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Revised Rainfall Threshold in the Indonesian Landslide Early Warning System.

Authors :
Yuniawan, Ragil Andika
Rifa'i, Ahmad
Faris, Fikri
Subiyantoro, Andy
Satyaningsih, Ratna
Hidayah, Alidina Nurul
Hidayat, Rokhmat
Mushthofa, Akhyar
Ridwan, Banata Wachid
Priangga, Eka
Muntohar, Agus Setyo
Jetten, Victor G.
Westen, Cees J. van
Bout, Bastian V. den
Sutanto, Samuel J.
Source :
Geosciences (2076-3263); Mar2022, Vol. 12 Issue 3, p129-N.PAG, 17p
Publication Year :
2022

Abstract

Landslides are one of the most disastrous natural hazards that frequently occur in Indonesia. In 2017, Balai Sabo developed an Indonesia Landslide Early Warning System (ILEWS) by utilizing a single rainfall threshold for an entire nation, leading to inaccuracy in landslide predictions. The study aimed to improve the accuracy of the system by updating the rainfall threshold. We analyzed 420 landslide events in Java with the 1-day and 3-day effective antecedent rainfall for each landslide event. Rainfall data were obtained from the Global Precipitation Measurement (GPM), which is also used in the ILEWS. We propose four methods to derive the thresholds: the first is the existing threshold applied in the Balai Sabo ILEWS, the second and third use the average and minimum values of rainfall that trigger landslides, respectively, and the fourth uses the minimum value of rainfall that induces major landslides. We used receiver operating characteristic (ROC) analysis to evaluate the predictability of the rainfall thresholds. The fourth method showed the best results compared with the others, and this method provided a good prediction of landslide events with a low error value. The chosen threshold was then applied in the Balai Sabo-ILEWS. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20763263
Volume :
12
Issue :
3
Database :
Complementary Index
Journal :
Geosciences (2076-3263)
Publication Type :
Academic Journal
Accession number :
156019091
Full Text :
https://doi.org/10.3390/geosciences12030129