Evaluation of short-term streamflow prediction methods in Urban river basins

Efficient and accurate streamflow predictions are important for urban water management. Data-driven models, especially neural network (NN) models can predict streamflow fast, while the results are uncertain in some complex river systems. Physically based models can reveal the underlying physics, but it is relatively slow and computationally...

Urban pluvial flooding prediction by machine learning approaches – a case study of Shenzhen city, China

Urban pluvial flooding is a threatening natural hazard in urban areas all over the world, especially in recent years given its increasing frequency of occurrence. In order to prevent flood occurrence and mitigate the subsequent aftermath, urban water managers aim to predict precipitation characteristics, including peak intensity, arrival time...

Accelerated lake expansion on the Tibetan Plateau in the 2000s: Induced by glacial melting or other processes?

ccelerated lake expansion in the 2000s has been confirmed by both dramatic lake-area increases (for 312 lakes larger than 10 km2) derived from optical images, and rapid water-level rises (for 117 lakes with water-level data) measured by satellite altimetry. However, the underlying climate causes remain unclear. This paper analyzes the...