Assessing the adequacy of traditional hydrological models for climate change impact studies: a case for long short-term memory (LSTM) neural networks
<p>Climate change impact studies are essential for understanding the effects of changing climate conditions on water resources. This paper assesses the effectiveness of long short-term memory (LSTM) neural networks compared to traditional hydrological models for these studies. Traditional hydr...
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| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2025-07-01
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| Series: | Hydrology and Earth System Sciences |
| Online Access: | https://hess.copernicus.org/articles/29/2811/2025/hess-29-2811-2025.pdf |
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