Methodologies for Risk Assessment of Landslides Induced by Rainfall and Earthquake

Abstract

Landslide is one of the greatest natural catastrophes and poses a major threat to lives and property worldwide. As development expands into unstable hill areas under the pressure of increasing population and urbanisation, the risk of landslide has been growing all over the world during the last decades. The present work aims at risk analysis of landslides in an effort to reduce the socio-economic impact of landslides and to mitigate the landslide risk effectively. The risk analysis of landslides is neither simple nor straightforward as the effects of different triggering factors have to be analyzed individually and managed separately. In this view, landslide risk analysis requires a detailed understanding of the physical process of landslides and the development of different methodologies to relate landslide occurrences with the characteristics of triggering factors. Rainfall and earthquakes are considered as the most common triggering factors for landslides. Due to the contrast in the characteristics of rainfall and earthquake loads, and their subsequent effects on the landslide movements, the evaluation of landslide risk by a single methodology becomes difficult, if not impossible. The present study introduces methods for risk analysis of landslides due to rainfall as well as earthquake events. These methods recognize the conditions that caused the slope to become unstable and the processes that triggered the landslide movement. Often landslides occur due to the combination of rainfall and earthquake events as the probability of concurrent rainfall and earthquake event in any area is not rare. Consequently, it is essential to evaluate the landslide risk by considering the unfortunate combination of independent events such as rainfalls and earthquakes, and the effects of their mutual interactions on landslide movements. Therefore, for regions prone to both earthquake and heavy rainfall events, risk analysis should take into consideration multiple processes rather than one single event to avoid underestimation...