In recent years, artificial intelligence in geosciences is spreading more and more, thanks to the availability of a large amount of data. In particular, the development of automatic raingauges networks allows to get rainfall data and makes these techniques effective, even if the performance of artificial intelligence models is a consequence of the coherency and quality of the input data. In this work, we intended to provide ma...

In a period in which climate change is significantly varying rainfall regimes and their intensity all over the world, river-flow prediction is a major concern of geosciences. In recent years there has been an increase in the use of deep-learning models for river-flow prediction. However, in this field we can observe two main issues: i) many case studies use similar (or the same) strategies without sharing the codes, and ii) th...

Urban flood models that use Digital Elevation Models (DEMs) to simulate extent and depth of flood inundation rely on the accuracy of DEMs for predicting flood events. Despite recent advances in developing vegetation corrected DEMs, the effect of building height and density errors in global DEMs in urban areas are still poorly understood, and their correction remains a challenge. In this research we developed a methodology for...