Application of GIS in Flood Risk Analysis and Mitigation Strategies: The Case of Uluova and İkitepe Streams

Year 2025, Volume: 8 Issue: 5, 1468 - 1477, 15.09.2025

Muhammed Uymaz , Meral Korkmaz

https://doi.org/10.34248/bsengineering.1739684

Abstract

In recent years, the frequency and severity of floods have increased significantly due to the effects of global climate change, leading to serious economic and social losses, particularly in agricultural production areas. Floods not only damage cultivated lands but also negatively affect the livelihoods and socio-economic structures of local communities. This situation necessitates accurate identification of flood risk in agricultural areas and timely implementation of appropriate mitigation measures. In this study, flood risk was investigated in agricultural lands surrounding the Uluova Stream located between Doğankuş, Karşıbağ, and the Keban Dam and the İkitepe Stream, which flows through the center of Mollakendi in Elazığ Province, Türkiye. These areas are characterized by intensive agricultural activities. Using Geographic Information Systems (GIS), seven key parameters distance to streams, land use, aspect, slope, soil structure, precipitation, and geological features were analyzed, and corresponding thematic maps were generated. Flood risk levels were determined through spatial analysis and classification of these parameters using ArcGIS software. Based on the results, areas with high flood risk were identified, and both structural and non-structural mitigation measures were proposed for these zones. The findings offer valuable insights to support sustainable agricultural production and rural development by minimizing potential flood damages and reducing associated economic risks in the region.

Keywords

ArcGIS , Flood management , Flood mitigation strategies , Flood risk , Geographic information systems (GIS)

Ethical Statement

Since this study did not involve research on humans or animals, ethical committee approval was not required.

Thanks

The authors would like to express their sincere gratitude to OpenAI's ChatGPT language model for providing language editing and technical writing assistance during the preparation of this study. The authors also gratefully acknowledge the General Directorate of State Hydraulic Works (DSİ) for providing access to the necessary data that significantly contributed to this research. This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

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