Flood Risk Mapping Based on Geographic Information System Analysis
DOI:
https://doi.org/10.70716/reswara.v2i2.373Keywords:
flood risk mapping, geographic information system, multi-criteria analysis, analytical hierarchy process, disaster risk reductionAbstract
Flood events are increasing in frequency and severity worldwide due to climate change, rapid urbanization, and land-use transformation. Flood risk mapping has therefore become a critical tool for disaster risk reduction and spatial planning. This study aims to develop and analyze a flood risk mapping framework based on Geographic Information System (GIS) and multi-criteria decision analysis techniques. The research integrates physical, environmental, and socio-economic factors including rainfall intensity, slope, elevation, land use, soil type, drainage density, and population exposure. Analytical Hierarchy Process (AHP) and weighted overlay analysis were applied to derive flood risk indices and spatial risk zoning. The results classify the study area into very low, low, moderate, high, and very high flood risk zones. High-risk zones are primarily located in low-lying floodplains with dense settlements and poor drainage conditions. The findings are consistent with previous studies in Asia, Africa, and Europe, demonstrating the robustness of GIS-based multi-criteria approaches for flood risk assessment. This research contributes to the growing body of evidence that GIS-based flood risk mapping is an effective and scalable tool for supporting disaster mitigation, land-use planning, and policy formulation. The study recommends integrating GIS-based flood risk maps into regional planning frameworks to improve flood preparedness and resilience.
References
Akallouch, A., Al Mashoudi, A., Ziani, M., & et al. (2024). GIS application in urban flood risk analysis: Midar as a case study. Open Journal of Ecology, 14(2). https://doi.org/10.4236/oje.2024.142009
Ariyani, D., Balqis, A. K., Abdaa, D., & et al. (2023). Flood hazard mapping using QGIS spatial analysis in Bangko and Masjid watershed at Riau, Indonesia. Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan, 13(3), 362–371. https://doi.org/10.29244/jpsl.13.3.362-371
Aydin, M. C., & Birincioğlu, E. S. (2022). Flood risk analysis using GIS-based analytical hierarchy process: A case study of Bitlis Province. Applied Water Science, 12, 51. https://doi.org/10.1007/s13201-022-01655-x
Bossa, Y. A., Djangni, O., Yira, Y., & et al. (2024). Flood risk assessment in the lower valley of Ouémé, Benin. Open Journal of Modern Hydrology, 14(2). https://doi.org/10.4236/ojmh.2024.142008
Burayu, D. G., Karuppannan, S., & Shuniye, G. (2023). Identifying flood vulnerable and risk areas using the integration of analytical hierarchy process (AHP), GIS, and remote sensing: A case study of southern Oromia region. Urban Climate, 48, 101640. https://doi.org/10.1016/j.uclim.2023.101640
Cai, S., Fan, J., & Yang, W. (2021). Flooding risk assessment and analysis based on GIS and the TFN-AHP method: A case study of Chongqing, China. Atmosphere, 12(5), 623. https://doi.org/10.3390/atmos12050623
Chakraborty, S., & Biswas, S. (2020). Application of geographic information system and HEC-RAS in flood risk mapping of a catchment. In Advances in Water Resources Engineering (pp. 233–245). Springer. https://doi.org/10.1007/978-981-13-7067-0_17
Das, J. (2023). GIS-based flood risk assessment using multi-criteria decision analysis of Shebelle River Basin in southern Somalia. SN Applied Sciences, 5, 27. https://doi.org/10.1007/s42452-023-05360-5
Gacu, J. G., Monjardin, C. E. F., Senoro, D. B., & et al. (2022). Flood risk assessment using GIS-based analytical hierarchy process in the municipality of Odiongan, Romblon, Philippines. Applied Sciences, 12(19), 9456. https://doi.org/10.3390/app12199456
Ghanem, M. A. A. N., & Zaifoglu, H. (2024). A geospatial analysis of flood risk zones in Cyprus: Insights from statistical and multi-criteria decision analysis methods. Environmental Science and Pollution Research. https://doi.org/10.1007/s11356-024-33391-x
Ibanga, O. A., & Idehen, O. F. (2020). GIS-based climate change induced flood risk mapping in Uhunmwonde local government area, Edo State, Nigeria. International Journal of Environment and Climate Change, 10(9), 225–238. https://doi.org/10.9734/IJECC/2020/V10I930225
Jain, T. (2023). A GIS-based flood risk assessment and mapping using morphometric analysis in the Kayadhu River Basin, Maharashtra. In Advances in Geographical and Environmental Sciences. Springer. https://doi.org/10.1007/978-981-99-2605-3_5
Jagtap, A. A., Shedge, D. K., & Chowdhary, V. R. (2023). Flood risk area identification of Pune district using GIS techniques. In Proceedings of the IEEE ICACCS 2023. https://doi.org/10.1109/ICACCS57279.2023.10112874
Kamuju, N. (2024). A study on flood hazard zonation mapping based on GIS-driven approach using remote sensing data and weighted overlay analysis (WOA) model. International Journal for Multidisciplinary Research, 6(5). https://doi.org/10.36948/ijfmr.2024.v06i05.27842
Kumar, N., & Jha, R. (2023). GIS-based flood risk mapping: The case study of Kosi River Basin, Bihar, India. Engineering, Technology & Applied Science Research, 13(1). https://doi.org/10.48084/etasr.5377
Kuswardhana, A. T., Hidayah, E., & Wahyono, R. U. A. (2023). Pemetaan geospasial risiko banjir di Sub-DAS Gunting, Jombang Jawa Timur. Rekayasa Sipil: Jurnal Ilmiah Teknik Sipil, 17(1). https://doi.org/10.21776/ub.rekayasasipil.2023.017.01.8
Purwanto, A., Rustam, R., Andrasmoro, D., & et al. (2022). Flood risk mapping using GIS and multi-criteria analysis at Nanga Pinoh West Kalimantan area. Indonesian Journal of Geography, 54(2). https://doi.org/10.22146/ijg.69879
Rasn, K. H., Nsaif, Q. A., Al-Obaidi, M. A., & et al. (2021). Designation of flood risk zones using the geographic information system technique and remote sensing data in Wasit, Iraq. Geomatics and Environmental Engineering, 15(3), 129–141. https://doi.org/10.7494/GEOM.2021.15.3.129
Rincón, D., Khan, U. T., & Armenakis, C. (2018). Flood risk mapping using GIS and multi-criteria analysis: A Greater Toronto Area case study. Geosciences, 8(8), 275. https://doi.org/10.3390/geosciences8080275
Saha, A. K., & Agrawal, S. (2020). Mapping and assessment of flood risk in Prayagraj district, India: A GIS and remote sensing study. Geoenvironmental Disasters, 7, 70. https://doi.org/10.1007/S41204-020-00073-1
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Copyright (c) 2024 Siti Rahmawati, Siti Rahmawati, Daniela Rincón (Author)
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