@article {29243,
	title = {Machine Learning for Streamflow Prediction: Current Status and Future Prospects},
	journal = {AGU Fall Meeting Abstracts},
	volume = {2019},
	year = {2019},
	pages = {H33L-2127},
	abstract = {<p>
	Accurate streamflow prediction is an open challenge in hydrology. We show that approaches based on machine learning can provide more accurate predictions than physically-based models and discuss potential for improvement in hybrid approaches.
</p>
},
	author = {M. Gauch and R. Tang and J. Mai and B. Tolson and S. Gharari and J. Lin}
}
