Estimation of rainfall threshold and its use in landslide hazard mapping of Kuala Lumpur metropolitan and surrounding areas

Abstract

This paper presents rainfall-induced landslide thresholds and predicts landslide hazard in Kuala Lumpur metropolitan city and surrounding areas. Landslide events from 2000 to 2012 were collected. The long and short antecedent rainfall days were prepared for landslide and non-landslide days simultaneously. First, threshold analysis was conducted by using data obtained from rainfall stations located in highly urbanized areas of Kuala Lumpur metropolis. Six rainfall gauges were selected, and the study area was divided into six zones according to rainfall gauges: Taman Desa Station (TD-KL), Genting Klang (GK-KL), LDG Edinburgh Station (LDGE-KL), SG Raya Hulu Langat Station (SRHL-Slg), Puchong Drop Station (PD-Slg), and Bukit Antarabangsa (BTA-Slg). After the threshold analysis was conducted for different periods (10, 15, and 30days) in each station, reliability index test was conducted to optimize the best threshold that limits the predicted events along the study period for each region. Second, the threshold analysis results were used as input in the Poisson probability model to estimate landslide temporal probability (P T ). Third, the spatial probability (P S ) analysis was prepared by using the evidential belief function multiplied by the P T to obtain the hazard maps for 1-, 3-, and 5-year scenarios. Finally, a validation process was conducted to test the prediction performance of the resultant hazard map for a 1-and 2-year prediction by using the landslide inventory of 2012 to early 2014, which was not included in the modeling of the hazard map. Results showed a valid correlation between the high and moderate hazardous areas for the six zones. The predicted hazard maps indicated a quantitative assessment of the prone areas and proved to be a valid disaster management tool. The produced hazard maps may play a vital role as input component in risk analysis.

Establishing rainfall frequency contour lines as thresholds for rainfall-induced landslides in Tegucigalpa, Honduras, 1980–2005

“…Thresholds are then constructed with lower rainfall demands to account for these landslides and because many other rainfall events that exceed the threshold do not trigger landslides, the predictive performance of the threshold is reduced. This may explain why in one of the zones in Kuala Lumpur, which was affected by several landslides with a major contribution from human activities despite being well protected against naturally occurring landslides, the predictive performance of its threshold was lower than the rest of the analyzed zones (Althuwaynee et al 2014). Third, many urban areas like Tegucigalpa are built upon active, slowly moving landslides or landslide deposits (Antronico et al 2013;Cascini et al 2005), given that these areas have more gentle slopes that are ideal for the development of unplanned infrastructure where flat, stable land is scarce (Cascini et al 2005).…”

“…Although the rainfall event immediately before a landslide is usually considered as the triggering rainfall, some research teams have found better results when the 3-day cumulative rainfall prior to the landslide is regarded as the triggering event (Althuwaynee et al 2014;Chleborad et al 2006;Zezêre et al 2015). Most researchers have considered convenient to evaluate different antecedent rainfall durations that usually range from 1 to 30 days.…”

“…In the last decade, various researchers have constructed daily versus antecedent rainfall plots to assess the temporal aspect of landslide occurrence (Bai et al 2014;Jaiswal and van Westen 2009) and the coupling with the spatial aspect for the elaboration of hazard maps Nat Hazards (Bui et al 2013;Althuwaynee et al 2014) and risk maps (Erener and Duzgun 2013). As given in Table 1, a common practice is to evaluate several techniques for the same study area in order to determine which one yields the best predictive performance (Chleborad et al 2006;Dahal and Hasegawa 2008;Kanungo and Sharma 2014;Zezêre et al 2015).…”

“…The ideal antecedent duration for the study area is usually selected based on the plot whose threshold line yields the best discriminative power between days with and without landslides. For such purpose, diagonal dividers that assign equal weights of importance to the daily and antecedent rainfall (Dahal and Hasegawa 2008;Kanungo and Sharma 2014) and envelope lines that connect the lowest points in the plots (Althuwaynee et al 2014;Bui et al 2013;Chleborad et al 2006;Jaiswal and van Westen 2009) are frequently used. However, these techniques may not produce reliable thresholds in study areas with a high incidence of urban landslides like Tegucigalpa, where the disturbances of mankind significantly alter the relationship between rainfall and slope failures that is easier to recognize in unpopulated slopes (Garcia-Urquia and Axelsson 2015).…”

Rainfall threshold calculation for debris flow early warning in areas with scarcity of data

“…In addition, some researchers have highlighted the importance of finding more robust hydrological bases to empirical rainfall thresholds for landslide initiation (Bogaard and Greco, 2018;Canli et al, 2017;Segoni et al, 2018). When data are scarce, a robust validation of a threshold model can be based on a quantitative comparison with alternate versions of the threshold (Althuwaynee et al, 2015) or with thresholds calculated with completely different approaches (Frattini et al, 2009;Lagomarsino et al, 2015). Wei et al (2017) investigated a rainfall threshold method for predicting the initiation of channelized debris flows in a small catchment, using field measurements of rainfall and runoff data.…”