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GIS-Based Flood Susceptibility Mapping Using Weighted Overlay Method in Barabai Sub-District, South Kalimantan, Indonesia

JURNAL GEOCELEBES · Vol. 10 No. 2 (2026) · pp. 217–240

DOI
10.70561/geocelebes.v10i2.50269
ISSN
2579-5546, 2579-5821
Published
2026-10-01
Publisher
Departemen Geofisika, FMIPA - Universitas Hasanuddin, Makassar
Language
en
License
creativecommons.org/licenses/by-nc-sa/4.0

Abstract

Flooding is a major hydrometeorological hazard in Indonesia. This study assesses flood susceptibility in Barabai Sub-District, Hulu Sungai Tengah Regency, South Kalimantan, using a GIS-based weighted overlay approach. Six flood-conditioning factors were integrated in the analysis, namely slope, elevation, soil texture, rainfall, land use/land cover (LULC), and distance from river networks. The analysis used multi-source geospatial data, including a 30 m SRTM DEM, CHIRPS rainfall (2021–2025), FAO DSMW soil data, ESRI Sentinel-2 LULC data, administrative boundaries, and satellite imagery. The results show that flood susceptibility in Barabai Sub-District is dominated by high and very high classes. High-susceptibility areas cover 26.66 km², equivalent to 70.44% of the study area, whereas very high-susceptibility areas occupy 9.18 km², or 24.25%. In contrast, low and very low susceptibility zones account for only 1.78 km² (4.70%) and 0.23 km² (0.61%), respectively. Overall, 94.69% of the study area falls within the high to very high susceptibility classes. Land cover analysis indicates notable changes between 2021 and 2025, including a reduction in cropland and the emergence of a water body associated with a government-built reservoir for flood mitigation. The spatial pattern of flood susceptibility is mainly controlled by low elevation, proximity to river channels, fine- to medium-textured soils, intensive agricultural and built-up land use, and the dominance of Quaternary alluvial deposits, while high annual rainfall acts as the primary triggering factor. These findings support flood mitigation and land-use planning, while future studies should incorporate field validation and hydrological modeling.

Keywords

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Ilham DaniAffiliation unknown2

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Metadata source: OAI-PMH (metadata jurnal) https://journal.unhas.ac.id/index.php/geocelebes/oai, first harvested 3 Nov 2026, last seen 3 Nov 2026.
Original metadata (oai_dc)
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	<dc:title xml:lang="en">GIS-Based Flood Susceptibility Mapping Using Weighted Overlay Method in Barabai Sub-District, South Kalimantan, Indonesia</dc:title>
	<dc:creator xml:lang="en">Erfani, Sandri</dc:creator>
	<dc:creator xml:lang="en">Nailatussa'adah</dc:creator>
	<dc:creator xml:lang="en">Ma’rifah, Rosna Amaliaatul</dc:creator>
	<dc:creator xml:lang="en">Putra, M. Rayya Andisa</dc:creator>
	<dc:creator xml:lang="en">Andika, Eka</dc:creator>
	<dc:creator xml:lang="en">Kurniawan, Andri</dc:creator>
	<dc:subject xml:lang="en">Barabai</dc:subject>
	<dc:subject xml:lang="en">Geographic Information System</dc:subject>
	<dc:subject xml:lang="en">Hydrometeorological Hazard</dc:subject>
	<dc:subject xml:lang="en">Land-Cover Dynamics</dc:subject>
	<dc:subject xml:lang="en">Multi-Criteria Spatial Analysis</dc:subject>
	<dc:subject xml:lang="en">Thematic Mapping</dc:subject>
	<dc:description xml:lang="en">Flooding is a major hydrometeorological hazard in Indonesia. This study assesses flood susceptibility in Barabai Sub-District, Hulu Sungai Tengah Regency, South Kalimantan, using a GIS-based weighted overlay approach. Six flood-conditioning factors were integrated in the analysis, namely slope, elevation, soil texture, rainfall, land use/land cover (LULC), and distance from river networks. The analysis used multi-source geospatial data, including a 30 m SRTM DEM, CHIRPS rainfall (2021–2025), FAO DSMW soil data, ESRI Sentinel-2 LULC data, administrative boundaries, and satellite imagery. The results show that flood susceptibility in Barabai Sub-District is dominated by high and very high classes. High-susceptibility areas cover 26.66 km², equivalent to 70.44% of the study area, whereas very high-susceptibility areas occupy 9.18 km², or 24.25%. In contrast, low and very low susceptibility zones account for only 1.78 km² (4.70%) and 0.23 km² (0.61%), respectively. Overall, 94.69% of the study area falls within the high to very high susceptibility classes. Land cover analysis indicates notable changes between 2021 and 2025, including a reduction in cropland and the emergence of a water body associated with a government-built reservoir for flood mitigation. The spatial pattern of flood susceptibility is mainly controlled by low elevation, proximity to river channels, fine- to medium-textured soils, intensive agricultural and built-up land use, and the dominance of Quaternary alluvial deposits, while high annual rainfall acts as the primary triggering factor. These findings support flood mitigation and land-use planning, while future studies should incorporate field validation and hydrological modeling.</dc:description>
	<dc:publisher xml:lang="en">Departemen Geofisika, FMIPA - Universitas Hasanuddin, Makassar</dc:publisher>
	<dc:date>2026-10-01</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:type xml:lang="en">Peer-reviewed Article</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://journal.unhas.ac.id/index.php/geocelebes/article/view/50269</dc:identifier>
	<dc:identifier>10.70561/geocelebes.v10i2.50269</dc:identifier>
	<dc:source xml:lang="en">JURNAL GEOCELEBES; Vol. 10 No. 2: October 2026; 217–240</dc:source>
	<dc:source>2579-5546</dc:source>
	<dc:source>2579-5821</dc:source>
	<dc:language>en</dc:language>
	<dc:relation>https://journal.unhas.ac.id/index.php/geocelebes/article/view/50269/15071</dc:relation>
	<dc:rights xml:lang="en">Copyright (c) 2026 JURNAL GEOCELEBES</dc:rights>
	<dc:rights xml:lang="en">https://creativecommons.org/licenses/by-nc-sa/4.0</dc:rights>
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