New Technologies for Hydrological Forecasting and Modeling

Dear Colleagues,

In the face of increasing climate variability, intensified hydrological extremes, and rapid environmental changes, the demand for advanced hydrological forecasting and modeling has never been more urgent. Traditional hydrological models, while valuable, often struggle to accommodate the complexity and dynamics of contemporary hydrological systems. Emerging technologies—such as remote sensing, real-time data assimilation, high-performance computing, and artificial intelligence (AI)—can improve our ability to predict, simulate, and manage water-related processes and hazards.

These technological innovations enable more accurate forecasting of floods, droughts, and water availability; enhance early warning systems; and support evidence-based decision-making for sustainable water resource management. As such, integrating new tools and methods into hydrological practice represents a key scientific and societal priority.

In this Special Issue of Water, we are particularly interested in studies related to recent advancements, applications, and evaluations of modern technologies in hydrological forecasting and modeling. We invite authors to present their research on the following topics (not limited to the list below):

• Real-time hydrological data assimilation and forecasting.
• Remote sensing for hydrological model input and validation.
• Integration of hydrological and hydraulic models.
• Uncertainty quantification and model evaluation techniques.
• Early warning systems for floods and droughts.
• Coupled models for land–atmosphere–water interactions.
• Climate change impact assessment on future hydrological conditions.
• Machine learning and AI applications in hydrology.

We look forward to your contributions.

Dr. Iwona Kuptel-Markiewicz
Dr. Agnieszka Rutkowska
Guest Editors

Dr. Katarzyna Baran-Gurgul
Guest Editor Assistant

Manuscript Submission Information

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