Impact-based Early Warning System for Debris flow in Malaysia: A Science-based and Localization Approach for Strengthening Disaster Resilience

Malaysia is committed to accelerate the achievement of UN Sendai Framework for Disaster Risk Reduction 2015-2030, and support a newly launched agenda, “The Early Warning for All initiative, 2023-2027”. While investing into landslide risk reduction strategies through the National Slope Master Plan 2009-2023, landslides remained the major contributor to the highest number of human losses in Malaysia, and even so with new, emerging risk and compounding disaster as a result of local climate change impact. So far, landslide and debris flow occurred more than 25 times with 442 casualties in the last three decade. Amongst are the geological disaster debris flow in Jerai Geopark (Yan, Kedah) recorded on 18 August 2021 resulted in six fatalities, with more than RM75 million direct economic losses reported, and indirect cascading impact to local socio-economic activity and food security system. This study advances the people-center, end-to-end early warning system for debris flow in the tourism-dominated region in Kedah. It is worth mentioning that this Japanese-designated EWS is the first-ever system locally built in Malaysia, which was co-designed, co-developed and co-implemented driven by the local communities and multi-stakeholders in a tropical environment. Several unmanned assisted vehicles-based LiDAR missions were jointly conducted to quantitatively understand the possible remaining systemic risk for future debris flow in the upstream of the study area located in the vicinity of the Mount of Jerai. A complete system consists of wire-cable detection, vibration sensor, and siren system coupling with historical inventory analysis, hazard mapping, exposure assessment and systemic risk evaluation. The EWS development was carried out across sector, and carefully installed based on the detailed geological survey, geohazard mapping, vulnerability analysis, and risk assessment over several water catchments in the areas. A science-based knowledge coupled with the Local, Traditional, and Indigenous Knowledge (LTIK) was collectively explored and translated into series of Community-led Disaster Risk Reduction (CLDRR), an extended version of traditional Community-based Disaster Risk Management (CBDRM) that widely conducted at various implementation scales. The early warning system was later integrated with the public warning system to expand its dissemination scales and acceptance level. Interestingly, a local landslide risk reduction model was co-developed with several partnership modality (public-private-academia-NGO), namely as YAN DRR Model, to support the build-back-better agenda and rejuvenate the multi-scale eco-tourism and food security industry. An integrated EWS system was tested and demonstrated in the last two- commemoration years. Several innovations for improving local risk communication system are intelligently explored and strategically documented. As a conclusion, the study provides a new insight into locally-led and nationally-supported landslide disaster risk reduction strategy, by empowering an impact-based early warning system for debris flow and landslides, integrating with the innovated LTIK approach and strengthening local champions in the vulnerable regions. Remarkably, this study demonstrates regional benchmarking, national commitment, and local wisdom to reduce the number of human- and economic losses through an impact-based early warning system, led by vulnerable community and powered by humanizing technology for building societal resilience in a changing climate.

Keywords: Landslide Disaster, Debris Flow, Disaster Risk Management, People-centered EWS