Jirayuth Srisat creator Sutat Weesakul Chairperson Babel, Mukand S. Examination Committee Natthachet Tangdamrongsub Examination Committee RTG Fellowships Scholarship Donor text series technical report th Pathum Thani, Thailand Asian Institute of Technology 2024 continuing eng

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199 leaves : ill.+ 1 online resource Mae Sai District, Chiang Rai located at border between Thailand and Myanmar, have the shared market with experiences recurrent flash flood. Main impact of the flash flood was property damage for business villagers. The present study aimed to analyze meteo hydrological conditions that cause flash floods. Then, develop empirical and modeling approach. Integrate the flood criteria, and finally propose flood warning framework. Rainfall data is limited and not available in Myanmar side. Eight rainfall stations and water level data from Thailand side were collected to analyze the rainfall, flood characteristics, and flood criteria. There are totally 13 flood events from years 2017 to 2022. Fieldwork and field investigation were carried out to have comprehensive information during the flood. The flood model is to use RRI model as a computational tool with Global Satellite Mapping of Precipitation NOW (GSMaP NOW) as satellite rainfall data. The results showed that the peak water level and 15-minute average weighted rainfall had the strongest correlation (0.73) among other meteo-hydrological parameters correlation, indicating that higher flood peak levels occur with heavier rainfall. However, flooding in the Mae Sai can occur even when rainfall is moderate because the initial water level in Sai River is high at the time. It was found that even 20 mm of rainfall within 24 hours could cause flooding at a high water level of 1.6 meters. Therefore, the flood is classified to the type of single and consecutive rainfall. Its criteria are based on rainfall and initial water level. For flood model calibration and validation, it provides 0.83 and 0.19 in terms of NSE respectively. A fieldwork and field investigation revealed that Mae Sai people need flood warnings 3-6 hours in advance, and flood warning using the public address speaker and broadcasting tower is the most required. Flood warning system framework was developed based on the present work both technical, management, and communication aspects. A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in Water Engineering and Management Thesis (M. Sc.) - Asian Institute of Technology, 2024 Flood warning systems Thailand Mae Sai (Amphoe) Flood forecasting Thailand Mae Sai (Amphoe) Asian Institute of Technology. http://203.159.5.9/ait-thesis/detail.php?q=B22097 http://203.159.5.9/ait-thesis/detail.php?q=B22097 250501 20260818095651.0