Abstract

Tropical cyclone (TC) Cempaka which occurred on 27–29 November 2017 has caused floods, landslides, and strong winds in certain areas of Java Island. Pacitan Regency was the most severely affected by TC Cempaka. The landslide frequency–area distribution curve of event inventory i.e. TC Cempaka can help to understand landslide susceptibility, hazard, vulnerability, and risk. Landslides were identified by using a local government database and by comparing pre- and post-event high-resolution satellite imageries. Field investigation was carried out in March 2018 to November 2018 to verify the landslide location and update the information. Power law, inverse gamma, and double Pareto model were employed to describe the frequency–magnitude of landslide (mLS) triggered by TC Cempaka. The exponent β values of power law, inverse gamma, and double Pareto were 2.6±0.28 (fitted for 8.5% of dataset), 2.2±0.08 (fitted for 83% of dataset), and 2.3±0.09 (best fitted for dataset), respectively. The P-values were 0.51, 0.67, and 0.91 for power law, inverse gamma, and double Pareto, respectively. This study revealed that rollover occurred at 200 and 300 m2 for double Pareto and inverse gamma, respectively. The cutoff points totaled 1096.49 ± 236.44 and 7235.4 ± 1896.7 m2 for double Pareto and power law, respectively. Rollover phenomenon was real and existed in the dataset because it was far from the minimum resolvable size of the landslide that the authors can delineate from the satellite images. mLS for Pacitan was distributed at around 2 to 4. The magnitude of large landslides was 3.2, that of medium landslides was less than 3, and that of small landslides was almost 4. Numerical estimation calculated a fixed mLS=3.01. Comparison analysis of β values obtained from several landslide inventories triggered by heavy rainfall suggests that the variability of β is related to the intensity and duration of rainfall. Triggering events, such as intensity and duration of rainfall, affect the proportion of large landslides that occur in an area. More complete landslide inventories and rainfall data or other landslide triggering factors from other areas are required for further relationship analysis between the β value and landslide triggering factors.

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