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Rainfall Threshold for Landslide Warning in Southern Thailand – An Integrated Landslide Susceptibility Map with Rainfall Event – Duration Threshold

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Southern Thailand is one of hotspots for landslides. So far, the rainfall triggered landslides in this region caused many sufferers and fatalities. On the basis of the rainfall data that triggered ninety-two landslide events during 1988–2018 and the landslide susceptibility maps published by the Department of Mineral Resources (DMR), this study introduced rainfall event-duration (ED) thresholds, namely EDm and EDh thresholds, for the places classified as the modest and the huge susceptibility levels, respectively. The modest susceptibility is a combination of very low, low, and moderate landslide susceptibility levels indicated in DMR maps. The huge susceptibility is a combination of high and very high landslide susceptibility levels indicated in DMR maps. Indicated by an area under the receiver operating characteristic curve (AUC), the EDm and EDh thresholds yielded the significantly better predictability than the original threshold did. Furthermore, the EDm threshold yielded the perfect prediction with AUC of 1.00.
Rocznik
Strony
124--133
Opis fizyczny
Bibliogr. 20 poz., rys., tab.
Twórcy
  • Center of Excellence in Civil Engineering, School of Civil Engineering, Institute of Engineering, Suranaree University of Technology 111 University Avenue, Muang, Nakhon Ratchasima 30000, Thailand
  • Center of Excellence in Civil Engineering, School of Civil Engineering, Institute of Engineering, Suranaree University of Technology 111 University Avenue, Muang, Nakhon Ratchasima 30000, Thailand
  • School of Civil Engineering, Rajamangala University of Technology Isan 744 Sura Narai Road, Muang District, Nakhon Ratchasima 30000, Thailand
autor
  • Faculty of Civil Engineering, Hanoi University of Mining and Geology, North Tu Liem District, Hanoi City, Vietnam
Bibliografia
  • 1. Aleotti P. 2004. A warning system for rainfall-induced shallow failures. Eng Geol., 73, 247–265. https://doi.org/10.1016/j.enggeo.2004.01.007
  • 2. Bonta J.V., Rao A.R. 1988. Factors affecting the identification of independent storm events. Journal of Hydrology, 98(3–4), 275–293. https://doi.org/10.1016/0022-1694(88)90018-2
  • 3. Caine, N. 1980. The Rainfall Intensity: Duration Control of Shallow Landslides and Debris Flows. Geografiska Annaler. Series A, Physical Geography, 62(1/2), 23–27. https://doi.org/10.2307/520449
  • 4. Chinkulkijniwat A., Salee R., Horpibulsuk S., Arulrajah A., Hoy M. 2022 Landslide rainfall threshold for landslide warning in Northern Thailand, Geomatics, Natural Hazards and Risk, 13(1), 2425–2241. https://doi.org/10.1080/19475705.2022.2120833
  • 5. Department of Mineral Resources 2019. Department of Mineral Resources, 75/10 Rama 6 Road, Thung Phayathai Sub-district, Ratchathewi District, Bangkok 10400, Thailand. webmaster@dmr.mail.go.th
  • 6. Department of Mineral Resources 2022. Landslide susceptibility map (last assess September 15th, 2022). https://gis.dmr.go.th/DMR-GIS/gis
  • 7. Gariano S.L., Melillo M., Peruccacci S., Brunetti M.T. 2019. How much does the rainfall temporal resolution affect rainfall thresholds for landslide triggering? Natural Hazards, 100, 655–670. https://doi.org/10.1007/s11069-019-03830-x
  • 8. Guzzetti F., Peruccacci S., Rossi M., Stark C.P. 2008. The rainfall intensity-duration control of shallow landslides and debris flows: an update. Landslides, 5, 3–17. https://doi.org/10.1007/s10346-007-0112-1.
  • 9. He S., Wang J., Liu S. 2020. Rainfall Event–Duration Thresholds for Landslide Occurrences in China. Water 12(2), 494. https://doi.org/10.3390/w12020494
  • 10. Jemec Auflič M., Šinigoj J., Krivic M., Podboj M., Peternel T., Komac M. 2016. Landslide prediction system for rainfall induced landslides in Slovenia (Masprem). Geologija, 59, 259–271. https://doi.org/10.5474/geologija.2016.016
  • 11. Jin S., Fu S. 2020. Mechanisms accounting for the repeated occurrence of torrential rainfall over South Thailand in early January 2017, Atmospheric and Oceanic Science Letters, 13(2), 155–162. https://doi.org/10.1080/16742834.2019.1706427
  • 12. Koenker R., Bassett G. 1978. Regression Quantiles. Econometrica 46(1), 33. https://doi.org/10.2307/1913643
  • 13. Koenker R. 2009. Quantile Regression in R: A Vignette. Available at http://www.econ.uiuc.edu/~roger/research/rq/vig.pdf.
  • 14. Koenker R., Hallock K.F. 2001. Quantile regression. Journal of Economic Perspectives, 15(4), 143–156. https://doi.org/10.1257/jep.15.4.143
  • 15. Salee R., Chinkulkijniwat A., Yubonchit S., Horpibulsuk S., Wangfaoklang C., Soisompong S. 2022. New threshold for landslide warning in the southern part of Thailand integrates cumulative rainfall with event rainfall depth-duration. Natural Hazards, 113(1), 125–141. https://doi.org/10.1007/s11069-022-05292-0
  • 16. Schmidt-Thomé P., Tatong T., Kunthasap P., Wathanaprida S. 2018. Community based landslide risk mitigation in Thailand. Episodes, 41(4), 225–233. https://doi.org/10.18814/epiiugs/2018/018017
  • 17. Segoni S., Lagomarsino D., Fanti R., Moretti S., Casagli N. 2015. Integration of rainfall thresholds and susceptibility maps in the Emilia Romagna (Italy) regional-scale landslide warning system. Landslides, 12, 773–785. https://doi.org/10.1007/s10346-014-0502-0
  • 18. Segoni S., Tofani V., Rosi A., Catani F., Casagli N. 2018. Combination of Rainfall Thresholds and Susceptibility Maps for Dynamic Landslide Hazard Assessment at Regional Scale. Front. Earth Sci., 6, 85. https://doi.org/10.3389/feart.2018.00085
  • 19. Vennari C., Gariano S.L., Antronico L., Brunetti M.T., Iovine G., Peruccacci S., Guzzetti F. 2014. Rainfall thresholds for shallow landslide occurrence in Calabria, southern Italy. Natural Hazards and Earth System Sciences, 14(2), 317–330. https://doi.org/10.5194/nhess-14-317-2014
  • 20. Vessia G., Parise M., Brunetti M.T., Peruccacci S., Rossi M., Vennari C., Guzzetti F. 2014. Automated reconstruction of rainfall events responsible for shallow landslides. Natural Hazards and Earth System Sciences, 14(9), 2399–2408. https://doi.org/10.5194/nhess-14-2399-2014.
Uwagi
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-2cec2071-aaa4-4372-89ec-9fcd38e61672
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