Performance evaluation of random forest model in flood hazard assessment of Kashkan Watershed

Document Type : Original Article

Authors

1 Department of Natural Engineering, Faculty of Natural Resources, Shahrekord University, Shahrekord, Iran.

2 Department of Natural Engineering, Faculty of Natural Resources, Lorestan University, Khorramabad, Iran.

Abstract
Flooding is one of the most dangerous natural events worldwide, caused by a combination of climatic, hydrological, geomorphological, and geological factors. Floods can occur due to heavy rainfall, prolonged rainfall, rapid snowmelt, or dam failure. Regardless of the cause, floods lead to widespread destruction and damage to human societies and infrastructure. Given the severe risks, assessing flood hazards has become essential. Flood sensitivity maps are useful tools to analyze and manage flood-prone areas.

Methods: This study aims to identify flood-sensitive zones using the Random Forest (RF) model in the Kashkan Basin, Lorestan Province. Thirteen flood-related factors and a map of past flood events were used. Of the 58 recorded flood locations, 73% were used for model training and 27% for validation.

Results: The analysis revealed that proximity to rivers, elevation, slope, and roughness index are the most influential factors in the region’s flooding. The RF model’s performance was evaluated using the ROC index, which scored 0.97, indicating excellent model accuracy in generating the flood sensitivity map.

Conclusions: Flooding is driven by various environmental and human factors. Based on the flood risk prediction map, proper management strategies can be implemented to reduce damage and casualties caused by floods.

Keywords


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Volume 4, Issue 2
Special Issue: Guest Editor: Prof. Ozgur Kisi
September 2025
Pages 131-159