Global River Topology (GRIT): a bifurcating river hydrography

Wortmann, M., Slater, L., Hawker, L., Liu, Y., Neal, J., Zhang, B., Schwenk, J., Allen, G., Ashworth, P., Boothroyd, R., Cloke, H. ORCID: https://orcid.org/0000-0002-1472-868X, Delorme, P., Gebrechorkos, S.H., Griffith, H., Leyland, J., McLelland, S., Nicholas, A.P., Sambrook-Smith, G., Vahidi, E., Parsons, D. and Darby, S.E. (2025) Global River Topology (GRIT): a bifurcating river hydrography. Water Resources Research. ISSN 0043-1397 (In Press)

Abstract/Summary

Existing global river networks underpin a wide range of hydrological applications but do not represent channels with divergent river flows (bifurcations, multi-threaded channels, canals), as these features defy the convergent flow assumption that elevation-derived networks (e.g. HydroSHEDS, MERIT Hydro) are based on. Yet, bifurcations are important features of the global river drainage system, especially on large floodplains and river deltas, and are also often found in densely populated regions. Here we developed the first raster and vector-based Global RIver Topology (GRIT) that not only represents the tributaries of the global drainage network but also the distributaries, including multi-threaded rivers, canals and deltas. We achieve this by merging a 30m Landsat-based river mask with elevation-generated streams to ensure a homogeneous drainage density outside of the river mask for rivers narrower than approximately 30m. Crucially, we employ the new 30 m digital terrain model, FABDEM, based on TanDEM-X, which shows greater accuracy over the traditionally used SRTM derivatives. After vectorisation and pruning, directionality is assigned by a series of elevation, flow angle and continuity approaches. The new global network and its attributes are validated using gauging stations, comparison with existing networks, and randomized manual checks. The new network represents 19.6 million km of streams and rivers with drainage areas greater than 50 km2 and includes 67,495 bifurcations. With the advent of hyper-resolution modelling and artificial intelligence, GRIT is expected to greatly improve the accuracy of many river-based applications such as flood forecasting, water availability and quality simulations, or riverine habitat mapping.

Item Type	Article
URI	https://reading-clone.eprints-hosting.org/id/eprint/121891
Refereed	Yes
Divisions	Science > School of Archaeology, Geography and Environmental Science > Department of Geography and Environmental Science Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
Publisher	American Geophysical Union
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