Top > JDR > Probable Flood Inundation Depth and Extent in the Chao Phraya ...

single-dr.php

JDR Vol.17 No.6 pp. 901-912
(2022)
doi: 10.20965/jdr.2022.p0901

Paper:

Views over last 60 days: 336

Probable Flood Inundation Depth and Extent in the Chao Phraya River Basin for Different Return Periods

Shakti P. C.*1,†, Mamoru Miyamoto*2, Daiki Kakinuma*2, Ryohei Misumi*1, Anurak Sriariyawat*3, and Supattra Visessri*3,*4

*1National Research Institute for Earth Science and Disaster Resilience (NIED)
3-1 Tennodai, Tsukuba, Ibaraki 305-0006, Japan

†Corresponding author

*2International Centre for Water Hazard and Risk Management under the auspices of UNESCO (ICHARM),
Public Works Research Institute (PWRI), Tsukuba, Japan

*3Department of Water Resource Engineering, Faculty of Engineering, Chulalongkorn University, Bangkok, Thailand

*4Disaster and Risk Management Information Systems Research Unit, Faculty of Engineering, Chulalongkorn University, Bangkok, Thailand

Received:
December 1, 2021
Accepted:
August 12, 2022
Published:
October 1, 2022
Creative Commons License
Keywords:
return period rainfall, hyetograph, hydrological simulation, flood inundation, Chao Phraya
Abstract

Understanding the potential flood inundation depth and extent over river basins can provide a reference for understanding and mitigating the flood risk. However, the development of design hyetographs for the evaluation of flood inundation under extreme rainfall is challenging. We evaluated the flood inundation depth and extent in the Chao Phraya River Basin, one of the largest river basins in Asia, which is often vulnerable to water-related disasters. Rainfall data from 119 stations within the basin were collected for a frequency analysis. After processing the 36-year daily rainfall data, a frequency analysis of the maximum monthly rainfall was performed at each station using the Gumbel distribution. The maximum monthly rainfall for various return periods varied substantially among stations. For an inundation analysis over the entire river basin, we produced design hyetographs by integrating extreme rainfall values for each month according to the return period. These design hyetographs were included in a rainfall-runoff-inundation model to simulate the maximum inundation depth profile over the basin for different return periods. The Maximum inundation depths were 8.3, 9.0, 9.7, and 10.5 m for return periods of 50, 100, 200, and 500 years, respectively, over the Chao Phraya River Basin. Similarly, approximately 16.3%, 17.1%, 17.8%, and 18.6% of the basin area was inundated (depth > 0.5 m) over the return periods, respectively. The results of this study provide a good reference for risk analyses and evaluations of the Chao Phraya River Basin.

