Deep representation learning enables cross-basin water quality prediction under data-scarce conditions
Abstract Artificial intelligence has been extensively used to predict surface water quality to assess the health of aquatic ecosystems proactively. However, water quality prediction in data-scarce conditions is a challenge, especially with heterogeneous data from monitoring sites that lack similarit...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-04-01
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| Series: | npj Clean Water |
| Online Access: | https://doi.org/10.1038/s41545-025-00466-2 |
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