Flood Risk Sensitivity Modeling Using Multi-Criteria Spatial Analysis, Case Study: Gotour Chai, Khoy County

Articles in Press

Document Type : Original Article

Authors

1 geomorphology /planing and environment science

2 Master of Science in Soil Science Engineering, Soil Stratification Origins, Department of Soil Science Engineering, Faculty of Agriculture, Urmia University, Iran

Abstract

Flooding is one of the natural disasters that causes economic losses and the death of many people every year. Among natural disasters, flooding is the deadliest crisis. The vastness of Iran, along with the diversity of climate and the spatial and temporal changes in rainfall in its watersheds, cause massive floods in the country every year. In recent years, the increase in rainfall due to the impact of climate change has been the main cause of flood risks.Therefore, the aim of the present study is to zone the flood risk sensitivity of the Khoy County basin. For this purpose, first, using Landsat images and object-oriented classification techniques, they were extracted and classified into classes (agricultural and garden lands, saline lands, residential lands, pastures and barren lands, and rocky outcrops). In the next stage, by identifying the factors affecting the flooding of the region and preparing information layers for each criterion in GIS, the standardization of the layers was carried out using the fuzzy membership function, the ranking and weighting of the criteria was carried out using the critical method and the ANP method using the Super Decision software, and the final modeling was carried out using the ANP multi-criteria analysis method. Then, the sensitivity analysis of the criteria was performed using the training data. Then, by applying different stages of the model on the maps, the flood sensitivity zoning map of the basin of the region was extracted in 5 classes from very high risk to very low risk.

Keywords

Main Subjects

Journal of Hydrogeomorphology

Articles in Press, Accepted Manuscript
Available Online from 28 September 2025

Files

History

  • Receive Date: 06 May 2025
  • Revise Date: 27 September 2025
  • Accept Date: 28 September 2025

Share

How to cite

Statistics