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Development of a Landslide Early Warning System in Indonesia

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Balai Litbang Sabo, Pusat Litbang Sumber Daya Air, Ministry of Public Works and Housing, Jl. Sabo No. 1, Maguwoharjo, Sleman, Daerah Istimewa Yogyakarta 55282, Indonesia
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Hydrology and Quantitative Water Management, Wageningen University and Research, Droevendaalsesteeg 3a, 6708 PB Wageningen, The Netherlands
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Author to whom correspondence should be addressed.
Geosciences 2019, 9(10), 451; https://doi.org/10.3390/geosciences9100451
Received: 19 September 2019 / Revised: 8 October 2019 / Accepted: 16 October 2019 / Published: 22 October 2019
(This article belongs to the Section Natural Hazards)
Landslides are one of the most disastrous natural hazards in Indonesia, in terms of number of fatalities and economic losses. Therefore, Balai Litbang Sabo (BLS) has developed a Landslide Early Warning System (LEWS) for Indonesia, based on a Delft–FEWS (Flood Early Warning System) platform. This system utilizes daily precipitation data, a rainfall threshold method, and a Transient Rainfall Infiltration and Grid-based Regional Slope-stability model (TRIGRS) to predict landslide occurrences. For precipitation data, we use a combination of 1-day and 3-day cumulative observed and forecasted precipitation data, obtained from the Tropical Rainfall Measuring Mission (TRMM) and the Indonesian Meteorological Climatological and Geophysical Agency (BMKG). The TRIGRS model is used to simulate the slope stability in regions that are predicted to have a high probability of landslide occurrence. Our results show that the landslides, which occurred in Pacitan (28 November 2017) and Brebes regions (22 February 2018), could be detected by the LEWS from one to three days in advance. The TRIGRS model supports the warning signals issued by the LEWS, with a simulated factor of safety values lower than 1 in these locations. The ability of the Indonesian LEWS to detect landslide occurrences in Pacitan and Brebes indicates that the LEWS shows good potential to detect landslide occurrences a few days in advance. However, this system is still undergoing further developments for better landslide prediction. View Full-Text
Keywords: landslides; early warning system; precipitation forecasts; rainfall threshold; slope stability model landslides; early warning system; precipitation forecasts; rainfall threshold; slope stability model
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Hidayat, R.; Sutanto, S.J.; Hidayah, A.; Ridwan, B.; Mulyana, A. Development of a Landslide Early Warning System in Indonesia. Geosciences 2019, 9, 451.

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