August 21, 2025Open Access

Bridging Basins with Algorithms: Machine Learning for Scalable Flood Prediction

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Discussion

Machine learning improves flood prediction reliability in data-scarce basins, suggesting new forecasting strategies.

Cross-basin prediction models achieved over 90% accuracy, outperforming traditional methods.
Gradient Boosting and Random Forest algorithms were pivotal in achieving high prediction accuracy.
Assessment utilized nine machine learning algorithms with six evaluation metrics for reliability.
Machine learning provides a promising solution for flood prediction, even in regions with limited historical data.

Yukseler et al. (2025) studied this question.

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