Exploring the Controlling Factors of Watershed Streamflow Variability Using Hydrological and Machine Learning Models

Studying streamflow processes and controlling factors is crucial for sustainable water resource management. This study demonstrated the potential of integrating hydrological models with machine learning by constructing two machine learning methods, Extreme Gradient Boosting (XGBoost) and Random Fore...

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