Streamflow prediction or estimation has been a very popular topic in hydrological field. The applications of streamflow prediction vary from drought management, flood prediction, hydropower operation and so on. Thus, having a well-performance model to predict streamflow is very important for these applications.

There are already tons of physical-based models estimating downstream flow using the information of precipitation, land-use parameters and temperature. In this project, however, the machine learning is used to predict the streamflow. Specifically, Support Vector Machine(SVM) and Artificial Neural Network(ANN) are used.

The package used in this project are scikit-learn SVM regression model and Tensorflow ANN model…

Yu-Chuan Tien 田育全

Currently a UCLA PhD Student.

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