Training and validation dataset

Hybrid streamflow modelling using machine learning and multi-model combination

Global Hydrological model outputs that have been processed and divided into different validation setups in an effort to improve streamflow forecasts. The dataset included the following validation setups:  all_stations, elbe, maas, elbe_catch,, maas_catch, rhine_catch, rhine_only, rhine_pcr. The GitHub repository contains comprehensive pre-processing instructions.