GIS-Based Flood Risk Assessment in the Johor River Basin Using AHP and Weighted Overlay
DOI:
https://doi.org/10.36777/jag2026.5.2.2Keywords:
Analytic hierarchy process, flood risk, geographic information system, Johor River Basin, multi-criteria decision analysisAbstract
Flood-risk studies in Malaysia have often concentrated on hydrological hazard, although the consequences of flooding also depend on where people and assets are located and how well communities can cope. This study develops a basin-wide flood-risk index for the Johor River Basin by integrating hazard, exposure and vulnerability within a geographic information system-based multi-criteria decision analysis. Nine hazard indicators, four exposure indicators and four vulnerability indicators were assembled from open geospatial datasets. The indicators were standardised into five ordinal classes, weighted using the Analytic Hierarchy Process, and combined through weighted overlay. The three component indices were then assigned equal weights to produce a composite flood-risk surface. High and very high risk covered 9.29% and 1.43% of the basin, respectively. These areas were concentrated around Kota Tinggi in the lower basin and, in smaller clusters, around Bandar Tenggara in the middle basin. A spatial consistency check used 24 locations listed in a Department of Irrigation and Drainage flood warning for 14-17 December 2025. Nineteen locations (79.17%) fell within high or very high risk classes, while 23 (95.83%) fell within moderate to very high classes. The resulting map is best interpreted as a relative screening tool for prioritising detailed investigation, land-use control and preparedness. Its main limitations are the use of mixed-date datasets, subjective weighting, a climatological rainfall surface, and the absence of hydrodynamic simulation and observed inundation footprints.
References
Abdulkareem, J. H., Pradhan, B., Sulaiman, W. N. A., & Jamil, N. R. (2018). Review of studies on hydrological modelling in Malaysia. Modeling Earth Systems and Environment, 4(4), 1577-1605. https://doi.org/10.1007/s40808-018-0509-y
de Brito, M. M., & Evers, M. (2016). Multi-criteria decision-making for flood risk management: A survey of the current state of the art. Natural Hazards and Earth System Sciences, 16(4), 1019-1033. https://doi.org/10.5194/nhess-16-1019-2016
Didan, K. (2015). MOD13Q1 MODIS/Terra vegetation indices 16-day L3 global 250 m SIN grid V006 [Data set]. NASA EOSDIS Land Processes Distributed Active Archive Center.
Elvidge, C. D., Zhizhin, M., Ghosh, T., Hsu, F.-C., & Taneja, J. (2021). Annual time series of global VIIRS nighttime lights derived from monthly averages: 2012 to 2019. Remote Sensing, 13(5), 922. https://doi.org/10.3390/rs13050922
European Space Agency. (2021). Copernicus DEM GLO-30 [Data set]. Copernicus Data Space Ecosystem.
Food and Agriculture Organization of the United Nations, & International Institute for Applied Systems Analysis. (2023). Harmonized World Soil Database version 2.0 [Data set].
Fick, S. E., & Hijmans, R. J. (2017). WorldClim 2: New 1-km spatial resolution climate surfaces for global land areas. International Journal of Climatology, 37(12), 4302-4315. https://doi.org/10.1002/joc.5086
Hirabayashi, Y., Mahendran, R., Koirala, S., Konoshima, L., Yamazaki, D., Watanabe, S., Kim, H., & Kanae, S. (2013). Global flood risk under climate change. Nature Climate Change, 3(9), 816-821. https://doi.org/10.1038/nclimate1911
Jongman, B., Ward, P. J., & Aerts, J. C. J. H. (2012). Global exposure to river and coastal flooding: Long term trends and changes. Global Environmental Change, 22(4), 823-835. https://doi.org/10.1016/j.gloenvcha.2012.07.004
Kazakis, N., Kougias, I., & Patsialis, T. (2015). Assessment of flood hazard areas at a regional scale using an index-based approach and Analytic Hierarchy Process: Application in Rhodope-Evros region, Greece. Science of the Total Environment, 538, 555-563. https://doi.org/10.1016/j.scitotenv.2015.08.055
Lehner, B., & Grill, G. (2013). Global river hydrography and network routing: Baseline data and new approaches to study the world's large river systems. Hydrological Processes, 27(15), 2171-2186. https://doi.org/10.1002/hyp.9740
Malczewski, J. (2006). GIS-based multicriteria decision analysis: A survey of the literature. International Journal of Geographical Information Science, 20(7), 703-726. https://doi.org/10.1080/13658810600661508
Muzamil, S. A. H. B. S., Zainun, N. Y., Ajman, N. N., Sulaiman, N., Khahro, S. H., Rohani, M. M., Mohd, S. M. B., & Ahmad, H. (2022). Proposed framework for the flood disaster management cycle in Malaysia. Sustainability, 14(7), 4088. https://doi.org/10.3390/su14074088
OpenStreetMap contributors. (2025). OpenStreetMap road network data for the Johor River Basin [Data set]. https://www.openstreetmap.org
Rosmadi, H. S., Ahmed, M. F., Mokhtar, M. B., & Lim, C. K. (2023). Reviewing challenges of flood risk management in Malaysia. Water, 15(13), 2390. https://doi.org/10.3390/w15132390
Saaty, T. L. (1980). The analytic hierarchy process: Planning, priority setting, resource allocation. McGraw-Hill.
