Published December 15, 2025 | Version 1.0
Dataset Open

Global River Topology (GRIT) vector datasets

  • 1. University of Oxford
  • 2. University of Bristol

Contributors

Research group:

Description

This is the vector 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.

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 (55.8 GB)

Name Size Download all
md5:92f48456a196c03d8f8110d11e480d15
808.1 MB Preview Download
md5:c7086353ca7cc3504df80ac23e0cedeb
360.1 MB Preview Download
md5:84bfa0bde17db5999535462e52653c99
18.2 MB Preview Download
md5:5e53f0ff95ff30434c98089983f4ade4
19.3 MB Preview Download
md5:efab038e871ea5e5bedd251bbfac4f4f
3.7 GB Preview Download
md5:291ffcaf9afaf1db5687d60d68928809
1.9 GB Preview Download
md5:a6ac4eba7c9706c1d80d914013fa519f
3.4 GB Preview Download
md5:c219db71ebceadabeb28d4dc33a4114a
1.9 GB Preview Download
md5:7ad6a8854e80103d2ec96c23fbcabe19
1.5 GB Preview Download
md5:7bafcfb501bb2060a3a5297c72f89666
843.1 MB Preview Download
md5:096668f077c19e370f1bbbdb34cd3f54
2.8 GB Preview Download
md5:c9b98b714a1eb84a5fb361a3ba8b20f0
1.6 GB Preview Download
md5:7825ea75cd62fdcfb6dde6600448cdad
2.2 GB Preview Download
md5:922d85c99e55eb207b6e8da67492216b
1.2 GB Preview Download
md5:4699c7a023abe81f44ce4469390631f9
1.6 GB Preview Download
md5:91b7c093f08520468c5f0eaab3a0f2b2
930.4 MB Preview Download
md5:a2d6afd70baa1c433d7725376f7e709c
1.3 GB Preview Download
md5:5d5b416c3737c9d92dab0b4222f4d863
728.9 MB Preview Download
md5:bc2e55d67e319dfb70ed0295a955017a
1.6 GB Preview Download
md5:9b396bd365ac631fc1589c68ac345c67
1.5 GB Preview Download
md5:6237a1038ab66ae98efe323708386d9f
1.4 GB Preview Download
md5:0d86cd9817a2eb0e24814525d04f4a90
1.4 GB Preview Download
md5:416d148d9e481e53d14addeb629884f4
678.9 MB Preview Download
md5:7af05354a5caa6cbf6bfe2b3e9767a1b
671.1 MB Preview Download
md5:7cab8efabac8beb786bb0f9e04cb28e3
1.2 GB Preview Download
md5:9efa04e9b10df41e3b91da14f7b28969
1.2 GB Preview Download
md5:8c551a5ac63b18c93adda0f4c5380242
987.0 MB Preview Download
md5:af5ef0fb10253444682c2fa3d8483f39
974.9 MB Preview Download
md5:5c467148dad0cecab48ddeaa8fbd229f
758.9 MB Preview Download
md5:e01a1e8ac5da2c8cff5d64a934103343
749.2 MB Preview Download
md5:3e33679b2310efff45ef6dd491ebd0db
573.4 MB Preview Download
md5:7e2609ec1da4d71b39a6b1cf59f85042
568.7 MB Preview Download
md5:690b8f14f5dbbb50cbca008b501af3e9
1.6 GB Preview Download
md5:826f63e8191f2645798c65920242d557
717.2 MB Preview Download
md5:4e78805607c45c23daa34b8ec3e7fae2
1.5 GB Preview Download
md5:7792f3dfd0e7754f40372e5ee37dd67d
720.6 MB Preview Download
md5:c20da145d78eda3bfddea9721393f0a6
630.4 MB Preview Download
md5:02a23ab0ba81301b2e90bcd64d753089
308.7 MB Preview Download
md5:6144a6e9b097791b1c98b931b176da22
1.2 GB Preview Download
md5:131ffddd6ada1d8231fbe8c010cb6941
600.6 MB Preview Download
md5:6a36fd387eb01861c77a6e26ea75e4a5
963.4 MB Preview Download
md5:b84c300b01f3926cb507f70181c9d70c
454.4 MB Preview Download
md5:2c03754a161f34eaa924a0e6ffab96a5
694.5 MB Preview Download
md5:d3106a46286d2d01c00a6a3e35507700
364.1 MB Preview Download
md5:c667ee50b3d49dbc3dfd55f4b2b5c69a
571.8 MB Preview Download
md5:171d32a7dbaf7760545349db65515285
279.8 MB Preview Download
md5:74d3971c4dd5da994ac63b559b25b93f
611.8 MB Preview Download
md5:b158a3af9b3ca9c5d28426a5812c0b60
271.1 MB Preview Download
md5:cb2ef3356886caff3a4c094f652e87a7
569.3 MB Preview Download
md5:c9a160718a4ebf03c8e1f72a66d6da69
271.8 MB Preview Download
md5:590f3c91556a766a23d9f1eeac823736
258.6 MB Preview Download
md5:31a351e8924e5e0c7beea97ee6b44d44
124.8 MB Preview Download
md5:93ba7d8674d6199cf3b3c6f4ec1fdb19
475.2 MB Preview Download
md5:90a0a8d3694e1fe6c1c189fee2b1c224
239.8 MB Preview Download
md5:bae4e0a9fa7c25e7cefe7f032356c58f
383.5 MB Preview Download
md5:52ab3e8707fcf34d3ccd29387f0dfdaa
180.9 MB Preview Download
md5:57ca7a2a5bcb93f5677d6d6b86e966aa
298.3 MB Preview Download
md5:cb4807e49623b1a68d8dd88d5b1ccdff
161.6 MB Preview Download
md5:f5f378620eb1e59da7682a991bb51ccc
111.0 MB Preview Download
md5:a3867012a286519be1f3593417cd8cf1
94.8 MB Preview Download
md5:95fe521908e2b04b1ab62b11f46a9d09
227.2 MB Preview Download
md5:e6c5db8d8ecd06d0bdc9bdb5eaebff09
108.0 MB Preview Download
md5:59d7685d6efad25746c5a2952326ff3e
14.8 kB Preview Download
md5:d31f56d7d0243f923db881ebfaa981d3
150.2 kB Preview Download

Additional details

Related works

Is described by
Publication: 10.1029/2024WR038308 (DOI)
Is supplement to
Dataset: 10.5281/zenodo.15715535 (DOI)

Funding

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

Dates

Updated
2025-12-15
v1.0

Software

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