A Multi-Scene Roadside Lidar Benchmark towards Digital Twins of Road Intersections

Rainfall-runoff simulation based on deep learning has become popular approaches in recent years with the drawback of significant time required for training. The study proposes an incremental learning method to accelerate rainfall-runoff simulation with deep learning models. The method was tested in Yangtze River and Han River drainage basin. The results show the feasibility, robustness, suitability and potential applications in flood emergency decision-making of the method.