Assessing groundwater level modelling using a 1-D convolutional neural network (CNN): linking model performances to geospatial and time series features
<p>Groundwater level (GWL) forecasting with machine learning has been widely studied due to its generally accurate results and low input data requirements. Furthermore, machine learning models for this purpose can be set up and trained quickly compared to the effort required for process-based numeri...
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| Huvudupphov: | , , , |
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| Materialtyp: | Artigo |
| Språk: | Inglês |
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Copernicus Publications
2024-10-01
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| Serie: | Hydrology and Earth System Sciences |
| Länkar: | https://hess.copernicus.org/articles/28/4407/2024/hess-28-4407-2024.pdf |
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