RiverMamba: A State Space Model for Global River Discharge and Flood Forecasting [data set] (doi:10.60507/FK2/T8QYWE)

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RiverMamba: A State Space Model for Global River Discharge and Flood Forecasting [data set]

doi:10.60507/FK2/T8QYWE

bonndata

2025-10-02

1

Shams Eddin, Mohamad Hakam; Zhang, Yikui; Kollet, Stefan; Gall, Juergen, 2025, "RiverMamba: A State Space Model for Global River Discharge and Flood Forecasting [data set]", https://doi.org/10.60507/FK2/T8QYWE, bonndata, V1

RiverMamba: A State Space Model for Global River Discharge and Flood Forecasting [data set]

doi:10.60507/FK2/T8QYWE

Shams Eddin, Mohamad Hakam (University of Bonn)

Zhang, Yikui (Forschungszentrum Jülich GmbH)

Kollet, Stefan (Forschungszentrum Jülich GmbH)

Gall, Juergen (University of Bonn)

https://github.com/HakamShams/RiverMamba_code

Grant no. 01IS24075A-D RAINA

SFB 1502/1–2022 – project no. 450058266

bonndata

Shams Eddin, Mohamad Hakam

Shams Eddin, Mohamad Hakam

2025-09-12

https://doi.org/10.60507/FK2/T8QYWE

Computer and Information Science, Earth and Environmental Sciences

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.

ERA5-Land hourly data from 1950 to present. Copernicus Climate Change Service (C3S) Climate Data Store (CDS): https://cds.climate.copernicus.eu/datasets

ECMWF-IFS HRES from ECMWF archive catalogue (MARS)

Joint Research Center, Copernicus Emergency Management Service (2019): River discharge and related historical data from the Global Flood Awareness System. Early Warning Data Store (EWDS): https://doi.org/10.24381/cds.a4fdd6b9

The Global Unified Gauge-Based Analysis of Daily Precipitation. National Oceanic and Atmospheric Administration (NOAA), Climate Prediction Center (CPC): https://psl.noaa.gov/data/gridded/data.cpc.globalprecip.html

LISFLOOD static and parameter maps, European Commission, Joint Research Centre (JRC) [Dataset] PID: http://data.europa.eu/89h/68050d73-9c06-499c-a441-dc5053cb0c86

HydroRIVERS and HydroATLAS, https://www.hydrosheds.org/products/hydrorivers

<a href="http://creativecommons.org/licenses/by/4.0">CC BY 4.0</a>

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