Spatial Analysis of Landslide Dynamics in Muara Enim Regency Based on Rainfall

Yosika Agustina  Billa; Wijaya  Mardiansyah; Netty  Kurniawati

doi:10.37899/journallamultiapp.v7i2.2955

Yosika Agustina Billa Sriwijaya University, Indonesia
Wijaya Mardiansyah Sriwijaya University, Indonesia
Netty Kurniawati Sriwijaya University, Indonesia

DOI: https://doi.org/10.37899/journallamultiapp.v7i2.2955

Keywords: Disaster Risk Management, Geographic Information Systems, Hazard Assessment, Inverse Distance Weighting, Landslide Dynamics, Rainfall Threshold, Remote Sensing, Risk Assessment, Spatial Analysis

Abstract

Muara Enim Regency experiences significant landslide hazards requiring comprehensive understanding of rainfall dynamics and triggering mechanisms. This research investigates the spatial and temporal relationships between rainfall patterns and landslide occurrence using quantitative descriptive analysis with Geographic Information Systems. The study analyzed CHIRPS satellite rainfall data and institutional disaster records spanning 2017 to 2024, encompassing 75 documented landslide events across 96 monthly observations within Muara Enim Regency (7,483 square kilometers). Data analysis employed Inverse Distance Weighting interpolation with power parameter two to generate monthly rainfall surfaces, supplemented by descriptive statistics quantifying annual and monthly precipitation variations. Results revealed annual rainfall fluctuation ranging from 2,267 millimeters (2019) to 3,656 millimeters (2022), with pronounced seasonal patterns showing peaks in December (363 millimeters) and March (350 millimeters), contrasting with dry season minima in August (136 millimeters) and September (154 millimeters). Landslide occurrence clustered prominently during February, March, and November, recording eight to nine documented events respectively, while August and September with minimal rainfall showed zero to one landslide event. Analysis demonstrates strong correlation between rainfall intensity and landslide frequency, substantiating rainfall as a primary triggering mechanism for slope instability in mountainous tropical regions. This research provides foundational empirical evidence supporting subsequent integrated landslide hazard assessment and early warning system development in Muara Enim Regency and comparable Indonesian mountain regions.

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