Machine learning to predict tributary phosphorus loads data

The water and climate data for Lake Erie, including:
Soil moisture, streamflow, water temperature, evaporation, baseflow.

This dataset is associated with the following publication:
Chang, F., M. Astitha, Y. Yuan, C. Tang, P. Vlahos, V. Cover, 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): 1-20, (2023).