Geomorphological analysis and early warning systems for landslide risk mitigation in Nepalese mid-hills

The Nepal Himalayas is one of the world's most active mountain belts and home to widespread natural hazards of various types, including landslides, which claim numerous lives and result in massive property damage in the country. Landslides occur due to the combined effects of seismic activity, monsoon rainfall, and improper land-use practices. The prevention and mitigation of landslides are challenging for countries such as Nepal. However, low-cost techniques such as bioengineering combined with affordable early warning systems have been implemented in recent decades. The Methum landslide in Lalitpur district, central Nepal, was selected as a case study to investigate the landslide geomorphology along with triggering factors and to evaluate the effectiveness of a landslide early warning system (LEWS). Multiple field visits were conducted to learn the patterns of landslide evolution, assess landslide risk, and identify potential triggers. This study analyzed aerial photos, satellite images, and precipitation records. Heavy rainfall and past earthquake events have been major landslide triggers, while sloped terrace farming has acted as a preparatory factor. LEWS, installed, measures rainfall, soil moisture, and displacement activity and generates an alarm to alert nearby inhabitants if any of these parameters exceed the threshold set. This monitoring system is a cost-effective technique and exemplifies the reduction of landslide risk at the community level in the landslide-prone mid-hills of Nepal.

Automated summary

The Nepal Himalayas is prone to landslides, which are caused by seismic activity, monsoon rainfall, and improper land-use practices. Mitigating and preventing landslides is challenging for countries like Nepal, but low-cost techniques like bioengineering combined with affordable early warning systems have been effective. A case study in Lalitpur district analyzed landslide geomorphology, triggering factors, and evaluated the effectiveness of a landslide early warning system (LEWS). The LEWS measures rainfall, soil moisture, and displacement activity to generate alarms for nearby residents, reducing landslide risk at the community level.