Publication: FLOOD SUSCEPTIBILITY MAPPING USING LOGISTIC REGRESSION ANALYSIS IN LAM KHAN CHU WATERSHED, CHAIYAPHUM PROVINCE, THAILAND
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Issued Date
2023
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application/pdf
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มหาวิทยาลัยศรีนครินทรวิโรฒ
Bibliographic Citation
Geography, Environment, Sustainability. Vol 16, No.2 (2023), p.41-56
Suggested Citation
Waiyasusri K., Wetchayont P., Tananonchai A., Suwanmajo D. FLOOD SUSCEPTIBILITY MAPPING USING LOGISTIC REGRESSION ANALYSIS IN LAM KHAN CHU WATERSHED, CHAIYAPHUM PROVINCE, THAILAND. Geography, Environment, Sustainability. Vol 16, No.2 (2023), p.41-56. doi:10.24057/2071-9388-2022-159 Retrieved from: https://hdl.handle.net/20.500.14740/10503
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Abstract
Due to Tropical Storm Dianmu’s influence in the Lam Khan Chu watershed (LKCW) area, central Thailand saw its worst flood in 50 years from September 23 to September 28, 2021. The flooding lasted for 1-2 months. The objective of this research is to study flood susceptibility using logistic regression analysis in LCKW area. According to the study 11 floods occurred repeatedly between 2005 and 2021, in the southern of Bamnetnarong district and continued northeast to Chaturat district and Bueng Lahan swamp. These areas are the main waterways of the LKCW area, the Lam Khan Chu stream and the Huai Khlong Phai Ngam, for which the dominant flow patterns are braided streams. The main factors influencing flooding are geology, stream frequency, topographic wetness index, drainage density, soil, stream power index, land-use, elevation, mean annual precipitation, aspect, distance to road, distance to village, and distance to stream. The results of the logistic regression analysis shed light on these factors. All such variables were demonstrated by the β value coefficient. The area’s susceptibility to flooding was projected on a map, and it was discovered to have extremely high and high levels of susceptibility, encompassing regions up to 148.308 km2 (8.566%) and 247.421 km2 (14.291%), respectively, in the vicinity of the two main river sides of the watershed. As a result of this research the flood susceptibility map will be used as a guideline for future flood planning and monitoring. © Waiyasusri K., Wetchayont P., Tananonchai A. et al.