EVALUATION OF LANDSLIDE SUSCEPTIBILITY USING TRIGRS METHOD AT ARJASARI, BANJARAN AND ITS SURROUNDINGS AREA, BANDUNG REGENCY, WEST JAVA

• Main Author: Ema Nurdiana, Della
• Format: Theses
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/74067
• Institution: Institut Teknologi Bandung

Rainfall is one of the triggering factors for landslides in Indonesia. Landslide susceptibility modeling related to rainfall can be done spatially with The Transient Rainfall Infiltration and Grid-based Regional Slope stability (TRIGRS). This study aimed to determine the parameters that affect landslide susceptibility and evaluate the slope stability model at Arjasari, Banjaran and its surroundings. This model used annual maximum rainfall data for 48 years to find the 10-year return period rainfall. The modeling was done using the three-day historical situation. The method used in this study was Gumbel's frequency distribution analysis and deterministic analysis of the Factor of Safety (FS) value calculation using the TRIGRS software. After that, AUC was used to verify the generated model. Based on the Gumbel's frequency distribution method, the planned rainfall is 116.86 mm. According to the TRIGRS model's validation, the slope parameter has the greatest influence on the slope stability model, followed by soil thickness, elevation, effective cohesiveness, effective internal shear angle, soil unit weight, flow direction, permeability, and diffusivity. Based on TRIGRS models, the vulnerable area (FS < 1.2) at the period before rain (T0) is 5,90 km2. When 1 day rainfall (T1), the vulnerable area is 11.71 km2. When 2 day rainfall (T2), vulnerable area is 13.11 km2. When 3 day rainfall (T3), vulnerable area is 13.38 km2. This shows that rainfall infiltration does affect the potential for landslides in the study area, which was indicated by the increasing rate of vulnerable area after rain for three days. According to the findings of the AUC analysis, The AUC calculation shows a value of 0.8 (excellent) for the slope stability models at T0, T1, T2, and T3, indicating that the model is feasible to use. Decreasing the FS value along with increasing slope also strengthens that the model is feasible to use.