Hybrid Modeling for Fine-Scale Runoff Prediction

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This research develops hybrid modeling approaches that pair process-based hydrologic models with data-driven methods to predict runoff at fine spatial scales, while keeping results physically interpretable.

The work spans edge-of-field runoff prediction, generalization of runoff-risk models, and methodological frameworks for improving data-driven model performance.

Related publications

• Assessing Hybrid Modeling for Fine-Scale Runoff Prediction (2024)
• A methodological framework for improving the performance of data-driven models (2023)
• Generalization of Runoff Risk Prediction (2022)
• Edge-of-field runoff prediction by a hybrid modeling approach (2021)