Abedini, M., & Karimi, A. R. (2026). Spatial Analysis of Flash Flood Hazard in the Karganroud Watershed Using the Global MFFPI Model and GIS-Based Approach. (e242805). Quantitative Geomorphological Research, [In Persian] https://doi:10.22034/gmpj.2026.569243.1596
Abedini, M., & Pasban, A. H. (2026). Zoning the potential flood hazard and its relationship with hydro-geomorphological indices using the MFFPI model in the Samian watershed. Water and Soil Management and Modelling, 6(1), 1–16. [In Persian] https://doi.org/10.22098/mmws.2025.16491.1537
Abedini, M., Babaee Olam, T., & Pasban, A. H. (2024). Flood risk assessment and zoning using MFFPI model (case study: Shafarood watershed, Gilan province). Geography and Human Relationships, 7(1), 871–821. [In Persian] https://doi.org/10.22034/gahr.2024.466493.2198
Abedini, M., Sabouri, H., & Pasban, A. H. (2025). Flood hazard zoning and its relationship with land use using the Analytic Network Process model (case study: Razi Chay watershed, Ardabil province). Journal of Sustainable Urban & Regional Development Studies (JSURDS), 6(2), 68–84. [In Persian] https://www.srds.ir/article_214387_en.html?
Benjamini, Y., & Hochberg, Y. (1995). Controlling the false discovery rate: A practical and powerful approach to multiple testing. Journal of the Royal Statistical Society: Series B (Methodological), 57(1), 289–300. https://doi.org/10.1111/j.2517-6161.1995.tb02031.x
Bilbie, F. (2026). Common Alerting Protocol (CAP) for flash flood early warning systems: A global review of implementations, Technical Approaches, and Operational Challenges Preprints, https://doi.org/10.20944/preprints202603.1203.v1
Fathololoumi, S., Vaezi, A. R., Alavipanah, S. K. & Ghorbani, A. (2020). Modeling the Influence of Biophysical Properties and Surface Topography on the Spatial Distribution of Soil Moisture in the Summer: A Case Study of Balikhli-Chay Watershed. Journal of Ecohydrology, 7(3), 563–581. [In Persian] https://doi.org/10.22059/ije.2020.299783.1307
Ginzarly, J., Joshi, M., & Teller, J. (2024). A multidimensional framework for assessing cultural heritage vulnerability to flood hazards. International Journal of Heritage Studies, 30(10), 1173–1192. doi.org/10.1080/13527258.2024.2378438
Gomez, H., & Kavzoglu, T. (2005). Assessment of shallow landslide susceptibility using artificial neural networks in Jabonosa River Basin, Venezuela. Engineering Geology, 78(1–2), 11–27. https://doi.org/10.1016/j.enggeo.2004.10.004
Jahangir, M. H., Mousavi Reineh, S. M., & Abolghasemi, M. (2019). Spatial prediction of flood zonation mapping in Kan River Basin, Iran, using artificial neural network algorithm. Weather and Climate Extremes, 25, 100215. https://doi.org/10.1016/j.wace.2019.100215
Khendlo, J. (2026). Integrating machine learning and participatory GIS with multi-temporal remote sensing for flood susceptibility and vulnerability mapping in Nkhotakota, Malawi. Research Square. https://doi.org/10.21203/rs.3.rs-8760455/v1
Kusratmoko, E., Septina, A. R., & Falensky, M. A. (2025). Assessment of flash flood hazard potential in a small mountainous Cikundul watershed in West Java, Indonesia. International Journal of Remote Sensing and Earth Sciences, 21(1), 3918. https://doi.org/10.30536/j.ijreses.2024.v21.a3918
Lucà, F., Conforti, M., & Robustelli, G. (2011). Comparison of GIS-based gullying susceptibility mapping using bivariate and multivariate statistics: Northern Calabria, South Italy. Geomorphology, 134(3-4), 297-308. https://doi.org/10.1016/j.geomorph.2011.07.006
Negahban, S., & Mokarram, M. (2024). Correlation of landform classification, land use and flood potential areas in Bushehr province. Quantitative Geomorphological Research, 13(1), 64-79. https://doi.org/10.22034/gmpj.2024.457694.1503
Oluwadare, T. S., Ribeiro, M. P., Chen, D., Babadi Ataabadi, M., Tabesh, S. H., & Daomi, A. E. (2025). Applying machine learning algorithms for spatial modeling of flood susceptibility prediction over Sao Paulo sub-region. Land, 14(5), 985. https://doi.org/10.3390/land14050985
