Abstract
In the central Nepal Himalaya, landslides form the major natural hazards annually resulting in many casualties and damage. Structural as well as non-structural measures are in place to minimize the risk of landslide hazard. To reduce the landslide risk, a Landslide Early Warning System (LEWS) as a non-structural measure has been piloted at Sundrawati village (Kalinchowk rural municipality, Dolakha district) to identify its effectiveness. Intensive discussions with stakeholders, aided by landslide susceptibility map, resulted in a better understanding of surface dynamics and the relationship between rainfall and surface movement. This led to the development of a LEWS comprised of extensometers, soil moisture sensors, rain gauge stations, and solar panels as an energy source that blows siren receiving signals via a micro-controller and interfacing circuit. The data generated through the system is transmitted via a Global System for Mobile Communications (GSM) network to responsible organizations in real-time to circulate the warning to local residents. This LEWS is user-friendly and can be easily operated by a community. The successful pilot early warning system has saved 495 people from 117 households in August 2018. However, landslide monitoring and dissemination of warning information remains a complex process where technical and communications skill should work closely together.
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Acknowledgment
We would like to acknowledge Government of Nepal, Ministry of Forests and Environment (MoFE)/DoFSC and Food and Agricultural Organizations of the United Nations (FAO) for overall support to conduct this study. The authors thanks to the then District Soil Conservation Office (DSCO), Dolakha, FAO field staffs and community of Sundrawati for their unconditional support during field work and grateful to staffs of SMART Nepal for timely installation of the LEWS in the Mehele landslide of Sundrawati village, Kalinchowk rural municipality, Dolakha.
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Thapa, P.S., Adhikari, B.R. Development of community-based landslide early warning system in the earthquake-affected areas of Nepal Himalaya. J. Mt. Sci. 16, 2701–2713 (2019). https://doi.org/10.1007/s11629-019-5586-5
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DOI: https://doi.org/10.1007/s11629-019-5586-5