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.

The mapping of soil movement was examined by comparing an extension of the deterministic Soil Stability Index Mapping (SINMAP) method, and an overlay method with trigger parameters of soil movement. The SINMAP model used soil parameters in the form of the cohesion value (c), internal friction angle (φ), and hydraulic conductivity (k_s) for the prediction of soil movement based on the factor of safety (FS), while the indirect method used a literature review and field observations. The weightings of soil movement trigger parameters in assessments were based on natural physical aspects: (1) slope inclination = 30%; (2) rock weathering = 15%; (3) geological structure = 20%; (4) rainfall = 15%; (5) groundwater potential = 7%; (6) seismicity = 3%; and (7) vegetation = 10%. The research area was located in the Buleleng district, in particular in the ancient mountain area of Buyan-Tamblingan, in the Sukasada sub-district. The hazard mapping gave a high and very high hazard scale. The SINMAP model gave a validation accuracy of 14.29%, while the overlay method with seven trigger parameters produced an accuracy of 71.43%. Based on the analysis of the very high and high hazard class and the validation of the landslide occurrence points, the deterministic method using soil parameters and water absorption gave a much lower accuracy than the overlay method with a study of soil motion trigger parameters.

Consolidation settlement is a general geotechnical problem particularly found in the area where is composed of soft soil. It is caused by the discharge of pore water pressure induced by the increase of stress in the soil mass. Construction of runway above soft soil requires analysis for stability related to the reduction of consolidation settlement and the recovery. This study aims to analyze the settlement comprehensively using empirical methods of Prefabricated Vertical Drains (PVD) and preloading installation. Preloading is a technique by which consolidation of soil can be achieved to a substantial amount before the imposition of actual construction load. According to soil investigation, the characteristic of the soil layer is clay soil, which has the potential to consolidation settlement. The result of the settlement analysis of the taxiway in the research area is from 33 cm to 214 cm. It takes ten years for primary consolidation to reach a 90% degree of consolidation. However, in the Hansbo method of Prefabricated Vertical Drains (PVD) and preloading are applied, with triangular configurations in depth of 11 meters and duration for variation embankment spacing of 1 m is 79 days, 1.5 m is 202 days and 2 m is 390 days. The conclusion of efficient distance of PVD installation and preloading is spacing of 1 m with 79 days for primary consolidation.

Increasing development of infrastructure in Indonesia has driven the need for effective ground improvement methods to accelerate the consolidation of soft soil, which is estimated to occupy around 10% of the country’s land area. A prefabricated vertical drain combined with vacuum preloading is among the most effective methods for this purpose. However, the prefabricated vertical drain creates a smear zone in the surrounding soil area during installation. This study examines the effectiveness of a newly developed mandrel system in reducing the smear zone during prefabricated vertical drain installation. Large-scale consolidation tests at a macro level and microstructure analysis using scanning electron microscopy at a micro level were employed to investigate the effect of soil water content and shear strength. The results show that the water content and shear strength of the soft soil gradually increased in the inner smear zone and transition zone, while both decreased in the radial distance. Furthermore, the soil structure underwent a transformation in which the particle area and pore area became a closed flake structure, and apparent agglomeration occurred. The test results indicate that the newly developed mandrel system can effectively reduce the smear zone. The macro to micro test results demonstrated that the mandrel system is successful in reducing the smear zone effect.

Landslides were addressed as one of the natural hazards that can create extensive disasters. Effective assessment to locate potential landslide events is crucial for planning and risk mitigation. This study, which is located in the Sumitro watershed, Kulon Progo, Yogyakarta, presents a novel approach to landslide susceptibility assessment by integrating the Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability Model (TRIGRS) with the Flow-R model. Five key parameters, namely slope, soil properties, groundwater level, soil thickness, and rainfall, were used to create the landslide susceptibility zonation. TRIGRS was used to identify the landslide initiation, while Flow-R was used to create the run-out area. The result was then validated through statistical evaluation using Area Under Curve (AUC) based on the landslide inventory. Results show that landslide susceptibility zonation created from TRIGRS alone resulted in an AUC value of 0.679, while the combination of TRIGRS-Flow-R susceptibility zonation shows a better AUC value of 0.728. The increase of the AUC value of almost 0.05 has enhanced the correlation between the landslide susceptibility zonation and landslide inventory from “acceptable” to “excellent” correlation. This result demonstrates that integrating Flow-R with TRIGRS improves the performance of landslide susceptibility zonation. This study offers a new perspective on creating landslide susceptibility zonation by combining two methods, yielding more reliable results. Doi: 10.28991/CEJ-2025-011-03-020 Full Text: PDF