Author

K. Parmar

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Open access Aug 2026

Physics-informed hybrid GR4J–XGBoost model for streamflow prediction: integrating conceptual states, SHAP interpretability, and uncertainty analysis

This study proposes a physics-informed hybrid modeling framework that integrates the GR4J conceptual model with the XGBoost machine learning algorithm, enabling a process-based representation of catchment dynamics within the machine learning framework.

Ozgur Kisi, S. Heddam, K. Parmar et al. · Scientific Reports · 0 citations