Performance of high-resolution satellite rainfall datasets in developing rainfall-duration threshold for landslide incidents over Badung Regency

Abstract

Abstract Satellite-based rainfall datasets provide high-resolution worldwide rainfall information, which has potential used in identifying rainfall conditions that trigger landslides. Landslides can be forecasted by rainfall thresholds which is used as an early warning system. The threshold model used needs to be validated to know the accuracy in forecasting landslide occurrences provoked by rainfall events. The objective of the current study is to evaluate the ability of three high-resolution satellite-based rainfall datasets (IMERG, GSMaP, and PERSIANN) to develop a rainfall thresholds model for landslide occurrences in Badung Regency. The recent study used cumulative rainfall events (1, 3, 5, 7, 10, 15, 21, and 30 days) leading up to the incidents of landslides. The determination of rainfall threshold values used the statistical distribution namely: first (Q1), second (Q2), and third quartile (Q3). Validation of rainfall threshold results was conducted utilizing receiver operating characteristic (ROC) curves and the area under curve (AUC). The analysis results show that the first quartile (Q1) exhibited the finest accuracy and gives a good estimation of landslide occurrence. Moreover, among all cumulative rainfall events, the 15-day cumulative rainfall demonstrates the highest AUC value (> 0.75), implying a greater likelihood of triggering landslide events over Badung Regency.