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Assessing Flood Risk of the Chao Phraya River Basin Based on Statistical Rainfall Analysis Assessing Flood Risk of the Chao Phraya River Basin Based on Statistical Rainfall Analysis Paper: Assessing Flood Risk of the Chao Phraya River Basin Based on Statistical Rainfall Analysis Shakti P. C.∗1,†, Mamoru Miyamoto∗2, Ryohei Misumi∗1,YousukeNakamura∗3, Anurak Sriariyawat∗4, Supattra Visessri∗4,∗5, and Daiki Kakinuma∗2 ∗1National Research Institute for Earth Science and Disaster Resilience (NIED) 3-1 Tennodai, Tsukuba, Ibaraki 305-0006, Japan †Corresponding author, E-mail: [email protected] ∗2International Centre for Water Hazard and Risk Management under the auspices of UNESCO (ICHARM), Public Works Research Institute (PWRI), Ibaraki, Japan ∗3Mitsui Consultants Co., Ltd., Tokyo, Japan ∗4Department of Water Resources Engineering, Faculty of Engineering, Chulalongkorn University, Bangkok, Thailand ∗5Disaster and Risk Management Information Systems Research Group, Faculty of Engineering, Chulalongkorn University, Bangkok, Thailand [Received June 25, 2020; accepted September 7, 2020] The Chao Phraya River Basin is one of the largest in water-related ones most commonly cause severe damage Asia and is highly vulnerable to water-related disas- to industries, property, and infrastructure, as well as loss ters. Based on rainfall gauge data over 36 years (1981– of lives almost on an annual basis worldwide [2]. Hence, 2016), a frequency analysis was performed for this numerous projects have focused on studying water-related basin to understand and evaluate its overall flood risk; disasters globally to address such issues. One of the most daily rainfall measurements of 119 rain gauge stations significant contributions of the private sector to disaster within the basin were considered. Four common prob- risk management is the Business Continuity Plan (BCP) ability distributions, i.e., Log-Normal (LOG), Gum- and Business Continuity Management (BCM) system, bel type-I (GUM), Pearson type-III (PE3), and Log- which were standardized as ISO22301 and disseminated Pearson type-III (LP3) distributions, were used to cal- across numerous business enterprises worldwide [3]. Re- culate the return period of rainfall at each station and cently, a major project on Regional Resilience Enhance- at the basin-scale level. Results of each distribution ment was launched by establishing the Area-BCM at in- were compared with the graphical Gringorten method dustrial complexes across Thailand, aiming to enhance re- to analyze their performance; GUM was found to be gional resilience by visualizing disaster risks through col- the best-fitted distribution among the four. Thereafter, laboration of industry, government, and academia. The design hyetographs were developed by integrating the project is mainly focused on Thailand and is under the return period of rainfall based on three adopted meth- Science and Technology Research Partnership for Sus- ods at basin and subbasin scales; each method had its tainable Development (SATREPS), a Japanese govern- pros and cons for hydrological applications. Finally, ment program that promotes international joint research. utilizing a Rainfall-Runoff-Inundation (RRI) model, The program is structured as a collaboration between the we estimated the possible flood inundation extent and Japan Science and Technology Agency (JST) [4]. Sev- depth, which was outlined over the Chao Phraya River eral components are to be integrated to build a resilient re- Basin using the design hyetographs with different re- gional community against disasters by visualizing disaster turn periods. This study can help enhance disaster risks and introduction of the Area-BCM. A hydrological resilience at industrial complexes in Thailand for sus- investigation dealing with disaster-risk is a key compo- tainable growth. nent of the project to highlight possible hydrological risk in the industrialized urban areas of Thailand. A basic approach in assessing hydrological risk and sci- Keywords: probability distribution, return period of rain- entifically evaluating a river basin is the collection and fall, design hyetograph, flood inundation, Chao Phraya analysis of hydrometeorological data. Precipitation is Basin a major component, which includes rain, snow, drizzle, and sleet. In the warm climate region, precipitation in the form of rain is common. Precipitation studies can 1. Introduction play a vital role in dealing with hydrological cycles in nature; the practice has been adopted globally. For in- Natural disasters have threatened human life and in- stance, analyzing rainfall data over a long-term could be a frastructure globally, and urbanized regions are espe- good reference for various hydrological analyses and wa- cially vulnerable [1]. Among the several natural disasters, ter resource-based