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.

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.

Bandar udara merupakan salah satu prasarana transportasi yang mempunyai peran yang sangat penting saat ini. Perkembangan angkutan udara yang pesat harus diimbangi dengan pengembangan bandar udara sehingga tujuan dari transportasi dapat terpenuhi. Dalam perencanaan, perancangan maupun pengembangan fasilitas bandar udara baik itu sisi udara (runway, taxiway, dan apron) maupun sisi darat (terminal penumpang) diperlukan banyak tabel dan rumus yang harus digunakan sehingga memungkinkan terjadinya kesalahan dalam proses analisis secara manual. Pemrograman komputer dalam pembuatan software prediksi kebutuhan runway, taxiway, apron dan terminal penumpang dapat dijadikan solusi agar proses analisis dapat dilakukan dengan cepat, tepat, dan teliti. Analisis pada fasilitas sisi udara (runway, taxiway dan apron) didasarkan pada pedoman ICAO (1999) sedangkan pada fasilitas sisi darat (terminal penumpang) didasarkan pada perpaduan beberapa pedoman seperti SKEP/347/XII/99, JICA(1992) dan IATA (1989). Software pemrograman yang digunakan dalam penelitian ini adalah Visual Basic 2010 berbasis Windows. Data yang digunakan untuk uji validitas merupakan data sekunder yang diambil dari penelitian-penelitian yang telah dilakukan sebelumnya. Pada fasilitas sisi darat dan udara, data sekunder diambil dari tugas akhir yang telah dilakukan sebelumnya oleh Zulaekhah (2010) dan Setyana (2010) dengan studi kasus pada Bandara Ngurah Rai, Bali. Hasil uji validitas dari perbandingan antara analisis secara manual dan dengan menggunakan program AirFuLs 10 pada fasilitas bandar udara seperti runway, taxiway, apron dan terminal penumpang sebesar 0,000%. Hal ini membuktikan bahwa program AirFuLs 1.0 yang telah dibuat dapat dikatakan valid untuk digunakan.

<p>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, 1<sup>st</sup> is the existing threshold applied in the Balai Sabo-ILEWS, the 2<sup>nd</sup> and the 3<sup>rd</sup> use the average and minimum of rainfall that trigger landslides, respectively, and the 4<sup>th</sup> 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 4<sup>th</sup> 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.</p>

Rawapening has an area of 2,667 acres, which now ceases to exist. This natural reservoir serves to preserve water, control flood, generate electric turbine, and raw water resource. The depth of this lake decreases 42 cm annually, with the shallowing could cause flooding of the lakeside and and reducing the water supply. This study finds the additional amount of structure and dimension of sabo dam to prevent hazards at each river: at Panjang 2 (B=20m H=2m, and B=25m H=2,5 m), at Galeh 2 (each of B=8m H=2,4m), at Legi 2 (B=10m H=2m, and B=25m and H=2,5m), at Parat 1 (B=13m H=2,7m), at upstream Sraten 1 (B=15m H=2,7m), at downstream Sraten 1 (B=15m H=2,7m), and at Kedungringgis 1 (B=12m H=1,8m). Existing materials are fine and rough sand. Using WaTEM/SEDEM, saboplan guideline by processing the designed capacity, it is estimated that each river’s potential annual yield (in tonnes): Panjang 86.221,8, Galeh/Torong 45.138,24, Legi 42.404,04, Parat 28.579,32, Sraten 25.988,76, and Kedung Ringis 6.955,2. Overall, sabo dam is designed to be a closed type dam located in inlet rivers of Rawapening. Sabo dam construction holds 25% of potential sediment. Collectively, it adds a control volume of 2.885 m3, from 11.539 m3 to become approximately to become 14.424 m3. To cope with sedimentation in Rawapening, the structural approachment (sabodam) should be combined with non structural approachment such as restoring land use in the upstream area for more optimal sedimentation control.Keywords: Sedimentation, rawapening, erosion, WaTEM/SEDEM