GIS-Based Flood Susceptibility Mapping Using Weighted Overlay Method in Barabai Sub-District, South Kalimantan, Indonesia
DOI:
https://doi.org/10.70561/geocelebes.v10i2.50269Keywords:
Barabai, Geographic Information System, Hydrometeorological Hazard, Land-Cover Dynamics, Multi-Criteria Spatial Analysis, Thematic MappingAbstract
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.
References
Aji, S. S., Utami, A. N., & Putri, D. H. (2025). Dampak Eksternalitas Negatif Akibat Bencana Alam Banjir Terhadap Masyarakat. Jurnal Sosial Humaniora, 16(2), 128–139. https://doi.org/10.30997/jsh.v16i2.19606
Amatebelle, C. E., Owolabi, S. T., Ogundeji, A. A., & Okolie, C. C. (2025). A systematic analysis of remote sensing and geographic information system applications for flood disaster risk management. Journal of Spatial Science, 70(3), 441–467. https://doi.org/10.1080/14498596.2025.2476973
Antara Kalsel. (2022). Masyarakat HST harapkan segera selesai kolam pengendalian banjir. AntaraNews. https://kalsel.antaranews.com/berita/336977/masyarakat-hst-harapkan-segera-selesai-kolam-pengendalian-banjir
Antara Kalsel. (2026). Banjir rendam ribuan rumah warga di HST, tiga kecamatan terdampak. AntaraNews. https://kalsel.antaranews.com/berita/519547/banjir-rendam-ribuan-rumah-warga-di-hst-tiga-kecamatan-terdampak
Badan Pusat Statistik Kabupaten Hulu Sungai Tengah. (2024). Kecamatan Barabai dalam Angka 2024. BPS Kabupaten Hulu Sungai Tengah. https://hulusungaitengahkab.bps.go.id/id/publication/2024/09/26/b6b6ce1d4288e254716d1ed3/kecamatan-barabai-dalam-angka-2024.html
Briantama, R. H., Suhartanto, E., & Sajali, M. A. (2024). Analisis Hidrologi dan Hidrolika Sungai Untuk Pemodelan Banjir Sebagai Upaya Mitigasi Bencana Pada Sungai Kali Surabaya. Jurnal Teknologi dan Rekayasa Sumber Daya Air, 4(1), 969–981. https://doi.org/10.21776/ub.jtresda.2024.004.01.082
detikNews. (2021). 6 Kabupaten di Kalsel Banjir, Hulu Sungai Tengah Terdampak Paling Parah. https://news.detik.com/berita/d-5831272/6-kabupaten-di-kalsel-banjir-hulu-sungai-tengah-terdampak-paling-parah
Dhungana, B., & Liu, W. (2024). Urban–Rural Exposure to Flood Hazard and Social Vulnerability in the Conterminous United States. ISPRS International Journal of Geo-Information, 13(9), 339. https://doi.org/10.3390/ijgi13090339
Diriba, D., Takele, T., Karuppannan, S., & Husein, M. (2024). Flood hazard analysis and risk assessment using remote sensing, GIS, and AHP techniques: a case study of the Gidabo Watershed, main Ethiopian Rift, Ethiopia. Geomatics, Natural Hazards and Risk, 15(1), 2361813. https://doi.org/10.1080/19475705.2024.2361813
Efraimidou, E., & Spiliotis, M. (2024). A GIS-Based Flood Risk Assessment Using the Decision-Making Trial and Evaluation Laboratory Approach at a Regional Scale. Environmental Processes, 11(1), 9. https://doi.org/10.1007/s40710-024-00683-w
ESRI. (2024). Data classification methods. https://doc.esri.com/en/arcgis-pro/latest/help/mapping/layer-properties/data-classification-methods.html
Fauzi, R. Al. (2022). Analisis tingkat kerawanan banjir Kota Bogor menggunakan metode overlay dan scoring berbasis sistem informasi geografis. Geomedia Majalah Ilmiah Dan Informasi Kegeografian, 20(2), 96–107. https://doi.org/10.21831/gm.v20i2.48017
Gasmi, F., & Aly, M. H. (2026). A Comprehensive Systematic Review of Contemporary Geospatial Approaches to Flood Hazard and Risk Assessment. Urban Science, 10(5), 271. https://doi.org/10.3390/urbansci10050271
Gultom, N., Badaruddin, B., & Kadir, S. (2022). Analisis Debit Air di Daerah Tangkapan Air (DTA) Barabai Kabupaten Hulu Sungai Tengah. Jurnal Sylva Scienteae, 5(5), 711–717. https://doi.org/10.20527/jss.v5i5.6693
