SEED-FD project NIR reflectance indices for river discharge variations

The dataset contains timeseries of NIR reflectance indices, proxy of river discharge variations, obtained using the CM approach (Filippucci et al., 2025a; Tarpanelli et al., 2013) at selected stations along the Danube, Paraná, Niger, and Juba rivers. Specifically, a total of 34 locations are analyzed: 13 for the Danube River, 10 for the Paraná River, 7 for the Niger River, and 4 for the Juba River.

The CM approach enables the estimation of river discharge proxies by analyzing near-infrared signals from periodically flooded areas and comparing them to signals from soil, water, and vegetation. This method uses calibration against in-situ data to identify the optimal periodically flooded areas for obtaining the proxy. When calibration data are not available during satellite passes, an uncalibrated procedure is applied to estimate river discharge proxies without observed data. This uncalibrated method is less effective in areas where the ratio between river width and sensor spatial resolution is low. The CM approach was applied to MODIS Terra, MODIS Aqua, and Sentinel-2 near-infrared data over the available satellite period (02/2000–02/2026). The river discharge proxies obtained from each sensor are made available through the attached NetCDF file, together with a merged product which maximizes the accuracy and frequency of the obtained river discharge proxies.

The Sentinel-2 (S2-1C) sensor generally provides the highest accuracy due to its high spatial resolution (10 m), which allows for precise identification of river features. However, its temporal resolution is limited by the satellite's revisit time (5 days, considering the Sentinel-2 constellation) and cloud coverage, and Sentinel-2 temporal availability only starts in 2016. MODIS products are generally characterized by lower accuracy due to their limited spatial resolution (250 m), but offer a higher temporal frequency and longer data history based on their launch dates and rapid revisit times.

For users aiming to obtain the most accurate river discharge proxies, using the S2-1C product time series is recommended. For users seeking the highest temporal availability, the merged product time series is suggested.

The approach is potentially applicable worldwide.

-------

SEED-FD (Strengthening Extreme Events Detection for Floods and Droughts) aims to advance global forecasts of extreme hydrological events by enhancing the Copernicus Emergency Management Service (CEMS). To achieve this, the project has developed improvements to CEMS’s underlying hydrological model, LISFLOOD, integrated Earth observation and in-situ micro-sensor data, and developed new tools to detect a wider range of extreme flood and drought events. These efforts contribute to more accurate and reliable forecasting, with a particular focus on data-scarce and high-risk regions in the Global South.

SEED-FD follows a phased approach, with developments first tested in data-rich river basins, including the Danube and Bhima, and then validated in the hydrologically diverse basins of Juba-Shebelle, Niger and Paraná. This process ensures the testing, refinement and assessment of the project results under different regional conditions, providing a basis for their potential global applicability. The improvements are intended to support future integration into operational CEMS services such as GloFAS and GDO, as well as potential uptake by other flood and drought forecasting and early warning systems.

By strengthening the scientific and technical basis for flood and drought forecasting, SEED-FD supports civil protection authorities, humanitarian actors and other decision-makers in better preparing for and responding to extreme hydrological events.

Funded by the European Union, Grant agreement ID: 101135110

Further information related to the project can be found here: https://www.seed-fd.eu/

The data have been used as input for SEED-FD use cases: https://www.seed-fd.eu/use-case-datasets-06-2026/

A precipitation dataset from satellite and reanalysis products (Filippucci et al., 2025b) was also developed within the SEED-FD project for five river basins, and is accessible via: https://zenodo.org/records/20747040

Additional locations with river discharge proxies are accessible through the CCI-Discharge initiative dataset: Tarpanelli, A.; Filippucci, P.; Sahoo, D.P. (2024): ESA River Discharge Climate Change Initiative (RD_cci): Combined river discharge product, v1.0. NERC EDS Centre for Environmental Data Analysis, 28 November 2024. doi:10.5285/d32244e674dd438ca4d321560daad755. https://dx.doi.org/10.5285/d32244e674dd438ca4d321560daad755