FengChang et al_ML Output.xlsx
Description
Outputs from WRF, EPIC, VIC. Outputs and analysis from the ML-based model described in the paper.
This dataset is associated with the following publication:
Feng Chang, C., M. Astitha, Y. Yuan, C. Tang, P. Vlahos, V. Garcia, and U. Khaira. A New Approach to Predict Tributary Phosphorus Loads Using Machine Learning– and Physics-Based Modeling Systems. Artificial Intelligence for the Earth Systems. American Meteorological Society, Boston, MA, USA, 2(3): 1-43, (2023).
Resources
| Name |
Format |
Description |
Link |
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53 |
FengChang%20et%20al_ML%20Outputs.xlsx |
https://pasteur.epa.gov/uploads/10.23719/1529548/FengChang%20et%20al_ML%20Outputs.xlsx |
Tags
- eutrophication
- tributary-phosphorus-loads
- numerical-prediction-models
- machine-learning