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1.0 Creative Commons Attribution 4.0 International License. This is the dataset used in the RiverMamba paper (see https://arxiv.org/abs/2505.22535). The aim of the RiverMamba project is to develop a deep learning model that is pretrained with long-term reanalysis data and fine-tuned on observations to forecast global river discharge and floods up to 7 days lead time on a 0.05° grid. The dataset includes the necessary data to train and run the model. The dataset includes the following: 1- CPC precipitation data 2- ECMWF-HRES meteorological forecasts 3-ERA5-Land reanalysis data 4- GloFAS reanalysis data 5- GloFAS static data 6- Reforecasts generated by RiverMamba 7- Pretrained RiverMamba models. https://github.com/HakamShams/RiverMamba_code, v1.0.0 The Federal Ministry of Research, Technology, and Space Grant no. 01IS24075A-D RAINA The German Research Foundation (DFG) SFB 1502/1–2022 – project no. 450058266