Landslide hazard of 2017 in Rangamati district had devastating impacts on development, thereby making landslide susceptibility mapping a prerequisite for disaster risk management. This study aims to map the future landslide susceptible areas by overlaying the landslide inventory of 2017 with causative factor maps using WoE and MFR and compare their results to determine that statistical model describes the susceptibility of the landslide occurrence better than the other. The analysis shows that although both models define the spatial relationship of past landslides with the triggering factors in a same way but in case of mapping, MFR had overestimated the high and low susceptible areas and underestimated the moderate susceptible areas than WoE. When validated from success rate curve by plotting the percentage of landslide susceptibility index rank against the percentage of cumulative landslide occurrence, it shows that the WoE model describes the landslides better than the MFR model. About 20% of the high susceptible areas include 85% of the total landslide area in case of the WoE model but the MFR model includes only 20%. On the other hand, the WoE model describes that 30% highly susceptible area covers more than 99% of the total landslide area while MFR defines only 78%.

Liquefaction can intensify the destruction caused by an earthquake; thus, a region with high liquefaction potential could be more disastrous. Bangladesh is surrounded by the Indo-Burma Folded Belt in the east, the Dauki Fault and Himalayan Syntaxis in the north that are known to have occurred high magnitude earthquakes (e.g., M w > 7) in the past. Therefore, assessing seismic hazards in the regions that are economically growing fast is of great interest. Among many other hazard assessment parameters, soil liquefaction potential index (LPI) can be used to assess seismic hazards. In this study, we have assessed the seismic hazard potential for a small town (Moulvibazar) in the northeast Bangladesh documenting liquefaction potential indices for different surface geological units using an earthquake of moment magnitude M w 8 having a peak horizontal ground acceleration (PGA) of 0.36 g. Twenty-five standard penetration test (SPT) boreholes were completed within the study area to obtain SPT-N values for two surface geological units: (1) Holo-Pleistocene low elevated terrace deposits (Zone 1) and (2) Holocene flood plain deposits (Zone 2). Using the SPT-N values, the LPI values have been calculated for the soil profile of each borehole. The LPI values in the town vary from 0 to 42.33, whereas values from 1.42 to 7.52 are in Zone 1 and values from 0 to 42.34 are in Zone 2. It has been predicted that 42% and 78% areas of Zone 1 and Zone 2, respectively, might exhibit surface manifestation of liquefaction. The results of this study can be used for seismic risk management of Moulvibazar town.

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Rainfall threshold estimation empirically to forecast rainfall-induced landslide events provides crucial information to reduce landslide impact. The landslide events triggered by rainfall are common in Cox's Bazar district, especially during the monsoon season. Geological settings and climatic conditions make this area more landslide-prone leading to huge losses of lives and property. Establishing an effective early warning system based on a rainfall threshold value has become a top priority to save people's lives, the economy, and the environment. We have employed three empirical approaches to estimate rainfall thresholds. Intensity-Duration, Event-Duration, and Antecedent Rainfall thresholds are the most conventional rainfall methods to identify the lowest amount of rainfall that triggers landslide. The Intensity-Duration (ID) and Event-Duration (ED) rainfall threshold equations are calculated using a simple power-law curve. For 5% exceedance probability level ID defined as: T5: I = 3.63 D-0.1313 & ED as T5: E = 3.63 D0.8687. Similarly, for 1% exceedance probability level ID defined as: T1: I= 2.78 D-0.1313 & T1: E = 2.78 D0.8687 for ED. Both 1% and 5% rainfall threshold equations are the minimum rainfall threshold equations. Since the 5% exceedance probability threshold line delineates the lower end of all the observed data points for landslide events, it is considered the minimum threshold line for Cox's Bazar. According to the 5% exceedance probability level threshold equation, mean intensity of 2.39 mmh-1 or 57.4 mm cumulated rainfall in 24 hours is required to initiate a landslide event. Whereas, for longer duration events such as 120h, rainfall intensity of 1.93 mmh-1 or continuous rainfall of 232 mm appears to be sufficient in landslide initiation. There is a less than 5% chance of a landslide below this threshold limit. In the context of 3-day and 5-day antecedent rainfall thresholds, we found that a minimum of 130 mm in 72 h (3-day) and 210 mm in 120 h (5-day) could initiate a landslide event. We have compared our thresholds with a few global and local rainfall threshold estimates. The Dhaka University Journal of Earth and Environmental Sciences, Vol. 11(1), 2022: 81-94

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