planning, which has been highlighted Journal of Disaster Research Vol.15 No.7, 2020 1025 P. C., S. et al. in several studies [5–7]. If looked into greater detail, a fall as the input for the hydrological model. frequency analysis of historical extreme rainfall events For a comprehensive hydrological analysis of rainfall can help calculate their frequency, as well as in predicting over a river basin focusing on historical data, we selected floods. Therefore, policy makers, engineers, and planners the Chao Phraya River Basin, one of the larger basins would be interested in understanding the probabilities of in Asia, which is considered an important river basin in occurrence of future events for various return periods. Thailand for several reasons [13]. Flooding is quite com- In general, long-term historical data sets have been an- mon in this basin, which always causes significant eco- alyzed using various statistical methods for this purpose. nomic losses. The rapid urbanization, industrialization, However, availability of such data may vary from place to and intensification of agricultural practices are quite com- place because of several factors such as the physiographic mon around the Chao Phraya River. The severe flood- condition, setting up of rain gauges, and climate; hence, ing that occurred during the 2011 monsoon season in- rainfall data over 30 years are believed to be reliable for undated large parts of Bangkok, causing 815 deaths and a frequency analysis of any river basin. Spatial distribu- over $45 billion in economic damages [14]. The Thai tion of rainfall pattern may vary greatly at any location. economy reportedly contracted by 9.0% in 2011 mainly Therefore, data from a dense network of rain gauges over owing to this severe flooding [13], which clearly indi- any basin is desirable to obtain reasonable estimates of the cated the risks of business disruption and further impact intensity and frequency of rare events; however, no strict on national, regional, and global economies through sup- rules exist for having a specific number of rain gauges. If ply chains when disasters occur anywhere [3]. Although a river basin has only a few rain gauges with data avail- several studies related to specific flooding events over the able over a long period, the results might be unreliable at a Chao Phraya River Basin exist [3, 13–20], a comprehen- basin scale; hence, a frequency analysis of rainfall based sive hydrological analysis considering historical rainfall on the most available number of rain gauges are useful data from several rain gauge stations is insufficient, es- and have various hydrological applications. In most cases, pecially for such a large river basin. Hence, a frequency a frequency analysis of the average rainfall of a basin has analysis of historical rainfall over the Chao Phraya River been performed for various return periods; in general, for Basin could certainly contribute to a flood risk analysis return periods of 50, 100, 200, and 500 years. Various and to the Area-BCM by providing insights on flood risk. methods and practices have been adopted to determine the Such an analysis could also be useful to planners, engi- probability of occurrence of events [6, 8–11]. Note that neers, and the general public within the considered river no fixed method exists for calculating the return period basin. of rainfall; hence, numerous discussions exist in selecting appropriate methods. Various theoretical and analytical distributions have 2. Data and Methods been used to calculate the return period of rainfall at a gauge station or at the basin scale; each distribution might Daily rainfall data from 1981–2016 from all 119 rain give slightly different values because each is based on gauge stations were used in this study. Fig. 1 shows the a different principle. Several studies show that the best geographical location of the Chao Phraya River Basin and distribution could vary for each region or river basin [6– the distribution of the rain gauge stations within. The dis- 8, 10, 11]. Hence, selecting an appropriate distribution to tribution of a dense rain gauge network appears in the cen- obtain a reliable return period of extreme rainfall for any tral part of the basin. The Royal Irrigation Department river basin is one of the major engineering challenges. (RID) and the Thai Meteorological Department (TMD) Conversely, the calculated return period of rainfall needs are responsible for regularly monitoring rainfall data at proper utilization in a hydrological analysis for mitigating these stations. Daily rainfall data were missing from sta- possible water-related disaster risks. Therefore, a design tions for some years and for some time intervals; to ad- hyetograph by combining various return periods of rain- dress this and recover missing data in good format
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