  The frequency and impact of floods are expected to increase due to climate
change. It is crucial to predict streamflow, consequently flooding, in order to
prepare and mitigate its consequences in terms of property damage and
fatalities. This paper presents a Graph Convolutional GRUs based model to
predict the next 36 hours of streamflow for a sensor location using the
upstream river network. As shown in experiment results, the model presented in
this study provides better performance than the persistence baseline and a
Convolutional Bidirectional GRU network for the selected study area in
short-term streamflow prediction.
