Published December 15, 2025 | Version 1.0

Global River Topology (GRIT) raster datasets

  • 1. ROR icon European Centre for Medium-Range Weather Forecasts
  • 2. ROR icon University of Oxford
  • 3. ROR icon University of Southampton
  • 4. ROR icon University of Bristol

Contributors

Research group:

Description

This is the raster dataset of the Global River Topology (GRIT). GRIT is a global river network that not only represents the tributary components of the global drainage network but also the distributary ones, including multi-thread rivers, canals and delta distributaries. It is also the first global hydrography (excluding Antarctica and Greenland) produced at 30m raster resolution. It is created by merging Landsat-based river mask (GRWL) with elevation-generated streams to ensure a homogeneous drainage density outside of the river mask (rivers narrower than approx. 30m). Crucially, it uses a new 30m digital terrain model (FABDEM, based on TanDEM-X) that shows greater accuracy over the traditionally used SRTM derivatives. After vectorisation and pruning, directionality is assigned by a combination of elevation, flow angle, heuristic and continuity approaches (based on RivGraph). The vector data including the network topology (lines and nodes, upstream/downstream IDs) is available as layers and attribute information in GeoPackage files (readable by QGIS/ArcMap/GDAL). The 30m raster data is available as compressed GeoTIFF files. See Wortmann et al. (2025, https://doi.org/10.1029/2024WR038308) for more details. See README.pdf for the technical discription of the available datasets.

Raster data are provided in 300x300km tiles, packaged by continental region. A raster tile index is provided in GRITv1.0_raster_tile_index_GLOBAL_EPSG8857.gpkg.

A map of GRIT segments labelled with OSM river names is available here:

https://michelwortmann.com/research/global-river-topology-grit/

Report bugs and feedback

Your feedback and bug reports are welcome here: GRIT bug report form

The feedback may be used to improve and validate GRIT in future versions.

 

Files

README.pdf

Files (182.8 GB)

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Additional details

Related works

Is described by
Publication: 10.1029/2024WR038308 (DOI)
Is supplement to
Dataset: 10.5281/zenodo.7629907 (DOI)

Funding

UK Research and Innovation
THE EVOLUTION OF GLOBAL FLOOD HAZARD AND RISK [EVOFLOOD] NE/S015728/1

Software

Repository URL
https://github.com/mwort/grit
Programming language
Python , Shell