Advancing Process Representation for Hydrological Modeling Across Spatiotemporal Scales
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing in Geology, Geomorphology and Hydrology".
Deadline for manuscript submissions: 28 February 2026 | Viewed by 23
Special Issue Editors
Interests: flood; flood modeling; flood forecasting; flood risk; environment research; remote sensing
Special Issue Information
Dear Colleagues,
Hydrological modeling is critical for addressing pressing global challenges, including water resource management, flood and drought prediction, and climate change adaptation. However, accurately representing hydrological processes across diverse spatial and temporal scales remains a significant challenge due to data limitations, computational constraints, and the complexity of human–natural coupled systems. Advances in process-based modeling, data assimilation, and multi-scale integration offer unprecedented opportunities to enhance the fidelity and predictive power of hydrological models.
This Special Issue aims to provide a scientific forum for advancing process representation in hydrological modeling, fostering innovation in methods that bridge local, regional, and global scales, as well as short- and long-term dynamics.
We welcome contributions that explore novel modeling frameworks (e.g., physically based, data-driven, stochastic, or hybrid models) and interdisciplinary perspectives to improve our understanding of hydrological systems and their responses to environmental change. By bringing together researchers and stakeholders, this Special Issue seeks to catalyze informed discussions and solutions for sustainable water management.
Dr. Yao Li
Prof. Dr. Tangao Hu
Guest Editors
Manuscript Submission Information
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Keywords
- hydrological modeling
- spatiotemporal scales
- flood
- drought
- data-scarce regions
- hybrid models
- remote sensing
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