Soil micromorphology for modeling spatial on landslide susceptibility mapping: a case study in Kelara Subwatershed, Jeneponto Regency of South Sulawesi, Indonesia

Asmita Ahmad (), Meutia Farida, Nirmala Juita and Muh Jayadi
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Asmita Ahmad: Hasanuddin University
Meutia Farida: Hasanuddin University
Nirmala Juita: Hasanuddin University
Muh Jayadi: Hasanuddin University

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2023, vol. 118, issue 2, No 26, 1445-1462

Abstract: Abstract Comprehensively, the results of categorizing the susceptibility levels demonstrate distinct results, where landslides are more common in areas with a relatively high to moderate susceptibility class in comparison with those with a high susceptibility class. For this research, the soil parameter test method was conducted by utilizing a split-plot design with land use as the main plot, slope as a subplot, and soil physics (permeability, bulk density, and porosity) as a sub-subplot with three replications. Spatial modeling through regression analysis by incorporating ordinary least squares. The interaction between the type of land use, slope, and physical properties of the soil on the occurrence of landslides at the study site demonstrates a strong relationship with a significant p-value = 0.043. Increased land use by the community has accelerated the formation of soil micromorphology in the form of plane voids, cross-striated and grano-striated, thereby catalyzing internal shifts (micro-shifts) in the soil body. The landslide susceptibility map at the study site has been categorized into seven spatial susceptibility classes: extremely low, very low, low, moderate, high, very high, and extremely high. Spatial modeling with OLS illustrates that the independent factors in the form of lithology, rainfall, slope, land cover/land use, and population only get an R2 value of 30.8%. Adding landslide independent parameter data in the form of soil organic carbon factor, texture, erodibility, and soil micromorphology produces a spatial model of landslide susceptibility with an increase in the accuracy value of R2 by 66.66%. The spatial model demonstrates a high level of consistency with very significant soil micromorphology at a p-value of

Keywords: Plane voids; Clay; Soil; Micromorphology; Landslide (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s11069-023-06063-1

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