Integrating Euclidean and non-Euclidean spatial information for deep learning-based spatiotemporal hydrological simulation
Spatiotemporal deep learning (DL) has emerged as a promising paradigm for hydrological simulation compared with lumped models using basin-averaged inputs. However, existing research primarily focuses on either Euclidean data, characterized by regular structures such as grid-like meteorological forci...
| Main Authors: | , , , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
Elsevier
2024
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