{"title":"Spatiotemporal variation of landslide using the projected rainfall data from climate change scenario","authors":"T. ., D. Wangmo, V. Sharma, K. Choden","doi":"10.25303/1601da036041","DOIUrl":null,"url":null,"abstract":"The adverse change in weather increases landslide risk every year due to climate change. Consequently, developmental activities were hampered due to the landslide. This study aimed at developing past landslides (1997, 2007, 2017) using national rainfall data and projected landslides for the years 2027, 2037, 2050 and 2100 using the projected rainfall data in three districts of Bhutan namely Zhemgang, Mongar and Bumthang. The study uses elevation, aspect, slope, curvature, TWI, SPI, NDVI, distance from the river, distance from road, lithology and flow accumulation as influencing factors apart from different year rainfall data. The frequency ratio was employed for data analysis. Kappa index and accuracy were used to validate the landslide map for the year 2017. The landslide risk zones are classified into very low, low, moderate, high and very high. It is observed that the total area of the very low zone decreased from 1997 to 2100 while the area of the very high-risk zone increases from 1997 to 2100. Among the districts, the Zhemgang dzongkhag was highly susceptible to landslides. On the other hand, Bumthang district is least impacted by the landslides.","PeriodicalId":50576,"journal":{"name":"Disaster Advances","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Disaster Advances","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.25303/1601da036041","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Engineering","Score":null,"Total":0}
引用次数: 0
Abstract
The adverse change in weather increases landslide risk every year due to climate change. Consequently, developmental activities were hampered due to the landslide. This study aimed at developing past landslides (1997, 2007, 2017) using national rainfall data and projected landslides for the years 2027, 2037, 2050 and 2100 using the projected rainfall data in three districts of Bhutan namely Zhemgang, Mongar and Bumthang. The study uses elevation, aspect, slope, curvature, TWI, SPI, NDVI, distance from the river, distance from road, lithology and flow accumulation as influencing factors apart from different year rainfall data. The frequency ratio was employed for data analysis. Kappa index and accuracy were used to validate the landslide map for the year 2017. The landslide risk zones are classified into very low, low, moderate, high and very high. It is observed that the total area of the very low zone decreased from 1997 to 2100 while the area of the very high-risk zone increases from 1997 to 2100. Among the districts, the Zhemgang dzongkhag was highly susceptible to landslides. On the other hand, Bumthang district is least impacted by the landslides.