Web-Based Landslide Early Warning System using GPM Precipitation Estimates

Malaysia is a country with tropical climates near the equatorial zone that yields higher extensive rainfall each year. This exposes Malaysia to landslide events, as rainfall is one of the major triggers that might cause a landslide. Most of the research showed that rainfall-induced landslide is affected by total rainfall and the initial condition of the slope as well as soil permeability and slope depth. The rainfall infiltration was influencing the development of landslides because it decreases the matric suction, increases the pore water pressure and causes the groundwater table to rise. Despite the rising susceptibility to landslides, landslide early warning systems must be developed to minimize the risk of landslide threat. Thus, the Web-based Landslide Early Warning System is used as a monitoring tool for landslides using Global Precipitation Measurement (GPM) precipitation data estimates to notify if there are any warning signs observed from potential landslides occurrences in Ulu Kelang. From rainfall threshold analysis, the warning level of landslide occurrence is categorized into four levels: low, moderate, high and very high. The daily rainfall is analysed every day as it is Real-time monitoring and continues to update within 24 hours on the website. The development of a Web-based landslide early warning system based on the relationship between rainfall threshold analysis and landslide occurrence that provided warning level and prediction of landslide occurrences based on a dynamic landslide hazard map. In addition, Early Warning System (EWS) also provides a risk situation and raises awareness among the community in the case study at Ulu Kelang, Selangor, Malaysia.

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Publication Details

Journal
Journal of Advanced Research in Applied Sciences and Engineering Technology
Published
2024-12-17
DOI
https://doi.org/10.37934/araset.62.3.151163
Primary Topic
Landslides and related hazards
Type
article
Field-Weighted Citation Impact
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article

Web-Based Landslide Early Warning System using GPM Precipitation Estimates

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Journal of Advanced Research in Applied Sciences and Engineering Technology
Landslides and related hazards
article

Web-Based Landslide Early Warning System using GPM Precipitation Estimates

Nani Fadzlina Naim, Noraisyah Tajudin, Norsuzila Ya’acob, Murizah Kassim, Azita Laily Yusof, Danang Lelono, Nurshazanaliza Basah
article en

Abstract

Malaysia is a country with tropical climates near the equatorial zone that yields higher extensive rainfall each year. This exposes Malaysia to landslide events, as rainfall is one of the major triggers that might cause a landslide. Most of the research showed that rainfall-induced landslide is affected by total rainfall and the initial condition of the slope as well as soil permeability and slope depth. The rainfall infiltration was influencing the development of landslides because it decreases the matric suction, increases the pore water pressure and causes the groundwater table to rise. Despite the rising susceptibility to landslides, landslide early warning systems must be developed to minimize the risk of landslide threat. Thus, the Web-based Landslide Early Warning System is used as a monitoring tool for landslides using Global Precipitation Measurement (GPM) precipitation data estimates to notify if there are any warning signs observed from potential landslides occurrences in Ulu Kelang. From rainfall threshold analysis, the warning level of landslide occurrence is categorized into four levels: low, moderate, high and very high. The daily rainfall is analysed every day as it is Real-time monitoring and continues to update within 24 hours on the website. The development of a Web-based landslide early warning system based on the relationship between rainfall threshold analysis and landslide occurrence that provided warning level and prediction of landslide occurrences based on a dynamic landslide hazard map. In addition, Early Warning System (EWS) also provides a risk situation and raises awareness among the community in the case study at Ulu Kelang, Selangor, Malaysia.

Journal of Advanced Research in Applied Sciences and Engineering TechnologyVol. 62(3)
Universitas Gadjah Mada (ID), Lincoln University College (MY), Universiti Teknologi MARA (MY)
Universiti Teknologi MARA
Openalex Percentile: Top 57%
Landslides and related hazards
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