Using artificial neural networks for predicting flood events in Artvin, Türkiye

Year 2025, Volume: 9 Issue: 2, 189 - 201

Olgu Aydın , Nussaibah B. Raja

https://doi.org/10.31127/tuje.1530593

Abstract

Flood risks in Artvin, Turkey, have become a critical concern due to the long-term economic, social, cultural, and environmental damages caused by flood-related disasters. Given this, it is essential to utilize reliable methods for flood prediction. Artificial Neural Networks (ANNs), adept at reacting to rapid changes in rainfall, are employed as a machine learning approach to provide valuable flood information for urban areas. This study aims to develop an accurate and timely flood prediction model for Artvin using daily average rainfall data from 58 weather stations between 2009 and 2016. Flow values for various locations in Artvin (Ardanuç, Arhavi, Artvin, Borçka, Hopa, Murgul, Şavşat, Yusufeli) are calculated using the rational method. ANNs were trained with daily rainfall data and consecutive rainfall inputs from 1 to 7 hours to predict flow values. The model’s performance, with 75% of the data used for training and 25% for validation, showed an error ratio of 0.225 and high prediction accuracy for flow values, exceeding 20 m³/h in most locations except Hopa. The R² results for 1–7 hours indicated high performance (0.643-0.725), suggesting effective warning times of 3–5 hours for Artvin. The study also highlights the increasing necessity for flood management strategies in the Eastern Black Sea Region, particularly Artvin, which has experienced severe flash floods and significant flooding events since 2017. The region’s frequent and intense rainfall, exacerbated by global climate change, underscores the urgent need for robust monitoring, early warning systems, and comprehensive flood mitigation plans to address drainage, land management, and safeguard infrastructure. Effective warning systems that provide real-time estimates of rainfall and flow are crucial for timely preventive measures.

Keywords

Rainfall, Flood forecasting, Artificial Neural Network (ANN), Early warning systems, Artvin

Ethical Statement

Yok

Supporting Institution

Ankara University Research Council

Project Number

#17B0649001

Thanks

Yok

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