Spatial Prediction of Flood hazard Potential Using Two Statistical Models: Surface Density and Frequency Ratio (Case Study: Buyouk Chai drainage basin, Sarab County)

Document Type : Original Article

Authors

1 Dept. of Geomorphology University of Tabriz and Iranian Hazardology Association

2 Postdoctoral Researcher. Department of Geomorphology, Faculty of Planning and Environmental Sciences, University of Tabriz. Tabriz, Iran

3 3MSc. Student Department of Geomorphology, Faculty of Planning and Environmental Sciences, University of Tabriz. Tabriz

10.22034/rsgi.2025.66386.1126

Abstract

Objective: Annually, intense and flood-inducing rainfall in northwestern Iran, particularly in the Buyouk Chai basin,human and financial losses. The Buyouk Chai basin, located in Sarab County, is considered a high-hazard area for flooding due to its vast area and adequate rainfall. The objective of this study is to spatially predict the potential flood hazard across this basin.
Methods: This research employs two statistical models: Surface Density and Frequency Ratio (FR). To prepare flood hazard potential maps for the study area, 11 parameters influencing flood occurrence were utilized, including elevation, slope, aspect, land use, vegetation index, precipitation, distance from river, drainage density, lithology, soil type, and topographic wetness index.
Results: The analysis of parameter significance revealed that low-lying areas with gentle slopes and regions close to rivers are most susceptible to flooding. The evaluation of model accuracy demonstrated that both models are capable of producing flood hazard maps with relatively high precision across different areas of the basin.
Conclusions: The findings indicate that topographic features, such as slopes and elevations, significantly influence water flow and flood hazard. The calculation of the area for each flood hazard class shows that in the Frequency Ratio model, over 10% of the region's area falls within the very high-hazard category, while in the Surface Density model, approximately 6% of the area is classified as very high-hazard in terms of flood potential. These results underscore the importance of topographic factors in flood hazard assessment and highlight the effectiveness of the employed models in identifying high-hazard zones.

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  • Receive Date: 13 March 2025
  • Revise Date: 17 April 2025
  • Accept Date: 04 August 2025