, “ECOCLIMAP-2/Europe: a twofold database of ecosystems and surface parameters at 1-km resolution based on satelllite information for use in land surface, meteorological and climate models,” Geoscientific Model Development Discussions, Vol.5, pp. 3573-3620, 2013.
  16. [16] M. B. Fekete and J. V. Charles, “Uncertainly in precipitation and their impacts on runoff estimates,” J. of Climate, Vol.17, pp. 294-304, 2003.

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