Evaluation of time series forecasting with SANN models for TerraClimate’s hydroclimatic data and trend monitoring
Hydroclimatic forecasting is vital for sustainable water resource management amid climate variability. This study evaluates the performance of deep learning models for predicting key hydroclimatic variables, rainfall, temperature, evapotranspiration, and runoff using TerraClimate data from Morocco’s...
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| Главные авторы: | , , |
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| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
Springer Nature
2025-12-01
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| Серии: | Water Science |
| Предметы: | |
| Online-ссылка: | https://www.tandfonline.com/doi/10.1080/23570008.2025.2574171 |
| Метки: |
Нет меток, Требуется 1-ая метка записи!
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