Training and validation dataset

<p><strong>Hybrid streamflow modelling using machine learning and multi-model combination</strong></p> <p>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:&nbsp;<em>&nbsp;all_stations, elbe, maas,&nbsp;elbe_catch,, maas_catch,&nbsp;rhine_catch, rhine_only, rhine_pcr.</em>&nbsp;The <a href="https://github.com/HassanAli99/ADS_Final_Thesis">GitHub </a>repository contains comprehensive pre-processing instructions.<br> <br> &nbsp;</p>