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April 30, 20260 citations

Evaluation of the accuracy level of landslide vulnerability maps for various rainfall models

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MRMuhamad Taopiq RizkiSSutoyoHPHeriansyah Putra

Key Points

  • This study aims to evaluate the accuracy of landslide hazard maps across different rainfall models.
  • Evaluated landslide hazard maps using daily, decadal, monthly, and annual rainfall models.
  • Validated landslide occurrence points using the DVMBG 2004 method.
  • Analyzed the area classified by each rainfall model for landslide vulnerability.
  • Maximum rainfall model classified a hazard area of 12,055.3 ha.
  • Average rainfall model classified a less vulnerable area of 9,253.45 ha.
  • Achieved an overall accuracy of 45.5% for landslide vulnerability maps.

Abstract

The Regional Disaster Management Agency (BPBD) and Communication and Information Agency (Diskominfo) of Garut Regency recorded seven landslide events in 2020 and nine in 2023 in the Banjarwangi District. These events were triggered by steep to very steep slopes with landslide-prone soil and rock types, and heavy rainfall. This study aimed to evaluate the accuracy of landslide hazard maps for various rainfall models, including daily, decadal, monthly, and annual rainfall, validated landslide occurrence points with the DVMBG 2004 method. The evaluation results showed that the maximum rainfall model had a hazard classification of 12,055.3 ha. The average rainfall model showed a less vulnerable classification, covering an area of 9,253.45 ha. Rainfall levels affect the classification of vulnerability, thereby impacting the accuracy. The results of evaluating the accuracy of landslide vulnerable suitability for various rainfall models showed a low accuracy of 45.5%. Therefore, further analysis is required to improve the accuracy of landslide vulnerability maps.

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Cite This Study

Rizki et al. (2026) studied this question.

synapsesocial.com/papers/69f2f1be1e5f7920c63875echttps://doi.org/10.1051/bioconf/202623402002/pdf
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