Revisited Rainfall Threshold In the Indonesia Landslide Early Warning System
- 1University of Gadjah Mada, Faculty of Engineering, Civil and Environmental, Yogyakarta, Indonesia (ragilandika@mail.ugm.ac.id)
- 2University of Twente, Faculty of Geoinformation Science and Earth Observation (ITC), Hengelosestraat 99, 7514 AE, Enschede, The Netherland (a.subiyantoro@utwente.nl)
- 3Department of Civil Engineering, Universitas Muhammadiyah Yogyakarta (UMY), Yogyakarta, Indonesia (muntohar@umy.ac.id)
- 4Balai Teknik Sabo, Direktorat Bina Teknik, Ministry of Public Works and Housing, Jl. Sabo No. 1, Maguwoharjo, Sleman, Yogyakarta 55282, Indonesia (akhyar.mushthofa@pu.go.id)
- 5Water System and Global Change group, Wageningen University and Research, Droevendaalsesteeg 3a, 6708 PB Wageningen, The Netherlands (samuel.sutanto@wur.nl)
- 6Center for Research and Development, Indonesian Agency for Meteorology, Climatology and Geophysics, Jakarta, 10720, Indonesia (ratnasat@gmail.com)
Landslides are one of the most disastrous natural hazards that frequently occur in Indonesia. Since 2017, Balai Sabo has developed an Indonesia Landslide Early Warning System (ILEWS) by utilizing a single rainfall threshold for an entire nation. This condition might lead to inaccuracy of the landslide prediction. Therefore, this study aims to improve the accuracy of the system by updating the rainfall threshold. This study focused on Java Island, where most of the landslides in Indonesia occur. We analyzed 420 landslide events with the one-day and three-day cumulative 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, 1st is the existing threshold applied in the Balai Sabo-ILEWS, the 2nd and the 3rd use the average and minimum of rainfall that trigger landslides, respectively, and the 4th uses the minimum values of rainfall that induce major landslides. We employed the Receiver Operating Characteristic (ROC) analysis to evaluate the predictability of the rainfall thresholds. The 4th method shows the best result compared to the others, and this method provides a good prediction of landslide events with a low error value. The chosen threshold will be used as a new threshold in the Balai Sabo-ILEWS.
How to cite: Yuniawan, R. A., Rifai, A., Faris, F., Westen, C. V., Jetten, V., den Bout, B., Subiyantoro, A., Muntohar, A., Musthofa, A., Hidayat, R., Hidayah, A., Ridwan, B., Priangga, E., Satyaningsih, R., and Sutanto, S.: Revisited Rainfall Threshold In the Indonesia Landslide Early Warning System , EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7863, https://doi.org/10.5194/egusphere-egu22-7863, 2022.