Fatmala, I. K., Pratiwi, C. I. B., Setiyono, K. A., Merlina, M., Dewantara, E. J., Fauziyyah, L., Rais, M. L., & Hizbaron, D. R. (2023). Analisis Jasa Ekosistem Pencegahan dan Penanggulangan Bencana Banjir di DAS Blukar Kabupaten Kendal. Jurnal Ilmu Lingkungan, 21(4), 965–973. https://doi.org/10.14710/jil.21.4.965-973
Handayani, W., Chigbu, U. E., Rudiarto, I., & Putri, I. H. S. (2020). Urbanization and Increasing Flood Risk in the Northern Coast of Central Java—Indonesia: An Assessment towards Better Land Use Policy and Flood Management. Land, 9(10), 343. https://doi.org/10.3390/land9100343
Hanie, M. Z., Tarigan, A. P. M., & Khair, H. (2017). Analisis Mitigasi Banjir di Daerah Aliran Sungai Babura Berbasis Sistem Informasi Geografis (SIG). Jurnal Dampak, 14(1), 23–32. https://doi.org/10.25077/dampak.14.1.23-32.2017
Helmi, H., Basri, H., Sufardi, S., & Helmi, H. (2019). Flood vulnerability level analysis as a hydrological disaster mitigation effort in Krueng Jreue Sub-Watershed, Aceh Besar, Indonesia. Jàmbá Journal of Disaster Risk Studies, 11(1), a737. https://doi.org/10.4102/jamba.v11i1.737
Heryanto, R., & Sanyoto, P. (1994). Peta Geologi Lembar Amuntai, Kalimantan. Pusat Penelitian dan Pengembangan Geologi. https://geologi.esdm.go.id/geomap/pages/preview/peta-geologi-lembar-amuntai-kalimantan
Indrasari, M., & Rudiarto, I. (2020). Kemampuan Kebertahanan Masyarakat pada Permukiman Rawan Banjir di Kecamatan Barabai, Kabupaten Hulu Sungai Tengah. Jurnal Wilayah dan Lingkungan, 8(2), 116–129. https://doi.org/10.14710/jwl.8.2.116-129
Irmawati, V., Cahyono, O., Mujiyo, M., Maro’ah, S., Istiqomah, N. M., & Romadhon, M. R. (2023). Flood Susceptibility Index Analysis Using Overlay Method and GIS-based. JST (Jurnal Sains dan Teknologi), 12(2), 553–561. https://doi.org/10.23887/jstundiksha.v12i2.52737
Izzati, H., & Rustandi, I. (2025). Normalisasi Lanskap Koridor Sungai Mati Citarum Dengan Analisis Hidrologi (Studi Kasus: Desa Rancamanyar, Kabupaten Bandung). Jurnal Teknik Sipil dan Arsitektur, 30(1), 32–41. https://doi.org/10.36728/jtsa.v30i1.4153
Khan, T. U., Nabi, G., Ullah, S., Akbar, A., Omifolaji, J. K., Achakzai, J. K., & Iqbal, A. (2025). Mapping flood resilience: a comprehensive geospatial insight into regional vulnerabilities. Frontiers in Water, 7, 1465505. https://doi.org/10.3389/frwa.2025.1465505
Latue, P. C., Septory, J. S. I., Somae, G., & Rakuasa, H. (2023). Pemodelan Daerah Rawan Banjir di Kecamatan Sirimau Menggunakan Metode Multi-Criteria Analysis (MCA). Jurnal Perencanaan Wilayah dan Kota, 18(1), 10–17. https://doi.org/10.29313/jpwk.v18i1.1964
Meng, M., Dąbrowski, M., Xiong, L., & Stead, D. (2022). Spatial planning in the face of flood risk: Between inertia and transition. Cities, 126, 103702. https://doi.org/10.1016/j.cities.2022.103702
Mondal, S., & Patel, P. P. (2018). Examining the utility of river restoration approaches for flood mitigation and channel stability enhancement: a recent review. Environmental Earth Sciences, 77(5), 195. https://doi.org/10.1007/s12665-018-7381-y
Nkeki, F. N., Bello, E. I., & Agbaje, I. G. (2023). Is the existing methods sustainable? A hybrid approach to flood risk mapping. MethodsX, 11, 102348. https://doi.org/10.1016/j.mex.2023.102348
Pandey, M., Arora, A., Arabameri, A., Costache, R., Kumar, N., Mishra, V. N., Nguyen, H., Mishra, J., Siddiqui, M. A., Ray, Y., Soni, S., & Shukla, U. (2021). Flood Susceptibility Modeling in a Subtropical Humid Low-Relief Alluvial Plain Environment: Application of Novel Ensemble Machine Learning Approach. Frontiers in Earth Science, 9, 659296. https://doi.org/10.3389/feart.2021.659296
