Empirically Based Rainfall Threshold for Landslides Occurrence in Peninsular Malaysia

Abstract

Empirical rainfall thresholds for the purpose of shallow landslide forecasting are proposed for Peninsular Malaysia where numerous slope failures are reported due to the intense rainfall in conjunction with the humid tropical climate. Thirty-seven cases of landslide-triggering-rainfall were selected from 1993 to 2018 to identify the correlation between rainfall and shallow landslide through the analysis of specific rainfall events. The derived rainfall parameters were applied to establish two rainfall thresholds of (Imean-D) and (Imax-D) via practical methods. For the identical range of event duration 1 < D < 263 h, the (Imean-D) threshold formula was expressed as I = 17.5 D−0.722, while the (Imax-D) threshold was defined as I = 37.8 D−0.114. Both thresholds performed different functionalities with a primary goal of predicting shallow landslides. When both (Imean-D) and (Imax-D) thresholds were compared with the thresholds proposed by various studies worldwide, both dominated the upper positions. More rainfall is required for land sliding due to the high thickness of the Malaysian soil that is associated with the abundant tropical downpour. From the perspective of the antecedent, the period of prolonged precipitation or short heavy rainfall from 1 to 10 days can result in shallow landslides for Peninsular Malaysia. In the context of geology, the igneous rock type of granite has the highest susceptibility to the shallow landslide at 65%, despite other rock types of sedimentary and metamorphic. The threshold validation depicted all True Positive events for the (Imax-D) threshold, and one Negative False event for the (Imean-D) threshold. The (Imean-D) threshold was revised to acquire the new value, but it needed to deal with the possibility of False Alarm and the (Imax-D) threshold seemed to be more credible to represent the rainfall-induced shallow landslide threshold for Peninsular Malaysia.

Spatiotemporal Characteristics and Rainfall Thresholds of Geological Landslide Disasters in ASEAN Countries

“…(Myanmar). In Peninsular Malaysia, the mean rainfall intensity-duration equation to determine the minimum average rainfall intensity that could trigger shallow landslides obtained by Maturidi et al [16] is 𝐼 = 17.5𝐷 . .…”

“…And the four early warning levels at a regional scale for landslides have been built based on the rainfall-landslides relationship [15]. In Peninsular Malaysia, researchers formulated two separate rainfall threshold curves based on average and peak rainfall intensities [16]. Despite these advancements, empirical rainfall thresholds remain susceptible to the limitations of historical data and regional specificity, which often necessitate recalibration of the I-D threshold models using local rainfall and landslide occurrences [10,17].…”

Empirical Approach Based Rainfall Threshold Estimation for Landslide Occurrence in Cox's Bazar District, Bangladesh

“…We had to count the amount of continuous rain that started before the landslide event day, as the exact time of the incident is unknown. The gap between two consecutive rainfall events is identified by the 24-hour rainfall gap (Maturidi et al, 2021). Mean intensity was derived by dividing the total amount of rain cumulated rainfall (E) by the duration of the rainfall event (D).…”

“…Guzzetti et al, 2007). Some authors, like Maturidi et al (2021) and Chen et al (2015), identified a lower slope value for a regional threshold. We discovered that among these thresholds, the Garhwal Himalayan range required only 21 mm of rainfall over 24 hours to start a landslide, indicating that the area's high elevation makes it susceptible even in the context of a small amount of rainfall.…”

Perceived Usefulness of Airborne LiDAR Technology in Road Design and Management: A Review

“…As such, an efficient road transportation system is a requirement in low-landed areas, in which flood is likely to occur. At the same time, roads in mountainous areas and on steep slopes may possibly collapse during heavy rains [98]. Therefore, airborne LiDAR technology becomes an essential tool to predict and control road safety in such areas.…”