2024
DOI: 10.1007/s11069-024-06528-x
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A fusion-based framework for daily flood forecasting in multiple-step-ahead and near-future under climate change scenarios: a case study of the Kan River, Iran

Marzieh Khajehali,
Hamid R. Safavi,
Mohammad Reza Nikoo
et al.

Abstract: This study proposes a novel fusion framework for ood forecasting based on machine learning, statistical, and geostatistical models for daily multiple-step-ahead and near future under climate change scenarios. To do this, remote sensing precipitation data of ERA5, CHIRPS, and PERSIANN-CDR were utilized to ll the gap data of meteorological stations. Four Individual Machine Learning (IML) models, including Random Forest, Multiple-Layer Perceptron, Support Vector Machine, and Extreme Learning Machine were develope… Show more

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