K. Waiyasusri, P. Wetchayont, Aekkacha Tananonchai, Dolreucha Suwanmajo
{"title":"基于Logistic回归分析的泰国Chaiyaphum省Lam Khan Chu流域洪水易感性制图","authors":"K. Waiyasusri, P. Wetchayont, Aekkacha Tananonchai, Dolreucha Suwanmajo","doi":"10.24057/2071-9388-2022-159","DOIUrl":null,"url":null,"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.","PeriodicalId":37517,"journal":{"name":"Geography, Environment, Sustainability","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Flood Susceptibility Mapping Using Logistic Regression Analysis In Lam Khan Chu Watershed, Chaiyaphum Province, Thailand\",\"authors\":\"K. Waiyasusri, P. Wetchayont, Aekkacha Tananonchai, Dolreucha Suwanmajo\",\"doi\":\"10.24057/2071-9388-2022-159\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":37517,\"journal\":{\"name\":\"Geography, Environment, Sustainability\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-06-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Geography, Environment, Sustainability\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.24057/2071-9388-2022-159\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"Agricultural and Biological Sciences\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Geography, Environment, Sustainability","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.24057/2071-9388-2022-159","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Agricultural and Biological Sciences","Score":null,"Total":0}
Flood Susceptibility Mapping Using Logistic Regression Analysis In Lam Khan Chu Watershed, Chaiyaphum Province, Thailand
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.
期刊介绍:
Journal “GEOGRAPHY, ENVIRONMENT, SUSTAINABILITY” is founded by the Faculty of Geography of Lomonosov Moscow State University, The Russian Geographical Society and by the Institute of Geography of RAS. It is the official journal of Russian Geographical Society, and a fully open access journal. Journal “GEOGRAPHY, ENVIRONMENT, SUSTAINABILITY” publishes original, innovative, interdisciplinary and timely research letter articles and concise reviews on studies of the Earth and its environment scientific field. This goal covers a broad spectrum of scientific research areas (physical-, social-, economic-, cultural geography, environmental sciences and sustainable development) and also considers contemporary and widely used research methods, such as geoinformatics, cartography, remote sensing (including from space), geophysics, geochemistry, etc. “GEOGRAPHY, ENVIRONMENT, SUSTAINABILITY” is the only original English-language journal in the field of geography and environmental sciences published in Russia. It is supposed to be an outlet from the Russian-speaking countries to Europe and an inlet from Europe to the Russian-speaking countries regarding environmental and Earth sciences, geography and sustainability. The main sections of the journal are the theory of geography and ecology, the theory of sustainable development, use of natural resources, natural resources assessment, global and regional changes of environment and climate, social-economical geography, ecological regional planning, sustainable regional development, applied aspects of geography and ecology, geoinformatics and ecological cartography, ecological problems of oil and gas sector, nature conservations, health and environment, and education for sustainable development. Articles are freely available to both subscribers and the wider public with permitted reuse.