Cite this article as:
Shakti P. C., M. Miyamoto, D. Kakinuma, R. Misumi, A. Sriariyawat, and S. Visessri, “Probable Flood Inundation Depth and Extent in the Chao Phraya River Basin for Different Return Periods,” J. Disaster Res., Vol.17 No.6, pp. 901-912, 2022.
Data files:
References
  1. [1] 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. doi: 10.20965/jdr.2013.p0397, 2013.
  2. [2] M. Mujumdar et al., “Droughts and Floods,” R. Krishnan et al., (Ed.), “Assessment of Climate Change over the Indian Region: A Report of the Ministry of Earth Sciences (MoES), Government of India,” pp. 117-141, Springer, doi: 10.1007/978-981-15-4327-2_6, 2020.
  3. [3] M. M. Q. Mirza, “Climate change, flooding in South Asia and implications,” Reg. Environ Change, Vol.11, pp. 95-107, doi: 10.1007/s10113-010-0184-7, 2011.
  4. [4] H. Oshikawa et al., “Impacts of recent climate change on flood disaster and preventive measures,” J. Disaster Res., Vol.3, No.2, pp. 131-141, doi: 10.20965/jdr.2008.p0131, 2008.
  5. [5] M. Nakamura et al., “Effects of global warming on heavy rainfall during the Baiu season projected by a cloud-system-resolving model,” J. Disaster Res., Vol.3, No.1, pp. 15-24, doi: 10.20965/jdr.2008.p0015, 2008.
  6. [6] S. Kusunoki et al., “Global Warming Projection by an Atmospheric Global Model with 20-km Grid,” J. Disaster Res., Vol.3, No.1, pp. 4-14, doi: 10.20965/jdr.2008.p0004, 2008.
  7. [7] IPCC, “Summary for Policymakers,” C. B. Field et al. (Eds.), “Climate Change 2014: Impacts, Adaptation, and Vulnerability, Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change,” pp. 1-32, Cambridge University Press, 2014.
  8. [8] T. Ishigaki et al., “Vulnerability to underground inundation and evacuation in densely urbanized area,” J. Disaster Res., Vol.11, No.2, pp. 298-305, doi: 10.20965/jdr.2016.p0298, 2016.
  9. [9] Science and Technology Research Partnership for Sustainable Development (SATREPS), “Regional Resilience Enhancement through Establishment of Area-BCM at Industry Complexes in Thailand,” https://www.jst.go.jp/global/english/kadai/h2908_thailand.html [accessed June 1, 2020]
  10. [10] M. A. Alam et al., “Best-fit probability distributions and return periods for maximum monthly rainfall in Bangladesh,” Climate, Vol.6, No.1, Article No.9, doi: 10.3390/cli6010009, 2018.
  11. [11] F. A. Huff and J. C. Neill, “Comparison of several methods for rainfall frequency analysis,” J. Geophys. Res., Vol.64, No.5, pp. 541-547, doi: 10.1029/JZ064i005p00541, 1959.
  12. [12] M. T. Amin, M. Rizwan, and A. A. Alazba, “A best-fit probability distribution for the estimation of rainfall in northern regions of Pakistan,” Open Life Sci., Vol.11, pp. 432-440, doi: 10.1515/biol2016-0057, 2016.
  13. [13] Z. Li et al., “Probability modeling of precipitation extremes over two river basins in northwest of china,” Adv. Meteorol., Vol.2015, Article No.374127, doi: 10.1155/2015/374127, 2015.
  14. [14] S. P. C. et al., “Assessing Flood Risk of the Chao Phraya River Basin Based on Statistical Rainfall Analysis,” J. Disaster Res., Vol.15, No.7, pp. 1025-1039, doi: 10.20965/jdr.2020.p1025, 2020.
  15. [15] Z. Li, F. Brissette, and J. Chen, “Finding the most appropriate precipitation probability distribution for stochastic weather generation and hydrological modelling in Nordic watersheds,” Hydrological Processes, Vol.27, No.25, pp. 3718-3729, doi: 10.1002/hyp.9499, 2013.
  16. [16] N. Kimura et al., “Hydrological flood simulation using a design hyetograph created from extreme weather data of a high-resolution atmospheric General Circulation Model,” Water, Vol.6, No.2, pp. 345-366, doi: 10.3390/w6020345, 2014.
  17. [17] T. Sayama et al., “Rainfall-runoff-inundation analysis of the 2010 Pakistan flood in the Kabul River basin,” Hydrological Science J., Vol.57, No.2, pp. 298-312, doi: 10.1080/02626667.2011.644245, 2012.
  18. [18] A. Sriariyawat et al., “Approach to estimate the flood damage in Sukhothai Province using flood simulation,” J. Disaster Res., Vol.8, No.3, pp. 406-414, doi: 10.20965/jdr.2013.p0406, 2013.
  19. [19] T. Sayama, Y. Tatebe, and S. Tanaka, “An emergency response-type rainfall-runoff-inundation simulation for 2011 Thailand floods,” J. Flood Risk Management, Vol.10, No.1, pp. 65-78, doi: 10.1111/jfr3.12147, 2017.
  20. [20] S. P. C., T. Nakatani, and R. Misumi, “Analysis of flood inundation in ungauged mountainous river basins: a case study of an extreme rain event on 5–6 July 2017 in Northern Kyushu, Japan,” J. Disaster Res., Vol.13, No.5, pp. 860-872, doi: 10.20965/jdr.2018.p0860, 2018.
  21. [21] S. P. C. and H. Kamimera, “Flooding in Oda River Basin during torrential rainfall event in July 2018,” Eng. J., Vol.23, No.6, pp. 477-485, doi: 10.4186/ej.2019.23.6.477, 2019.
  22. [22] S. P. C., H. Kamimera, and R. Misumi, “Inundation analysis of the Oda River Basin in Japan during the flood event of 6–7 July 2018 utilizing local and global hydrographic data,” Water, Vol.12, No.4, Article No.1005, doi: 10.3390/w12041005, 2020.
  23. [23] S. P. C., K. Hirano, and S. Iizuka, “Flood inundation mapping of the Hitachi region in the Kuji River Basin, Japan, during the October 11–13, 2019 extreme rain event,” J. Disaster Res., Vol.15, No.6, pp. 712-725, doi: 10.20965/jdr.2020.p0712, 2020.
  24. [24] S. P. C., N. Shrestha, and P. Gurung, “Step wise multi-criteria performance evaluation of rainfall-runoff models using WETSPRO,” J. of Hydrology and Meteorology, Vol.7, No.1, pp. 18-29, doi: 10.3126/jhm.v7i1.5613, 2010.

Creative Commons License  This article is published under a Creative Commons Attribution-NoDerivatives 4.0 Internationa License.

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, Opera.

Last updated on Apr. 18, 2024