We introduce a machine-learning framework to study spatial characteristics and drivers of regional floods in eastern China, using 38 years of flood peak data from a vast gauging network. Our analyses provide better understanding of contrasting flood behaviors by explicitly characterizing their spatial extents. This knowledge can help improve flood risk management.