Shadiqe, J. (2025, December 12). Flood warning for low-lying areas in Johor from Dec 14-17. New Straits Times. https://www.nst.com.my/news/nation/2025/12/1336124/flood-warning-low-lying-areas-johor-dec-14%E2%80%9317
Sidek, L. M., Jaafar, A. S., Majid, W. H. A. W. A., Basri, H., Marufuzzaman, M., Fared, M. M., & Moon, W. C. (2021). High-resolution hydrological-hydraulic modeling of urban floods using InfoWorks ICM. Sustainability, 13(18), 10259. https://doi.org/10.3390/su131810259
Sirko, W., Kashubin, S., Ritter, M., Annkah, A., Bouchareb, Y. S. E., Dauphin, Y., Keysers, D., Neumann, M., Cisse, M., & Quinn, J. A. (2021). Continental-scale building detection from high-resolution satellite imagery. arXiv. https://doi.org/10.48550/arXiv.2107.12283
Souissi, D., Zouhri, L., Hammami, S., Msaddek, M. H., Zghibi, A., & Dlala, M. (2020). GIS-based MCDM-AHP modeling for flood susceptibility mapping of arid areas, southeastern Tunisia. Geocarto International, 35(9), 991-1017. https://doi.org/10.1080/10106049.2019.1566405
Tan, M. L., Ibrahim, A. L., Yusop, Z., Duan, Z., & Ling, L. (2015). Impacts of land-use and climate variability on hydrological components in the Johor River Basin, Malaysia. Hydrological Sciences Journal, 60(5), 873-889. https://doi.org/10.1080/02626667.2014.967246
Tatem, A. J. (2017). WorldPop, open data for spatial demography. Scientific Data, 4, 170004. https://doi.org/10.1038/sdata.2017.4
United Nations Office for Disaster Risk Reduction. (2022). Global assessment report on disaster risk reduction 2022: Our world at risk - Transforming governance for a resilient future. United Nations.
UNESCO Regional Office for Science and Technology for Southeast Asia. (1997). Catalogue of rivers for Southeast Asia and the Pacific: Volume I - Mainland and insular Southeast Asia. UNESCO.
Ward, P. J., Jongman, B., Weiland, F. S., Bouwman, A., van Beek, R., Bierkens, M. F. P., Ligtvoet, W., & Winsemius, H. C. (2013). Assessing flood risk at the global scale: Model setup, results, and sensitivity. Environmental Research Letters, 8(4), 044019. https://doi.org/10.1088/1748-9326/8/4/044019
WorldPop. (2024). Global high-resolution population estimates and age-sex structures [Data set]. University of Southampton. https://www.worldpop.org
Zanaga, D., Van De Kerchove, R., Daems, D., De Keersmaecker, W., Brockmann, C., Kirches, G., Wevers, J., Cartus, O., Santoro, M., Fritz, S., Lesiv, M., Herold, M., Tsendbazar, N. E., Xu, P., Ramoino, F., & Arino, O. (2022). ESA WorldCover 10 m 2021 v200 [Data set]. Zenodo. https://doi.org/10.5281/zenodo.7254221
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Journal of Asian Geography

This work is licensed under a Creative Commons Attribution 4.0 International License.