Pasban, A. H., Abedini, M., & Frotan, M. (2022). Evaluation and analysis of the impact of land use on soil erosion using the RUSLE experimental model (case study: Balikhlochai watershed, Ardabil province). Geography and Human Relationships, 5(3), 238–258. [In Persian] https://doi.org/10.22034/gahr.2023.382150.1796
Rahimi, M. & Vahabzadeh Zargari, M. (2026). Assessment of Land-Use Changes Impact on River Morphology and Its Implications for Increasing Flood Hazard (Case Study: QaraSu River, Ardabil). Journal of Geography and Environmental Hazards, 15(1), 1-22. [In Persian] https://doi:10.22067/geoeh.2025.95345.1607
Rahimi, M., Malekmohammadi, B., Firozjaei, M. K., Kerachian, R., Arsanjani, J. J., Tan, M. L., … & AghaKouchak, A. (2026). Integrating geospatial intelligence and machine learning for flood susceptibility mapping. Scientific Reports, 16(1), 10228. https://doi.org/10.1038/s41598-026-41014-3
Rezaei Moghaddam, M. H., Mokhtari, D., Rahimpoor, T., & Skandar, M. (2025). Flood flow zoning for different return periods using hydrodynamic model HEC-RAS (case study: Gomanab Chai River). Quantitative Geomorphological Research, 13(4), 23–36. [In Persian] https://doi.org/10.22034/gmpj.2024.480574.1523
Safari Namivandi, M. (2025). Assessment of the flooding situation in the cities of Khuzestan province. Geography and Human Relationships, 7(4), 299–315. [In Persian] https://doi.org/10.22034/gahr.2025.514247.2433
Saikh, N. I., & Mondal, P. (2023). GIS-based machine learning algorithm for flood susceptibility analysis in the Pagla River Basin, Eastern India. Natural Hazards Research, 3(3), 420–436. https://doi.org/10.1016/j.nhres.2023.05.004
Shapiro, S. S., & Wilk, M. B. (1965). An analysis of variance test for normality (complete samples). Biometrika, 52(3–4), 591–611. https://doi.org/10.1093/biomet/52.3-4.591
Sibandze, P., Kalumba, A. M., Afuye, G. A., & Kganyago, M. (2025). Integrating remote sensing data and fully connected CNN for flood probability and risk assessment in the Port St Johns coastal town, South Africa. Remote Sensing Applications: Society and Environment, 39, 101630. https://doi.org/10.1016/j.rsase.2025.101630
Taloor, A. K., Manhas, D. S., & Kothyari, G. C. (2021). Retrieval of land surface temperature, normalized difference moisture index, normalized difference vegetation index of the Ravi basin using Landsat data. Applied Computing and Geosciences, 9, 100051. https://doi.org/10.1016/j.acags.2020.100051
Taloor, A. K., Sharma, S., Sharma, D., Chib, R., Jasrotia, R., Gupta, S., … & Kale, R. V. (2024). Estimation of MFFPI for flood hazards assessment using geospatial technology in the Tawi Basin, India. Geosystems and Geoenvironment, 3(1), 100–123. https://doi.org/10.1016/j.geogeo.2023.100233
Tincu, L., Lazar, I., & Lazar, G. (2018). Modified flash flood potential index in order to estimate areas with predisposition to water accumulation. Open Geosciences, 10(1), 593–606.
Tong, H. T., Pham, M. P., & Nguyen, N. T. T. (2026). Flood disaster risk identification using integrated fuzzy MCDA and GIS in Song Hinh District, Phu Yen Province. Journal of Degraded and Mining Lands Management, 13(2), 10165–10176. https://doi.org/10.15243/jdmlm.2026.132.10165
Ullah, N., Chao, L., Khan, T. U., Sai, W. L., Yazhuo, Z., Khan, I. A., … & Hu, Y. (2024). Insights into climate change dynamics: A tourism climate index-based evaluation of Gilgit-Baltistan, Pakistan. Heliyon, 10(15), e35315.
Vilasan, R. T., & Kapse, V. S. (2022). Evaluation of the prediction capability of AHP and F-AHP methods in flood susceptibility mapping of Ernakulam district (India). Natural Hazards, 112(2), 1767-1793. https://doi.org/10.1007/s11069-022-05248-4
Weday, G. A., Chukalla, A. D., & Hunde, D. K. (2023). GIS-based flood susceptibility analysis using analytical hierarchy process in Huluka watershed, Oromia, Ethiopia. Environmental Systems Research, 12(1), 3. https://doi.org/10.1186/s40068-022-00283-5
Wondim, Y. K. (2016). Flood hazard and risk assessment using GIS and remote sensing in lower Awash sub-basin, Ethiopia. Journal of Environment and Earth Science, 6(1), 94–117.