Poros Kalimantan. (2021). Awal 2021, Banjir Terparah Sepanjang Sejarah di HST. Poros Kalimantan. https://poroskalimantan.com/awal-2021-banjir-terparah-sepanjang-sejarah-di-hst/
Prabowo, E. (2018). Studi Pengendalian Banjir di Kota Barabai terkait Rencana Pembangunan Bendungan Pancur Hanau di Sungai Barabai Kabupaten Hulu Sungai Tengah. Jurnal Teknologi Berkelanjutan, 7(01), 43–51. https://doi.org/10.20527/jtb.v7i01.114
Putri, A. S. R., & Triyatno, T. (2025). Analisis Bahaya Banjir Beserta Dampaknya pada Hulu Das Batang Sumpur di Kecamatan Lubuk Sikaping Kabupaten Pasaman. Jurnal Hutan Tropis, 13(4), 488–499. https://doi.org/10.20527/jht.v13i4.24632
Ramadhan, R., Hanif, M., Marzuki, M., Hashiguchi, H., Harjupa, W., & Yusnaini, H. (2026). Spatio-temporal variability of hydrometeorological disasters in Indonesia based on national disaster risk management data. International Journal of Disaster Risk Reduction, 143, 106256. https://doi.org/10.1016/j.ijdrr.2026.106256
Rentschler, J., Salhab, M., & Jafino, B. A. (2022). Flood exposure and poverty in 188 countries. Nature Communications, 13(1), 3527. https://doi.org/10.1038/s41467-022-30727-4
Rizani, M. A., Setiawan, K. P., Sa’dianoor, S., Jarmani, A., Ramadaniar, H. R., Abida, M. R., & Mahasina, D. A. (2023). Analisa Perubahan Tata Guna Lahan Terhadap Ketinggian Banjir di Kota Barabai. Sebatik, 27(2), 480–490. https://doi.org/10.46984/sebatik.v27i2.2173
Sapoetra, R., Mustofa, U., Pratomo, R. A., & Hidayat, A. (2024). Arahan Mitigasi Bencana Banjir Pada Kecamatan Balikpapan Timur. COMPACT: Spatial Development Journal, 3(1), 167–173. https://doi.org/10.35718/compact.v3i1.1146
Septian, A., Elvarani, A. Y., Putri, A. S., Maulia, I., Damayanti, L., Pahlevi, M. Z., & Aswad, F. H. (2020). Identifikasi Zona Potensi Banjir Berbasis Sistem Informasi Geografis Menggunakan Metode Overlay dengan Scoring di Kabupaten Agam, Sumatera Barat. Jurnal Geosains dan Remote Sensing, 1(1), 11–22. https://doi.org/10.23960/jgrs.2020.v1i1.25
Sihaini, E., Supriyono, S., Yunita, M., Alfi, M., & Guntar, D. (2026). Analisis Spasial Tingkat Kerentanan Banjir di Kabupaten Kampar, Provinsi Riau Berdasarkan Sistem Informasi Geografis (SIG). Dinamika Sosial: Jurnal Pendidikan Ilmu Pengetahuan Sosial, 5(1), 69–85. https://doi.org/10.18860/dsjpips.v5i1.24940
Sulaeman, A., Suhartanto, E., & Sumiadi, S. (2017). Analisis Genangan Banjir Akibat Luapan Bengawan Solo untuk Mendukung Peta Risiko Bencana Banjir di Kabupaten Bojonegoro. Jurnal Teknik Pengairan, 8(2), 146–157. https://doi.org/10.21776/ub.pengairan.2017.008.02.1
Utama, F. P., Setiawan, Y., Vatresia, A., & Sari, J. P. (2021). Flood Vulnerability Analysis using Weighted Overlay. IT Journal Research and Development, 6(2), 70–82. https://doi.org/10.25299/itjrd.2022.6193
Vio, D., de Souza, J. O. P., Motta, G. H. M. B., & de Souza, L. C. (2025). Machine learning on alluvial deposit Identification in dryland area. Revista Contexto Geográfico, 10(24), 138–182. https://doi.org/10.28998/contegeo.10i.24.18434
Witts, D., Hall, R., Nichols, G., & Morley, R. (2012). A new depositional and provenance model for the Tanjung Formation, Barito Basin, SE Kalimantan, Indonesia. Journal of Asian Earth Sciences, 56, 77–104. https://doi.org/10.1016/j.jseaes.2012.04.022
Zhou, Q., Su, J., Arnbjerg-Nielsen, K., Ren, Y., Luo, J., Ye, Z., & Feng, J. (2021). A GIS-Based Hydrological Modeling Approach for Rapid Urban Flood Hazard Assessment. Water, 13(11), 1483. https://doi.org/10.3390/w13111483
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