Hybrid Hydrological Forecasting Through a Physical Model and a Weather-Informed Transformer Model: A Case Study in Greek Watershed

Hybrid Hydrological Forecasting Through a Physical Model and a Weather-Informed Transformer Model: A Case Study in Greek Watershed

This study explores a hybrid AI framework for streamflow forecasting that integrates physically based hydrological modeling, bias correction, and deep learning. HEC-HMS simulations generate synthetic discharge, which a machine learning-based bias correction model adjusts for irrigation-induced discr...

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Bibliographic Details
Main Authors: Haris Ampas, Ioannis Refanidis, Vasilios Ampas
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Applied Sciences
Subjects:
hybrid modeling
streamflow forecasting
hydrological simulation
deep learning in hydrology
temporal fusion transformer
HEC-HMS
Online Access:https://www.mdpi.com/2076-3417/15/12/6679
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https://www.mdpi.com/2076-3417/15/12/6679

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